Literature DB >> 15013165

Chemical fingerprinting of gasoline. 2. Comparison of unevaporated and evaporated automotive gasoline samples.

P M L Sandercock1, E Du Pasquier.   

Abstract

Analysis of the C(0)- to C(2)-naphthalene compounds present in automotive gasoline using gas chromatography-mass spectrometry with selected ion monitoring (GC-MS (SIM)) and principal component analysis (PCA) was used to discriminate between different samples of gasoline. Phase one of this study explored the ability of this method to differentiate gasoline samples at different levels of evaporation. A total of 35 random samples of unevaporated gasoline, covering three different grades (regular unleaded, premium unleaded and lead replacement), were collected in Sydney, Australia and examined. The high-boiling C(0)- to C(2)-naphthalene compounds present in the gasoline were used to chemically fingerprint each sample at different levels of evaporation. Samples of 25, 50, 75 and 90% evaporated gasoline (by weight) were generated from the 35 samples of unevaporated gasoline. Analysis of the data by PCA followed by linear discriminant analysis (LDA) showed that the 35 samples formed 18 unique groups, irrespective of the level of evaporation. Good discrimination between gasoline samples that were collected on the same day was obtained. Phase two of this study examined the change in gasoline samples over time. The C(0)- to C(2)-naphthalene composition in 96 samples of gasoline collected from three service stations over a 16-week period was examined using the method described. In most cases, it was found that the C(0)- to C(2)-naphthalene profile changed from week to week, and from station to station. In a comparison of all 96 samples together it was found that the majority could be differentiated from one another. The application of the method to forensic casework is discussed.

Entities:  

Year:  2004        PMID: 15013165     DOI: 10.1016/j.forsciint.2003.11.016

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  4 in total

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2.  Artificial intelligence and thermodynamics help solving arson cases.

Authors:  Sander Korver; Eva Schouten; Othonas A Moultos; Peter Vergeer; Michiel M P Grutters; Leo J C Peschier; Thijs J H Vlugt; Mahinder Ramdin
Journal:  Sci Rep       Date:  2020-11-25       Impact factor: 4.379

3.  Characterization and Differentiation of Petroleum-Derived Products by E-Nose Fingerprints.

Authors:  Marta Ferreiro-González; Gerardo F Barbero; Miguel Palma; Jesús Ayuso; José A Álvarez; Carmelo G Barroso
Journal:  Sensors (Basel)       Date:  2017-11-05       Impact factor: 3.576

4.  Effects of Fire Suppression Agents and Weathering in the Analysis of Fire Debris by HS-MS eNose.

Authors:  Barbara Falatová; Marta Ferreiro-González; Carlos Martín-Alberca; Danica Kačíková; Štefan Galla; Miguel Palma; Carmelo G Barroso
Journal:  Sensors (Basel)       Date:  2018-06-14       Impact factor: 3.576

  4 in total

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