Urban Transportation Greenhouse Gas Emissions and Their Link with Urban Form,Transit Accessibility,and Emerging Green Technologies

A greenhouse gas (GHG) emissions inventory is estimated at the household level from disaggregated trip data considering all emitting modes. Trip-level GHG emissions are estimated by combining data sources (e.g., origin–destination surveys, vehicle fleet characteristics, transit rider ship data) and by using modeling tools (traffic assignment and GHG models) developed for Montreal, Quebec, Canada. A simultaneous equation model framework is implemented to investigate links between urban form, transit supply, sociodemographics, and travel GHGs, taking into account the issue of residential self-selection. The potential impacts of land use and transit supply strategies with emerging green technology scenarios are then compared with each other. Findings are consistent with the literature; built environment attributes are statistically significant (10% increase in density, transit accessibility, and land use mix results in 3.5%, 5.8%, and 2.5% GHG reductions, respectively), and the number of workers and retirees make important contributions to GHG emissions at the household level (102% increase from adding one worker and 51% decrease from adding one retiree). Also, if the current transit fleet were replaced with electric trains and hybrid buses, transit GHGs would decrease by 32%. If current trends persist in the private motor vehicle fleet, continued improvements in car fuel economy are estimated to reduce car GHGs 7% by 2020. The two most effective strategies for reducing regional and household GHGs appear to be to improve the fuel efficiency of the private motor vehicle fleet and to increase transit accessibility.