A rapid analytical method for predicting the oxygen demand of wastewater

被引:34
作者
Fogelman, Shoshana
Zhao, Huijun
Blumenstein, Michael
机构
[1] Griffith Univ, Sch Environm & Appl Sci, Fac Environm Sci, Australian Rivers Inst, Gold Coast, Qld 9726, Australia
[2] Griffith Univ, Sch Informat & Commun Technol, Fac Engn & Informat Technol, Gold Coast, Qld 9726, Australia
关键词
chemical oxygen demand; wastewater monitoring; UV-Vis spectrometry; artificial neural networks; multicomponent analysis;
D O I
10.1007/s00216-006-0817-3
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:1773 / 1779
页数:7
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