A lumped parameter chemical–physical model for tubular photobioreactors

Multiscale modelling of mixotrophic algal growth in pilot-scale photobioreactors and its application to microalgal cultivation using wastewater

This multiscale model quantifies transport and reaction processes in mixotrophic microalgal growth at three characteristic length scales, namely, macro (photobioreactor), meso (algal cell), micro (organelles). The macro and the meso scale equations capture the temporal dynamics of the transport of CO₂, O₂, H⁺, organic carbon and nitrogen sources in the photobioreactor and the cell, respectively, while the micro scale quantifies the reaction rates of CO₂ fixation and photorespiration in the chloroplast, and mitochondrial respiration. Our model is validated using our experiments (R² = 0.96-0.99) on urea, CO₂ (0.04-5%), and acetic acid-mediated mixotrophic cultivation of Chlorella sorokiniana for 138 h using municipal wastewater (with and without media) at 11,000 lx light in 25-liter pilot-scale bubble-column photobioreactors, which produces 0.47-2.74 g/L biomass with 22.8-29.6% lipids, while reducing the COD, ammonium, phosphate, nickel, and H⁺ concentrations by 65-89%. The alga assimilates the ammonium and the phosphates present in wastewater into amino acids and ATP, respectively. Our simulations quantify the autotrophic and heterotrophic components of mixotrophic biomass yield to find the optimal inlet CO₂ concentration (of 3%) that synergizes autotrophic CO₂ sequestration with heterotrophic assimilation of organic carbon, thereby maximizing both autotrophic and heterotrophic growths. Super-optimal levels of inlet CO₂ acidify the stroma of the chloroplast, inhibit RuBisCo's enzymatic activity for CO₂ fixation in the Calvin Cycle, decelerate carrier-mediated uptake of acetate, and reduce biomass yields. Our harvesting process drastically reduces the algal harvesting time to less than 29 min. This multiscale reaction-transport model provides a useful tool for further scaling up this pilot-scale technology that synergistically integrates CO₂ sequestration and wastewater treatment with rapid microalgal cultivation (using municipal wastewater without autoclaving) and cost-effective harvesting.

Modelado y control de la producción de microalgas en fotobiorreactores industriales

<p>Este artículo presenta una visión general sobre el proceso de producción de microalgas desde un punto de vista de modelado y control de procesos. En primer lugar se exponen las ventajas y el potencial de este tipo de microorganismos, así como los distintos tipos de reactores que se suelen utilizar para su producción. Posteriormente, se analiza el comportamiento dinámico de este tipo de procesos, el cual es muy complejo y cambiante debido a variaciones en las condiciones ambientales tanto diarias como anuales, y se presentan los distintos balances que permiten describir la evolución de las principales variables del sistema. Se exponen distintos tipos de modelos a nivel biológico y a nivel estructural que han sido validados a escala industrial. Tras analizar su comportamiento dinámico, se motivan los distintos problemas de control existentes en este tipo de sistemas y se resume una amplia batería de estrategias de control que han sido evaluadas con éxito en fotobiorreactores industriales. Finalmente, se concluye el trabajo con un balance de los aspectos más importantes expuestos a lo largo del mismo.</p>

A new model to analyze the temperature effect on the microalgae performance at large scale raceway reactors

In this study a simplified temperature model for raceway reactors is developed, allowing to determine the temperature of the microalgae culture as a function of reactor design and environmental conditions. The model considers the major phenomena taking place in raceway reactors, especially heat absorption by radiation and heat losses by evaporation among others. The characteristic parameters of the model have been calibrated using genetic algorithms, next being validated with a long set of more than 50 days covering different weather conditions. It is worth to highlight the use of the developed model as a tool to analyze the influence of the temperature on the performance of microalgae cultures at large scale. As example, the annual variation of the performance of up to five different microalgae strains has been determined by computing the temperature index, thus the normalized value of performance of whatever microalgae at the real temperature with respect to that achievable at optimal temperature can be established. Results confirm that only strains tolerant to wide ranges of temperature can be efficiently produced all the year around in large scale outdoor raceway reactors without additional temperature control systems.

