955 resultados para Material Particulado


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Este artigo mostra a distribuição dos nutrientes no estuário do rio Paracauari, durante um ciclo hidrológico amazônico (2008), e no final do período de La Niña (abril de 2008). Esse estuário é influenciado por clima tropical úmido e meso-marés (3 a 4m), semi-diurna. A amostragem foi realizada em 10 estações em três períodos sazonais distintos: chuvoso (março), intermediário (junho) e menos chuvoso (setembro). Medimos “in situ” os parâmetros físico-químicos utilizando uma sonda multiparâmetro; analisamos os nutrientes dissolvidos (nitrato, nitrito, n-amoniacal, fosfato e silicato) por espectofotometria e o material particulado em suspensão por gravimetria. Observamos amplas variações sazonais nas concentrações dos parâmetros estudados. A temperatura da água (média de 28,58 ºC) é bastante homogênea, típica das águas tropicais. O pH variou de ácido (5,80) à alcalino (7,86) e a salinidade entre 0,06 a 7,56 ambos com valores máximos na foz, devido à maior influência marinha. As águas são mal oxigenadas no período chuvoso (2,35 mg.L-1) e bem no menos chuvoso (6,55 mg.L-1). As concentrações de material particulado em suspensão e de nutrientes foram máximas no período chuvoso devido ao aporte natural proveniente das áreas adjacentes.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Química - IQ

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Pós-graduação em Engenharia Mecânica - FEG

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Fluidization consists in a bed of solid particles acquire fluid behavior by using a fluid (in this case air) flowing through the solid particles. Because of this, it can be a good mix of these materials, as well as to show increased rates of heat and mass transport. The fluid flowing through the spaces between the particles gives an interstitial velocity, that if is too low does not cause movement of the particulates. The gradual increase in speed will generate small vibrations between the particles promotes its fluidization. Our study focus in the fluid state of solid bed , when the fluid velocity reaches a state where the drag forces are sufficient to support the weight of the solid particles making these solids behave like fluids . Knowledge of the minimum velocity required to fluidize that particles is of great importance since below this speed there is no fluidization, and far above it, the solids are carried out of the bed. The fluidized bed reactor is widely used in physics and engineering, particularly in gas-solid fluidization, with emphasis on thermochemical processes

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The use of biomass as an energy source has been increasing in Brazil, with emphasis on the use of wood biomass, such as bark, wood chips and sawdust, that after receiving the appropriate treatment can be used in burners for power generation. However, from this burning are emitted fine particles known as particulate matter and a wide range of toxic organic and inorganic components in the form of gases that contribute greatly to air pollution and global warming, affecting human health, the environment and climate. The objective of this project was the quantification of gaseous and particulate, using and evaluating the equipment DR4000 ( Dataram 4 ) sampling of particulates smaller than 2.5μm and EUROTRON ( Ecoline 4000 ) when sampling gaseous pollutants, emitted from the burning of biomass in real time in the firing burner to a chimney attached biomass . We note that there are no specific rules that establish emission limits for particulate matter with diameter less than 2.5μm that are most harmful to human health and the highest concentrations reached about 800000μg/m3, for smaller diameters. It is noticeable the need for sampling of pollutants especially in industries that use biomass to fuel that could be implanted emission control equipment

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It is clear today the ever-accelerating search for new fuels that will eventually replace those that will survive in our society, which are fossil fuels. For this reason, a fuel used since the dawn of humanity and much studied since then, considered the generator of clean, renewable energy, can earn more and more space in the power generation sector, which is biomass. We performed two experiments with two different types of biomass, one from the Amazon rainforest and other pine and eucalyptus as waste from the sawmill UNESP Itapeva. In the first experiment, conducted at the Laboratory of Combustion and Propulsion INPE Cachoeira Paulista were conducted three tests in a chimney with a fan creating forced ventilation, where the biomass was burned and deposited on a support beneath the hood. In the second experiment was conducted to analyze the emission of particulate matter using biomass (waste) from the sawmill on the campus of UNESP experimental Itapeva the burning of it in a burner for heating water for a wood oven. In these experiments we used a particle called DATARAM4 sampler that is capable of sampling both outdoors and inside of pipelines, which is the focus of this work. With this equipment it was possible to measure the concentration of particulate matter in all the firings as above, and compare them to levels acceptable in the current law, always trying to analyze the so-called fine particles, which are those with diameters less than 2.5 μm. Using data obtained from the equipment was also possible to evaluate the diametral distribution of particulate matter in question, and verify which phases of the flares in the concentration and the diameters of the particles are the most critical. In this work we concluded that in all firings conducted concentrations of particulate matter were higher than that allowed by the law, and the diameters were found that are more harmful to human health

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Air pollution is an environmental issue worldwide and frequently cause negative effects on population health and ecosystems on cities. The relationship between climate and atmospheric pollution can be used as a surrogate to the intensity of air pollution. The present and quantity of some gases can be used as indicators to air quality: particulate matter (PM), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), and nitrogen dioxide (NO2). Among those gases, CO has its major source within the cities, where automobiles are the main emitter. But measure pollutant concentration are challenging, sometimes because the lack of good equipments due to high costs and of the large variability of models that varies in precision, way of measure and distribution of sellers. Modeling are useful when there are an intend to evaluate air pollution, its sources and evaluate scenarios. This work aims to use CAL3QHCR model developed by the U.S Environmental Protection Agency (EPA) to generate predictive surfaces of CO concentration distribution on a site within Campinas city, located in São Paulo state, Brazil. CAL3QHCR model use data urban automobile circulation to generate spatial results for CO distribution. We observed that the pollution concentration was lower on our modeling than the concentrations measured by Companhia Ambiental do Estado de São Paulo (CETESB), the main environmental company on the São Paulo state. Also the correlation between average estimates of our model and the measure by CETESB was weak, indicating that the model used on this study need to be or better parameterized, or the scale we measured of CO emissions need to be rescaled. Although the model failed to correlate to CETESB data, maybe one that explore the estimated emissions distributed within the sites to understand spatial distributions of CO on the regions. Also, the generated information can also be used to other studies, and come to be useful to explain heat island

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Abstract A fuzzy linguistic model based on the Mamdani method with input variables, particulate matter, sulfur dioxide, temperature and wind obtained from CETESB with two membership functions each was built to predict the average hospitalization time due to cardiovascular diseases related to exposure to air pollutants in São José dos Campos in the State of São Paulo in 2009. The output variable is the average length of hospitalization obtained from DATASUS with six membership functions. The average time given by the model was compared to actual data using lags of 0 to 4 days. This model was built using the Matlab v. 7.5 fuzzy toolbox. Its accuracy was assessed with the ROC curve. Hospitalizations with a mean time of 7.9 days (SD = 4.9) were recorded in 1119 cases. The data provided revealed a significant correlation with the actual data according to the lags of 0 to 4 days. The pollutant that showed the greatest accuracy was sulfur dioxide. This model can be used as the basis of a specialized system to assist the city health authority in assessing the risk of hospitalizations due to air pollutants.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)