A methodological framework for urban noise exposure assessment exploiting citizen itineraries and environmental noise maps

• Traditional noise exposure assessments focus on residences and ignore daily mobility. • A scalable methodology integrates GPS tracks with strategic noise maps for individual exposure estimation. • Madrid case study shows personal mobility can significantly increase daily noise exposure. • This approach enables users to make informed route choices based on acoustic comfort. • The method lays groundwork for future epidemiological studies incorporating real-life movement. Environmental noise is a persistent and growing public health concern, particularly in densely populated urban areas. Conventional assessment tools, such as noise monitoring stations and strategic noise maps, typically estimate exposure based on acoustic energy distribution and noise levels evaluated on residential building facades. These approaches fail to account for the spatiotemporal dynamics associated with individual mobility throughout the city. This study introduces and validates a novel methodology for estimating personal noise exposure along urban outdoor routes. By integrating individual trajectories with high-resolution noise maps and temporal noise patterns, the approach captures exposure variability across different times of day. We applied the methodology to real-world routes in Madrid, Spain, encompassing diverse pedestrian activities, such as running, walking, and sightseeing. We used publicly available environmental noise data for this application. Validation with short pedestrian routes of approximately five minutes demonstrated close agreement with direct measurements. Eighty-three percent of the runs showed deviations below 4 dB, most of which were within ± 2.5 dB. This supports the robustness of the method as a practical estimator of personal noise exposure in urban environments. In our Madrid case study, level differences between alternative routes typically ranged from 2 to 3 dBA, occasionally reaching up to 5 dBA. This highlights the influence of route choice on individual exposure. Due to its scalability, this methodology could be incorporated into digital navigation platforms, such as Google Maps, to provide users with information on noise exposure along different routes. This would enable more informed and noise-conscious mobility decisions.