Single-Measurement Excitation/Emission Matrix Spectrofluorometer for Determination of Hydrocarbons in Ocean Water. 2. Calibration and Quantitation of Naphthalene and Styrene

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). The use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

Interference-free quantitation of aromatic amino acids in two complex systems by three-way calibration with ultraviolet-visible spectrophotometer: Exploration of trilinear decomposition of spectrum-pH data

Aromatic amino acids play an extremely important role in life activities and participate in many biological processes. Their concentration levels are associated with a variety of diseases, such as phenylketonuria and colorectal cancer. Therefore, the quantification of aromatic amino acids is an important task. In the present work, a novel and rapid three-way analytical method was proposed to detect the levels of aromatic amino acids in prostate cancer cells (PC3 cells) and Dulbecco's modified minimal essential medium (DMEM cell culture), by using the affordable ultraviolet-visible spectrophotometer. First, spectrum-pH second-order data were designed per sample; Second, properties of the resulted spectrum-pH-sample three-way data were investigated by utilizing the parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), and constrained alternating trilinear decomposition (CATLD) algorithms, and a flexible scanning approach for determining the constraint parameters of CATLD was proposed; Third, a three-way calibration method based on the CATLD algorithm with the proposed scanning approach was developed for interference-free quantification of aromatic amino acids in these systems. The average relative predictive errors of validation (ARPEV) for phenylalanine, tyrosine, and tryptophan were 1.4%, 3.0%, and 0.7% in prostate cancer cells, and ARPEV for phenylalanine, tyrosine, and tryptophan were 4.1%, 1.2%, and 0.7% in DMEM cell culture. The predicted contents of tyrosine and tryptophan in DMEM cell culture were 64.2 ± 2.9 μg mL^-1, 5.6 ± 0.3 μg mL^-1, there are no significant differences in the concentrations between the developed analytical method and high performance liquid chromatography method. The proposed spectrum-pH-sample three-way calibration method based on CATLD algorithm can provide an interesting analytical strategy with high selectivity and accuracy for ultraviolet-visible spectrophotometer.

Inhibition of typical phenolic compounds entering into condensed freshwater by surfactants during solar-driven seawater distillation

Recently, solar-driven seawater desalination based on air-water interfacial heating has triggered significant research interest due to its high water evaporation rate, high photothermal conversion efficiency, low energy consumption, simple operation and low cost. However, as the air-water interface temperature reaches as high as 40-70 °C, volatile organic compounds (VOCs) will volatilize into the condensed desalinated water and results in the polluted freshwater. In this work, anionic, cationic, and nonionic surfactants were applied for the first time to inhibit the phenolic compounds such as phenol, p-methylphenol and p-chlorophenol entering into the condensed freshwater. Results showed that the concentration of phenol could be reduced by the addition of cetyl trimethyl ammonium bromide (CTAB). The phenol's distillation concentration ratio (R_D) reduced from 76% to 35% due to the electrostatic interaction and the micellar encapsulation between the CTAB and phenol. Moreover, parameters including CTAB dose, initial phenol concentration, solar intensity, pH, and salinity that affecting the R_D were also investigated. Finally, a real seawater solar-driven distillation experiment also revealed that the water quality of freshwater was improved by the addition of CTAB. This work revealed that the surfactants such as CTAB can be potentially used to inhibit VOCs entering into the condensed freshwater during solar-driven seawater distillation.

Multilinear Mathematical Separation in Chromatography

Chromatography is a powerful and generally applicable method for the analytical separation and quantification of the chemical constituents in complex mixtures because chromatographic separation can provide high selectivity by isolating all analytes from interferences. Multiway analysis based on the multilinear model is an increasingly widely used method for interference-free and fast determination of the chemical constituents also in complex mixtures because multilinear mathematical separation can provide high selectivity by extracting the pure signal of the analyte from the mixed signal of a real sample. By combining chromatographic separation with mathematical separation, multiway calibration method, multiway standard additions method, and multiway internal standard method can be established. Chromatography assisted by multiway analysis can reduce the requirements for complete chromatographic separation, save elution time, and decrease the consumption of the mobile phase, particularly when the peak coelution problem is difficult to solve. This review presents the fundamentals and analytical applications of multilinear mathematical separation in chromatography.

