Comparing two empirical models used to predict process parameter dynamics during ozonation of synthetic dye wastewater
Ozonation of a synthetic wastewater contaminated with acid yellow 17 dye and glucose was evaluated in a semi-batch bubble column. Data collected during this study suggests that the ozonation process removed color (represented as A 400 ) more efficiently than chemical oxygen demand (COD) regardless o...
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Published in | Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering Vol. 44; no. 2; pp. 192 - 197 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Philadelphia, PA
Taylor & Francis Group
01.01.2009
Taylor & Francis |
Subjects | |
Online Access | Get full text |
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Summary: | Ozonation of a synthetic wastewater contaminated with acid yellow 17 dye and glucose was evaluated in a semi-batch bubble column. Data collected during this study suggests that the ozonation process removed color (represented as A
400
) more efficiently than chemical oxygen demand (COD) regardless of initial experimental conditions. With a 40-minute run time, the maximum A
400
and COD removal efficiencies were 99.9 and 52.9%, respectively. Results indicated that the addition of COD to the system in the form of glucose had no effect on color removal efficiencies. The removal efficiencies of both color (A
400
) and COD in relation to the ozone utilized by the system were modeled using two previously derived empirical methods. Linear regression analysis was used to evaluate the effectiveness of both models to predict removal efficiencies of process parameters such as color and COD and to estimate ozone utilization. Results indicate both models predict color (A
400
) and COD removal as well as ozone utilization, but care should be taken when using the models to describe removal efficiencies when the wastewater inlet characteristics are variable. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 1093-4529 1532-4117 |
DOI: | 10.1080/10934520802539871 |