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Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received August 6, 2009
Accepted September 21, 2009

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Optimal strategies of fill and aeration in a sequencing batch reactor for biological nitrogen and carbon removal

Moo Hwan Cho^† Jintae Lee Joon Ha Kim¹ Henry C. Lim²

School of Display and Chemical Engineering, Yeungnam University, Gyeongsan, Gyeongbuk 712-749, Korea ¹Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology, Gwangju 500-712, Korea ²Department of Chemical Engineering and Material Science, University of California, Irvine, CA 92697, USA

Korean Journal of Chemical Engineering, March 2010, 27(3), 925-929(5), 10.1007/s11814-010-0122-x

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Abstract

A modified version of the IAWQ activated sludge model No. 1 (ASM 1) is adopted for the simulation of a sequencing batch reactor (SBR) to optimize the removal of nitrogen (T-N) and organic matters (COD) from wastewater. Since the removal of nitrogen requires both aerobic nitrification and anaerobic denitrification, we seek to find the optimal strategies of substrate fill and aeration. Substrate filling strategy critically influences the removal efficiency of T-N and COD; one fast discrete fill in the beginning of a cycle leads to the best result, while a slow continuous fill_x000D_ results in poor nitrification. In addition, the total aeration time is more important for the removal efficiency than the aeration frequency. A short aeration is beneficial for T-N removal, while a long aeration is beneficial for COD removal as expected. As a result, there is an optimal condition of aeration for the simultaneous removal of T-N and COD.

Keywords

Wastewater Treatment Nitrogen Removal Sequential Batch Reactor Optimization Strategy

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