Note:

The public nuisance and health concerns caused by odours from livestock facilities are among the key issues that affect neighbouring communities and the growth of the livestock industry across Canada. A setback distance is the common regulatory practice to reduce odour impact on the neighbouring areas. The air dispersion modeling method may be a more accurate tool for establishing setback distances since it considers site-specific airborne emissions, such as odour and gases from the animal production site as well as weather conditions and then estimates a concentration of the pollutant (odour, ammonia, etc.). Although various dispersion models have been studied to predict odour concentration from agricultural sources, limited field data exist to evaluate their applicability in agricultural odour dispersion. Thus, the purpose of this project was to evaluate the selected commercial air dispersion models with field plume measurements from swine operations. <p>Firstly, this thesis describes a sensitivity analysis of how the climatic parameters affect model simulations for four selected air dispersion models, ISCST3, AUSPLUME, CALPUFF, and CALPUFF. Under the steady state weather condition, mixing height had no effect on the livestock odour dispersion, while atmospheric stability, wind speed and wind direction had great effect on the livestock odour dispersion. Ambient temperature had a moderate effect compared with other parameters. Under variable weather conditions, the predicted odour concentrations were much lower than the results under steady state weather conditions. <p>A series of comparisons between model predictions of the same four models and field odour measurements were conducted. When using the livestock odour plume measurement data from University of Manitoba, three equations were used to convert the model predicted odour concentration to field measured odour intensity. The equations did not predict odour intensity very well. No model showed obvious better performance than the others. Scaling factors did not improve the results considerably. When using the odour plume measurement data from University of Minnesota, INPUFF2 performed better than CALPUFF. Scaling factors did improve the modeled results. When using the odour plume measurement data from University of Saskatchewan, INPUFF2 also performed better than CALPUFF. Scaling factors were still useful for the results improvements.<p>Finally, because CALPUFF is the US EPA preferred model and predicted the highest values under variable weather conditions in the sensitivity study, we used it to simulate odour plumes on selected three swine sites using hourly weather data from 1993 to 2002 in Yorkton, Saskatchewan. The maximum predicted distance were 2.9 km for 1 OU, which was lower than the recommended maximum setback distance of 3.2 km. <p>It is recommended that the variable weather conditions be used in the setback distance determination. CALPUFF is the preferred model and INPUFF2 is another option for field odour plume simulation, however scaling factors are needed to bring the model predictions close to the field measured results. Because the models evaluated were not developed for odour dispersion simulation, a model that can accurately predict livestock odour dispersion should be developed to take into account of the difference between odour and gas and wind direction shifts within the simulation time interval.

The public nuisance and health concerns caused by odours from livestock facilities are among the key issues that affect neighbouring communities and the growth of the livestock industry across Canada. A setback distance is the common regulatory practice to reduce odour impact on the neighbouring areas. The air dispersion modeling method may be a more accurate tool for establishing setback distances since it considers site-specific airborne emissions, such as odour and gases from the animal production site as well as weather conditions and then estimates a concentration of the pollutant (odour, ammonia, etc.). Although various dispersion models have been studied to predict odour concentration from agricultural sources, limited field data exist to evaluate their applicability in agricultural odour dispersion. Thus, the purpose of this project was to evaluate the selected commercial air dispersion models with field plume measurements from swine operations. <p>Firstly, this thesis describes a sensitivity analysis of how the climatic parameters affect model simulations for four selected air dispersion models, ISCST3, AUSPLUME, CALPUFF, and CALPUFF. Under the steady state weather condition, mixing height had no effect on the livestock odour dispersion, while atmospheric stability, wind speed and wind direction had great effect on the livestock odour dispersion. Ambient temperature had a moderate effect compared with other parameters. Under variable weather conditions, the predicted odour concentrations were much lower than the results under steady state weather conditions. <p>A series of comparisons between model predictions of the same four models and field odour measurements were conducted. When using the livestock odour plume measurement data from University of Manitoba, three equations were used to convert the model predicted odour concentration to field measured odour intensity. The equations did not predict odour intensity very well. No model showed obvious better performance than the others. Scaling factors did not improve the results considerably. When using the odour plume measurement data from University of Minnesota, INPUFF2 performed better than CALPUFF. Scaling factors did improve the modeled results. When using the odour plume measurement data from University of Saskatchewan, INPUFF2 also performed better than CALPUFF. Scaling factors were still useful for the results improvements.<p>Finally, because CALPUFF is the US EPA preferred model and predicted the highest values under variable weather conditions in the sensitivity study, we used it to simulate odour plumes on selected three swine sites using hourly weather data from 1993 to 2002 in Yorkton, Saskatchewan. The maximum predicted distance were 2.9 km for 1 OU, which was lower than the recommended maximum setback distance of 3.2 km. <p>It is recommended that the variable weather conditions be used in the setback distance determination. CALPUFF is the preferred model and INPUFF2 is another option for field odour plume simulation, however scaling factors are needed to bring the model predictions close to the field measured results. Because the models evaluated were not developed for odour dispersion simulation, a model that can accurately predict livestock odour dispersion should be developed to take into account of the difference between odour and gas and wind direction shifts within the simulation time interval.

