Multi-scale modeling of light-limited growth in microalgae production systems
Creators: name: Nikolaou, Andreas
Publisher: name: Imperial College London
Year: 2015

description: Microalgae are often seen as important candidates for biofuel production. Claimed advantages over conventional oil crops include their fast growth rate and high lipid content as well as an independence from arable land and fresh water. Commercial viability of microalgae-derived biofuel is currently hindered by the high nutrient requirement, the trade-off between growth and lipid accumulation, sub-optimal growth conditions in large-scale culturing systems and difficulties related to the lipid extraction process. This thesis is concerned with the effect that the light conditions have on microalgae growth. The main contributions are related to the development of multi-scale mathematical models that span several orders of magnitude in both time and space and are suitable for predictions of photosynthetic production of microalgae in laboratory as well as industrial scale systems. Advanced mathematical techniques have been used along with state-of-the-art experimental methods in order to accurately represent microalgae cultures. The first three chapters focus on the development and identification of laboratory-scale models, while the last chapter develops a multi-physics modeling framework, where laboratory-scale predictions are extrapolated to industrial scale. More specifically, Chapter 3 presents a model that couples nutrient- and light-limitation, simultaneously accounting for photoacclimation and photoinhibition. This model is able to predict photosynthesis-irradiance (PI) response curves by accounting for different photoacclimation strategies. A self-developed Monte Carlo method has been used to estimate the exact confidence regions of the model parameters. The results show that even though a statistically meaningful coupling between photoacclimation and photoinhibition can be established, the exclusive use of PI curves is insufficient for the estimation of the parameters that describe the fast time-scale photosynthetic processes. Moreover, it is concluded that a quasi steady-state assumption in PI curve modeling may lead to confusing interpretation of the experimental observations. Chapter 4 attempts to resolve the aforementioned issues with the development of a model of chlorophyll fluorescence that couples photosynthetic production, photoinhibition and photoregulation to predict the light-limited photosynthetic operation of microalgae. This model achieves a significant improvement in the utilization of experimental information that is suitable for model identification and enables the quantitative characterization of the state of the reaction centers of photosystem II (PSII) from fluorescence fluxes, giving thereby a detailed description of the photoinhibition dynamics. Moreover, a theoretical connection between fluorescence and PI experimentation is established. In Chapter 5, model-based design of experiments, along with a more advanced description of photoregulation, practically demonstrate the capabilities of the fluorescence model in simultaneously predicting fluorescence fluxes and photosynthesis rate measurements. Additionally, the followed approach leads to the accurate estimation of the parameters representing the fast time-scale photosynthetic processes. Overall, the fluorescence model successfully combines fluorescence, photosynthesis rate and antenna size measurements, enabling thereby the accurate estimation of a large number of parameters. The prediction accuracy of the photosynthesis rate especially, suggests that fluorescence can be used to screen the photosynthetic performance of different microalgae strains as well as predict the photosynthetic productivity of culturing systems. In Chapter 6 the fluorescence model is extended to account for photoacclimation and is integrated with physics models that characterize hydrodynamics and light attenuation in large-scale cultivation systems. More specifically, the hydrodynamic conditions of a raceway pond are characterized in terms of individual cell trajectories using computational fluid dynamics (CFD). Large-scale productivity predictions are then obtained by averaging over all the trajectories. Analysis of the outcomes shows that both mixing and light attenuation affect the photosynthetic productivity in raceway ponds, while photoacclimation and photoinhibition have a significant impact too. The thesis concludes with Chapter 7 where significant contributions and future directions of research are discussed. The focus is on microalgae growth modeling extensions, possible applications of the developed fluorescence models in industrial aquaculture and model-based optimization of light-limited culturing systems.