Mohamadnia, S., Thygesen, A., Ghofrani-Isfahani, P., Monachese, A.P., Valverde-Pérez, B., Angelidaki, I., 2023. Valorization of potato starch wastewater using anaerobic acidification coupled with Chlorella sorokiniana cultivation. J. Appl. Phycol. 35 (6), 2645-2658.

Monje, V., Junicke, H., Batstone, D.J., Kjellberg, K., Gernaey, K.V., Flores-Alsina, X., 2022. Prediction of mass and volumetric flows in a full-scale industrial wastewater treatment plant. Chem. Eng. J. 445, 136774.

Monod, J., 2012. The Growth of Bacterial Cultures. Selected Papers in Molecular Biology by Jacques Monod, 139, p. 606.

Morales, M., Afaljo, C., Bernard, O., 2021. Microalgal lipids: A review of lipids potential and quantification for 95 phytoplankton species. Biomass Bioenergy 150, 106108.

Morgado, D., Fanesi, A., Martin, T., Tebbani, S., Bernard, O., Lopes, F., 2024. Non-destructive monitoring of microalgae biofilms. Bioresour. Technol. 398, 130502.

Munoz, R., Guieysse, B., 2006. Algal-bacterial processes for the treatment of hazardous contaminants: a review. Water Res. 40 (15), 2799-2815.

Mutale-Joan, C., Sbabou, L., Hicham, E.A., 2023. Microalgae and cyanobacteria: how exploiting these microbial resources can address the underlying challenges related to food sources and sustainable agriculture: a review. J. Plant Growth Regul. 42 (1), 1-20.

Natrah, F.M., Bossier, P., Sorgeloos, P., Yusoff, F.M., Defoirdt, T., 2014. Significance of microalgal-bacterial interactions for aquaculture. Rev. Aquacult. 6 (1), 48-61.

Nguyen, B.T., Rittman, B.E., 2018. Low-cost optical sensor to automatically monitor and control biomass concentration in microalgal cultivation. Algal Res. 32, 101-106.

Nikolaou, A., Hartmann, P., Sciandra, A., Chachuat, B., Bernard, O., 2016. Dynamic coupling of photoacclimation and photoinhibition in a model of microalgal growth. J. Theor. Biol. 390, 61-72.

Nordio, R., Rodriguez-Miranda, E., Casagli, F., Sánchez-Zurano, A., Guzmán, J.L., Acién, G., 2024. ABACO-2: a comprehensive model for microalgae-bacteria consortia validated outdoor at pilot-scale. Water Res. 248, 120837.

Nordio, R., Casagli, F., Rodriguez-Miranda, E., Guzman, J.L., Bernard, O., Acien, G., 2025. Benchmarking of ALBA and ABACO-2 models for algae-bacteria wastewater treatment. Algal Res. 89, 104049.

Orth, J.D., Thiele, I., Palsson, B.O., 2010. What is flux balance analysis? Nat. Biotechnol. 28, 245-248.

Ota, S., Kawano, S., 2019. Three-dimensional ultrastructure and hyperspectral imaging of metabolite accumulation and dynamics in Haematococcus and Chlorella. Microscopy 68, 57-68.

Otálora, P., Guzmán, J.L., Acién, F.G., Berenguel, M., Reul, A., 2021. Microalgae classification based on machine learning techniques. Algal Res. 55.

Otálora, P., Guzmán, J.L., Berenguel, M., Acién, F.G., 2023. Data-driven pH model in raceway reactors for freshwater and wastewater cultures. Mathematics 11 (7), 1614.

Oviedo, J.A., Munoz, R., Donoso-Bravo, A., Bernard, O., Casagli, F., Jeison, D., 2022. A half-century of research on microalgae-bacteria for wastewater treatment. Algal Res. 67, 102828.

Palacios, O.A., López, B.R., de Bashan, L.E., 2022. Microalga growth-promoting Bacteria (MGPB): a formal term proposed for beneficial bacteria involved in microalgal-bacterial interactions. Algal Res. 61, 102585.

Parashar, M., Kurc, T., Klie, H., Wheeler, M.F., Saltz, J.H., Jammoul, M., Dong, R., 2023. Dynamic data-driven application systems for reservoir simulation-based optimization: lessons learned and future trends. In: Handbook of Dynamic Data Driven Applications Systems, 2. Springer International Publishing, Cham, pp. 287-330.

