Investigators:
Dr. Randall L. Guensler, Georgia Tech
Dr. Michael O. Rodgers, Georgia Tech
Xiaodan Xu, Ph.D. Student, Georgia Tech
Haobing Liu, Ph.D. Student, Georgia Tech
Project Overview:
Travel demand models (TDM) are developed by Metropolitan Planning Organizations (MPOs) for analyzing regional travel patterns, and are often used to prepare activity inputs for use with the U.S. Environmental Protection Agency’s (EPA) MOtor Vehicle Emission Simulator (MOVES) for regional emissions inventory development, transportation air quality conformity analysis, and microscale air quality impact assessment. Modelers are required to either prepare multiple MOVES runs for various scenarios, or develop their own MOVES pre-processors and post-processors for emission modeling. Either approach is cumbersome and time-consuming. To reduce modeling time and resource requirements, the team has developed a tool that automates the processing of TDM outputs and produces the same results as MOVES. In this study, MOVES-Matrix emissions modeling processor was linked directly with TDM to develop emissions estimates at both the link and inventory levels. MOVES-Matrix was developed by iteratively running the MOVES across all possible combinations of input variables to create a multi-dimensional emission rate lookup matrix and produce much faster outputs at runtime. The Atlanta Regional Commission (ARC) TDM was used within metropolitan Atlanta area to demonstrate the performance of the automated tool. For this purpose, inventory-level emission modeling was first conducted using MOVES, and these emission results were compared with results from the automated process. Link-level emissions were similarly analyzed. The results indicate that the tool produces emission results identical to the direct application of MOVES, while significantly reducing processing time. The tool is beneficial for use in inventory development, conformity analysis, and microscale dispersion modeling.