High-performance liquid chromatographic determination of phenolic compounds in natural water coupled with on-line flow injection membrane extraction-preconcentration

Determination of phenolic compounds in water using a multivariate statistical analysis method combined with three-dimensional fluorescence spectroscopy

Phenolic compounds are toxic chemical pollutants present in water. Three-dimensional fluorescence spectroscopy analysis is an effective and rapid method for real-time phenol monitoring in aquatic environments. However, similar chemical structures of phenols result in highly overlapping three-dimensional fluorescence spectra. Therefore, it is extremely difficult to analyze and quantify the concentration of components in a mixture system that includes two or more phenolic compounds. In this article, we study the mixed phenol system containing phenol, o-cresol, p-cresol, m-cresol, catechol, and resorcinol combined with excitation-emission matrix (EEM) fluorescence data. A multivariate statistical method called best linear unbiased prediction (BLUP) is proposed to analyze the spectra with the aim to achieve quantitative results and a trilinear decomposition algorithm called parallel factor analysis (PARAFAC) was used for comparison. Two experiments with different calibration samples were set to validate the effectiveness of BLUP through recovery, ARecovery (Average Recovery), AREP (Average Relative Error of Prediction), and RMSE (Root Mean Square Error). Overall, the average recovery of each component in experiment 1 and experiment 2 ranged from 95.91% to 111.62% and 82.91% to 129.02%, respectively. Based on the results of the experiments, the concentration of phenolic compounds in water can be quantitatively determined by combining three-dimensional fluorescence spectroscopy with the BLUP method.

Simultaneous measurement of phenols by three-way fluorescence spectroscopy: A comparison of N-PLS/RBL, U-PLS/RBL and PARAFAC

Phenol, o-cresol, p-cresol, catechol and resorcinol are five phenolic compounds with extremely similar structure. Their fluorescence spectra are hard to be analyzed because of the serious spectral overlaps between any two of the five phenolic components in the mixture system. In this experiment, multi-dimensional partial least-squares (N-PLS), unfolded partial least-squares (U-PLS) with residual bilinearization (RBL) and parallel factor analysis (PARAFAC) are employed to analyze the three-way fluorescence spectra aiming to achieve quantitative results. Meanwhile, a contrast of these three methods is given. The experiment results show that N-PLS/RBL and U-PLS/RBL algorithms are superior to PARARFAC in terms of analysis of highly overlapping three-way fluorescence spectra for concentration determination.