Climate change is one of the greatest and probably most challenging environmental, social and economical threats facing the world this century. Human activities have altered the chemical composition of the atmosphere through the buildup of significant quantities of greenhouse gases (GHGs), which remain in the atmosphere for long periods of time and intensify the natural greenhouse effect. Increasing concentrations of greenhouse gases, mainly CO2, are likely to accelerate the rate of climate change. Concerns are growing about how increases in CO2 caused by human activities are contributing to the natural greenhouse effect and raising the Earth's average temperature. Electricity generation, especially from fossil fuel, and petroleum industries contribute the most to greenhouse gases emissions in Canada. As of 2004, they contributed to about 37% of total (GHGs). Risks of climate change and subsequent future environmental regulations are pressing electricity and petroleum refining industries to minimize their greenhouse gas emissions, mainly CO2. Fossil fuel power plants and refineries are now being challenged to comply with the Kyoto protocol by the United Nations Framework Convention and Climate Change (UNFCC). Canada???s target is a reduction in CO2 emissions of 6% from 1990 level. In this thesis, an optimization approach for integrating planning and CO2 reduction is developed for electricity and refinery sectors. Three different CO2 mitigation options are considered in each case. For the electricity sector, these mitigation options were 1) fuel balancing (optimal adjustment of the operation of existing generating stations to reduce CO2 emissions without making structural changes to the fleet), 2) fuel switching (switching from carbon intensive fuel to less carbon intensive fuel, essentially switching from coal to natural gas) and 3) implementing different technologies for efficiency improvement. The optimization model takes into account meeting electricity demand and achieving a certain CO2 reduction target at a minimum overall cost. The model was formulated as a Mixed Integer Non Linear Program (MINLP) and was implemented in GAMS (General Algebraic Modeling System). Exact linearization techniques were employed to facilitate solution development. The computer program was capable of determining the best strategy or mix of strategies to meet a certain CO2 reduction target at minimum cost. The model was illustrated on a case study for Ontario Power Generation (OPG) fleet. The results showed that for 1% CO2 reduction target, only fuel balancing need to be applied and even a decrease of about 1.3% in overall cost was obtained. The optimizer chose to increase production from all non fossil fuel power plants and to decrease production from natural gas power plant. This is because natural gas is the most expensive fuel that OPG uses. For higher reduction targets, it was necessary to implement fuel switching. For 30% reduction, for example, 11 boilers out of 27 (4 are already natural gas) are switched from coal to natural gas and the cost increases by about 13%. Applying efficiency improvement technologies such as installing new turbine blades was a good option only at small reduction targets. As the reduction target increases, the optimizer chose not to implement efficiency improvement technologies and only fuel switching was the best option to select in addition to fuel balancing. For the refinery sector, a similar strategy was applied. An optimization model was developed to maximize profit from selling final products and to meet a given CO2 reduction target with products demand and specifications. Three CO2 mitigation options were considered and these were: 1) balancing that implies the increase in production from units that emit less CO2 emissions provided that demand is met, 2) fuel switching that involves switching from current carbon intensive fuel to less carbon intensive fuel such as natural gas, 3) implementation of CO2 capture technologies. Chemical absorption (MEA) process was used as the capture process. Prior to the development of the refinery planning model, a sub-model was developed for each unit in a refinery layout. Then, the sub-models were integrated into a master planning model to meet final products demand and specifications with the objective of maximizing profit without CO2 mitigation options. The model was solved first as a Non Linear Program (NLP). Then, binary variables representing the existence or no existence of fuel switching option and CO2 capture processes were introduced into the model. The model was formulated as a Mixed Integer Non Linear Program (MINLP), coded in GAMS, and applied to different case studies. The results showed that the refinery planning model tends to produce more from the most profitable product, which is gasoline, and chose to blend products into the most profitable pool unless the demand needs to be satisfied for certain other products. The model, for example, chose to send kerosene from the diesel hydrotreater to the kerosene pool and not to the diesel pool since kerosene has higher selling value than diesel. When CO2 mitigation options were introduced into the model, only 0.4% CO2 reduction was achieved by simply decreasing