14 resultados para Environmental impact statements

em Universidad Politécnica de Madrid


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The environmental impact of systems managing large (kg) tritium amount represents a public scrutiny issue for the next coming fusion facilities as ITER and DEMO. Furthermore, potentially new dose limits imposed by international regulations (ICRP) shall impact next coming devices designs and the overall costs of fusion technology deployment. Refined environmental tritium dose impact assessment schemes are then overwhelming. Detailed assessments can be procured from the knowledge of the real boundary conditions of the primary tritium discharge phase into atmosphere (low levels) and into soils. Lagrangian dispersion models using real-time meteorological and topographic data provide a strong refinement. Advance simulation tools are being developed in this sense. The tool integrates a numerical model output records from European Centre for Medium range Weather Forecast (ECMWF) with a lagrangian atmospheric dispersion model (FLEXPART). The composite model ECMWF/FLEXTRA results can be coupled with tritium dose secondary phase pathway assessment tools. Nominal tritium discharge operational reference and selected incidental ITER-like plant systems tritium form source terms have been assumed. The realtime daily data and mesh-refined records together with lagrangian dispersion model approach provide accurate results for doses to population by inhalation or ingestion in the secondary phase

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The paper considers short-term releases of tritium (mainly but not only tritium hydride (HT)) to the atmosphere from a potential ITER-like fusion reactor located in the Mediterranean Basin and explores if the short range legal exposure limits are exceeded (both locally and downwind). For this, a coupled Lagrangian ECMWF/FLEXPART model has been used to follow real time releases of tritium. This tool was analyzed for nominal tritium operational conditions under selected incidental conditions to determine resultant local and Western Mediterranean effects, together with hourly observations of wind, to provide a short-range approximation of tritium cloud behavior. Since our results cannot be compared with radiological station measurements of tritium in air, we use the NORMTRI Gaussian model. We demonstrate an overestimation of the sequence of tritium concentrations in the atmosphere, close to the reactor, estimated with this model when compared with ECMWF/FLEXPART results. A Gaussian “mesoscale” qualification tool has been used to validate the ECMWF/FLEXPART for winter 2010/spring 2011 with a database of the HT plumes. It is considered that NORMTRI allows evaluation of tritium-in-air-plume patterns and its contribution to doses.

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One of the key scrutiny issues of new coming energy era would be the environmental impact of fusion facilities managing one kg of tritium. The potential change of committed dose regulatory limits together with the implementation of nuclear design principles (As Low as Reasonably achievable - ALARA -, Defense in Depth -D-i-D-) for fusion facilities could strongly impact on the cost of deployment of coming fusion technology. Accurate modeling of environmental tritium transport forms (HT, HTO) for the assessment of fusion facility dosimetric impact in Accidental case appears as of major interest. This paper considers different short-term releases of tritium forms (HT and HTO) to the atmosphere from a potential fusion reactor located in the Mediterranean Basin. This work models in detail the dispersion of tritium forms and dosimetric impact of selected environmental patterns both inland and in-sea using real topography and forecast meteorological data-fields (ECMWF/FLEXPART). We explore specific values of this ratio in different levels and we examine the influence of meteorological conditions in the HTO behavior for 24 hours. For this purpose we have used a tool which consists on a coupled Lagrangian ECMWF/FLEXPART model useful to follow real time releases of tritium at 10, 30 and 60 meters together with hourly observations of wind (and in some cases precipitations) to provide a short-range approximation of tritium cloud behavior. We have assessed inhalation doses. And also HTO/HT ratios in a representative set of cases during winter 2010 and spring 2011 for the 3 air levels.

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We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3.

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The European Commission established Mid-term evaluation for the period 2007-2013 on Rural Development Programs as part of a continuous evaluation system. Mid-term evaluations are important for the Commission because they help measuring the success of a program, as well as giving advice and pointing out good practices for the current and consecutive programming periods. One of the main elements used to achieve these objectives is the impact indicators estimation of the program. This paper will focus on how impact indicators estimation is done for just the environmental indicators. To do this the 88 Mid-term evaluations of Rural Development Programs for 2007-2013 period, were analyzed. This study shows how far the actual methodologies to obtain impact indicators? values are from what the European Commission expects when demanding this task to be done.

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Data centers are easily found in every sector of the worldwide economy. They are composed of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of Data Centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grep 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, Data Centers are responsible for more than 2% of total carbon dioxide emissions.

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Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

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The European construction industry is supposed to consume the 40% of the natural European resources and to generate the 40% of the European solid waste. Conscious of the great damage being suffered by the environment because of construction activity, this work tries to provide the building actors with a new tool to improve the current situation. The tool proposed is a model for the comprehensive evaluation of construction products by determining their environmental level. In this research, the environmental level of a construction product has been defined as its quality of accomplishing the construction requirements needed by causing the minimum ecological impact in its surrounding environment. This information allows building actors to choose suitable materials for building needs and also for the environment, mainly in the project stage or on the building site, contributing to improve the relationship between buildings and environment. For the assessment of the environmental level of construction products, five indicators have been identified regarding their global environmental impact through the product life cycle: CO2 emissions provoked during their production, volume and toxicity of waste generated on the building site, durability and recycling capacity after their useful life. Therefore, the less environmental impact one construction product produces, the higher environmental level performs. The model has been tested in 30 construction products that include environmental criteria in their description. The results obtained will be discussed in this article. Furthermore, this model can lay down guidelines for the selection of ecoefficient construction products and the design of new eco-competitive and eco-committed ones

