Journal
FUEL
Volume 283, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2020.118854
Keywords
Crude oil; Fuels; Chemometrics; NIR portable
Categories
Funding
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil (CAPES) [001]
- LABPETROUFES
- FAPES [33530.503.20537.12092017]
- CAPES [23038.007083/2014-40]
- CNPq [422515/2016-7, 305359/2017-7]
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This study highlights the effectiveness of a portable NIR spectrometer in discriminating and quantifying crude oils and derivatives in blends. Regression models can accurately quantify oil content in mixtures, while PLS-DA allows for the identification of different products with high sensitivity and specificity.
Improper mixtures of: motor oil with crude oil; and derivatives mixed with other derivatives of lesser commercial value were identified in Brazil by companies in the energy sector. This study shows the great response that a portable NIR spectrometer had to discriminate crude oils and derivatives and to quantify them in blends (crude oils with used motor oil; and naphtha, gasoline, diesel, and kerosene). NIR spectra set were acquired in triplicate using a microNIR (TM) portable spectrometer, where it was possible to discriminate crude oil from used motor oil with 100% sensitivity, specificity, and precision. Regression models can quantify the oil content of a ternary mixture containing two crude oils (light and heavy oil) and a used motor oil with root mean square error of prediction (RMSEP) of 6.2 and 4.8 wt%, and R(2)p = 0.9871 and 0.9870 for support vector regression (SVR) and partial least squares (PLS), respectively. About the NIR spectra of naphtha, gasoline, diesel, and kerosene, partial least squares discriminant analysis (PLS-DA) allows the identification of any of these products with sensitivity, specificity, and precision of 100%. For the blends of gasoline and naphtha, the limit of detection (LOD), limit of quantification (LOQ), and RMSEP were 1.3, 4.4, and 1.4 wt%, respectively. Likewise, for diesel and kerosene blends, the PLS model allows the identification of the diesel with LOD, LOQ, and RMSEP of 2.8 wt %, 9.3 wt%, and 11.4 wt%, respectively.
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