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Alejo, L., Atkinson, J., Guzman-Fierro, V., & Roeckel, M. (2018). Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques. Environ. Sci. Pollut. Res., 25(21), 21149–21163.
Abstract: Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. The analytical method considers the protein as the only source of ammonia production in AD after degradation. Total ammonia nitrogen (TAN), total solids (TS), chemical oxygen demand (COD), and total volatile solids (TVS) were measured in the influent and effluent of the process. The TAN concentration in the effluent was predicted, this being the most inhibiting and polluting compound in AD. Despite the limited data available, the SVM-based model outperformed the analytical method for the TAN prediction, achieving a relative average error of 15.2% against 43% for the analytical method. Moreover, SVM showed higher prediction accuracy in comparison with Artificial Neural Networks. This result reveals the future promise of SVM for prediction in non-linear and dynamic AD processes.
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Cordova, S., Canizares, C., Lorca, A., & Olivares, D. E. (2021). An Energy Management System With Short-Term Fluctuation Reserves and Battery Degradation for Isolated Microgrids. IEEE Trans. Smart Grid, 12(6), 4668–4680.
Abstract: Due to the low-inertia and significant renewable generation variability in isolated microgrids, short time-scale fluctuations in the order of seconds can have a large impact on a microgrid's frequency regulation performance. In this context, the present paper presents a mathematical model for an Energy Management System (EMS) that takes into account the operational impact of the short-term fluctuations stemming from renewable generation rapid changes, and the role that renewable curtailment and batteries, including their degradation, can play to counter-balance these variations. Computational experiments on the real Kasabonika Lake First Nation microgrid and CIGRE benchmark test system show the operational benefits of the proposed EMS, highlighting the need to properly model short-term fluctuations and battery degradation in EMS for isolated microgrids with significant renewable integration.
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del Rio, A. V., Stachurski, A., Mendez, R., Campos, J. L., Surmacz-Gorska, J., & Mosquera-Corral, A. (2017). Short- and long-term orange dye effects on ammonium oxidizing and anammox bacteria activities. Water Sci. Technol., 76(1), 79–86.
Abstract: The effects of orange azo dye over ammonia oxidizing bacteria (AOB) and anammox bacteria activities were tested. Performed batch tests indicated that concentrations lower than 650 mg(orange)/L stimulated AOB activity, while anammox bacteria activity was inhibited at concentrations higher than 25 mg(orange)/L. Long-term performance of a continuous stirred tank reactor (CSTR) for the partial nitritation and a sequencing batch reactor (SBR) for the anammox process was tested in the presence of 50 mg(orange)/L. In the case of the partial nitritation process, both the biomass concentration and the specific AOB activity increased after 50 days of orange azo dye addition. Regarding the anammox process, specific activity decreased down to 58% after 12 days of operation with continuous feeding of 50 mg(orange)/L. However, the anammox activity was completely recovered only 54 days after stopping the dye addition in the feeding. Once the biomass was saturated the azo dye adsorption onto the biomass was insignificant in the CSTR for the partial nitritation process fed with 50 mg(orange)/L. However, in the SBR the absorption was determined as 6.4 mg(orange)/g volatile suspended solids. No biological decolorization was observed in both processes.
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Donoso, R. A., Ruiz, D., Garate-Castro, C., Villegas, P., Gonzalez-Pastor, J. E., de Lorenzo, V., et al. (2021). Identification of a self-sufficient cytochrome P450 monooxygenase from Cupriavidus pinatubonensis JMP134 involved in 2-hydroxyphenylacetic acid catabolism, via homogentisate pathway. Microb. Biotechnol., 14(5), 1944–1960.
Abstract: The self-sufficient cytochrome P450 RhF and its homologues belonging to the CYP116B subfamily have attracted considerable attention due to the potential for biotechnological applications based in their ability to catalyse an array of challenging oxidative reactions without requiring additional protein partners. In this work, we showed for the first time that a CYP116B self-sufficient cytochrome P450 encoded by the ohpA gene harboured by Cupriavidus pinatubonensis JMP134, a beta-proteobacterium model for biodegradative pathways, catalyses the conversion of 2-hydroxyphenylacetic acid (2-HPA) into homogentisate. Mutational analysis and HPLC metabolite detection in strain JMP134 showed that 2-HPA is degraded through the well-known homogentisate pathway requiring a 2-HPA 5-hydroxylase activity provided by OhpA, which was additionally supported by heterologous expression and enzyme assays. The ohpA gene belongs to an operon including also ohpT, coding for a substrate-binding subunit of a putative transporter, whose expression is driven by an inducible promoter responsive to 2-HPA in presence of a predicted OhpR transcriptional regulator. OhpA homologues can be found in several genera belonging to Actinobacteria and alpha-, beta- and gamma-proteobacteria lineages indicating a widespread distribution of 2-HPA catabolism via homogentisate route. These results provide first time evidence for the natural function of members of the CYP116B self-sufficient oxygenases and represent a significant input to support novel kinetic and structural studies to develop cytochrome P450-based biocatalytic processes.
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Pabon-Pereira, C. P., Hamelers, H. V. M., Matilla, I., & van Lier, J. B. (2020). New Insights on the Estimation of the Anaerobic Biodegradability of Plant Material: Identifying Valuable Plants for Sustainable Energy Production. Processes, 8(7), 23 pp.
Abstract: Based on fifteen European plant species, a statistical model for the estimation of the anaerobic biodegradability of plant material was developed. We show that this new approach represents an accurate and cost-effective method to identify valuable energy plants for sustainable energy production. In particular, anaerobic biodegradability (B-o) of lignocellulosic material was empirically found to be related to the amount of cellulose plus lignin, as analytically assessed by the van Soest method, i.e., the acid detergent fiber (ADF) value. Apart from being theoretically meaningful, the ADF-based empirical model requires the least effort compared to the other four proposed conceptual models proposed, as individual fractions of cellulose, hemicellulose, and lignin do not need to be assessed, which also enhances the predictive accuracy of the model's estimation. The model's results showed great predictability power, allowing us to identify interesting crops for sustainable crop rotations. Finally, the model was used to predictB(o)of 114 European plant samples that had been previously characterized by means of the van Soest method.
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