Photocatalytic Degradation-Excitation−Emission Matrix Fluorescence for Increasing the Selectivity of Polycyclic Aromatic Hydrocarbon Analyses

Four- and five-way excitation-emission luminescence-based data acquisition and modeling for analytical applications. A review

The latest advances in both theory and experimental procedures on third-order/four-way and fourth-order/five-way calibration methods are discussed. This report is focused on excitation-emission (fluorescence and phosphorescence) matrices generation, employing different variables as the third data mode (time retention in chromatography, pH gradient, fluorescence/phosphorescence lifetime, kinetics, or other chemical treatments). Fully capitalizing on the second-order advantage, it has been possible to develop appealing analytical applications in spite of the complexity of the data. Extraction of the significant chemical information about the system under study as well as the individual abundance of the contributing constituents after proper higher-order data decomposition has allowed to analytical researchers performing quantitative analysis of complex samples. The experimental works reported up to the present are introduced and discussed in order to illustrate concepts. Throughout this work, the analytical benefits achieved by modeling third- and fourth-order data are exposed, attempting to contribute to the ongoing debate in the chemometric community regarding the existence and the true nature of the third-order advantage.

Comparison of several third-order correction algorithms applied to fluorescence excitation-emission-sample data array: Interference-free determination of polycyclic aromatic hydrocarbons in water pollution

Interference-free determination of polycyclic aromatic hydrocarbons (PAHs) in water pollution is proposed based on third-order correction algorithms with quadrilinear component modeling applied to the constructed four way fluorescence excitation-emission-sample data array with higher accuracy and better predictive ability than second-order (three-dimension) correction. Alternating weighted residue constraint quadrilinear decomposition (AWRCQLD), quadrilinear parallel factor analysis (4-PARAFAC), alternate penalty quadrilinear decomposition (APQLD) and alternate penalty trilinear decomposition (APTLD) are applied to acenaphthene (ANA), naphthalene (NAP) and fluorene (FLU) respectively. Fulvic acid affects PAHs determination seriously in real-world situation, so it is simulated as an interfering agent. Excitation-emission fluorescence matrixes (EEMs) of PAHs are measured at different volumes of fulvic acid simulated different interference conditions, to construct a four-way data array. After the four-way spectra data is analyzed by AWRCQLD, 4-PARAFAC, and APQLD, three-way EEMs analyzed by APTLD, results show that, on the one hand, PAHs can be measured more accurately with four-way data combined with third-order calibration than lower-order. On the other hand, AWRCQLD algorithm can reflect the superiority of third-order advantage better with higher recovery rate and smaller root mean square error, than other third-order or second-order correction algorithms.

Four-dimensional data coupled to alternating weighted residue constraint quadrilinear decomposition model applied to environmental analysis: Determination of polycyclic aromatic hydrocarbons

Qualitative and quantitative analysis of polycyclic aromatic hydrocarbons (PAHs) was carried out by three-dimensional fluorescence spectroscopy combining with Alternating Weighted Residue Constraint Quadrilinear Decomposition (AWRCQLD). The experimental subjects were acenaphthene (ANA) and naphthalene (NAP). Firstly, in order to solve the redundant information of the three-dimensional fluorescence spectral data, the wavelet transform was used to compress data in preprocessing. Then, the four-dimensional data was constructed by using the excitation-emission fluorescence spectra of different concentration PAHs. The sample data was obtained from three solvents that are methanol, ethanol and Ultra-pure water. The four-dimensional spectral data was analyzed by AWRCQLD, then the recovery rate of PAHs was obtained from the three solvents and compared respectively. On one hand, the results showed that PAHs can be measured more accurately by the high-order data, and the recovery rate was higher. On the other hand, the results presented that AWRCQLD can better reflect the superiority of four-dimensional algorithm than the second-order calibration and other third-order calibration algorithms. The recovery rate of ANA was 96.5%~103.3% and the root mean square error of prediction was 0.04μgL^-1. The recovery rate of NAP was 96.7%~115.7% and the root mean square error of prediction was 0.06μgL^-1.

Determination of polycyclic aromatic hydrocarbons by four-way parallel factor analysis in presence of humic acid

There is not effective method to solve the quenching effect of quencher in fluorescence spectra measurement and recognition of polycyclic aromatic hydrocarbons in aquatic environment. In this work, a four-way dataset combined with four-way parallel factor analysis is used to identify and quantify polycyclic aromatic hydrocarbons in the presence of humic acid, a fluorescent quencher and an ubiquitous substance in aquatic system, through modeling the quenching effect of humic acid by decomposing the four-way dataset into four loading matrices corresponding to relative concentration, excitation spectra, emission spectra and fluorescence quantum yield, respectively. It is found that Phenanthrene, pyrene, anthracene and fluorene can be recognized simultaneously with the similarities all above 0.980 between resolved spectra and reference spectra. Moreover, the concentrations of them ranging from 0 to 8μgL(-1) in the test samples prepared with river water could also be predicted successfully with recovery rate of each polycyclic aromatic hydrocarbon between 100% and 120%, which were higher than those of three-way PARAFAC. These results demonstrate that the combination of four-way dataset with four-way parallel factor analysis could be a promising method to recognize the fluorescence spectra of polycyclic aromatic hydrocarbons in the presence of fluorescent quencher from both qualitative and quantitative perspective.

