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A novel mechanistic model for nitrogen removal in algal-bacterial photo sequencing batch reactors

Journal Article


Abstract


  • 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.

UOW Authors


  •   Nghiem, Long (external author)

Publication Date


  • 2018

Citation


  • Peng, L., Ngo, H. H., Guo, W. S., Liu, Y., Wang, D., Song, S., . . . Ni, B. J. (2018). A novel mechanistic model for nitrogen removal in algal-bacterial photo sequencing batch reactors. Bioresource Technology, 267, 502-509. doi:10.1016/j.biortech.2018.07.093

Scopus Eid


  • 2-s2.0-85050140805

Start Page


  • 502

End Page


  • 509

Volume


  • 267

Abstract


  • 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.

UOW Authors


  •   Nghiem, Long (external author)

Publication Date


  • 2018

Citation


  • Peng, L., Ngo, H. H., Guo, W. S., Liu, Y., Wang, D., Song, S., . . . Ni, B. J. (2018). A novel mechanistic model for nitrogen removal in algal-bacterial photo sequencing batch reactors. Bioresource Technology, 267, 502-509. doi:10.1016/j.biortech.2018.07.093

Scopus Eid


  • 2-s2.0-85050140805

Start Page


  • 502

End Page


  • 509

Volume


  • 267