The impact of urban block typology on pollutant dispersion

Silva, Fabiana Trindade da; Reis, Neyval Costa; Santos, Jane Méri; Goulart, Elisa Valentim; Alvarez, Cristina Engel de

doi:10.1016/j.jweia.2021.104524

Cited by 26 publications

(7 citation statements)

References 48 publications

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“…To investigate the speed achieved by a RANS model in an urban geometry, the popular and open-source CFD environment OpenFOAM [9] was used to solve the system of equations with the shear stress transport (SST) k − ω [10][11][12] turbulence closure in parallel on a local server with 80 cores. This closure was validated for urban geometries in [13,14], and it is an adequate choice because of its relatively low computational cost. OpenFOAM has support for both compressible and incompressible turbulent flow simulations in 3D, as well as an extensive set of turbulence closures for RANS modelling.…”

Section: Introductionmentioning

confidence: 99%

Use and Scalability of OpenFOAM for Wind Fields and Pollution Dispersion with Building- and Ground-Resolving Topography

Elfverson

Lejon

2021

Atmosphere

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Complex flow and pollutant dispersion simulations in real urban settings were investigated by using computational fluid dynamics (CFD) simulations with the SST k−ω Reynolds-averaged Navier–Stokes (RANS) equation with OpenFOAM. The model was validated with a wind-tunnel experiment using two surface-mounted cubes in tandem, and the flow features were reproduced with the correct qualitative behaviour. The real urban geometry of the Parade Square in Warsaw, Poland was represented with both laser-scanning data for the ground geometry and the CityGML standard to describe the buildings as an example. The Eulerian dispersion of a passive scalar and the flow behaviour could be resolved within minutes over a computational domain with a size of 958 × 758 m2 and a height of 300 m with over 2 M cells due to the good and strong parallel scalability in OpenFOAM. This implies that RANS modelling with parallel computing in OpenFOAM can potentially be used as a tool for situational awareness on a local urban scale; however, entire cities would be too large.

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Section: Introductionmentioning

confidence: 99%

Use and Scalability of OpenFOAM for Wind Fields and Pollution Dispersion with Building- and Ground-Resolving Topography

Elfverson

Lejon

2021

Atmosphere

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“…It should be noted that the majority of the publications (63%) follow the best practice guidelines for domain height and accept this dimension to be equal or greater than 6H. Some of them even use much higher values: 12H [16], 17H [48], 25H [49], and 33.3H [50]. However, there is still a rather high percentage (19%) that do not comply with the existing recommendations.…”

Section: Domain Heightmentioning

confidence: 99%

“…Findings suggest that the urban landscape, building geometries, and various mechanical means are important measures to control air pollution. In this regard, some authors have introduced the definition of different urban and ventilation indices, describing city breathability and supporting a sustainable building design [15,16]. However, such parameters are still not widely utilized in urban planning and have not yet been included in a legislative framework.…”

Section: Introduction 1why Air Pollution Is a Hot Topicmentioning

confidence: 99%

Air Pollution Dispersion Modelling in Urban Environment Using CFD: A Systematic Review

et al. 2022

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Air pollution is a global problem, which needs to be understood and controlled to ensure a healthy environment and inform sustainable development. Urban areas have been established as one of the main contributors to air pollution, and, as such, urban air quality is the subject of an increasing volume of research. One of the principal means of studying air pollution dispersion is to use computational fluid dynamics (CFD) models. Subject to careful verification and validation, these models allow for analysts to predict air flow and pollution concentration for various urban morphologies under different environmental conditions. This article presents a detailed review of the use of CFD to model air pollution dispersion in an urban environment over the last decade. The review extracts and summarises information from nearly 90 pieces of published research, categorising it according to over 190 modelling features, which are thematically systemised into 7 groups. The findings from across the field are critically compared to available urban air pollution modelling guidelines and standards. Among the various quantitative trends and statistics from the review, two key findings stand out. The first is that, despite the existence of best practice guidelines for pollution dispersion modelling, anywhere between 12% and 34% of the papers do not specify one or more aspects of the utilised models, which are required to reproduce the study. The second is that none of the articles perform verification and validation according to accepted standards. The results of this review can, therefore, be used by practitioners in the field of pollution dispersion modelling to understand the general trends in current research and to identify open problems to be addressed in the future.

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“…Jiang et al [23] used CFD to simulate the changes in neighborhood microclimate and pollutant diffusion distribution under different weather conditions and proposed three strategies for the optimization of urban planning to alleviate air pollution. Fabiana et al [24] investigated the impact of different urban block types on the diffusion of urban pollutants. Using computational fluid dynamics technology, five types of real cities were studied: single, independent buildings, central courtyards, internal courtyards, and determinant layouts.…”

Section: Previous Studiesmentioning

confidence: 99%

“…Accurate simulation of natural ventilation is particularly important for this entire village. Therefore, in this study, we chose to measure wind environment data during the peak tourist season, which has high temperatures and heavy rainfall (22)(23)(24). We compared the measured data with the simulated data to verify the accuracy of the three CFD model simulations.…”

Section: Data Measurement and Model Settingmentioning

confidence: 99%

Wind Environment Simulation Accuracy in Traditional Villages with Complex Layouts Based on CFD

Yao

Han

Dewancker

2021

IJERPH

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Using wind speed, wind direction, and turbulence intensity values as evaluation indicators, the ventilation performance of villages with complex building layouts was studied. We used the SKE, RNG, and RKE solvers in CFD-3D steady-state Reynolds-averaged Navier–Stokes (RANS) to simulate the wind environment of a village. The findings show that for the simulation of rural wind environments with complex building layouts, steady-state simulation solvers need to be evaluated in detail to verify their accuracy. In this study, a village with a complex architectural layout in Southern Shaanxi, China, was taken as the research object, and three steady-state simulation solvers were used to evaluate the ventilation performance of the village. The simulated data were compared with the measured data to find the most suitable solver for this kind of village wind environment simulation. The results show that for the simulation of the village wind environment with a complex building layout, the RNG simulation results have the lowest reliability among the three steady-state solvers. The reliability of wind speed distribution and turbulence intensity distribution are 0.7881 and 0.2473, respectively. However, the wind speed and turbulence intensity values obtained by the SKE solver are the closest to the measured values, which are 0.8625 and 0.9088, respectively. Therefore, for villages with complex building layouts, the SKE solver should be the first choice for simulating wind environment distribution. When using the RNG solver, the overall turbulence intensity value obtained is higher than the measured value. The average deviation between the simulated data and SKE and RKE at a height of 1.7 m is 42.61%. The main reason for this is that RNG overestimates the vortices and underestimates the airflow rate in the building intervals.

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The impact of urban block typology on pollutant dispersion

Cited by 26 publications

References 48 publications

Use and Scalability of OpenFOAM for Wind Fields and Pollution Dispersion with Building- and Ground-Resolving Topography

Use and Scalability of OpenFOAM for Wind Fields and Pollution Dispersion with Building- and Ground-Resolving Topography

Air Pollution Dispersion Modelling in Urban Environment Using CFD: A Systematic Review

Wind Environment Simulation Accuracy in Traditional Villages with Complex Layouts Based on CFD

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