Numerical simulations of the flow field and pollutant dispersion in an idealized urban area under different atmospheric stability conditions

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Highlights

  • Influence of atmospheric stability on urban dispersion is investigated numerically.

  • Canyon vortex intensity differs under unstable, neutral and stable conditions.

  • Stable atmospheric stratification will aggravate urban pollution consequence.

  • Plume deflection is a significant characteristic of the urban dispersion.

Abstract

This study simulated the flow and near-field plume dispersion in an urban-like environment under unstable, neutral and stable atmospheric stratification using the steady Reynolds-averaged Navier-Stokes (RANS) methodology. First, a validation study for two trials of the Mock Urban Setting Test (MUST) experiments is performed to examine the predictive performance of the computational fluid dynamics (CFD) model, Fluidyn-PANACHE. The effects of atmospheric stability on the flow structure in street canyons under perpendicular incident flow conditions are investigated. In addition, the patterns of urban dispersion in different cases of stability are also analysed under perpendicular and oblique wind direction conditions. The results show that in the urban environment, the influence of atmospheric stability on the canyon vortex intensity, flow structure and plume dispersion is apparent; intense thermal turbulence enhances the vortex intensity and plume dilution in the street canyon under unstable conditions; when the atmospheric conditions are stable, the vertical profile of the streamwise velocity is significantly decreased by the obstacles, and the concentration level and spread of pollutants increase in the street canyon due to relatively weak turbulent motions; plume deflection within the obstacle array is noteworthy when the incident flow is oblique; in particular, the transport of the plume is basically independent of the wind direction very near the ground.

Introduction

The dispersion of airborne contaminants in urban environments has been a prominent issue over the last 20 years. The accidental release of hazardous gases and traffic emissions in urban areas pose potential risks to public safety and health. Thus, a comprehensive understanding of the processes that influence urban dispersion is essential for risk assessment and environmental protection. The interaction between atmospheric flow and buildings results in a complex flow field and turbulent structure, which makes the urban dispersion process more complicated. In addition, these processes are also affected by meteorological conditions, such as atmospheric stability.

Most of the early reports about urban dispersions are field, wind-tunnel and water-tunnel experiment studies. These experiments mainly investigate the effects of obstacle groups on plume dispersion patterns. Davidson et al., 1995, Davidson et al., 1996 studied the effects of cube groups on the plume dispersion of a ground-level source at a distance far upwind via field and wind tunnel experiments. The results show that some dispersion characteristics in the obstacle array are broadly similar to those on flat terrain. Macdonald et al. (1997, 1998) showed that a larger plan area density and obstacle aspect ratio increase the lateral distributions of near-field plumes by performing further field and wind-tunnel experiments. The influence of obstacle arrays on far-field dispersion is limited. Therefore, Gaussian plume models generally work well in urban areas sufficiently far from the source. However, for a source located in the array, the near-field dispersion depends strongly on the shape and configuration of the obstacle. Mavroidis (2000) investigated the flow and dispersion around a single obstacle in aligned and staggered arrays. The results show that the discrepancies in the flow field and dimensions of the recirculation zone cause different concentration profiles in the wake of different obstacles within the array. Belcher (2005) reviewed important fluid dynamic processes that affect neighbourhood scale dispersion within the urban canopy and further interpreted the mechanisms of several dispersion processes (e.g., topological dispersion and secondary sources). Some full-scale field experiments were conducted in real cities with a specific configuration, such as Allwine et al. (2002) and Allwine et al. (2004). To gain insight into the general impact of buildings, other outdoor experiments were performed in a simplified representation of a city, for example, Kit Fox (Hanna and Chang, 2001) and the MUST series experiment (Biltoft, 2001). The MUST experiment was conducted to acquire copious data of the flow and dispersion in an urban-like area. These experimental data improved the understanding of urban dispersion and supported the development and validation of numerical models (Yee and Biltoft, 2004). In addition, many laboratory experiments simulated the flow and dispersion in the MUST array (Gailis, 2004; Hilderman and Chong, 2004). Yee et al. (2006) compared the results from the aforementioned physical modelling with MUST field data and focused on the effects of obstacles on plume details (such as concentration fluctuation).

Over the years, with the improvement of computational power and development of computational fluid dynamics, CFD simulation has become an alternative research tool due to its low cost in comparison to field and wind-tunnel experiments and has been able to reproduce detailed diffusion processes around complex geometries. Many numerical studies have already provided detailed descriptions of the flow field and dispersion processes in urban-like arrays with different shapes and arrangements of obstacles and aspect ratios of street canyons (e.g., Hanna et al., 2002; Coceal et al., 2006, 2007; Xie and Castro, 2009; Martilli and Santiago, 2007; Boppana et al., 2010). Santiago et al. (2007) simulated the flow and plume dispersion in the regular array of cubes with the standard k - ε turbulence model and validated the simulated results using statistical evaluation methods. Tan et al. (2018) studied the transport and dispersion of carbon dioxide plumes in a long street with an intersection using the SST k - ω model. Many numerical studies further investigated the patterns of plume dispersion within the obstacle array based on the MUST field experiments. Milliez and Carissimo (2007) used a CFD code, Mercure_Saturne, to simulate 20 trials of the MUST experiments under different meteorological conditions and emphasized the effect of elongated buildings on plume deflection in the obstacle array. Santiago et al. (2010) and Dejoan et al. (2010) studied the flow and plume dispersion in the MUST array based on the large-eddy simulation (LES) and RANS methodologies, respectively. Santiago et al. (2010) indicated the impact of geometric irregularities on the local time-mean flow properties when the incident wind is perpendicular to the obstacle array. Dejoan et al. (2010) further considered the effect of incident wind angle deviation on plume dispersion and indicated that near-ground plume deflection is the consequence of a strong channelling effect in the array; additionally, plume orientation varies with altitude. Branford et al. (2011) simulated tracer dispersion from a point source in a regular array of cubes for different wind directions and analysed some processes affecting the plume structure. The results show that recirculation promotes the detrainment of pollutants in the street canyons; topological dispersion can arise when the array layout is in a staggered arrangement with respect to the approaching flow direction.

