Agustina V. Schenone

Fast chromatographic method for the determination of dyes in beverages by using high performance liquid chromatography—Diode array detection data and second order algorithms

A fast chromatographic methodology is presented for the analysis of three synthetic dyes in non-alcoholic beverages: amaranth (E123), sunset yellow FCF (E110) and tartrazine (E102). Seven soft drinks (purchased from a local supermarket) were homogenized, filtered and injected into the chromatographic system. Second order data were obtained by a rapid LC separation and DAD detection. A comparative study of the performance of two second order algorithms (MCR-ALS and U-PLS/RBL) applied to model the data, is presented. Interestingly, the data present time shift between different chromatograms and cannot be conveniently corrected to determine the above-mentioned dyes in beverage samples. This fact originates the lack of trilinearity that cannot be conveniently pre-processed and can hardly be modelled by using U-PLS/RBL algorithm. On the contrary, MCR-ALS has shown to be an excellent tool for modelling this kind of data allowing to reach acceptable figures of merit. Recovery values ranged between 97% and 105% when analyzing artificial and real samples were indicative of the good performance of the method. In contrast with the complete separation, which consumes 10 mL of methanol and 3 mL of 0.08 mol L(-1) ammonium acetate, the proposed fast chromatography method requires only 0.46 mL of methanol and 1.54 mL of 0.08 mol L(-1) ammonium acetate. Consequently, analysis time could be reduced up to 14.2% of the necessary time to perform the complete separation allowing saving both solvents and time, which are related to a reduction of both the costs per analysis and environmental impact.

Photo-Fenton degradation of the herbicide 2,4-D in aqueous medium at pH conditions close to neutrality

A theoretical and experimental study of the photo-Fenton degradation of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) in water is presented. A kinetic model derived from a reaction sequence is proposed using the ferrioxalate complex as iron source for conditions of pH = 5. The kinetic model was employed to predict the concentrations of 2,4-D, 2,4-dichlorophenol (2,4-DCP), hydrogen peroxide (HP) and oxalate (Ox) in a flat plate laboratory reactor irradiated with a solar simulator. Two types of incident irradiation levels were tested by different combinations of attenuation filters. The effects of the oxalate/Fe(+3) molar ratio (Ox/Fe), the reaction temperature (T) and the 2,4-D/HP molar ratio (R) on the photo-Fenton process were also investigated. For low radiation level and operating conditions of R = 50 and T = 50 °C, a 2,4-D conversion of 95.6% was obtained after 180 min. Moreover, the 2,4-D conversion was almost 100% in only 120 min when the system was operated under the same operating conditions and high radiation level. From the proposed model and the experimental data, the corresponding kinetic parameters were estimated applying a nonlinear regression method. A good agreement between the kinetic model and experimental data, for a wide range of simulated solar operating conditions, was observed. For 2,4-D, 2,4-DCP, HP and Ox concentrations, the calculated RMSE were 1.21 × 10(-2), 5.45 × 10(-3), 2.86 × 10(-1) and 2.65 × 10(-2) mM, respectively.

Determination of tartrazine in beverage samples by stopped-flow analysis and three-way multivariate calibration of non-linear kinetic-spectrophotometric data

The performance of MCR-ALS was studied in the modeling of non-linear kinetic-spectrophotometric data acquired by a stopped-flow system for the quantitation of tartrazine in the presence of brilliant blue and sunset yellow FCF as possible interferents. In the present work, MCR-ALS and U-PCA/RBL were firstly applied to remove the contribution of unexpected components not included in the calibration set. Secondly, a polynomial function was used to model the non-linear data obtained by the implementation of the algorithms. MCR-ALS was the only strategy that allowed the determination of tartrazine in test samples accurately. Therefore, it was applied for the analysis of tartrazine in beverage samples with minimum sample preparation and short analysis time. The proposed method was validated by comparison with a chromatographic procedure published in the literature. Mean recovery values between 98% and 100% and relative errors of prediction values between 4% and 9% were indicative of the good performance of the method.

Second-order advantage achieved by modeling excitation–emission fluorescence matrices affected by inner filter effects using a strategy which combines standardization and calibration: Reducing experimental and increasing analytical sensitivity

A methodology based on second-order data (excitation emission matrices) modeling with one of most popular algorithms presenting the second-order advantage, parallel factor analysis (PARAFAC), combined with transference of calibration is proposed to predict the analyte concentration when significant inner filter effects occur, even in the presence of unexpected sample components. The quantitation of phenylephrine hydrochloride (PHE) in water samples (concentrations ranged between 250 and 750 ng mL(-1)) in the presence of ibuprofen, acetyl salicylic acid and paracetamol (which produce inner filter effect across the useful wavelength range) was achieved. The strategy allows reducing the experimental work and increasing the analytical sensitivity in the determination of the analyte of interest in the presence of unexpected compounds and matrix effect caused by inner filter, avoiding the preparation of a large number of solutions and maintaining acceptable figures of merit. Recoveries between 97 and 102% for validation and real spiked water samples, respectively, and a relative prediction error of 5% were achieved. Results were compared with those obtained after the application of the classical standard addition method combined with PARAFAC, carrying out five additions to each sample, in triplicate. The presented methodology constitutes a simple and low-cost method for the determination of PHE in water samples with a considerable reduction in standard handling and time. This methodology can be extended to other systems presenting matrix effect and, consequently, can become in a useful tool to know the amount of pharmaceuticals in the aquatic environment and to evaluate the effect of conventional wastewater treatment plants in the elimination of pharmaceutical compounds.

Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method.

A new residual modeling algorithm for nonbilinear data is presented, namely unfolded partial least squares with interference modeling of non bilinear data by multivariate curve resolution by alternating least squares (U-PLS/IMNB/MCR-ALS). Nonbilinearity represents a challenging data structure problem to achieve analyte quantitation from second-order data in the presence of uncalibrated components. Total synchronous fluorescence spectroscopy (TSFS) generates matrices which constitute a typical example of this kind of data. Although the nonbilinear profile of the interferent can be achieved by modeling TSFS data with unfolded partial least squares with residual bilinearization (U-PLS/RBL), an extremely large number of RBL factors has to be considered. Simulated data show that the new model can conveniently handle the studied analytical problem with better performance than PARAFAC, U-PLS/RBL and MCR-ALS, the latter modeling the unfolded data. Besides, one example involving TSFS real matrices illustrates the ability of the new method to handle experimental data, which consists in the determination of ciprofloxacin in the presence of norfloxacin as interferent in water samples.

Unfolded partial least squares/residual bilinearization combined with the Successive Projections Algorithm for interval selection: enhanced excitation-emission fluorescence data modeling in the presence of the inner filter effect

The use of the successive projections algorithm (SPA) for elimination of uninformative variables in interval selection, and unfold partial least squares regression (U-PLS) modeling of excitation-emission matrices (EEM), when under the inner filter effect (IFE) is reported for first time. Post-calibration residual bilinearization (RBL) was employed against events of unknown components in the test samples. The inner filter effect can originate changes in both the shape and intensity of analyte spectra, leading to trilinearity losses in both modes, and thus invalidating most multiway calibration methods. The algorithm presented in this paper was named iSPA-U-PLS/RBL. Both simulated and experimental data sets were used to compare the prediction capability during: (1) simulated EEM; and (2) quantitation of phenylephrine (PHE) in the presence of paracetamol (PAR) (or acetaminophen) in water samples. Test sets containing unexpected components were built in both systems [a single interference was taken into account in the simulated data set, while water samples were added with varying amounts of ibuprofen (IBU), and acetyl salicylic acid (ASA)]. The prediction results and figures of merit obtained with the new algorithm were compared with those obtained with U-PLS/RBL (without intervals selection), and with the well-known parallel factors analysis (PARAFAC). In all cases, U-PLS/RBL displayed better EEM handling capability in the presence of the inner filter effect compared with PARAFAC. In addition, iSPA-U-PLS/RBL improved the results obtained with the full U-PLS/RBL model, in this case demonstrating the potential of variable selection.

Photo-Fenton degradation of a herbicide (2,4-D) in groundwater for conditions of natural pH and presence of inorganic anions

The effects of four inorganic anions (Cl-, SO42-, HCO3-, NO3-) usually present in groundwater were investigated on the photo-Fenton degradation of 2,4-dichlorophenoxyacetic acid (2,4-D). A kinetic model derived from a reaction sequence is proposed using the ferrioxalate complex as iron source at pH close to natural conditions (pH = 5). It was demonstrated that oxalate not only maintained iron in solution for the natural groundwater system, but also increased the photochemical activation of the process. Results showed that the minimum conversion of 2,4-D for the simulated groundwater after 180 min was 63.80%. This value was only 14.1% lower than the conversion achieved without anions. However, with all anions together, the consumption of hydrogen peroxide (HP) per mole of herbicide showed an increase with respect to the test without anions. Only one kinetic parameter was estimated for each anion applying a nonlinear regression method. Subsequently, these optimized kinetic constants were used to simulate the system behaviour, considering the influence of all the studied anions together. A good agreement between kinetic model predictions and experimental data was observed, with the following errors: RMSE2,4-D = 3.98 × 10-3 mM, RMSEHP = 1.83 × 10-1 mM, RMSEOX = 1.39 × 10-2 mM, and RMSE2,4-DCP = 5.59 × 10-3  mM.

A Kinetic Study for the Fenton and Photo-Fenton Paracetamol Degradation in a Pilot Plant Reactor

The present study aims at proposing a kinetic model that can capture the complexity and non - linear nature of the Fenton and photo - Fenton processes in the degradation of a model pollutant . Moreover, t he pro posed model is also able to account for the effect of the Local Volumetric Rate of Photon Absorption (LVRPA), depending on the radiation field within the annular photoreactor and consequently including the reactor dimensions and lamp characteristics. Parac etamol (PCT) was selected as model pollutant, because it is widely used as antipyretic and analgesic. Three kinetic parameters, accounting for the Fenton - like reaction and the hydroxyl radical attack to hydrogen peroxide and paracetamol, were estimated. Me an Square Error (MSE) and Root Mean Square Error (RMSE) were calculated to validate the model reliability