Potential of e-bikes to replace passenger car trips and reduce greenhouse gas emissions

In Sweden, the transport sector accounts for 32% of greenhouse gas emissions, with passenger cars contributing to 62% of these. In this context, electric bikes, commonly known as e-bikes, have emerged as a promising solution for reducing carbon emissions in the transport sector. This paper explores the potential of e-bikes in substituting passenger car trips and reducing transportation-related emissions. To achieve this objective, we use a synthetic population in the Västra Götaland (VG) region, Sweden, with daily activity schedules and simulate an average weekday of travelling with e-bikes instead of their private cars. For assessing the potential for e-bike substitution, the current literature often relies on trip-level analysis, which does not adequately consider people’s daily travel-activity plans, resulting in an unrealistic estimation of replaceable trips and their carbon emissions reduction. Combining an e-bike speed model by agents’ characteristics and an open-source routing engine, our simulation identifies potential car trips that can be replaced with e-bikes, considering all activities and the travel between them for an average weekday. The simulation results suggest that e-bikes could replace 57.6% of car trips. Building on this, we explore the potential reduction in greenhouse gas emissions from car trips taken by residents in the study area. If the top 70% of feasible car users, ranked by shortest to longest daily travel distances, switch to e-bikes, emissions could be reduced by 10.1% compared to 2018 levels. If all feasible car users adopt e-bikes, a reduction of up to 22.8% in emissions could be achieved, representing the upper limit presented by our study. The findings also reveal that males under 40 years old provide the highest e-bike substitution rates in their daily activity schedules, and in areas with a high population density, replaceable car trips are more common than in rural areas. This research provides valuable insights into e-bike substitution and its impact on emission reduction. It contributes to the existing literature through its modelling approach that realistically considers individuals’ socio-demographic characteristics and daily activity schedules when assessing the substitution potential.