Articles producció científica> Química Analítica i Química Orgànica

Near-Infrared Spectroscopy Coupled with Multivariate Methods for the Characterization of Ethanol Adulteration in Premium 91 Gasoline

  • Identification data

    Identifier: imarina:3661895
    Authors:
    Mabood F., Boqué R., Hamaed A., Jabeen F., Al-Harrasi A., Hussain J., Alameri S., Albroumi M., Al Nabhani M., Naureen Z., Al Rawahi M., Al Futaisi F.
    Abstract:
    Ethanol, as a result of its high octane rating of 108, is often added as adulterant to premium 91 gasoline fuels to boost up their octane ratings to 96 or more, but it does not provide the same power to the engine as that of superpremium 96 gasoline fuels. In this study, sensitive near-infrared spectroscopy (NIRS) coupled with chemometrics was proposed for analysis of the ethanol content in premium 91 gasoline fuels. Standard samples of premium 91 octane gasoline were collected from Oman Oil Refineries and Petroleum Industries Company commonly known as ORPIC. The premium 91 samples were then intentionally spiked with ethanol at various levels. NIRS was employed in the absorption mode to obtain the spectra of all samples scanning from 700 to 2500 nm. Then, partial least squares regression (PLSR), partial least squares discriminant analysis (PLS-DA), and principal component analysis (PCA) were applied to model and interpret the near-infrared (NIR) spectra. A PLS-DA model was developed to discriminate between the pristine gasoline samples and those intentionally mixed with ethanol, with excellent results [R2 = 98% and root-mean-square error (RMSE) = 0.049%] by random cross-validation. A PLSR model was established to determine the ethanol content in premium 91 gasoline samples, with values of R2 = 99% and root-mean-square error of cross-validation (RMSECV) = 1.88% and R2 = 99% and root-mean-square error of prediction (RMSEP) = 1.58 for cross-validation and test-set validation results, respectively. This newly developed method is simple and rapid and can quantify less than 2% ethanol adulteration in premium 91 gasolines.
  • Others:

    Author, as appears in the article.: Mabood F., Boqué R., Hamaed A., Jabeen F., Al-Harrasi A., Hussain J., Alameri S., Albroumi M., Al Nabhani M., Naureen Z., Al Rawahi M., Al Futaisi F.
    Department: Química Analítica i Química Orgànica
    URV's Author/s: Boqué Martí, Ricard
    Keywords: Nir Multivariate analysis Gasoline Adulteration
    Abstract: Ethanol, as a result of its high octane rating of 108, is often added as adulterant to premium 91 gasoline fuels to boost up their octane ratings to 96 or more, but it does not provide the same power to the engine as that of superpremium 96 gasoline fuels. In this study, sensitive near-infrared spectroscopy (NIRS) coupled with chemometrics was proposed for analysis of the ethanol content in premium 91 gasoline fuels. Standard samples of premium 91 octane gasoline were collected from Oman Oil Refineries and Petroleum Industries Company commonly known as ORPIC. The premium 91 samples were then intentionally spiked with ethanol at various levels. NIRS was employed in the absorption mode to obtain the spectra of all samples scanning from 700 to 2500 nm. Then, partial least squares regression (PLSR), partial least squares discriminant analysis (PLS-DA), and principal component analysis (PCA) were applied to model and interpret the near-infrared (NIR) spectra. A PLS-DA model was developed to discriminate between the pristine gasoline samples and those intentionally mixed with ethanol, with excellent results [R2 = 98% and root-mean-square error (RMSE) = 0.049%] by random cross-validation. A PLSR model was established to determine the ethanol content in premium 91 gasoline samples, with values of R2 = 99% and root-mean-square error of cross-validation (RMSECV) = 1.88% and R2 = 99% and root-mean-square error of prediction (RMSEP) = 1.58 for cross-validation and test-set validation results, respectively. This newly developed method is simple and rapid and can quantify less than 2% ethanol adulteration in premium 91 gasolines.
    Thematic Areas: Química Materiais Interdisciplinar Geociências General chemical engineering Fuel technology Farmacia Ensino Engineering, chemical Engenharias iii Engenharias ii Engenharias i Energy engineering and power technology Energy & fuels Economia Ciências biológicas ii Ciências ambientais Ciências agrárias i Ciência de alimentos Chemical engineering (miscellaneous) Chemical engineering (all) Biotecnología Astronomia / física
    ISSN: 15205029
    Author's mail: ricard.boque@urv.cat
    Author identifier: 0000-0001-7311-4824
    Last page: 7597
    Record's date: 2024-09-07
    Journal volume: 31
    Papper version: info:eu-repo/semantics/acceptedVersion
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Energy & Fuels. 31 (7): 7591-7597
    APA: Mabood F., Boqué R., Hamaed A., Jabeen F., Al-Harrasi A., Hussain J., Alameri S., Albroumi M., Al Nabhani M., Naureen Z., Al Rawahi M., Al Futaisi F. (2017). Near-Infrared Spectroscopy Coupled with Multivariate Methods for the Characterization of Ethanol Adulteration in Premium 91 Gasoline. Energy & Fuels, 31(7), 7591-7597. DOI: 10.1021/acs.energyfuels.7b00870
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2017
    First page: 7591
    Publication Type: Journal Publications
  • Keywords:

    Chemical Engineering (Miscellaneous),Energy & Fuels,Energy Engineering and Power Technology,Engineering, Chemical,Fuel Technology
    Nir
    Multivariate analysis
    Gasoline
    Adulteration
    Química
    Materiais
    Interdisciplinar
    Geociências
    General chemical engineering
    Fuel technology
    Farmacia
    Ensino
    Engineering, chemical
    Engenharias iii
    Engenharias ii
    Engenharias i
    Energy engineering and power technology
    Energy & fuels
    Economia
    Ciências biológicas ii
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Chemical engineering (miscellaneous)
    Chemical engineering (all)
    Biotecnología
    Astronomia / física
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