Oil spill in northeastern Brazil: Application of fluorescence spectroscopy and PARAFAC in the analysis of oil-related compounds

Between November 2019 and February 2020, 53 water samples were collected along 430 km of coastline in northeastern Brazil, which was the location of an oil spill that occurred in August 2019. Synchronous fluorescence matrices (SFMs) were acquired to avoid regions affected by Raman Stokes scatterings and second harmonic signals, and then, the SFMs were converted into excitation-emission matrices (EEM) by shear transformation. The matrix coupled with parallel factor analysis (PARAFAC) was used in the study of fluorescent components present in the collected waters. A sample collected before the oil spill and another from Florianópolis-SC, 2000 km from the incident, were used as references for nonimpacted waters. In the postspill samples, 4 components were determined, with component 1 (λ_exc = 225 nm, λ_em = 475 nm) being associated with humic-like organic matter (terrestrial), component 2 (λ_exc = 230 nm, λ_em = 390 nm) being associated with humic-like organic matter (marine), component 3 (λ_exc = 225/295 nm, λ_em = 345 nm) being associated with dibenzothiophene-like components also observed in tests with crude oil samples, and component 4 (λ_exc = 220/280 nm, λ_em = 340 nm) being associated with a naphthalene-like substance. Principal component analysis (PCA) was performed on the PARAFAC scores. The distribution of samples along the 4 components was observed and compared with the reference samples.

Excitation-Emission Matrix Spectroscopy for Analysis of Chemical Composition of Combustion Generated Particulate Matter

Analysis of particulate matter (PM) is important for the assessment of human exposures to potentially harmful agents, notably combustion-generated PM. Specifically, polycyclic aromatic hydrocarbons (PAHs) found in ultrafine PM have been linked to cardiovascular diseases and carcinogenic and mutagenic effects. In this study, we quantify the presence and concentrations of PAHs with lower molecular weight (LMW, 126 < MW < 202) and higher molecular weight (HMW, 226 < MW < 302), i.e., smaller and larger than Pyrene, in combustion-generated PM using excitation-emission matrix (EEM) fluorescence spectroscopy. Laboratory combustion PM samples were generated in a laminar diffusion inverted gravity flame reactor (IGFR) operated on ethylene and ethane. Fuel dilution by Ar in 0% to 90% range controlled the flame temperature. The colder flames result in lower PM yields however, the PM PAH content increases significantly. Temperature thresholds for PM transition from low to high organic carbon content were characterized based on the maximum flame temperature (T_max,c ∼ 1791 to 1857 K) and the highest soot luminosity region temperature (T*_c ∼ 1600 to 1650K). Principal component regression (PCR) analysis of the EEM spectra of IGFR samples correlates to GCMS data with R² = 0.988 for LMW and 0.998 for HMW PAHs. PCR-EEM analysis trained on the IGFR samples was applied to PM samples from woodsmoke and diesel exhaust, the model accurately predicts HMW PAH concentrations with R² = 0.976 and overestimates LMW PAHs.

Characterisation by Excitation-Emission Matrix Fluorescence Spectroscopy of Pigments in Mucus Secreted of Earthworm Eisenia foetida Exposed to Lead

The earthworm exposed to toxics shows physiological responses as: avoidance and mucus secretion. Heavy metals are particularly toxic to earthworms and the mucus secretion has been considered as a defence mechanism against undesirable substance. The chromophores present in the mucus secretion of Eisenia foetida have been poorly studied. Mucus secretion of E. foetida was induced by PbCl_2. High PbCl₂ concentrations provoked abundant mucus secretion which showed fluorescence when illuminated by UV light. Dialysis membrane separation, UV Visible and Excitation-Emission Matrix Fluorescence (EEM) spectroscopy were used to characterise the fluorescent pigments. EEM spectroscopy analysis of the mucus secretion signalled three excitation-emission peaks at: 310/380 nm, 370/520 nm and 440/520 nm. Two fluorophores were separated by dialysis. One of them matched the fluorescent compound riboflavin excitation-emission profile; the other is a protein with a peak 290/350 nm. Native-PAGE electrophoresis was conducted to assess the riboflavin-biding ability of the coelomic fluid protein produced by Eisenia foetida showing a high riboflavin-biding ability.

