Optimization of CO2 biofixation rate by microalgae in a hybrid microfluidic differential carbonator using response surface methodology and desirability function

• Published in: Journal of CO2 utilization 2020-12, Vol.42, p.101291, Article 101291
• Main Authors: Abdulla Yusuf, Hayat, Hossain, S. M. Zakir, Khamis, Ahmed Ali, Radhi, Hassan Tariq, Jaafar, Ahmed Salman
• Format: Article
• Language: English
• Subjects: CO2biofixation; Microalgae; Microfluidic; Optimization; Response surface methodology
• ISSN: 2212-9820; 2212-9839
• DOI: 10.1016/j.jcou.2020.101291

•An in-house fabricated hybrid microfluidic-differential carbonator (μ-DC) was applied.•Microalgae (Chlorella vulgaris sp.) is a potential candidate for CO2 biofixation.•RSM with FC−CCD method is used to optimize conditions for maximizing CO2 biofixation.•Multiobjective optimization method was applied using desirability function.•A platform is developed that may facilitate research in algal bioengineering. The atmospheric CO2 concentration has been increasing meaningfully in recent years and is involved in climate change. The conventional approaches to reduce atmospheric CO2 need significant area of storage related with high costs of monitoring, operation, and maintenance. The microalgae based CO2 capture is an environmentally sustainable choice and the captured CO2 is not required to dispose further. However, culture conditions of microalgae are very important to maximize CO2 biofixation rate. Therefore, this study is aimed to investigate the factors of CO2 biofixation rate utilizing Chlorella vulgaris microalgae in an in-house fabricated microreactor (a hybrid microfluidic-differential carbonator, μ-DC). Initially, the microalgal capability of biofixation was investigated at different independent variables: volume % of CO2, light intensity, and inlet ratio of microalgae to media. The effects of these variables were analyzed using full factorial design (FFD) and found that light intensity had less impact compared to others, while both CO2 concentration and mciroalgae to media ratio were found to be significant factors. The response surface methodology (RSM) with face centered central composite design (FC−CCD) and desirability function based approaches were then used for both single- and multi-objective optimization. In multi-objective optimization, the optimized conditions were: 6% CO2 in air and 0.018 microalgae to media ratio, at which specific growth rate (SGR) of 0.766 d−1, cell counts of 24.36 × 103 and CO2 biofixation rate of 0.2416 gL−1d−1 with high overall desirability value (D > 0.7). The values of the coefficient of determination (R2) for the fitted models were found to be more than 80 %. The predictive models were evaluated further based on other performance measuring indicators or error terms (e.g., relative error, mean absolute error, root mean square error) and these values were found apparently to be low, indicating that the model predictions were closer to the experimental results. ANOVA analyses showed that all developed models were stati