Date Approved

2006

Degree Type

Open Access Thesis

Degree Name

Master of Science (MS)

Department or School

Physics and Astronomy

Committee Member

Edward Nam, PhD

Committee Member

James Sheerin, PhD

Committee Member

Ernest Behringer, PhD

Abstract

As the United States Environmental Protection Agency (EPA) seeks to model vehicle emissions based on dynamic engine operating conditions, modal PM datasets will be investigated for their robustness and limitations under the requirements of the EPA’s model: MOVES. The Kansas City PM Characterization Study tested more than 500 light-duty gasoline cars and trucks on a dynamometer in summertime and wintertime temperatures with four different modal PM2.5 instruments.

Using data reduction techniques used to prepare other datasets for the MOVES model, the modal PM data were analyzed to determine its ability to be incorporated into MOVES. It was found through averages of vehicles that trucks emit more PM2.5 than cars, and wintertime emissions are greater than summertime emissions. The use of the data for MOVES is currently under review as separation of elemental and organic carbon fractions and correlations between age, model year, and other pollutants still need development.

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