production from the hydrocracker (HC) unit and increasing production from the fluidized catalytic cracking (FCC) unit. This was done because the FCC unit tends to emit less CO2 compared to the HC unit. At higher reduction target such as 1%, fuel switching was implemented by choosing the FCC to run with natural gas. The profit decreased slightly because of the retrofit cost of switching. It was noticed also that fuel switching can achieve a maximum of 30% reduction in CO2 emissions. This was achieved by switching all units to run with natural gas that emits less CO2 emissions. For a reduction target higher than 30%, CO2 capture technologies need to be applied. For 60% reduction, the optimization chose to switch three units (out of 8) and to capture CO2 emissions coming from four units. Only the FCC remained unchanged. A decrease in the profit was noticed as the reduction target increases since more units need to be switched and more CO2 need to be captured. The results showed that adding sequestration cost further decreased the profit. However, it was noticed that the selling price of final products had the most effect on the profit. An increase of 20%, for example, in final products??? prices, leads to a 10% increase in profit even when the CO2 reduction target was as high as 80%. When the retrofit cost for switching and capture was decreased by 30%, the effect on the profit was noticed only at higher reduction targets since more units were switched and more CO2 capture units were implemented

Climate change is one of the greatest and probably most challenging environmental, social and economical threats facing the world this century. Human activities have altered the chemical composition of the atmosphere through the buildup of significant quantities of greenhouse gases (GHGs), which remain in the atmosphere for long periods of time and intensify the natural greenhouse effect. Increasing concentrations of greenhouse gases, mainly CO2, are likely to accelerate the rate of climate change. Concerns are growing about how increases in CO2 caused by human activities are contributing to the natural greenhouse effect and raising the Earth's average temperature. Electricity generation, especially from fossil fuel, and petroleum industries contribute the most to greenhouse gases emissions in Canada. As of 2004, they contributed to about 37% of total (GHGs). Risks of climate change and subsequent future environmental regulations are pressing electricity and petroleum refining industries to minimize their greenhouse gas emissions, mainly CO2. Fossil fuel power plants and refineries are now being challenged to comply with the Kyoto protocol by the United Nations Framework Convention and Climate Change (UNFCC). Canada’s target is a reduction in CO2 emissions of 6% from 1990 level. In this thesis, an optimization approach for integrating planning and CO2 reduction is developed for electricity and refinery sectors. Three different CO2 mitigation options are considered in each case. For the electricity sector, these mitigation options were 1) fuel balancing (optimal adjustment of the operation of existing generating stations to reduce CO2 emissions without making structural changes to the fleet), 2) fuel switching (switching from carbon intensive fuel to less carbon intensive fuel, essentially switching from coal to natural gas) and 3) implementing different technologies for efficiency improvement. The optimization model takes into account meeting electricity demand and achieving a certain CO2 reduction target at a minimum overall cost. The model was formulated as a Mixed Integer Non Linear Program (MINLP) and was implemented in GAMS (General Algebraic Modeling System). Exact linearization techniques were employed to facilitate solution development. The computer program was capable of determining the best strategy or mix of strategies to meet a certain CO2 reduction target at minimum cost. The model was illustrated on a case study for Ontario Power Generation (OPG) fleet. The results showed that for 1% CO2 reduction target, only fuel balancing need to be applied and even a decrease of about 1.3% in overall cost was obtained. The optimizer chose to increase production from all non fossil fuel power plants and to decrease production from natural gas power plant. This is because natural gas is the most expensive fuel that OPG uses. For higher reduction targets, it was necessary to implement fuel switching. For 30% reduction, for example, 11 boilers out of 27 (4 are already natural gas) are switched from coal to natural gas and the cost increases by about 13%. Applying efficiency improvement technologies such as installing new turbine blades was a good option only at small reduction targets. As the reduction target increases, the optimizer chose not to implement efficiency improvement technologies and only fuel switching was the best option to select in addition to fuel balancing. For the refinery sector, a similar strategy was applied. An optimization model was developed to maximize profit from selling final products and to meet a given CO2 reduction target with products demand and specifications. Three CO2 mitigation options were considered and these were: 1) balancing that implies the increase