Emissions from Low- and Mid-Level Blends of Anhydrous Ethanol in Gasoline

• Main Authors: Clark, Nigel, Klein, Tammy, Higgins, Terry, McKain, David L
• Format: Report
• Language: English
• ISSN: 0148-7191; 2688-3627
• DOI: 10.4271/2019-01-0997

Typically ethanol is present in gasoline as a 10% blend by volume (E10), although E15, E85 (51 to 83%), and E0 are also available at selected stations. Numerous studies of tailpipe regulated emissions have been conducted to compare emissions from E10 and E0, and there is a growing body of literature addressing blends of E15 and higher. Isolating the effect of ethanol in a study is philosophically difficult, because the ethanol naturally displaces some hydrocarbons, because the ethanol interacts with the remaining gasoline, and because properties of mixing are often nonlinear. Some studies have used splash blending, simply mixing the ethanol with a reference gasoline to produce a blend for comparison to the reference. Others have used match blending, where the objective is to match selected properties of the blend to properties of a reference gasoline. Recent studies have examined both port injected and direct injected engines, the latter being both naturally aspirated and turbocharged, and differing test cycles have been used. In consequence, the conclusions of the studies are not uniform. This paper examines the available data and statistical analyses to determine the effects of blending approach, engine technology and test cycle on the comparative emissions. Of central interest are the parameters selected as study variables or to be held constant in match blending of fuels at different ethanol levels. Distillation matching must acknowledge the effect of ethanol on the curve, demanding correction by selective addition of hydrocarbons. Some multivariate studies have employed aromatic content and the particle mass index for additional matching With splash blending studies, the parameters vary by inherent nature of the mix, and octane number (ON) rises with ethanol content. Statistics and causes behind variability of results are explained, and the match blends employed in studies are compared with common refinery practice in producing gasoline. Results demonstrate the importance of including all multivariate study parameters for emissions prediction.