Evaluating the impact of roadside vegetation barriers on urban air pollution using low-cost mobile sensors

Abstract

Urban population growth has led to an increase in the number of people living near major roads and highways, increasing exposure to roadside air pollution. This has raised significant public health concerns and driven efforts to regulate air quality in these micro-environments. Solutions such as the implementation of vegetation barriers can reduce exposure to traffic-related emissions by influencing pollutant dispersion patterns. Three primary methods are commonly used to characterize pollutant distribution in complex urban environments: (i) geostatistical analysis using remote sensing, (ii) high-precision measurements across physical barriers, and (iii) dispersion models, particularly computational fluid dynamics (CFD) models. Although numerous studies have investigated the role of vegetation in mitigating traffic-related air pollution, most have relied on small-scale assessments or modeled data. This study presents a comprehensive workflow for evaluating the effectiveness of vegetation barriers in improving urban air quality. It utilizes real-world data collected over two years (May 2015-December 2017) using low-cost mobile sensors in Pamplona, Spain –a medium-sized European city representative of 80% of urban areas in Europe– within the framework of the LIFE+Respira project. Seven pollutants (CO, NO, NO₂, O₃, PM₁, PM_2.5, and PM₁₀) were analyzed. Results revealed significant reductions in CO, NO, and NO₂ levels behind vegetation barriers, while O₃ increased. Findings for PMx were mixed, suggesting that barrier effectiveness depends on particle size and vegetation characteristics. These results are consistent with previous research validating the methodology. Future studies could refine this approach, assess long-term vegetation impacts, and explore additional environmental factors influencing urban air pollution dynamics.