A novel mechanistic model for nitrogen removal in algal-bacterial photo sequencing batch reactors
[Display omitted] •A model was constructed for algal-bacterial photo sequencing batch reactors.•The kinetics of AOB, NOB and HB were coupled to those of microalgae.•The model considered variables such as light intensity, inorganic carbon, etc.•The model was evaluated by experimental data under highl...
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Veröffentlicht in: | Bioresource technology 2018-11, Vol.267, p.502-509 |
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Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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•A model was constructed for algal-bacterial photo sequencing batch reactors.•The kinetics of AOB, NOB and HB were coupled to those of microalgae.•The model considered variables such as light intensity, inorganic carbon, etc.•The model was evaluated by experimental data under highly different conditions.
A comprehensive mathematical model was constructed to evaluate the complex substrate and microbial interaction in algal-bacterial photo sequencing batch reactors (PSBR). The kinetics of metabolite, growth and endogenous respiration of ammonia oxidizing bacteria, nitrite oxidizing bacteria and heterotrophic bacteria were coupled to those of microalgae and then embedded into widely-used activated sludge model series. The impact of light intensity was considered for microalgae growth, while the effect of inorganic carbon was considered for each microorganism. The integrated model framework was assessed using experimental data from algal-bacterial consortia performing sidestream nitritation/denitritation. The validity of the model was further evaluated based on dataset from PSBR performing mainstream nitrification. The developed model could satisfactorily capture the dynamics of microbial populations and substrates under different operational conditions (i.e. feeding, carbon dosing and illuminating mode, light intensity, influent ammonium concentration), which might serve as a powerful tool for optimizing the novel algal-bacterial nitrogen removal processes. |
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ISSN: | 0960-8524 1873-2976 |
DOI: | 10.1016/j.biortech.2018.07.093 |