This paper introduces an innovative modeling framework designed to assess energy efficiency in freight transportation, a sector that contributes a significant share of worldwide greenhouse gas and black carbon emissions. This study applies a set of tools to assess well-to-wheel energy use and environmental impacts for three freight transport scenarios: conventional diesel trucks, grid-mix-powered (general energy grids) battery electric vehicles (BEVs), and rooftop solar-powered BEVs. The case study examines energy use and emissions for both upstream activities (well-to-pump) and on-road activities (pump-to-wheel). The modeling combines trip prediction and trajectory simulation from the Georgia Tech RoadwaySim model, with on-road energy use and emission rates from the EPA's MOVES model and Georgia Tech's Fuel and Emissions Calculator, and upstream energy and emission assessment for fuel/power delivered to the vehicle using the Argonne National Lab's GREET® model. The case study applies the tools to live clam logistics in the Atlanta Metro area, and the results highlight the efficiency advantages of solar-powered BEVs over diesel trucks in seafood transportation, especially when the battery electric trucks are powered by rooftop solar where potential energy use reductions of up to 52 % and significant emission reductions can be achieved. The upstream energy generation results from the GREET® model further emphasized the significant role of energy production in overall energy consumption. While the transition to BEVs promises substantial energy and emission reductions, this paper acknowledges the practical challenges involved in this shift and calls for detailed case study analyses across logistics sectors to assess the best vehicle powertrain fits for individual transportation sectors.