Micro-Scale On-Road Vehicle-Specific Emissions Measurement and Modeling

Abstract

The main objectives of this work are to quantify and compare intra- and inter-vehicle variability in fuel use and emissions and to develop capabilities of measuring and estimating fuel use and emissions at the micro-scale. This dissertation developed methodology to achieve the objectives, including experimental design for on-road data collection using a portable emission measurement system (PEMS), road grade estimation, evaluation of measurement accuracy, quantification of intra- and inter-vehicle variability in emissions, and micro-scale emissions modeling. A Light Detection and Ranging (LIDAR)-based method for road grade estimation was shown to be accurate and reliable. Measurement accuracy on a trip or mode basis was shown to be adequate. Routes, drivers, road grade, and time of day are significant sources of intra-vehicle variability. Significant inter-vehicle variability in emissions was observed, although only a small number of vehicles were tested and all belong to the same vehicle class. Thus, for accurate emission inventory development, both intra- and inter-vehicle variability should be taken into account. Consecutive averages were used for micro-scale emissions modeling to account for the response time of the PEMS. Choice of averaging time determines the model spatial and temporal resolution of prediction. Models for all pollutants are generally accurate, and precise in fuel use and CO2 emission estimation and moderately precise for other pollutants for various averaging times. Furthermore, models are capable of capturing the micro-scale events in emissions. Thus, the modeling schemes developed here can be used for a variety of applications including identification of the hotspots in emissions, transportation improvement programs on a corridor or intersection level, and more representative and accurate regional emission inventories development.