Individual exposure to air pollution depends not only upon pollution concentrations in the surrounding environment, but also on the volume of air inhaled, which is determined by an individual’s physiology and activity level. This study focuses on journey-time exposure, using network analysis in a GIS environment to identify pedestrian routes between multiple origins and destinations throughout the city of Lancaster, North West England. For each segment of a detailed footpath network, exposure was calculated accounting for PM2.5 concentrations (estimated using an atmospheric dispersion model) and respiratory minute volume (varying between individuals and with slope). For each of the routes generated the cumulative exposure to PM2.5 was estimated, allowing for easy comparison between multiple routes.
Significant variations in exposure were found between routes depending on their geography, as well as in response to variations in background concentrations and meteorology between days. Differences in physiological characteristics such as age or weight were also seen to impact journey-time exposure considerably. In addition to assessing exposure for a given route, the approach was used to identify alternative routes that minimised journey-time exposure. Exposure reduction potential varied considerably between days, with even subtle shifts in route location, such as to the opposite side of the road, showing significant benefits.
The method presented is both flexible and scalable, allowing for the interactions between physiology, activity level, pollution concentration and journey duration to be explored. In enabling physiology and activity level to be integrated into exposure calculations a more comprehensive estimate of journey-time exposure can be made, which has potential to provide more realistic inputs for epidemiological studies.