Trees grown in streets impact air quality by influencing ventilation (aerodynamic effects), pollutant deposition (dry deposition on vegetation surfaces), and atmospheric chemistry (emissions of biogenic volatile organic compounds, BVOCs). To qualitatively evaluate the impact of trees on pollutant concentrations and assist decision-making for the greening of cities, 2-D simulations on a street in greater Paris were performed using a computational fluid dynamics tool coupled to a gaseous chemistry module. Globally, the presence of trees has a negative effect on the traffic-emitted pollutant concentrations, such as NO2 and organic condensables, particularly on the leeward side of a street. When not under low wind conditions, the impact of BVOC emissions on the formation of most condensables within the street was low owing to the short characteristic time of dispersion compared with the atmospheric chemistry. However, autoxidation of BVOC quickly forms some extremely-low volatile organic compounds, potentially leading to the formation of ultra-fine particles. Planting trees in streets with traffic is only effective in mitigating the concentration of some oxidants such as ozone (O3), which has low levels in cities regardless of this, and hydroxyl radical (OH), which may slightly lower the rate of oxidation reactions and the formation of secondary species in the street.

Cities are heterogeneous environments, and pollutant concentrations are often higher in streets compared with in the upper roughness sublayer (urban background) and cannot be represented using chemical-transport models that have a spatial resolution on the order of kilometers. Computational Fluid Dynamics (CFD) models coupled to chemistry/aerosol models may be used to compute the pollutant concentrations at high resolution over limited areas of cities; however, they are too expensive to use over a whole city. Hence, simplified street-network models, such as the Model of Urban Network of Intersecting Canyons and Highways (MUNICH), have been developed. These include the main physico-chemical processes that influence pollutant concentrations: emissions, transport, deposition, chemistry and aerosol dynamics. However, the streets are not discretized precisely, and concentrations are assumed to be homogeneous in each street segment. The complex street micro-meteorology is simplified by considering only the vertical transfer between the street and the upper roughness sublayer as well as the horizontal transfer between the streets. This study presents a new parametrization of a horizontal wind profile and vertical/horizontal transfer coefficients. This was developed based on a flow parametrization in a sparse vegetated canopy and adapted to street canyons using local-scale simulations performed with the CFD model Code_Saturne. CFD simulations were performed in a 2D infinite street canyon, and three streets of various aspect ratios ranging from 0.3 to 1.0 were studied with different incoming wind directions. The quantities of interest (wind speed in the street direction and passive tracer concentration) were spatially averaged in the street to compare with MUNICH. The developed parametrization depends on the street characteristics and wind direction. This effectively represents the average wind profile in a street canyon and the vertical transfer between the street and the urban roughness sublayer for a wide range of street aspect ratios while maintaining a simple formulation.

Trees provide many ecosystem services in cities such as urban heat island reduction, water runoff limitation, and carbon storage. However, the presence of trees in street canyons reduces the wind velocity in the street and limits pollutant dispersion. Thus, to obtain accurate simulations of pollutant concentrations, the aerodynamic effect of trees should be taken into account in air quality models at the street level. The Model of Urban Network of Intersecting Canyons and Highways (MUNICH) simulates the pollutant concentrations in a street network, considering dispersion and physico-chemical processes. It can be coupled to a regional-scale chemical transport model to simulate air quality over districts or cities. The aerodynamic effect of the tree crown is parameterized here through its impact on the average wind velocity in the street direction and the vertical transfer coefficient associated with the dispersion of a tracer. The parameterization is built using local-scale simulations performed with the computational fluid dynamics (CFDs) code Code_Saturne. The two-dimensional CFD simulations in an infinite street canyon are used to quantify the effect of trees, depending on the tree characteristics (leaf area index, crown volume fraction, and tree height to street height ratio) using a drag porosity approach. The tree crown slows down the flow and produces turbulent kinetic energy in the street, thus impacting the tracer dispersion. This effect increases with the leaf area index and the crown volume fraction of the trees, and the average horizontal velocity in the street is reduced by up to 68 %, while the vertical transfer coefficient by up to 23 % in the simulations performed here. A parameterization of these effects on horizontal and vertical transfers for the street model MUNICH is proposed. Existing parameterizations in MUNICH are modified based on Code_Saturne simulations to account for both building and tree effects on vertical and horizontal transfers. The parameterization is built to obtain similar tree effects (quantified by a relative deviation between the cases without and with trees) between Code_Saturne and MUNICH. The vertical wind profile and mixing length depend on leaf area index, crown radius, and tree height to street height ratio. The interaction between the trees and the street aspect ratio is also considered.

