The effect of truck loading factor on a major trucking route in Québec and on GHG emissions

ABSTRACT

In this paper, we hypothesized that it is possible to reduce trucking
greenhouse gas emissions in a relatively short time horizon by improving
efficiency. As a matter of fact, improving truck efficiency by increasing their loading
factor, in other words, maximizing the time when trucks are fully loaded and
minimizing when they run without a cargo is a low hanging fruit that could be
enforced by local incentives or regulations for long-haul cargo. This study analyzes
the effect of truck loading factor on a major trucking route in Québec (highway 20)
and it estimates potential GHG emission economy with a linear regression for
different average load-factor scenarios. The regression analysis shows that
removing 20% of the empty trucks travelling in the province of Quebec could lead
to an annual reduction of 1.2 million tons of CO2 and social savings of nearly 300
million $. Results are based on a Monte Carlo analysis made with a tool called the
MapEUR which uses different databases on trucks registrations, operation, road
characteristics and weather conditions to estimate the fuel consumption of all the
trucks travelling of a specific road segment and a given period. The scenario
comparison provides better understanding of the potential benefits of increasing
load factors and guide the amount of efforts that should be given from fleet
operators and policy makers toward such solutions.