A novel control strategy for enhancing biological N-removal in a granular sequencing batch reactor: A model-based study

Eduardo Isanta, Mónica Figueroa, Anuska Mosquera-Corral, Luis Campos, Julián Carrera, Julio Pérez

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    17 Citations (Scopus)

    Abstract

    Biological nitrogen removal in aerobic granular sequencing batch reactors is sensitively affected by process conditions (e.g. dissolved oxygen (DO) concentration, nitrogen loading rate (NLR), influent C/N ratio, among others). The variation of one of these process conditions affects the others, because often they are tightly linked. These interrelationships are a drawback for the experimental assessment of the target domain of process conditions required to enhance N-removal. Here, we have developed a model to determine the guidelines to design an automatic control strategy with the final aim of enhancing biological N-removal in a granular sequencing batch reactor. The model was first calibrated with experimental data from a granular sequencing batch reactor treating swine wastewater. Specific simulations were designed to elucidate the effect of DO concentration (0.5-8mgO2L-1), granule size (0.5-3.5mm), influent C/N ratio (4-10gO2g-1N) and NLR (0.41-0.82gNL-1d-1) on the nitrification-denitrification efficiency. Simulation results showed that, in general, high N-removal efficiencies (from 70% to 85%) could be obtained only setting the appropriate DO concentration. That appropriate DO concentration could be easily found based on effluent ammonium concentration. Those results were used to propose a control strategy to enhance N-removal efficiencies. The control strategy was based on a closed DO loop with variable DO set-point. The DO set-point was established at a constant value for the whole cycle (i.e. once per cycle), based on the on-line measurement of ammonium concentration at the end of the previous cycle. © 2013 Elsevier B.V..
    Original languageEnglish
    Pages (from-to)468-477
    JournalChemical Engineering Journal
    Volume232
    DOIs
    Publication statusPublished - 1 Oct 2013

    Keywords

    • Aerobic granular sludge
    • Dissolved oxygen concentration
    • Mathematical modeling
    • Nitrification-denitrification
    • On-line ammonium concentration
    • Particle size

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