A rapid analytical method for predicting the oxygen demand of wastewater

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Title A rapid analytical method for predicting the oxygen demand of wastewater
Author Zhang, Shanqing; Zhao, Huijun; Blumenstein, Michael Myer
Journal Name Analytical & Bioanalytical Chemistry
Year Published 2006
Place of publication Heidelberg, Germany
Publisher Springer -Verlag
Abstract In this study, an investigation was undertaken to determine whether the predictive accuracy of an indirect, multiwavelength spectroscopic technique for rapidly determining oxygen demand (OD) values is affected by the use of unfiltered and turbid samples, as well as by the use of absorbance values measured below 200 nm. The rapid OD technique was developed that uses UV–Vis spectroscopy and artificial neural networks (ANNs) to indirectly determine chemical oxygen demand (COD) levels. It was found that the most accurate results were obtained when a spectral range of 190–350 nm was provided as data input to the ANN, and when using unfiltered samples below a turbidity range of 150 NTU. This is because high correlations of above 0.90 were obtained with the data using the standard COD method. This indicates that samples can be measured directly without the additional need for preprocessing by filtering. Samples with turbidity values higher than 150 NTU were found to produce poor correlations with the standard COD method, which made them unsuitable for accurate, real-time, on-line monitoring of OD levels.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/s00216-006-0817-3
Volume 386
Page from 1773
Page to 1779
ISSN 1618-2642
Date Accessioned 2007-03-01
Date Available 2010-08-26T07:35:50Z
Language en_AU
Research Centre Environmental Futures Research Institute; Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Sensor (Chemical and Bio-) Technology
URI http://hdl.handle.net/10072/14408
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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