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Statistical Approach To The Development Of A Microscale Model For Estimating Exhaust Emissions Of Light Duty Gasoline Vehicles

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Statistical Approach To The Development Of A Microscale Model For Estimating Exhaust Emissions Of Light Duty Gasoline Vehicles

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dc.contributor.author Afotey, Benjamin Nmai en_US
dc.date.accessioned 2009-09-16T18:20:20Z
dc.date.available 2009-09-16T18:20:20Z
dc.date.issued 2009-09-16T18:20:20Z
dc.date.submitted January 2008 en_US
dc.identifier.other DISS-10111 en_US
dc.identifier.uri http://hdl.handle.net/10106/1849
dc.description.abstract Today, air pollution is taking a growing toll on human health, the environment and the economy, despite decades of efforts to combat it. Although it was once a primary urban phenomenon in industrialized countries, today air pollution has spread worldwide. Mobile, industrial and natural sources constitute the major sources of air pollution. Around the world, major cities in industrialized countries have in recent times been battling air pollution from mobile sources. Beijing, New Delhi, Dallas/ Fort Worth and Los Angeles are no exceptions.Pronounced interest has focused on mobile source (vehicle exhaust) emissions in recent decades. A rapid increase in the number of vehicles in use and a corresponding increase in vehicle miles traveled (VMT), especially in urban areas, have made vehicle emissions suspected culprits for some major health and environmental problems observed among urban populations. At the state and regional levels, transportation and air quality engineers are developing various transportation models to help estimate vehicle exhaust emission.This research involves development of a statistical model for vehicle tailpipe emissions estimation. Second-by-second data collection was carried out using an On Board emissions measurement System (OBS-1300 system) which was installed in the 2007 Dodge Charger Car acquired by the Civil Engineering Department of the University of Texas at Arlington (UTA).The test procedure involved 40 hours of second-by-second emissions data collection. Two roadway types, arterial and highway, were considered and data was collected for two different time periods, off peak and peak.The model built contains predictor variables such as velocity and acceleration, and thus is able to address driving dynamics and with excellent potential of estimating second-by-second vehicle emissions. en_US
dc.description.sponsorship Sattler, Melanie en_US
dc.language.iso EN en_US
dc.publisher Civil & Environmental Engineering en_US
dc.title Statistical Approach To The Development Of A Microscale Model For Estimating Exhaust Emissions Of Light Duty Gasoline Vehicles en_US
dc.type Ph.D. en_US
dc.contributor.committeeChair Sattler, Melanie en_US
dc.degree.department Civil & Environmental Engineering en_US
dc.degree.discipline Civil & Environmental Engineering en_US
dc.degree.grantor University of Texas at Arlington en_US
dc.degree.level doctoral en_US
dc.degree.name Ph.D. en_US
dc.identifier.externalLink http://www.uta.edu/ra/real/editprofile.php?onlyview=1&pid=972
dc.identifier.externalLinkDescription Link to Research Profiles

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