Penaranda, D., Casagli, F., Morales, M., Beline, F., Bernard, O., 2025. Ex-ante LCA for circular resource management of liquid digestate, by predictive modeling of algae-bacterial processes. J. Ind. Ecol. 1-15.

Peng, L., Ni, B.J., Ye, L., Yuan, Z., 2015. N2O production by ammonia oxidizing bacteria in an enriched nitrifying sludge linearly depends on inorganic carbon concentration. Water Res. 74, 58-66.

Perez-García, O., Escalante, F.M.E., de Bashan, L.E., Bashan, Y., 2011. Heterotrophic cultures of microalgae: metabolism and potential products. Water Res. 45 (1), 11-36.

Pessi, B.A., Pruvost, E., Talec, A., Sciandra, A., Bernard, O., 2022. Does temperature shift justify microalgae production under greenhouse? Algal Res. 61, 102579.

Pessi, B.A., Baroukh, C., Bacquet, A., Bernard, O., 2023. A universal dynamical metabolic model representing mixotrophic growth of Chlorella sp. on wastes. Water Res. 229, 119388.

Pisa, I., Santin, I., Morell, A., Vicario, J.L., Vilanova, R., 2019. LSTM-based wastewater treatment plants operation strategies for effluent quality improvement. IEEE Access 7, 159773-159786.

Podevin, M., Fotidis, I.A., Angelidaki, I., 2017. Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives. Crit. Rev. Biotechnol. 38 (5), 704-718.

Pozzobon, V., Perré, P., 2020. Multiscale numerical workflow describing microalgae motion and light pattern incidence towards population growth in a photobioreactor. J. Theor. Biol. 498, 110293.

Puyol, D., Barry, E.M., Hülsen, T., Batstone, D.J., 2017. A mechanistic model for anaerobic phototrophs in domestic wastewater applications: photo-anaerobic model (PANM). Water Res. 116, 241-253.

Qiu, Y., Griffin, C.T., Ekström, S., Valverde-Pérez, B., Smets, B.F., Climent, J., Domingo-Félez, C., Martínez Cuenca, R., Plósz, B.Gy., 2024. Numerical modelling of surface aeration and N₂O emission in biological water resource recovery. Water Res. 255, 121398.

Qiu, Y., Bakos, V., Stewart-Campbell, N., Plósz, B.G., 2024b. Dynamic α-factor models for fine-bubble- and surface aeration - impact of settleability and implications on N2O emission. Chem. Eng. J. 488, 150650.

Ramanan, R., Kim, B.H., Cho, D.H., Oh, H.M., Kim, H.S., 2016. Algae-bacteria interactions: evolution, ecology and emerging applications. Biotechnol. Adv. 34 (1), 14-29.

Ranganathan, P., Pandey, A.K., Sirohi, R., Tuan Hoang, A., Kim, S.-H., 2022. Recent advances in computational fluid dynamics (CFD) modelling of photobioreactors: design and applications. Bioresour. Technol. 350, 126920.

Ras, M., Steyer, J.P., Bernard, O., 2013. Temperature effect on microalgae: a crucial factor for outdoor production. Rev. Environ. Sci. Biotechnol. 12 (2), 153-164.

Rasouli, Z., Valverde-Pérez, B., D'Este, M., De Francisci, D., Angelidaki, I., 2018. Nutrient recovery from industrial wastewater as single cell protein by a co-culture of green microalgae and methanotrophs. Biochem. Eng. J. 134, 129-135.

Raue, A., Karlsson, J., Saccomani, M.P., Jirstrand, M., Timmer, J., 2014. Comparison of approaches for parameter identifiability analysis of biological systems. Bioinformatics 30 (10), 1440-1448.

Refsgaard, J.C., van der Sluijs, J.P., Hojberg, A.L., Vanrolleghem, P.A., 2007. Uncertainty in the environmental modelling process – a framework and guidance. Environ. Model Softw. 22 (11), 1543-1556.