Impact of odour emissions from livestock operation sites on the air quality of neighboring areas has raised public concerns. A practical means to solve this problem is to set adequate setback distance. Air dispersion modeling was proved to be a promising method in predicting proper odour setback distance. Although a lot of air dispersion models have been used to predict odour concentrations downwind agricultural odour sources, not so much information regarding the capability of these models in odour dispersion modeling simulation could be found because very limited field odour data are available to be applied to evaluate the modeling result. A main purpose of this project was evaluating AERMOD and CALPUFF air dispersion models for odour dispersion simulation using field odour data.<p> Before evaluating and calibrating AERMOD and CALPUFF, sensitivity analysis of these two models to five major climatic parameters, i.e., mixing height, ambient temperature, stability class, wind speed, and wind direction, was conducted under both steady-state and variable meteorological conditions. It was found under steady-state weather condition, stability class and wind speed had great impact on the odour dispersion; while, ambient temperature and wind direction had limited impact on it; and mixing height had no impact on the odour dispersion at all. Under variable weather condition, maximum odour travel distance with odour concentrations of 1, 2, 5 and 10 OU/m3 were examined using annual hourly meteorological data of year 2003 of the simulated area and the simulation result showed odour traveled longer distance under the prevailing wind direction.<p> Evaluation outcomes of these two models using field odour data from University of Minnesota and University of Alberta showed capability of these two models in odour dispersion simulation was close in terms of agreement of modeled and field measured odour occurrences. Using Minnesota odour plume data, the difference of overall agreement of all field odour measurements and model predictions was 3.6% applying conversion equation from University of Minnesota and 3.1% applying conversion equation from University of Alberta between two models. However, if field odour intensity 0 was not considered in Minnesota measured odour data, the difference of overall agreement of all field odour measurements and model predictions was 3.1% applying conversion equation from University of Minnesota and 1.6% applying conversion equation from University of Alberta between two models. Using Alberta odour plume data, the difference of overall agreement of all field odour measurements and model predictions was 0.7% applying conversion equation from University of Alberta and 1.2% applying conversion equation from University of Minnesota between two models. However, if field odour intensity 0 was not considered in Alberta measured odour data, the difference of overall agreement of all field odour measurements and model predictions was 0.4% applying conversion equation from University of Alberta and 0.7% applying conversion equation from University of Minnesota between two models. Application of scaling factors can improve agreement of modeled and measured odour intensities (including all field odour measurements and field odour measurements without intensity 0) when conversion equation from University of Minnesota was used.<p> Both models were used in determining odour setback distance based on their close performance in odour dispersion simulation. Application of two models in predicting odour setback distance using warm season (from May to October) historical annul hourly meteorological data (from 1999 to 2002) for a swine farm in Saskatchewan showed some differences existed between models predicted and Prairie Provinces odour control guidelines recommended setbacks. Accurately measured field odour data and development of an air dispersion model for agricultural odour dispersion simulation purpose as well as acceptable odour criteria could be considered in the future studies.

