Abstract
Microalgae-based tertiary wastewater treatment has the potential to meet stringent effluent phosphorus limits, with the added benefit of producing a marketable feedstock. However, without validated models embedded in process simulators, the industry lacks the tools to evaluate the benefits and trade-offs of integrating tertiary microalgal treatment with conventional wastewater systems. In this study, an updated lumped pathway metabolic model was developed to predict effluent phosphorus concentration and biomass yield in response to dynamic influent and varying environmental conditions. The model was implemented in QSDsan – an open-source, Python-based design/simulation platform. Global sensitivity analysis was performed to prioritize model parameters for calibration. The model was then calibrated and validated using batch experiments and continuous online monitoring data from a full-scale microalgae-based tertiary wastewater treatment plant. Overall, the QSDsan-based microalgae process simulator was able to predict effluent phosphorus within 0.02–0.04 mg-P·L-1, while also capturing general trends of state variables according to nutrient availability.
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Data availability
The datasets generated and/or analyzed during the current study are available in the EXPOsan GitHub repository and can be accessed via these links: https://github.com/QSD-Group/EXPOsan/tree/main/exposan/pm2_batch/data, https://github.com/QSD-Group/EXPOsan/tree/main/exposan/pm2_ecorecover/data.
Code availability
The underlying code for this study is available on GitHub and can be accessed via these links: https://github.com/QSD-Group/QSDsan/blob/main/qsdsan/processes/_pm2.py. https://github.com/QSD-Group/EXPOsan/tree/main/exposan/pm2_batch, https://github.com/QSD-Group/EXPOsan/tree/main/exposan/pm2_ecorecover.
References
Li, K. et al. Microalgae-based wastewater treatment for nutrients recovery: A review. Bioresour. Technol. 291, 121934 (2019).
Mohsenpour, S. F., Hennige, S., Willoughby, N., Adeloye, A. & Gutierrez, T. Integrating micro-algae into wastewater treatment: A review. Sci. Total Environ. 752, 142168 (2021).
Molitor, H. R. et al. Intensive Microalgal Cultivation and Tertiary Phosphorus Recovery from Wastewaters via the EcoRecover Process. Environ. Sci. Technol. 58, 8803–8814 (2024).
Bunce, J. T., Ndam, E., Ofiteru, I. D., Moore, A. & Graham, D. W. A Review of Phosphorus Removal Technologies and Their Applicability to Small-Scale Domestic Wastewater Treatment Systems. Front. Environ. Sci. 6, 8 (2018).
Tamburic, B., Evenhuis, C. R., Crosswell, J. R. & Ralph, P. J. An empirical process model to predict microalgal carbon fixation rates in photobioreactors. Algal Res. 31, 334–346 (2018).
Mazzelli, A. et al. Multivariate modeling for microalgae growth in outdoor photobioreactors. Algal Res. 45, 101663 (2020).
Shoener, B. D. et al. Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review. Water Res. X 2, 100024 (2019).
Baroukh, C., Muñoz-Tamayo, R., Bernard, O. & Steyer, J.-P. Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production. Curr. Opin. Biotechnol. 33, 198–205 (2015).
Li, C.-T. et al. Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity. npj Syst. Biol. Appl 5, 33 (2019).
Pessi, B. A., Baroukh, C., Bacquet, A. & Bernard, O. A universal dynamical metabolic model representing mixotrophic growth of Chlorella sp. on wastes. Water Res. 229, 119388 (2023).
Roels, J. A. Energetics and Kinetics in Biotechnology. (Elsevier Biomedical Press, Amsterdam, 1983).
Smolders, G. J. F., Van Der Meij, J., Van Loosdrecht, M. C. M. & Heijnen, J. J. Stoichiometric model of the aerobic metabolism of the biological phosphorus removal process. Biotech. Bioeng. 44, 837–848 (1994).
Smolders, G. J. F., Van Der Meij, J., Van Loosdrecht, M. C. M. & Heijnen, J. J. A structured metabolic model for anaerobic and aerobic stoichiometry and kinetics of the biological phosphorus removal process. Biotech. Bioeng. 47, 277–287 (1995).
Van Aalst-van Leeuwen, M. A., Pot, M. A., Van Loosdrecht, M. C. M. & Heijnen, J. J. Kinetic modeling of poly(β-hydroxybutyrate) production and consumption by Paracoccus pantotrophus under dynamic substrate supply. Biotechnol. Bioeng. 55, 773–782 (1997).
Jiang, Y., Hebly, M., Kleerebezem, R., Muyzer, G. & Van Loosdrecht, M. C. M. Metabolic modeling of mixed substrate uptake for polyhydroxyalkanoate (PHA) production. Water Res. 45, 1309–1321 (2011).
Hanschen, E. R. & Starkenburg, S. R. The state of algal genome quality and diversity. Algal Res. 50, 101968 (2020).
Guest, J. S., Van Loosdrecht, M. C. M., Skerlos, S. J. & Love, N. G. Lumped pathway metabolic model of organic carbon accumulation and mobilization by the alga Chlamydomonas reinhardtii. Environ. Sci. Technol. 47, 3258–3267 (2013).
Li, Y. et al. QSDsan: an integrated platform for quantitative sustainable design of sanitation and resource recovery systems. Environ. Sci.: Water Res. Technol. 8, 2289–2303 (2022).
Henze, M., Gujer, W., Mino, T. & Van Loosedrecht, M. Activated Sludge Models ASM1, ASM2, ASM2d and ASM3. Water Intell. Online 5, 9781780402369–9781780402369 (2015).
