An approach of localizing MOVES to estimate emission factors of trucks

Abstract

Freight has become one of the major contributors to air pollution. This research proposes a method to systematically estimate truck vehicle emissions at the road segment level through localizing MOVES, a widely-used vehicle emission estimation model. We first design a protocol of converting percentage values of rotating speed and torque of engine to second-by-second vehicle speed to accommodate the differences between driving cycles adopted in local emission standards and those used in MOVES. In order to identify the best model year for estimating emissions under different local emission standards, we propose an approach of comparing emission outcomes rather than emission factors, considering the differences in unit used between MOVES and emission standards. To calculate road segment level emission factors, we weight original factors by integrating vehicle fleet information which contains the shares of vehicles under different emission standards and at different ages. We apply the approach to a major freight corridor area in Shanghai and calculate emission factors by air pollutant, average speed of road sections, and road type. Dynamic emissions of each road section per hour are calculated to reflect the spatial distribution of truck emissions. The research outcomes may help local departments, especially in developing countries, better estimate freight vehicle emissions and make policies correspondingly to control their impacts on public health.