Efficient oil spill identification utilizing hydrophobic sampling paper and gas chromatography/mass spectrometry

Abstract

With oil spills imposing detrimental effects on marine environments and their associated legal implications, accurate and efficient oil spill identification is crucial to determine clean-up procedures and assign responsibility. The standard forensic method for oil spill identification, developed by the European Committee for Standardization (CEN), utilizes gas chromatography mass spectrometry (GC/MS) and comparison of diagnostic ion ratios derived from hydrocarbon biomarkers to match source oil samples with environmental spills. This study explored the use of hydrophobic paper as a convenient sampling method for oil spill forensic investigation. Hydrophobic paper was dipped into the surface of unweathered and weathered oil slicks including marine diesel, crude oil, and heavy fuel oils prior to simple extraction in a binary organic solvent. The extracts were concentrated by nitrogen blowdown and analyzed by GC/MS for subsequent diagnostic ion ratio analysis and ion ratio bar graph oil-matching comparison. Simulated environmental oil samples were successfully matched with their source materials after forty-three days of weathering for all the listed oils apart from heavy fuel oils, which were identified after fifty days. The use of the convenient paper sampling technique in conjunction with GC/MS diagnostic ratio analysis demonstrated a promising approach to enhance the efficiency of oil spill forensic investigations.

Graphical abstract: Efficient oil spill identification utilizing hydrophobic sampling paper and gas chromatography/mass spectrometry

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Article information

Article type
Paper
Submitted
26 Mar 2025
Accepted
04 Jul 2025
First published
11 Jul 2025

Anal. Methods, 2025, Advance Article

Efficient oil spill identification utilizing hydrophobic sampling paper and gas chromatography/mass spectrometry

J. Shaw, J. Lesuk, L. Rabinovitch, T. Filewood, H. Kwok, J. Yan, P. Brunswick, T. Huan and D. Shang, Anal. Methods, 2025, Advance Article , DOI: 10.1039/D5AY00503E

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