Benefits of Air Quality Simulation Models

As the air quality modeling needs of transportation planning professionals become more complex, the models must follow suit to provide more sophisticated and advanced capabilities. The current CALINE and CAL3QHC-series roadway models promulgated by the Environmental Protection Agency (EPA) provide static environments with time-averaged, aggregate variables that are unsuitable tor micro-scale assessments. Therefore, the successor (next generation) models should be based on a simulation approach and leverage new computing technology to provide more realistic and robust modeling environments. The TRaffic Air Quality Simulation Model (TRAQSIM) developed by Wyle Laboratories meets each of these qualities. TRAQSIM's 4-dimensional (4D) environment with virtually no temporal and spatial constraints provides the model with significant growth potential including the possibility of modeling the effects of road grade and facilitating the emissions and dispersion modeling of both particulate matter (PM) and chemically reactive pollutants. As an example of the robustness of a simulation environment, the ability to directly assess input and output uncertainties is presented in this paper. The assessment is conducted for a queue reduction example where Monte Carlo simulations are used to determine whether or not the air quality related to different scenario cases are statistically different from a baseline case. These methods and results provide additional quantitative information to help transportation land use and in planning professionals make informed decisions.