Optimization of some fermentation conditions for bioethanol production from microalgae using response surface method

  • El-Mekkawi S
  • Abdo S
  • Samhan F
  • et al.
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Abstract

Algal biomass fermentation is one of the promising alternatives for bioethanol production. The bioethanol yield relies on fermentation conditions as the algal biomass amount, the yeast volume (% v/v), and the fermentation time. In this work, algal biomass harvested from a pilot-scale high rate algal pond (HRAP) was fermented anaerobically using immobilized Saccharomyces cerevisiae (ATCC 4126). The HRAP was constructed at the Zenin wastewater treatment plant (WTP), Giza, Egypt. A separate hydrolysis fermentation process (SHF) was applied for algal biomass. The effect of the algal biomass amount, the yeast volume (% v/v), and the time of fermentation as three independent variables were studied simultaneously and analyzed statistically using Design-Expert software V6.0.8. The harvested algal biomass from HRAP contains 45% carbohydrates and was dominated by Microcystis sp. The results revealed that optimum bioethanol yield 18.57 g/L is achieved by fermenting 98.7 g/L algae using 15.09% of the volume immobilized yeast for 43.6 h with a 95% confidence interval. Microalgae grown on wastewater are a promising source of bioethanol production. Maximizing the ethanol production is achieved by optimizing the fermentation parameters as algal biomass, fermentation time, and yeast volume percent. The simultaneous optimization of the parameters using a statistical program is an effective way to maximize the production and predict a model that describes the relationship between these parameters and their response. The prospective research is going to study the effect of these predicted parameters on continuous fermentation on the semi-pilot scale.

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El-Mekkawi, S. A., Abdo, S. M., Samhan, F. A., & Ali, G. H. (2019). Optimization of some fermentation conditions for bioethanol production from microalgae using response surface method. Bulletin of the National Research Centre, 43(1). https://doi.org/10.1186/s42269-019-0205-8

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