Aerodynamic effects of trees on pollutant concentration in street canyons

Science of the Total Environment 407 (2009) 5247–5256

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Science of the Total Environment j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s c i t o t e n v

Aerodynamic effects of trees on pollutant concentration in street canyons Riccardo Buccolieri a,b,⁎, Christof Gromke c,d, Silvana Di Sabatino a, Bodo Ruck d a

Dipartimento di Scienza dei Materiali, Universiy of Salento, Via Monteroni, 73100 Lecce, Italy Dipartimento di Chimica, University of Bari, Via E. Orabona 4, 70126 Bari, Italy c WSL Institute for Snow and Avalanche Research SLF, Flueelastr. 11, 7260 Davos Dorf, Switzerland d Laboratory of Building- and Environmental Aerodynamics, Institute for Hydromechanics, University of Karlsruhe, Kaiserstr. 12, 76128 Karlsruhe, Germany b

a r t i c l e

i n f o

Article history: Received 21 March 2009 Received in revised form 15 June 2009 Accepted 18 June 2009 Available online 10 July 2009 Keywords: Street canyon Tree planting Crown porosity Traffic pollutant concentration Wind tunnel and CFD

a b s t r a c t This paper deals with aerodynamic effects of avenue-like tree planting on flow and traffic-originated pollutant dispersion in urban street canyons by means of wind tunnel experiments and numerical simulations. Several parameters affecting pedestrian level concentration are investigated, namely plant morphology, positioning and arrangement. We extend our previous work in this novel aspect of research to new configurations which comprise tree planting of different crown porosity and stand density, planted in two rows within a canyon of street width to building height ratio W/H = 2 with perpendicular approaching wind. Sulfur hexafluoride was used as tracer gas to model the traffic emissions. Complementary to wind tunnel experiments, 3D numerical simulations were performed with the Computational Fluid Dynamics (CFD) code FLUENT™ using a Reynolds Stress turbulence closure for flow and the advection–diffusion method for concentration calculations. In the presence of trees, both measurements and simulations showed considerable larger pollutant concentrations near the leeward wall and slightly lower concentrations near the windward wall in comparison with the tree-less case. Tree stand density and crown porosity were found to be of minor importance in affecting pollutant concentration. On the other hand, the analysis indicated that W/H is a more crucial parameter. The larger the value of W/H the smaller is the effect of trees on pedestrian level concentration regardless of tree morphology and arrangement. A preliminary analysis of approaching flow velocities showed that at low wind speed the effect of trees on concentrations is worst than at higher speed. The investigations carried out in this work allowed us to set up an appropriate CFD modelling methodology for the study of the aerodynamic effects of tree planting in street canyons. The results obtained can be used by city planners for the design of tree planting in the urban environment with regard to air quality issues. © 2009 Elsevier B.V. All rights reserved.

1. Introduction Air quality is a major concern for people living in urban areas. Buildings act as artificial obstacles to the wind flow and may cause stagnant conditions within the city, even for relatively high velocity approaching flow. Traffic emissions commonly constitute the major source for air pollution in cities and have large impact on the health of city population. In the last years, there has been an increasing development of suitable atmospheric dispersion models for urban air quality management (Vardoulakis et al., 2003; Holmes and Morawska, 2006). At the micro-scale, a full Computational Fluid Dynamics (CFD) model is the preferred way of investigation (Britter and Hanna, 2003; Britter and Schatzman, 2007). CFD has become an attractive tool to predict

⁎ Corresponding author. Dipartimento di Scienza dei Materiali, University of Salento, Via Monteroni, 73100 Lecce, Italy. Tel.: +39 0832 297 115; fax: +39 0832 297 100. E-mail address: [email protected] (R. Buccolieri). 0048-9697/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.scitotenv.2009.06.016

concentration fields near buildings as it allows to consider the effect of complex building arrangements and shapes, but it can be extremely demanding in computational resources. Although flow and pollutant dispersion in street canyons are influenced by the interaction of various objects, in most of the previous experiments and CFD simulations only the influence of building geometry has been considered. Overviews on this topic are given in reviews by Li et al. (2006) and Vardoulakis et al. (2003) which summarize recent progress and advancements in CFD modelling of wind field and pollutant transport in street canyons. These papers underlined benefits and deficiencies of different approaches when applied to wind flow and concentration simulations. They concluded that the current status of CFD modelling is far from meeting the great needs of assessing and monitoring air quality and much work has to be done in the research community. More recent studies analysed the role of parameters affecting flow and dispersion, such as building geometry, street dimensions, wind direction (e.g. Di Sabatino et al., 2008; McNabola et al., 2009), building packing density (e.g. Di Sabatino et al., 2007), thermal stratification (e.g. Baik et al., 2007;