The mesoscale atmospheric model Meso-NH is used to investigate the influence of mesoscale atmospheric turbulence on the mean flow, turbulence, and pollutant dispersion in an idealized urban-like environment, the array of containers investigated during the Mock Urban Setting Test field experiment. First, large-eddy simulations are performed as in typical computational fluid dynamics-like configurations, i.e., without accounting for the atmospheric- boundary-layer (ABL) turbulence on scales larger than the building scale. Second, in a multiscale configuration, turbulence of all scales prevailing in the ABL is accounted for by using the grid-nesting approach to downscale from the mesoscale to the microscale. The building-like obstacles are represented using the immersed boundary method and a new turbulence recycling method is used to enhance the turbulence transition between two nested domains. Upstream of the container array, flow characteristics such as wind speed, direction and turbulence kinetic energy are well reproduced with the multiscale configuration, showing the efficiency of the grid-nesting approach in combination with turbulence recycling for downscaling from the mesoscale to the microscale. Only the multiscale configuration is able to reproduce the mesoscale turbulent structures crossing the container array. The accuracy of the numerical results is evaluated for wind speed, wind direction, and pollutant concentration. The microscale numerical simulation of wind speed and pollutant dispersion in an urban-like environment benefits from taking into account the ABL turbulence. However, this benefit is significantly less important than that described in the literature for the Oklahoma City Joint Urban 2003 real case. The present study highlights that pollutant dispersion simulation improvement when accounting for ABL turbulence is dependent on the specific configuration of the city.

We present a conservative second order staggered time scheme for dry and moist variable density air flow implemented in the open source CFD solver code saturne. The staggered time arrangement introduced by Pierce and Moin [1] is extended to finite volumes and discontinuous solutions. An Helmholtz equation is solved in order include the thermodynamical pressure variation and to remove the acoustic CFL restriction. The internal energy equation supplemented by a corrective source term based on the kinetic energy dissipation [2] is solved, allowing the scheme to be consistent with discontinuous solutions. The water phase change is treated by considering thermodynamical equilibrium. Dalton’s law is used to compute the density and the temperature is obtained from the internal energy equation, solving with Newton’s method in case of phase change. A numerical analysis is presented to insure the positivity of the thermodynamic variables, followed by the scheme verification and validation. First, dry air cases are presented: a natural convection and shock cases are used to verify its accuracy related to singularities and buoyancy effects. Moreover, a pressure cooker like system shows the scheme good reproduction of pressure variations and correct time error convergences rates. Finally, the moist air module is verified against analytical cases.

