Analysis of green algal growth via dynamic model simulation and process optimization

• Published in: Biotechnology and bioengineering Vol. 112; no. 10; pp. 2025 - 2039
• Main Authors: Zhang, Dongda, Chanona, Ehecatl Antonio Del-Rio, Vassiliadis, Vassilios S, Tamburic, Bojan
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01-10-2015; Wiley Subscription Services, Inc
• Subjects: Algae; Biodiesel fuels; Biomass; Bioreactors - microbiology; Biotechnology; Carbon Dioxide - metabolism; Chlamydomonas reinhardtii; Chlamydomonas reinhardtii - growth & development; Computer simulation; Culture Media - chemistry; Dynamic models; dynamic simulation; Heterotrophic Processes; Light; Mathematical models; microalgae; Models, Biological; Models, Theoretical; Optimization; photobioreactor scale-up; Phototrophic Processes; process optimisation; Productivity; Simulation; process optimisation; microalgae; photobioreactor scale-up; dynamic simulation; Chlamydomonas reinhardtii
• ISSN: 0006-3592; 1097-0290
• DOI: 10.1002/bit.25610

ABSTRACT
Chlamydomonas reinhardtii is a green microalga with the potential to generate sustainable biofuels for the future. Process simulation models are required to predict the impact of laboratory‐scale growth experiments on future scaled‐up system operation. Two dynamic models were constructed to simulate C. reinhardtii photo‐autotrophic and photo‐mixotrophic growth. A novel parameter estimation methodology was applied to determine the values of key parameters in both models, which were then verified using experimental results. The photo‐mixotrophic model was used to accurately predict C. reinhardtii growth under different light intensities and in different photobioreactor configurations. The optimal dissolved CO2 concentration for C. reinhardtii photo‐autotrophic growth was determined to be 0.0643 g·L−1, and the optimal light intensity for algal growth was 47 W·m−2. Sensitivity analysis revealed that the primary factor limiting C. reinhardtii growth was its intrinsic cell decay rate rather than light attenuation, regardless of the growth mode. The photo‐mixotrophic growth model was also applied to predict the maximum biomass concentration at different flat‐plate photobioreactors scales. A double‐exposure‐surface photobioreactor with a lower light intensity (less than 50 W·m−2) was the best configuration for scaled‐up C. reinhardtii cultivation. Three different short‐term (30‐day) C. reinhardtii photo‐mixotrophic cultivation processes were simulated and optimised. The maximum biomass productivity was 0.053 g·L−1·hr−1, achieved under continuous photobioreactor operation. The continuous stirred‐tank reactor was the best operating mode, as it provides both the highest biomass productivity and lowest electricity cost of pump operation. Biotechnol. Bioeng. 2015;112: 2025–2039. © 2015 Wiley Periodicals, Inc.
Two dynamic models were constructed to simulate green algal (Chlamydomonas reinhardtii) photo‐autotrophic and photo‐mixotrophic growth; a novel dynamic parameter estimation methodology was applied and verified using experimental results. The models were used to predict algal growth in scaled‐up flat‐plate photobioreactors with different configurations. Process optimization was used to determine that the continuous stirred tank photobioreactor results in highest algal biomass productivity.