A Comparative Analysis of Analytical Techniques for Rapid Oil Spill Identification

The complex chemical composition of crude oils presents many challenges for rapid chemical characterization in the case of a spill. A number of approaches are currently used to fingerprint petroleum-derived samples. Gas chromatography coupled with mass spectrometry (GC-MS) is the most common, albeit not very rapid, technique; however, with GC-MS alone, it is difficult to resolve the complex substances in crude oils. The present study examined the potential application of ion mobility spectrometry-mass spectrometry (IMS-MS) coupled with chem-informatic analyses as an alternative high-throughput method for the chemical characterization of crude oils. We analyzed 19 crude oil samples from on- and offshore locations in the Gulf of Mexico region in the United States using both GC-MS (biomarkers, gasoline range hydrocarbons, and n-alkanes) and IMS-MS (untargeted analysis). Hierarchical clustering, principal component analysis, and nearest neighbor-based classification were used to examine sample similarity and geographical groupings. We found that direct-injection IMS-MS performed either equally or better than GC-MS in the classification of the origins of crude oils. In addition, IMS-MS greatly increased the sample analysis throughput (minutes vs hours per sample). Finally, a tabletop science-to-practice exercise, utilizing both the GC-MS and IMS-MS data, was conducted with emergency response experts from regulatory agencies and the oil industry. This activity showed that the stakeholders found the IMS-MS data to be highly informative for rapid chemical fingerprinting of complex substances in general and specifically advantageous for accurate and confident source-grouping of crude oils. Collectively, the present study shows the utility of IMS-MS as a technique for rapid fingerprinting of complex samples and demonstrates its advantages over traditional GC-MS-based analyses when used for decision-making in emergency situations. Environ Toxicol Chem 2021;00:1-16. (c) 2020 SETAC

Automated summary

This study examined the potential of IMS-MS as a high-throughput method for the chemical characterization of crude oils, finding it to be either equal or better than GC-MS in classifying the origins of crude oils and greatly increasing sample analysis throughput. The study demonstrated the utility of IMS-MS for rapid fingerprinting of complex samples and showed its advantages over traditional GC-MS-based analyses in emergency decision-making situations.