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To determine the risk of nitrate pollution in agricultural systems have identified several indexes and efficiencies that may lead an effective N fertilizer management for obtain the maximum yield with minimum environmental impact and health

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streets in local residential areas in large cities, real traffic tests for pollutant emissions and fuel consumption have been carried out in Madrid city centre. Emission concentration and car activity were simultaneously measured by a Portable Emissions Measurement System. Real life tests carried out at different times and on different days were performed with a turbo-diesel engine light vehicle equipped with an oxidizer catalyst and using different driving styles with a previously trained driver. The results show that by reducing the speed limit from 50 km h-1 to 30 km h-1, using a normal driving style, the time taken for a given trip does not increase, but fuel consumption and NOx, CO and PM emissions are clearly reduced. Therefore, the main conclusion of this work is that reducing the speed limit in some narrow streets in residential and commercial areas or in a city not only increases pedestrian safety, but also contributes to reducing the environmental impact of motor vehicles and reducing fuel consumption. In addition, there is also a reduction in the greenhouse gas emissions resulting from the combustion of the fuel.

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Proper management of the N applied to crops is necessary in order to increase yield, improve water use efficiency (WUE) and reduce the pollutions risks with the least economic, environmental and health costs. A field study with melon crops was conducted during 2005, 2006 and 2007 in central Spain, using 11 different amounts of N. Some environmental indexes have been proposed, to provide an essential tool for determining the groundwater pollution risks associated with common agricultural practices. These indexes are related to variation in the nitrate concentration of drinking water (Impact Index (II)) and groundwater (Environmental Impact Index (EII)). Also, the Management Efficiency (ME) was calculated, which is related to the amount of fruit produced per gram of N leached (Nl). To determine the optimum dose of N, it was also necessary to know the N mineralisation (NM). Our results show that 160 kg ha?1 of available N (Nav) produced the maximum fruit yield (FY), enhanced WUE and gave an NM of 85 kg ha?1, while the impact indexes did not exceed the fixed maximum allowable limits and ME was adequate. The proposed indexes proved to be an effective tool for determining the risk of nitrate contamination and confirmed that the optimum dose of N corresponded to the maximum FY with minimal loss of Nl.

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Insulating materials in buildings are one of the main factors that should be taken into account when talking about sustainability since with a correct application it could imply important savings for the citizens. In the course of its life, a building requires a series of supplies to perform the duties it has been built for, generating an impact on the environment. The selection of one material or another will establish partly the global environmental impact of the building. Choosing the right insulating material will determine the building's general degree of sustainability, both in its heating savings (energy consumption) and in the environmental impacts caused by its LCA (greenhouse gas emissions). Therefore, we propose to establish guidelines to characterize the insulating material with a better environmental performance in all the stages of its life cycle, taking into account the construction system, the use of the building and its location.

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Proper management of the N applied to crops is necessary in order to increase yield, improve water use efficiency (WUE) and reduce the pollutions risks with the least economic, environmental and health costs. A field study with melon crops was conducted during 2005, 2006 and 2007 in central Spain, using 11 different amounts of N. Some environmental indexes have been proposed, to provide an essential tool for determining the groundwater pollution risks associated with common agricultural practices. These indexes are related to variation in the nitrate concentration of drinking water (Impact Index (II)) and groundwater (Environmental Impact Index (EII)). Also, the Management Efficiency (ME) was calculated, which is related to the amount of fruit produced per gram of N leached (Nl). To determine the optimum dose of N, it was also necessary to know the N mineralisation (NM). Our results show that 160 kg ha−1 of available N (Nav) produced the maximum fruit yield (FY), enhanced WUE and gave an NM of 85 kg ha−1, while the impact indexes did not exceed the fixed maximum allowable limits and ME was adequate. The proposed indexes proved to be an effective tool for determining the risk of nitrate contamination and confirmed that the optimum dose of N corresponded to the maximum FY with minimal loss of Nl.

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The environmental performance of a 50 MW parabolic trough Concentrated Solar Power (CSP) plant hybridised with different fuels was determined using a Life Cycle Assessment methodology. Six different scenarios were investigated, half of which involved hybridisation with fossil fuels (natural gas, coal and fuel oil), and the other three involved hybridisation with renewable fuels (wheat straw, wood pellets and biogas). Each scenario was compared to a solar-only operation. Nine different environmental categories as well as the Cumulative Energy Demand and the Energy Payback Time (EPT) were evaluated using Simapro software for 1 MWh of electricity produced. The results indicate a worse environmental performance for a CSP plant producing 12% of the electricity from fuel than in a solar-only operation for every indicator, except for the eutrophication and toxicity categories, whose results for the natural gas scenario are slightly better. In the climate change category, the results ranged between 26.9 and 187 kg CO2 eq/MWh, where a solar-only operation had the best results and coal hybridisation had the worst. Considering a weighted single score indicator, the environmental impact of the renewable fuels scenarios is approximately half of those considered in fossil fuels, with the straw scenario showing the best results, and the coal scenario the worstones. EPT for solar-only mode is 1.44 years, while hybridisation scenarios EPT vary in a range of 1.72 -1.83 years for straw and pellets respectively. The fuels with more embodied energy are biomethane and wood pellets.