in production from units that emit less CO2 emissions provided that demand is met, 2) fuel switching that involves switching from current carbon intensive fuel to less carbon intensive fuel such as natural gas, 3) implementation of CO2 capture technologies. Chemical absorption (MEA) process was used as the capture process. Prior to the development of the refinery planning model, a sub-model was developed for each unit in a refinery layout. Then, the sub-models were integrated into a master planning model to meet final products demand and specifications with the objective of maximizing profit without CO2 mitigation options. The model was solved first as a Non Linear Program (NLP). Then, binary variables representing the existence or no existence of fuel switching option and CO2 capture processes were introduced into the model. The model was formulated as a Mixed Integer Non Linear Program (MINLP), coded in GAMS, and applied to different case studies. The results showed that the refinery planning model tends to produce more from the most profitable product, which is gasoline, and chose to blend products into the most profitable pool unless the demand needs to be satisfied for certain other products. The model, for example, chose to send kerosene from the diesel hydrotreater to the kerosene pool and not to the diesel pool since kerosene has higher selling value than diesel. When CO2 mitigation options were introduced into the model, only 0.4% CO2 reduction was achieved by simply decreasing production from the hydrocracker (HC) unit and increasing production from the fluidized catalytic cracking (FCC) unit. This was done because the FCC unit tends to emit less CO2 compared to the HC unit. At higher reduction target such as 1%, fuel switching was implemented by choosing the FCC to run with natural gas. The profit decreased slightly because of the retrofit cost of switching. It was noticed also that fuel switching can achieve a maximum of 30% reduction in CO2 emissions. This was achieved by switching all units to run with natural gas that emits less CO2 emissions. For a reduction target higher than 30%, CO2 capture technologies need to be applied. For 60% reduction, the optimization chose to switch three units (out of 8) and to capture CO2 emissions coming from four units. Only the FCC remained unchanged. A decrease in the profit was noticed as the reduction target increases since more units need to be switched and more CO2 need to be captured. The results showed that adding sequestration cost further decreased the profit. However, it was noticed that the selling price of final products had the most effect on the profit. An increase of 20%, for example, in final products’ prices, leads to a 10% increase in profit even when the CO2 reduction target was as high as 80%. When the retrofit cost for switching and capture was decreased by 30%, the effect on the profit was noticed only at higher reduction targets since more units were switched and more CO2 capture units were implemented

The development of steel industry makes progress simultaneously with economy and society of a country. The steel industry is an important industry for each country. From 2001, there was an insufficient supply gap of steel due to strong demand of China, which pushes main integrated steel works to increase their capacities. However, the mitigation pressure of the emission of Green House Gas make a limitations for capacity expansion. The objective of this study is to make appropriate policies for integrated steel works to cope with new operation environment. From the analysis of steel industry, this study discovers the features and the related operation issues of global steel industry. The relationship between production and CO2 emission was investigated, and the casual loop among the production, revenue, and CO2 emission was analyzed. A dynamic model was developed by system dynamics approach and related tools to simulate the dynamic relationship between the revenue and CO2 emission of steel work. After thorough tests of reliability, model behavior, and policy implications, this model was used to investigate the influence of main operational and environmental parameters on the revenue of steel work. The appropriate production policies for steel works was also proposed. Simulation results showed that, there was no universal production policy without the economic penalty for CO2 emission, but keeping the production under regulation limit was the most suitable strategy after the implementation of economic penalty. Increasing energy utilization efficiency, the ration of R&D budget in annual profit, and lowering the growth rate of production would facilitate the revenue increase of steel work. The simultaneous adjustment of these parameters could downgrade the negative effect of economic penalty. The main strategy to cope with the pressure of the CO2 mitigation is to reduce the unit cost of mitigation. Four approaches can be adopted by the steel work to tackle the CO2 mitigation. They are (1) carefully scheduling the capacity expansion of steel work, (2) actively deriving the legislation of economic penalty for CO2 emission, (3) reducing the unit cost for CO2 mitigation, (4) enhancing the power of R&D activities.

