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A general kinetic model for biological nutrient removal activated sludge systems: model evaluation.

Zhi-rong Hu1, M C Wentzel, G A Ekama

  • 1Water Research Group, Department of Civil Engineering, University of Cape Town, Rondebosch 7701, Cape Town, South Africa. zhironghu@yahoo.com

Biotechnology and Bioengineering
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This study validates a kinetic model for biological nutrient removal activated sludge systems. The model accurately predicts COD removal, nitrification, denitrification, and phosphorus removal in both conventional and external nitrification systems.

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Area of Science:

  • Environmental Engineering
  • Wastewater Treatment Technologies
  • Biotechnology

Background:

  • Biological nutrient removal (BNR) activated sludge (AS) systems are crucial for wastewater treatment.
  • Existing models require validation for diverse configurations like external nitrification (EN) BNRAS (ENBNRAS) systems.
  • Accurate kinetic modeling is essential for optimizing treatment efficiency and predicting system behavior.

Purpose of the Study:

  • To evaluate the predictive capabilities of a general kinetic model for BNRAS systems, specifically ENBNRAS.
  • To assess the model's performance against extensive experimental data for both internal nitrification (IN) and external nitrification (EN) configurations.
  • To calibrate model parameters for improved accuracy in simulating various nutrient removal processes.

Main Methods:

  • Simulation of conventional INBNRAS systems using the Hu et al. (2007) kinetic model.
  • Evaluation and calibration of model parameters against experimental datasets.
  • Simulation of ENBNRAS systems to assess model applicability to external nitrification processes.
  • Comparison of model predictions with experimental data for COD removal, nitrification, denitrification, and biological excess phosphorus removal (BEPR).

Main Results:

  • The kinetic model, with calibrated parameters, accurately predicts COD removal, nitrification, denitrification, and both aerobic and anoxic/aerobic BEPR in INBNRAS systems.
  • The model successfully simulates the behavior of ENBNRAS systems, including COD, nitrification, denitrification, and particularly anoxic P uptake BEPR.
  • Kinetic and stoichiometric parameters from INBNRAS modeling were largely applicable to ENBNRAS, with only specific parameters (micro(NIT), K(MP), eta(PAO), eta(H)) requiring calibration.

Conclusions:

  • The generalized kinetic model is robust and capable of simulating a wide range of BNRAS systems, including complex ENBNRAS configurations.
  • Model calibration enhances its predictive power for key wastewater treatment performance indicators.
  • The study provides a validated modeling framework for optimizing BNRAS and ENBNRAS processes.