Method development for forensic oil identification by direct analysis in real time time-of-flight mass spectrometry
- Language of the publication
- English
- Date
- 2023-11-02
- Type
- Submitted manuscript
- Author(s)
- Tikkisetty, Krishnaja
- Filewood, Taylor
- Yan, Jeffrey
- Kwok, Honoria
- Brunswick, Pamela
- Cody, Robert
- Shang, Dayue
- Publisher
- Royal Society of Chemistry
Abstract
The current well established chromatography and mass spectrometry based oil spill identification procedures, such as those outlined by the European Committee for Standardization, are highly reliable as methods, highly defensible in the court of law, and widely applicable to majority of oil spill situations. Nevertheless, the methodology is time consuming and labour intensive, which may not be ideal when dealing with emerency oil spill situation. In this study, direct analysis in real time time-of-flight mass spectrometry (DART/TOFMS) was used to successfully develop an efficient oil identification method. To confirm the accuracy of this method the spilled oil samples were tested from five previous years of blind Round Robin testing organized by the oil spill identification network of experts (OSINET) under the Bonn Agreement. Heatmap inspection, principal component analysis and finally discriminant analysis of principal components were used to arrive final predictions regarding the identities of the spilled oil samples. The results were compared with previous gas chromatography flame ionization detection (GC/FID) and gas chromatography triple quadrupole mass spectrometry (GC/MS/MS) analyses of the same oils. While taking only about a tenth of the time, the DART/TOFMS analysis produced results similar to that of classical GC/FID and GC/MS/MS procedures. The ability of DART/TOFMS to display this level of validity exemplifies its potential a new tool for supplementing classical analyses for oil spill forensics.
Subject
- Nature and environment,
- Science and technology
Rights
Pagination
9 pages
Peer review
No
Open access level
Green
Identifiers
- ISSN
- 1759-9679
Article
- Journal title
- Analytical Methods
- Journal volume
- 15
- Journal issue
- 44
- Accepted date
- 2023-10-16
- Submitted date
- 2023-07-25
Relation
- Is replaced by:
- https://doi.org/10.1039/D3AY01282D