Emission Fluorescence Matrices Research Articles

Chemometric determination of PAHs in aerosol samples by fluorescence spectroscopy and second‐order data analysis algorithms

The development of a method based on the combination of excitation–emission fluorescence matrices (EEMs) and second‐order algorithms is proposed to identify and quantify 10 polycyclic aromatic hydrocarbons (PAHs) in extracts of aerosol samples, a particularly complex sample matrix because of the low amount of PAHs and the numerous fluorescent interferences. Parallel factor analysis, unfolded partial least squares coupled to residual bilinearization (RBL) and multivariate curve resolution – alternating least squares offered satisfactory results for their identification and quantification and were also helpful for the optimization of the extraction procedure for these substances by means of analysis of a standard reference material.Multivariate curve resolution – alternating least squares and parallel factor analysis combined with EEM proved to be fast and cheap analysis methods that are able to do semiquantitative monitoring of PAHs patterns in the inhalable and respirable fractions of atmospheric aerosols, important features for routine environmental monitoring. Accurate quantifications could also be achieved when the strategy of standard addition method was used.Unfolded partial least squares/RBL achieved slightly better quantitative results when sample matrices were moderately complex; in aerosol sample analysis, the selection of number of RBL contributions turned particularly difficult—because of the lack of information on the sample composition—and the time‐consuming application of the method did not suggest its use for routine environmental monitoring.Finally, results of EEM with second‐order methods in agreement with gas chromatography‐mass spectrometry analysis of ambient air samples proved the suitability of the methodology proposed because of the sensitivity of fluorescence measurements and the lower analytical cost and fast computation time compared with standard analytical procedures. Copyright © 2014 John Wiley & Sons, Ltd.

Comparison of second-order multivariate methods for screening and determination of PAHs by total fluorescence spectroscopy

This work explores the feasibility of screening and determination of ten polycyclic aromatic hydrocarbons (PAHs) through excitation–emission fluorescence matrices (EEMs) and in the presence of interferences by using different second-order data analysis algorithms: parallel factor analysis (PARAFAC), multivariate curve resolution–alternating least squares (MCR–ALS), and unfolded partial least squares coupled to residual bilinearization (U-PLS/RBL).The scope of the proposed techniques is discussed for qualitative and quantitative analysis of the selected PAHs in the presence of interferences and sample matrix effects. The target compounds were 9 of the 16 United States Environmental Protection Agency (US-EPA) priority PAHs: fluoranthene, benzo[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, dibenzo[a,h]anthracene, benzo[ghi]perylene, indeno[1,2,3-cd]pyrene, and one internal standard: 2-2′ binaphthyl.The suitability of these methods was compared under different chemical situations, where they were demonstrated to be powerful tools to resolve complex mixtures of analytes of similar structure in the presence of unexpected compounds. Qualitative and quantitative analysis of samples required the joint effort of the different algorithms to exploit the advantages of fast screening (PARAFAC and MCR–ALS) and accurate analyte determination (U-PLS/RBL) provided by the different methods.

Studying the Interaction of Pirarubicin with DNA and Determining Pirarubicin in Human Urine Samples: Combining Excitation -Emission Fluorescence Matrices with Second-order Calibration Methods

In this paper, UV-vis spectroscopy and fluorescence were combined to study the binding of Calf thymus DNA (ct-DNA) with the anthacycline antibiotic drug pirarubicin (THP). Ethidium bromide (EB) as the fluorescence probe was used to study the competitive binding interactions of THP with DNA by excitation-emission fluorescence matrices (EEFMs) coupled with the parallel factor analysis (PARAFAC) and the alternating normalization-weighted error algorithm (ANWE) with the second-order advantage. All the results conformed that THP mainly bound with DNA by intercalation. Meanwhile, the two second-order calibration methods have been successfully applied to quantify THP in urine samples. Figures of merit were applied to compare the performance of the two methods. The results presented in this work showed that both the PARAFAC and ANWE methods were the convincing way to be applied in the complex biological systems even in the presence of uncalibrated interferences.

Application of unfold principal component analysis and parallel factor analysis to the exploratory analysis of olive oils by means of excitation–emission matrix fluorescence spectroscopy

Discrimination between virgin olive oils and pure olive oils is of primary importance for controlling adulterations. Here, we show the potential usefulness of two multiway methods, unfold principal component analysis (U-PCA) and parallel factor analysis (PARAFAC), for the exploratory analysis of the two types of oils. We applied both methods to the excitation–emission fluorescence matrices (EEM) of olive oils and then compared the results with the ones obtained by multivariate principal component analysis (PCA) based on a fluorescence spectrum recorded at only one excitation wavelength. For U-PCA and PARAFAC, the ranges studied were λ ex=300–400 nm, λ em=400–695 nm and λ ex=300–400 nm, λ em=400–600 nm. The first range contained chlorophylls, whose peak was much more intense than those of the rest of species. The second range did not contain the chlorophylls peak but only the fluorescence spectra of the remaining compounds (oxidation products and Vitamin E). The three-component PARAFAC model on the second range was found to be the most interpretable. With this model, we could distinguish well between the two groups of oils and we could find the underlying fluorescent spectra of three families of compounds.