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

Abstract

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—most harmful as 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 reveal 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 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. Environmental ImplicationsPM2.5, known for its adverse effects including severe respiratory and cardiovascular diseases in humans, and its hazards to degrade ecosystem health, poses significant environmental threats. This study reveals how tree leaves interact with these fine particulates, focusing on the distinct capabilities of various tree species based on their leaf characteristics. By demonstrating that specific leaf waxy and physiological attributes enhance PM2.5 constituent capture, the research supports bio-inspired approaches to air quality management. Strategic tree planting and potential genetic modifications of trees emerge as viable strategies for reducing atmospheric PM2.5, offering sustainable solutions to mitigate particulate pollution.