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Paraffins, Iso-Paraffins, Naphthenes and Aromatics (PINA) in Hydrocarbon Streams

Applications | 2008 | Agilent TechnologiesInstrumentation
GC
Industries
Energy & Chemicals
Manufacturer
Agilent Technologies

Summary

Importance of the topic


Accurate profiling of fuel hydrocarbons by PINA classification is essential for ensuring combustion quality, reducing emissions and meeting regulatory standards.

Objectives and study overview


This work demonstrates a multidimensional GC approach using the PIONA+ system to separate and quantify paraffins, iso-paraffins, naphthenes and aromatics in spark ignition fuel matrices.

Methodology


A three-column network with timed backflushes and thermal trapping directs distinct hydrocarbon classes through OV-275 and CP-Sil 5CB phases. The schedule comprises early elution of C1–C12 naphthenes and paraffins, mid-range aromatics, and later removal of heavier fractions.

Used Instrumentation


  • PIONA+ multi-column GC module
  • Agilent/Varian 450-GC gas chromatograph
  • Thermal trapping manifolds
  • Galaxie software with PIONA+ plugin

Main results and discussion


In the calibration standard (CP299107), mass percentage distribution showed 24.91% paraffins, 21.40% iso-paraffins, 20.82% naphthenes and 11.24% aromatics, with heavy fraction (>200 °C) at 14.83%. Volume percentages were similar. A reformer feed sample yielded 41.23% naphthenes, 27.13% iso-paraffins, 22.12% paraffins and 8.97% aromatics, with minimal high-boiling compounds. These profiles underline the system’s resolution and quantitative precision.

Benefits and practical applications


  • Rapid, automated quantitation of PINA groups for quality control.
  • Compliance with industry methods for fuel specification.
  • Adaptable to various fuel types and method protocols.

Future trends and potential uses


Integration with mass spectrometric detection and enhanced data analytics may advance speciation of trace hydrocarbons. Miniaturized multidimensional systems and AI-driven chromatogram interpretation promise faster throughput and deeper insight.

Conclusion


The multidimensional PIONA+ GC method effectively separates and quantifies hydrocarbon classes in spark ignition fuels, providing robust, high-resolution data critical for fuel evaluation and regulatory compliance.

References


Agilent Technologies (2008) Application Note SI-01318: PINA in Hydrocarbon Streams.

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