Métodos numéricos e estatísticos aplicados à modelagem de um reator em batelada anaeróbio, no tratamento da drenagem ácida de mina

• Ano de defesa: 2016
• Autor(a) principal: Couto, Pâmela Talita Do
• Orientador(a): Valdiviesso, Gustavo Do Amaral
• Banca de defesa: Zaiat, Marcelo, Silva, Daniel Juliano Pamplona Da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Alfenas
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência e Engenharia Ambiental
• Departamento: Instituto de Ciência e Tecnologia
• País: Brasil
• Palavras-chave em Português: Minas – Drenagem; Modelagem matemática; Biorreatores; Estatística; Águas residuais – Purificação – Tratamento biológico
• Área do conhecimento CNPq: ENGENHARIA SANITARIA::TRATAMENTO DE AGUAS DE ABASTECIMENTO E RESIDUARIAS
• Link de acesso: https://repositorio.unifal-mg.edu.br/handle/123456789/870

The acid mine drainage (AMD) is one of the most serious environmental problems in mining industry, because it affects the quality of groundwater and surface water, soil and, consequently, human health. This wastewater is formed by the oxidation of sulphide minerals when exposed to weathering, such as water and oxygen, thus causing acid that with the rain is loaded leaching the elements present in the area. This wastewater is characterized by its low concentration of organic material and low pH, high conductivity, high concentrations of sulphate and heavy metals. Conventionally in industry, the AMD is treated by the process of neutralization using calcium oxides, but an alternative to this process is the anaerobic treatment of the AMD in anaerobic reactors containing sulfate reducing bacteria (SRB), which reduce sulfate to sulfide consuming ions (H+), consequently there is an increased of the pH effluent and this sulfide reacts with the metals present in solution, precipitating in the form of metal sulfides. However, in addition to know how to proceed the treatment of wastewater in anaerobic reactors it is important to realize the modeling of data to understand in detail all the process, since the model allows us to clearly see the influence of one variable on the others. So, the main objective of this study was to model the experimental data from anaerobic treatment of the AMD in a batch reactor in bench scale, previously operated. It was proposed the model of Malthus-Monod-Fick to determine which groups of microorganisms were active in the system and also to evaluate whether there was any effect of internal mass transfer in the granule over the overall order of the reaction. And for this specifically, it was explored statistical tools little used in reactor modeling area, such as Maximum Likelihood Method and the Chi-square test of hypothesis, looking for this way to obtain the maximum information through the developed model. The proposed model was implemented in programming language using C ++ with the Root library, used mainly to process large volumes of data and perform statistical analysis, based on the simple premise that evaluates the performance of only one bacterial group working in the system to the most complex premise that takes into account restriction of substrate diffusion inside the granule. It was concluded in this study that more than one bacterial group acted in the system, the SRB and the fermentative bacteria (this group includes all kinds of microorganisms that compete with SRB by electron donor, ethanol), that a long the time the microbial community became more selected because the reactor operating conditions chosed to favor SRB and due to this selection was the growth of a biofilm which acted as a restriction to intern mass transfer. Finally, it has been proven mathematically, with statistical validation model, this mass diffusion restriction over time was responsible for a overall behavior of the first order even using values Monod coefficients small (KS e KA), typical a zero-order kinetics, in which the substrate consumption rate is independent of the concentration of this same substrate.