Rapid and simultaneous determination of three fluoroquinolones in animal-derived foods using excitation-emission matrix fluorescence coupled with second-order calibration method

The matter of fluoroquinolone residues in various foods still arouses wide public concern nowadays. In the present work, the strategy of excitation-emission matrix (EEM) fluorescence data coupled with second-order calibration method based on alternating normalization-weighted error (ANWE) algorithm was used to determine ofloxacin, lomefloxacin and ciprofloxacin in milk powder, milk and beef. Owning the unique "second-order advantage", the ANWE-assisted analytical method was proved to successfully and eco-friendly resolve the overlapped fluorescence spectra of multi-component in complex food matrixes without tedious pretreatment steps and sophisticated high-cost instrumentations. The feasibility of the proposed method was validated by experiments. The average spiked recoveries of three fluoroquinolones range from 82.6% to 110.5% with relative standard deviations lower than 7.4%, and the limits of detection range from 0.18 and 2.41 ng mL^-1. For further evaluation, analytical figures of merit such as sensitivity and selectivity, as well as the RSDs of intra-day (≦10.6%) and inter-day (≦9.4%) were calculated. The satisfactory analytical results demonstrated that the proposed strategy could be a competitive alternative for simple, rapid and simultaneous determination of multiple fluoroquinolones in animal-derived food samples.

Simultaneously quantifying intracellular FAD and FMN using a novel strategy of intrinsic fluorescence four-way calibration

The simultaneous quantitative analysis of intracellular metabolic coenzymes flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN) is of interest because they participate in many electron-transfer reactions of metabolism. But, the simultaneous quantitative analysis of FAD and FMN is hard to be achieved by traditional analytical methods. This paper proposes a novel strategy of intrinsic fluorescence coupled with four-way calibration method for simultaneous quantitative analysis of intracellular metabolic coenzymes FAD and FMN. Through mathematical separation, this proposed analytical method efficiently achieved the simultaneous quantitative analysis of metabolic coenzymes FAD and FMN in the cell, despite the fact that uncalibrated spectral interferents coexist in the system. The predicted concentrations of FAD and FMN in the cell are 217.0 ± 6.9 and 155.0 ± 1.7 pmol/10⁶ cells respectively, which were validated by the approved liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. This analytical method with second-order advantage simply requires the cell solution to be diluted by a buffer, it could introduce an interesting analytical strategy for multianalyte direct quantitative analysis in complex biological systems. In addition, we explore the third-order advantage of four-way calibration by a comparative study based on this real fluorescence data. The comparisons indicate that a four-way calibration method can provide higher sensitivity and more resolving power than a three-way calibration method.

Rapid, simultaneous and interference-free determination of three rhodamine dyes illegally added into chilli samples using excitation-emission matrix fluorescence coupled with second-order calibration method

In this study, a smart and green analytical method based on the second-order calibration algorithm coupled with excitation-emission matrix (EEM) fluorescence was developed for the determination of rhodamine dyes illegally added into chilli samples. The proposed method not only has the advantage of high sensitivity over the traditional fluorescence method but also fully displays the "second-order advantage". Pure signals of analytes were successfully extracted from severely interferential EEMs profiles via using alternating trilinear decomposition (ATLD) algorithm even in the presence of common fluorescence problems such as scattering, peak overlaps and unknown interferences. It is worth noting that the unknown interferents can denote different kinds of backgrounds, not only refer to a constant background. In addition, the method using interpolation method could avoid the information loss of analytes of interest. The use of "mathematical separation" instead of complicated "chemical or physical separation" strategy can be more effective and environmentally friendly. A series of statistical parameters including figures of merit and RSDs of intra- (≤1.9%) and inter-day (≤6.6%) were calculated to validate the accuracy of the proposed method. Furthermore, the authoritative method of HPLC-FLD was adopted to verify the qualitative and quantitative results of the proposed method. Compared with the two methods, it also showed that the ATLD-EEMs method has the advantages of accuracy, rapidness, simplicity and green, which is expected to be developed as an attractive alternative method for simultaneous and interference-free determination of rhodamine dyes illegally added into complex matrices.

