A model integrating fluid dynamics in photosynthesis and photoinhibition processes

Experimental and theoretical investigations of rotating algae biofilm reactors (RABRs): Areal productivity, nutrient recovery, and energy efficiency

Microalgae biofilms have been demonstrated to recover nutrients from wastewater and serve as biomass feedstock for bioproducts. However, there is a need to develop a platform to quantitatively describe microalgae biofilm production, which can provide guidance and insights for improving biomass areal productivity and nutrient uptake efficiency. This paper proposes a unified experimental and theoretical framework to investigate algae biofilm growth on a rotating algae biofilm reactor (RABR). Experimental laboratory setups are used to conduct controlled experiments on testing environmental and operational factors for RABRs. We propose a differential-integral equation-based mathematical model for microalgae biofilm cultivation guided by laboratory experimental findings. The predictive mathematical model development is coordinated with laboratory experiments of biofilm areal productivity associated with ammonia and inorganic phosphorus uptake by RABRs. The unified experimental and theoretical tool is used to investigate the effects of RABR rotating velocity, duty cycle (DC), and light intensity on algae biofilm growth, areal productivity, nutrient uptake efficiency, and energy efficiency in wastewater treatment. Our framework indicates that maintaining a reasonable light intensity range improves biomass areal productivity and nutrient uptake efficiency. Our framework also indicates that faster RABR rotation benefits biomass areal productivity. However, maximizing the nutrient uptake efficiency requires a reasonably low RABR rotating speed. Energy efficiency is strongly correlated with RABR rotating speed and DC.

Irradiance penetration distribution and flashing light frequency simultaneously affected with microalgal cell absorption and CO2 bubble scattering in a raceway pond

In order to investigate light penetration and flashing light frequency for microalgal cell-CO₂ bubble culture system in a raceway pond, user-defined function for CO₂ mass transfer and bubble scattering models coupled with discrete ordinates radiation model were adopted to clarify simultaneous effects of microalgal cell absorption and CO₂ bubble scattering. Light intensity along the microalgal suspension depth attenuated more rapidly with increased biomass concentration, decreased bubble generation diameter, increased CO₂ gas content and incident light intensity. Ratio of light zone decreased from 81.13 % to 20.00 % when biomass concentration increased from 0 to 0.4 g/L because of light absorption and shading effects of microalgae. When bubble generation diameter increased from 0.1 to 1.6 mm, ratio of light zone increased from 37.95 % to 42.64 %, while microalgal flashing light cycle first decreased to a valley of 1.81 s at 0.8 mm and then increased. Local light intensity in the upper layers was more enhanced due to lots of CO₂ bubbles gathering and reflecting more light with decreased bubble diameter and increased gas content. Light attenuated more rapidly in microalgal suspension with decreased bubble generation diameter and increased CO₂ gas content because of increased bubble diffraction coefficient and contact area. When initial CO₂ volume fraction increased from 0.02 to 0.2, flashing light frequency of microalgal cells decreased from 0.55 to 0.29 Hz and light zone time ratio φ decreased from 36.90 % to 18.40 %. At a biomass concentration of 0.1 g/L and a bubble flow rate of 0.1 m/s, the maximum light penetration and microalgal growth rate was achieved when bubble diameter, incident light intensity and gas content were optimally at 0.8 mm, 200 W/m² and 0.02, respectively. This work provides data support and theoretical guidance for photobioreactor design and optimization of light energy utilization.

Theoretical growth rate of microalgae under high/low-flashing light

Dynamic light regimes strongly impact microalgal photosynthesis efficiency. Finding the optimal way to supply light is then a tricky problem, especially when the growth rate is inhibited by overexposition to light and, at the same time, there is a lack of light in the deepest part of the culture. In this paper, we use the Han model to study the theoretical microalgal growth rate by applying periodically two different light intensities. Two approaches are considered depending on the period of the light pattern. For a large light period, we demonstrate that the average photosynthetic rate can be improved under some conditions. Moreover, we can also enhance the growth rate at steady state as given by the PI-curve. Although, these conditions change through the depth of a bioreactor. This theoretical improvement in the range of 10-15% is due to a recovery of photoinhibited cells during the high irradiance phase. We give a minimal value of the duty cycle for which the optimal irradiance is perceived by the algae culture under flashing light regime.

Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review

Computational Fluid Dynamics (CFD) have been frequently applied to model the growth conditions in photobioreactors, which are affected in a complex way by multiple, interacting physical processes. We review common photobioreactor types and discuss the processes occurring therein as well as how these processes have been considered in previous CFD models. The analysis reveals that CFD models of photobioreactors do often not consider state-of-the-art modeling approaches. As a comprehensive photobioreactor model consists of several sub-models, we review the most relevant models for the simulation of fluid flows, light propagation, heat and mass transfer and growth kinetics as well as state-of-the-art models for turbulence and interphase forces, revealing their strength and deficiencies. In addition, we review the population balance equation, breakage and coalescence models and discretization methods since the predicted bubble size distribution critically depends on them. This comprehensive overview of the available models provides a unique toolbox for generating CFD models of photobioreactors. Directions future research should take are also discussed, mainly consisting of an extensive experimental validation of the single models for specific photobioreactor geometries, as well as more complete and sophisticated integrated models by virtue of the constant increase of the computational capacity.

Recent advances in computational fluid dynamics (CFD) modelling of photobioreactors: Design and applications

The development of photobioreactor is important for sustainable production of renewable fuels, wastewater treatment and CO₂ fixation. For the design and scale-up of a photobioreactor, CFD can be used as an indispensable tool. The present study reviews the recent status of computational flow modelling of various types of photobioreactors, involving fluid dynamics, light transport, and algal growth kinetics. An integrated modelling approach of hydrodynamics, light intensity, mass transfer, and biokinetics in photobioreactor is discussed further. Also, this reviews intensified system to improve the mixing, and light intensity of photobioreactors. Finally, the prospects and challenges of CFD modelling in photobioreactors are discussed. Multi-scale modelling approach and development of low-cost efficient computational framework are the areas to be considered for modelling of photobioreactor in near future. In addition, it is necessary to use process intensification techniques for photobioreactors for improving their hydrodynamics, mixing and mass transfer performances, and algal growth productivity.

A Detailed Hydrodynamic Study of the Split-Plate Airlift Reactor by Using Non-Invasive Gamma-Ray Techniques

This study focused on detailed investigations of selected local hydrodynamics in split airlift reactor by using an unconventional measurements facility: computed tomography (CT) and radioactive particle tracking (RPT). The local distribution in a cross-sectional manner with its radial’s profiles for gas holdup, liquid velocity flow field, shear stresses, and turbulent kinetic energy were studied under various gas velocity 1, 2 and 3 cm/s with various six axial level z = 12, 20, 40, 60, 90 and 112 cm. The distribution in gas–liquid phases in the whole split reactor column, the riser and downcomer sides, including their behavior at the top and bottom sections of the split plate was also described. The outcomes of this study displayed an exemplary gas–liquid phases dispersion approximately in all reactor’s zones and had large magnitude over the ring of the sparger as well as upper the split plate. Furthermore, the outcomes pointed out that the distribution of this flow may significantly impacts the performance of the split reactor, which may have essential influence on its performance particularly for microorganisms culturing applications. These outcomes are dependable as benchmark information to validate computational fluid dynamics (CFD) simulations and other models.

How Do Operational and Design Parameters Effect Biomass Productivity in a Flat-Panel Photo-Bioreactor? A Computational Analysis

Optimal production of microalgae in photo-bioreactors (PBRs) largely depends on the amount of light intensity received by individual algal cells, which is affected by several operational and design factors. A key question is: which process parameters have the highest potential for the optimization of biomass productivity? This can be analyzed by simulating the complex interplay of PBR design, hydrodynamics, dynamic light exposure, and growth of algal cells. A workflow was established comprising the simulation of hydrodynamics in a flat-panel PBR using computational fluid dynamics, calculation of light irradiation inside the PBR, tracing the light exposure of individual cells over time, and calculation the algal growth and biomass productivity based on this light exposure. Different PBR designs leading to different flow profiles were compared, and operational parameters such as air inlet flowrate, microalgal concentration, and incident light intensity were varied to investigate their effect on PBR productivity. The design of internal structures and lighting had a significant effect on biomass productivity, whereas air inlet flowrate had a minimal effect. Microalgal concentration and incident light intensity controlled the amount of light intensity inside the PBR, thereby significantly affecting the overall productivity. For detailed quantitative insight into these dependencies, better parameterization of algal growth models is required.

