Urban Green System Planning Insights for a Spatialized Balance between PM 10 Dust Retention Capacity of Trees and Urban Vehicular PM 10 Emissions

MariaElena Menconi, Rosaria Abbate, Luca Simone and David Grohmann ()
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MariaElena Menconi: Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06100 Perugia, Italy
Rosaria Abbate: Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06100 Perugia, Italy
Luca Simone: Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06100 Perugia, Italy
David Grohmann: Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06100 Perugia, Italy

Sustainability, 2023, vol. 15, issue 7, 1-17

Abstract: Reducing air pollution is a crucial challenge in urban areas. In this regard, urban green infrastructures could play a pivotal role. In the literature, scholars analyzed both the ability of species-specific and layout-specific green infrastructures to reduce air pollution and the best location sites of new green infrastructures to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement based on vegetation species-specific performance and differentiated demand for the ecosystem services of city areas. This paper uses tree cadastre data from a medium-sized city in central Italy (Perugia) and the traffic open-layers of Gmaps to develop a spatial analysis of the urban trees’ performance in PM 10 dust retention, and the PM 10 produced by vehicular emissions, respectively. The method generates a spatialized balance between demand (air-polluted sites by traffic) and supply (PM 10 dust retention by trees) to support local decisions about the best locations for new green infrastructures and the choice between species. The paper analyzed 6710 urban trees in an area of 42.62 km 2 with a linear road density of 15 km/km 2 . Platanus hybrida Mill. ex Münchh, Celtis australis L., Ulmus carpinifolia L., Pinus pinaster Aiton, Quercus ilex L., Quercus robur L., and Tilia cordata Mill. are the resulting optimal species to reduce PM 10 , with median values of 219.62, 181.47, 166.67, 154.66, 143.90, 118.61, and 118.04 g tree −1 yr −1 , respectively. The paper is a first contribution in developing GIS-based tools that vary the recommended location sites and species for new green infrastructures based on the demanded ecosystem service. Urban planners are called to dynamically use and integrate numerous tools, such as the one developed here, to seek complex solutions capable of increasing the sustainability of urban systems.

Keywords: green infrastructure; urban forest; tree cadastre; air pollutant; ecosystem service; compensation point; Geographic Information System; GIS; urban planning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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