Two methodologies were developed to monitor the biodiesel content of mafurra in mixtures with diesel using hydrogen nuclear magnetic resonance (1H NMR) Spectroscopy combined with the multivariate regression by orthogonal projections to latent structure (OPLS) and partial least squares (PLS). The efficiency of these methodologies was analyzed based on the figures of merit and the fit of the models through the correlation of the measured and predicted values of the calibration and prediction sets. The results of the figures of merit in the OPLS model were better than in the PLS model. A high correlation between the measured and predicted values was evident in the OPLS model, with a correlation coefficient (R2) greater than 0.99, demonstrating a better fit of the OPLS model in relation to the PLS model which presented a correlation coefficient (R2) less than 0.98. The OPLS model is more robust and has good predictive capacity than the PLS model because it obtained a higher Q 2 value. The excellent results of the application of 1H NMR spectroscopy combined with multivariate regression by OPLS suggest that this analytical methodology is ideal, feasible, efficient and suitable for use by inspection agencies to control the quality of this fuel.

Mid-Infrared absorption spectroscopy associate with the Partial Least Squares regression is the official method to monitor Brazilian commercial diesel quality. This method, however, uses solvents and a large number of samples for the construction of the calibration curves, which generates waste and increases the time needed for the analysis. In order to develop a non-destructive method, being possible to recover the sample after its quantification, decrease the quantity of samples and make use of a single calibration curve, in this study we used the oilseed crambe, which is not used in human food, for the methyl biodiesel production and PLS analysis for their content determination in mixtures with diesel at a concentration range of 1.00 to 30.00 (% v/v). The global model for crambe methyl biodiesel obatined RMSEC = 0.26 (% v/v), RMSECV = 0.35 (% v/v) and RMSEP = 0.41 (% v/v). Complementary, variable selection method iPLS was applied in the global model in order to reduce the spectral range required to regression construction and to improve the RMSEP, RMSECV and RMSEC values.

Adulterants in biodiesel/diesel blends modifies its physical and chemical properties. In this work, Fourier Transform Mid-Infrared spectrometry (FT-MIR) and multivariate control charts based on Net Analyte Signal (NAS) were used to monitor the quality of Crambe methyl biodiesel in relation to the biodiesel content and the presence of adulterants. The calibration model was constructed from the decomposition of the instrumental signals of the calibration samples into three vectors: NAS, interference and residual. From these vectors, three control charts were built: (i) NAS chart to monitor the analyte of interest (Crambe methyl biodiesel); (ii) Interference chart to monitor the data matrix (all components in diesel without the analyte of interest); and (iii) Residual chart to monitor any non-systematic variations. To validate the calibration model, other groups of B10, BX and B10 samples adulterated by direct addition of soybean oil and used fry oil in the range of 4.85-30.13% (v/v) were used. All samples prepared in-quality specifics were correctly classified as “in-quality control” samples, and other samples were correctly classified as “out-of-quality control” samples. Therefore, the methodology developed proved to be efficient in monitoring the quality of this fuel and it can be used by supervisory and quality control agencies.

In this study the coagulation-flocculation process was evaluated as an alternative for treatment of biodiesel wastewater. The role of two coagulants, Al3+ and Fe3+, as well as its dosage, pH, treatment time, stirring and aeration were evaluated. It was observed that in the treatment using Al3+ the pH of the effluent (9.7) does not need to be adjusted, while for Fe3+ a previous adjustment to pH 5.0 was necessary. On the other hand, a high concentration of Al3+ (243 mg L-1) and a relatively long treatment time (70 min) were required to reach more than 96% of turbidity removal, when compared to the processing using Fe3+ (56 mg L-1 and 53 min), attributed to the formation of different mole fractions of hydrolyzed cationic species. Under the optimized conditions, more than 96% of turbidity, apparent color and suspended solids, and 82% of oil and fats were removed.

This paper presents methodologies for monitoring the quality of methyl cotton biodiesel in biodiesel/diesel blends using mid-infrared spectroscopy (MIR) and chemometrics tools. The first method relates to the construction of multivariate control charts with the aim of qualitatively monitoring the samples according to the Brazilian specification for biodiesel in the biodiesel/diesel blends (7.00 ± 0.5% v/v of biodiesel). The second concerns the construction of partial least squares (PLS) to determine the content of the biodiesel in the biodiesel/diesel blend. The PLS model was validated from multivariate figures of merit according to the guidelines of ASTM E1655-05 and IUPAC. The results from both methods were satisfactory for both qualitative and quantitative monitoring. Therefore, the proposed methodologies for monitoring the quality of biodiesel in biodiesel/diesel blends are fast, practical, economical and efficient and can be used by industries and service stations.

