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On the use of numerical modelling for near-field pollutant dispersion in urban environments − A review
2016
Lateb, M. | Meroney, R.N. | Yataghene, M. | Fellouah, H. | Saleh, F. | Boufadel, M.C.
This article deals with the state-of-the-art of experimental and numerical studies carried out regarding air pollutant dispersion in urban environments. Since the simulation of the dispersion field around buildings depends strongly on the correct simulation of the wind-flow structure, the studies performed during the past years on the wind-flow field around buildings are reviewed. This work also identifies errors that can produce poor results when numerically modelling wind flow and dispersion fields around buildings in urban environments. Finally, particular attention is paid to the practical guidelines developed by researchers to establish a common methodology for verification and validation of numerical simulations and/or to assist and support the users for a better implementation of the computational fluid dynamics (CFD) approach.
Mostrar más [+] Menos [-]Influence of avenue-trees on air quality at the urban neighborhood scale. Part I: Quality assurance studies and turbulent Schmidt number analysis for RANS CFD simulations
2015
Gromke, Christof | Blocken, Bert
Flow and dispersion of traffic pollutants in a generic urban neighborhood with avenue-trees were investigated with Computational Fluid Dynamics (CFD). In Part I of this two-part contribution, quality assessment and assurance for CFD simulations in urban and vegetation configurations were addressed, before in Part II flow and dispersion in a generic urban neighborhood with multiple layouts of avenue-trees were studied. In a first step, a grid sensitivity study was performed that inferred that a cell count of 20 per building height and 12 per canyon width is sufficient for reasonable grid insensitive solutions. Next, the performance of the realizable k-ε turbulence model in simulating urban flows and of the applied vegetation model in simulating flow and turbulence in trees was validated. Finally, based on simulations of street canyons with and without avenue-trees, an appropriate turbulent Schmidt number for modeling dispersion in the urban neighborhood was determined as Sct = 0.5.
Mostrar más [+] Menos [-]Effects of inhomogeneous ground-level pollutant sources under different wind directions
2021
Wang, Huanhuan | Ngan, Keith
Effects of source inhomogeneity on pollutant dispersion from a cubic building array are investigated as a function of the external wind direction. Using building-resolving large-eddy simulation, it is found that the results depend strongly on the source location and source uniformity inside a near-field region defined by a radius of homogenisation (RAD) based on the spatial autocorrelation of the pollutant concentration. The sensitivity of the RAD to the source location changes abruptly around 30° and is greatly reduced for wind angles between 30 and 45°, in agreement with velocity statistics and the mean horizontal streamlines. The optimal source allocation, which is a proxy for emissions from time-dependent traffic, also changes around 30°. This work clarifies the relationship between inhomogeneous velocity and pollutant statistics and may be applied to the formulation of traffic control policy.
Mostrar más [+] Menos [-]A Review on Atmospheric Dispersion System for Air Pollutants Integrated with GIS in Urban Environment
2022
Namrata and N. D. Wagh
The objective of this article is to present comprehensive findings and analysis of studies performed on air pollutant dispersion in urban environments. It captures India’s rising environmental pollution due to urbanization, industrialization, and population growth. Dispersion of pollutants due to the wind in the lower Atmospheric Boundary Layer (ABL) is a major concern nowadays. The dispersion field around the buildings is a critical parameter to analyze and it primarily depends on the correct simulation of the wind flow structure. Therefore, studies performed on this in past years are being reviewed. Additionally, a brief review of different air dispersion models that are integrated with the Geographic Information System (GIS) has been studied in this article to assess the exposure. The results of these studies provide the urban air dispersion model aligning to three sub-models i.e., Emission, Weather Prediction, and Dispersion models. Various factors like wind speed, wind direction, cloud cover, traffic emission, disposal of waste, transportation, and others are considered. This study also captures the problems and risks being faced while creating a model, and its possible mitigation approaches.
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