Impact of odour emissions from livestock operation sites on the air quality of neighboring areas has raised public concerns. A practical means to solve this problem is to set adequate setback distance. Air dispersion modeling was proved to be a promising method in predicting proper odour setback distance. Although a lot of air dispersion models have been used to predict odour concentrations downwind agricultural odour sources, not so much information regarding the capability of these models in odour dispersion modeling simulation could be found because very limited field odour data are available to be applied to evaluate the modeling result. A main purpose of this project was evaluating AERMOD and CALPUFF air dispersion models for odour dispersion simulation using field odour data.<p> Before evaluating and calibrating AERMOD and CALPUFF, sensitivity analysis of these two models to five major climatic parameters, i.e., mixing height, ambient temperature, stability class, wind speed, and wind direction, was conducted under both steady-state and variable meteorological conditions. It was found under steady-state weather condition, stability class and wind speed had great impact on the odour dispersion; while, ambient temperature and wind direction had limited impact on it; and mixing height had no impact on the odour dispersion at all. Under variable weather condition, maximum odour travel distance with odour concentrations of 1, 2, 5 and 10 OU/m3 were examined using annual hourly meteorological data of year 2003 of the simulated area and the simulation result showed odour traveled longer distance under the prevailing wind direction.<p> Evaluation outcomes of these two models using field odour data from University of Minnesota and University of Alberta showed capability of these two models in odour dispersion simulation was close in terms of agreement of modeled and field measured odour occurrences. Using Minnesota odour plume data, the difference of overall agreement of all field odour measurements and model predictions was 3.6% applying conversion equation from University of Minnesota and 3.1% applying conversion equation from University of Alberta between two models. However, if field odour intensity 0 was not considered in Minnesota measured odour data, the difference of overall agreement of all field odour measurements and model predictions was 3.1% applying conversion equation from University of Minnesota and 1.6% applying conversion equation from University of Alberta between two models. Using Alberta odour plume data, the difference of overall agreement of all field odour measurements and model predictions was 0.7% applying conversion equation from University of Alberta and 1.2% applying conversion equation from University of Minnesota between two models. However, if field odour intensity 0 was not considered in Alberta measured odour data, the difference of overall agreement of all field odour measurements and model predictions was 0.4% applying conversion equation from University of Alberta and 0.7% applying conversion equation from University of Minnesota between two models. Application of scaling factors can improve agreement of modeled and measured odour intensities (including all field odour measurements and field odour measurements without intensity 0) when conversion equation from University of Minnesota was used.<p> Both models were used in determining odour setback distance based on their close performance in odour dispersion simulation. Application of two models in predicting odour setback distance using warm season (from May to October) historical annul hourly meteorological data (from 1999 to 2002) for a swine farm in Saskatchewan showed some differences existed between models predicted and Prairie Provinces odour control guidelines recommended setbacks. Accurately measured field odour data and development of an air dispersion model for agricultural odour dispersion simulation purpose as well as acceptable odour criteria could be considered in the future studies.

No description available.

A realização deste estudo teve por objetivo caracterizar o funcionamento de uma célula pneumática de flotação e comparar o seu desempenho às diferentes tecnologias [células mecânicas e colunas de flotação] já instaladas e em operação nos circuitos industriais da Samarco Mineração - no Circuito de Grossos e no Circuito de Finos. Utilizou-se, para a realização dos ensaios e/ou das análises, uma célula mecânica laboratorial [modelo Wemco®], uma célula pneumática piloto [modelo MBE®] e um medidor de tamanho de bolhas e de velocidade superficial do ar [modelo APBS®]. Neste estudo, utilizaram-se amostras coletadas na alimentação dos dois referidos circuitos industriais de flotação - executando-se, posteriormente, etapas complementares de caracterização mineralógica, levantamento