Screening Brazilian Commercial Gasoline Quality by ASTM D6733 GC and Pattern-Recognition Multivariate SIMCA Chemometric Analysis

Gomes, Gláucia Silvério; Santos, Bruno César Diniz Brito dos; Oliveira, José Eduardo de; Flumignan, Danilo Luiz

doi:10.1365/s10337-009-0958-6

Cited by 7 publications

(3 citation statements)

References 7 publications

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“…Fuel quality is one of the essential parameters of environmental assessment and a measure of public health, necessary for the developing economies. Due to the financial benefits arising from the taxation policy of the Government, automotive gasoline and diesel are often adulterated to maximize the profits [2,[6][7][8][9]. The selection criteria for adulterant are based on its ready miscibility with the fuel, availability at cheaper rates and similarity in the physicochemical properties as compared to the unadulterated fuel.…”

Section: Introductionmentioning

confidence: 99%

Determination of kerosene as an adulterant in diesel through chromatography and high-resolution mass spectrometry

et al. 2019

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In India, adulteration of petroleum-based automotive fuels is a serious concern which has attracted the attention of media and regulators from time to time. Monitoring adulteration of automotive fuels is often challenging due to the similarity in the properties of adulterants with that of the fuel (gasoline or diesel). The present study investigates a typically prevalent case of Euro IV diesel fuel adulteration with low-value subsidized kerosene. Diesel samples contaminated with kerosene were analyzed for density, viscosity, atmospheric distillation, aniline point, total sulfur and cetane index to generate an initial assessment of the adulteration. In view of the inadequacy of these methods in identifying the diesel adulteration even with up to 40% kerosene, chromatographic [gas chromatography (GC) and high-performance liquid chromatography (HPLC)] and high-resolution mass spectrometric (HRMS) analysis were carried out to detect the fingerprint regions in samples. Total sulphur, aniline point and atmospheric distillation (recovery at 250 °C) gives primary evidence for determining the presence of kerosene (adulterant) in diesel fuel. There was a considerable increase in the n-C 10 to n-C 12 and decrease in n-C 15 to n-C 20 hydrocarbons in the adulterated samples through GC. Similarly, the HRMS measurements showed a significant increase of alkylbenzenes concentration in the adulterated samples. A good correlation was observed between HPLC and HRMS results of saturates, mono, di, tri+-aromatics in adulterated diesel samples. The Student's t test showed an excellent correlation between the values of different hydrocarbon groups in all the samples obtained with HPLC and HRMS analysis.

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Section: Introductionmentioning

confidence: 99%

Determination of kerosene as an adulterant in diesel through chromatography and high-resolution mass spectrometry

et al. 2019

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“…Usually, amongst all analytical techniques, gas chromatographic and infrared spectroscopic methods are employed for establishing adulteration and predict physicochemical parameters in gasoline [10][11][12][13][14][15][16][17][18][19][20]. However, chromatographic techniques are generally slow, time-consuming and expensive for the analysis of a large number of samples, making impracticable its in routine application.…”

Section: Introductionmentioning

confidence: 99%

Multivariate calibrations on 1H NMR profiles for prediction of physicochemical parameters of Brazilian commercial gasoline

Flumignan

Sequinel

Hatanaka

et al. 2012

Fuel

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“…Among all analytical techniques, gas chromatography (GC) methods are employed for establishing adulteration and predict physicochemical parameters in gasoline. − However, these techniques are generally slow, time-consuming and expensive for the analysis of a large number of samples, making impracticable its in routine application. On the other hand, spectroscopy methods are quite suitable for such determinations. − Especially, NMR spectroscopy has become a powerful tool for gasoline analysis without pretreatment. − Besides that, 13 C NMR measurements are fast and can be easily automated, allowing the analysis of a large number of samples in a short period of time and, therefore, are recommended for routine applications in quality-control monitoring programs.…”

Section: Introductionmentioning

confidence: 99%

Carbon Nuclear Magnetic Resonance Spectroscopic Profiles coupled to Partial Least-Squares Multivariate Regression for Prediction of Several Physicochemical Parameters of Brazilian Commercial Gasoline

et al. 2012

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Brazilian commercial gasoline follows a rigid quality control, regulated by Brazilian Government Petroleum, Natural Gas, and Biofuels Agency, ANP, following international analytical protocols, such as ASTM and ABNT, covered by Regulation ANP No. 309. Each property is a complicated function of the gasoline chemical composition, which would be represented by diverse types of mathematical correlations. However, these correlations are not adjusted to Brazilian gasoline, whose chemical composition is modified by anhydrous ethanol addition. The purpose of this work is to find correlations, using partial least-squares (PLS) regressions, between 13 C NMR Brazilian gasoline fingerprintings and several physicochemical parameters, such as relative density, distillation curve (temperatures related to 10, 50, and 90% of distilled volume, final boiling point and residue), octane numbers (motor and research octane number and antiknock index), hydrocarbon compositions (olefins, aromatics, and saturated) and anhydrous ethanol and benzene. 150 representative gasoline samples, collected randomly from different gas stations, were analyzed following international analytical protocols. All 13 C NMR spectroscopic fingerprintings, reported in parts per million (ppm), FIDs (free induction decays) were zero filled and Fourier transformed. A data matrix, composed of 13 C NMR chemical shifts and physicochemical parameters, was constructed and used in PLS regression. 13 C NMR fingerprinting of 100 gasoline samples were employed in the training set, and 50 samples formed the prediction set. In 13 C NMR-PLS models, root-mean square error of calibration (RMSEC) and prediction (RMSEP) were the mains parameters considered to select the "best model", which shown results roughly similar in magnitude to the repeatability and reproducibility of ASTM and NBR officials analytical protocols. 13 C NMR-PLS multivariate regression, as an alternative analytical methodology, offers an appealing procedure for commercial automotive gasoline quality control.

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Screening Brazilian Commercial Gasoline Quality by ASTM D6733 GC and Pattern-Recognition Multivariate SIMCA Chemometric Analysis

Cited by 7 publications

References 7 publications

Determination of kerosene as an adulterant in diesel through chromatography and high-resolution mass spectrometry

Determination of kerosene as an adulterant in diesel through chromatography and high-resolution mass spectrometry

Multivariate calibrations on 1H NMR profiles for prediction of physicochemical parameters of Brazilian commercial gasoline

Carbon Nuclear Magnetic Resonance Spectroscopic Profiles coupled to Partial Least-Squares Multivariate Regression for Prediction of Several Physicochemical Parameters of Brazilian Commercial Gasoline

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