Effects of short-term weathering on the stable carbon isotope compositions of crude oils and fuel oils. Issue 1 (15th June 2017)

• Record Type: Journal Article
• Authors: Liu, Yu; Xu, Jixiang; Chen, Wenjing; Li, Ying
• Is Part Of: Marine pollution bulletin. Volume 119:Issue 1(2017)
• Page Start: 238
• Page End: 244
• Publication Date: 2017-06-15
• Subjects: Oil spills -- n-Alkanes -- Diagnostic ratios -- Stable carbon isotope -- Short-term weathering; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2017.04.003
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: A short-term simulated weathering experiment was performed on two crude oils and two heavy fuel oils under natural conditions to evaluate the effects of natural weathering processes by using gas chromatography–mass spectrometry combined with gas chromatography–isotopic ratio mass spectrometry. The results of diagnostic ratios of n-alkanes show that only odd to even predominance (OEP1, OPE2) and carbon preference index (CPI) remain stabilized during the 28 d weathering process, but they cannot effectively distinguish the four types of oils. Statistical analyses based on paired sample t -test and principal component analysis (PCA) revealed that stable carbon isotope compositions of n -alkanes in the four studied oils have no significant changes over the weathering time, and that the carbon isotope discrimination (Δδ 13 C) of n-alkanes is < 3‰. We have provided evidence that the stable carbon isotope compositions of n -alkanes compared to n -alkanes diagnostic ratios significantly improve the efficiency and fidelity of the oil fingerprint identification. Highlights: The isotopic fingerprint of oil spill is more resistant to weathering than chemical fingerprints. The oil samples cannot be distinguished by chemical composition, which can be identified by stable isotopic composition. Oil spill identification capability can be improved by statistical analysis combined with carbon isotope fingerprints.