Local and non-local effects of building arrangements on pollutant fluxes within the urban canopy

Goulart, Elisa Valentim; Reis, Neyval Costa; Lavor, Vitor; Castro, Ian P.; Santos, Jane Méri; Xie, Zheng-Tong

doi:10.1016/j.buildenv.2018.09.023

Cited by 14 publications

(13 citation statements)

References 26 publications

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“…It is to be noted that close to the ground the turbulent flux component u T in Eq. 10 is always very small or negative compared to the advective part U T (Fuka et al 2018;Goulart et al 2019). Similarly, the advective component U T in the vicinity of the ground is also very small as the mean flow speed is nearly zero.…”

Section: Ground Temperature Sensitivity Testmentioning

confidence: 93%

Thermal Stratification Effects on Turbulence and Dispersion in Internal and External Boundary Layers

Sessa

Xie

Herring

2020

Boundary-Layer Meteorol

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A synthetic-turbulence and temperature-fluctuation-generation method is developed and embedded in large-eddy simulations to investigate the effects of weak stable stratification (i.e. Richardson number Ri ≤ 1) on turbulence and dispersion following a simulated ruralto-urban transition. The modelling approach is validated by comparing predictions of mean velocity, turbulent stresses, and point-source dispersion against data from a wind-tunnel experiment that simulates a stable atmospheric boundary layer (Ri = 0.21) approaching a regular array of uniform rectangular blocks. The depth of the internal boundary layer (IBL) that develops from the leading edge of the block array is determined using the wall-normal turbulent stress method proposed by Sessa et al. (J Wind Eng Ind Aerodyn 182:189-291, 2018). This shows that the depth and growth rate of the IBL are sensitive to the thermal stability and the turbulence kinetic energy (TKE) prescribed at the inlet, such that the IBL depth reduces as the TKE of the inflow is reduced while maintaining the same Ri, or as the Ri is increased while maintaining the same inflow TKE. When a ground level line source is introduced it is found that increasing Ri evidently reduces the vertical scalar fluxes at the canopy height, while increasing the mean concentrations within the streets. Furthermore, as with IBL development it is found that for a given value of Ri the effect of stratification becomes more pronounced as the inflow level of TKE is reduced, affecting scalar fluxes within and above the canopy, and volume-averaged mean concentrations within the streets.

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Section: Ground Temperature Sensitivity Testmentioning

confidence: 93%

Thermal Stratification Effects on Turbulence and Dispersion in Internal and External Boundary Layers

Sessa

Xie

Herring

2020

Boundary-Layer Meteorol

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“…Studies investigating such effects are either based on experimental observations, physical models, numerical simulations, or combined approaches of varying complexity. To mention a few examples, studies have been carried out for isolated buildings (Higson et al, 1996;Foroutan et al, 2018;Jiang and Yoshie, 2020), arrays of mounted obstacles (Coceal et al, 2014;Fuka et al, 2018;Goulart et al, 2019), and urban canopies close to reality (Auguste et al, 2020;Hertwig et al, 2021). While for single buildings, the number of variables reduces to the shape and orientation of the obstacle relative to the approaching flow, the relative position of obstacles to each other (aligned vs. staggered) is at least as important for building arrays.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, transversal and vertical dispersion is more pronounced in the staggered case. For vertical dispersion, both the contributions by the mean flow from the diverging streamlines in front of the upstream faces and turbulent dispersion in the building wakes are of similar importance (Goulart et al, 2019). Buildings not only enhance dispersion but can also trap pollution within horizontal re-circulation zones, which then act as secondary sources (Coceal et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions

et al. 2022

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Abstract. There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. In this paper, CAIRDIO is applied on the simulation of black carbon and particulate matter dispersion for an entire mid-size city using a uniform horizontal grid spacing of 40 m. For model evaluation, measurements from five operational air monitoring stations representative for the urban background and high-traffic roads are used. The comparison also includes the mesoscale host simulation, which provides the boundary conditions. The measurements show a dominant influence of the mixing layer evolution at background sites, and therefore both the mesoscale and large-eddy simulation (LES) results are in good agreement with the observed air pollution levels. In contrast, at the high-traffic sites the proximity to emissions and the interactions with the building environment lead to a significantly amplified diurnal variability in pollutant concentrations. These urban road conditions can only be reasonably well represented by CAIRDIO while the meosocale simulation indiscriminately reproduces a typical urban-background profile, resulting in a large positive model bias. Remaining model discrepancies are further addressed by a grid-spacing sensitivity study using offline-nested refined domains. The results show that modeled peak concentrations within street canyons can be further improved by decreasing the horizontal grid spacing down to 10 m, but not beyond. Obviously, the default grid spacing of 40 m is too coarse to represent the specific environment within narrow street canyons. The accuracy gains from the grid refinements are still only modest compared to the remaining model error, which to a large extent can be attributed to uncertainties in the emissions. Finally, the study shows that the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. The results, however, also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.

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“…Studies investigating such effects are either based on experimental observations, physical models, numerical simulations or combined approaches of varying complexity. To mention few examples, studies have been carried out for isolated buildings (Higson et al, 1996;Foroutan et al, 2018;Jiang and Yoshie, 2020), arrays of mounted obstacles (Coceal et al, 2014;Fuka et al, 2018;Goulart et al, 2019), and urban canopies close to reality (Auguste et al, 2020;Hertwig et al, 2021). While for single buildings, the number of variables reduces to the shape and orientation of the obstacle relative to the approaching flow, the relative position of obstacles to each other (aligned vs. staggered) is at least as important for building arrays.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, transversal and vertical dispersion is more pronounced in the staggered case. For vertical dispersion, both the contributions by the mean flow from the diverging streamlines in front of the upstream faces and turbulent dispersion in the building wakes are of similar importance (Goulart et al, 2019). Buildings do not only enhance dispersion but can also trap pollution within horizontal re-circulation zones, which then act as secondary sources (Coceal et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

On the application and grid-size sensitivity of the urban dispersion model CAIRDIO for the simulation of a real city and realistic meteorology

Weger

Heinold

Wiedensohler

et al. 2021

Preprint

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Abstract. There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. For this purpose, CAIRDIO is applied in dispersion simulation of black carbon and particulate matter for an entire mid-size city using an uniform horizontal resolution of 40 m in this paper. For evaluation, the simulation results are compared with measurements from 5 operational air monitoring stations, which are representative for the urban background and high-traffic roads, respectively. Moreover, the comparison includes the mesoscale host simulation, which provides the boundary conditions. The temporal variability of the concentration measurements at the background sites was largely influenced only by the characteristics of the mixing layer. As a consequence, the model results were not significantly dependent on spatial resolution, so that the mesoscale simulation also performed reasonably well. At the traffic sites, however, concentrations were in addition markedly influenced by the proximity to road-traffic sources and the surrounding building environment. Here, the mesoscale simulation indiscriminately reproduced almost the same urban-background profiles, which resulted in a large positive model bias. On the other hand, the CAIRDIO simulation was able to respond to the significantly amplified diurnal variability with its pronounced rush-hour peaks. This resulted in a consistent improvement of the model deviation to mea- surements compared to the mesoscale simulation. Nevertheless, discrepancies to measurements remain in the 40 m-CAIRDIO simulation, e.g., an underestimation of peak concentrations at two traffic sites inside narrow street canyons. To further research resolution sensitivity, the horizontal grid spacing of locally nested CAIRDIO domains is refined down to 5 m. While for the street canyons the representation of peak concentrations can be improved using horizontal grid spacings of up to 10 m, no further improvements beyond this resolution can be observed. This suggests that the too low peak concentrations with the default grid spacing of 40 m result from an inadequate representation of the traffic emissions inside narrow street canyons. If the total gain in accuracy due to the grid refinements is put in relation to the remaining model error, the improvements are only modest. In conclusion, the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. Nevertheless, the results also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.

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Local and non-local effects of building arrangements on pollutant fluxes within the urban canopy

Cited by 14 publications

References 26 publications

Thermal Stratification Effects on Turbulence and Dispersion in Internal and External Boundary Layers

Thermal Stratification Effects on Turbulence and Dispersion in Internal and External Boundary Layers

On the application and grid-size sensitivity of the urban dispersion model CAIRDIO v2.0 under real city weather conditions

On the application and grid-size sensitivity of the urban dispersion model CAIRDIO for the simulation of a real city and realistic meteorology

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