Multivariate Calibration of a UV-Vis Spectrophotometer Used for Online Measurements of Chemical Oxygen Demand in Dyeing Wastewater

In order to realize the on-line measurement of chemical oxygen demand (COD) in dyeing wastewater after sewage treatment, and to overcome the disadvantages of the standard method and the rapid spectrophotometric method, a COD detection method based on UV-Vis spectroscopy with multivariate calibration was developed in this study. The mixtures of dyes were selected as the researching examples. A novel self-developed optical fibre sensor system was used to directly measure UV-Vis spectroscopy of dye solution. The system could realize on-line in-situ detection of the spectrum for higher concentration solution, without sampling and dilution process. In this study, both methods, principal component regression (PCR) and partial least squares (PLS), were used to develop regression models (Absorbance-COD) respectively to predict COD of training set and prediction set after the spectrum preprocessing including z-score, smoothing, 1st derivation, etc. With experiments using mixtures of dyes solution, the results show that PCR model with z-score preprocessing performed best in the three preprocessing methods (0. 961 for determination coefficient 122, 21. 8 for root mean square error of prediction (RMSEP)). Further study identified that using z-score, PLS model (0. 974 for R-2, 19. 6 for RMSEP) achieved better results than PCR did. The results indicated that without the process of digestion, it was feasible to use UV-Vis combined with z-score preprocessing and PLS calibration for COD detection. The method could apply to the rapid and accurate determination of COD in mixtures dyes solution and proved to be successful in enhancing the prediction performance of COD and showed good potential to be applied in on-line water quality monitoring. The overall results showed that the self-developed system could be applied to on-line detection of COD in mixtures dyes solution. This study laid a foundation for further implementation of on-line in-situ detection of COD and other water quality parameters of dyeing wastewater.