Fingerprinting Crude Oils and Tarballs Using Biomarkers and Comprehensive Two-Dimensional Gas Chromatography
Applications | 2013 | RestekInstrumentation
Crude oils contain biomarker compounds that serve as molecular fossils, critical for tracing oil origin in spill events and environmental studies. Traditional one-dimensional GC approaches often struggle with complex mixtures and isobaric interferences. Comprehensive two-dimensional GC coupled with time-of-flight MS (GCxGC-TOFMS) enhances separation power, specificity, and peak capacity, enabling robust oil fingerprinting and forensic matching even for weathered samples.
This study applied GCxGC-TOFMS to analyze a range of crude oils from diverse regions and weathered tarball samples collected along the Florida Gulf Coast following the 2010 Deepwater Horizon spill. By evaluating 43 diagnostic biomarker ratios, the research aimed to (1) establish distinctive molecular profiles for different oils, (2) assess the impact of weathering on fingerprint integrity, and (3) identify potential source matches for tarballs washed ashore up to one year after the incident.
Sample Preparation:
GCxGC-TOFMS offers superior separation power, peak capacity, and specificity for crude oil and tarball fingerprinting compared to 1D GC techniques. The structured two-dimensional chromatograms and comprehensive spectral data facilitate reliable source identification, even for weathered samples, making GCxGC-TOFMS a vital tool for environmental forensics.
GCxGC, GC/MSD, GC/TOF
IndustriesEnvironmental
ManufacturerAgilent Technologies, LECO
Summary
Importance of Topic
Crude oils contain biomarker compounds that serve as molecular fossils, critical for tracing oil origin in spill events and environmental studies. Traditional one-dimensional GC approaches often struggle with complex mixtures and isobaric interferences. Comprehensive two-dimensional GC coupled with time-of-flight MS (GCxGC-TOFMS) enhances separation power, specificity, and peak capacity, enabling robust oil fingerprinting and forensic matching even for weathered samples.
Objectives and Overview
This study applied GCxGC-TOFMS to analyze a range of crude oils from diverse regions and weathered tarball samples collected along the Florida Gulf Coast following the 2010 Deepwater Horizon spill. By evaluating 43 diagnostic biomarker ratios, the research aimed to (1) establish distinctive molecular profiles for different oils, (2) assess the impact of weathering on fingerprint integrity, and (3) identify potential source matches for tarballs washed ashore up to one year after the incident.
Methodology
Sample Preparation:
- Calibration standards included hopane/sterane mixtures, degradation compounds, diamondoids, and deuterated PAH internal standards in isooctane.
- Crude oils were diluted to 10 mg/mL in methylene chloride; a weathered riser oil sample was simulated by evaporative heating to 50% mass.
- Tarballs were extracted in methylene chloride overnight, filtered, spiked with internal standards, and diluted to 1 mL.
Instrumentation
- Instrument: LECO Pegasus 4D GCxGC-TOFMS with Agilent 6890 GC and 7683 autosampler/injector.
- Columns: Rxi-17Sil MS primary (60 m × 0.25 mm × 0.10 µm), Rxi-1HT secondary (1 m × 0.25 mm × 0.10 µm).
- Carrier gas: He at 1 mL/min; injection: 1 µL split 10:1 at 275 °C.
- Oven program: 40 °C (1 min) to 320 °C at 2.5 °C/min; secondary oven offset +5 °C; modulation period 2.8 s.
- MS conditions: EI ionization, m/z 45–550, acquisition rate 100 spectra/sec.
Data Processing
- LECO ChromaTOF™ software with data resampling into three groups: steranes/hopanes, dibenzothiophenes/phenanthrenes, and alkyl benzenes.
- Diagnostic biomarker ratios calculated as 100×A/(A+B), where A and B represent calibrated or internal-standard–normalized areas.
Main Results and Discussion
- Optimized GCxGC conditions achieved high first- and second-dimension separation efficiency, preserving structured chromatograms for complex mixtures.
- GCxGC resolved isobaric interferences, e.g., separating adamantane from coeluting compounds not distinguishable by 1D GC.
- Extracted ion chromatograms of steranes (m/z 217, 218) and hopanes (m/z 191) showed clear pattern differences among oils from the U.S., Canada, Middle East, and Nigeria.
- Inclusion of alkylated dibenzothiophenes and phenanthrenes improved discrimination between geographically close oils.
- Weathering experiments demonstrated loss or alteration of light biomarkers (diamondoids, pristane/phytane), emphasizing the need for robust ratio selection.
- Correlation plots using 43 biomarker ratios confirmed that a weathered riser oil sample remained identifiable versus unweathered source oil.
- Among six tarball samples, one soft-interior tarball (#11) collected in July 2011 showed a strong correlation to the Deepwater Horizon riser oil profile, while others were ruled out.
Benefits and Practical Applications
- Single-injection GCxGC-TOFMS consolidates multiple analyte classes without off-line cleanups, increasing throughput.
- Structured contour plots accelerate compound identification and enable use of non-library biomarkers.
- Enhanced resolution and full mass spectral data reduce false positives from isobaric overlaps, strengthening forensic conclusions.
Future Trends and Applications
- Integration with advanced statistical and chemometric tools for automated source apportionment.
- Expansion of biomarker databases for improved matching of heavily weathered or aged residues.
- Development of field-deployable or portable GCxGC systems to support rapid on-site environmental assessments.
- Combination with high-resolution MS and complementary detectors for deeper molecular insights.
Conclusion
GCxGC-TOFMS offers superior separation power, peak capacity, and specificity for crude oil and tarball fingerprinting compared to 1D GC techniques. The structured two-dimensional chromatograms and comprehensive spectral data facilitate reliable source identification, even for weathered samples, making GCxGC-TOFMS a vital tool for environmental forensics.
References
- C. Hickman, K. Bowman, Crude Oil and Natural Gas Formation, BP Energy Education Program, BP Australia Pty Ltd, 2008.
- L. Faksness, H. Weiss, P. Daling, Revision of the Nordtest Methodology for Oil Spill Identification, SINTEF Report STF66 A02028, 2002.
- L. Blumberg, M. Klee, Characteristic Thermal Constant and Dimensionless Heating Rate; The Links to Optimum Heating Rate in GC, Analytical Chemistry 72 (2000) 4080.
- C. Eiselbeck, R. Nelson, K. Grice, J. Curiale, C. Reddy, Comparison of GC-MS, GC-MRM-MS, and GCxGC for Higher Plant Biomarkers, Geochimica et Cosmochimica Acta 87 (2012) 299.
- Z. Wang, S. Stout, Oil Spill Environmental Forensics: Fingerprinting and Source Identification, Elsevier, 2007.
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