Abstract
Competition for electrons among different steps of denitrification has previously been shown to occur, and to play an important role in the accumulation and emission of N2O in wastewater treatment. However, this electron competition is not recognized in the current denitrification models, limiting their ability to predict N2O accumulation during denitrification. In this work, a new denitrification model is developed for wastewater treatment processes. It describes electron competition among the four steps of denitrification, through modeling the carbon oxidation and nitrogen reduction processes separately, in contrast to the existing models that directly couple these two types of processes. Electron carriers are introduced to link carbon oxidation, which donates electrons to carriers, and nitrogen oxides reduction, which receives electrons from these carriers. The relative ability of each denitrification step to compete for electrons is modeled through the use of different affinity constants with reduced carriers. Model calibration and validation results demonstrate that the developed model is able to reasonably describe the nitrate, nitrite, and N2O reduction rates of a methanol-utilizing denitrifying culture under various carbon and nitrogen oxides supplying conditions. The model proposed, while subject to further validation, is expected to enhance our ability to predict N2O accumulation in denitrification. © 2013 American Chemical Society.
| Original language | English |
|---|---|
| Pages (from-to) | 11083-11091 |
| Journal | Environmental Science and Technology |
| Volume | 47 |
| Issue number | 19 |
| DOIs | |
| Publication status | Published - 1 Oct 2013 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
This study was funded by the Australian Research Council, Western Australia Water Corporation and Melbourne Water Corporation through projects LP0991765 and DP0987204. Y.P. acknowledges UQ Research Scholarship (UQRS) support. B.-J.N. acknowledges the support of Australian Research Council Discovery Early Career Researcher Award (DE130100451) and The University of Queensland (UQ) Postdoctoral Fellowship.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
Policy Impact
- Cited in Policy Documents
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