The Ebikes scenario is thus currently implemented as an extension of Go Dutch but could be implemented as an extension of other scenarios. The Ebike scaling factors were generated through analysis of the English, Dutch and Swiss National Travel Surveys, in which we estimated how much more likely it was that a given commute trip would be cycled by Ebike owners versus cyclists in general. We parameterised the Ebike scaling factors as interactions with trip distance and with hilliness, to take account of the fact that electric cycles enable longer journeys and reduce the barrier of hills. Additional scenarios could be developed (see Discussion). If deployed in other settings, the PCT will likely benefit from scenarios that relate to both the current policy context and long-term aspirations. • Ebikes. This scenario models the additional increase in cycling that would be achieved through the widespread uptake of electric cycles (‘ebikes’). This scenario is generated by taking baseline propensity to cycle, applying the Dutch scaling factors described above, and then additionally applying Ebike scaling factors. The Ebikes scenario is thus currently implemented as an extension of Go Dutch but could in future be implemented as an extension of other scenarios. The Ebike scaling factors were generated through analysis of the UK, Dutch and Swiss National Travel Surveys, in which we estimated how much more likely it was that a given commute trip would be cycled by Ebike owners versus cyclists in general. We parameterised the scaling factors as varying according to trip distance and according to hilliness, by fitting interaction terms between these two characteristics and ebike ownership (Appendix Equation 1B). We did this to take account of the fact that electric cycles enable longer journeys and reduce the barrier of hills 16