de dados e análise estatística dos resultados. Como conclusões, em maior relevância, citam-se: a) Para as células pneumáticas, maiores aplicabilidades industriais foram identificadas para o modelo Pneuflot®, processando carvão e em operações na China. Foram mapeadas células de 4,1 a 5,0 m de diâmetro processando volumes de polpa superiores a 1.000 m3/h; b) Em análise de influência das variáveis, foi identificado que o percentual de sólidos da alimentação e a velocidade da polpa no distribuidor possuem elevada influência sobre as variáveis respostas do processo de flotação; c) Em célula pneumática, em escala piloto e em regime batch, observou-se que: para a flotabilidade de sílica, a constante cinética (k) foi fortemente influenciada pela granulometria, sendo de 0,719 min-1 para a amostra CG e de 0,237 min-1 para a amostra CF; d) Utilizando-se de modelos cinéticos, dimensionaram-se circuitos de células pneumáticas. Conforme especificações atualmente praticadas e sem otimizações, seriam necessárias 8 células para o Circuito de Grossos e 11 células para o Circuito de Finos. e) Em comparativos entre células mecânicas e colunas de flotação [em escala industrial], constataram-se maiores eficiências de circuitos contendo células pneumáticas [dimensionados a partir de resultados em escala piloto]; e f) Em análise de dispersão do ar, realizaram-se medições e/ou identificação das correlações existentes entre as variáveis velocidade superficial do ar (Jg), diâmetro médio de bolhas ou diâmetro de Sauter (d32), hold-up do ar (Eg) e fluxo superficial de área de bolhas (Sb). / This study aimed to characterize the operation of pneumatic cells and compare their performance to other different technologies [mechanical cells and columns] already installed and in operation in the industrial circuits of the company Samarco Mineração - Circuit of Coarse materials and Circuit of Fine materials. It was used, for the tests and/or assays, a laboratorial mechanical cell [Wemco® model], a pilot pneumatic cell [MBE® model] and a bubbles size and superficial air velocity measurer [APBS® model]. For these, feed samples of both industrial flotation circuits were taken - followed by complementary steps of mineralogical characterization, data collection and statistical analyzes of results. As conclusions, in higher relevance, have been noted: a) For the pneumatic cells, larger industrial applications were identified for the Pneuflot® model, processing coal and in operation in China. Cells measuring from 4,1 to 5,0 m of diameter were listed processing volumes higher than 1.000 m3/h; b) In an analysis of the influence of variables, it was identified that the percentage of solids in the feed and the velocity of slurry in the distributor have high influence on the process responses of flotation; c) In a pneumatic cell, on a pilot scale and under batch regime, for the floatability of silica, the kinetic constant (k) was strongly influenced by the size of particles, of 0,719 min-1 for the sample CG [from Coarse Circuit] and of 0,237 min-1 for the sample CF [from Fine Circuit]; d) Using kinetic models, circuits of pneumatic cells have been designed. According to the current specifications and without optimizations, 8 cells would be necessary for the Coarse Circuit and 11 cells for the Fine Circuit; e) In comparisons between mechanical cells and columns [on an industrial scale], greater efficiencies were noted for circuits containing pneumatic cells [designed from results on a pilot scale]; and f) In an analysis of the air dispersion, measurements and/or identification of existing correlations between the variables superficial air velocity (Jg), bubble size diameter (d32), air hold-up (Eg) and superficial area bubble flux (Sb) have been done.

Submitted by Liliane Ferreira (ljuvencia30@gmail.com) on 2018-04-23T11:10:57Z No. of bitstreams: 2 Dissertação - Gabriel Cristóbal Valenzuela Saavedra - 2018.pdf: 4929181 bytes, checksum: 32d6c5535f93ba6a8920d6f67beb26e8 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-04-23T11:57:24Z (GMT) No. of bitstreams: 2 Dissertação - Gabriel Cristóbal Valenzuela Saavedra - 2018.pdf: 4929181 bytes, checksum: 32d6c5535f93ba6a8920d6f67beb26e8 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-04-23T11:57:24Z (GMT). No. of bitstreams: 2 Dissertação - Gabriel Cristóbal Valenzuela Saavedra - 2018.pdf: 4929181 bytes, checksum: 32d6c5535f93ba6a8920d6f67beb26e8 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-03-28 / Outro / El presente estudio tiene como finalidad encontrar un camino metodológico para modelar la dispersión de contaminantes atmosféricos provenientes de fuentes de emisión fija, a través de materiales baratos y simples. El camino insto de la revisión teórica de los principales conceptos de la contaminación atmosférica y la calidad del aire, así conocer cuales factores