Title : Simulation of photo-bioreactors for microalgae cultivation and comparison with experimental data
Microalgae represent renewable feedstocks for the production of a wide range of consumer goods such as biofuels, nutraceuticals, pharmaceuticals, bioplastics, functional food, lubricants for industrial applications, and feed for aquaculture systems. When compared to traditional crops, microalgae are characterized by higher photosynthetic efficiency and biomass productivity, as well as the capability to grow in non-arable/arid lands by exploiting wastewaters and CO2 as a source of nutrients.
Despite these aspects, when considering the large-scale applications, the existing microalgae technology is still not widespread. Moreover, the encouraging experimental results so far obtained at the laboratory scale have been hardly reproduced when trying to transpose the cultivation systems to the industrial production scale. Thus, the scale-up of the cultivation systems and the optimization of key operating parameters still represent a crucial goal to be fulfilled by the scientific community in order to permit the industrial exploitation of microalgae.
In this view, mathematical models capable to predict the photobioreactor behavior when changing the operating conditions are particularly useful. For this reason, several mathematical models of microalgae growth within different cultivation systems have been proposed in the literature in the last decade. However, validation of proposed models by comparison with experimental data was only seldom satisfactory. This not because of the literature models aren’t able to capture the experimental results but rather because the agreement between model results and experimental data is typically achieved by tuning a too high number of model parameters. Consequently, the literature models are usually characterized by too high degrees of freedom and thus fail when used to predict photobioreactor's behavior at different operating scales.
In the light of what above, there is a call for mathematical models validated by tuning the correct number of parameters in relation to the number of interpreted experiments so that to obtain tools with a real predictive character. Along these lines, some examples of mathematical models validated through comparison with experimental data by adjusting the values of a congruent number of model parameters are reported in this work. The discussed mathematical models will regard different experimental systems. In particular, the effects of different operating conditions on the growth of several strains belonging to Trebouxiophyceae class were investigated. In fact, members of this class were recognized for their biotechnological potential in various sectors. In detail, the models will pertain to the use of pure CO2 for the cultivation of Chlorella Vulgaris in semi-batch photobioreactors; the effect of different iron concentrations on the growth and lipid production by C. Vulgaris, the effect of nitrogen starvation on the lipid productivity by Chlorella sorokiniana in both batch and BIOCOIL photobioreactors; the effect of pH on the lipid productivity of the extremophile strain Coccomyxa melkonianii and finally the use of sea-wastewater mixtures for biofuels production through the strain Pseudochloris wilhelmii. Finally, some relevant examples of the application of a specific class of mathematical models based on population balance equations for the analysis of the evolution of the size structure of the microalgae cell population will be discussed.