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A rapid analytical method for predicting the oxygen demand of wastewater

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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.

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Authors and Affiliations

  1. Australian Rivers Institute, School of Environmental and Applied Sciences, Faculty of Environmental Sciences, Gold Coast Campus, Griffith University, PMB 50 Gold Coast Mail Centre, 9726, QLD, Australia

    Shoshana Fogelman & Huijun Zhao

  2. School of Information and Communication Technology, Faculty of Engineering and Information Technology, Gold Coast Campus, Griffith University, PMB 50 Gold Coast Mail Centre, 9726, QLD, Australia

    Michael Blumenstein

Authors
  1. Shoshana Fogelman
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  2. Huijun Zhao
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  3. Michael Blumenstein
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Corresponding author

Correspondence to Shoshana Fogelman.

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Fogelman, S., Zhao, H. & Blumenstein, M. A rapid analytical method for predicting the oxygen demand of wastewater. Anal Bioanal Chem 386, 1773–1779 (2006). https://doi.org/10.1007/s00216-006-0817-3

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  • DOI: https://doi.org/10.1007/s00216-006-0817-3

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