Modeling the GCxGC Elution Patterns of a Hydrocarbon Structure Library To Innovate Environmental Risk Assessments of...

Area of Science:

• Analytical Chemistry
• Environmental Science
• Petroleum Geochemistry

Background:

• Comprehensive two-dimensional gas chromatography (GCxGC) excels at separating complex petroleum mixtures.
• Interpreting GCxGC data for petroleum composition is challenging and requires specialized expertise.
• Existing industry methods for hydrocarbon blocks (HCBs) lack transparent links to GCxGC data, hindering environmental risk assessment.

Purpose of the Study:

• To develop a GCxGC elution model for predicting petroleum substance compositions.
• To establish a transparent association between HCBs and GCxGC chromatogram data.
• To facilitate environmental risk assessments of petroleum substances and related environmental samples.

Main Methods:

• Developed a GCxGC elution model for user-defined petroleum compositions.
• Calibrated the model using experimental GCxGC retention times of 56 known hydrocarbons.
• Simulated retention times for over 15,000 hydrocarbon structures (C10-C30) across 11 classes.

Main Results:

• GCxGC retention times were quantitatively associated with hydrocarbon class and carbon number.
• The model accurately predicted retention times for a wide range of petroleum constituents.
• Simulation data demonstrated the model's utility across diverse petroleum substance types.

Conclusions:

• The developed GCxGC elution model enhances the transparency and efficiency of petroleum substance analysis.
• This innovation supports improved methods for investigating chemical compositions and environmental properties of petroleum.
• Facilitates more robust environmental risk assessments by connecting compositional data to GCxGC analysis.