Bioprocess strategies for enhancing the outdoor production of Nannochloropsis gaditana: an evaluation of the effects of pH on culture performance in tubular photobioreactors

A priority of the industrial applications of microalgae is the reduction of production costs while maximizing algae biomass productivity. The purpose of this study was to carry out a comprehensive evaluation of the effects of pH control on the production of Nannochloropsis gaditana in tubular photobioreactors under external conditions while considering the environmental, biological, and operational parameters of the process. Experiments were carried out in 3.0 m³ tubular photobioreactors under outdoor conditions. The pH values evaluated were 6.0, 7.0, 8.0, 9.0, and 10.0, which were controlled by injecting pure CO₂ on-demand. The results have shown that the ideal pH for microalgal growth was 8.0, with higher values of biomass productivity (P_b) (0.16 g L^-1 d^-1), and CO₂ use efficiency ([Formula: see text]) (74.6% w w^-1); [Formula: see text]_/biomass value obtained at this pH (2.42 [Formula: see text] g_biomass^-1) was close to the theoretical value, indicating an adequate CO₂ supply. At this pH, the system was more stable and required a lower number of CO₂ injections than the other treatments. At pH 6.0, there was a decrease in the P_b and [Formula: see text]; cultures at pH 10.0 exhibited a lower P_b and photosynthetic efficiency as well. These results imply that controlling the pH at an optimum value allows higher CO₂ conversions in biomass to be achieved and contributes to the reduction in costs of the microalgae production process.

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).

Noble metal, oxide and chalcogenide-based nanomaterials from scalable phototrophic culture systems

Phototrophic cell or tissue cultures can produce nanostructured noble metals, oxides and chalcogenides at ambient temperatures and pressures in an aqueous environment and without the need for potentially toxic solvents or the generation of dangerous waste products. These "green" synthesized nanobiomaterials can be used to fabricate biosensors and bio-reporting tools, theranostic vehicles, medical imaging agents, as well as tissue engineering scaffolds and biomaterials. While successful at the lab and experimental scales, significant barriers still inhibit the development of higher capacity processes. While scalability issues in traditional algal bioprocess engineering are well known, such as the controlled delivery of photons and gas-exchange, the large-scale algal synthesis of nanomaterials introduces additional parameters to be understood, i.e., nanoparticle (NP) formation kinetics and mechanisms, biological transport of metal cations and the effect of environmental conditions on the final form of the NPs. Only after a clear understanding of the kinetics and mechanisms can the strain selection, photobioreactor type, medium pH and ionic strength, mean light intensity and other relevant parameters be specified for an optimal bioprocess. To this end, this mini-review will examine the current best practices and understanding of these phenomena to establish a path forward for this technology.

Dimensionless equations to describe microalgal growth in a planar cultivation system

OBJECTIVES

To develop dimensionless equations to describe microalgal growth in planar photobioreactor or raceway pond systems that are generalized to all phototrophic species and reactor length scales.

RESULTS

Expressions for biomass growth and mean light intensity within a nutrient replete, well-mixed, phototrophic cell culture in a planar cultivation system were developed in terms of dimensionless variables for biomass, time and light intensity, plus two new dimensionless parameters. The first dimensionless parameter represents a species-specific physiological characteristic based on maximum growth rate and cell maintenance, while the second represents the light input. Optimal biomass productivities and photosynthetic conversion efficiencies are easily determined from the dimensionless expressions and system-specific performances can be easily determined by back substituting with the relevant cell culture and photobioreactor parameters.

CONCLUSION

The dimensionless expressions are useful for understanding and determining the relevant bioprocess parameters in a generalized form applicable to all strains and reactor length scales.