Multi-scale influence of urban green space vegetation on deposition and diffusion of atmospheric particulate matter: Implications for functional design

Urban PM pollution remains a major environmental concern, with green space vegetation aiding its mitigation. Nonetheless, limited integration of deposition and diffusion effects across multiple spatial scales has hindered the development of practical guidelines for vegetation-based PM management. This study selected representative vegetation communities and tree species within the urban green spaces of Xianyang for three repeated sampling sessions. Field monitoring combined with particle-size analysis via elutriation was employed to analyze the temporal and spatial patterns of PM concentrations and deposition at both the community and individual plant scales. Cross-scale interrelationships were further assessed to infer the role of vegetation in PM deposition and diffusion processes. This study indicated: (1) All vegetation communities showed higher PM2.5 but generally reduced PM10 and TSP concentrations compared to open squares. closed mixed onelayered communities were most efficient in lowering PM10 and TSP concentration, while broadleaf-dominated communities showed the highest deposition per unit area, with deposition positively correlating with PM concentrations. (2) Picea asperata, Pinus bungeana, and Juniperus chinensis demonstrated the highest PM deposition per leaf area, whereas Salix matsudana, Melia azedarach, and Styphnolobium japonicum exhibited superior total deposition per plant. (3) Community structure had limited influence on species deposition capacity, while species composition significantly affected both deposition and concentration of the community. (4) PM deposition significantly increased over sampling periods. (5) PM concentrations decreased throughout the day. Meteorological conditions significantly affected PM concentration levels. These insights facilitate the development of function-oriented vegetation designs for urban green spaces aimed at optimized PM mitigation.