This work aimed at employing partial least square discriminant analysis (PLS2-DA), allied to mid-infrared (MIR) spectroscopy as an analytical method for simultaneous classification of biodiesels from different oils (soybean and used frying oil) and routes (methylic and ethylic). The evaluation of the model was verified through values of sensitivity and specificity for each parameter, in the interest class. PLS2-DA model showed 100% correct classification in the discrimination of types of biodiesels. Therefore, the proposed methodology is fast, because it allows simultaneous classification of different types of biodiesels. Consequently, it can be used in quality control of this type of biofuel.

Este trabalho descreve a influência e otimização dos reagentes de Fenton (concentração de Fe2+ e H2O2) na eficiência da mineralização do herbicida paraquat (PQT, 50 mg L-1) em água, após 60 min (equivalendo a 642 kJ L-1 de radiação UVA acumulada) de tratamento por processo foto-Fenton em escala de laboratório, usando planejamento composto central (CCD). Sob condições otimizadas, experimentos cinéticos foram feitos, avaliando a remoção do PQT, sua mineralização e toxicidade em escala de laboratório, usando irradiação artificial, e em planta piloto sob irradiação solar. A mesma eficiência de remoção e mineralização do PQT foram obtidas em ambos os reatores utilizados. A toxicidade das amostras, estimada em termos de mortalidade de Artemia salina, diminui simultaneamente com o decaimento da concentração de PQT, sugerindo a formação de intermediários de menor toxicidade. Dessa maneira, o processo foto-Fenton/solar pode ser considerado uma alternativa viável para o tratamento de águas residuais contendo PQT.

This study describes the influence and optimization of Fenton's reagent (concentration of Fe2+ and H2O2 ) on the efficiency of mineralization of the herbicide paraquat (PQT, 50 mg L-1) in water, after 60 min (equivalent to 642 kJ L-1 of accumulated UVA radiation) treatment by photo-Fenton process in laboratory scale, using central composite design (CCD). Under optimized conditions, kinetic experiments were done, evaluating the PQT removal, its mineralization and toxicity in laboratory scale, using artificial irradiation, and in a pilot plant under solar irradiation. The same removal efficiency and mineralization of PQT were obtained in both reactors. The toxicity of the samples, estimated in terms of mortality of Artemia salina, decreases simultaneously with the decay of concentration of PQT, suggesting the formation of intermediates of lower toxicity. In this way, the solar photo-Fenton process can be considered as a viable alternative for the treatment of wastewater containing PQT.

This paper describes the development of methods for the determination of Pb and Mn in fishes by GF AAS after solubilization with tetramethylamonium hidroxide. The optimization of the operational conditions and the choice of modifier were made using multivariated optimization. Analytical Figures of Merit were adequately to propose. The Limit of Quantification obtained were 150 and 18.5 µg kg-1 to Mn and Pb, respectively. No significant difference was found between the slope values obtained for the aqueous and standard addition calibration curves. The D.P.R. was always lower than 12% and the analysis of the SRM NRCC TORT2 showed 80-120% of recovery.

The copper and cadmium complexation properties in natural sediment suspensions of reservoirs of the Tietê River were studied using the solid membrane copper and cadmium ion-selective electrodes. The complexation and the average conditional stability constants were determined under equilibrium conditions at pH=6.00 ± 0.05 in a medium of 1.0 mol L-1 sodium nitrate, using the Scatchard method. The copper and cadmium electrodes presented Nernstian behavior from 1x10-6 to 1x10-3 mol L-1 of total metal concentration. Scatchard graphs suggest two classes of binding sites for both metals. A multivariate study was done to correlate the reservoirs and the variables: complexation properties, size, total organic carbon, volatile acid sulfide, E II and pH.

Inductively Coupled Plasma Optical Emission Spectrometry was used to determine Ca, Mg, Mn, Fe, Zn and Cu in samples of processed and natural coconut water. The sample preparation consisted in a filtration step followed by a dilution. The analysis was made employing optimized instrumental parameters and the results were evaluated using methods of Pattern Recognition. The data showed common concentration values for the analytes present in processed and natural samples. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) indicated that the samples of different kinds were statistically different when the concentrations of all the analytes were considered simultaneously.