Project number: MT-11-03

Funding source: Caltrans

Total cost: $89,312

Performance period: 08/2010 to 07/2011

Estimating greenhouse gases (GHGs) and other emissions (especially diesel particulates) is an increasingly important basis for regional policy analysis. According to the EPA (2010b), the transportation sector contributed 27.2 percent of total GHG emissions in 2008, and 50 percent of these were from truck operations. This research focuses on estimating GHGs and other emissions (e.g. PM) from freight movements on roads in California (a prototypical example because of its leadership in air quality policy making) as well as the concurrent effects of various regulation scenarios. In this way, we address questions of sustainability and environmental policy as well as efficiency in freight transportation. We build on important data sources such as, ZIP code-level IMPLAN input-output data and the Freight Analysis Framework (FAF) which provides information on interregional freight movements throughout the U.S. for 2002-2035. We use these data to estimate interregional trade flows between ZIP code areas by applying a gravity model. We translate the estimated interregional trade flows into vehicle miles traveled (VMT) by applying a User Equilibrium model. The estimated VMT in turn are used as inputs to the emissions model to estimate GHGs and other emissions. We demonstrate that interregional freight flow data can be an important data source for emission models. The results are useful not only for estimating GHGs and other emissions based on estimated freight flows, but also for evaluating environmental impacts of policy alternatives. The results are useful not only for estimating GHGs and other emissions based on estimated freight flows, but also for evaluating area specific environmental impacts of policy alternatives. The analysis shows that emissions impacts vary by study area as well as by policy. A policy alternative that brings a significant impact in a specific area may show a trivial impact in a broader region or vice versa. Also an emissions reduction in one area may be because of emissions increases in another area. Therefore it is important to simulate possible emissions impacts by applying a spatially disaggregated model to help decision makers weigh alternatives.