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Kang et al., 2008), vehicular movement (e.g. Kumar et al., 2008; Solazzo et al., 2007) etc. However, up to now limited work has been done to check the performance of CFD models for routine air pollution studies and at present there is still no standardization of modelling practise for atmospheric applications. This is part of the research performed within the COST Action 732. Quality assurance and improvement of micro-scale meteorological models. http://www. mi.uni-hamburg.de/Home.484.0.html (2005−2009). In urban areas, tree planting plays an important role which may be of botanical or aesthetic significance or have environmental value. Tree planting may also define and contribute to the character of a city. Vegetation is a major parameter in urban environmental quality for outdoor thermal comfort, temperature control due to evapotranspiration and shading, the filtering and recycling of pollutants and as urban wildlife habitats etc. (see e.g. Akbari et al., 2003). However, when the focus is on pollutant concentrations at pedestrian level (which corresponds to about 1 to 2 m above the ground), the obstruction effect of vegetation to the wind leads to reduced ventilation and dilution of pollutants which needs to be quantified. This can be done either by means of laboratory experiments or numerical investigations. Several vegetation canopy models proposed for the study of aerodynamic effects of trees can be found in literature. Mochida et al. (2008) and Mochida and Lun (2008) reviewed recent achievements in the field of canopy flows modeling the presence of trees. Overall, those studies emphasized that the aerodynamic effects of trees is to decrease wind velocity and to increase turbulence. On the other hand, the impact of trees in street canyons on pollutant dispersion has been far less considered (Gross, 1987; Ries and Eichhorn, 2001; Gromke and Ruck, 2007; Gromke et al., 2008; Gromke and Ruck, 2009; Litschke and Kuttler, 2008; Balczó et al., 2009). Litschke and Kuttler (2008) reported on field studies, numerical and physical modelling of filtration performance of plants with respect to atmospheric dust. The intention of this review was tailored to assess the extent to which a reduction in particle concentration can be accomplished by existing vegetation or targeted planting. They underlined that the deposition of particles on plant surfaces is influenced by a variety of factors. Among them, the diameter and shape of the particles, the planting configuration and the meteorological parameters, such as relative humidity of air, wind speed and turbulence, play an important role on deposition velocity and filtration performance. Although particle deposition on plant surfaces corresponds to particle removal from the air and therefore to the reduction of pollutant concentration, it must also be noted that plants themselves represent obstacles to air flow which can reduce air exchange compared with tree-less areas. The reduction in pollutant concentration through deposition must therefore be set off against this contrary effect, which tends to increase pollutant concentration as found by Gromke and Ruck (2007, 2009). They investigated the aerodynamic impact of tree planting in several street canyon configurations by means of wind tunnel studies. For perpendicular approaching flow, they reported moderate to strong increases in pollutant concentrations at the leeward wall and slight decreases at the windward wall in comparison to the tree-less configuration due to modification of air exchange and entrainment conditions inside the canyon. For more details and download of the wind tunnel measurement results, see the internet database CODASC (Concentration Data of Street Canyons) (CODASC. Concentration Data of Street Canyon, internet database, http://www.codasc.de, 2008). Parts of the above mentioned wind tunnel studies were numerically reproduced in our recent study (Gromke et al., 2008), where we investigated flow fields and dispersion in an urban street canyon of aspect ratio W/H = 1 (with W the street width and H the building height) by means of the commercial CFD code FLUENT (Fluent V6.3 User's Manual. http:// www.fluent.com, 2006). The overall scope of this paper is to analyse aerodynamic effects of tree planting on pollutant concentration in idealized street canyons

