Model based optimization of partial nitrification by monitoring nitrous oxide (N2O) emission

被引:3
|
作者
Wu, Jun [1 ]
Xu, Ting [1 ]
Jiang, Xinyue [1 ]
Yan, Gang [1 ]
Yu, Lingtang [1 ]
机构
[1] Yangzhou Univ, Sch Environm Engn & Sci, 196 West Huayang Rd, Yangzhou 225127, Jiangsu, Peoples R China
来源
关键词
Model based optimization; Model predictive control; Partial nitrification; Nitrous oxide emission; Oxygen transfer coefficient;
D O I
10.1016/j.jece.2015.05.017
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The successful operation of partial nitrification relies on the optimal condition in which the ammonia oxidizing bacteria (AOB) is favored over nitrite oxidizing bacteria (NOB). The fluctuation of influent load means the optimal condition varies dynamically. The routine monitoring such as dissolved oxygen (DO), nitrite and ammonia concentration is usually used for the system optimization. The sensors used for these routine monitoring are usually submerged in a hostile activated sludge environment and are subjected to sensor fouling. In this paper, the non-invasive off-gas nitrous oxide (N2O) monitoring was used for the optimization of partial nitrification. An empirical N2O emission model and a two-step nitrification activated sludge model No. 1 (ASM1) were used for the optimization study based on the concept of model predictive control. The results indicated that the non-invasive N2O monitoring can be used as an alternative to the nitrite and ammonia sensor for the optimization of partial nitrification process. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1602 / 1613
页数:12
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