University of California Transportation Center

The San Pedro Bay Ports (SPBP) of Los Angeles and Long Beach in Southern California comprise one of the largest container port complexes in the world. The SPBP contribute significantly to both regional and national economies in California, and the US, respectively. However, the ongoing growth and economic benefits of the SPBP are threatened by negative externalities associated with port operations, particularly increasing congestion and air pollution. The objective of this paper is to explore a new approach to estimating vehicle emission impacts of freight corridor operations related to the port area, particularly those associated with heavy duty diesel trucks. The approach involves use of a microscopic traffic simulation model to capture detailed vehicle trajectories and congestion effects (ultimately including the effects of Intelligent Transportation System strategies), emissions modeling, and modeling the spatial dispersion of pollutants in the corridor, to facilitate estimation of the health and environmental justice impacts of freight corridor operations. In this paper we focus on operation of the I-710 freeway in the Alameda Corridor, leading from the SPBP area for about 20 miles toward Los Angeles. In a parallel effort we are also studying rail operations in the same corridor. In the future both the rail and highway elements will be combined to form an integrated, overall assessment of air quality impacts in the corridor. In this paper, seven scenarios were evaluated in addition to the 2005 Base Scenario: replacement of the current fleet of port heavy duty diesel trucks with zero emission trucks (25%, 50%, and 100% of port trucks), elimination of port heavy duty diesel truck trips (25%, 50%, and 100% reductions) that would correspond to shifting more containers to other modes such as rail, and implementation of a truck restricted-lane on I-710 preventing trucks from using the left most lanes. The results show that fleet replacement with cleaner trucks yields the most emission reductions both quantitatively and spatially.