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A generalized model for aerobic granule-based sequencing batch reactor. 1. Model development.

Kui-Zu Su1, Han-Qing Yu

  • 1School of Chemistry, University of Science & Technology of China, Hefei, Anhui, 230026 China.

Environmental Science & Technology
|August 18, 2006
PubMed
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A generalized model simulates aerobic granule sequencing batch reactors (SBRs), improving accuracy by refining biological process descriptions and incorporating granule characteristics. This validated model aids in understanding SBR performance and optimizing wastewater treatment.

Area of Science:

  • Environmental Engineering
  • Biotechnology
  • Chemical Engineering

Background:

  • Aerobic granule-based sequencing batch reactors (SBRs) are crucial for advanced wastewater treatment.
  • Accurate modeling is essential for optimizing SBR performance and understanding complex biological and physical processes.

Purpose of the Study:

  • To develop and validate a generalized model for aerobic granule SBRs.
  • To investigate the influence of granule characteristics on reactor performance.
  • To enhance the understanding of biological processes, hydrodynamics, mass transfer, and diffusion within SBRs.

Main Methods:

  • A discretization methodology was employed for model development and calculations.
  • The Activated Sludge Model No. 1 was modified to represent biological processes within granules.

Related Experiment Videos

  • Model structure was refined based on discrepancies between calculated and measured results, including simultaneous substrate consumption.
  • Main Results:

    • The model accurately simulates aerobic granule SBRs, considering biological processes, hydrodynamics, mass transfer, and diffusion.
    • Calculations revealed the contributions of different granule sizes and slices to concentration changes.
    • Oxygen concentration profiles and consumption rates within granules varied throughout the operating cycle.

    Conclusions:

    • The developed model and discretization method are applicable and valid for simulating aerobic granule SBRs.
    • The refined model provides insights into the spatial and temporal variations of key components within granules.
    • This study enhances the predictive capability for optimizing SBR operations in wastewater treatment.