Street-Level Urban Air Quality Patterns: Insights from a Comprehensive Mobile Measurement Campaign in Budapest

Urban air quality exhibits significant spatial variability at street level due to the complex interactions between traffic patterns, building structures, vegetation, and local microclimate. Traditional fixed monitoring stations provide valuable long-term data but cannot capture these fine-scale variations that directly affect human exposure to pollutants. Since 2022, we have implemented an extensive bicycle-based mobile measurement campaign in Budapest, Hungary, to characterize these patterns and develop methodologies for high-resolution urban air quality assessment.

Our approach utilizes bicycle-mounted instruments to collect spatially dense data on PM_2.5 and PM₁₀ concentrations across diverse urban environments. The measurement setup includes calibrated TSI DustTrak II Aerosol Monitor (8532) instruments equipped with impactors, along with temperature and humidity sensors with appropriate shielding. GPS data provides precise location information for each measurement point. The sampling routes were carefully designed to represent various urban settings, including high-traffic corridors, residential areas, street canyons, open boulevards, and green spaces. Over 200 measurement runs have been conducted to date, creating a robust dataset for analysis. A sophisticated data processing workflow was developed, including outlier removal, noise reduction, and spatial gridding techniques.

Analysis of this comprehensive dataset has revealed distinct patterns in the spatial distribution of particulate matter across the urban landscape. We identified characteristic "local air quality zones" associated with specific urban features and configurations. The dataset allows for the investigation of both spatial patterns and temporal variations in urban air quality, providing insights not available from fixed-site monitoring. The PM_2.5/PM₁₀ ratio variations across urban fabric have offered additional insights into the likely sources and characteristics of particulate pollution in different urban environments.

Our findings demonstrate that urban morphology creates distinct microclimatic and air quality zones at scales too fine to be captured by traditional monitoring networks. The methodology developed provides a robust framework for high-resolution urban air quality assessment applicable to other urban environments. These insights can inform targeted interventions in urban planning and traffic management to reduce exposure to air pollution at the street level. The approach also establishes a foundation for the validation and calibration of low-cost sensor networks and computational fluid dynamics models for urban applications. Ongoing work is focused on quantifying the relationships between urban features and air quality outcomes, as well as exploring seasonal and diurnal patterns in these relationships.

This work has been implemented by the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014) project within the framework of Hungary's National Recovery and Resilience Plan supported by the Recovery and Resilience Facility of the European Union.