An overview about the study of downwash effects on dispersion of airborne pollutants

Canepa, Elisa

doi:10.1016/j.envsoft.2003.11.011

Cited by 39 publications

(13 citation statements)

References 50 publications

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“…However, according to numerous references, their short comings resulting from: (i) the isotropic turbulent viscosity concept (Nallasamy, 1987;Pope, 2000;Wright and Easom, 2003) and (ii) the steady-state methodology (Rodi, 1997;Cheng et al, 2003;Canepa, 2004;Shirasawa et al, 2008) do not allow to these models to correctly reproduce many wind-flow characteristics such as transient vortices, periodic fluctuations, etc. Therefore, their use is restricted and suited to statistically steady mean flows that are, in turn, a difficult requirement to satisfy when it is question of flows in urban environments.…”

Section: Numerical Modelling Errorsmentioning

confidence: 98%

“…;Canepa (2004);Ahmad et al (2005);Li et al (2006);Holmes and Morawska (2006); Moreira et al (2009); Fernando et al (2010); Blocken and Stathopoulos (2010); Kawamoto et al (2011); Moonen et al (2012a); Capelli et al (2013); Tominaga and Stathopoulos (2013); Di-Sabatino et al (2013); Blocken et al (2013); Musalaiah et al (2013); Meroney and Derickson (2014); Blocken (2014); Xia et al (2014); Janhall (2015); Chen et al (2015) Practice guidelines…”

mentioning

confidence: 98%

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On the use of numerical modelling for near-field pollutant dispersion in urban environments − A review

Lateb

Meroney

Yataghene

et al. 2016

Environmental Pollution

230

107

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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.

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Section: Numerical Modelling Errorsmentioning

confidence: 98%

mentioning

confidence: 98%

On the use of numerical modelling for near-field pollutant dispersion in urban environments − A review

Lateb

Meroney

Yataghene

et al. 2016

Environmental Pollution

230

107

View full text Add to dashboard Cite

show abstract

“…A review of these can be found in Canepa (2004). The two most commonly used models are those developed by Schulman and Scire (1980) and Huber and Snyder (1982).…”

Section: Stack Building and Terrain Effectsmentioning

confidence: 99%

An On Line Atmospheric Dispersion Model (OLADMO) for the World Wide Web

Clegg¹

2006

Surv Geophys

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This paper presents an overview of earlier and current methods of modelling atmospheric dispersion, and proposes and evaluates a screening model for operation over the World Wide Web. The On Line Atmospheric Dispersion Model (OLADMO) is a quasi boundary layer parameterised Gaussian plume model with additional algorithms to account for plume rise, building wake effects and deposition processes. The Monin-Obukhov length boundary layer parameter is utilised to define six stability classes in order to determine atmospheric turbulence and stability, whilst new equations, derived from an intercomparison study of old and next generation dispersion models, are used to calculate the horizontal and vertical dispersion coefficients r y and r z . Using data from two field experiments in Copenhagen, Denmark and Lillestrøm, Norway, the model results from OLADMO are found to compare favourably with the results from several old and next generation dispersion models. As a consequence of the unique nature of the meteorological and location factors of the Lillestrøm experiment, all models struggled to represent the concentrations observed during the field study adequately. However, OLADMO was the best performing model in this case, with a mean normalised crosswind integrated concentration 13% closer to the mean observed concentration than its nearest competitor. Because the evaluation of the model was conducted with a limited dataset, several limitations and improvements to both the model and experimental procedure are suggested.

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“…For example, see the reviews by Canepa (2004), Walsh and Jones (2002) and Olesen and Genikhovich (2000). The physical processes involved are similar to those in vehicle wakes in many respects and a similar approach can be adopted.…”

Section: Approaches Derived From Building Wakesmentioning

confidence: 99%

An overview of experimental results and dispersion modelling of nanoparticles in the wake of moving vehicles

Carpentieri

Kumar

Robins

2011

Environmental Pollution

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An overview about the study of downwash effects on dispersion of airborne pollutants

Cited by 39 publications

References 50 publications

On the use of numerical modelling for near-field pollutant dispersion in urban environments − A review

On the use of numerical modelling for near-field pollutant dispersion in urban environments − A review

An On Line Atmospheric Dispersion Model (OLADMO) for the World Wide Web

An overview of experimental results and dispersion modelling of nanoparticles in the wake of moving vehicles

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