Transportation is a major emitter of greenhouse gas (GHG) emissions in the United States accounting for 27% of the country’s emissions, second only to the electricity sector. As a result, reducing GHG emissions are essential for mitigating some of the most damaging potential impacts associated with climate change and because of the importance and relative size of the transportation sector, it would need to contribute a significant amount of emissions reduction.
This report describes the development and use of an U.S. energy system optimization model (US-TIMES) in order to analyze the reductions in GHG emissions that can come about through policy targets. These policy targets induce technology investments and operation in order to satisfy the demand for energy services and environmental policy constraints (notably GHG emission targets).
The model development focused on two key areas within the transportation sector, light-duty vehicles and heavy-duty vehicles. In the light-duty space, we incorporated consumer choice elements into the energy system optimization framework through increasing consumer heterogeneity and adding non-monetary decision factors such as risk and fueling inconvenience. For heavy-duty vehicles, we adopt a segmentation approach and update vehicle cost and performance assumptions from our recent work. The model is used to project scenarios for low carbon futures from a reference scenario all the way to an 80% GHG reduction target.