Currently, there are two mixtures of biodiesel/diesel fuel sold in Brazil: BX/S500 and BX /S10 (X = volume/volume biodiesel percentage; S500 and S10 = sulfur content in diesel fuels - 500 ppm and 10 ppm, respectively). In order to differentiate these mixtures, red dye is added to diesel oil as required by the National Agency for Petroleum, Natural Gas and Biofuels (ANP), regulatory agency in Brazil. Since the palm oil biodiesel has also a reddish color, mixing this product with diesel fuel leads to difficulty in visual differentiation of the mixtures BX/S500 and BX/S10. We propose the use of UV-Vis spectrophotometry, which is a low cost, simple and rapid technique. Spectra obtained for different mixtures show that qualitative distinction is possible. For quantification of red dye in the presence of palm oil biodiesel, the method is limited when dye is present in low concentrations (< 0.1 mg L-1) due to matrix effects. The method showed good repeatability of the absorbance responses, wide linear dynamic range (0.02 mg L-1 to 40.00 mg L-1) and low limits of detection and quantification (0.006 mg L-1 and 0.019 mg L-1, respectively).

<p>Triacetin (or glycerol triacetate) was obtained by acetylating the glycerol by-product of biodiesel production process. This procedure is an interesting alternative that follows the principles of green chemistry. In this work, triacetin was synthesized using reactions between glycerol and acetic acid, as well as glycerol and acetic anhydride, using homogeneous and heterogeneous acid catalysis. The goal is to use this product as an additive for biodiesel produced from palm oil, which is a fuel with physical properties that require improvement. The products were characterized by Fourier transform infrared spectroscopy (FTIR), ¹³C nuclear magnetic resonance (NMR) and gas chromatography (GC). The reaction between glycerol and acetic anhydride was the most effective for obtaining the desired product, with an approximate selectivity of 98% for triacetin. The triacetin was added to diesel fuel oil and biodiesel in proportions from 5 to 10% v/v, and the mixtures were tested in an electrical generator. In the test, the engine showed no problems during operation, and incorporating the mixtures did not result in significant consumption. Small reductions were detected in CO, O₂ and opacity, but no changes were observed in the emissions of NO_x and CO₂.</p>

Três origens diferentes de biodiesel (algodão, mamona e palma) foram adulteradas com óleo de soja cru, em concentrações variando de 1 a 40% (m/m). Estas amostras foram analisadas por espectrometria de infravermelho médio (MIR) e os seus espectros foram estudados em três diferentes faixas espectrais: espectro inteiro (4000-665 cm-1), e nas faixas de 1800-1700 cm-1 e 1800-1000 cm-1. Para determinar a origem do biodiesel utilizado no sistema adulterado, os dados espectrais foram analisados pela ferramenta análise de componentes principais (PCA) e a melhor segregação das origens foi obtida para o espectro inteiro (4000-665 cm-1). A variância explicada foi de 99%, para os três primeiros componentes. Para quantificar o óleo de soja cru foi aplicada a ferramenta mínimos quadrados parciais (PLS). Os melhores resultados foram obtidos para a região espectral de 1800-1000 cm-1, com valores de RMSEP (erro médio quadrático de previsão) variando de 1,10 a 1,47% (m/m).

Three different biodiesel sources (cotton, castor and palm) were adulterated with raw soybean oil at concentrations ranging from 1-40% (m/m). These samples were analyzed by infrared spectrometry (MIR) and their spectra were studied at three different spectral ranges: full spectrum (4000-665 cm-1), and the spectral ranges of 1800-1700 cm-1 and 1800-1000 cm-1. To determine the source of biodiesel used in the adulterated system, the data were analyzed by PCA (principal components analysis) spectral analysis tool and the best segregation of the sources was obtained at the range of 4000-665 cm-1. The explained variance was of 99% for the first three components. To quantify the raw soybean oil partial least squares (PLS) tool was applied. The best results were obtained for the spectral range of 1800-1000 cm-1, with values of RMSEP (root mean square error of prediction) varying from 1.10 to 1.47% (m/m).