In recent years, there has been a concern for the amount of carbon dioxide released into the atmosphere and how it will be captured. One way to capture carbon dioxide is with algae. In this study, algae's growth was measured at different temperatures. The first part of the study was to grow Scenedesmus and Chlorella with M8 or urea growth media at a temperature of 25, 30 or 35ºC. It was found that 30ºC had the best growth rates for both algae. The second part studied Scenedesmus growth with urea, more in-depth, and found the optimum growth temperature to be 27.5ºC with a growth rate of 0.29 1/hr. The last part of the study was a heat transfer model which predicted the temperature of a greenhouse and an outdoor unit. The model could also predict the growth rate of the algae and the temperature if flue gas is mixed in with the algae.

Unicellular microalgae are a renewable bioresource that can meet the challenge forfood and energy in a growing world population. Using sunlight, CO2, nutrients,and water, algal cells produce biomass in the form of sugars, proteins and oils, allof which carry commercial value as food, feed and bioenergy. Flue gas CO2 andwastewater nutrients are inexpensive sources of carbon and fertilizers. Microalgaecan mitigate CO2 emissions and reduce nutrients from waste streams whileproducing valuable biomass.My focus was on some of the challenging aspects of cultivating microalgae ascrop: the response of biomass production and quality to seasonality, nutrients andbiological interactions. Approach spans from laboratory experiments to large-scaleoutdoor cultivation, using single microalgal strains and natural communities insouthern (Portugal) and northern (Sweden) Europe.Half of the seasonal variation in algal oil content was due to changes in light andtemperature in outdoor large-scale cultures of a commercial strain (Nannochloropsisoculata). Seasonal changes also influence algal oil composition with more neutrallipids stored in cells during high light and temperature. Nitrogen (N) stress usuallyenhances lipid storage but suppresses biomass production. Our manipulationshowed that N stress produced more lipids while retaining biomass. Thus,projecting annual biomass and oil yields requires accounting for both seasonalchanges and N stress to optimize lipid production in commercial applications.Baltic Sea microalgae proved to be a potential biological solution to reduce CO2emissions from cement flue gas with valuable biomass production. A multi-speciescultivation approach rather than single-species revealed that natural or constructedcommunities of microalgae can produce equivalent biomass quality. Diversecommunities of microalgae can offer resilience and stability due to more efficientresource utilization with less risk of contamination, less work and cost for culturemaintenance.Stable algal biomass production (annual basis) was achieved in outdoor pilot-scale(1600 L) cultivation of Baltic Sea natural communities using cement flue gas as aCO2 source. Results indicate favorable algal oil content at northern Europeanlatitudes compared to southern European latitudes.My thesis establishes the potential of cultivating microalgae as a bioresource inScandinavia, and using a community approach may be one step towardssustainable algal technology.

Today, a lot of resources are put into researching technological solutions concerning “carbon neutral” displacement materials and products, with the common goal of mitigating the amount of carbon dioxide in the atmosphere. The aim of this study was to find out whether a displacement of concrete to glulam beams, in the construction industry, could create substitution effects that reduces the amount of carbon dioxide in the atmosphere. To go about this, interviews were conducted with one producer of glulam beams, four construction companies and a non-profit foundation that funds research in fire prevention. Furthermore, sustainability declarations of glulam beams from three glulam beam producers, were analyzed. To compare carbon dioxide emissions in different scenarios, the interview results, as well as the sustainability declarations of the glulam beam producers, were compared and examined. Calculations of carbon dioxide sequestered in glulam beams and emitted from the concrete industry in Sweden were also regarded. The results showed that the possible substitution effects derived from a displacement of concrete to glulam beams, would have a small mitigating impact on the amount of CO2 in the atmosphere. However, recent findings point out that the pay back period for harvested trees, is longer than assumed. Moreover, the concrete production is not decreasing, but increasing. In respect of Jevons’ paradox (which concludes that higher efficiency in production leads to more consumption, not less), the conclusion of this study, was that no substitution will mitigate enough CO2 in the atmosphere. Our approach to consumption is what must change.