Reichert, P., Borchardt, D., Henze, M., Rauch, W., Shanahan, P., Somlyódy, L., Vanrolleghem, P., 2001. River water quality model no. 1 (RWQM1): II. Biochemical process equations. Water Sci. Technol. 43 (5), 11-30.

Richmond, A., 2004. Handbook of microalgal culture: biotechnology and applied phycology. Otonor.Catie.Ac.Cr 472.

Rieger, L., Gillot, S., Langergraber, G., Ohtsuki, T., Shaw, A., Takacs, I., Winkler, S., 2013. Guidelines for Using Activated Sludge Models. IWA Publishing.

Robles, A., Capson-Tojo, G., Galés, A., Ruano, M.V., Sialve, B., Ferrer, J., Steyer, J.P., 2020. Microalgae-bacteria consortia in high-rate ponds for treating urban wastewater: elucidating the key state indicators under dynamic conditions. J. Environ. Manag. 261, 110244.

Rodríguez-Rángel, H., Arias, D.M., Morales-Rosales, L.A., González-Huitron, V., Valenzuela Partida, M., García, J., 2022. Machine learning methods modeling carbohydrate-enriched cyanobacteria biomass production in wastewater treatment systems. Energies 15 (7), 2500.

Romero-García, J.M., Acién-Fernández, F.G., Fernández-Sevilla, J.M., 2012. Development of a process for the production of l-amino-acids concentrates from microalgae by enzymatic hydrolysis. Bioresour. Technol. 112, 164-170.

Ross, O.N., Geider, R.J., 2009. New cell-based model of photosynthesis and photo-acclimation: accumulation and mobilisation of energy reserves in phytoplankton. Mar. Ecol. Prog. Ser. 383, 53-71.

Rossi, S., Díez-Montero, R., Rueda, E., Castillo Cascino, F., Parati, K., García, J., Ficara, E., 2020. Free ammonia inhibition in microalgae and cyanobacteria grown in wastewaters: photo-respirometric evaluation and modelling. Bioresour. Technol. 305 (February), 123046.

Rossi, S., Capson-Tojo, G., Sánchez-Zurano, A., Carecci, D., Batstone, D.J., Acien-Fernández, G., Ficara, E., 2025. Recent advances and challenges in mechanistic modelling of photosynthetic processes for wastewater treatment. Water Res. 278, 123216.

Rosso, L., Lobry, J.R., Bajard, S., Flandrois, J.P., 1995. Convenient model to describe the combined effects of temperature and pH on microbial growth. Appl. Environ. Microbiol. 61, 610-616.

Rueda, E., García, J., 2021. Optimization of the phototrophic Cyanobacteria polyhydroxybutyrate (PHB) production by kinetic model simulation. Sci. Total Environ. 800.

Santos-Ballardo, D.U., Rossi, S., Hernández, V., Gómez, R.V., del Carmen Rendón-Unceta, M., Caro-Corrales, J., Valdez-Ortiz, A., 2015. A simple spectrophotometric method for biomass measurement of important microalgae species in aquaculture. Aquaculture 448, 87-92.

Schneider, M.Y., Quaghebeur, W., Borzooei, S., Froemelt, A., Li, F., Saagi, R., Wade, M.J., Zhu, J.J., Torfs, E., 2022. Hybrid modelling of water resource recovery facilities: status and opportunities. Water Sci. Technol. 85 (9), 2503-2524.

Serra-Maia, R., Bernard, O., Gonçalves, A., Bensalem, S., Lopes, F., 2016. Influence of temperature on Chlorella vulgaris growth and mortality rates in a photobioreactor. Algal Res. 18, 352-359.

Shoener, B., Schramm, S., Béline, F., Bernard, O., Martínez von Dossow, C., Plósz, B.Gy., Snowling, S., Steyer, J.P., Valverde-Pérez, B., Wágner, D.S., Guest, J.P., 2019. Microalgae and cyanobacteria modeling in water resource recovery facilities: a critical review. Water Res. X 2, 100024.

Silkina, A., Flynn, K., Llewellyn, C., Bayliss, C., 2015. Standard Operating Procedures for Analytical Methods and Data Collection in Support of Pilot-Scale Cultivation of Microalgae. Public Output report WP1A3. 01 of the EnAlgae Project.

