Models for nitrification process design: one or two AOB populations?

Area of Science:

• Environmental microbiology
• Wastewater engineering
• Bioprocess modeling

Background:

• Nitrification models traditionally use a single ammonia oxidizer biomass (AOB) state variable.
• This simplification limits predictive accuracy in dynamic environments.

Purpose of the Study:

• To enhance nitrification system modeling by incorporating two distinct AOB populations.
• To investigate the impact of process conditions on AOB competition and dynamics.

Main Methods:

• Developed a two-state AOB model with differing kinetic parameters.
• Analyzed AOB population dynamics under varying temperature, internal mixed liquor recycle rate (IMLR), and sludge transfer conditions through three case studies.

Main Results:

• The two-state model accurately predicts nitrification in switching environments.
• Demonstrated temperature sensitivity differences influencing AOB dynamics during bioaugmentation.
• Showcased competition dynamics between fast-growing and K-strategist AOB based on IMLR.
• Illustrated AOB overgrowth or coexistence based on differing decay kinetics after sludge transfer.

Conclusions:

• A two-state AOB model provides superior prediction accuracy for nitrification systems.
• Process conditions significantly dictate competitive advantages and population dynamics of AOB.
• This modeling approach is crucial for optimizing wastewater treatment plant operations.