Micro-meteorological studies of urban flow and pollution dispersion often assume a neutral atmosphere and often the three-dimensional variation in temperature fields and flow around buildings is neglected in most building energy balance models. The aim of this work is to present the results of development and validation of a three-dimensional tool coupling thermal energy balance of the buildings and modelling of the atmospheric flow and dispersion in urban areas. To do so, a 3D microscale atmospheric radiative scheme has been developed in the atmospheric module of the computational fluid dynamics (CFD) code Code_Saturne adapted to detailed building geometries. The full coupling of the radiative transfer and fluid dynamics models has been validated with idealized cases. In this paper, our focus is to simulate and compare with measurements the diurnal evolution of the brightness surface temperatures and the momentum and energy fluxes for a neighborhood in the city center of Toulouse, in the southwest part of France. This is performed by taking into account the 3D effects of the flow around the buildings and all thermal exchanges, in real meteorological conditions, and compare them to aircraft infrared images and in situ measurements on a meteorological mast. The calculation mesh developed for the city center and the simulation conditions for the selected day of the field campaign are presented. The results are evaluated with the measurements from the Canopy and Aerosol Particles Interactions in TOulouse Urban Layer experiment (CAPITOUL). In addition, the second purpose of this work is to investigate a hypothetical release of passive pollutant dispersion in the same area of Toulouse under different thermal transfer conditions for the street and the buildings surfaces: neutral and 3D radiative transfer heating. The presence of heat transfer continually modifies the airflow field while the airflow in the neutral case reaches a stationary state. Compared to the neutral case, taking into account the thermal transfer enhances the turbulence kinetic energy and vertical velocity (especially at the roof level) due to buoyancy forces. The simulation results also show that the thermal effects considerably alter the plume shape.

In this study, we present a robust conservative time‐staggered scheme for variable density flow. This pressure correction scheme uses the compressible Navier–Stokes equations and is implemented in the collocated finite‐volume open‐source computational fluid dynamics solver code_saturne. The Helmholtz equation is solved for the pressure increment, taking the thermodynamic pressure into account and avoiding the acoustic time step limitation. The internal energy equation is used and completed by a source term derived from the discrete kinetic energy equation, thus enforcing total energy conservation and consistency for irregular solutions. A numerical analysis providing conditions ensuring the positivity of the thermodynamic variables is proposed. The scheme is verified and validated against analytical and experimental test cases. Its ability to reproduce the pressure variation while conserving the mass is demonstrated. Its conservative property and time convergence order are also verified. An irregular shock solution is studied, emphasizing the importance of the source term in the internal energy equation. Finally, the scheme is validated against reference numerical results on a two‐dimensional natural convection cavity and experimental data on a three‐dimensional ventilation test case. The comparison against experimental data is made using first‐and second‐order turbulent simulations.

The goal of this research is to assess environmental quality at the neighbourhood level through a multi-dimensional and multi-sensory approach that combines social and physical methodologies. For this purpose, an interdisciplinary protocol has been designed to simultaneously collect physical parameter measurements (related to microclimate and acoustics) and survey data on perceptions (involving residents and non-residents). The cross-referenced analysis of data collected at six contrasting places in a district in Toulouse (France) enabled us (i) to better understand and prioritise the factors that influence residents' assessment of the quality of their living environment and (ii) to understand to what extent the differentiation of the places by the inhabitants converges with the differentiation of these places based on acoustic and micrometeorological measurements. The statistical analysis based on individuals showed the importance of noise and air quality that rank just after the aesthetic dimension for all respondents. Nevertheless, the quality of maintenance and the feeling of security that the place inspires seem to be as crucial as these environmental criteria for the inhabitants. The analysis focused on the sites highlighted the consistency between the typology of places based on perceptions and that based on acoustic measurements, which confirms the high inhabitants' sensitivity to this environmental component.

Air-pollution modelling at the local scale requires accurate meteorological inputs such as from the velocity field. These meteorological fields are generally simulated with microscale models (here Code_Saturne ), which are forced with boundary conditions provided by larger scale models or observations. Local atmospheric simulations are very sensitive to the boundary conditions, whose accurate estimation is difficult but crucial. When observations of the wind speed and turbulence or pollutant concentration are available inside the domain, they provide supplementary information via data assimilation, to enhance the simulation accuracy by modifying the boundary conditions. Among the existing data assimilation methods, the iterative ensemble Kalman smoother (IEnKS) is adapted to urban-scale simulations. This method has already been found to increase the accuracy of wind-resource assessment. Here we assess the ability of the IEnKS method to improve scalar-dispersion modelling—an important component of air-quality modelling—by assimilating perturbed measurements inside the urban canopy. To test the data assimilation method in urban conditions, we use the observations provided by the Mock Urban Setting Test field campaign and consider cases with neutral and stable conditions, and the boundary conditions consisting of the horizontal velocity components and turbulence. We prove the capacity of the IEnKS method to assimilate observations of velocity as well as pollutant concentration. In both cases, the accuracy of pollutant concentration estimates is enhanced by 40–60%. We also show that assimilating both types of observations allows further improvements of turbulence predictions by the model.

