13 resultados para Indoor Particle Number Concentration
em Instituto Politécnico do Porto, Portugal
Resumo:
Due to their detrimental effects on human health, scientific interest in ultrafine particles (UFP), has been increasing but available information is far from comprehensive. Children, who represent one of the most susceptible subpopulation, spend the majority of time in schools and homes. Thus, the aim of this study is to (1) assess indoor levels of particle number concentrations (PNC) in ultrafine and fine (20–1000 nm) range at school and home environments and (2) compare indoor respective dose rates for 3- to 5-yr-old children. Indoor particle number concentrations in range of 20–1000 nm were consecutively measured during 56 d at two preschools (S1 and S2) and three homes (H1–H3) situated in Porto, Portugal. At both preschools different indoor microenvironments, such as classrooms and canteens, were evaluated. The results showed that total mean indoor PNC as determined for all indoor microenvironments were significantly higher at S1 than S2. At homes, indoor levels of PNC with means ranging between 1.09 × 104 and 1.24 × 104 particles/cm3 were 10–70% lower than total indoor means of preschools (1.32 × 104 to 1.84 × 104 particles/cm3). Nevertheless, estimated dose rates of particles were 1.3- to 2.1-fold higher at homes than preschools, mainly due to longer period of time spent at home. Daily activity patterns of 3- to 5-yr-old children significantly influenced overall dose rates of particles. Therefore, future studies focusing on health effects of airborne pollutants always need to account for children’s exposures in different microenvironments such as homes, schools, and transportation modes in order to obtain an accurate representation of children overall exposure.
Resumo:
The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.
Resumo:
The evaluation of benzene in different environments such as indoor (with and without tobacco smoke), a city area, countryside, gas stations and near exhaust pipes from cars running on different types of fuels was performed. The samples were analyzed using gas chromatography (GC) with flame ionization detection (FID) and tandem mass spectrometric detection (MS/MS) (to confirm the identification of benzene in the air samples). Operating conditions for the GC-MS analysis were optimized as well as the sampling and sample preparation. The results obtained in this work indicate that i) the type of fuel directly influences the benzene concentration in the air. Gasoline with additives provided the highest amount of benzene followed by unleaded gasoline and diesel; ii) the benzene concentration in the gas station was always higher than the advisable limit established by law (5 μg m−3) and during the unloading of gasoline the achieved concentration was 8371 μg m−3; iii) the data from the countryside (Taliscas) and the urban city (Matosinhos) were below 5 μg m−3 except 5 days after a fire on a petroleum refinery plant located near the city; iv) it was proven that in coffee shops where smoking is allowed the benzene concentration is higher (6 μg m−3) than in coffee shops where this is forbidden (4 μg m−3). This method may also be helpful for environmental analytical chemists who use GC-MS/MS for the confirmation or/and quantification of benzene.
