973 resultados para Shrimp-Farms
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Dissertação de Mestrado em Engenharia do Ambiente.
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Dissertação de Mestrado, Engenharia Zootécnica (Zootecnia), 27 de abril de 2015, Universidade dos Açores.
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Dissertação para obtenção do grau de Engenharia Civil na Área de Especialização de Edificações
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A verificação das Características Garantidas associadas aos equipamentos, em especial dos aerogeradores, incluídos no fornecimento de Parques Eólicos, reveste-se de particular importância devido, principalmente, ao grande volume de investimento em jogo, ao longo período necessário ao retorno do mesmo, à incerteza quanto à manutenção futura das actuais condições de remuneração da energia eléctrica produzida e ainda à falta de dados históricos sobre o período de vida útil esperado para os aerogeradores. Em face do exposto, é usual serem exigidas aos fornecedores, garantias do bom desempenho dos equipamentos, associadas a eventuais penalidades, quer para o período de garantia, quer para o restante período de vida útil, de modo a minimizar o risco associado ao investimento. No fornecimento de Parques Eólicos existem usualmente três tipos de garantias, nomeadamente, garantia de Curva de Potência dos aerogeradores, garantia de Disponibilidade dos equipamentos ou garantia de Produção de Energia. Estas poderão existir isoladamente ou em combinação, dependendo das condições contratuais acordadas entre o Adjudicatário e o Fornecedor. O grau de complexidade e/ou trabalho na implementação das mesmas é variável, não sendo possível afirmar qual delas é a mais conveniente para o Adjudicatário, nem qual a mais exacta em termos de resultados. Estas dúvidas surgem em consequência das dificuldades inerentes à recolha dos próprios dados e também da relativamente ampla margem de rearranjo dos resultados permitido pelas normas existentes, possibilitando a introdução de certo tipo de manipulações nos dados (rejeições e correlações), as quais podem afectar de forma considerável as incertezas dos resultados finais dos ensaios. Este trabalho, consistiu no desenvolvimento, execução, ensaio e implementação de uma ferramenta informática capaz de detectar de uma forma simples e expedita eventuais desvios à capacidade de produção esperada para os aerogeradores, em função do recurso verificado num dado período. Pretende ser uma ferramenta manuseável por qualquer operador de supervisão, com utilização para efeitos de reparações e correcção de defeitos, não constituindo contudo uma alternativa a outros processos abrangidos por normas, no caso de aplicação de penalidades. Para o seu funcionamento, são utilizados os dados mensais recolhidos pela torre meteorológica permanente instalada no parque e os dados de funcionamento dos aerogeradores, recolhidos pelo sistema SCADA. Estes são recolhidos remotamente sob a forma de tabelas e colocados numa directoria própria, na qual serão posteriormente lidos pela ferramenta.
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Clinical and environmental samples from Portugal were screened for the presence of Aspergillus and the distributions of the species complexes were determined in order to understand how their distributions differ based on their source. Fifty-seven Aspergillus isolates from clinical samples were collected from 10 health institutions. Six species complexes were detected by internal transcribed spacer sequencing; Fumigati, Flavi, and Nigri were found most frequently (50.9%, 21.0%, and 15.8%, respectively). β-tubulin and calmodulin sequencing resulted in seven cryptic species (A. awamorii, A. brasiliensis, A. fructus, A. lentulus, A. sydowii, A. tubingensis, Emericella echinulata) being identified among the 57 isolates. Thirty-nine isolates of Aspergillus were recovered from beach sand and poultry farms, 31 from swine farms, and 80 from hospital environments, for a total 189 isolates. Eleven species complexes were found in these 189 isolates, and those belonging to the Versicolores species complex were found most frequently (23.8%). There was a significant association between the different environmental sources and distribution of the species complexes; the hospital environment had greater variability of species complexes than other environmental locations. A high prevalence of cryptic species within the Circumdati complex was detected in several environments; from the isolates analyzed, at least four cryptic species were identified, most of them growing at 37ºC. Because Aspergillus species complexes have different susceptibilities to antifungals, knowing the species-complex epidemiology for each setting, as well as the identification of cryptic species among the collected clinical isolates, is important. This may allow preventive and corrective measures to be taken, which may result in decreased exposure to those organisms and a better prognosis.
