Electric vehicles and traffic related pollution reduction: a simulation model for Hamilton, Ontario, Canada

This paper analyzes the potential contribution of electric vehicles in greenhouse gas (GHG) emissions reduction over the next decade following a simulation procedure.  Emissions were assessed through a stepwise methodological approach at the transportation link level in the Hamilton Census Metropolitan Area (CMA). Firstly, different EV market penetration scenarios were introduced and compared to the base case scenario. Following these, the spatial distribution patterns of EVs were predicted using vehicle registration data for the Hamilton CMA as well as socioeconomic data obtained from census records. Properly modified matrices were used as input into our traffic simulation model in order to assign traffic on the network and estimate volumes for each of the links. To this end MOBILE 6.2C[1] was customized so as to compute the emission factors. The hourly emissions of each link were mapped in a GIS environment. We conclude that different utilization patterns result to varying spatial distributions of traffic related emissions in the links and even a modest adoption of EV technology may lead to their significant reduction.