determinan áreas vulnerables a la contaminación atmosférica. Se usó una fuente de emisión fija de una industria alimentaria para mostrar un análisis de lo que sería un estudio de impacto ambiental de las emisiones producto de la operación normal de la fábrica para el año 2012, sin la intención de evaluar, si no, para mostrar cómo se aplica el modelo en un caso práctico. De esta forma, colocar en disposición una metodología que pueda ser usada en estudios que ayuden a la toma de decisión para la planificación en la introducción de nuevas fuentes de emisión o la alteración de las antiguas. Como resultado, se consiguen imágenes donde es fácilmente reconocible el área de susceptibilidad de las emisiones provenientes de la fuente fija, las que son interpretadas para aclarar que podría pasar frente a los diversos escenarios posibles. / O presente estudo teve como objetivo encontrar o caminho metodológico para modelar a dispersão de poluentes atmosféricos provenientes de fontes de emissão fixa, através de materiais baratos e simples. O percurso instou da revisão teórica e dos principais conceptos da poluição e qualidade do ar para saber quais são os fatores que determinam áreas vulneráveis à poluição atmosférica. Usou-se uma fonte de emissão atmosférica fixa de uma indústria alimentar para mostrar um analises do que seria um estudo de impacto das emissões produto da operação normal da fábrica para o ano 2012, sem a intenção de avaliar a indústria, mas para mostrar como se aplica o modelo de dispersão em casos práticos. Dessa forma, disponibilizar uma metodologia que possa ser usada em estudos que ajudem a tomar decisões de planejamento para a colocação de novas fontes de emissão ou a alteração das antigas. Como resultado, se consegue imagens onde é facilmente reconhecível a área de susceptibilidade das emissões provenientes da fonte fixa, as quais são interpretadas para esclarecer o que poderia acontecer frente aos diversos cenários possíveis.

Orientador: Edson Tomaz / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-11T08:10:14Z (GMT). No. of bitstreams: 1 Lyra_DiogenesGanghisPimentelde_D.pdf: 6815705 bytes, checksum: b2d5b551ed1a7b66a23067f33e565249 (MD5) Previous issue date: 2008 / Resumo: A poluição atmosférica tem sido um dos principais temas de interesse no meio científico, tendo em vista sua implicação na qualidade da saúde humana, dos ecossistemas e dos bens construídos, identificando-se com uma dimensão fundamental na busca do desenvolvimento sustentável. A avaliação da qualidade do ar numa região depende da obtenção de dados confiáveis que descrevam as condições ambientais existentes e que sejam representativos da região em estudo. Os parâmetros a serem monitorados permitirão determinar o grau de controle necessário e, portanto, os respectivos recursos.desta forma encarar-se a poluição atmosférica como um problema de gestão pública e do bem estar comum. O presente trabalho apresenta o projeto para instalação de uma Rede de Monitoramento da Qualidade do Ar para a Região Metropolitana de Salvador - RMS, detalhando os parâmetros a serem monitorados, a localização dos pontos de monitoramento, num total de 25 estações, a especificação preliminar dos equipamentos e outros recursos e necessidades para o monitoramento dos poluentes convencionais, assim como dos parâmetros meteorológicos. A implantação desta Rede de Monitoramento da Qualidade do Ar - RMA ratificará a abertura e o interesse da gestão municipal atual com relação ao conhecimento da qualidade do ar a nível regional, demonstrando sua preocupação com relação à exposição da população à poluição ambiental urbana. Palavras-chave: Poluição do ar, estudo de dispersão e emissões atmosféricas / Abstract: The atmospheric pollution has been one of the main points of interest in the scientific community, considering its implication on the human health quality, the ecosystems and buildings, identifying itself to the main dimension in the search for the sustainable development. The air quality evaluation in a region depends on the availability of reliable data describing the existing ambient conditions, being representative. The parameters to be monitored will allow the assessment of the degree of the necessary control e, therefore, the respective resources. All of this makes us face the atmospheric pollution as a problem of public administration and welfare. The present work presents then, the project of an Air Quality Monitoring Network to be installed in the RMS, detailing the parameter to be monitored, the location of the monitoring points, totalizing 25 stations, the preliminary specification of the equipment and other resources and necessities for the conventional pollutants monitoring, as well as the meteorological parameters. The implementation of this Air Monitoring Network will reassure the municipal management openness and concerns regarded the air quality knowledge at a regional level, outlining its concerns regarded the population exposure to the ambient urban pollution. Key word: air pollution, air dispersion and emission atmospheric / Doutorado / Desenvolvimento de Processos Químicos / Doutor em Engenharia Química

