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Related Experiment Videos

The EAWAG Bio-P module for activated sludge model No. 3.

L Rieger1, G Koch, M Kühni

  • 1Swiss Federal Institute for Environmental Science and Technology (EAWAG) and Swiss Federal Institute of Technology (ETH), Dübendorf. rieger@eawag.ch

Water Research
|September 17, 2002
PubMed
Summary

A new module enhances biological phosphorus removal prediction using a modified ASM3 model. This model accurately simulates wastewater treatment data without complex fermentation or precipitation processes.

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Area of Science:

  • Environmental Engineering
  • Water Treatment Technologies
  • Biochemical Engineering

Background:

  • Biological phosphorus removal is crucial for wastewater treatment.
  • Existing models like ASM2d have limitations in predicting enhanced phosphorus removal.
  • Accurate modeling is needed for optimizing wastewater treatment plant (WWTP) performance.

Purpose of the Study:

  • To develop and calibrate an additional module for predicting enhanced biological phosphorus removal.
  • To integrate this module with a calibrated version of the Activated Sludge Model No. 3 (ASM3).
  • To validate the model's performance using diverse experimental and full-scale data.

Main Methods:

  • Modified processes from ASM2d were adapted, excluding readily degradable substrate fermentation.

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  • Biomass decay was modeled using endogenous respiration, consistent with ASM3.
  • The model did not incorporate an additional glycogen pool or biologically induced phosphorus precipitation.
  • Systematic calibration was performed using batch experiments, a full-scale WWTP, and a pilot plant dataset.

    • Main Results:

    • The developed module, based on a calibrated ASM3, successfully predicted enhanced biological phosphorus removal.
    • A standard parameter set enabled accurate simulation of data from various sources.
    • The model demonstrated robustness across different experimental and operational conditions.

    Conclusions:

    • The proposed module provides a reliable tool for predicting enhanced biological phosphorus removal.
    • The model's simplified approach, omitting fermentation and precipitation, still achieves accurate predictions.
    • This advancement aids in the optimization and design of WWTPs for improved phosphorus management.