Abstract
Air pollution, especially fine particulate matter (PM(2.5)), is a major environmental risk factor for human health in Europe. Monitoring of air quality takes place using expensive reference stations. Low-cost sensors are a promising addition to this official monitoring network as they add spatial and temporal resolution at low cost. Moreover, low-cost sensors might allow for better characterization of personal exposure to PM(2.5). In this study, we use 500 dust (PM(2.5)) sensors mounted on bicycles to estimate typical PM(2.5) levels to which cyclists are exposed in the province of Utrecht, the Netherlands, in the year 2020. We use co-located sensors at reference stations to calibrate and validate the mobile sensor data. We estimate that the average exposure to traffic related PM(2).(5,) on top of background concentrations, is approximately 2 μg/m(3). Our results suggest that cyclists close to major roads have a small, but consistently higher exposure to PM(2.5) compared to routes with less traffic. The results allow for a detailed spatial representation of PM(2.5) concentrations and show that choosing a different cycle route might lead to a lower exposure to PM(2.5). Finally, we conclude that the use of mobile, low-cost sensors is a promising method to estimate exposure to air pollution.