Integrating Engine Start, Soak, Evaporative, and Truck Hoteling Emissions in MOVES-Matrix

摘要

The MOVES (MOtor Vehicle Emissions Simulator) model was developed by the US Environmental Protection Agency (EPA) to estimate air pollution emissions from mobile sources and should be used to generate emission data for regional conformity analysis in all states except California1. However, the complicated MOVES interface makes it difficult to assess emissions from large scale transportation networks that are dynamic in nature. For complex transportation systems analyses, rather than applying the MOVES model directly, researchers can now use MOVES-Matrix instead; where the matrix is a huge multidimensional array of MOVES outputs generated by running MOVES through every combination of input variables2. The MOVES-Matrix system allows energy emissions analyses to be conducted very quickly and dynamically. In previous research, MOVES-Matrix has been coupled with a variety of traffic analysis and air quality assessment tools, including travel demand models, Vissim traffic simulation, AERMOD pollutant dispersion models, and monitored instrumented vehicle data3'4'5'6. Until recently, MOVES-Matrix has been used to only analyze running exhaust emissions. Air quality analysis required by USEPA also includes the engine start exhaust, hoteling for long-haul combination trucks, evaporative emissions for hydrocarbons (HCs), and brake wear/tire wear for particulate matter (PM) from on-network and off-network sources7. In the latest version, MOVES-Matrix has been expanded to incorporate additional emission rates to generate the complete air pollutant speciation profiles for all pollutant selected. In this study, MOVES-Matrix has been used to analyze engine start, truck hoteling, evaporative and brake/tire wear and running exhaust. This paper first introduces the methodology of developing MOVES-Matrix for each emission process (engine start, extended idling, etc.), and the travel activity for corresponding process is identified in MOVES algorithms. Second, the emission speciation profiles are generated by matching the travel activity with applicable emission rates for each pollutant process. Finally, a case study is conducted for the metropolitan Atlanta, GA area to verify the feasibility of applying MOVES-Matrix and to ensure that the approach obtains the exact same results as applying MOVES directly. The travel activity inputs mainly come from regional travel data generated by the Atlanta Regional Commission's (ARC's) Travel Demand Model8. The emission results from MOVES-Matrix were compared to MOVES output to verify the approach.