As part of the European Union’s climate commitment including the adoption of the Paris agreement, the European commission has developed a long-term strategy with the goal to reach net zero CO2emissions in 2050. To achieve this, a transformation of the European industry is necessary, as it represents 30% of EU’s total emissions. A major challenge will be to cut emissions in the CO2intensive steel industry, which is considered hard to abate. To reach the Paris agreement, deep emission cuts are necessary to occur within a decade, before cumulative emissions are too high. Today, about 60% of all steel in the EU is produced using coke as feedstock, a process resulting in large CO2 emissions. A new process in which hydrogen is used instead of coke is under development, with no direct CO2 emissions as result. The implementation of such technologies can help shift the production from fossil based to renewable, with declining emissions as a result. Until now, most abatement methods are focused on the supply side, finding technical solutions that can reduce emissions. This study shows that technology can play an important role in the transformation of the steel industry but will not alone achieve the necessary reductions fast enough. To achieve near-zero emissions in the steel industry, the solution set needs to widen to include demand side measures. The results show that circular economy principles that promote higher shares of recycled steel and reduced losses have the potential to lower total demand. This also applies for circular business models, by which incentives for higher utilisation and lifetimes of products can be created. In this report, demand-side measures are analysed using a stock-based steel demand model. It is estimated that demand-side measures can decrease the steel demand by 27% in 2050, compared to a business as usual scenario. Applying circular principles would also increase the share of recycled steel being produced from old steel scrap, a process far less CO2 intensive than virgin production. The findings are, that demand side measures can provide immediate deep emission cuts necessary, saving time before new technologies are implemented. The lower steel demand also helps making the transition from fossil to fossil-free steel production easier. By a combination of demand side reductions and hydrogen-DR the steel industry in Europe can reach near-zero emissions by 2050.

Cette thèse s’attache à la maximisation de la consommation du dioxyde de carbone par les microalgues. En effet, suite aux différentes problématiques environnementales actuelles liées principalement aux émissions importantes de gaz à effet de serre et notamment le CO2, il a été démontré que les microalgues jouent un rôle très prometteur pour la bio-fixation du CO2. Dans cette optique, nous nous intéressons à la mise en place d’une loi de commande robuste permettant de garantir des conditions opératoires optimales pour une culture de la microalgue Chlorella vulgaris dans un photobioréacteur instrumenté. Cette thèse repose sur trois axes principaux. Le premier porte sur la modélisation de la croissance de l’espèce algale choisie à partir d’un modèle mathématique traduisant l’influence de la lumière et de la concentration en carbone inorganique total. En vue de la commande, le deuxième axe est consacré à l’estimation de la concentration cellulaire à partir des mesures disponibles en temps réel du dioxyde de carbone dissous. Trois types d’observateurs ont été étudiés et comparés : filtre de Kalman étendu, observateur asymptotique et observateur par intervalles. Le dernier axe concerne l’implantation d’une loi de commande prédictive non-linéaire couplée à une stratégie d’estimation pour la régulation de la concentration cellulaire autour d’une valeur maximisant la consommation du CO2. Les performances et la robustesse de cette commande ont été validées en simulation et expérimentalement sur un photobioréacteur instrumenté à l’échelle de laboratoire. Cette thèse est une étude préliminaire pour la mise en œuvre de la maximisation de la fixation du dioxyde de carbone par les microalgues. / This thesis deals with the optimization of carbon dioxide consumption by microalgae. Indeed, following several current environmental issues primarily related to large emissions of CO2, it is shown that microalgae represent a very promising solution for CO2 mitigation. From this perspective, we are interested in the optimization strategy of CO2 consumption through the development of a robust control law. The main aim is to ensure optimal operating conditions for a Chlorella vulgaris culture in an instrumented photobioreactor. The thesis is based on three major axes. The first one concerns growth modeling of the selected species based on a mathematical model reflecting the influence of light and total inorganic carbon concentration. For the control context, the second axis is related to biomass estimation from the real-time measurement of dissolved carbon dioxide. This step is necessary for the control part due to the lack of affordable real-time sensors for this kind of measurement. Three observers structures have been studied and compared: an extended Kalman filter, an asymptotic observer and an interval observer. The last axis deals with the implementation of a non-linear predictive control law coupled to the estimation strategy for the regulation of the cellular concentration around a value which maximizes the CO2 consumption. Performance and robustness of this control law have been validated in simulation and experimentally on a laboratory-scale instrumented photobioreactor. This thesis represents a preliminary study for the optimization of CO2 mitigation strategy by microalgae.

