Detailed Hydrocarbon Analysis by Nexis GC-2030 Using ASTM D6730

Detailed Hydrocarbon Analysis of Gasoline by Nexis GC-2030 Using ASTM D6730 — Summary

Importance of the topic:

Gasoline composition comprises hundreds of hydrocarbons plus oxygenates; accurate identification and quantification are essential for refinery process control, regulatory compliance and product quality assurance. Detailed hydrocarbon analysis (DHA) per ASTM D6730 provides compound-level information across a wide boiling range (to ca. 225 °C), enabling better control of blending, octane-rating contributions, emissions-relevant species (e.g., benzene) and oxygenate content (ethanol, MTBE, ETBE). Automation and robust software decrease analyst workload and increase reproducibility for routine QA/QC and research applications.

Objectives and overview of the study/article:

This application note demonstrates compositional analysis of gasoline according to ASTM D6730 using the Shimadzu Nexis GC-2030 equipped with a two-column arrangement and flame ionization detection (FID). It evaluates chromatographic separation, quantitation accuracy versus a certified reference gasoline mixture, and workflows using PONAsolution Ver.6 software to streamline identification and reporting for PIONA/DHA analyses.

Methodology and analytical approach:

- Chromatographic strategy: a slightly polar pre-column (SH PONA Tuning Column, cut from 5.0 m to 3.2 m) was connected to a long nonpolar main column (SH-1 PONA, 100 m) to achieve separation of >100 components specified by ASTM D6730. This two-column arrangement improves resolution of closely eluting pairs that are difficult to resolve on a single column.

- Detector and quantitation: FID was used with the corrected percentage peak area method as required by ASTM D6730. Retention index–based identification is supported by the PONAsolution library tailored to ASTM standards.

- Retention time control: inlet pressure and carrier flow were adjusted so methane retention at 35 °C matched the ASTM retention-time criterion (7.00 ± 0.02 min). Oven program, injection, split and gas flows were set to cover the target boiling range to ~225 °C.

Used instrumentation:

• Gas chromatograph: Nexis GC-2030 with AOC-30i autosampler (SPL injection).
• Injection liner: tapered split/splitless liner with fixed wool (into wool).
• Columns: SH PONA Tuning Column (5.0 m × 0.25 mm I.D. × 1.0 µm, cut to 3.2 m) as pre-column; SH-1 PONA (100 m × 0.25 mm I.D. × 0.5 µm) as main column.
• Detector: FID-2030 (with makeup N2 flow and H2/air detector gases).
• Auxiliary: CRG-2030 CO2 for carrier gas control.
• Software: LabSolutions and PONAsolution Ver.6 (with ASTM-specific retention index libraries).

Main results and discussion:

- Peak resolution: The two-column setup effectively separated challenging pairs (examples: tert-butanol vs. 2‑methylbutene‑2; 1‑methylcyclopentene vs. benzene) demonstrated using an oxy-blend test mixture. The pre-column + long nonpolar main column strategy enhanced selectivity and peak shapes required by ASTM D6730.

- Quantitative accuracy: Analysis of a certified gasoline reference standard showed excellent agreement with certificate values. For evaluated compounds (benzene, toluene, xylene, methanol, ethanol, MTBE, ETBE) measured concentrations differed from certified values by ≤0.5 percentage points, indicating high quantitative fidelity using the ASTM D6730/FID workflow.

- Data processing and workflow gains: PONAsolution Ver.6 provides retention index libraries for ASTM methods and automates key tasks: automatic identification of n‑alkanes (which anchors retention-time correction for the remaining components), two‑point identification for local retention adjustments, overlay of reference and sample chromatograms for manual confirmation, and AART-assisted automatic identification for DHA. These features reduce manual identification time and support generation of PIONA vs. carbon-number tables and individual component concentration reports.

- Comparison with VUV-based methods: ASTM methods using vacuum ultraviolet (VUV) detectors (D8369, D8071) identify compounds by combining retention indices with VUV spectra, which allows spectral deconvolution of coelutions. The D6730/FID approach identifies a larger number of individual compounds (reported ~180) compared with the select compound lists typically handled by D8369 and D8071 with VUV, but FID lacks spectral deconvolution capability—making chromatographic separation and software-based retention-index matching crucial.

Benefits and practical applications:

• Conforms to ASTM D6730 for detailed gasoline composition reporting, useful for refinery QA/QC, blending control, regulatory monitoring and R&D.
• PONAsolution automation reduces labor-intensive peak assignment and speeds routine sample throughput while preserving the ability for manual confirmation when needed.
• Two-column configuration (slightly polar pre-column + long nonpolar main column) provides the chromatographic resolving power necessary to quantify closely eluting species without resorting to spectral detectors.
• High quantitative accuracy demonstrated with certified reference materials (differences ≤0.5% for target analytes).

Limitations and considerations:

• FID cannot provide spectral information for deconvolution of coeluting components; successful identification therefore depends on retention-index libraries and robust chromatographic resolution.
• Extensive method development and maintenance (column life, retention shifts) may be required over time; libraries typically remain valid until column degradation causes retention shifts.
• Analysis time is relatively long due to the need to cover a wide boiling range and separate many components; throughput considerations should be balanced against required detail level.

Future trends and potential applications:

• Hybrid workflows combining retention-index libraries with spectral detectors (VUV, MS) could merge the broad compound coverage of D6730 with spectral deconvolution to handle residual coelutions more robustly.
• Further advances in software—improved spectral libraries, machine‑learning assisted peak deconvolution and automated reporting—will reduce manual oversight and increase throughput.
• Shorter, higher-resolution column technologies and two-dimensional GC approaches could speed analyses while preserving or improving resolution for DHA-level detail.
• Greater standardization and sharing of retention-index libraries across labs will enhance reproducibility for inter-laboratory comparisons and regulatory testing.

Conclusion:

The Nexis GC-2030 configured with a slightly polar pre-column and a long nonpolar SH-1 PONA main column, combined with PONAsolution Ver.6 data processing, can perform ASTM D6730-compliant detailed hydrocarbon analysis of gasoline with high chromatographic resolution and quantitation accuracy. The approach balances chromatographic complexity with software automation to deliver reproducible PIONA and individual compound reports suitable for refinery QC, regulatory monitoring and research applications.

References:

1. Kei Usui, Chisato Kanamori. Detailed Hydrocarbon Analysis by Nexis GC-2030 Using ASTM D6730. Shimadzu Application News, First Edition Apr 2026. Document code: 01-00863-EN.
2. Shimadzu Corporation. Nexis GC-2030 product and software information (LabSolutions, PONAsolution, AOC-30i). Apr 2026.