Concerns over the potential negative health effects from exposure to air pollution have led to interest in assessing personal exposure and finding ways to reduce it. As journey-time exposure accounts for a disproportionately high amount of an individual’s total exposure, this article assesses the potential to apply least-cost techniques within a GIS in order to identify paths of lower journey-time exposure. The methodology adopted uses pollution surfaces for PM10 and CO generated by the dispersion model ADMS, with an analysis mask derived from OS MasterMap to create a least-cost surface. Actual routes taken by a cohort of 11–13 year old children on their journeys to school are used to compare observed journey time exposure with the exposure along alternative routes generated using the least-cost path function. While the least-cost approach proved to be successful in defining low exposure routes the ability to scale up this approach is constrained by the amount of editing required to successfully create an analysis mask from OS MasterMap data. Such alternative routes have the potential to assist in promoting safer environmental choices, however, their likelihood of adoption is dependant on a number of social and environmental influences which affect an individual’s route choice.