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In this work, competitive adsorption of four food dyes (Sunset Yellow, Allura Red, tartrazine, and Brilliant Black) by heated pine wood is studied using multivariate calibration. Partial least squares PLS1 and principal component regression PCR are effectively applied for simultaneous determination of food dyes with high accuracy (96.2–103.6%) and low relative prediction error (2.3–6.9%). Using multivariate calibration, the dyes are detected down to 0.11, 0.15, 0.24, and 0.29 mg L−1. The removal of dyes increased at acidic solution and H-bonding is the main controlling mechanism. The maximum removal capacities (according to Langmuir model) are 3.4, 2.5, 4.8, and 7.1 mg g−1for tartrazine, Brilliant Black, Allura Red, and Sunset Yellow, respectively, at pH 2.0 and 25°C. The competition factors (CFs) are estimated from the isotherms to assess the degree of competition between dyes toward the surface. The CFs are 0.64, 0.66, 0.77, and 0.77 for Brilliant Black, Allura Red, Sunset Yellow, and tartrazine, respectively. Accordingly, Brilliant Black is the most affected dye while Sunset Yellow and tartrazine are the least affected in multi-solute adsorption. This study demonstrates the useful application of multivariate calibration for studying competitive adsorption of colored pollutants with minimum experimental efforts expenses. [ABSTRACT FROM PUBLISHER]

Abstract: The viscosity index (VI) and the base number (BN) of motor oils are the most important parameters to be measured in order to assess their performance and service time. Both parameters were simply obtained for virgin and recycled motor oil samples using multivariate calibration based on the FTIR data. Analysis showed that the PLS-1 has outperformed CLS and PCR for the oil parameters prediction. Five and four PLS-1 latent variables were found optimum to obtained the VI and the BN from the FTIR data; respectively. With high accuracy (99–102%) and precision (3–11%), the BN could be determined over the range 4.57–16.45mgKOHg−1 and the VI over the range 96–153. The outputs of the PLS-1 were found comparable to those obtained by the expensive and time-consuming ASTM methods. This developed method is highly recommended for quick monitoring of the motor oil quality parameters. [Copyright &y& Elsevier]

Abstract: The precise determination of the heat of combustion is of great importance for trading automotive diesel. The net heat of combustion (NHC) of fuel is related to the hydrogen elemental composition of fuel as obtained by elemental analysis. Heat of combustion expressed as gross heat of combustion (GHC) and net heat of combustion (NHC) have been predicted from data obtained by proximate analysis (density, ash, water and sulphur content) (ASTM D4868). GHC was obtained using bomb calorimetry (ASTM D240). The results of ASTM D4868 and ASTM D240 were found in good agreement. GHC and NHC fall within the relatively narrow range 45.24–46.08 and 41.91–43.27MJ/kg, respectively. GHCs of tested diesel samples are, on average, about 7% greater than NHCs. The present paper also present a simple analytical method for determination of hydrogen content, GHC, and NHC of automotive diesel fuel using FTIR spectroscopy and partial-least squares calibration (PLS-1). PLS-1 had a high prediction power for prediction of hydrogen from FTIR spectra of diesel samples. The spectral ranges used in calibration were 400–670 and 2846–2970cm−1. On the other hand, classical least squares calibration (CLS) was found invalid for determination of hydrogen content in diesel. The results obtained by the proposed analytical method were almost to those obtained by ASTM D4868 and ASTM D240. PLS-1 method, offers a simple and reliable analytical method for quantification of hydrogen content in diesel samples without running expensive analysis like those carried out using carbon, hydrogen, and nitrogen (CHN) instruments. [Copyright &y& Elsevier]

Abstract: The application of solid-phase extraction with multivariate calibration for simultaneous determination of three toxic pesticides in tap and reservoir waters was presented. The proposed analytical method was used for the determination of atrazine, methidathion, and propoxur in complex water samples without the need for chromatographic separation. Among the applied multivariate calibration methods, partial least squares (PLS-1) method was found the most effective for pesticides quantification. Multiwalled carbon nanotubes (MWCNTs) adsorbent showed a perfect extraction/preconcentration of pesticides present at trace levels. The experimental factors that affect pesticides extraction by MWCNTs adsorbent such as sample volume, eluent volume, solution pH, and extraction flow rate were studied and optimized. The figures of merit of the proposed method were: limits of detection 3, 2, and 3μgl−1 and linear ranges 5–30, 3–60, and 5–40μgl−1 for atrazine, methidathion, and propoxur, respectively. A good precision was reported for the method, R.S.D. values were always less than 5.0%. Satisfactory results were reported for simultaneous determination of trace levels of pesticides in complex matrices. In tap water, the percent recoveries for pesticides were extended from 95 to 104% and R.S.D. from 1 to 3%, while lower recoveries were observed in reservoir water: 84–93% (R.S.D.: 1–3). Although the pesticides can be accurately quantified by SPE and liquid chromatography, SPE–PLS-1 method was found simpler and operated at lower running costs. [Copyright &y& Elsevier]

Highlights: [•] Competitive sorption of two cationic dyes of significant spectral overlapping is studied using MVC. [•] Simultaneous determination of two dyes (spectral overlap 96.4%) is achieved using PLS1. [•] Irregular L2-isotherm shape was observed for dyes sorption in binary systems. [•] Langmuir model was found applicable for presenting competitive sorption of cationic dyes. [•] Competitive sorption process of cationic dyes was found exothermic and spontaneous. [Copyright &y& Elsevier]