Model-Based Prediction of Perceived Light Flashing in Recirculated Inclined Wavy-Bottomed Photobioreactors

Microalgae biomass production rate in short light-path photobioreactors potentially can be improved by mixing-induced flashing light regimes. A cascade photobioreactor features a thin liquid layer flowing down a sloping, wavy-bottomed surface where liquid flow exhibits peculiar local recirculation hydrodynamics, potentially conducive to an ordered flashing light regime. This article presents a model-based analysis of the frequency distribution of perceived irradiance in said wavy-bottomed photobioreactor. The model combines a Lagrangian description of the motion of individual cells, in turn derived from the hydrodynamic parameters of the photobioreactor extracted from an experimentally validated Computational Fluid Dynamic model, with a simplified description of the irradiance field across the culture thickness, down to the spectral analysis of perceived irradiance. The main finding of the work is that the wavy bottomed photobioreactor provides a ‘robust’ spectral excitation to the circulating microalgae up to 3 Hz frequency, while in flat panels and bubble columns excitation decays evenly at a 24 db/octave rate. This analysis paves the way to improving the light flashing performance of the wavy-bottomed photobioreactor with respect to geometry (cavity size and installation inclination) and operation (flow rate).

Cultivating Microalgae in Desert Conditions: Evaluation of the Effect of Light-Temperature Summer Conditions on the Growth and Metabolism of Nannochloropsis QU130

Temperature and light are two of the most crucial factors for microalgae production. Variations in these factors alter their growth kinetics, macromolecular composition and physiological properties, including cell membrane permeability and fluidity. The variations define the adaptation mechanisms adopted by the microalgae to withstand changes in these environmental factors. In the Qatar desert the temperature varies widely, typically between 10° and 45 °C There are also wide variations in light intensity, with values of over 1500 μmolhν.m−2s−1 in summer. A study of the effects of these thermal and light fluctuations is therefore essential for large-scale outdoor production systems, especially during the summer when temperature and light fluctuations are at their highest. The aim of this work is to study the impact of temperature and light intensity variations as encountered in summer period on the Nannochloropsis QU130 strain, which was selected for its suitability for outdoor cultivation in the harsh conditions of the Qatar desert. It was carried out using lab-scale photobioreactors enabling simulation of both constant and dynamic temperature and light regimes. Biomass productivity, cell morphology and biochemical compositions were examined first in constant conditions, then in typical outdoor cultivation conditions to elucidate the adjustments in cell function in respect of fluctuations. The dynamic light and temperature were shown to have interactive effects. The application of temperature cycles under constant light led to a 13.6% increase in biomass productivity, while a 45% decrease was observed under light and temperature regimes due to the combined stress. In all cases, the results proved that N. sp. QU130 has a high level of adaptation to the wide fluctuations in light and temperature stress. This was shown through its ability to easily change its physiology (cell size) and metabolic process in response to different cultivation conditions.

Synergising biomass growth kinetics and transport mechanisms to simulate light/dark cycle effects on photo-production systems

Light attenuation is a primary challenge limiting the upscaling of photobioreactors for sustainable bio-production. One key to this challenge, is to model and optimise the light/dark cycles so that cells within the dark region can be frequently transferred to the light region for photosynthesis. Therefore, this study proposes the first mechanistic model to integrate the light/dark cycle effects into biomass growth kinetics. This model was initially constructed through theoretical derivation based on the intracellular reaction kinetics, and was subsequently modified by embedding a new parameter, effective light coefficient, to account for the effects of culture mixing. To generate in silico process data, a new multiscale reactive transport modelling strategy was developed to couple fluid dynamics with biomass growth kinetics and light transmission. By comparing against previous experimental and computational studies, the multiscale model shows to be of high accuracy. Based on its simulation result, an original correlation was proposed to link effective light coefficient with photobioreactor gas inflow rate; this has not been done before. The impact of this study is that by using the proposed mechanistic model and correlation, we can easily control and optimise photobioreactor gas inflow rates to alleviate light attenuation and maintain a high biomass growth rate.