The purpose of this report is to get an overview of the CO2 reduction possibilities when adopting different renewable energy source, when the case studied building sustains a district heating network connection and when not, and how the renewable energy source flexibilities (Solar and Wind) differ depending on region. The method regards a ETC house that falls into the climate positive category and assesses the reduction when comparing CO2 emissions form the energy demand. The result for the flexibilities is then compared to the BBR demand. The result shows a difference of around 10% in production for the flexibilities when comparing the northern and middle region with the southern. And a decrease between 19-36% gCO2. Comparing a scenario with and without a connection to the district heating network showed that when the ground source heat pump offsets the energy demand, CO2, and cost reductions (6 and 4% respectively) can be seen. With an average installation cost, the payback period for the ground source heat pump can be estimated to be around 4 year. In conclusion the thesis project shows that the climate is a ruling factor when assessing energy questions for the residential sector. It also shows the difference in CO2 and cost that comes with it can be reduced and help mitigated the sectors effects on the environment. This in turn shows that the overall reduction of CO2 for the case studied building follows the demands and goals set by the European commission and gives motivation to expand the construction as cost is also reduced.

[ES] Reducir las emisiones de gases contaminantes de los motores de combustión interna alternativos (MCIA) es uno de los mayores retos para combatir el calentamiento global. Dado que los motores seguirán siendo utilizados por la industria durante décadas, es necesario desarrollar nuevas tecnologías. En este contexto, la presente tesis doctoral viene motivada por la necesidad de seguir mejorando los motores, tanto desde el punto de vista de la ingeniería técnica como desde el punto de vista social, debido a los efectos de los gases de efecto invernadero. El objetivo principal de esta tesis es desarrollar una metodología de optimización para sistemas de combustión de motores de encendido por compresión (MEC) mediante el acoplamiento de algoritmos de optimización con simulación por ordenador. Con la optimización de los sistemas de combustión es posible aumentar la eficiencia de los motores, reduciendo así el consumo de combustible junto con la reducción de emisiones contaminantes, en particular óxidos de nitrógeno (NOx) y hollín. En el primer paso, se abordan diferentes algoritmos de optimización con el fin de elegir el mejor candidato para esta metodología. A partir de aquí, la primera optimización se centra en un motor de encendido por compresión que funciona con combustible convencional para validar la metodología y también para evaluar el estado actual de evolución de estos motores. Con el objetivo de reducir el consumo de combustible manteniendo los niveles de NOx y hollín por debajo de los valores de un motor real, se inicia el proceso de optimización. Los resultados obtenidos confirman que un nuevo sistema de combustión específico para este motor podría generar una reducción del consumo de combustible manteniendo las emisiones de gases por debajo del valor estipulado. Además, se concluye que los motores MEC que utilizan combustible convencional se encuentran ya en un nivel de eficiencia muy elevado, y es difícil mejorarlos sin utilizar un sistema de postratamiento. Así pues, el segundo bloque de optimización se basa en el uso de motores MEC que funcionan con un combustible alternativo, que en este caso es el OME. El objetivo de este estudio es diseñar un sistema de combustión específico para un motor que utilice este combustible y que ofrezca un rendimiento del mismo orden de magnitud que un motor diésel. En la búsqueda de una mayor eficiencia, las emisiones de NOx son una restricción del sistema de optimización para que el sistema de combustión no emita más gases que un motor real. En este caso, el hollín no se tiene en cuenta debido a que las características del combustible no producen este tipo de contaminante. Los resultados mostraron que un sistema de combustión diseñado específicamente para esta operación podía ofrecer altas eficiencias, incluso la eficiencia obtenida fue alrededor de 2,2 % mayor en comparación con el motor diesel real. Además, fue posible reducir a la mitad las emisiones de NOx cuando el motor funciona