Resumo:
This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
Resumo:
A Qualidade do Ar Interior (QAI) é um fator de grande preocupação. A importância de manter um ambiente salubre é mais acentuada em estabelecimentos escolares (EE), tendo em conta, que no interior destes permanecem crianças durante um elevado período de tempo. É fundamental garantir uma boa QAI nos edifícios escolares, de forma a salvaguardar a saúde, o bem-estar e o conforto dos ocupantes, bem como, não comprometer o seu desempenho escolar. Recentemente, foram construídos novos edifícios escolares e alguns dos existentes foram alvo de obras de remodelação. Contudo, a crescente tendência em construir edifícios cada vez mais herméticos, com vista à diminuição dos gastos de energia, origina problemas como a reduzida ventilação dos espaços. Vários estudos têm demonstrado a influência das atividades de limpeza na QAI. No entanto, verifica-se que na maioria das escolas não existem ainda procedimentos de limpeza padronizados. A falta de instruções de trabalho e a ausência de formação às assistentes operacionais pode comprometer a eficácia dos procedimentos de higienização, o que poderá ter influência na QAI dos espaços. Este estudo teve como principal objetivo avaliar a QAI em escolas básicas de 1.º ciclo. Foram contemplados no estudo fatores como a tipologia do edifício, a ocupação das salas e as atividades de limpeza. Procedeu-se à caracterização dos EE e à monitorização de parâmetros ambientais, como a temperatura do ar, a humidade relativa, a velocidade do ar, o dióxido de carbono, o monóxido de carbono, as partículas, os microrganismos mesófilos totais e os fungos. Estes parâmetros foram avaliados nas salas com ocupação, sem ocupação e durante a implementação de um plano de higienização. A ventilação inadequada parece ser o fator que mais condiciona a QAI das salas de aula avaliadas. Registaram-se elevadas concentrações de dióxido de carbono e de microrganismos mesófilos totais, que parecem estar relacionados com a permanência dos ocupantes nos locais e com a falta de ventilação adequada dos espaços. A concentração de dióxido de carbono foi mais elevada em edifícios recentes. Os picos elevados na concentração de partículas parecem estar associados com as atividades dos ocupantes. Obtiveram-se concentrações menores de fungos e de microrganismos mesófilos totais ao longo da implementação do plano de higienização, o que poderá significar que os procedimentos de limpeza contribuem para reduzir os níveis de contaminação dos espaços interiores. No entanto, tendo em conta, que a concentração de microrganismos mesófilos totais permaneceu elevada, as operações de limpeza parecem não ser suficientes para garantir uma boa QAI. O aumento da ventilação dos espaços poderia contribuir significativamente para a melhoria da QAI dos espaços avaliados.
Resumo:
Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.
Resumo:
Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) agents interacting locally with their environment cause coherent functional global patterns to emerge. Particle swarm optimization (PSO) is a form of SI, and a population-based search algorithm that is initialized with a population of random solutions, called particles. These particles are flying through hyperspace and have two essential reasoning capabilities: their memory of their own best position and knowledge of the swarm's best position. In a PSO scheme each particle flies through the search space with a velocity that is adjusted dynamically according with its historical behavior. Therefore, the particles have a tendency to fly towards the best search area along the search process. This work proposes a PSO based algorithm for logic circuit synthesis. The results show the statistical characteristics of this algorithm with respect to number of generations required to achieve the solutions. It is also presented a comparison with other two Evolutionary Algorithms, namely Genetic and Memetic Algorithms.
Resumo:
O objectivo principal deste trabalho é a realização de uma auditoria, à qualidade do ar interior (QAI), a um edifício de serviços – COCIGA, SA, tendo como base o Regulamento dos Sistemas Energéticos de Climatização dos Edifícios (RSECE). A auditoria QAI implica a medição de vários parâmetros físicos, químicos, microbiológicos e também a inspecção aos componentes do sistema de climatização com a finalidade de averiguar o seu estado de limpeza e manutenção. Assim, foram seleccionados 3 espaços, para a realização de amostragens designados por Comercial - Produtos, AVAC e Mezaninne das oficinas, nos quais foi efectuada a medição de diversos parâmetros, de acordo com as imposições do RSECE, utilizando medidores portáteis ou recorrendo a métodos analíticos. Relativamente aos parâmetros físicos, registaram-se valores de temperatura, para os três espaços estudados, entre os 21 e os 24 ºC e valores médios de humidade relativa de cerca de 50 %. Outro parâmetro medido, e de grande importância para garantir o