ANALYSING ATMOSPHERIC IMPACTS OF REGIONAL TRUCK EMISSIONS USING AN INTEGRATED MODELLING APPROACH

Abstract

Transportation technology is providing new ways to mitigate multipollutant emissions co-emitted from on-road sources. Zero-emission vehicles (ZEV) are more common in passenger vehicles and other light-duty vehicles; however, they remain a relatively new technology for most medium-duty and heavy-duty vehicles. As more trucks are adopting zero-emission technology, we need to evaluate whether these mitigation strategies are sufficient in meeting regional reduction goals. Previous studies have evaluated the multipollutant impacts of trucks and other vehicles; however, these methods estimate vehicle activity by empirical data such as surveys, which, unlike process-based models, are not amenable to evaluating significant future technology adoption. This research presents a new method to quantify the atmospheric impacts and evaluate mitigation strategies of zero-emission technology in trucks at a regional scale using an integrated assessment model (IAM). This model establishes a connection between EMME, a travel demand model, MOVES, a mobile emissions simulator, and EASIUR, a regression model that produces marginal damage estimates. The IAM estimates a baseline and compares the total damages of alternative scenarios, using different ZEV adoption rates applied to trucks. The annual, ground-level emissions were estimated for the following pollutants using the developed IAM: primary PM2.5, NOX, SO2, NH3, CO2, CH4, and N2O. The results from the application of the IAM to the baseline scenario show that the total annual damages resulting from atmospheric emissions from trucks for the Province of Ontario in 2012 is approximately $1.82 Billion (2005 USD). Most of these damages are in Southern Ontario, with Toronto, Peel and York being the top three contributors. Adoption of ZEV decreases these damages linearly. Ontario has an adoption rate goal for ZEV of 5$89 Million (2005 USD) in benefits annually from trucks alone. This result varies by up to ±25% according to the sensitivity analysis related to the travel and emissions models. Future work should focus on the relationship between emissions to damages, which likely remain the largest source of uncertainty