Biofuels derived from microalgae may represent a key source for alternative energy vectors. Moreover, microalgae exhibit a great potential for sustainable production of a wide range of commodities and value-added products, including cosmetics, pharmaceuticals and nutraceuticals, which makes them suitable for biorefinery applications. Their high productivity and their ability to accumulate large amounts of lipids, along with their independence from arable land, put them in a competitive position with respect to traditional oil crops. However, the economical and energetic sustainability of large scale microalgae cultivation for biodiesel production are still debated. The most optimistic previsions are in fact based on gross estimates of productivity, derived by extrapolation of laboratory-scale data.
Therefore, the development of reliable mathematical models that are capable of quantitative predictions of the behaviour of large-scale outdoor microalgae culture is of paramount importance. Such models prove especially useful in identifying which parameters have the largest impact on productivity, thereby providing a means for enhancing the growth conditions through design and operational changes. Moreover, accurate forecasts of microalgal growth in the outdoor conditions can lead to a better understanding of the real potential of microalgae-based biofuels.
This Thesis aims of investigating the complex effect of light in the photosynthetic apparatus activity, and its effect on microalgae growth. The work presented in this Thesis follows two general lines. The first contribution has been to propose a general approach for model development. The proposed methodology guides the modelling effort in order to assure both an accurate representation of the calibration data, but most importantly also the identifiability of the model. The identifiability of a model, i.e. the possibility to estimate in accurate and reliable way its parametric set, is in fact, a necessary property for the model to be confidently used in process scale-up and optimization. The proposed methodology has been successfully applied to growth and fluorescence data of the sea water alga Nannochloropsis Salina.
A second contribution is concerned with Pulsed Amplitude Modulation (PAM) fluorometry. A dynamic model of chlorophyll fluorescence has been developed. The model integrates photoproduction, photoregulation and photoinhibition processes in a semi-mechanistic way. The model has been calibrated against fluorescence data of a sample of the microalga Nannochloropsis gaditana. The proposed fluorescence model is capable of quantitative prediction of the state of the photosynthetic apparatus of microalgae in terms of their open, closed and damaged reaction centres under variable light conditions. Two promising application of the fluorescence model have also been analysed: (i) the model has been used for the prediction of photosynthesis rate versus irradiance (PI)-response curves based on PAM fluorometry; and (ii) a model based experiment design (MBDoE) approach has been followed to define new information rich PAM protocols to further validate and refine the model structure
