Abstract
The growing population in cities is causing a deterioration of air quality due to the emission of pollutants, causing serious health impacts. Trees and urban forests can contribute through the interception and removal of air pollutants such as particulate matter (PM). The dry deposition of PM by vegetation depends on air pollutant concentration, meteorological conditions, and specific leaf traits. Several studies explored the ability of different plant species to accumulate PM on leaf structures leading to the development of models to quantify the PM removal. The i-Tree Eco is the most used model to evaluate ecosystem services provided by urban trees. However, fine particulate matter (PM2.5) removal is still calculated with a poorly evaluated function of deposition velocity (which depends on wind speed and leaf area) without differentiating between tree species. Therefore, we present an improvement of the standard model calculation introducing a leaf trait index to distinguish the species effect on PM net removal. We also compared model results with measurements of deposited leaf PM by vacuum filtration. The index includes the effect of morphological and functional leaf characteristics of tree species using four parameters: leaf water storage, deposition velocity, resuspension rate and leaf washing capacity. Leaves of 11 common urban tree species were sampled in representative areas of the city of Ferrara (Italy) and at different times of the year from 2018 to 2021. This includes four deciduous broadleaf trees (Tilia cordata, Platanus acerifolia, Acer platanoides, Celtis australis), three evergreen broadleaf trees (Quercus ilex, Magnolia grandiflora, Nerium oleander), and four conifers (Thuja orientalis, Cedrus libani, Pinus pinaster, Picea abies). The results provide significant advancement in assessing PM removal using decision support tools such as models to properly select tree species for future urban tree planting programs aimed at improving air quality.
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