Experimental and Model-Based Analysis to Optimize Microalgal Biomass Productivity in a Pilot-Scale Tubular Photobioreactor

Abstract

A dynamic coarse-grained model of microalgal growth considering light availability and temperature under discontinuous bioprocess operation was parameterized using experimental data from 15 batch cultivations of Nannochloropsis granulata in a pilot-scale tubular photobioreactor. The methodology applied consists of a consecutive two-step model parameter estimation using pooled, clustered and reorganized data to obtain initial estimates and multi-experiment fitting to obtain the final estimates, which are: maximum specific growth rate μ_max = 1.56 d^-1, specific photon half-saturation constant K _S,ph = 1.89 ${\text{mol}}_{\text{ph}}{{\text{g}}_{\text{X}}}^{-1}{\text{d}}^{-1}$ , specific photon maintenance coefficient m _ph = 0.346 ${\text{mol}}_{\text{ph}}{{\text{g}}_{\text{X}}}^{-1}{\text{d}}^{-1}$ and the cardinal temperatures T _min = 2.3°C, T _opt = 27.93°C and T _max = 32.59°C. Biomass productivity prediction proved highly accurate, expressed by the mean absolute percent error MAPE = 7.2%. Model-based numerical optimization of biomass productivity for repeated discontinuous operation with respect to the process parameters cultivation cycle time, inoculation biomass concentration and temperature yielded productivity gains of up to 35%. This optimization points to best performance under continuous operation. The approach successfully applied here to small pilot-scale confirms an earlier one to lab-scale, indicating its transferability to larger scale tubular photobioreactors.

Keywords: Nannochloropsis; biomass productivity optimization; coarse-grained modeling; light limitation; microalgal cultivation; temperature.