Abstract
This work focus on the assessment of green infrastructures benefits on air quality in Porto urban area, applying the CFD model VADIS to a particular area within the city. Three scenarios have been considered: (i) the baseline refers to the current morphological characteristics of the area; (ii) a green scenario comprises the replacement of built-up areas by green areas; and (iii) a green scenario corresponding to the implementation of green roofs. The results of baseline simulations shows a good agreement with local measurements with a NMSE of 0.4, 0.6 and 2.1 for CO, NO\(_2\) and PM10 concentrations, respectively. The benefits of green infrastructures on air quality are assessed for future medium-term climate scenarios (2041–2070), applying a cascade of numerical models, from global to urban scale, the WRF-VADIS modelling system. Future climate data point out a decrease in the number of days with moderate to strong wind speed, and an increase in the number of days recording low wind speed conditions. The assessment of green infrastructures effects on air quality under future climate focus on low wind speed conditions. The results clearly show the disturbances exerted by green infrastructures, which are positively or negatively affecting mainly the adapted areas and their close surroundings.
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Acknowledgements
Thanks are due for the financial support to CESAM (UID/AMB/50017 – POCI-01-0145-FEDER-007638), to the FCT/MCTES through national funds (PIDDAC), and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. The authors also acknowledge the Portuguese “Ministério da Ciência, Tecnologia e Ensino Superior” for the PhD Grant of Sandra Sorte (SFRH/BD/117164/2016).
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Rodrigues, V. et al. (2020). Modelling the Potential of Green Infrastructures to Reduce the Impact of Climate Change on Air Quality at Microscale. In: Mensink, C., Gong, W., Hakami, A. (eds) Air Pollution Modeling and its Application XXVI. ITM 2018. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-22055-6_23
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DOI: https://doi.org/10.1007/978-3-030-22055-6_23
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