29 resultados para Emissions atmosfèriques


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas Ambientais

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Dissertação para obtenção do Grau de Doutor em Alterações Climáticas e Políticas de Desenvolvimento Sustentável

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Dissertação para obtenção do Grau de Doutor em Ambiente

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Increasingly stringed regulations for diesel engine emissions have a significant impact on the required efficiency of DOC. Lowered DOC oxidation efficiency due to thermal aging effects influences the efficiency of the exhaust aftertreatment systems downstream of the DOC. In this work carried out in the Jean Le Rond d’Alembert Institute the effect of hydrothermal aging on the reactivity and structure of a commercial DOC was investigated. The characterization of the catalytic performance was carried out on a synthetic gas bench using carrots catalyst under conditions close to the realistic conditions i.e. using a synthetic gas mixture, representative of the exhaust gases from diesel engines. Different structural characterization techniques were performed: textural and morphological proprieties were analyzed by BET and TEM, the characterization of the presented crystallographic phases was performed by DRX and the determination of the number of reducible species was possible by TPR. TEM results shown, an increase of the metal particle size with the aging caused by the agglomeration of metal particles, revealing the presence of metal sintering. DRX results also suggest the presence of support sintering. Furthermore, DRX and BET results unexpectedly reveal that the most drastic aging conditions used actually activated the catalyst surface. As expected, the aging affected negatively the catalyst performance on the oxidation of methane and CO, however an improvement of the NO oxidation performance with the aging was observed. Nevertheless, for the aging conditions used, catalytic activity results show that the influence of aging in DOC performance was not significant, and therefore, more drastic aging conditions must be used.

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This publication reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

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Carbon dioxide valorization, will not only help to relieve the greenhouse effect but might also allow us to transform it in value-added chemicals that will help overcoming the energy crisis. To accomplish this goal, more research that focus on sequestering CO2 and endeavors through a carbon-neutral or carbon-negative strategy is needed in order to handle with the dwindling fossil fuel supplies and their environmental impact. Formate dehydrogenases are a promising means of turning CO2 into a biofuel that will allow for a reduction of greenhouse gas emissions and for a significant change to the economic paramount. The main objective of this work was to assess whether a NAD+-independent molybdenum-containing formate dehydrogenase is able to catalyze the reduction of CO2 to formate. To achieve this, a molybdenum-containing formate dehydrogenase was isolated from the sulfate reducing bacteria Desulfovibrio desulfuricans ATCC 27774. Growth conditions were found that allowed for a greater cellular mass recovery and formate dehydrogenase expression. After growth trials, kinetic assays for formate oxidation and CO2 reduction were performed and kinetic parameters determined. For the formate oxidation reaction, a KM of 49 μM and a turnover constant of 146 s-1 were determined. These kinetic parameters are in agreement with those determined by Mota, et al. (2011). Finally, we found that this molybdenum-containing enzyme was able to catalyze the reduction of CO2 to formate with a turnover constant of 4.6 s-1 and a KM of 13 μM. For the first time a NAD+-independent molybdenum-containing formate dehydrogenase was found to catalyze CO2 reduction, allowing its use as a biocatalyst in energetically efficient CO2 fixation processes that can be directed towards bioremediation or as an alternative and renewable energy source. Characterizing these enzymes may lead to the development of more efficient synthetic catalysts, make them readily available and more suited for practical applications.

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Field Lab of Entrepreneurial Innovative Ventures

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Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.

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An ion emitter consisting of a sharp silver tip covered in RbAg4I5 solid electrolyte film has been developed and studied. An accelerating potential is applied and Ag+ ions are emitted from the tip’s apex by field evaporation. The emitted ions are collected by a Faraday cup, producing a current on the pico/nanoampere level which is read by an electrometer. The tips were produced mechanically by sandpaper polishing. The sharpest tip produced had a 2:4 m apex radius. Two deposition methods were studied: thermal vacuum and pulsed laser deposition. The best tip produced a peak current value of 96nA at 180oC, and a quasi-stable 4nA emission current at 160oC, both using an extraction potential of 10kV . The emission dependence on time, temperature and accelerating potential has been studied. Deposited films were characterized by X-ray diffraction (XRD), profilometry, optical and Scanning Electron Microscope (SEM) and Secondary Ion Mass Spectroscopy (SIMS) measurements. Several ion emitters were developed, the latter ones were all able to maintain stable high ion emissions for long periods of time. This investigation was a continuation of an ongoing project backed by the European Space Agency, with the objective of making a proof of concept of this kind of ion emitter with potential application on ion thrusters for orbiting satellites. Going forward, it would be interesting to make a finer analysis of the electrolyte’s conductivity at high temperatures, explore Wien Effect-based emission and to further develop a multi-tip ion emitter prototype.

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The recent proposals presented by EPA aimed to reduce the dependency of fossil fuels and to lower current emissions levels, hoping to gradually shift electric generation units to renewable energy sources. Actually, the Final Rule Proposal announcement day exhibited a negative Abnormal Return on Fossil Fuels but the following days had positive Abnormal Returns, mostly due to legislative change perceived by financial markets which eased up implementation periods of the proposed measures in the Final Rule when compared to the Draft Rule. Oppositely, Renewables and Solar Portfolios exhibited negative Cumulative Abnormal Returns over the period surrounding the Final Rule.