Article ID Journal Published Year Pages File Type
4996549 Bioresource Technology 2017 10 Pages PDF
Abstract

•The N2O emission factor of A/O WWTP was 1.60% of N-load.•A proper control of DO could remarkably reduce N2O emission in A/O process.•A BP-ANN model simulating N2O emission from A/O process was established.•The two-hidden-layers model could achieve a good prediction of N2O emission.

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.

Related Topics
Physical Sciences and Engineering Chemical Engineering Process Chemistry and Technology
Authors
, , , , , , , , , , , ,