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Mainka, Anna; Nocoń Witold, 2026, "Personal PM2.5 exposure during real-world cycling trips: data for benefit–risk modelling", https://doi.org/10.18150/VDIMJT, RepOD, V1
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This dataset contains trip-level data supporting a study on personal PM₂.₅ exposure during real-world cycling and the modelled balance between physical-activity benefits and air-pollution-related health risks. The dataset comprises 162 cycling trips, including 78 trips conducted during the heating season and 84 during the non-heating season. It contains personal PM₂.₅ concentrations measured during cycling, corresponding background PM₂.₅ concentrations, trip duration, anonymised participant identifiers, season classification, and variables used in the exposure and health benefit–risk calculations. Where applicable, the dataset also includes derived variables used to estimate inhaled PM₂.₅ dose, equivalent long-term exposure, physical-activity-related relative risk, PM₂.₅-related relative risk, and the combined net relative risk. The data are provided to support transparency, reproducibility, and independent verification of the analyses presented in the associated manuscript submitted to Toxics. No directly identifying personal information is included in the deposited dataset.
Personal exposure was assessed using low-cost sensors compared to stationary measurements. These findings highlight the influence of transport modes and seasonal conditions on real-time exposure to air pollution. The results highlight the necessity for targeted interventions—such as infrastructure improvements and regulatory measures—to reduce commuters’ exposure to traffic-related pollutants and enhance urban air quality.
personal exposure, PM2.5, cycling, air pollution, active transport, inhaled dose, physical activity, health risk assessment
Mainka, Anna, Witold Nocoń, Aleksandra Malinowska, et al. 2025. “Exposure to NO2 and PM2.5 While Commuting: Utility of Low-Cost Sensor.” Applied Sciences-Basel 15 (11): 5965. https://doi.org/10.3390/app15115965. https://doi.org/10.3390/app15115965 doi: 10.3390/app15115965
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