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Social concerns for environmental impact on air, water and soil pollution have grown along with the accelerated growth of pig production. This study intends to characterize air contamination caused by fungi and particles in swine production, and, additionally, to conclude about their eventual environmental impact. Fiftysix air samples of 50 litters were collected through impaction method. Air sampling and particle matter concentration were performed in indoor and also outdoor premises. Simultaneously, temperature and relative humidity were monitored according to the International Standard ISO 7726 – 1998. Aspergillus versicolor presents the highest indoor spore counts (>2000 CFU/m3) and the highest overall prevalence (40.5%), followed by Scopulariopsis brevicaulis (17.0%) and Penicillium sp. (14.1%). All the swine farms showed indoor fungal species different from the ones identified outdoors and the most frequent genera were also different from the ones indoors. The distribution of particle size showed the same tendency in all swine farms (higher concentration values in PM5 and PM10 sizes). Through the ratio between the indoor and outdoor values, it was possible to conclude that CFU/m3 and particles presented an eventual impact in outdoor measurements.
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O uso da energia eólica para a produção de eletricidade apresenta na última década um crescimento apreciável. Monitorizar o desempenho dos aerogeradores torna-se um processo incontornável, quer por motivos financeiros, quer por questões operacionais. Os investimentos despendidos na construção de parques eólicos são muito consideráveis, pelo que é essencial a análise constante dos aspetos preponderantes no retorno do investimento. A maximização da energia produzida por cada aerogerador é o objetivo principal da monitorização dos parques eólicos. Os sistemas Supervisory Control and Data Acquisition (SCADAs) instalados nos parques eólicos permitem uma supervisão em tempo real relativamente ao estado e funcionamento dos aerogeradores, adquirindo uma elevada importância na avaliação dos rendimentos energéticos e anomalias de funcionamento, garantido desta forma melhorias de produtividade. O objetivo deste trabalho é estimar a energia produzida pelos aerogeradores quando ocorrem falhas de comunicação com o seu contador interno ou avaria do mesmo. A ocorrência destas situações não permite a monitorização da energia produzida durante esse período. Foram analisados dados operacionais dos aerogeradores relativos a um parque eólico localizado na zona Norte de Portugal, sendo usados os dados recolhidos pelo sistema SCADA sobre a forma de médias de 10 min referentes ao período de janeiro de 2011 a agosto 2011. O desempenho da rede neuronal depende da qualidade e quantidade do conjunto de dados usados para o treino da rede. Os dados usados devem representar de forma fiel o estado que se pretende para o equipamento. Para a obtenção do objetivo proposto foi fundamental a identificação das grandezas disponíveis a utilizar no método de cálculo da energia produzida. Os resultados obtidos com aplicação das redes neuronais no método de cálculo da energia produzida por aerogeradores demonstram que independentemente do período de indisponibilidade da informação referente à energia produzida é possível estimar o valor da mesma.
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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.
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Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.
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The most common scenario in occupational settings is the co-exposure to several risk factors. This aspect has to be considered in the risk assessment process because can alter the toxicity and the health effects when dealing with a co-exposure to two or more chemical agents. A study was developed aiming to elucidate if there is occupational co-exposure to aflatoxin B1 (AFB1) and ochratoxin (OTA) in Portuguese swine production. To assess occupational exposure to both mycotoxins, a biomarker of internal dose was used. The same blood samples from workers of seven swine farms and controls were consider to measure AFB1 and OTA. Twenty one workers (75%) showed detectable levels of AFB1 with values ranging from <1 ng/ml to 8.94 ng/ml and with significantly higher concentration when compared with controls. In the case of OTA, there wasn't found a statistical difference between workers and controls and the values for workers group ranged from 0.34 ng/ml to 3.12 ng/ml and 1.76 ng/ml to 3.42 ng/ml for control group. The results suggest that occupational exposure to AFB1 occurs. However, in the case of OTA results, seems that food consumption plays an important role in both groups exposure. The results claim attention for the possible implications on health of this co-exposure.
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Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.
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Thesis submitted to the Faculty of Sciences and Technology, New University of Lisbon, for the degree of Doctor of Philosophy in Environmental Sciences
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The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.