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

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.