Long-term dynamic and pseudo-state modeling of complete partial nitrification process at high nitrogen loading rates...

Area of Science:

• Environmental Engineering
• Wastewater Treatment Technologies
• Biochemical Engineering

Background:

• Partial nitrification is crucial for the nitrite shunt and Anammox processes in wastewater treatment.
• Maintaining stable nitrite accumulation at high nitrogen loading rates (NLR) remains a significant challenge, impacting process feasibility for high-nitrogen wastewater.
• Existing methods for modeling such processes often require complex respirometric analysis.

Purpose of the Study:

• To calibrate and validate a BioWin® process model for a lab-scale sequencing batch reactor (SBR) performing partial nitrification.
• To describe the long-term dynamic behavior of the SBR under varying operational conditions.
• To introduce an identifiability analysis to simplify SBR model calibration, removing the need for respirometric analysis.

Main Methods:

• Utilized operational data from a lab-scale SBR operating at nitrogen loading rates (NLRs) from 0.3-1.2 kg/(m³d).
• Employed a process model developed in BioWin® for calibration and validation.
• Integrated an identifiability analysis into the calibration protocol.

Main Results:

• The calibrated model accurately predicted daily effluent concentrations of ammonia, nitrate, and nitrite.
• The model also accurately predicted effluent alkalinity and pH across different operational conditions.
• The identifiability analysis successfully eliminated the requirement for respirometric analysis during calibration.

Conclusions:

• The validated BioWin® model provides an accurate representation of partial nitrification in an SBR.
• The model enhances the understanding and prediction of process performance, supporting the feasibility of the nitrite shunt process.
• The integrated identifiability analysis offers a more efficient approach to SBR model calibration for wastewater treatment applications.