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Short Abstract

This study documented individual- and community-level ripple effects of bike commuters participating in a citizen science intervention, where they monitored particulate matter and noise with personal sensors and compared real-time exposures across routes.

Abstract

Cycling provides health and environmental benefits, but cyclists are exposed to environmental stressors. The Urban Cycling Lab in Ljubljana applied a transdisciplinary CS approach to evaluate cyclists’ exposure to particulate matter (PM2.5) and noise, while assessing how CS can foster behaviour change and community empowerment. This study documented psychosocial impacts at the individual level (behavioral adaptations) and community level (collective awareness and empowerment).

A two-week theory-driven intervention engaged 206 bike commuters in assessing particulate matter and noise using personal sensors. Participants accessed a digital platform to compare real-time, geo-coded exposure across their commuting routes. A mixed-methods evaluation combined an online survey, mobile “ride-along” interviews, and a participatory evaluation workshop, altogether aimed at capturing shifts in route choice, environmental health literacy, and potential ripple effects of participation.

Survey data indicated moderate concern about air pollution but limited awareness of health risks and low adoption of protective behaviours. Ride-along interviews showed that exposure data enhanced sensory awareness, motivated some participants to adapt routes, and highlighted preferences for quieter, greener commutes despite longer travel times. Workshop discussions revealed community-level impacts, with participants reporting that the project gave visibility to cycling issues from a scientific perspective and provided new opportunities for dialogue with peers and decision-makers.

Exposure to environmental data can foster behaviour change, environmental health literacy, and civic engagement among cyclists. Embedding participatory evaluation into CS interventions captures these intangible social impacts and shows how robust environmental data collection can be coupled with community empowerment to advance more equitable urban mobility systems.