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Reduction and prediction of N2O emission from an Anoxic/Oxic wastewater treatment plant upon DO control and model simulation

Abstract : In order to make a better understanding of the characteristics of N2O emission in A/O wastewater treatment plant, full-scale and pilot-scale experiments were carried out and a back propagation artificial neural network model based on the experimental data was constructed to make a precise prediction of N2O emission. Results showed that, N2O flux from different units followed a descending order: aerated grit tank > oxic zone ≫ anoxic zone > final clarifier > primary clarifier, but 99.4% of the total emission of N2O (1.60% of N-load) was monitored from the oxic zone due to its big surface area. A proper DO control could reduce N2O emission down to 0.21% of N-load in A/O process, and a two-hidden-layers back propagation model with an optimized structure of 4:3:9:1 could achieve a good simulation of N2O emission, which provided a new method for the prediction of N2O emission during wastewater treatment. © 2017
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01581229
Contributor : Laurent Jonchère <>
Submitted on : Monday, September 4, 2017 - 2:38:48 PM
Last modification on : Thursday, March 5, 2020 - 2:04:24 PM

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S. Sun, Z. Bao, R. Li, D. Sun, H. Geng, et al.. Reduction and prediction of N2O emission from an Anoxic/Oxic wastewater treatment plant upon DO control and model simulation. Bioresource Technology, Elsevier, 2017, 244, pp.800--809. ⟨10.1016/j.biortech.2017.08.054⟩. ⟨hal-01581229⟩

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