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Short Abstract

Citizen scientists collected data on urban stressors while cycling. We created a robust, policy-ready evidence base revealing where exposures are highest. While these results inform public debate on green corridors and low-traffic streets, formal policy uptake remains limited despite clear insights.

Abstract

Citizen science can generate highly relevant environmental evidence, yet its translation into policy remains uneven. In the Urban Cycling Lab Ljubljana, part of the Horizon Europe URBANOME project, 206 daily cyclists monitored particulate matter (PM₂.₅) and noise (Leq) with personal sensors while contributing socio-demographic and health-perception data. We developed a transparent, reproducible analysis stream to harmonise various inputs (minute-level sensors, GPS routes, questionnaires), ensure data quality, and produce (policy-ready) exposure indicators.

Cycling routes were classified into high-traffic (HIT) and low-traffic (LIT) corridors. Analyses consistently showed higher PM₂.₅ and noise exposures on HIT routes compared to LIT corridors across participant groups. These findings were distilled into accessible, actionable visuals and summary tables, designed to support evidence-based planning of greener, quieter cycling infrastructure.

The project succeeded in raising public and professional awareness of air quality and noise in urban cycling and sparked discussions around low-traffic streets and green corridors. However, formal uptake by city policymakers has so far been limited. This gap appears linked less to data quality or clarity than to institutional inertia and the absence of mechanisms to integrate citizen-generated evidence into planning. Early engagement with municipal stakeholders created awareness but did not translate into sustained commitment or action.

This case demonstrates both the potential and the persistent barriers in transforming citizen science–driven exposure data into policy change, highlighting the need for stronger institutional pathways for adoption.