After the summer 2015 chlorine releases during the Jack Rabbit II field experiment at Dugway Proving Ground, a special sonic anemometer study was carried out in October 2015 and March 2016. The goal was to provide documented wind fields in similar conditions to the actual releases and to study building wakes without risk for the instruments. This study included 30 sonic anemometers that were placed around these “buildings” to best capture the recirculating regions. Building wakes are important for the dispersion of pollutants in cities and around industrial plants and therefore we have selected two time periods during March 2016, in order to present model to model and model to data comparisons. There are four models involved in the comparison ranging from a diagnostic wind model with wake parameterization and Lagrangian particle dispersion and a CFD model with a k-ε turbulence closure and solving the Eulerian dispersion equation. Detailed comparisons are carried out for the wind speed and for the turbulence level. Six virtual releases are added in the simulations to investigate how the wake resolving method can affect the dispersion. For the wind speed comparison, the models give fair to good comparison with the sonic measurements. However, for the turbulence comparison the results clearly show a need for improvement, even for the k-ε closure, which still provides the best results. For the concentrations, for which there is no corresponding measurements, we find that the simulations are much closer than for the turbulence comparison.

Accurate wind fields simulated by CFD models are necessary for many environmental and safety micrometeorological applications, such as wind resource assessment. Atmospheric simulations at local scale are largely determined by boundary conditions (BCs), which are generally provided by mesoscale models (e.g., WRF). In order to improve the accuracy of the BCs, especially in the lowest levels, data assimilation methods might be used to take available observations into account. Among the existing data assimilation methods, the iterative ensemble Kalman smoother (IEnKS) has been chosen and adapted to micro-meteorology by taking BCs into account. In the present study, we assess the ability of the IEnKS to improve wind simulations over a very complex topography, by assimilating a few in situ observations. The IEnKS is tested with the CFD model Code_Saturne in 2D and 3D using both twin experiments and field observations. We propose a method to determine the first estimate of the BCs and to construct the associated background error covariance matrix, from the statistical analysis of three years of WRF simulations. The IEnKS is proved to greatly reduce the error and the uncertainty of the BCs and thus of the simulated wind field. Consequently, the wind potential is more accurately estimated.

Precise wind fields simulated by CFD models are used for many environmental and safety micro-meteorological applications, such as dispersion modelling or wind potential assessment. Atmospheric simulations at local scale are largely determined by boundary conditions, which are provided, for instance, by meso-scale models (e.g., WRF). In order to improve the accuracy of the boundary conditions (BC), especially in the lowest levels more perturbed by high resolution topography, data assimilation methods might be used to take available observations into account. Data assimilation methods have been generally developed for larger scale meteorology and initial conditions. Among the existing methods, the iterative ensemble Kalman smoother (IEnKS) has been chosen as it is independent of the atmospheric model and it is able to handle non-linear operators. The IEnKS has been adapted to local scale atmospheric simulations by taking BCs into account. This adapted version has previously been tested on a simple shallow-water model in 1D. In the present study, we analyse the performances of the IEnKS in 3D with the CFD model Code Saturne using both twin experiments and field observations over a realistic, very complex topography. We propose a method to determine the first estimate of the control vector, which corresponds to the BCs, and to construct the associated background error covariance matrix, from the statistical analysis of three years of WRF simulations. The IEnKS is proved to greatly reduce the error and the uncertainty on the BCs and thus on the simulated wind field over the small-scale domain. The IEnKS is also tested in urban conditions with observations provided by the Mock Urban Setting Test field campaign. This study case allows to evaluate the possibility to assimilate either wind observations (speed and direction) or pollutant concentration values. We present here the first results obtained in this urban configuration.

