Uncoupling solid and hydraulic retention time in photobioreactors for microalgae mass production: A model-based analysis

Methods for the separation of hydraulic retention time and solids retention time in the application of photosynthetic microorganisms in photobioreactors: a review

Photosynthetic microorganisms have a wide range of biotechnical applications, through the application of their versatile metabolisms. However, their use in industry has been extremely limited to date, partially because of the additional complexities associated with their cultivation in comparison to other organisms. Strategies and developments in photobioreactors (PBRs) designed for their culture and applications are needed to drive the field forward. One particular area which bears examination is the use of strategies to separate solid- and hydraulic-residence times (SRT and HRT), to facilitate flow-through systems and continuous processing. The aim of this review is to discuss the various types of PBRs and methods which are currently demonstrated in the literature and industry, with a focus on the separation of HRT and SRT. The use of an efficient method of biomass retention in a PBR may be advantageous as it unlocks the option for continuous operation, which may improve efficiency, and improve economic feasibility of large-scale implementation of photosynthetic biocatalysts, especially where biomass is not the primary product. Due to the underexplored nature of the separation of HRT and SRT in reactors using photosynthetic microorganisms, limited literature is available regarding their performance, efficiencies, and potential issues. This review first introduces an overview into photosynthetic microorganisms cultivated and commonly exploited for use in biotechnological applications, with reference to bioreactor considerations specific to each organism. Following this, the existing technologies used for the separation of HRT and SRT in PBRs are explored. The respective advantages and disadvantages are discussed for each PBR design, which may inform an interested bioprocess engineer.

Influence of salinity on microalgae-bacteria symbiosis treating shrimp farming wastewater

Shrimp farming has strongly developed in recent years, and became an important economic sector that helps create jobs and increase incomes for Vietnamese. However, the aquatic environment has also been greatly affected by the development due to the amount of wastewater discharged from shrimp farms. Among biological processes used for treating shrimp farming wastewater, the application of microalgae-bacteria co-culture is considered high potential due to its treatment and energy saving. Consequently, a photobioreactor operated with microalgae-bacteria co-culture was employed to treat shrimp farming wastewater. The salinity of wastewater and the operating condition (ratio of biomass retention time and hydraulic retention time, BRT/HRT) are the major factors affecting pollutant removal. Thus, this study investigated the effects of salinities of 0.5-20 ppt and BRT/HRT ratios of 1.5-16 on the removal performance. The results indicated that the nutrient removal was reduced when PBR operated under salinity over than 10 ppt and BRT/HRT over 5.5. Particularly, the nitrogen and phosphorus removal rates were achieved 6.56 ± 1.33 gN m-3 d-1 and 1.49 ± 0.59 gP m-3 d-1, and the removal rates decreased by 2-4 times under a salinity >10 ppt and 2-6 times under a BRT/HRT ratio >5.5. Whereas, organic matter treatment seems not to be affected when the removal rate was maintained at 28-34 gCOD m-3 d-1 under various conditions.

Wastewater from textile digital printing as a substrate for microalgal growth and valorization

This study aims at evaluating an innovative biotechnological process for the concomitant bioremediation and valorization of wastewater from textile digital printing technology based on a microalgae/bacteria consortium. Nutrient and colour removal were assessed in lab-scale batch and continuous experiments and the produced algae/bacteria biomass was characterized for pigment content and biomethane potential. Microbial community analysis provided insight of the complex community structure responsible for the bioremediation action. Specifically, a community dominated by Scenedesmus spp. and xenobiotic and dye degrading bacteria was naturally selected in continuous photobioreactors. Data confirm the ability of the microalgae/bacteria consortium to grow in textile wastewater while reducing the nutrient content and colour. Improvement strategies were eventually identified to foster biomass growth and process performances. The experimental findings pose the basis of the integration of a microalgal-based process into the textile sector in a circular economy perspective.

Microalgae growth in ultra-thin steady-state continuous photobioreactors: assessing self-shading effects

To disclose the net effect of light on microalgal growth in photobioreactors, self-shading and mixing-induced light–dark cycles must be minimized and discerned from the transient phenomena of acclimation. In this work, we performed experiments of continuous microalgal cultivation in small-scale photobioreactors with different thicknesses (from 2 to 35 mm): working at a steady state allowed us to describe the effect of light after acclimation, while the geometry of the reactor was adjusted to find the threshold light path that can discriminate different phenomena. Experiments showed an increased inhibition under smaller culture light paths, suggesting a strong shading effect at thicknesses higher than 8 mm where mixing-induced light–dark cycles may occur. A Haldane-like model was applied and kinetic parameters retrieved, showing possible issues in the scalability of experimental results at different light paths if mixing-induced light–dark cycles are not considered. To further highlight the influence of mixing cycles, we proposed an analogy between small-scale operations with continuous light and PBR operations with pulsed light, with the computation of characteristic parameters from pulsed-light microalgae growth mathematical modeling.