These prior studies mainly addressed the impacts of wind direction and geometry configuration on the flow and pollutant dispersion in the urban environment. Some studies have indicated that the influence of thermal stratification on flow and pollutant dispersion cannot be neglected. Uehara et al. (2000) identified that thermal stratification influences the intensity of cavity eddies in street canyons by performing wind tunnel experiments. Pontiggia et al. (2009) developed an approach that can consider atmospheric stratifications in CFD simulations by adding a source term to the balance equation of the turbulence dissipation rate (ε). Steffens et al. (2013) studied the effects of a solid barrier on the spatial distributions of pollutants under various atmospheric stability conditions. Mavroidis et al. (2012) studied the residence of atmospheric pollutants in the wake of a cubic building under different stability conditions using CFD simulation. These researchers found that the residence time of the pollutant under unstable conditions is shorter than that under stable conditions. Xie (2010) compared the simulated concentration profile under neutral and unstable atmospheric conditions (bulk Richardson number, Rib = 0, −0.1, −0.24 and −0.9) in an urban environment and showed that the effect of thermal stratification on urban dispersion is not negligible. Xie et al. (2013) further studied the flow and dispersion in a staggered array of cubes under different atmospheric conditions; however, this work only analyses some local flow properties. At present, studies on the effect of thermal stratification on urban dispersion are lacking. Therefore, there is a need to further study the general effect of atmospheric stability on flow patterns and pollutant dispersion in an urban area.

In this study, validation simulations of the MUST field dispersion experiments are performed using a CFD model, Fluidyn-PANACHE. The predictive performance is evaluated by statistical comparisons between the simulated concentrations and observations. To further study the effects of atmospheric stability (unstable, neutral and stable) on the flow and dispersion in an urban environment, this work simulates the flow field and plume dispersion released from a point source within a regular obstacle array under different stability conditions. In addition, the influence of oblique wind direction (45°) on plume dispersion is considered.

Section snippets

Numerical models

A three-dimensional CFD model Fluidyn-PANACHE is applied to simulate atmospheric flows and pollutant dispersion in open and complex environments based on the RANS methodology (Fluidyn-PANCHE, 2010; Kumar et al., 2015). In this simulation, we utilized a modified standard k - ε model to acquire the steady-state flow field based on the steady RANS approach. Additionally, the Boussinesq approximation was used to simplify the computation. Air was considered an incompressible fluid, and its density

Geometric description

In the simulation, the height (H) of the rectangular obstacle is 2 m. The dimensions of the obstacle are H×3H×H. The configuration studied consists of 56 obstacles, with dimensions of 8 obstacles in the streamwise direction (x-axis) and 7 obstacles in the spanwise direction (y-axis). The overall length and width of the array are 36H and 33H, respectively. The obstacle spacings in the lengthwise and spanwise directions are 4H and 2H. The origin of the Cartesian coordinates used is located at the

Description of the MUST experiment

The MUST field experiment was conducted for the Defense Threat Reduction Agency (DTRA) at the U.S. Army Dugway Proving Ground Horizontal Grid test site during 6–27 September 2001. The MUST experiment is designed to support the development and validation of urban dispersion models. Biltoft (2001) and Yee and Biltoft (2004) introduced detailed descriptions of the experimental setup, layout of containers, meteorological conditions and source parameters. The urban-like area is modelled by an array

Results and discussion

The vertical profiles of normalised streamwise velocity (u/Uref) at different locations are compared between the unstable, neutral and stable conditions (see Fig. 1c). The contours of u/Uref, normalised vertical velocity w/Uref and normalised turbulent kinetic energy k/Uref 2 and flow field structure on the y/H = 0 plane are mainly studied when the wind direction is perpendicular to the array. In addition, simulated concentrations are normalized by the formula K=CUrefH2/Q (C is the volume

Conclusions

In this study, a validation simulation was conducted to examine the performance of modelling of the MUST dispersion experiment using the CFD code Fluidyn-PANACHE. The predictive ability of the model for urban dispersion was verified by comparing the simulated concentrations with observations. Furthermore, a numerical study was performed to investigate the flow patterns and plume dispersion within an urban-like area under unstable, neutral and stable atmospheric conditions. We focused on the

Declaration of Competing Interest

The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

Acknowledgements

The authors would like to thank China Institute for Radiation Protection (CIRP) for their technical support.

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