Making intra-urban monitoring ‘a walk in the park’: A mobile monitoring approach for assessing pedestrians’ environmental conditions

• Study pilots a trolley measuring environmental conditions operated by a pedestrian • Combines environmental monitoring with fisheye photographs and thermal imagery • PET in vegetated areas (NDVI>0.285) were 11.8°C cooler than in tree-sparse areas • Non-linear, negative relationship was found between wind speed and PM 0.3 levels • PM 0.3 and PM 10 levels were higher in urban parks due to reduced wind speed by trees Heat island effects and air pollution influence urban climates and air quality, impacting pedestrians’ health, comfort, and well-being. This study develops and pilots the Trolley-based Environmental Monitoring System (TEMS), which was validated in a medium-sized city in the UK. Three monitoring campaigns took place during May and June 2024. The mobile transects covered the city’s built and natural environments, including high-density university buildings, museum precinct, medium-density dwellings, highways, and two parks. Appropriate apparatus was specified to monitor environmental variables integrated into a trolley that was easily operated by a single pedestrian. Fisheye photographs were taken to calculate the sky view factor, and the trolley position was recorded by a GPS device. Observed environmental conditions were compared, and additional mapping data were introduced to develop a geospatial model. Vegetated areas (NDVI>0.285) reduced mean air temperatures by 4.8°C and Physiological Equivalent Temperature by 11.8°C compared with tree-sparse areas. However, the PM 0.3 and PM 10 levels in the park were 1,275,675 particles/m 3 and 813 particles/m 3 higher than in medium-density dwellings with limited trees. Therefore, careful tree plantation strategies are required to avoid unintended air quality trade-offs. Some data quality issues persisted in the transect. GPS data required cleaning to ensure the route was accurately reflected, while air quality monitoring was limited by the particle meter’s sample duration, reducing both its spatial and temporal granularity. The methodology can be replicated in the future with the potential to dynamically monitor thermal comfort and air quality along intra-urban transects with different urban morphologies.