Dynamic model of microalgal production in tubular photobioreactors

Abstract

A dynamic model for microalgal culture is presented. The model takes into account the fluid-dynamic and mass transfer, in addition to biological phenomena, it being based on fundamental principles. The model has been calibrated and validated using data from a pilot-scale tubular photobioreactor but it can be extended to other designs. It can be used to determine, from experimental measurements, the values of characteristic parameters. The model also allows a simulation of the system’s dynamic behaviour in response to solar radiation, making it a useful tool for design and operation optimization of photobioreactors. Moreover, the model permits the identification of local pH gradients, dissolved oxygen and dissolved carbon dioxide; that can damage microalgae growth. In addition, the developed model can map the different characteristic time scales of phenomena inside microalgae cultures within tubular photobioreactors, meaning it is a valuable tool in the development of advanced control strategies for microalgae cultures.

Introduction

Microalgae have traditionally been cultivated in open photobioreactors such as “open raceways” due to the simplicity and low cost of this type of design. Unfortunately, these photobioreactors only allow minimal control of the operating conditions. In addition, the cultures can easily be contaminated. These systems are typically used on a commercial cultivation scale for both microalgae and cyanobacteria, such as Spirulina and Dunaliella, although production at low scale of other strains has also been reported (Richmond and Cheng-Wu, 2001, Jime´nez et al., 2003, Moreno et al., 2003, Moheimani and Borowitzka, 2007, Radmann et al., 2007). However, to produce high-value algal products from strains that cannot be maintained in open ponds, it is necessary to use closed photobioreactors such as tubular photobioreactors, which allow the control of operating conditions, thus cultures are reproducible and avoid contamination (Wang et al., 2012). Closed photobioreactors have been used in the cultivation of Porphyridium, Phaeodactylum, Nannochloropsis, Chlorella, Haematococcus and Tetraselmis, among others (Chini et al., 1999, Rebolloso et al., 1999, Acién et al., 2001, Ugwu et al., 2002, García-Malea et al., 2009). Moreover, tubular photobioreactors can satisfy the Good Manufacturing Practice (GMP) requirements for pharmaceutical products, thus making them useful for the production of biomass in food, feed and additives.

Whatever the photobioreactor used, the photosynthetic production of algae is always accompanied by the production of oxygen and uptake of carbon dioxide. This fact provokes alterations in the culture medium and the pH is constantly being modified. Oxygen levels above air saturation (0.225 molO₂ m⁻³ at 20 °C) can inhibit photosynthesis in many algal species, even if carbon dioxide concentration is maintained at elevated levels. Furthermore, elevated levels of oxygen combined with high levels of irradiance can lead to severe photo-oxidation (Rebolloso et al., 1999). Therefore, an important aspect of design and scale-up of tubular photobioreactors is establishing combinations of tube length, flow rate, and irradiance levels that do not allow oxygen to build-up to inhibitory levels (Camacho et al., 1999, Posten, 2009, Wang et al., 2012). Apart from this, microalgae cultures require CO₂ as the carbon source, at concentrations below boundary values, which would otherwise limit their growth. To maintain microalgae activity, CO₂ shortage should be avoided; for this, it has been suggested that partial pressure should be higher than 0.2 kPa (0.076 mol m⁻³) (Doucha et al., 2005). CO₂ is usually provided as the gas phase for both carbon supply and pH control. Thus, in tubular photobioreactors, pH control is performed by means of pure carbon dioxide injection; although flue gases can also be used. The supply of pure carbon dioxide can constitute up to 30% of the overall microalgae production cost (Acién et al., 2012). Moreover, the carbon losses in tubular photobioreactors can be higher than 50%, but can be reduced below 30% through proper design and operation of the photobioreactor (Acién et al., 1999, Camacho et al., 1999). To reduce this even further, it is necessary to design advanced control strategies that take into account the mixing and mass transfer phenomenon that occurs in the system (Garci´a et al., 2003). For this purpose, adequate dynamic models are required to design more advanced control strategies such as Model Predictive Control (MPC) that can greatly contribute to carbon loss avoidance. Simply by employing a black-box dynamic model, a classical MPC control strategy was designed allowing carbon loss reduction down from 20% to less than 5% (Berenguel et al., 2004). Thus, having a yet more detailed dynamic model, where physico-chemical phenomena are taken into account, will contribute to improving this issue even more, especially on a larger scale.

In this way, the design of tubular photobioreactors has been widely analysed, by considering the influence of fluid-dynamics and mass transfer on the growth of microalgae cultures, but most of the performed analysis were based on steady state equations, therefore they overlooked dynamic analysis or photobioreactor optimization (Acién et al., 1998, Camacho et al., 1999, Babcock et al., 2002, Ugwu et al., 2002, Hall et al., 2003, Posten, 2009, Wang et al., 2012). These studies noticed that not only oxygen accumulation was a problem but also carbon limitation and pH variations along the large tube length. This is an important issue because the carbon dioxide concentration at any point in the tube should not fall below a critical value to avoid limiting photosynthesis. For that reason, an understanding of how the performance is affected by design and operational factors is necessary e.g. the length and diameter of the tube, the flow rate, the dissolved oxygen and carbon dioxide concentration profiles, and the gas–liquid mass transfer. Note again that the availability of a dynamic model capturing these phenomena is extremely useful from a control standpoint. The control problem concerning microalgae biomass production in large-scale photobioreactors is composed of different control levels because, depending on the final use of the resulting biomass, different control objectives will have to be fulfilled during the production process. Therefore the existence of different objectives (productivity, economic issues, environmental, quality aspects, etc.) generate a hierarchical multi-scale control problem that can be addressed using different control techniques including non-linear multi-scale MPC, as well as event-based sampling and control approaches (Ramírez et al., 2012). Hence, it will be necessary to develop models, estimators and predictors, of the biomass concentration variables, the environmental variables and the rest of the associated process variables.

This paper presents the development of a dynamic model for microalgal culture in tubular photobioreactors, which predicts the main variables in these kinds of systems: dissolved oxygen and carbon dioxide concentration in the culture, photosynthesis rate and biomass concentration; in addition to oxygen and carbon dioxide molar fraction in the gas phase as well as carbon dioxide losses. The model is based on mass balances and transport phenomena, the thermodynamic relationship, and equations simulating the biological phenomena taking place inside the culture – thus it is based on fundamental principles instead of empirical equations. It takes into account the kinetics of the different phenomena occurring and, as a result, a complete dynamic simulation model is obtained. The model has been calibrated and validated using experimental results from a pilot scale tubular photobioreactor (3.0 m³). Given that the developed model is based on fundamental principles, it can be applied to other photobioreactor types, thus enhancing its applicability in the design and operation of microalgae-based processes.