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[NTC2016-SU-R-10] A Model System for Greenhouse Gas Emissions Estimation and Green Policy Evaluation



Description: 

Energy consumption and pollutant emissions from road transportation have increased significantly in recent decades. In the United States, more than 27% of total Greenhouse Gas Emissions (GHGEs) are from the transportation sector. Within the sector, light-duty vehicles are the largest pollutant sources, accounting for 61% of the total GHGEs [EPA, 2013]. Although mobile sources contribute a large percentage of GHGEs, technology is not yet available to measure and tax emissions for each vehicle [Feng et al., 2005]. Therefore, it is necessary to develop and apply effective and quantitative methodologies to support public authority decision making [Liu et al., 2014] and to analyze the impacts of taxation policies on the reduction of GHGEs.

The state-of-the-art in calculating GHGEs from vehicle usage employs either the standard values of conversion that consider lifecycle emissions from the Environmental Protection Agency (EPA) or the emission rates per miles from the California Air Resources Board (CARB) [Feng et al., 2005, Fullerton, 2005, Fullerton and Gan, 2005, Musti and Kockelman, 2011]. Another method to estimate vehicle GHGEs is to combine demand models and emission simulators such as the EPA’s MOBILE6 and MOVES, and the EMFAC model developed in California for emissions forecasting. Observing that GHGEs from light-duty vehicle are closely linked to households’ car holding and driving behaviors, Vyas et al. found that the combination of the number of vehicles owned by a household, vehicle type, and the usage of vehicles is an important determinant of households’ vehicle GHGEs and fuel consumption [Vyas et al., 2012]. They were the first to integrate a household vehicle ownership model with a large activity-based micro-simulation system - SimAGENT which is able to dynamically estimate vehicle GHGEs at a household-level.

Following this line of research, in this project we propose to combine an integrated discrete- continuous car ownership model and MOVES2014 to estimate households’ vehicle GHGEs. The proposed framework can be used to evaluate the impact of different vehicle-related policies on emission reductions.