The transparent, flexible, and open-source Python library carculator_truck is introduced to perform the life cycle assessment of a series of medium- and heavy-duty trucks across different powertrain types, size classes, fuel pathways, and years in a European context. Unsurprisingly, greenhouse gas emissions per ton-km reduce as size and load factor increase. By 2040, battery and fuel cell electric trucks appear to be promising options to reduce greenhouse gas emissions per ton-km on long distance segments, even where the required range autonomy is high. This requires that various conditions are met, such as improvements at the energy storage level and a drastic reduction of the greenhouse gas intensity of the electricity used for battery charging and hydrogen production. Meanwhile, these options may be considered for urban and regional applications, where they have a competitive advantage thanks to their superior engine efficiency. Finally, these alternative options will have to compete against more mature combustion-based technologies which, despite lower drivetrain efficiencies, are expected to reduce their exhaust emissions via engine improvements, hybridization of their powertrain, as well as the use of biomass-based and synthetic fuels.
Keywords: battery; electric; freight; fuel cell; open-source; prospective; tank-to-wheel; transport.