Optimization of Bioethanol Produced from Chlorella vulgaris

Abstract

Increasing global energy demand, together with the ecological impacts of fossil fuels, has renewed interest in biofuels. Microalgae such as Chlorella vulgaris have attracted significant interest because of their high carbohydrate content and rapid growth, as well as because their cultivation does not require arable land to the same extent as traditional crops. This positions C. vulgaris as a promising feedstock for third-generation bioethanol. In this study, dried C. vulgaris biomass was pretreated with α-amylase, followed by enzymatic hydrolysis to release fermentable sugars. A Box–Behnken design within response surface methodology was employed to investigate the effects of pH, inoculum size, and retention time on sugar release and ethanol production. The overall model was highly significant (F = 186.28, P < 0.001). Retention time exerted the greatest influence on hydrolysis and yield (F = 1551.39, P < 0.001), followed by pH (F = 48.50, P < 0.001); inoculum size had no significant effect (F = 2.49, P = 0.130). Quadratic terms contributed significantly to the model (F = 23.44, P < 0.001), whereas two-variable interactions were not significant (F = 1.28, P = 0.309). Peak yields exceeding 73% were obtained at pH 5.0–6.0 with a retention time of 72 h, and the validation trials closely matched the model predictions. ANOVA indicated a significant lack of fit (F = 26.64, P < 0.001), suggesting that the quadratic model did not adequately represent the response surface and that the actual relationship among the variables may be more complex than can be captured by a second-order equation. Despite this limitation, the close agreement between predicted and observed yields indicates that the model retained practical value for forecasting bioethanol production under the investigated fermentation conditions.