Sin, G., Gernaey, K.V., Neumann, M.B., van Loosdrecht, M.C.M., Gujer, W., 2009. Uncertainty analysis in WWTP model applications: a critical discussion using an example from design. Water Res. 43 (11), 2894-2906.

Singh, D., Nedbal, L., Ebenhöh, O., 2018. Modelling phosphorus uptake in microalgae. Biochem. Soc. Trans. 46 (2), 483-490.

Solimeno, A., Gómez-Serrano, C., Acién, F.G., 2019. BIO_ALGAE 2: improved model of microalgae and bacteria consortia for wastewater treatment. Environ. Sci. Pollut. Res. 26 (25), 25855-25868.

Solon, K., Flores-Alsina, X., Mbamba, C.K., Volcke, E.I., Tait, S., Batstone, D., Jeppsson, U., 2015. Effects of ionic strength and ion pairing on (plant-wide) modelling of anaerobic digestion. Water Res. 70, 235-245.

Stegemüller, L., Caccavale, F., Valverde-Pérez, B., Angelidaki, I., 2025. Online monitoring of *Haematococcus lacustris* cell cycle using machine and deep learning techniques. Bioresour. Technol. 418, 131976.

Steuer, R., Knoop, H., MacHné, R., 2012. Modelling cyanobacteria: from metabolism to integrative models of phototrophic growth. J. Exp. Bot. 63 (6), 2259-2274.
Syed, T., Krujatz, F., Ihjadene, Y., Mühlstädt, G., Hamedi, H., Mädler, J., Urbas, L., 2024. A review on machine learning approaches for microalgae cultivation systems. Comput. Biol. Med. 172, 108248.

Takahashi, T., 2018. Applicability of automated cell counter with a chlorophyll detector in routine management of microalgae. Sci. Rep. 8 (1), 4967.

Tchobanoglous, G., Stensel, H., Tsuchihashi, R., Burton, F., 2014. Wastewater Engineering: Treatment and Resource Recovery, Fifth edition. McGraw-Hill Education.

Torfs, E., Nicolaï, N., Daneshgar, S., Copp, J.B., Haimi, H., Ikumi, D., Johnson, B., Plósz, B.Gy., Snowling, S., Townley, LI, Valverde-Pérez, B., Vanrolleghem, P.A., Vezzaro, L., Nopens, I., 2022. The transition of WRRF models to digital twin applications. Water Sci. Technol. 85 (10), 2840–2853.

Tribe, L.A., Briens, C.L., Margaritis, A., 1995. Determination of the volumetric mass transfer coefficient (k,a) using the dynamic "gas out-gas in" method: analysis of errors caused by dissolved oxygen probes. Biotechnol. Bioeng. 46, 388–392.

Van Daele, T., Van Hoey, S., Gernaey, K.V., Krühne, U., Nopens, I., 2015. A numerical procedure for model identifiability analysis applied to enzyme kinetics. Comput. Aided Process Eng. 37, 575–580.

van Loosdrecht, M.C.M., Nielsen, P.H., Lopez-Vazquez, C.M., Brdjanovic, D., 2016. Experimental Methods in Wastewater Treatment. IWA Publishing.

Varling, A.S., Chrysochoidis, V., Bisinella, V., Valverde-Pérez, B., Christensen, T.H., 2025. Climate change impact of biological treatment of liquid digestate from anaerobic digestion of food waste. Waste Manag. 193 (1), 339–349.

Vulsteke, E., Van Den Hende, S., Bourez, L., Capoen, H., Rousseau, D.P.L., Albrecht, J., 2017. Economic feasibility of microalgal bacterial floc production for wastewater treatment and biomass valorization: a detailed up-to-date analysis of up-scaled pilot results. Bioresour. Technol. 224, 118–129.

Wagner, H., Liu, Z., Langner, U., Stehfest, K., Wilhelm, C., 2010. The use of FTIR spectroscopy to assess quantitative changes in the biochemical composition of microalgae. J. Biophotonics 3 (8-9), 557–566.

Wágner, D.S., Valverde-Pérez, B., Sæbø, M., de la Sotilla, M.B., Van Wagenen, J., Smets, B.F., Plósz, B.G., 2016. Towards a consensus-based biokinetic model for green microalgae–the ASM-A. Water Res. 103, 485–499.