Multiscale numerical workflow describing microalgae motion and light pattern incidence towards population growth in a photobioreactor

In this article, a numerical workflow describing the microalgal growth inside of a photobioreactor is proposed. CFD is used to compute reactor internal hydrodynamics taking into account marine impeller rotation and sparged bubbles motion. Lagrangian approach is used to track microalgae motion inside of the culture vessel. The illumination across the reactor is obtained using the classical Beer-Lambert's law. The combination of light field and cell motion allows to reconstruct the light history of each microalgae. These histories are then supplied to Han's model which predicts individual growth rate and experienced photodamages. Once computed, several thousands of trajectories are agglomerated at the population level yielding the photobioreactor performances. After having ensured properties convergence, this procedure is applied to a large range of optical density (0 to 4.0), i.e. cell concentration, and incident light intensities (0 to 2000 μmolPhoton/m2/s). From this exploration, it is possible to determine the photobioreactor response surfaces in terms of growth rate and photodamages. These are latter used to propose an optimal lighting strategy for biomass production - reducing photobioreactor operation time by 16% compared to classical two-step procedure - and assist light induced stress with the aim of triggering secondary metabolites production.

BIO_ALGAE 2: improved model of microalgae and bacteria consortia for wastewater treatment

A new set up of the integral mechanistic BIO_ALGAE model that describes the complex interactions in mixed algal-bacterial systems was developed to overcome some restrictions of the model. BIO_ALGAE 2 includes new sub-models that take into account the variation of microalgae and bacteria performance as a function of culture conditions prevailing in microalgae cultures (pH, temperature, dissolved oxygen) over daily and seasonal cycles and the implementation of on-demand dioxide carbon injection for pH control. Moreover, another aim of this work was to study a correlation between the mass transfer coefficient and the hydrodynamics of reactor. The model was calibrated using real data from a laboratory reactor fed with real wastewater. Moreover, the model was used to simulate daily variations of different components in the pond (dissolved oxygen, pH, and CO₂ injection) and to predict microalgae (X_ALG) and bacteria (X_H) proportions and to estimate daily biomass production (C_b). The effect of CO₂ injection and the influence of wastewater composition on treatment performance were investigated through practical study cases. X_ALG decreased by 38%, and X_H increased by 35% with respect to the system under pH control while microalgae and bacteria proportions are completely different as a function of influent wastewater composition. Model simulations have indicated that C_b production (~ 100 gTSS m^-3 day^-1 for manure and centrate) resulted lower than C_b production obtained using primary influent wastewater (155 gTSS m^-3 day^-1).

Laboratory-scale photobiotechnology-current trends and future perspectives

Phototrophic bioprocesses are a promising puzzle piece in future bioeconomy concepts but yet mostly fail for economic reasons. Besides other aspects, this is mainly attributed to the omnipresent issue of optimal light supply impeding scale-up and -down of phototrophic processes according to classic established concepts. This MiniReview examines two current trends in photobiotechnology, namely microscale cultivation and modeling and simulation. Microphotobioreactors are a valuable and promising trend with microfluidic chips and microtiter plates as predominant design concepts. Providing idealized conditions, chip systems are preferably to be used for acquiring physiological data of microalgae while microtiter plate systems are more appropriate for process parameter and medium screenings. However, these systems are far from series technology and significant improvements especially regarding flexible light supply remain crucial. Whereas microscale is less addressed by modeling and simulation so far, benchtop photobioreactor design and operation have successfully been studied using such tools. This particularly includes quantitative model-assisted understanding of mixing, mass transfer, light dispersion and particle tracing as well as their relevance for microalgal performance. The ultimate goal will be to combine physiological data from microphotobioreactors with hybrid models to integrate metabolism and reactor simulation in order to facilitate knowledge-based scale transfer of phototrophic bioprocesses.

Advanced integration of fluid dynamics and photosynthetic reaction kinetics for microalgae culture systems

Background

Photosynthetic microalgae have been in the spotlight of biotechnological production (biofuels, lipids, etc), however, current barriers in mass cultivation of microalgae are limiting its successful industrialization. Therefore, a mathematical model integrating both the biological and hydrodynamical parts of the cultivation process may improve our understanding of relevant phenomena, leading to further optimization of the microalgae cultivation.

Results

We introduce a unified multidisciplinary simulation tool for microalgae culture systems, particularly the photobioreactors. Our approach describes changes of cell growth determined by dynamics of heterogeneous environmental conditions such as irradiation and mixing of the culture. Presented framework consists of (i) a simplified model of microalgae growth in a culture system (the advection-diffusion-reaction system within a phenomenological model of photosynthesis and photoinhibition), (ii) the fluid dynamics (Navier-Stokes equations), and (iii) the irradiance field description (Beer-Lambert law). To validate the method, a simple case study leading to hydrodynamically induced fluctuating light conditions was chosen. The integration of computational fluid dynamics (ANSYS Fluent) revealed the inner property of the system, the flashing light enhancement phenomenon, known from experiments.

