Abstract

The ecosystem services provided by urban forests contribute to ameliorate air quality and human well-being in cities. An integrated approach based on direct measurements of leaf functional multi-traits and on estimation of the plant mitigation potential was used for predicting the species-specific impact on air quality of 29 species, including trees and shrubs, commonly present in the urban context. In addition, volatile organic compound (VOC) emissions and ozone forming potential (OFP) of each species were evaluated. At plant levels, pollution deposition equations and the i-Tree Eco model were applied for estimating particulate (PM10) and ozone (O3) removal potential and for calculating carbon dioxide (CO2) storage and sequestration by the studied species. The results highlight the plant species-specific ability to capture atmospheric pollutants based on their physiological (CO2 assimilation and stomatal conductance) and morphological (stomata, trichomes, waxes and cuticular ornamentation) leaf traits. Trees with abundant trichomes, waxes and wrinkled leaf surfaces are considered more suitable for capturing pollutants. Most of the studied species are suitable for urban planning programs as they result for the majority low VOC emitters and consequently are characterized by low or moderate OFP. Annual O3 and PM10 removal of the investigated trees species ranged from about 58–140 g plant−1 yr−1 and from about 17–139 g plant−1 yr−1, respectively. Total tree CO2 storage ranged from about 164–215 kg plant−1 and gross annual CO2 sequestration from 11 to 20 kg plant−1 year−1. Liriodendron tulipifera, Celtis australis, Acer campestre and Acer platanoides, were efficient species in capturing PM10 and absorbing O3. Prunus cerasifera, Quercus cerris, together with Celtis australis, Acer campestre and Acer platanoides, were efficient for carbon sequestration and storage. As aspected, lower potential of pollutant removal and CO2 storage and sequestration were estimated for shrubs, due to their smaller leaf area and structure.

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