Reduction and prediction of N2O emission from an Anoxic/Oxic wastewater treatment plant upon DO control and model simulation
Reduction and prediction of N2O emission from an Anoxic/Oxic wastewater treatment plant upon DO control and model simulation
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基于 DO 控制和模型模拟的缺氧/好氧废水处理厂 N2O 排放减少和预测
DOI：
10.1016/j.biortech.2017.08.054
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发表时间：
2017
影响因子：
11.4
通讯作者：
Zhao Xuxin
中科院分区：
文献类型：
--
作者：
Sun Shichang;Bao Zhiyuan;Li Ruoyu;Sun Dezhi;Geng Haihong;Huang Xiaofei;Lin Junhao;Zhang Peixin;Ma Rui;Fang Lin;Zhang Xianghua;Zhao Xuxin
为了更好地了解a /O污水处理厂N2O排放特征，开展了全规模和中试实验，并基于实验数据构建了反向传播人工神经网络模型，对N2O排放进行了精确预测。结果表明：不同单元的N2O通量大小依次为：曝气砂池>氧区>缺氧区>终澄清池>主澄清池，但由于氧区表面积大，N2O总排放量的99.4% （n -负荷的1.60%）来自氧区。适当的DO控制可使A/O过程中N2O排放量降至n负荷的0.21%，且优化结构为4:3:9:1的两隐层反向传播模型可以很好地模拟N2O排放，为污水处理过程中N2O排放的预测提供了一种新的方法。
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.