Research Projects

Project at a Glance

Title: Development of exhaust speciation profiles for commercial jet engines.

Principal Investigator / Author(s): Whitefield, Philip D.

Contractor: University of Missouri

Contract Number: 04-344


Research Program Area: Emissions Monitoring & Control

Topic Areas: Mobile Sources & Fuels


Abstract:

This study reports the emissions of CO, CO2, NOx, Particulate Matter (PM) mass, speciated PM and speciated hydrocarbons at six thrust settings: 4%, 7%, 30%, 40%, 65% and 85%, measured from both engines on four parked 737 aircraft at the Oakland International Airport. The engine types were selected to represent both old and new technologies. Tests were performed to determine whether or not all engines studied were operating in a representative manner. Of the 8 engines studied, only one was found to have performance deterioration and it was excluded from the engine average results. Size distributions from 5nm to 1Ķm were measured for all test points and associated aerosol shape parameters, and mass and number-based emission indices were evaluated along with real-time chemical speciation for some hydrocarbons. This work was conducted by the University of Missouri-Rolla and Aerodyne Research Inc. The bulk of the Total Organic Gases (TOG) speciation was pursued using off-line filter sampling approaches conducted by the University of California - Riverside. After the field campaign was completed it became apparent that a leak had occurred in the sampling system for the sub-set of filters designated for light hydrocarbons (C1-C12) and carbonyls, and the Summa canister data was lost for unknown reasons. The emission indices for these species are not quantifiable. Despite this loss of data this study has resulted in the first quantitative values obtained using state of the art techniques of engine emission factors for PM and some TOG for the most common classes of gas turbine engines currently operating in the US domestic fleet. The data from this test will serve to improve air quality prediction models used in Environmental Impact Statements and Reports for airport expansion projects, and for developing effective State Implementation Plans.


 

For questions regarding research reports, contact: Heather Choi at (916) 322-3893

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