Conclusion

Our physically accurate model of microalgae culture naturally exhibits features of real system, can be applied to any geometry of microalgae mass cultivation and thus is suitable for biotechnological applications.

Multiphysics simulation of algal growth in an airlift photobioreactor: Effects of fluid mixing and shear stress

A multiphysics model has been developed to predict the effects of fluid mixing and shear stress on microalgal growth in an airlift photobioreactor. The model integrates multiphase flow dynamics, radiation transport, shear stress, and algal growth kinetics using an Eulerian approach. The model is first validated by comparing its predictions with experimental data, and then the radiation transport and algal growth kinetics submodels are added to predict biomass accumulation under different flow conditions. The simulations correctly predict biomass growth curves for a wide range of superficial gas flow rates and demonstrate that biomass productivity increases with increased gas flow rate due to better light delivery to microorganisms. However, at the higher gas flow rates considered, shear stress on microorganisms inhibits biomass growth. Lastly, it is shown that the Eulerian approach used here provides a less cumbersome computational approach and provides better predictions than the circulation time and Lagrangian approaches.

Microalgae-bacteria models evolution: From microalgae steady-state to integrated microalgae-bacteria wastewater treatment models - A comparative review

The search for environmentally neutral alternative fuels had revived the interest for microalgae-bacteria wastewater treatment systems. The potential achieving of bioproducts from microalgae biomass has also greatly contributed. The reactions that occur in these systems are complex, and the degree of scientific knowledge is still scarce compared to that of conventional bacteria wastewater treatments. Mathematical models offer a great opportunity to study the simultaneous effect of the multiple factors affecting microalgae and bacteria, thus allowing for the prediction of final biomass production, and contributing to the system design optimization in terms of operation and control. During the last decades, numerous models describing microalgae growth have been proposed. However, a lower number of integral models considering microalgae as well as bacteria is available. In this paper, the evolution of microalgae models from simple steady-state models (usually dependent on one factor) to more complex dynamic models (with two or more factors) has been revised. A summary of integrated microalgae-bacteria models has been reviewed, outlining their main features and presenting their processes and value parameters. Eventually, a critical discussion on integrated models has been put forward.

A penalty on photosynthetic growth in fluctuating light

Fluctuating light is the norm for photosynthetic organisms, with a wide range of frequencies (0.00001 to 10 Hz) owing to diurnal cycles, cloud cover, canopy shifting and mixing; with broad implications for climate change, agriculture and bioproduct production. Photosynthetic growth in fluctuating light is generally considered to improve with increasing fluctuation frequency. Here we demonstrate that the regulation of photosynthesis imposes a penalty on growth in fluctuating light for frequencies in the range of 0.01 to 0.1 Hz (organisms studied: Synechococcus elongatus and Chlamydomonas reinhardtii). We provide a comprehensive sweep of frequencies and duty cycles. In addition, we develop a 2^nd order model that identifies the source of the penalty to be the regulation of the Calvin cycle – present at all frequencies but compensated at high frequencies by slow kinetics of RuBisCO.

Comprehensive computational model for combining fluid hydrodynamics, light transport and biomass growth in a Taylor vortex algal photobioreactor: Lagrangian approach

A comprehensive quantitative model incorporating the effects of fluid flow patterns, light distribution, and algal growth kinetics on biomass growth rate is developed in order to predict the performance of a Taylor vortex algal photobioreactor for culturing Chlorella vulgaris. A commonly used Lagrangian strategy for coupling the various factors influencing algal growth was employed whereby results from computational fluid dynamics and radiation transport simulations were used to compute numerous microorganism light exposure histories, and this information in turn was used to estimate the global biomass specific growth rate. The simulations provide good quantitative agreement with experimental data and correctly predict the trend in reactor performance as a key reactor operating parameter is varied (inner cylinder rotation speed). However, biomass growth curves are consistently over-predicted and potential causes for these over-predictions and drawbacks of the Lagrangian approach are addressed.

