Abstract
Despite being well established, a major limitation remains in ethanol fermentation processes: the presence of ethanol inhibits yeast activity, affecting the cell growth rate and, consequently, the ethanol production rate. For this reason, low ethanol concentrations of around 8–9% v/v are reached at the end of the fermentation, hence requiring the consumption of a significant amount of energy for recovery of the fermentation product, while generating large amounts of vinasse. This situation requires the use of large fermentation tanks in order to achieve satisfactory ethanol production. Additionally, due to the large amount of heat generated by the fermentation processes, the temperature control of industrial fermentation tanks is a great challenge in tropical regions such as Brazil. The goal of the present study was to analyze the influence of operating variables on the performance of ethanol stripping at bench and pilot scales, using carbon dioxide as the carrier gas, and to propose a model describing the changes in ethanol mass and solution temperature during the stripping process. Bench scale experiments were conducted using a 5-L bubble column filled with 10% v/v hydroalcoholic solution, and the pilot scale experiments were performed using a 95-L column filled with industrial fermented wine without yeast. A factorial design was applied to identify the most important operating variables for the following stripping performance parameters: entrainment factor, concentration factor, and temperature reduction factor. The results showed that both temperature and entrainment factor were positively influenced by initial solution temperature and specific CO2 flow rate, and negatively affected by height-to-diameter ratio. The temperature of the carbon dioxide did not affect either of these performance parameters. The simulation results revealed that the stripping model accurately described the decreases in ethanol mass and solution temperature during the stripping operation, with good agreement between the experimental and simulated data, and errors less than 5% in most cases.
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