At what extent the benefits of introducing alternative light-duty vehicles offset those of increasing the buses average occupancy?

•Characterization of fuel consumption, emissions and daily distance, of road fleet by probability distribution functions.•The co-benefit of congestion level decrease due to mode-shifting from LDV to bus is explored.•A potential decrease in NOx + PM of 23% is foreseen, by 50% LDV replacement or mode-shifting (bus occupancy 40–80%).•A decrease of CO2 is foreseen as being 20%, by 50% LDV replacement or mode-shifting (bus occupancy 30–60%).•Electricity mix relaying on renewables will increase the window were the energy and CO2 benefits match to 35%.

This paper quantifies the energy and emissions benefits of introducing electric drive vehicles (pure electric, plug-in hybrid and fuel cell) on a conventional light-duty fleet (LDV) versus promoting the intensification of the public transportation use by means of mode-shifting and increased average bus occupancy. The impact is assessed in terms of energy, local pollutants, HC, CO, NOx, PM, and global emissions of CO2. The specific fleet of Portugal is used as case study. This fleet has roughly 6 million LDV (30% diesel, 70% gasoline) and 15,000 buses, with a mobility indicator of 106 thousand million passengerxkm (pkm). Probability density functions for energy consumption and emissions are derived for conventional, electric drive vehicles, and buses, avoiding considering one representative vehicle of each. Scenarios of 30–50% conventional fleet replacement is compared against scenarios of bus occupancy increase from 20% to 80%. The increased bus occupancy is made by mode-shifting from conventional LDV vehicles keeping the mobility pkm and bus supply. The co-benefit of congestion level decrease due to mode-shifting is explored. The effect of different electricity mixes is also analyzed. The methodology used allowed obtaining likelihood functions for energy consumption and emissions for each scenario and offset areas where the benefits match. The use of the methodology for other countries and time frames is discussed and China is used as an example, in 2050.