Use of zero order diffraction of a grating monochromator towards convenient and sensitive detection of fluorescent analytes in multi fluorophoric systems

White light excitation fluorescence (WLEF) is known to possess analytical advantage in terms of enhanced sensitivity and facile capture of the entire fluorescence spectral signature of multi component fluorescence systems. Using the zero order diffraction of the grating monochromator on the excitation side of a commercial spectrofluorimeter, it has been shown that WLEF spectral measurements can be conveniently carried out. Taking analyte multi-fluorophoric systems like (i) drugs and vitamins spiked in urine sample, (ii) adulteration of extra virgin olive oil with olive pomace oil and (iii) mixture of fabric dyes, it was observed that there is a significant enhancement of measurement sensitivity. The total fluorescence spectral response could be conveniently analysed using PLS2 regression. This work brings out the ease of the use of a conventional fluorimeter for WLEF measurements.

Quantitative fluorescence kinetic analysis of NADH and FAD in human plasma using three- and four-way calibration methods capable of providing the second-order advantage

The metabolic coenzymes reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) are the primary electron donor and acceptor respectively, participate in almost all biological metabolic pathways. This study develops a novel method for the quantitative kinetic analysis of the degradation reaction of NADH and the formation reaction of FAD in human plasma containing an uncalibrated interferent, by using three-way calibration based on multi-way fluorescence technique. In the three-way analysis, by using the calibration set in a static manner, we directly predicted the concentrations of both analytes in the mixture at any time after the start of their reactions, even in the presence of an uncalibrated spectral interferent and a varying background interferent. The satisfactory quantitative results indicate that the proposed method allows one to directly monitor the concentration of each analyte in the mixture as the function of time in real-time and nondestructively, instead of determining the concentration after the analytical separation. Thereafter, we fitted the first-order rate law to their concentration data throughout their reactions. Additionally, a four-way calibration procedure is developed as an alternative for highly collinear systems. The results of the four-way analysis confirmed the results of the three-way analysis and revealed that both the degradation reaction of NADH and the formation reaction of FAD in human plasma fit the first-order rate law. The proposed methods could be expected to provide promising tools for simultaneous kinetic analysis of multiple reactions in complex systems in real-time and nondestructively.

Chemometrics-assisted determination of amiloride and triamterene in biological fluids with overlapped peaks and unknown interferences

Background: Amiloride (AMI) and triamterene (TRI) are both potassium-saving diuretics, which are ordinarily used as doping to enhance the performance of athletes in sports. For the similar structures and complex matrices existence, chromatography and extraction are commonly employed to realize the determination of AMI and TRI in biological fluids, which are very time-consuming and laborious. Results: A novel method is presented to simultaneous interference-free determination of AMI and TRI in complex biological fluids samples using excitation–emission matrix fluorescence coupled with second-order calibration method based on alternating normalization-weight error algorithm. Conclusion: The proposed method can obtain accurate qualitative and quantitative information of the analytes, even in the presence of the interference from complex biological fluids, which requires few prior purification and separation procedures.

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.

Chemical evolution of Macondo crude oil during laboratory degradation as characterized by fluorescence EEMs and hydrocarbon composition

The fluorescence EEM technique, PARAFAC modeling, and hydrocarbon composition were used to characterize oil components and to examine the chemical evolution and degradation pathways of Macondo crude oil under controlled laboratory conditions. Three major fluorescent oil components were identified, with Ex/Em maxima at 226/328, 262/315, and 244/366 nm, respectively. An average degradation half-life of ∼20 d was determined for the oil components based on fluorescence EEM and hydrocarbon composition measurements, showing a dynamic chemical evolution and transformation of the oil during degradation. Dispersants appeared to change the chemical characteristics of oil, to shift the fluorescence EEM spectra, and to enhance the degradation of low-molecular-weight hydrocarbons. Photochemical degradation played a dominant role in the transformation of oil components, likely an effective degradation pathway of oil in the water column. Results from laboratory experiments should facilitate the interpretation of field-data and provide insights for understanding the fate and transport of oil components in the Gulf of Mexico.

