Sooting Tendencies of Co-optima Test Gasolines and Their Surrogates

Seon Ah Kim, Peter St. John, Akshay Kumar Jain, Charles McEnally, Yuan Xuan, Dhrubajyoti Das, Thomas Kwan, Lance Tan, Junqing Zhu, Lisa Pfefferle

Research output: Contribution to journalArticlepeer-review

38 Scopus Citations


This study characterized the sooting tendencies of a set of gasolines and their surrogates using both experimental and computational methods. Sooting tendency was defined in terms of the soot yield when 1000 ppm of the test fuel is doped into the fuel of a methane/air flame, and it provides a measure of the intrinsic chemical tendency of the fuels to form soot in a generic combustion environment. The test fuels were real gasolines containing enhanced concentrations of alkanes, aromatics, cycloalkanes, olefins, and ethanol. These compositional differences caused the experimentally measured sooting tendencies of the fuels to vary by 240%. The surrogates were 3 mixtures defined by Szybist et al. (2017) and 3 alternative formulations modified for greater experimental convenience. The sooting tendencies measured for the surrogate mixtures agreed with the real fuels to within 15%, and varied with composition in the same order. The sooting tendencies of the surrogates could be predicted to within experimental error with an empirical quantitative structure-property relationship and a linear mixing model. The experimental flames were computationally simulated with a 743-species mechanism, and sooting tendencies derived from the results agreed with the measured values to within 11%. Overall, these results show that the sooting behavior of gasoline can vary considerably within the range of acceptable compositions, and that these variations can be accurately predicted with empirical models and computational simulations.
Original languageAmerican English
Pages (from-to)961-968
Number of pages8
JournalProceedings of the Combustion Institute
Issue number1
StatePublished - 2019

NREL Publication Number

  • NREL/JA-5100-71630


  • environmental impact
  • IC engines
  • particulates


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