A Method of Assessing and Reducing the Impact of Heavy Gasoline Fractions on Particulate Matter Emissions from Light-Duty Vehicles

Abstract

The hydrocarbons constituting the heavy tail of gasoline are key contributors to particulate matter (PM) emissions from spark-ignition (SI) engines. They are predominantly aromatic and, to a signifi-cant degree, bicyclic aromatic. For example, above a boiling point of 400 degrees F, the content of bicyclic compounds in the United States (US) summer regular-grade E10 gasoline exceeds 50%v. Various gasoline parameters, such as the PM Index, Particulate Evaluation Index (PEI), Particulate and Soot Correlation Equation (PASCE), or Threshold Sooting Index (TSI), have been proposed as predictors of PM emissions from SI engines. In particular, the PM Index, whose value is dominated by the content of heavy aromatics and which, so far, has yielded the most predictive PM emissions models, appears to be the best metric to achieve this objective. However, the calculation of its value for any gasoline requires knowledge of the compositional profile of that fuel, which, in turn, calls for a detailed hydrocarbon analysis (DHA) of the fuel. Unfortunately, the DHA is a sophisticated, time-consuming, and costly gas chromatographic (GC) method. Therefore, alternative approaches are being explored.A novel method of assessing and reducing the impact of heavy gasoline fractions on PM emis-sions from SI engines is being proposed in this article. It is based on the GC simulated distillation (SimDis) method which, unlike the DHA, is fast, simple, and inexpensive. SimDis also has the important ability to directly link existing gasoline DHA databases to PM Index-based emissions models to assess PM emission impacts.