Rapid simultaneous determination of four non-steroidal anti-inflammatory drugs by means of derivative nonlinear variable-angle synchronous fluorescence spectrometry

A rapid, simple, and inexpensive spectrofluorimetric method has been proposed for the simultaneous quantification of diflunisal, salicylic acid, fenoprofen, and 6-methoxy-2-naphthylacetic acid (6MNA). First-derivative nonlinear variable-angle synchronous fluorescence spectrometry has been developed to improve the selectivity of fluorescence measurements without loss of sensitivity. It allows the simultaneous determination of different substances in a mixture from a single spectrum based on a single scan. The analyses were performed in an ethanol-water (70%) medium at a pH of 9.2, adjusted by using ammonium/ammonia (0.5 M) as a buffer solution. The linear concentration ranges are 30.0-100.0, 100.0-600.0, 50.0-150.0, and 30.0-100.0 ng/mL for salicylic acid, fenoprofen, diflunisal, and 6-methoxy-2-naphthylacetic acid, respectively, at lambda(ex)/lambda(em) = 281.1/423.6, 241.2/301.2, 284.1/403.8, and 268.7/339.6 nm, respectively. Analytical parameters of the proposed method were calculated according to the error propagation theory. The sensitivity, repeatability, reproducibility, and limits of detection achieved with the proposed method are adequate for the determination of these anti-inflammatory drugs.

Utilization of a submersible UV fluorometer for monitoring anthropogenic inputs in the Mediterranean coastal waters

We evaluated the performances of a submersible ultraviolet fluorometer (EnviroFlu-HC, TriOS Optical Sensors) dedicated to the real time measurement of polycyclic aromatic hydrocarbons (PAHs) in the aquatic media. We conducted calibration experiments and in situ measurements in the coastal Mediterranean Sea. We found that the EnviroFlu-HC was not strictly specific to PAHs, even though it exhibited the highest sensitivity for phenanthrene, but could response to tryptophan-like material as well, and in a much less extent, to humic substances. The sensor signal showed great spatial and temporal variations in clean and polluted sites, with likely a high contribution of PAHs in the harbors, and a high contribution of tryptophan-like and humic-like materials in the sewage effluent. We conclude that the EnviroFlu-HC is a good tool for monitoring anthropogenic inputs in the coastal waters, although its utilization should be combined to other fluorescence measurements to improve the information about the nature of the aromatic compounds detected.

Determination of naphthalene by competitive fluorescence immunoassay

A reliable and sensitive competitive fluorescence immunoassay for the quantitative determination of naphthalene (NA) was developed. 2-naphthoxy acetic acid (NAA) was selected as the hapten of naphthalene. Active ester method (AEM) was used to couple the NAA to carrier proteins (bovine serum albumin) to form artificial immune antigen. Male New Zealand white rabbits were immunized with this antigen to obtain polyclonal antibodies, with which, a novel fluorescence immunoassay for detection of NA was described. Under best conditions, NA can be determined in the concentration range of 0.1-100 microg/L with a detection limit of 0.05 microg/L. The cross-reactivities of the anti-NA antibody to seven structurally related compounds were below 15%. Some environmental samples were analyzed with satisfactory results. It shows a good accuracy and suitability to analyze NA in environmental water.

Application of ultraviolet fluorometry and excitation-emission matrix spectroscopy (EEMS) to fingerprint oil and chemically dispersed oil in seawater

Excitation-emission matrix spectroscopy (EEMS) was used to characterize the ultra violet fluorescence fingerprints of eight crude oils (with a 14,470-fold range of dynamic viscosity) in seawater. When the chemical dispersant Corexit 9500 was mixed with the oils prior to their dispersion in seawater, the fingerprints of each oil changed primarily as an increase in fluorescence over an emission band centered on 445 nm. In order to simplify the wealth of information available in the excitation-emission matrix spectra (EEMs), two ratios were calculated. A 66-90% decrease in the slope ratio was observed with the addition of Corexit. When the slope ratios were reduced in complexity to intensity ratios, similar trends were apparent. As a result either of the ratios could be used as a simple and rapid means of identifying and monitoring chemically dispersed oil in the open ocean.

Multivariate methods on the excitation emission matrix fluorescence spectroscopic data of diesel–kerosene mixtures: A comparative study

Quantitative determination of kerosene fraction present in diesel has been carried out based on excitation emission matrix fluorescence (EEMF) along with parallel factor analysis (PARAFAC) and N-way partial least squares regression (N-PLS). EEMF is a simple, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. Calibration models consisting of varying compositions of diesel and kerosene were constructed and their validation was carried out using leave-one-out cross validation method. The accuracy of the model was evaluated through the root mean square error of prediction (RMSEP) for the PARAFAC, N-PLS and unfold PLS methods. N-PLS was found to be a better method compared to PARAFAC and unfold PLS method because of its low RMSEP values.