Casagli, F., Zuccaro, G., Bernard, O., Steyer, J.-P. & Ficara, E. ALBA: A comprehensive growth model to optimize algae-bacteria wastewater treatment in raceway ponds. Water Res. 190, 116734 (2021).
Nordio, R. et al. ABACO-2: a comprehensive model for microalgae-bacteria consortia validated outdoor at pilot-scale. Water Res. 248, 120837 (2024).
Boyle, N. R. & Morgan, J. A. Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii. BMC Syst. Biol. 3, 4 (2009).
Lehninger, A. L., Nelson, D. L. & Cox, M. M. Lehninger Principles of Biochemistry. (W.H. Freeman, New York, 2013).
Manichaikul, A. et al. Metabolic network analysis integrated with transcript verification for sequenced genomes. Nat. Meth. 6, 589–592 (2009).
Gardner-Dale, D. A., Bradley, I. M. & Guest, J. S. Influence of solids residence time and carbon storage on nitrogen and phosphorus recovery by microalgae across diel cycles. Water Res. 121, 231–239 (2017).
Fedders, A. C. et al. Comparable Nutrient Uptake across Diel Cycles by Three Distinct Phototrophic Communities. Environ. Sci. Technol. 53, 390–400 (2019).
Bradley, I. M., Sevillano-Rivera, M. C., Pinto, A. J. & Guest, J. S. Impact of solids residence time on community structure and nutrient dynamics of mixed phototrophic wastewater treatment systems. Water Res. 150, 271–282 (2019).
Imam, S. et al. A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses. Plant J. 84, 1239–1256 (2015).
Perez-Garcia, O., Bashan, Y. & Esther Puente, M. Organic Carbon Supplementation of Sterilized Municipal Wastewater is Essential for Heterotrophic Growth and Removing Ammonium by the Microalga Chlorella vulgaris. J. Phycol. 47, 190–199 (2011).
Schramm, S. M. Development of universal stoichiometric coefficients for modeling microalgal cultivation systems. (University of Illinois Urbana-Champaign, Civil and Environmental Engineering, 2018).
Roels, J. A. Application of macroscopic principles to microbial metabolism. Biotech. Bioeng. 22, 2457–2514 (1980).
Geider, R. J., Maclntyre, H. L. & Kana, T. M. A dynamic regulatory model of phytoplanktonic acclimation to light, nutrients, and temperature. Limnol. Oceanogr. 43, 679–694 (1998).
Carletti, M., Barbera, E., Filippini, F. & Sforza, E. Effect of ammonium/nitrate ratio on microalgae continuous cultures: Species-specificity of nutrient uptake and modelling perspectives. J. Water Process Eng. 58, 104762 (2024).
Goldman, J. C. & Carpenter, E. J. A kinetic approach to the effect of temperature on algal growth1. Limnol. Oceanogr. 19, 756–766 (1974).
Siaut, M. et al. Oil accumulation in the model green alga Chlamydomonas reinhardtii: characterization, variability between common laboratory strains and relationship with starch reserves. BMC Biotechnol. 11, 7 (2011).
Bradley, I. M., Li, Y. & Guest, J. S. Solids Residence Time Impacts Carbon Dynamics and Bioenergy Feedstock Potential in Phototrophic Wastewater Treatment Systems. Environ. Sci. Technol. 55, 12574–12584 (2021).
Rieger, L. Guidelines for Using Activated Sludge Models. (IWA Publishing, London, New York, 2013).
Kazbar, A. et al. Effect of dissolved oxygen concentration on microalgal culture in photobioreactors. Algal Res. 39, 101432 (2019).
Molina, E., Fernández, J., Acién, F. G. & Chisti, Y. Tubular photobioreactor design for algal cultures. J. Biotechnol. 92, 113–131 (2001).
Pulz, O. Photobioreactors: production systems for phototrophic microorganisms. Appl Microbiol Biotechnol. 57, 287–293 (2001).
Vonshak, A., Torzillo, G., Accolla, P. & Tomaselli, L. Light and oxygen stress in Spirulina platensis (cyanobacteria) grown outdoors in tubular reactors. Physiol. Plant. 97, 175–179 (1996).
Rose, K. A., Smith, E. P., Gardner, R. H., Brenkert, A. L. & Bartell, S. M. Parameter sensitivities, monte carlo filtering, and model forecasting under uncertainty. J. Forecast. 10, 117–133 (1991).
Acknowledgements
The authors would like to acknowledge the CLEARAS Water Recovery staff, the Village of Roberts Director of Public Works, John Bond, and the Public Works staff for their on-site support and expertise. This work was funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, under Award Number DE-EE0009270. The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Energy.
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Conceptualization: G.-Y.K., B.D.S., and J.S.G.; Funding acquisition: J.S.G., I.M.B. and A.J.P.; Methodology: G.-Y.K., X.Z., B.D.S., S.M.S., E.M., S.D.S., and J.S.G.; Software: X.Z. and Y.L.; Experiments: H.R.M., G.-Y.K., and E.H.; Manuscript writing: G.-Y.K. and J.S.G. in collaboration with all authors.
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Kim, GY., Molitor, H.R., Zhang, X. et al. Development of an open-source process simulator for microalgae-based tertiary phosphorus recovery. npj Clean Water (2025). https://doi.org/10.1038/s41545-025-00545-4
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DOI: https://doi.org/10.1038/s41545-025-00545-4
