A multivariate approach to oil hydrocarbon fingerprinting and spill source identification

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Tiered approaches for oil spill fingerprinting have evolved rapidly since the 1990s. Chemometrics provides a large number of tools for pattern recognition, calibration, and classification that can increase the speed and the objectivity of the fingerprinting analysis and allow for more extensive use of the available data. A framework (integrated multivariate oil hydrocarbon fingerprinting - IMOF) for the use of chemometric approaches in tiered oil spill fingerprinting is presented in this chapter. It consists of four main steps where a suite of analytical instruments, data preprocessing and multivariate statistical methods, as well as data evaluation and visualization tools have been tested. IMOF is exemplified using parallel factor analysis of fluorescence excitation-emission spectra, and pixel-based analysis of gas chromatography - mass spectrometry selected ion chromatograms (GC-MS SICs). Its application to other data types such as GC-flame ionization detection, liquid chromatography-MS, and two-dimensional GC and LC are briefly discussed.

Original languageEnglish
Title of host publicationStandard handbook oil spill environmental forensics : fingerprinting and source identification
EditorsScott Stout, Zhendi Wang
Number of pages42
PublisherElsevier
Publication date2016
Edition2.
Pages747-788
Chapter16
ISBN (Print)978-0-12-803832-1
DOIs
Publication statusPublished - 2016

    Research areas

  • Chemometrics, Fluorescence spectroscopy, GC-FID, GC-MS, Multivariate data analysis, Oil classification, Oil matching, Pattern recognition, Pixel-based analysis

ID: 172029276