Parallel factor analysis (PARAFAC) of target analytes in GC x GC-TOFMS data: automated selection of a model with an appropriate number of factors

PARAFAC (parallel factor analysis) is a powerful chemometric method that has been demonstrated as a useful deconvolution technique in dealing with data obtained using comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC x GC-TOFMS). However, selection of a PARAFAC model having an appropriate number of factors can be challenging, especially at low S/N or for analytes in the presence of chromatographic and spectral overlapping compounds (interferences). Herein, we present a method for the automated selection of a PARAFAC model with an appropriate number of factors in GC x GC-TOFMS data, demonstrated for a target analyte of interest. The approach taken in the methodology is as follows. PARAFAC models are automatically generated having an incrementally higher number of factors until mass spectral matching of the corresponding loadings in the model against a target analyte mass spectrum indicates overfitting has occurred. Then, the model selected simply has one less factor than the overfit model. Results indicate this model selection approach is viable across the detection range of the instrument from overloaded analyte signal down to low S/N analyte signal (total ion current signal intensity at analyte peak maximum S/N < 1). While the methodology is generally applicable to comprehensive two-dimensional separations using multichannel spectral detection, we evaluated it with several target analytes using GC x GC-TOFMS. For brevity in this report, only results for bromobenzene as target analyte are presented. Alternatively, instead of using the model with one less factor than the overfit model, one can select the model with the highest mass spectral match for the target analyte from among all the models generated (excluding the overfit model). Both model selection approaches gave essentially identical results.

Simultaneous analysis of the photocatalytic degradation of polycyclic aromatic hydrocarbons using three-dimensional excitation–emission matrix fluorescence and parallel factor analysis

Polycyclic aromatic hydrocarbons (PAHs) may be photochemically degraded. Monitoring of degradation process of PAHs is carried out by traditional methods, which normally imply time-consuming procedures that do not allow the chemical process to be analyzed in real time. In the present study, photodegradation kinetics of dibenz[a,h]anthracene, benz[a]anthracene, benz[a]pyrene and benz[k]fluorantene were investigated in aqueous solutions under different conditions. A 2(3) factorial design was used for optimizing the degradation process. Fluorescence spectroscopy is a fast, cheap and sensitive analytical method, attractive for use in conjunction with chemometric methods; in this case three-way analytical methodology based on fluorescence excitation-emission matrix (EEM) and parallel factor analysis (PARAFAC) was employed. A four-factor PARAFAC model made it possible to resolve the species presents in the degradation mixture and quantify the relative concentration of the analytes throughout the degradation. Several different parameters, such as core consistency, percentage of fit and correlation coefficients between recovered and reference spectra were employed to determine the suitable number of factors for the PARAFAC model. This new methodology allows us to determine satisfactorily the PAHs concentration during the photodegradation in mixtures of arbitrary composition, representing an interesting alternative to the conventional techniques normally used for the monitoring of degradation reactions.

An improved trilinear decomposition algorithm based on a Lagrange operator

An improved trilinear decomposition algorithm based on a Lagrange operator (LO) is developed in this paper, which introduces a Lagrange operator and penalty terms in the loss function to improve the performance of the algorithm. Compared to the traditional parallel factor (PARAFAC) algorithm, the algorithm not only may converge much faster, but also overcome the sensibility to estimate the number of components. A set of simulated and measured excitation/emission fluorescence data were treated by both the proposed and traditional PARAFAC algorithm to compare their efficiencies. The analytical results obtained with real chemical system containing aspirin and its metabolic products show that the trilinear decomposition methodology is a promising tool to obtain spectral and composition information from mixtures without chemical separation.

Interference-free analysis using three-way fluorescence data and the parallel factor model. Determination of fluoroquinolone antibiotics in human serum

Three-way fluorescence data and multivariate calibration based on parallel factor analysis (PARAFAC) are combined for the simultaneous quantitation of three fluoroquinolone anitibiotics (norfloxacin, enoxacin, and ofloxacin) in human serum samples. The three analytes can be adequately determined with limits of detection of 0.2, 3.0, and 0.5 microg L(-1), respectively, with minimum experimental effort. The selected analytical methodology fully exploits the so-called second-order advantage of the employed three-way data, allowing obtaining individual concentrations of calibrated analytes in the presence of any number of uncalibrated (serum) components. In contrast to PARAFAC, less satisfactory results were obtained with a multidimensional partial least-squares (nPLS) model trained with the same calibration set.