con OME. El último bloque de optimización se refiere a una nueva arquitectura de motor que permite eliminar las emisiones de NOx. El modelo de oxicombustión resulta apasionante, ya que se elimina el nitrógeno de la mezcla de admisión y, por tanto, no se generan emisiones que contengan N2. Además, con el uso de este modo de combustión, es posible capturar CO$_{2}$ de los gases de escape, que luego puede venderse en el mercado. Dado que se trata de un tema nuevo y poco investigado, los resultados son prometedores. Demuestran que fue posible obtener un sistema de combustión específico capaz de ofrecer niveles de eficiencia cercanos a los de los motores convencionales. Además, se eliminaron las emisiones de NOx, así como las de hollín. Adicionalmente, este sistema fue capaz de reducir las emisiones de CO y HC a niveles similares a los motores convencionales. Por otra parte, los resultados presentados en esta tesis doctoral proporcionan una base de datos ampliada para explorar el funcionamiento del motor CI. / [CAT] Reduir les emissions de gasos contaminants dels motors de combustió interna alternatius (MCIA) és un dels majors reptes per a combatre el camvi climàtic. Atés que els motors continuaran sent utilitzats per la indústria durant dècades, és necessari desenvolupar noves tecnologies. En aquest context, la present tesi doctoral ve motivada per la necessitat de continuar millorant els motors, tant des del punt de vista de l'enginyeria tècnica com des del punt de vista social, degut a l'efecte dels gasos d'efecte d'hivernacle. L'objectiu principal d'aquesta tesi és desenvolupar una metodologia d'optimització per a sistemes de combustió de motors d'encesa provocada mitjançant l'acoblament d'algorismes d'optimització amb simulació per ordinador. Amb l'optimització dels sistemes de combustió és possible augmentar l'eficiència dels motors, reduint així el consum de combustible, concomitantment amb la reducció d'emissions de gasos, en particular òxids de nitrogen (NOx) i sutge. En el primer pas, s'aborden diferents algorismes d'optimització amb la finalitat d'elegir el millor candidat per a aquesta metodologia. A partir d'ací, la primera optimització se centra en un motor d'encesa per compressió que funciona amb combustible convencional per a validar la metodologia i també per a avaluar l'estat actual d'evolució d'aquests motors. Amb l'objectiu de reduir el consum de combustible mantenint els nivells de NOx i sutge per davall dels valors d'un motor real, s'inicia el procés d'optimització. Els resultats obtinguts confirmen que un nou sistema de combustió específic per a aquest motor podria generar una reducció del consum de combustible mantenint les emissions de gasos per davall del valor estipulat. A més, es conclou que els motors d'encesa per compressió que utilitzen combustible convencional es troben ja en un nivell d'eficiència molt elevat, i és difícil millorar-los sense utilitzar un sistema de posttractament. Així doncs, el segon bloc d'optimització es basa en l'ús de motors d'encesa per compressió que funcionen amb un combustible alternatiu, que en aquest cas és el OME. L'objectiu d'aquest estudi és dissenyar un sistema de combustió específic per a un motor que utilitze aquest combustible i que oferisca un rendiment del mateix ordre de magnitud que un motor dièsel. En la cerca d'una major eficiència, les emissions de NOx són una restricció del sistema d'optimització perquè el sistema de combustió no emeta més gasos que un motor real. En aquest cas, el sutge no es té en compte pel fet que les característiques del combustible no produeixen aquest tipus de contaminant. Els resultats van mostrar que un sistema de combustió dissenyat específicament per a aquesta operació podia oferir altes eficiències, fins i tot l'eficiència obtinguda va ser al voltant de 2,2 % major en comparació amb el motor dièsel real. A més, va ser possible reduir a la meitat les emissions de NOx quan el motor funciona amb OME. L'últim bloc d'optimització es refereix a una nova arquitectura del motor que permet eliminar les emissions de NOx. El model de oxicombustió resulta apassionant, ja que s'elimina el nitrogen de la mescla d'admissió i, per tant, no es generen emissions que continguen N2. A més, amb l'ús d'aquesta manera de combustió, és possible capturar CO$_{2}$ dels gasos de fuita, que després pot vendre's en el mercat. Atés que es tracta d'un tema nou i poc investigat, els resultats són prometedors. Demostren que va ser possible obtindre un sistema de combustió específic capaç