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.
","abstract_html":"<p>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.</p> <p>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.</p>","abstract_has_math":false,"creators":["Roesler, Erika Louise"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Open Access Thesis","degree_discipline":"Physics and Astronomy","degree_department":null,"school":null,"contributors":["Edward Nam, PhD","James Sheerin, PhD","Ernest Behringer, PhD"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006-01-01T08:00:00Z","date_published":"2006-01-01T08:00:00Z","updated_at":"2026-07-24T02:16:24Z","subjects":["Automobiles motor Eexhaust gas measurement","Waste gases Measurement","Automobiles motors exhaust gas","Kansas","Kansas City Analysis","Physics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/22","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Edward Nam, PhD","James Sheerin, PhD","Ernest Behringer, PhD"]},{"key":"dc:creator","label":"Author","values":["Roesler, Erika Louise"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Physics and Astronomy"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Automobiles motor Eexhaust gas measurement","Waste gases Measurement","Automobiles motors exhaust gas","Kansas","Kansas City Analysis","Physics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/22"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Analysis of tailpipe particulate matter emission from a sampling of Kansas City vehicles"]}]}],"canonical_facts":{"dc:contributor":["Edward Nam, PhD","James Sheerin, PhD","Ernest Behringer, PhD"],"dc:creator":["Roesler, Erika Louise"],"dc:description.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.
"],"dc:identifier":["https://commons.emich.edu/theses/22"],"dc:subject":["Automobiles motor Eexhaust gas measurement","Waste gases Measurement","Automobiles motors exhaust gas","Kansas","Kansas City Analysis","Physics"],"dc:title":["Analysis of tailpipe particulate matter emission from a sampling of Kansas City vehicles"],"thesis:degree_discipline":["Physics and Astronomy"],"thesis:degree_level":["Open Access Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T02:16:24Z"}