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Advisor(s)
Abstract(s)
This study investigates the impact of street trees on air pollutant concentrations, specifically NO₂
and PM10, in urban environments using computational fluid dynamics (CFD) simulations with
ENVI-met software. The study explores how different levels of tree cover influence the dispersion
of atmospheric pollutants, focusing on three scenarios: current tree cover, complete removal of
street trees, and a 50 % reduction in tree cover. Avenida da Liberdade in Lisbon, known for its
high tree density, serves as the study site. To ensure the accuracy of the simulations, the method
was validated using air quality data from a local monitoring station, supplemented by an analysis
of lichen diversity on 80 trees, a common biomonitor for pollution. The results indicate that both
NO₂ and PM10 concentrations are higher under tree canopies, with the greatest increase observed
on the windward side of the avenue. Specifically, PM10 levels rose by up to 2.97 %, and NO₂ by
up to 25.84 % in the scenario with the highest tree cover. Moreover, the study highlights that
street trees have a more significant effect on NO₂ concentrations compared to PM10. The findings
suggest that, in this specific case—where there is a high density of trees and low wind speed—
reducing tree coverage and improve permeability to the wind, could improve pollution dispersion. This study provides key findings into the complex role of urban trees in air quality and offers
a foundation for future research into the modelling of additional pollutants, such as PM2.5 and
ozone, to gain a more comprehensive understanding of their impacts on urban air quality.
Description
Keywords
Air quality Urban vegetation Urban pollutant simulation Wind speed Lichens
Pedagogical Context
Citation
Girotti, C., Matos, P. S. A., Shimomura, A. R. P., Kurokawa, F. A., Correia, E & Lopes, A. (2025). Microclimate simulation and lichen-based validation analyzing street trees' impact on atmospheric pollutant dispersion at the urban canyon scale. Urban Climate, 62, 102549. https://doi.org/10.1016/j.uclim.2025.102549
Publisher
Elsevier