High-Fidelity Modelling Methodology of Light-Limited Photosynthetic Production in Microalgae

Reliable quantitative description of light-limited growth in microalgae is key to improving the design and operation of industrial production systems. This article shows how the capability to predict photosynthetic processes can benefit from a synergy between mathematical modelling and lab-scale experiments using systematic design of experiment techniques. A model of chlorophyll fluorescence developed by the authors [Nikolaou et al., J Biotechnol 194:91-99, 2015] is used as starting point, whereby the representation of non-photochemical-quenching (NPQ) process is refined for biological consistency. This model spans multiple time scales ranging from milliseconds to hours, thus calling for a combination of various experimental techniques in order to arrive at a sufficiently rich data set and determine statistically meaningful estimates for the model parameters. The methodology is demonstrated for the microalga Nannochloropsis gaditana by combining pulse amplitude modulation (PAM) fluorescence, photosynthesis rate and antenna size measurements. The results show that the calibrated model is capable of accurate quantitative predictions under a wide range of transient light conditions. Moreover, this work provides an experimental validation of the link between fluorescence and photosynthesis-irradiance (PI) curves which had been theoricized.

Simulating cyanobacterial phenotypes by integrating flux balance analysis, kinetics, and a light distribution function

BACKGROUND

Genome-scale models (GSMs) are widely used to predict cyanobacterial phenotypes in photobioreactors (PBRs). However, stoichiometric GSMs mainly focus on fluxome that result in maximal yields. Cyanobacterial metabolism is controlled by both intracellular enzymes and photobioreactor conditions. To connect both intracellular and extracellular information and achieve a better understanding of PBRs productivities, this study integrates a genome-scale metabolic model of Synechocystis 6803 with growth kinetics, cell movements, and a light distribution function. The hybrid platform not only maps flux dynamics in cells of sub-populations but also predicts overall production titer and rate in PBRs.

RESULTS

Analysis of the integrated GSM demonstrates several results. First, cyanobacteria are capable of reaching high biomass concentration (>20 g/L in 21 days) in PBRs without light and CO2 mass transfer limitations. Second, fluxome in a single cyanobacterium may show stochastic changes due to random cell movements in PBRs. Third, insufficient light due to cell self-shading can activate the oxidative pentose phosphate pathway in subpopulation cells. Fourth, the model indicates that the removal of glycogen synthesis pathway may not improve cyanobacterial bio-production in large-size PBRs, because glycogen can support cell growth in the dark zones. Based on experimental data, the integrated GSM estimates that Synechocystis 6803 in shake flask conditions has a photosynthesis efficiency of ~2.7 %.

CONCLUSIONS

The multiple-scale integrated GSM, which examines both intracellular and extracellular domains, can be used to predict production yield/rate/titer in large-size PBRs. More importantly, genetic engineering strategies predicted by a traditional GSM may work well only in optimal growth conditions. In contrast, the integrated GSM may reveal mutant physiologies in diverse bioreactor conditions, leading to the design of robust strains with high chances of success in industrial settings.

Photobioreactors for microalgal cultures: A Lagrangian model coupling hydrodynamics and kinetics

Closed photobioreactors have to be optimized in terms of light utilization and overall photosynthesis rate. A simple model coupling the hydrodynamics and the photosynthesis kinetics has been proposed to analyze the photosynthesis dynamics due to the continuous shuttle of microalgae between dark and lighted zones of the photobioreactor. Microalgal motion has been described according to a stochastic Lagrangian approach adopting the turbulence model suitable for the photobioreactor configuration (single vs. two-phase flows). Effects of light path, biomass concentration, turbulence level and irradiance have been reported in terms of overall photosynthesis rate. Different irradiation strategies (internal, lateral and rounding) and several photobioreactor configurations (flat, tubular, bubble column, airlift) have been investigated. Photobioreactor configurations and the operating conditions to maximize the photosynthesis rate have been pointed out. Results confirmed and explained the common experimental observation that high concentrated cultures are not photoinhibited at high irradiance level.

An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth

Despite the high potential as feedstock for the production of fuels and chemicals, the industrial cultivation of microalgae still exhibits many issues. Yield in microalgae cultivation systems is limited by the solar energy that can be harvested. The availability of reliable models representing key phenomena affecting algae growth may help designing and optimizing effective production systems at an industrial level. In this work the complex influence of different light regimes on seawater alga Nannochloropsis salina growth is represented by first principles models. Experimental data such as in vivo fluorescence measurements are employed to develop the model. The proposed model allows description of all growth curves and fluorescence data in a reliable way. The model structure is assessed and modified in order to guarantee the model identifiability and the estimation of its parametric set in a robust and reliable way.