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V. Rodrigues et al.
in mitigating air pollution in urban areas, mainly considering the effects of trees
induced by mechanical drag and/ or including the removal capacity of trees by deposition and filtration mechanisms [1, 2]. Although the effects of green infrastructures
(GI) on the atmospheric dynamics have been widely studied, a deeper knowledge
is still required regarding the overall perturbations induced by trees on turbulent
flows and, consequently, on pollutants dispersion. Furthermore, the study of climate
change (CC) ranges from global scale down to the regional and urban scale [3, 4].
Nevertheless, the full understanding of the impact of CC on urban microclimate and
air quality at local scale remains a challenge with a lack of accurate predictions. This
study aims to improve our understanding of how the changes on global and regional
circulations will affect local scale urban microclimate, assessing the impact of GI on
air quality under future climate scenarios for Porto’s urban area.
23.2 Methodology
A cascade of numerical models, from global to local scale, was applied to Porto
urban area. The numerical model Weather Research and Forecasting (WRF) [5] was
applied for 4 nested domains, with 27, 9, 3 and 1 km resolution. Two simulations were
performed, a representative simulation of the recent past climate, and a representative
simulation of the future medium-term climate assuming the Representative Concentration Pathway Scenario RCP8.5. The CFD model VADIS was then applied to Porto
urban area to assess local scale flow dynamics and air quality [6]. VADIS is applied
to an area defined in the city centre of Porto turned into a computational domain
of 1300 m × 1300 m × 150 m (Fig. 23.1), which includes the air quality station Francisco Sá Carneiro-Campanhã, mainly influenced by road-traffic emissions. The CFD
simulations were performed with a grid resolution of 3 m × 3 m × 3 m. Figure 23.1a
shows the computational domain for the baseline simulations. Figure 23.1b presents
the implementation area for the green scenarios, identified by the red rectangles,
which corresponds to 35% of the current built-up area located in the Southeast part
of the domain. The green parks scenario corresponds to the replacement of the builtup area by green parks, while the green roofs scenario includes the implementation
of green roofs within the buildings of the selected area.
Hourly averaged CO, NO x and PM10 emission rates from on-road transport vehicles were calculated using the Transport Emission Model for Line Sources (TREM).
The hourly emission rates are estimated for each road segment, considering the local
information on traffic counting data. Vehicle counting data was acquired using automatic devices installed in seven distinct locations. Empirical rates expressing the
relation with the traffic in the surrounding roads were applied in case of roads without available data [6]. The high emission levels are registered during the morning
until evening, while the low emission levels are estimated during the night. Several baseline CFD simulations were performed for 24th September 2010, due to the
availability of traffic counting data. The meteorological inflow data for these CFD
simulations were obtained from mesoscale simulations using WRF model. The future
V. Rodrigues et al.
in mitigating air pollution in urban areas, mainly considering the effects of trees
induced by mechanical drag and/ or including the removal capacity of trees by deposition and filtration mechanisms [1, 2]. Although the effects of green infrastructures
(GI) on the atmospheric dynamics have been widely studied, a deeper knowledge
is still required regarding the overall perturbations induced by trees on turbulent
flows and, consequently, on pollutants dispersion. Furthermore, the study of climate
change (CC) ranges from global scale down to the regional and urban scale [3, 4].
Nevertheless, the full understanding of the impact of CC on urban microclimate and
air quality at local scale remains a challenge with a lack of accurate predictions. This
study aims to improve our understanding of how the changes on global and regional
circulations will affect local scale urban microclimate, assessing the impact of GI on
air quality under future climate scenarios for Porto’s urban area.
23.2 Methodology
A cascade of numerical models, from global to local scale, was applied to Porto
urban area. The numerical model Weather Research and Forecasting (WRF) [5] was
applied for 4 nested domains, with 27, 9, 3 and 1 km resolution. Two simulations were
performed, a representative simulation of the recent past climate, and a representative
simulation of the future medium-term climate assuming the Representative Concentration Pathway Scenario RCP8.5. The CFD model VADIS was then applied to Porto
urban area to assess local scale flow dynamics and air quality [6]. VADIS is applied
to an area defined in the city centre of Porto turned into a computational domain
of 1300 m × 1300 m × 150 m (Fig. 23.1), which includes the air quality station Francisco Sá Carneiro-Campanhã, mainly influenced by road-traffic emissions. The CFD
simulations were performed with a grid resolution of 3 m × 3 m × 3 m. Figure 23.1a
shows the computational domain for the baseline simulations. Figure 23.1b presents
the implementation area for the green scenarios, identified by the red rectangles,
which corresponds to 35% of the current built-up area located in the Southeast part
of the domain. The green parks scenario corresponds to the replacement of the builtup area by green parks, while the green roofs scenario includes the implementation
of green roofs within the buildings of the selected area.
Hourly averaged CO, NO x and PM10 emission rates from on-road transport vehicles were calculated using the Transport Emission Model for Line Sources (TREM).
The hourly emission rates are estimated for each road segment, considering the local
information on traffic counting data. Vehicle counting data was acquired using automatic devices installed in seven distinct locations. Empirical rates expressing the
relation with the traffic in the surrounding roads were applied in case of roads without available data [6]. The high emission levels are registered during the morning
until evening, while the low emission levels are estimated during the night. Several baseline CFD simulations were performed for 24th September 2010, due to the
availability of traffic counting data. The meteorological inflow data for these CFD
simulations were obtained from mesoscale simulations using WRF model. The future