Network-Based Simulation of Air Pollution Emissions Associated with Truck Operations

Abstract

Estimating greenhouse gases (GHGs) and other emissions (especially diesel particulates) is an increasingly important basis for regional policy analysis. According to the EPA (2010a), the transportation sector contributed 27.2% of total GHG emissions in 2008, and 50% 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 as well as the concurrent effects of various mitigation scenarios. The study demonstrates that interregional freight flow data, along with FAF data can be important data sources for emission models. 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 has a significant impact in a specific area may have a trivial impact in a broader region. 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. The study can also be applied for analyzing environmental justice when the emission results are disaggregated into small areas.