Wágner, D.S., Radovici, M., Smets, B.F., Angelidaki, I., Valverde-Pérez, B., Plósz, B.Gy., 2016b. Harvesting microalgae using activated sludge can decrease polymer dosing and enhance methane production via co-digestion in a bacterial-microalgal process. Algal Res. 20, 197–204.

Wágner, D.S., Valverde-Pérez, B., Plósz, B.G., 2018. Light attenuation in photobioreactors and algal pigmentation under different growth conditions - model identification and complexity assessment. Algal Res. 35, 488–499.

Wágner, D.S., Cazzaniga, C., Steidl, M., Dechesne, A., Valverde-Pérez, B., Plósz, B.Gy., 2021. Optimal influent N-to-P ratio for stable microalgal cultivation in water treatment and nutrient recovery. Chemosphere 262, 127939.

Walter, E., Pronzato, L., 1997. Identification of parametric models: from experimental data. Springer. (Communications and Control Engineering, London.

Wenk, P., Gotovos, A., Bauer, S., Gorbach, N.S., Krause, A., Buhmann, J.M., 2019. April. Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. In: The 22nd International Conference on Artificial Intelligence and Statistics. PMLR, pp. 1351–1360.

Wicklein, E., Batstone, D.J., Ducoste, J., Laurent, J., Griborio, A., Wicks, J., Saunders, S., Samstag, R., Potier, O., Nopens, I., 2015. Good modelling practice in applying computational fluid dynamics for WWTP modelling. Water Sci. Technol. 73, 969–982.

Wieland, F.G., Hauber, A.L., Rosenblatt, M., Tönsing, C., Timmer, J., 2021. On structural and practical identifiability. Curr. Opin. Syst. Biol. 25, 60–69.

Williams, P.J.L.B., Laurens, L.M., 2010. Microalgae as biodiesel & biomass feedstocks: Review & analysis of the biochemistry, energetics & economics. Energy Environ. Sci. 3 (5), 554–590.

Wolf, G., Picioreanu, C., van Loosdrecht, M.C.M., 2007. Kinetic modeling of phototrophic biofilms: the PHOBIA model. Biotechnol. Bioeng. 97 (5), 1064–1079.

Wolf-Gladrow, D.A., Zeebe, R.E., Klaas, C., Körtzinger, A., Dickson, A.G., 2007. Total alkalinity: the explicit conservative expression and its application to biogeochemical processes. Mar. Chem. 106 (1–2), 287–300.

Wongburi, P., Park, J.K., 2023. Prediction of wastewater treatment plant effluent water quality using recurrent neural network (RNN) models. Water 15 (19), 3325.

Wu, G.F., Wu, Q.Y., Shen, Z.Y., 2001. Accumulation of poly-β-hydroxybutyrate in cyanobacterium Synechocystis sp. PCC6803. Bioresour. Technol. 76 (2), 85-90.

Yahia, B., Malphettes, L., Heinzle, E., 2015. Macroscopic modeling of mammalian cell growth and metabolism. Appl. Microbiol. Biotechnol. 99 (17), 7009–7024.

Yang, Z., Cheng, J., Ye, Q., Liu, J., Zhou, J., Cen, K., 2016. Decrease in light/dark cycle of microalgal cells with computational fluid dynamics simulation to improve microalgal growth in a raceway pond. Bioresour. Technol. 220, 352–359.

Yang, S.H., Hu, B.G., Cournède, P.H., 2008. Structural identifiability of generalized constraint neural network models for nonlinear regression. Neurocomputing 72 (1–3), 392–400.

Zhang, D., Del Rio-Chanona, E.A., Petsagkourakis, P., Wagner, J., 2019. Hybrid physics-based and data-driven modeling for bioprocess online simulation and optimization. Biotechnol. Bioeng. 116 (11) (2919–293).

Zhang, Y., Wang, J.H., Zhang, J.T., Chi, Z.Y., Kong, F.T., Zhang, Q., 2023. The long overlooked microalgal nitrous oxide emission: characteristics, mechanisms, and influencing factors in microalgae-based wastewater treatment scenarios. Sci. Total Environ. 856, 159153.