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Journal of Chromatography A
Volume 1137, Issue 1, 22 December 2006, Pages 101-109
 
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doi:10.1016/j.chroma.2006.10.015    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2006 Elsevier B.V. All rights reserved.

Differentiation of types of crude oils in polluted soil samples by headspace-fast gas chromatography–mass spectrometry

José Luis Pérez Pavóna, Corresponding Author Contact Information, E-mail The Corresponding Author, Armando Guerrero Peñab, Carmelo García Pintoa and Bernardo Moreno Corderoa

aDepartamento de Química Analítica, Nutrición y Bromatología, Facultad de Ciencias Químicas, Universidad de Salamanca, 37008 Salamanca, Spain bLaboratorio de Suelos, Plantas y Aguas, Campus Tabasco, Colegio de Postgraduados, Supera-Anuies, Mexico

Received 7 July 2006; 
revised 3 October 2006; 
accepted 3 October 2006. 
Available online 23 October 2006.

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Abstract

The coupling of a headspace sampler to a fast gas chromatography system with mass spectrometry detection is proposed as a method for the identification of the sources of contamination in soils due to the presence of hydrocarbons derived from petroleum. The samples are subjected to the headspace generation process, with no prior treatment, and the volatiles generated are separated by fast gas chromatography. The total time of the chromatogram per sample is less than six minutes. Chemometric treatments, such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and soft independent modelling of class analogy (SIMCA) were applied to the signals obtained for the different samples. The variables used for the chemometric treatments include m/z ratios characteristic of linear and branched saturated hydrocarbons, alkyl cyclohexanes, benzene, toluene, xylenes, C3-benzenes, naphthalene and methyl-naphthalenes. The results obtained show clear differentiated clusters for the different crude oils and correct predictions when SIMCA is applied, thus allowing the differentiation of types of crude oils contaminating soils in a rapid and reliable manner.

Keywords: Crude oils differentiation; Polluted soils; Headspace; Fast gas chromatography; Mass spectrometry

Article Outline

1. Introduction
2. Experimental
2.1. Matrices
2.2. Types of crude oils
2.3. Samples
2.4. Apparatus
2.5. Procedure
2.6. Data analysis
3. Results and discussion
3.1. Analysis of the crude oil samples studied
3.2. Identification of the type of crude oil present in polluted soils by HS-Fast GC–MS
3.2.1. Hierarchical cluster analysis
3.2.2. Principal component analysis
3.2.3. Soft independent modeling of class analogy
3.2.4. Construction of a single model for the identification of sources of pollution
4. Conclusions
Acknowledgements
References











Journal of Chromatography A
Volume 1137, Issue 1, 22 December 2006, Pages 101-109
 
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