Mapping the constituent preference of tree species for capturing particulate matter on leaf surfaces using single-particle mass spectrometry and supervised machine learning.

Respiratory health is negatively influenced by the dimensions and constituents of particulate matter (PM). Although mass concentration is widely acknowledged to be key to assessing dust retention by urban trees, the role of plant leaves in filtering PM from the urban atmosphere, particularly regarding the particle dimensions and chemical constituents of retained PM on the leaf, remains elusive. Here we combined single-particle aerosol mass spectrometry and a particle resuspension chamber to investigate how urban tree species capture PM constituents. Results indicate that leaves are efficient in capturing relatively larger particles (1.0-2.0 µm). Compositionally, airborne particles were mostly composed of elemental carbon (EC, 20%), organic carbon (OC, 17%), and secondary reaction products (13%). However, leaf surfaces revealed a preference for retaining crustal species, comprising 55% of captured particulates. Notably, specific tree species demonstrated varied affinities for different PM constituents: Osmanthus fragrans Lour. predominantly captured levoglucosan (LEV), indicative of its efficiency against biomass burning particles, whereas Cinnamomum camphora (L.) J.Presl and Sabina chinensis var. kaizuca W.C.Cheng & W.T.Wang were more effective in capturing heavy metals (HMs). XGBoost modelling identified indicator ions, e.g., CN-, NO3-, NO2-, PO3-, with SHAP values surpassing 0.035, suggesting a preferential adsorption of these ions among different tree species. These findings demonstrate that the particulate capture efficiency of urban tree species varies with species-specific leaf properties, particularly in their ability to selectively adsorb particles containing hazardous constituents such as LEV and HMs. This study provides a scientific basis for the strategic selection of tree species in urban forestry initiatives aimed at improving air quality and public health.

Selective capture of PM2.5 by urban trees: The role of leaf wax composition and physiological traits in air quality enhancement.

Human health risks from particles with a diameter of less than 2.5 µm (PM2.5) highlight the role of urban trees as bio-filters in air pollution control. However, whether the size and composition of particles captured by various tree species differ or not remain unclear. This study investigates how leaf attributes affect the capture of PM2.5, which can penetrate deep into the lungs and pose significant health risks. Using a self-developed particulate matter (PM) resuspension chamber and single-particle aerosol mass spectrometer, we measured the size distribution and mass spectra of particles captured by ten tree species. Notably, Cinnamomum camphora (L.) J.Presl and Osmanthus fragrans Lour. are more effective at capturing particles under 1 µm, which are most harmful because they can reach the alveoli, whereas Ginkgo biloba L. and Platanus × acerifolia (Aiton) Willd. tend to capture larger particles, up to 1.6 µm, which are prone to being trapped in the upper respiratory tract. Leaf physiological traits such as stomatal conductance and water potential significantly enhance the capture of larger particles. The Adaptive Resonance Theory neural network (ART-2a) algorithm classified a large number of single particles to determine their composition. Results indicate distinct inter-species variations in chemical composition of particles captured by leaves. Moreover, we identified how specific leaf wax compositions-beyond the known sticky nature of hydrophobic waxes-contribute to particle adhesion, particularly highlighting the roles of fatty acids and alkanes in adhering particles rich in organic carbon and heavy metals, respectively. This research advances our understanding by linking leaf physiological and wax characteristics to the selective capture of PM2.5, providing actionable insights for urban forestry management. The detailed exploration of particle size and composition, tied to specific tree species, enriches the current literature by quantifying how and why different species contribute variably to air quality improvement. This adds a crucial layer of specificity to the general knowledge that trees serve as bio-filters, offering a refined strategy for planting urban trees based on their particulate capture profiles.