Detailed Hydrocarbon Analysis by GC-VUV Using ASTM D8369

Significance of the topic

The detailed compositional analysis of gasoline is essential because fuel composition strongly affects physical and combustion properties, regulatory compliance, and downstream processing. Traditional flame ionization detector (FID)-based Detailed Hydrocarbon Analysis (DHA) methods provide extensive separation but are time-consuming and can suffer from coelution and ambiguous identifications. Vacuum ultraviolet (VUV) detection combined with spectral deconvolution and retention index (RI) libraries offers faster, more reliable identification and quantitation of complex gasoline mixtures, enabling routine, high-confidence PIONA (Paraffins, Isoparaffins, Olefins, Naphthenes, Aromatics) profiling and oxygenate analysis under ASTM D8369.

Objectives and study overview

This application note demonstrates compositional gasoline analysis using a Nexis GC-2030 equipped with a VUV detector (VGA-101) following ASTM D8369 (Verified Hydrocarbon Analysis). The goals were to: validate a GC‑VUV workflow for identification and quantitation of gasoline constituents; show spectral deconvolution of coeluted peaks; compare quantitative accuracy to the conventional ASTM D6730 (FID) approach; and demonstrate streamlined QC and automated data processing using VUV Analyze software.

Methodology and instrumentation

The study applied an RI-based workflow beginning with measurement of an alkane retention index mix (VUV-RT) to build an RI file, followed by system validation (VUV1) and QC verification (VUV-CS) prior to sample analysis. Key analytical features included spectral matching against a VUV absorbance library, automated deconvolution of coeluting peaks (up to five components), and the Corrected Percentage Peak Area Method for quantitation as specified in D8369.

Instrumentation used

• Gas chromatograph: Nexis GC-2030 with AOC-30i autosampler.
• VUV detector: VGA-101 (VUV).
• Column: SH-1 (60 m × 0.25 mm I.D. × 0.25 μm).
• Auxiliary: CRG-2030 low-temperature column oven control (N2) for improved low-boiling separation.
• Software: LabSolutions (GC control), VUVision (VUV control), VUV Analyze (spectral deconvolution, RI handling, automated reports).

Key method parameters (representative): injection temperature 250 °C, column flow 2.0 mL/min (He), split 300, injection volume 1.0 μL, oven program with initial hold and multi-rate ramps to 200 °C, transfer line and flow cell 275 °C, makeup gas pressure ~0.60 psi, acquisition frequency 5.0 Hz.

Main results and discussion

• Spectral identification and deconvolution: VUV absorbance spectra provided compound-class-specific signatures (paraffins, isoparaffins, naphthenes, aromatics, olefins, oxygenates) that, together with RI data, enabled reliable identification of coeluting peaks. The VUV Analyze software successfully decomposed complex absorbance profiles into library components (example: 2,3,3-trimethylpentane + toluene), with low residuals indicating accurate fits.

• Speed and throughput: Using GC-VUV and the D8369 workflow reduced analysis time from roughly three hours (typical FID DHA per D6730) to approximately 49–50 minutes while maintaining identification fidelity due to combined RI and spectral criteria.

• Quantitative accuracy: Analysis of a certified multi-component standard showed measured values within 0.5 vol% of certified concentrations for key analytes (benzene, toluene, xylene, methanol, ethanol, MTBE, ETBE), demonstrating quantitative equivalence to ASTM D6730 (FID) results.

• QC and validation: System validation used VUV1 and VUV-CS standards. Acceptance checks included benzene response tuning (target ~2.25–2.75), PIONA mass percentage verification, and relative sensitivity checks (tetradecane/pentane, C14/C5). The dedicated VUV Analyze methods automated qualitative/quantitative calls and pass/fail reporting, ensuring reproducible system readiness prior to routine sample runs.

• Data visualization and reporting: Results can be reviewed as color-coded chromatograms by PIONA class, two-dimensional carbon-number vs. class tables, and individual component concentration reports. The software displays absorbance spectra per retention time and residuals for transparency of assignments.

Benefits and practical applications

• Faster throughput: Substantially reduced run time compared with long FID DHA separations, increasing sample throughput for routine QC and research.
• Improved identification confidence: Combining spectral fingerprints with RI reduces misidentification risk for coeluted species and structurally similar compounds.
• Automated workflow: VUV Analyze supports automated RI calibration, spectral matching, deconvolution, quantitation, and pass/fail QC, decreasing analyst time and subjectivity.
• Method flexibility: A single VUV detector can support multiple ASTM methods (D8369, D8071, D8267, D8368) by changing columns, allowing analysis of gasoline, diesel, and jet fuel on the same platform.

Future trends and potential applications

The incorporation of VUV spectral detection into routine fuel analysis is likely to expand as spectral libraries grow and software deconvolution improves. Expected developments include: enhanced automated library matching with machine-learning-driven spectral deconvolution, broader validated methods for biofuel and blended fuels (oxygenates and renewable components), integration with high-throughput routines in refinery QC, and expanded multi-fuel workflows on shared GC-VUV platforms. Increased adoption will also motivate standardized spectral libraries and inter-laboratory validation efforts to further harmonize quantitative results across platforms.

Conclusion

GC-VUV analysis following ASTM D8369 delivers rapid, reliable compositional profiling of gasoline with quantitative performance comparable to conventional FID-based DHA while offering superior handling of coelution via spectral deconvolution. The combined use of retention indices and VUV absorbance spectra provides robust identification, and dedicated software automates validation, QC, and reporting, making this approach attractive for laboratories requiring high-throughput, high-confidence fuel analysis.

References

• ASTM D8369 — Verified Hydrocarbon Analysis by GC-VUV (application context and method framework as used in this study).
• ASTM D6730 — Detailed Hydrocarbon Analysis (FID-based DHA) (comparative reference for traditional method).
• ASTM D8071 — GC-VUV methods for hydrocarbon analysis (related VUV-based method).
• Shimadzu Nexis GC-2030 system documentation and VGA-101 VUV detector (instrumentation and configuration details summarized in the study).
• VUV Analyze and VUVionics application notes and software documentation (spectral deconvolution and automated reporting functionality).