Modeling light duty vehicle emissions based on instantaneous speed and acceleration levels

This dissertation develops a framework for modeling vehicle emissions microscopically. In addition, the framework is utilized to develop the VT-Micro model using a number of data sources. Key input variables to the VT-Micro model include instantaneous vehicle speed and acceleration levels. Estimating accurate mobile source emissions is becoming more and more critical as a result of increasing environmental problems in large metropolitan urban areas. Current emission inventory models, such as MOBILE and EMPAC, are designed for developing large scale inventories, but are unable to estimate emissions from specific corridors and intersections. Alternatively, microscopic emission models are capable of assessing the impact of transportation scenarios and performing project-level analyses.; The VT Micro model was developed using data collected at the Oak Ridge National Laboratory (ORNL) that included fuel consumption and emission rate measurements (CO, HC, and NO_x) for five light-duty vehicles (LDVs) and three light-duty trucks (LDTs) as a function of the vehicle's instantaneous speed and acceleration levels. The hybrid regression models predict hot stabilized vehicle fuel consumption and emission rates for LDVs and LDTs. The model is found to be highly accurate compared to the ORNL data with coefficients of determination ranging from 0.92 to 0.99. The study compares fuel consumption and emission results from MOBILE5a, VT-Micro, and CMEM models. The dissertation presents that the proposed VT-Micro model appears to be good enough in terms of absolute light-duty hot stabilized normal vehicle tailpipe emissions. Specifically, the emission estimates were found to be within the 95 percent confidence limits of field data and within the same level of magnitude as the MOBILE5a model estimates. Furthermore, the proposed VT-Micro model was found to reflect differences in drive cycles in a fashion that was consistent with field observations. Specifically, the model accurately captures the increase in emissions for aggressive acceleration drive cycles in comparison with other drive cycles.; The dissertation also presents a framework for developing microscopic emission models. The framework develops emission models by aggregating data using vehicle and operational variables. Specifically, statistical techniques for aggregating vehicles into homogenous categories are utilized as part of the framework. In addition, the framework accounts for temporal lags between vehicle operational variables and vehicle emissions. Finally, the framework is utilized to develop the VT-Micro model version 2.0 utilizing second-by-second chassis dynamometer emission data for a total of 60 light duty vehicles and trucks. (Abstract shortened by UMI.)...