We clarify issues related to the expression of Lagrangian stochastic models used for atmospheric dispersion applications. Two aspects are addressed: the need to verify the well-mixed criterion and the correspondence between Eulerian and Lagrangian turbulence models when they are combined in practical simulations. In particular, it is recalled that the fulfillment of the well-mixed criterion depends only on the proper incorporation of the mean pressure-gradient term as the mean drift term of the Langevin equation. New consistency issues between duplicate fields within Eulerian/Lagrangian hybrid formulations are also brought out, especially regarding turbulence models, boundary conditions, and divergence-free condition. Such hybrid methods, where mean flow quantities calculated with an Eulerian approach are provided to the Lagrangian approach, are commonly used in atmospheric dispersion simulations for their numerical efficiency. Nevertheless, it is shown that serious inconsistencies can result from coupling Eulerian and Lagrangian models that do not correspond to the same level of description of the fluid turbulence.

We present an intercomparison of two models applied to a major boulevard in a Paris suburb accounting for building effects: (1) a computational fluid dynamics (CFD) model providing a detailed three-dimensional representation of the atmospheric flow and pollutant dispersion (Code_Saturne) and (2) a street-network model with well-mixed steady-state concentrations within street segments coupled with a regional chemical-transport model (SinG). Simulations were performed for five cases representing different meteorological conditions (wind direction and speed) and two sensitivity cases with different emissions. We compare model results to measurements of NOx at two monitoring stations on either side of the street. Results exhibit (a) a complex behavior highlighting effects of the street-network configuration and emission patterns on the cross-street concentration gradient and (b) a satisfactory performance with assumption of well-mixed concentrations within street-canyons for mean NOx (MNE of 39% and 22%; and NMB of -29% and -7% for Code_Saturne and SinG, respectively).

We present an adaptation of the Lagrangian stochastic dispersion model of the computational fluid dynamics (CFD) open source code Code_Saturne to simulate atmospheric dispersion of pollutants in complex urban geometries or around industrial plants. The wind is modeled within the same code with an Eulerian RANS (Reynolds-averaged Navier-Stokes equations) approach and thus involves the solution for the ensemble-mean velocity field and turbulent moments, using eddy viscosity or Reynolds stress turbulence models adapted to the atmosphere and complex geometries. The Lagrangian stochastic model used for the dispersion of the particles within this flow field is the simplified Langevin model, which pertains to the approaches referred to as PDF (Probability Density Function) methods. This formulation of model has not been widely used in atmospheric applications, despite interesting theoretical and computational benefits. Therefore, its usage must be validated on different atmospheric cases. In this paper, we present the validation of the model with a field experiment, considering atmospheric stratification and buildings: the MUST (Mock Urban Setting Test) campaign, conducted in Utah’s desert, USA.

Lagrangian atmospheric dispersion models consist of tracking the trajectories of particles of pollutant emitted into the atmosphere. In this paper, the objective is to compare the Lagrangian and Eulerian dispersion models in the same computational fluid dynamics code (Code_Saturne), therefore using the same wind and turbulence fields for both. The Lagrangian stochastic model used in this work is the simplified Langevin model (SLM) of Pope (1985, 2000) and pertains to the approaches referred to as probability density function methods. This model has been extensively used in turbulent combustion or multiphase flows, but to our knowledge, it has not been used in atmospheric dispersion applications. First, we show that the SLM respects the well-mixed criterion. Then, we validate the model in the case of a continuous point release with uniform mean wind speed and turbulent diffusivity. Finally, we validate the model with an experimental campaign involving a stably stratified surface layer.

