Chemometrics analysis of petroleum-based accelerants in fire debris

Petroleum-based accelerants such as diesel, gasoline, kerosene and others are usually related to fire debris analysis because they are inexpensive, readily available and commonly used to enhance the burning intensity of fire. However, combustion process and the presence of pyrolysis products can lea...

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Main Author:	Ahmad Shuhaimi, Fatin Amalina
Format:	Thesis
Language:	English
Published:	2015
Subjects:	QD Chemistry
Online Access:	http://eprints.utm.my/id/eprint/53622/1/FatinAmalinaMFS2015.pdf
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id	my-utm-ep.53622
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spelling	my-utm-ep.536222020-08-23T07:45:16Z Chemometrics analysis of petroleum-based accelerants in fire debris 2015-04 Ahmad Shuhaimi, Fatin Amalina QD Chemistry Petroleum-based accelerants such as diesel, gasoline, kerosene and others are usually related to fire debris analysis because they are inexpensive, readily available and commonly used to enhance the burning intensity of fire. However, combustion process and the presence of pyrolysis products can lead to misclassification of accelerants to the arson investigator. Furthermore, fire debris which has been exposed for several days may undergo some component lost and makes the detection more difficult. In this study, gas chromatography-mass spectrometry (GC-MS) was used to identify the accelerants present in simulated arson incidents. Total ion chromatogram and the peak area from the GC-MS data were used to perform chemometrics techniques which include principal component analysis (PCA), linear discriminant analysis (LDA), partial least square-discriminant analysis (PLS-DA) and support vector machine (SVM). The performance of these methods was further tested by analyzing samples which have been exposed for several days in the environment. Three accelerant classes were formed by these classification models which consist of gasoline, kerosene and diesel. Supervised pattern recognition technique showed satisfactory results, in terms of correctly classified samples, which were 90.4% (LDA), 85.3% (PLS-DA) and 96.7% (SVM) for training sets. A test set produced a value of 87.5% correct classification for LDA, 83.3% for PLS-DA while the best classification is 91.7% by SVM. Fire debris analysis using GC-MS with the aid of chemometrics methods give a promising result in the identification and classification of accelerants used to initiate the fire in arson cases. 2015-04 Thesis http://eprints.utm.my/id/eprint/53622/ http://eprints.utm.my/id/eprint/53622/1/FatinAmalinaMFS2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:84651 masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QD Chemistry
spellingShingle	QD Chemistry Ahmad Shuhaimi, Fatin Amalina Chemometrics analysis of petroleum-based accelerants in fire debris
description	Petroleum-based accelerants such as diesel, gasoline, kerosene and others are usually related to fire debris analysis because they are inexpensive, readily available and commonly used to enhance the burning intensity of fire. However, combustion process and the presence of pyrolysis products can lead to misclassification of accelerants to the arson investigator. Furthermore, fire debris which has been exposed for several days may undergo some component lost and makes the detection more difficult. In this study, gas chromatography-mass spectrometry (GC-MS) was used to identify the accelerants present in simulated arson incidents. Total ion chromatogram and the peak area from the GC-MS data were used to perform chemometrics techniques which include principal component analysis (PCA), linear discriminant analysis (LDA), partial least square-discriminant analysis (PLS-DA) and support vector machine (SVM). The performance of these methods was further tested by analyzing samples which have been exposed for several days in the environment. Three accelerant classes were formed by these classification models which consist of gasoline, kerosene and diesel. Supervised pattern recognition technique showed satisfactory results, in terms of correctly classified samples, which were 90.4% (LDA), 85.3% (PLS-DA) and 96.7% (SVM) for training sets. A test set produced a value of 87.5% correct classification for LDA, 83.3% for PLS-DA while the best classification is 91.7% by SVM. Fire debris analysis using GC-MS with the aid of chemometrics methods give a promising result in the identification and classification of accelerants used to initiate the fire in arson cases.
format	Thesis
qualification_level	Master's degree
author	Ahmad Shuhaimi, Fatin Amalina
author_facet	Ahmad Shuhaimi, Fatin Amalina
author_sort	Ahmad Shuhaimi, Fatin Amalina
title	Chemometrics analysis of petroleum-based accelerants in fire debris
title_short	Chemometrics analysis of petroleum-based accelerants in fire debris
title_full	Chemometrics analysis of petroleum-based accelerants in fire debris
title_fullStr	Chemometrics analysis of petroleum-based accelerants in fire debris
title_full_unstemmed	Chemometrics analysis of petroleum-based accelerants in fire debris
title_sort	chemometrics analysis of petroleum-based accelerants in fire debris
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2015
url	http://eprints.utm.my/id/eprint/53622/1/FatinAmalinaMFS2015.pdf
_version_	1747817596723396608

Chemometrics analysis of petroleum-based accelerants in fire debris

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