On-board Measurement and Analysis of On-Road Vehicle Emissions
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Date
2002-11-17
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Abstract
Recent developments in on-board instrumentation enable measurement of vehicle activity and emissions under real-world conditions as opposed to laboratory tests. Variability in vehicle emissions as a result of variation in vehicle operation, roadway characteristics, or other factors can be represented and analyzed more reliably than with other measurement methods.
The primary purpose of this dissertation is to develop methodologies for on-board vehicle activity and emissions data collection and data screening. Successful application of the developed methodology resulted at data collected in two signalized corridors in Cary, North Carolina. Eight gasoline fueled light-duty vehicles and four drivers were tested, resulting in a total of 824 one-way runs representing approximately 1,000 vehicle-hours and 2,020 vehicle-miles of simultaneous second-by-second vehicle activity and emissions data. A priori modal definitions were developed based upon vehicle speed and acceleration. It was found that modal definitions yield statistically significantly different emission rates for idle, acceleration, cruise, and deceleration.
A secondary, but equally important, purpose was to utilize vehicle activity and emissions data collected to tackle real-world problems related to vehicle emissions. One of these problems is to investigate emissions hotspots along roadways. Methods were developed to identify hotspot locations and applied to two example case studies to illustrate the types of insights obtained from this analysis. Based upon statistical and graphical analysis, hotspots were attributed most typically to stop-and-go traffic conditions which result in sudden changes in speed and accelerations.
The sensitivity of different emissions factor estimation methods (i.e., distance-based, time-based, and fuel-based) was evaluated with respect to vehicle operation modes. The effect of changes in signal timing and coordination on vehicle emissions was also investigated. For the example case study it was found that coordinated signal timing improved traffic flow on Walnut Street, which lead to a reduction in vehicle emissions. For Chapel Hill Road, emissions of NO, CO, and HC were lower in the uncongested case compared to the congested case. It was found that differences in emissions were highly associated with differences in quantitative measures of traffic flow such as average speed, average control delay, and average number of stops per mile.
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modal analysis, statistical analysis, on-board data collection, vehicle emissions, air pollution, environment
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Degree
PhD
Discipline
Civil Engineering