Detailed, high resolution, unsteady RANS simulations are used to study short episodes of local pollution dispersion in the neighborhood of Bordelongue in Toulouse in the framework of the French ANR project EUREQUA (Haoues-Jouve et al. 2015). These urban areas consist of various types of buildings and obstacles: small houses, tower blocks, highway, local streets, vegetation areas, etc. The 3D geometry of this urban area was constructed with an in house tool developed around the open-source geometry and mesh generator SALOME, based on the available geophysical data from the French geographical institute (IGN). The open-source computational fluid dynamics (CFD) code Code_Saturne, with the atmospheric option developed at CEREA, was used to carry out the simulations. The vegetation composed of tall trees is considered as a porous volume which induces a drag force to the air flowing through it. The pollutants of the local traffic emissions are considered as passive scalars (no chemical reaction). The global meteorology, including stratification conditions, is taken into account using boundary conditions obtained from mesoscale simulations performed over the region, with a zoom over the city by the Meso-NH code and the TEB urban parameterization. The simulation results of the air flow and pollution dispersion are compared with measurements obtained with fixed stations especially set up in the area during the campaigns. A good agreement is found between the measurements and simulations in terms of wind velocity and air temperature. For the wind direction the agreement is only fair with a Mean Bias of nearly 25 degrees but nevertheless we find a good agreement with the NOx concentration time series at a local measuring station inside the neighborhood. This good agreement is explained partly by the adjustment of the unknown local emission factor but also by the configuration of the ring road surrounding in part the neighborhood, making it less sensitive to wind direction errors. Two urban renewal scenarios proposed by architects and local inhabitants are simulated under the same meteorological conditions. Increasing the height of anti-noise walls (from 3 to 6 m) does not improve the neighborhood air quality (except very locally) and the suppression of a big building block next to the ring road has a mixed effect, displacing the pollution (concentration increased in some area, decreased in some others). (c) 2016 Elsevier B.V. All rights reserved.

Atmospheric dispersion modelling requires meteorological inputs over local domains with possibly complex topographies. These local wind fields may be difficult to simulate with CFD models, in particular because of their sensitivity to geometrical features and to model inputs, especially the boundary conditions which are generally provided by larger-scale models or measurements. Using data assimilation, a few measurements inside the domain could add information to the imprecise boundary conditions and thus greatly enhance the precision of the dispersion simulations. Three data assimilation techniques (3DVar, the back and forth nudging algorithm, and the iterative ensemble Kalman smoother) have been adapted to local scale simulations by taking boundary conditions into account instead of initial conditions for which they are usually applied. Their performances have been evaluated at small scales, with a simple representation of the atmosphere into two layers, using 1D solution of the shallow-water equations.

Polydisperse evaporating spray study is complex due to the influence of a large number of physical parameters. Several studies have performed CFD simulations to investigate the cooling performance of water spray systems, but a few have investigated their impact upon heat exchangers. For industrial applications, developing a new and simple approach to simulate polydisperse evaporating sprays upon complex 3D geometries is of great interest. Thus this paper is the first contribution to a CFI) numerical tool development to study water spray impact on heat exchangers and presents a CFD water spray model. The spray model is divided into two steps: the spray formation and its dispersion in air flow. The spray development step describes the moment from droplet injection to the position where droplet velocity equals air velocity. This position and the spray dimension are accessed through the droplet trajectory analysis, while the amount of liquid water evaporated is obtained by integrating the droplet size decrease equation. This first part provides boundary conditions for the second step used in a 3D CFD software: CodeSaturne. This CFD code solves the Navier-Stokes equations for the spray with the k-epsilon turbulence model. Three transport variables are introduced: the liquid potential temperature, theta(L), the total water specific humidity, q(w) which are conservative variables for the evaporation processes; and the total number, of droplets, N-c. The droplet evaporation is added to the N-c equation through a source term approach. A lognormal law is also used to represent and follow the evolution of the droplet spectra. The model results are compared with experimental results from droplets injected in counter-flow configurations in a wind tunnel. Temperature fields show good agreements with the experimental data. Finally, this paper provides a parametric analysis of water evaporation and air cooling upon a specified surface. The impacts of the relative humidity, spray angle, water mass flow rate and droplet size distribution are investigated. Our approach is an alternative to classical Lagrangian approaches used in spray applications. It provides accurate and consistent results with low computational time in comparison with the literature.