An N2O emissions model featuring newly integrated abiotic pathways in nitrification

Journal Article (2026)
Author(s)

Wenbo Yu (Beijing University of Civil Engineering and Architecture)

Xiaodi Hao (Beijing University of Civil Engineering and Architecture)

Yuanyuan Wu (Beijing University of Civil Engineering and Architecture)

Mark C.M. van Loosdrecht (Beijing University of Civil Engineering and Architecture, TU Delft - BT/Environmental Biotechnology)

Research Group
BT/Environmental Biotechnology
DOI related publication
https://doi.org/10.1016/j.watres.2025.125096
More Info
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Publication Year
2026
Language
English
Research Group
BT/Environmental Biotechnology
Journal title
Water Research
Volume number
290
Article number
125096
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9
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Abstract

Nitrification in biological wastewater treatment is a significant source of nitrous oxide (N2O), a potent greenhouse gas (GHG). There are some models that describe the biological N2O production process, but they don't include abiotic N2O production pathways which, remarkably, contribute up to 50% of the total N2O emissions under high nitrite (NO2-) conditions. This limitation frequently results in pronounced predictive biases under high influent ammonium (NH4+) and intermediate NO2- conditions (such as in the partial nitrification + Anammox system), leading to the misidentification of N2O emissions, undermining the development of effective mitigation strategies. To address this gap, a key abiotic N2O production pathway was integrated into an existing model of nitrification which includes biological N2O emissions. The upgraded model was systematically evaluated using literature-derived case studies, and can effectively predict the contributions of the abiotic pathway to N2O emissions (49%), compared to experimental data (51%). A local sensitivity analysis confirms that the upgraded model has a resilience to perturbations within most parameters, although very high concentrations of NO2- (>1,000 mg N/L) necessitate a precise calibration of ammonium oxidation to nitrite (the AOB process), in which related parameters can more easily be measured in experiments. Moreover, a global sensitivity analysis demonstrates that dissolved oxygen (DO) and alkalinity are the most sensitive of the four key environmental factors (NH4+, NO2-, DO and alkalinity) which control N2O emissions.

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