Modeling the decay of ammonium oxidizing bacteria
Giulio Munz1, Claudio Lubello, Jan A Oleszkiewicz
1Department of Civil Engineering, University of Manitoba, Winnipeg, Manitoba, Canada. giulio@dicea.unifi.it
Water Research
|October 12, 2010
Summary
Ammonium oxidizing biomass (AOB) decay is sensitive to oxygen levels, increasing significantly with higher concentrations. Unlike some models suggest, nitrite and nitrate absence had minimal impact on AOB decay rates.
Area of Science:
- Environmental microbiology
- Wastewater treatment engineering
- Biochemical kinetics
Background:
- Ammonium oxidizing biomass (AOB) is crucial for nitrification in wastewater treatment.
- Understanding AOB endogenous decay is vital for optimizing biological nutrient removal processes.
- Existing models often assume significant impacts of nitrite/nitrate on AOB decay, requiring experimental validation.
Purpose of the Study:
- To investigate factors influencing the endogenous decay of ammonium oxidizing biomass (AOB).
- To quantify AOB decay rates under varying oxygen, nitrite, and nitrate conditions.
- To develop and validate a simple expression for AOB decay.
Main Methods:
- Utilized a bench-scale sequencing batch reactor (SBR) for controlled experiments.
- Monitored AOB decay under different dissolved oxygen concentrations.
- Assessed the influence of anaerobic conditions, nitrite, and nitrate on decay rates.
- Calibrated and validated a proposed AOB decay expression using batch and continuous reactor data.
Main Results:
- AOB decay rate increased with oxygen concentration, reaching 0.4 d(-1) at 7 mg O(2) L(-1).
- Decay under anaerobic conditions was low (0.03 d(-1)), contrasting with some literature.
- Nitrite and nitrate absence showed a weak correlation with decay, challenging common assumptions in process models.
Conclusions:
- Oxygen concentration is a primary driver for AOB endogenous decay.
- The impact of nitrite and nitrate on AOB decay is less significant than often modeled.
- A validated simple expression for AOB decay was proposed, improving process modeling capabilities.
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