Second order advantage applied to the spectrophotometric analysis of ciprofloxacin and dexamethasone in ophthalmic drops; automatic green method using on-line photodegradation

On-line photodegradation and spectrophotometric analysis assisted by multivariate curve resolution-alternating least squares (MCR-ALS) was developed the simultaneous determination of ciprofloxacin (CIP) and dexamethasone (DEX) in ophthalmic suspensions using an automated flow-batch analysis (FBA) system. CIP and DEX have strongly overlapped UV spectra. Overcoming this lack of selectivity involves augmenting data dimensionality. This could be performed by adding information about the sample photodegradation to obtain the so-called second order advantage. Commercial sample analysis was successfully performed and no statistical differences (α = 0.05) with respect to pharmacopeia methods were obtained. The proposed method offers several advantages over the methods developed to date. In agreement with the principles of green chemistry, only water was used as solvent, low amounts of waste were generated and on-line waste treatment was included in the system. Moreover, the cost per analysis was significantly reduced compared to methods that employ separative techniques.

Identification and quantification of known polycyclic aromatic hydrocarbons and pesticides in complex mixtures using fluorescence excitation-emission matrices and parallel factor analysis

Polycyclic aromatic hydrocarbons (PAHs) and pesticides are among the most widespread organic contaminants in aquatic environments. Because of their aromatic structure, PAHs and pesticides have intrinsic fluorescence properties in the ultraviolet/blue spectral range. In this study, excitation-emission matrix (EEM) fluorescence spectroscopy and parallel factor (PARAFAC) analysis were used to characterise and discriminate fluorescence signatures of nine PAHs and three pesticides at the μg L(-1) level in the presence of humic substances (0.1-10 mgCL(-1)). These contaminants displayed a diversity of fluorescence signatures regarding spectral position (λEx: 220-335 nm, λEm: 310-414 nm), Stokes shift (39-169 nm) and number of peaks (1-8), with detection limits ranging from 0.02 to 1.29μgL(-1). The EEM/PARAFAC method applied to mixtures of PAHs with humic substances validated a seven-component model that included one humic-like fluorophore and six PAH-like fluorophores. The EEM/PARAFAC method applied to mixtures of pesticides with humic substances validated a six-component model that included one humic-like fluorophore and three pesticide-like fluorophores. The EEM/PARAFAC method adequately quantified most of the contaminants for humic substance concentrations not exceeding 2.5 mg CL(-1). The application of this method to natural (marine) samples was demonstrated through (1) the match between the Ex and Em spectra of PARAFAC components and the Ex and Em spectra of standard PAHs, and (2) the good linear correlations between the fluorescence intensities of PARAFAC components and the PAH concentrations determined by GC-MS.

Coaxial fiber-optic chemical-sensing excitation-emission matrix fluorometer

Great reductions in the overall size and complexity of high throughput multichannel UV-visible fluorometers were achieved by coupling a compact optical fiber array to compact dispersive transmission optics. The coaxial configuration centers on the insertion of a silica/silica optical fiber into the hollow region of a UV-fused silica capillary waveguide. The outer core delivers the maximum power of the narrow wavelength region of the excitation spectrum created by coupling a xenon arc discharge lamp to a compact spectrometer. The molecular fluorescence resulting from the interaction of light emitted at the distal end of the hollow waveguide and the sample matrix is received and transmitted to a CCD via a compact dispersive grating-prism (grism) optical assembly. A linear array of the coaxial optical fibers permits a full excitation-emission matrix spectrum of the analyte matrix to be projected onto the face of the CCD. The in situ identification and monitoring of polycyclic aromatic hydrocarbons was carried out for the initial application testing for this prototype.

Nonlinear four-way kinetic-excitation-emission fluorescence data processed by a variant of parallel factor analysis and by a neural network model achieving the second-order advantage: malonaldehyde determination in olive oil samples

Four-way data were obtained by recording the kinetic evolution of excitation-emission fluorescence matrices for the product of the Hantzsch reaction between the analyte malonaldehyde and methylamine. The reaction product, 1,4-disubstituted-1,4-dihydropyridine-3,5-dicarbaldehyde, is a highly fluorescent compound. The nonlinear nature of the kinetic fluorescence data has been demonstrated, and therefore the four-way data were processed with parallel factor analysis combined with a nonlinear pseudounivariate regression, based on a quadratic polynomial fit, and also with a recently introduced neural network methodology, based on the combination of unfolded principal component analysis, residual trilinearization, and radial basis functions. The applied chemometric strategies are not only able to adequately model the nonlinear data but also to successfully determine malonaldehyde in olive oil samples. This is possible since the experimentally recorded four-way data, modeled with the above-mentioned advanced chemometric approaches, permit the achievement of the second-order advantage. This allows us to predict the analyte concentration in a complex background, in spite of the nonlinear behavior and in the presence of uncalibrated interferences. The present work is a new example of the use of higher-order data for the resolution of a complex nonlinear system, successfully employed in the context of food chemical analysis.