Integrated microalgae-bacteria modelling: application to an outdoor membrane photobioreactor (MPBR).

A mechanistic model describing the key interactions occurring in microalgae-bacteria consortia systems was developed and validated. The proposed model includes the most relevant features of microalgae, such as light dependence, endogenous respiration, growth, and nutrient consumption for different nutrient sources. The model is coupled to the plant-wide model BNRM2, including heterotrophic and nitrifying bacteria, and chemical precipitation processes, among others. A major novelty of the model is microalgae growth inhibition by nitrite. Validation was conducted using experimental data from a pilot-scale membrane photobioreactor (MPBR) fed with permeate from an anaerobic membrane bioreactor (AnMBR). Three experimental periods dealing with different interactions between nitrifying bacteria and microalgae were validated. The model was able to accurately represent the dynamics occurring in the MPBR, predicting the relative abundance of microalgae and bacteria over time. Specifically, >500 pairs of experimental and modeled data were evaluated, giving an average R2 coefficient of 0.9902. The validated model was also used to evaluate different offline control strategies for enhancing process performance. For example, partial-nitrification resulting in NO2-N accumulation (i.e., microalgae growth inhibition) could be avoided by increasing biomass retention time from 2.0 to 4.5 days. It has been also concluded that microalgae biomass growth rate could be also enhanced by punctually increasing the dilution rate, allowing to outcompete nitrifying bacteria.

Assessing and modeling nitrite inhibition in microalgae-bacteria consortia for wastewater treatment by means of photo-respirometric and chlorophyll fluorescence techniques.

Total nitrite (TNO2 = HNO2 + NO-2) accumulation due to the activity of ammonia-oxidizing bacteria (AOB) was monitored in microalgae-bacteria consortia, and the inhibitory effect of nitrite/free nitrous acid (NO2-N/FNA) on microalgae photosynthesis and inhibition mechanism was studied. A culture of Scenedesmus was used to run two sets of batch reactors at different pH and TNO2 concentrations to evaluate the toxic potential of NO2-N and FNA. Photo-respirometric tests showed that NO2-N accumulation has a negative impact on net oxygen production rate (OPRNET). Chlorophyll a fluorescence analysis was used to examine the biochemical effects of NO2-N stress and the mechanism of NO2-N inhibition. The electron transport rate (ETR), non-photochemical quenching (NPQ), and JIP-test revealed that the electron transport chain between Photosystems II and I (PS II and PS I) was hindered at NO2-N concentrations above 25 g N m-3. Electron acceptor QA was not able to reoxidize and could not transfer electrons to the next electron acceptor, QB, accumulating P680+ (excited PS II reaction center) and limiting oxygen production. A semi-continuous reactor containing a Scenedesmus culture was monitored by photo-respirometry tests and Chlorophyll a fluorescence to calibrate NO2-N inhibition (5-35 g N m-3). Non-competitive inhibition and Hill-type models were compared to select the best-fitting inhibition equations. Inhibition was correctly modeled by the Hill-type model and a half inhibition constant (KI) for OPRNET, NPQ, maximum photosynthetic rate (ETRMAX) and the performance index PIABS was 23.7 ± 1.2, 26.36 ± 1.10, 39 ± 2 and 26.5 ± 0.4, respectively.

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.