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Ozone: Science & Engineering
The Journal of the International Ozone Association
Volume 36, 2014 - Issue 5
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Original Articles

Regression Modeling of Ozonation Process in Wastewater Treatment Plants for Reduction of Waste Activated Sludge

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Pages 451-464 | Received 18 Aug 2013, Accepted 21 Jan 2014, Published online: 11 Sep 2014
 

Abstract

This research was based on the hypothesis that waste activated sludge (WAS) from municipal wastewater treatment plants can be reduced by ozonation of excess biosolids to induce cell lysis and by promoting utilization of intracellular products released by ozonation of biosolids in the aeration basins. In this research, mathematical modeling studies were performed in order to define process design and major components of ozonation. The main purpose of the model simulations was to evaluate the effect of operational parameters of the ozonation system (such as dosage and duration of ozonation) and to determine the amount of solids to be ozonated in order to achieve desired mass reductions in WAS. This modeling study focused on identification of design parameters and their suggested range of operation. The model presented in this study does not intend to detail and analyze the impact of the scientific variables in the ozonation mechanism, nor does it try to model the biosolids destruction mechanisms when ozonation is applied. The computer model simulations indicated that zero biosolids yield conditions can be achieved if more biosolids than was grown on the influent wastewater was processed through the ozonation system. The simulations suggested that zero biosolids yield conditions can be observed if 2.4 times as much biosolids as was grown on the influent wastewater was processed through the ozonation column, with a daily R of about 0.08 mg O3/mg TSS-day. Furthermore, zero biosolids yield conditions can also be observed if only the amount of waste biosolids grown on the influent wastewater was processed through the ozonation column with a higher average daily R of 0.2 mg O3/mg TSS-day.

ACKNOWLEDGMENT

The authors would like to thank Dr. Nirmalakhandan for his support and guidance through the initial phases of this research. This study was conducted using the laboratory equipment and supplies provided by Dr. Nirmalakhandan. His support and ideas during the development of the original LCWWTP model is appreciated.

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