PM_2.5 is an air pollutant that has a direct link to increased cardiovascular and respiratory morbidity and mortality, which has been demonstrated in numerous studies. Existing research highlights species-specific variations in the capacity of trees to capture and retain particulate matter (PM). However, a critical gap remains regarding sensitivity analyses of i-Tree Eco model assumptions. Such analyses are crucial for validating the model’s PM deposition estimates against empirically derived efficiencies, a deficiency that the present study addresses. The study consisted of two steps: a tree inventory was carried out at three selected sites, based on which, an ecosystem service analysis was performed using i-Tree Eco, and samples were taken from the leaves of trees at the analysed sites, which were the basis for comparing the data from the i-Tree Eco method and laboratory methods. The study focused on comparing PM_2.5 and PM₁₀ removal estimates derived from both the model and laboratory measurements. The results revealed significant discrepancies between the modelled and laboratory values. A comparison of the average annual PM₁₀ accumulation measured using laboratory methods for individual tree species showed that Tilia sp. achieved 24%, Fraxinus sp. 47.6%, Aesculus sp. 50.77%, and Quercus robur 23.4% of the PM₁₀ uptake efficiency estimated by the i-Tree Eco model. For PM_2.5 uptake, the values obtained through both methods were more consistent. Furthermore, trees growing under more challenging environmental conditions exhibited smaller diameter at breast height (DBH) and lower PM₁₀ and PM_2.5 removal efficiency according to both methods. While I-Tree Eco incorporates tree biophysical characteristics and health status, its methodology currently lacks the resolution to reflect site-specific environmental conditions and local pollutant concentrations at the individual tree level. Therefore, laboratory methods are indispensable for calibrating, validating, and supplementing i-Tree Eco estimates, especially when applied to diverse urban environments. Only the combined application of empirical and model-based methods provides a comprehensive understanding of the potential of urban greenery to improve air quality.

The conflicting demands of urban trees and walkable surfaces result in significant financial burdens for municipal administrators who understand that urban residents want tree-lined walkable surfaces. This study investigates three methodologies for mitigating this tension: suspended grating systems, modular box systems, and structural soils. A Multi-Criteria Analysis (MCA) was conducted to evaluate their suitability in dense urban areas, employing criteria categorized into Environmental, Economical, and Other considerations. The comparison focused on critical aspects such as the impact on tree health (root growth, water availability), installation complexity, initial costs, and overall suitability for diverse urban contexts. The MCA indicates that, under the given weighting of criteria, suspended grating systems (especially those suited for existing trees) rank the highest, primarily due to their superior root protection and minimal disturbance to established root systems. In contrast, modular box systems and structural soils emerge as particularly strong contenders for new tree plantings. Structural soils may have application at sites with existing trees, but the costs of removing native soil are a consideration. Sensitivity analysis suggests that modular box systems may become the preferred option when greater emphasis is placed on stormwater management and new plantings, rather than on challenges for existing trees or underground infrastructure. Structural soils score well in cost-effectiveness and installation speed but require careful implementation to address their lower root protection performance and long-term maintenance concerns. Ultimately, the optimal solution depends on unique site-specific conditions and budgetary constraints, emphasizing the necessity of tailored approaches to balance urban infrastructure with tree health.