This paper examines temporal variation in the demand for cycling to understand how environmental
conditions may promote or hinder active travel. The role of environmental conditions is considered in
terms of the prevailing weather as well as concentration levels of local air pollutants. Using data
derived from the London Bicycle Sharing Scheme, a set of autoregressive distributed lag models are
specified to explore these relationships. The models distinguish casual cyclists from regular cyclists to
allow the analysis to consider the demand profiles of these two market segments separately rather
than jointly. The analysis makes use of an open science approach, with the data inspected, the models
applied, and the results derived being made freely available to interested parties through an online
repository.
The results of the models indicate that the demand of casual cyclists is more strongly linked to
concurrent weather condition as compared to the demand of regular cyclists, though regular cyclists
seem to be more inclined to delay trips to avoid inclement weather. The associations between cycling
demand and air quality levels is mixed, with high concentrations of ozone linked with lower levels of
demand from regular cyclists while high concentrations of particulate matter 10 are positively related
to both regular and casual cycling demand. The findings of this paper could provide benefits to bicycle
sharing system managers such as in planning the schedule of maintenance work as well as highlighting
the need to inform cyclists about the actions they can take to reduce their exposure to local air
pollutants.
This paper was accepted for publication in the journal Journal of Transport Geography and the definitive published version is available at https://doi.org/10.1016/j.jtrangeo.2020.102854