d'oferir nivells d'eficiència pròxims als dels motors convencionals. A més, es van eliminar les emissions de NOx, així com les de sutge. Addicionalment, aquest sistema va ser capaç de reduir les emissions de CO i HC a nivells similars als motors convencionals. D'altra banda, els resultats presentats en aquesta tesi doctoral proporcionen una base de dades ampliada per a explorar el funcionament del motor CI. / [EN] Reducing emissions of pollutant gases from internal combustion engines (ICE) is one of the biggest challenges to combat global warming. As the engines will continue to be used by industry for decades, it is necessary to develop new technologies. In this context, the present doctoral thesis was motivated by the need to further improve engines, both from a technical engineering and social point of view, due to the effects of greenhouse gases. The main objective of this thesis is to develop an optimization methodology for compression ignition (CI) engine combustion systems by coupling optimization algorithms with computer simulation. With the optimization of the combustion systems, it is possible to increase the efficiency of the engines, thus reducing fuel consumption, concomitantly with the reduction of gas emissions, in particular nitrogen oxides (NOx) and soot. In the first step, different optimization algorithms are addressed in order to elect the best candidate for this methodology. From this point on, the first optimization is focused on a CI engine operating with conventional fuel in order to validate the methodology and also to evaluate the current state of evolution of these engines. With the goal of reducing fuel consumption while keeping NOx and soot levels below the values of a real engine, the optimization process begins. The results obtained confirm that a new combustion system specifically for this engine could generate a reduction in fuel consumption while keeping gas emissions below the stipulated value. Furthermore, it is concluded that CI engines using conventional fuel are already at a very high-efficiency level, and it is difficult to improve them without the use of an after-treatment system. Thus, the second optimization block is based on the use of CI engines operating on an alternative fuel, which in this case is OME. This study aimed to design a specific combustion system for an engine using this fuel that delivers efficiency on the same order of magnitude as a diesel engine. While searching for better efficiency, the NOx emissions are a restriction of the optimization system so that the combustion system does not emit more gases than a real engine. In this case, soot is not considered due to the characteristics of the fuel not producing this kind of pollutant. The results showed that a combustion system designed specifically for this operation could deliver high efficiencies, including the efficiency obtained was around 2.2 \% higher compared to the real diesel engine. In addition, it was possible to halve the NOx emissions when the engine operates with OME. The last optimization block concerns a new engine architecture that makes it possible to eliminate NOx emissions. The oxy-fuel combustion model is exciting since nitrogen is eliminated from the intake mixture, and thus no emissions containing N2 are generated. Furthermore, with the use of this combustion mode, it is possible to capture CO$_{2}$ from the exhaust gas, which can then be sold to the market. Since this is a new and little-researched topic, the results are promising. They show that it was possible to obtain a specific combustion system capable of delivering efficiency levels close to conventional engines. Furthermore, NOx emissions were eliminated, as well as soot emissions. Additionally, this system was able to reduce CO and HC emissions to levels similar to conventional engines. Moreover, the results presented in this doctoral thesis provide an extended database to explore the CI engine operation. Additionally, this work showed the potential of computational simulation allied with mathematical methods in order to design combustion systems for different applications. / I want to thanks the Universitat Politecnica de Valencia for his predoctoral contract (FPI-2019-S2-20-555), which is included within the framework of Programa de Apoyo para la Investigacion y Desarrollo (PAID). / Spohr Fernandes, C. (2023). Analysis and CFD-Guided optimization of advanced combustion systems in compression-ignited engines [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/193292