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With increasing evidence for climate change in response to greenhouse gasses (GHG) emitted by human activities, pressure is growing to reduce fuel consumption via increased vehicle efficiency and to replace fossil fuels with renewable fuels. While real-world experience with bio-ethanol and a growing body of research on many other renewable fuel pathways provide some guidance as to the cost of renewable transportation fuel, there has been little work comparing that cost to alternative means for achieving equivalent GHG reductions. In earlier work, we developed an optimization model that allowed the transportation and electricity generation sectors to work separately or jointly to achieve GHG reduction targets, and showed that cooperation can significantly reduce the society cost of GHG reductions.

Ford's portfolio approach to sustainable mobility offers a large range of fuel-efficient engines and alternative-fuel vehicles - including EcoBoost®, hybrid, plug-in hybrid, flexible fuel, battery-electric, B20 biodiesel and compressed natural gas or liquefied petroleum gas (CNG/LPG) vehicles. The Ford Fleet Purchase Planner has been developed to assist fleet customers in comparing these alternatives and understanding which vehicles offer the optimal mix to achieve CO₂ emission reductions while balancing corporate financial goals. Vehicle fleets for large corporations can have thousands of vehicles that are replaced on a timescale of months to years. We present the three main components of the Fleet Purchase Planner (patent pending) that provide fleet customers the lowest cost solution to achieving their sustainability goals: the Vehicle Emissions & Fuel Cost Calculator, the Fleet CO₂ Emissions Footprint Status Calculator, and the Purchase Recommender.

In recent years, electrification has emerged as an important means to reduce the carbon footprint of personal transportation. A key question for both policy makers and vehicle manufacturers is how quickly electric vehicles (EV) will be adopted by consumers. EV adoption will be impacted by external factors such as the price differential between gasoline and electricity, large incremental vehicle costs, and strong government policies that are far less significant for other advanced vehicle technologies such as hybrid electric vehicles (HEV) or the Ford Eco-Boost engine technology. The ability to reflect these additional externalities in adoption models will improve the reliability of EV market penetration forecasts and the quality of policy analysis. The Bass diffusion model is well established in studies of the adoption of new technologies, but it is not able to reflect those external factors related to EVs in its usual form.