A realização deste estudo teve por objetivo caracterizar o funcionamento de uma célula pneumática de flotação e comparar o seu desempenho às diferentes tecnologias [células mecânicas e colunas de flotação] já instaladas e em operação nos circuitos industriais da Samarco Mineração - no Circuito de Grossos e no Circuito de Finos. Utilizou-se, para a realização dos ensaios e/ou das análises, uma célula mecânica laboratorial [modelo Wemco®], uma célula pneumática piloto [modelo MBE®] e um medidor de tamanho de bolhas e de velocidade superficial do ar [modelo APBS®]. Neste estudo, utilizaram-se amostras coletadas na alimentação dos dois referidos circuitos industriais de flotação - executando-se, posteriormente, etapas complementares de caracterização mineralógica, levantamento de dados e análise estatística dos resultados. Como conclusões, em maior relevância, citam-se: a) Para as células pneumáticas, maiores aplicabilidades industriais foram identificadas para o modelo Pneuflot®, processando carvão e em operações na China. Foram mapeadas células de 4,1 a 5,0 m de diâmetro processando volumes de polpa superiores a 1.000 m3/h; b) Em análise de influência das variáveis, foi identificado que o percentual de sólidos da alimentação e a velocidade da polpa no distribuidor possuem elevada influência sobre as variáveis respostas do processo de flotação; c) Em célula pneumática, em escala piloto e em regime batch, observou-se que: para a flotabilidade de sílica, a constante cinética (k) foi fortemente influenciada pela granulometria, sendo de 0,719 min-1 para a amostra CG e de 0,237 min-1 para a amostra CF; d) Utilizando-se de modelos cinéticos, dimensionaram-se circuitos de células pneumáticas. Conforme especificações atualmente praticadas e sem otimizações, seriam necessárias 8 células para o Circuito de Grossos e 11 células para o Circuito de Finos. e) Em comparativos entre células mecânicas e colunas de flotação [em escala industrial], constataram-se maiores eficiências de circuitos contendo células pneumáticas [dimensionados a partir de resultados em escala piloto]; e f) Em análise de dispersão do ar, realizaram-se medições e/ou identificação das correlações existentes entre as variáveis velocidade superficial do ar (Jg), diâmetro médio de bolhas ou diâmetro de Sauter (d32), hold-up do ar (Eg) e fluxo superficial de área de bolhas (Sb). / This study aimed to characterize the operation of pneumatic cells and compare their performance to other different technologies [mechanical cells and columns] already installed and in operation in the industrial circuits of the company Samarco Mineração - Circuit of Coarse materials and Circuit of Fine materials. It was used, for the tests and/or assays, a laboratorial mechanical cell [Wemco® model], a pilot pneumatic cell [MBE® model] and a bubbles size and superficial air velocity measurer [APBS® model]. For these, feed samples of both industrial flotation circuits were taken - followed by complementary steps of mineralogical characterization, data collection and statistical analyzes of results. As conclusions, in higher relevance, have been noted: a) For the pneumatic cells, larger industrial applications were identified for the Pneuflot® model, processing coal and in operation in China. Cells measuring from 4,1 to 5,0 m of diameter were listed processing volumes higher than 1.000 m3/h; b) In an analysis of the influence of variables, it was identified that the percentage of solids in the feed and the velocity of slurry in the distributor have high influence on the process responses of flotation; c) In a pneumatic cell, on a pilot scale and under batch regime, for the floatability of silica, the kinetic constant (k) was strongly influenced by the size of particles, of 0,719 min-1 for the sample CG [from Coarse Circuit] and of 0,237 min-1 for the sample CF [from Fine Circuit]; d) Using kinetic models, circuits of pneumatic cells have been designed. According to the current specifications and without optimizations, 8 cells would be necessary for the Coarse Circuit and 11 cells for the Fine Circuit; e) In comparisons between mechanical cells and columns [on an industrial scale], greater efficiencies were noted for circuits containing pneumatic cells [designed from results on a pilot scale]; and f) In an analysis of the air dispersion, measurements and/or identification of existing correlations between the variables superficial air velocity (Jg), bubble size diameter (d32), air hold-up (Eg) and superficial area bubble flux (Sb) have been done.