Identification of major water-soluble fluorescent components of some petrochemicals

The chemical identities of several organic compounds that dominate the ultraviolet (UV) fluorescence of water after exposure to gasoline, diesel fuel and crude oil are presented. A combination of high-performance liquid chromatography with UV-fluorescence detection, fluorescence spectroscopy and gas chromatography-mass spectrometry (GC-MS) is used to show that naphthalene, methylnaphthalene and methylstyrene are the major fluorescent species in water following exposure to gasoline. These compounds are not dominant in water exposed to other petrochemicals we studied.

Three-way analysis of fluorescence spectra of polycyclic aromatic hydrocarbons with quenching by nitromethane

The application of trilinear decomposition (TLD) to the analysis of fluorescence excitation-emission matrices of mixtures of polycyclic aromatic hydrocarbons (PAHs) is described. The variables constituting the third-order tensor are excitation wavelength, emission wavelength, and concentration of a fluorescence quencher (nitromethane). The addition of a quencher to PAH mixtures selectively reduces the fluorescence intensity of mixture components according to the Stern-Volmer equation. TLD allows the three-way matrix to be decomposed to give unique solutions for the excitation spectrum, emission spectrum, and quenching profiles for each component. The availability of spectra and calculated Stern-Volmer constants can aid in the identification of unknown components. Preprocessing of the data to correct for Rayleigh/Raman scatter and primary absorption by the quencher is necessary. Both three-component (anthracene, pyrene, 1-methylpyrene) and four-component (fluoranthene, anthracene, pyrene, 2,3-benzofluorene) synthetic mixtures are successfully resolved by TLD using quencher concentrations up to 100 mM. Results are compared using both alternating least-squares and direct trilinear decomposition algorithms. The reproducibility of extracted Stern-Volmer constants is determined from replicate experiments. To illustrate the application of TLD to a real sample, a chromatographic cut from the analysis of a light gas oil sample was used. Analysis of the TLD extracted spectra and quenching constants suggests the presence of three classes of polycyclic aromatic hydrocarbons consistent with data from a second dimension of chromatography and mass spectrometry.

Application of quantitative chemometric analysis techniques to direct sampling mass spectrometry

This paper explores the use of direct sampling mass spectrometry coupled with multivariate chemometric analysis techniques for the analysis of sample mixtures containing analytes with similar mass spectra. Water samples containing varying mixtures of toluene, ethyl benzene, and cumene were analyzed by purge-and-trap/direct sampling mass spectrometry. Multivariate calibration models were built using partial least-squares regression (PLS), trilinear partial least-squares regression (tri-PLS), and parallel factor analysis (PARAFAC), with the latter two methods taking advantage of the differences in the temporal profiles of the analytes. The prediction errors for each model were compared to those obtained with simple univariate regression. Multivariate quantitative methods were found to be superior to univariate regression when a unique ion for quantitation could not be found. For prediction samples that contained unmodeled, interfering compounds, PARAFAC outperformed the other analysis methods. The uniqueness of the PARAFAC model allows for estimation of the mass spectra of the interfering compounds, which can be subsequently identified via visual inspection or a library search.

Mitigation of Rayleigh and Raman spectral interferences in multiway calibration of excitation-emission matrix fluorescence spectra

A weighted parallel factor analysis (W-PARAFAC) model is applied to excitation-emission matrix (EEM) fluorescence spectra of carbamate pesticides to aid with calibration in the presence of Raman scattering. Traditional PARAFAC inefficiently models the Raman scattering, resulting in prediction and calibration errors when a significant background is present. Four different weighting strategies were investigated and compared with subtraction of the appropriate sample background. Using a binary weighting strategy produced superior results, compared with a continuous distribution of weights. Further choice of weighting strategies, which are optimized to include either maximum analyte signal or to exclude a maximum amount of background scattering, is dependent on the degree of overlap and relative signal intensity.