Optimizing particulate matter removal through rainfall: Role of duration, intensity, and species in green...

This study investigates how short-duration intense rainfall events enhance the removal of particulate matter (PM) from plant leaf surfaces in urban environments, thereby contributing to the regulation of air pollution in urban environments and advancing the estimation and measurement of ecosystem services modelling in urban green spaces associated with air pollution regulation and remediation. Using controlled artificial rainfall simulations, we identified optimal combinations of rainfall phase (duration), intensity, plant species, plant height above ground (representing the nozzle-to-leaf distance), and particle diameter to maximize PM removal. Our findings indicate that rainfall phase is crucial in the PM removal process, while particle diameter has minimal influence. Throughout all rainfall phases, plant species consistently play a significant role, driven by differences in leaf morphology and microstructure. The study also identifies optimal rainfall conditions for different species, suggesting dynamic adjustments to intensity and nozzle distance throughout the event to enhance PM removal efficiency. For equal rainfall amounts, lower-intensity, longer-duration events are generally more effective, though nozzle distance should align with species-specific preferences. In contrast, higher rainfall intensities (45-60 mm/h) paired with shorter nozzle distances (1 m plant height, 11 m distance) optimize PM removal for fixed rainfall durations. These findings not only identify optimal rainfall conditions for specific species, providing practical strategies for urban green infrastructure management, but also provide valuable insights into estimating the air purification benefits of rainfall-driven PM removal from leaf surfaces.