An N₂O emissions model featuring newly integrated abiotic pathways in nitrification

Area of Science:

• Environmental Science
• Environmental Engineering
• Biogeochemistry

Background:

• Biological nitrification in wastewater treatment is a major source of nitrous oxide (N₂O), a potent greenhouse gas (GHG).
• Existing models often neglect abiotic N₂O production pathways, which can account for up to 50% of total emissions under high nitrite conditions.
• This omission leads to significant predictive biases, particularly in partial nitrification/Anammox systems, hindering effective mitigation efforts.

Purpose of the Study:

• To address the gap in current models by integrating a key abiotic N₂O production pathway into an existing biological nitrification model.
• To improve the accuracy of N₂O emission predictions in wastewater treatment processes.
• To provide a more robust tool for developing effective N₂O mitigation strategies.

Main Methods:

• Integrated a crucial abiotic N₂O production pathway into a pre-existing model of biological nitrification and N₂O emissions.
• Evaluated the upgraded model's performance using literature-derived case studies.
• Conducted local and global sensitivity analyses to assess model resilience and identify key controlling factors.

Main Results:

• The upgraded model accurately predicted the contribution of the abiotic pathway to N₂O emissions (49% predicted vs. 51% experimental).
• Local sensitivity analysis indicated model resilience, with high nitrite concentrations (>1,000 mg N/L) requiring precise calibration of ammonium oxidation to nitrite (AOB process).
• Global sensitivity analysis identified dissolved oxygen (DO) and alkalinity as the most influential environmental factors controlling N₂O emissions.

Conclusions:

• The integration of abiotic pathways significantly enhances the predictive capability of nitrification models for N₂O emissions.
• The model provides a more reliable tool for understanding and mitigating greenhouse gas emissions from wastewater treatment.
• Dissolved oxygen and alkalinity are critical parameters for managing N₂O production in these systems.