conforto dos ocupantes, foi a velocidade do ar nos postos de trabalho. De acordo com o RSECE este valor não deve ser superior a 0,2 m/s, o que se verificou em todos os pontos medidos. O último parâmetro físico medido foi a concentração de partículas (PM10) tendo-se obtido valores de cerca de 23 μg/m3ar, valor bastante inferior ao máximo permitido pelo RSECE (150 μg/m3ar). Também no que diz respeito aos parâmetros químicos, ou seja, CO2, CO, formaldeído e ozono, não se verificaram valores superiores aos regulamentares. No caso do CO2, o valor máximo encontrado, nestes três espaços, foi de 745 ppm na Mezaninne das Oficinas e para o CO, na zona AVAC com uma concentração de 0,73 ppm. A medição do formaldeído registou valores perto dos 45 μg/m3ar e o ozono apenas foi detectado, em concentração muito reduzida, na zona Comercial – Produtos. Por fim, as concentrações de bactérias e fungos, de acordo com o RSECE, não devem ultrapassar as 500 UFC/m3ar (parâmetros microbiológicos). Em qualquer dos espaços, os valores medidos foram inferiores ao máximo legal, não ultrapassando as 50 UFC/m3ar. Da avaliação do projecto AVAC, e através da medição dos caudais de insuflação/ extracção em cada zona, concluiu-se que os seus valores não estão de acordo com os valores do projecto inicial que poderá ser imputada a uma insuficiência no funcionamento do sistema detectada na altura das medições. No que diz respeito ao estado de limpeza do sistema AVAC, apenas foi possível inspeccionar as unidades de tratamento de ar, tendo-se constatado que se encontram em boas condições. Ou seja, do ponto de vista do RSECE, e referindo-nos apenas à vertente da Qualidade do Ar Interior, o edifício em causa, cumpre todos os limites impostos para as concentrações de poluentes mas, apresenta algumas deficiências no que respeita aos caudais de ar novo insuflados em cada espaço.
Resumo:
This paper presents an ankle mounted Inertial Navigation System (INS) used to estimate the distance traveled by a pedestrian. This distance is estimated by the number of steps given by the user. The proposed method is based on force sensors to enhance the results obtained from an INS. Experimental results have shown that, depending on the step frequency, the traveled distance error varies between 2.7% and 5.6%.
Resumo:
This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
Resumo:
The intensification of agricultural productivity is an important challenge worldwide. However, environmental stressors can provide challenges to this intensification. The progressive occurrence of the cyanotoxins cylindrospermopsin (CYN) and microcystin-LR (MC-LR) as a potential consequence of eutrophication and climate change is of increasing concern in the agricultural sector because it has been reported that these cyanotoxins exert harmful effects in crop plants. A proteomic-based approach has been shown to be a suitable tool for the detection and identification of the primary responses of organisms exposed to cyanotoxins. The aim of this study was to compare the leaf-proteome profiles of lettuce plants exposed to environmentally relevant concentrations of CYN and a MC-LR/CYN mixture. Lettuce plants were exposed to 1, 10, and 100 lg/l CYN and a MC-LR/CYN mixture for five days. The proteins of lettuce leaves were separated by twodimensional electrophoresis (2-DE), and those that were differentially abundant were then identified by matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF/TOF MS). The biological functions of the proteins that were most represented in both experiments were photosynthesis and carbon metabolism and stress/defense response. Proteins involved in protein synthesis and signal transduction were also highly observed in the MC-LR/CYN experiment. Although distinct protein abundance patterns were observed in both experiments, the effects appear to be concentration-dependent, and the effects of the mixture were clearly stronger than those of CYN alone. The obtained results highlight the putative tolerance of lettuce to CYN at concentrations up to 100 lg/l. Furthermore, the combination of CYN with MC-LR at low concentrations (1 lg/l) stimulated a significant increase in the fresh weight (fr. wt) of lettuce leaves and at the proteomic level resulted in the increase in abundance of a high number of proteins. In contrast, many proteins exhibited a decrease in abundance or were absent in the gels of the simultaneous exposure to 10 and 100 lg/l MC-LR/CYN. In the latter, also a significant decrease in the fr. wt of lettuce leaves was obtained. These findings provide important insights into the molecular mechanisms of the lettuce response to CYN and MC-LR/CYN and may contribute to the identification of potential protein markers of exposure and proteins that may confer tolerance to CYN and MC-LR/CYN. Furthermore, because lettuce is an important crop worldwide, this study may improve our understanding of the potential impact of these cyanotoxins on its quality traits (e.g., presence of allergenic proteins).