Advanced HRT-Controller Aimed at Optimising Nitrogen Recovery by Microalgae: Application in an Outdoor Flat-Panel Membrane Photobioreactor

A fuzzy knowledge-based controller of hydraulic retention time (HRT) was designed and tested in an outdoor membrane photobioreactor (MPBR) to improve nitrogen recovery from a microalgae cultivation system, maintaining the algae as photosynthetically active as possible and limiting their competition with other microorganisms. The hourly flow of the MPBR system was optimised by adjusting the influent flow rate to the outdoor environmental conditions which microalgae were exposed to at any moment and to the nitrogen uptake capacity of the culture. A semi-empirical photosynthetically active radiation (PAR) prediction model was calibrated using total cloud cover (TCC) forecast. Dissolved oxygen, standardised to 25 °C (DO25), was used as an on-line indicator of microalgae photosynthetic activity. Different indexes, based on suspended solids (SS), DO25, and predicted and real PAR, were used as input variables, while the initial HRT of each operating day (HRT0) and the variation of HRT (ΔHRT) served as output variables. The nitrogen recovery efficiency, measured as nitrogen recovery rate (NRR) per nitrogen loading rate (NLR) in pseudo-steady state conditions, was improved by 45% when the HRT-controller was set in comparison to fixed 1.25-d HRT. Consequently, the average effluent total soluble nitrogen (TSN) concentration in the MPBR was reduced by 47%, accomplishing the discharge requirements of the EU Directive 91/271/EEC.

Global sensitivity and uncertainty analysis of a microalgae model for wastewater treatment

The results of a global sensitivity and uncertainty analysis of a microalgae model applied to a Membrane Photobioreactor (MPBR) pilot plant were assessed. The main goals of this study were: (I) to identify the sensitivity factors of the model through the Morris screening method, i.e. the most influential factors; (II) to calibrate the influential factors online or offline; and (III) to assess the model's uncertainty. Four experimental periods were evaluated, which encompassed a wide range of environmental and operational conditions. Eleven influential factors (e.g. maximum specific growth rate, light intensity and maximum temperature) were identified in the model from a set of 34 kinetic parameters (input factors). These influential factors were preferably calibrated offline and alternatively online. Offline/online calibration provided a unique set of model factor values that were used to match the model results with experimental data for the four experimental periods. A dynamic optimization of these influential factors was conducted, resulting in an enhanced set of values for each period. Model uncertainty was assessed using the uncertainty bands and three uncertainty indices: p-factor, r-factor and ARIL. Uncertainty was dependent on both the number of influential factors identified in each period and the model output analyzed (i.e. biomass, ammonium and phosphate concentration). The uncertainty results revealed a need to apply offline calibration methods to improve model performance.

Kinetic modeling of autotrophic microalgae mainline processes for sewage treatment in phosphorus-replete and -deplete culture conditions

A kinetic model of autotrophic microalgal growth in sewage was developed to determine the biokinetic processes involved, including carbon-, nitrogen- and phosphorus-limited microalgal growth, dependence on light intensity, temperature and pH, light attenuation and gas exchange to the atmosphere. A new feature was the differentiation between two metabolic pathways of phosphorus consumption according to the availability of extracellular phosphorus. Two scenarios were differentiated: phosphorus-replete and -deplete culture conditions. In the former, the microalgae absorbed phosphorus to grow and store polyphosphate. In the latter the microalgae used the stored polyphosphate as a phosphorus source for growth. Calibration and validation were performed with experimental data from a pilot-scale membrane photobioreactor (MPBR) fed with the permeate obtained from an anaerobic membrane bioreactor (AnMBR) pilot plant fed with real urban wastewater. 12 of the model parameters were calibrated. Despite the dynamics involved in the operating and environmental conditions, the model was able to reproduce the overall process performance with a single set of model parameters values. Four periods of different environmental and operational conditions were accurately simulated. Regarding the former, light and temperature ranged 10-406 μmol·m^-2·s^-1 and 19.7-32.1 °C, respectively. Concerning the later, the photobioreactors widths were 0.25 and 0.10 m, and the biomass and hydraulic retention times ranged 3-4.5 and 1.5-2.5 days, respectively. The validation of the model resulted in an overall correlation coefficient (R²) of 0.9954. The simulation results showed the potential of the model to predict the dynamics of the different components: the relative proportions of microalgae, nitrogen and phosphorus removal, polyphosphate storage and consumption, and soluble organic matter concentration, as well as the influence of environmental parameters on the microalgae's biokinetic processes. The proposed model could provide an effective tool for the industry to predict microalgae production and comply with the discharge limits in areas declared sensitive to eutrophication.

On-line monitoring of photosynthetic activity based on pH data to assess microalgae cultivation

Microalgae performance of outdoor cultivation systems is influenced by environmental and operating dynamics. Monitoring and control systems are needed to maximise biomass productivity and nutrient recovery. The goal of this work was to corroborate that pH data could be used to monitor microalgae performance by means of data from an outdoor membrane photobioreactor (MPBR) plant. In this system, microalgae photosynthetic activity was favoured over other physical and biological processes, so that the pH data dynamics was theoretically related to the microalgae carbon uptake rate (CUR). Short- and long-term continuous operations were tested to corroborate the relationship between the first derivate of pH data dynamics (pH') and microalgae photosynthetic activity. Short-term operations showed a good correlation between gross pH' values and MPBR performance. An indicator of the maximum daily average microalgae activity was assessed by a combination of on-line pH' measurements obtained in the long-term and a microalgae growth kinetic model. Both indicators contributed to the development of advanced real-time monitoring and control systems to optimise microalgae cultivation technology.