Abstract: Biodiesel is the main alternative to fossil diesel. The key advantages of its use are the fact that it is a non-toxic renewable resource, which leads to lower emissions of polluting gases. European governments are targeting the incorporation of 20% of biofuels in the general fuels until 2020. Chemically, biodiesel is a mixture of fatty acid methyl esters, derived from vegetable oils or animal fats, which is usually produced by a transesterification reaction, where the oils/fats react with an alcohol, in the presence of a catalyst. The European Standard (EN 14214) establishes 25 parameters that have to be analysed to certify biodiesel quality and the analytical methods that should be used to determine those properties. This work reports the use of near infrared (NIR) spectroscopy to determine the esters content in biodiesel as well as the content in linolenic acid methyl esters (C18:3) in industrial and laboratory-scale biodiesel samples. Furthermore, calibration models for myristic (C14:0), palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2) acid methyl esters were also obtained. Principal component analysis was used for the qualitative analysis of the spectra, while partial least squares regression was used to develop the calibration models between analytical and spectral data. The results confirm that NIR spectroscopy, in combination with multivariate calibration, is a promising technique to assess the biodiesel quality control in both laboratory-scale and industrial scale samples.
Abstract: Biodiesel is one of the main alternatives to fossil diesel. It is a non-toxic renewable resource, which leads to lower emissions of polluting gases. In fact, European governments are targeting the incorporation of 20% of biofuels in the fossil fuels until 2020. Chemically, biodiesel is a mixture of fatty acid methyl esters, derived from vegetable oils or animal fats, which is usually produced by a transesterification reaction, where the oils or fats react with an alcohol, in the presence of a catalyst. The European Standard (EN 14214) establishes 25 parameters that have to be analysed to certify biodiesel quality and the analytical methods that should be used to determine those properties. This work reports the use of near infrared (NIR) spectroscopy to determine some important biodiesel properties: the iodine value, the cold filter plugging point, the kinematic viscosity at 40 °C and the density at 15 °C. Principal component analysis was used to perform a qualitative analysis of the spectra and partial least squares regression to develop the calibration models between analytical and spectral data. The results support that NIR spectroscopy, in combination with multivariate calibration, is a promising technique applied to biodiesel quality control, in both laboratory and industrial-scale samples.
Abstract: The transesterification of vegetable oils, animal fats or waste oils with an alcohol (such as methanol) in the presence of a homogeneous catalyst (sodium hydroxide or methoxyde) is commonly used to produce biodiesel. The quality control of the final product is an important issue and near infrared (NIR) spectroscopy recently appears as an appealing alternative to the conventional analytical methods. The use of NIR spectroscopy for this purpose first involves the development of calibration models to relate the near infrared spectrum of biodiesel with the analytical data. The type of pre-processing technique applied to the data prior to the development of calibration may greatly influence the performance of the model. This work analyses the effect of some commonly used pre-processing techniques applied prior to partial least squares (PLS) and principal components regressions (PCR) in the quality of the calibration models developed to relate the near infrared spectrum of biodiesel and its content of methanol and water. The results confirm the importance of testing various pre-processing techniques. For the water content, the smaller validation and prediction errors were obtained by a combination of a second order Savitsky-Golay derivative followed by mean centring prior to PLS and PCR, whereas for methanol calibration the best results were obtained with a first order Savitsky-Golay derivative plus mean centring followed by the orthogonal signal correction.
