Modelagem matemática da cinética da decomposição aeróbia da matéria orgânica - Fleck, Leandro (2014)
The development of human activities generates high amounts of industrial effluent, which has a high impact on watercourses, mainly due to organic load constituents. Among the methods used to control water pollution, the method of mathematical modeling stands out, a simulation tool that allows the generation of future scenarios. This study proposes to generate a mathematical model of water quality that simulates the process of aerobic self-depuration of organic matter from watercourses. For this purpose, it was used a water bath coupled to a jar test, providing temperature control from 20 to 28 °C, and flow velocity from 0.29 to 0.87 m s-1, similarly to natural conditions. The trials were conducted using a synthetic effluent with an initial COD concentration of 50 mg L-1, based on a Central Composite Design (DCC), composed of seven trials. All trials lasted 15 days, with effluent samples collected daily for the analysis of Chemical Oxygen Demand (COD) and Dissolved Oxygen (OD). A mathematical equation was developed for each day of self-depuration. The final mathematical model gathers 15 equations of self-depuration. The significance of the equations was measured using the analysis of variance to 10%. To validate the proposed model, a self-depuration trial was carried out under the conditions of 26 °C and 0.38 m s-1 with an initial COD concentration of 30 mg L-1. The analysis of variance was performed for the proposed mathematical model as well as the analysis of normality and homoscedasticity for waste, with a significance level of 5%.There are indications that the temperature significantly had an influence in the kinetics of aerobic decomposition of organic matter in the first and from the sixth to the fifteenth day self-depuration. The flow velocity significantly influenced in the eighth and from the twelfth to the fifteenth day of self-depuration, and the interaction between the factors in the eighth and fifteenth day of self-depuration, with p-values lower than the significance level adopted. With a confidence interval of 90%, the equations representing the first and from the seventh to the fifteenth day of self-depuration are statistically significant, with coefficients of determination (R2) greater than 84%. The proposed model adequately described the experimental data obtained in the validation trial, presented p-value of 2.49 E-17, lower than the level of significance adopted, of 5%. Thus, the model proposed can be considered statistically significant, describing the total variation of responses, with a ratio of 99.46%. The proposed mathematical model described the process of self-depuration in watercourses within the temperature and flow velocity intervals in which it was generated