Enhancing Arthrospira platensis productivity by optimizing mixing rates in a self-cooling flat plate photobioreactor

Abstract

Arthrospira platensis has been a dietary staple for decades. While raceway ponds are commonly used for mass cultivation, closed photobioreactors (PBRs) offer higher productivity and reduced contamination risks. Mixing rate is a critical factor influencing microalgal growth and productivity. This study examines the impact of air injection flow rates (0.17–0.27 vvm), corresponding to superficial gas velocities of 0.00315–0.0050 m·s⁻¹, on the growth, productivity, and effective quantum yield (f'q/f'm) of A. platensis in a 140 L self-cooling flat plate PBR with an infrared-reflective thin-film coating that enables passive temperature control and reduces energy demand for cooling.

The optimal gas velocity of 0.00389 m·s⁻¹ yielded an average productivity of 0.126 g·L⁻¹·d⁻¹. Beyond this velocity, at 0.00426 m·s⁻¹, there was neither significant increase in productivity, nor a notable decrease in f'q/f'm. However, at higher gas velocities of 0.00463 m·s⁻¹ and 0.0050 m·s⁻¹, f'q/f'm decreased significantly, by up to 48.6 %, indicating adverse effects on the microalgal cells. Lower velocities (<0.00389 m·s⁻¹) did not affect f'q/f'm but resulted in inadequate mixing, reducing biomass productivity by 16.4 % and 23.8 % for 0.00352 and 0.00315 m·s⁻¹.

A validated growth model accurately predicted A. platensis growth (R² = 94.5 % for biomass, 81.2 % for temperature). Moreover, Experimental data from Perth, Australia, during spring and winter aligned closely with model predictions. This integration of experimental data and predictive modelling highlights the importance of precise mixing rate optimization in maximizing microalgal productivity and demonstrates the reliability of such models for advancing large-scale algal cultivation.