A Forward-Looking Stochastic Fleet Model for Analysing the Impact of Uncertainty on Light-Duty Vehicles Fuel Use and Emissions

Transport policy research seeks to predict and substantially reduce the future transport-related greenhouse gasemissions and fuel consumption to prevent negative climate change impacts and protect the environment.However, making such predictions is made difficult due to the uncertainties associated with the anticipateddevelopments of the technology and fuel situation in road transportation, which determine the total fuel useand emissions of the future light-duty vehicle fleet. These include uncertainties in the performance of futurevehicles, fuels’ emissions, availability of alternative fuels, demand, as well as market deployment of newtechnologies and fuels. This paper develops a methodology that quantifies the impact of uncertainty on theU.S. transport-related fuel use and emissions by introducing a probabilistic fleet model that takes detailedtechnological and demand inputs. This model stochastically calculates the probability density functions forfuel use and emissions over time by propagating and calculating the effect of input uncertainties throughoutfleet calculations. The fleet turn over is tracked based on the calendar year, vehicle model year, the marketpenetration rate of advanced technologies and fuels, and the scrappage rate of vehicles on the road. Full lifecycleemissions of fuels are projected and tracked in this model. Three carefully chosen illustrative examplesare assessed using the developed methodology in this paper. The results show the probability distribution ofthe total light-duty vehicle fleet fuel use and emissions out to year 2050, including the mean, mode, standarddeviation, spread, and confidence interval of these outputs in the near to long term...