following the procedure set up in Gromke et al. (2008). We focus on different street canyon/tree planting configurations by means of both wind tunnel experiments and numerical simulations. It is known that wind tunnel experiments provide data usually for a limited number of measurement locations. This limitation can be compensated by numerical simulations which may be used to obtain flow and concentration fields in detailed locations according to the specific task. In this study, numerical simulations were performed by using the CFD code FLUENT. A Reynolds Stress Model (RSM) model (Launder et al., 1975) was preferred to the standard k–ε model (Launder and Spalding, 1974) which was inadequate for this application (Gromke et al., 2008). Among all the tree parameters, crown porosity, tree positioning and arrangement are identified as the major elements affecting pedestrian level pollutant concentrations in street canyons. The variation of these parameters also allows to meet the increasing city planning requirements concerning the optimum tree configurations that maximise air quality and pedestrian comfort. At first, analyses are performed in a street canyon of aspect ratio W/H = 2. Results are also compared with those of previous investigations by Gromke et al. (2008) to obtain a first conclusion on the effect of street canyon aspect ratios on pedestrian level pollutant concentration. Finally, we also studied the effect of variations in the approaching mean wind speed with the aim of generalising our results to different urban flow conditions. The analysis of the aerodynamic effects of tree planting and the methodology set up in the present paper can be used to improve urban planning for preventing further air pollution and diminishing exposure and enhance people's comfort. 2. Methodology Both wind tunnel experiments and 3D CFD simulations were carried out to analyse the role of crown porosity and stand density of trees in affecting pollutant dispersion in street canyons. In this study we consider trees as porous obstacles. Depending on the porosity, a pressure loss coefficient was identified in order to characterize the aerodynamic effect of tree planting and to model the porous crown media in the CFD simulations. The role of plant physiology (filtration, deposition etc.) is left to future work. 2.1. Description of wind tunnel setup and measurements The wind tunnel model (scale 1:150) consists of two parallel aligned rows of houses forming an isolated urban street canyon of length L = 180 m, height H = 18 m and street width W = 36 m (Fig. 1a,b). Tree models of different crown porosities were placed in two rows on both sides of the street (Fig. 1b,c). A boundary layer flow approaching perpendicular to the street axis with mean velocity profile exponent α = 0.30 and turbulence intensity profile exponent αI = − 0.36 according to the power law formulation were reproduced: uðzÞ = uH




α

z

ð1Þ

zref

Iu ðzÞ = Iu ðzref Þ




z

zref

−α

I

ð2Þ

In the present investigations, a flow velocity of uH = 4.70 m/s at building height H was set-up. The Reynolds number Re, calculated by using the building height and the above velocity uH, was equal to 37,000 and ensured a Reynolds number independent flow. For more comprehensive information on the simulated atmospheric boundary layer flow, including data on the integral length scale profile Lux(z) and spectral distributions of turbulent kinetic energy Suu(z,f), see Gromke and Ruck (2005).

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Fig. 1. a) Sketch of the street canyon model. b) Image of the street canyon with tree planting. c) Tree crown cross-sections and line sources positions. d) Positions of measurement taps at canyon walls (from CODASC, 2008).

Four tracer gas emitting line sources (Fig. 1a,c) were embedded at street level for simulating the release of traffic exhausts following Meroney et al. (1996). In this approach, tracer gas was streaming in a line-like chamber mounted below the model setup with openings facing the street side. The line source emission homogeneity was assured by small, equidistantly spaced openings with a high pressure drop, making the tracer gas release independent of local and instantaneous pressure fluctuations at street level. In order to account for the traffic exhausts released on the sidewise street intersections, the line source exceeded the street canyon by approximately 10% on each side. The line source strength was monitored and controlled by a flow meter, ensuring a constant tracer gas supply during the measurements. Sulfur hexafluoride (SF6) was used as tracer gas to model the traffic emissions. Measurement taps were applied along the leeward and windward canyon walls (wall A and wall B, respectively) to sample the nearfaçade canyon air. Taps were positioned a few millimetres away from the wall corresponding to 0.75 m in full scale. In detail the taps were arranged on a grid layout in the z and y directions at two fixed locations x/H = − 0.46 in front of wall A and x/H = +0.46 in front of wall B as shown in Fig. 1d. These were chosen as they are considered suitable to evaluate pedestrian exposure. The total number of measurement points were 98 that is 49 at each wall. Table 1 reports vertical (along the z direction) and horizontal (along the y direction) normalised positions of measurement taps. The samples were analyzed by Electron Capture Detection (ECD) yielding mean concentrations and normalized according to: þ

c =

cuH H QT = l

ð3Þ

with c the measured concentration and QT/l tracer gas source strength per unit length of the line source.

The modelling of porous tree crowns was derived from the approach undertaken in Gromke and Ruck (2008) and Gromke and Ruck (2009). Porous tree crowns were realized using custom-made lattice cages forming cubes with cross-sections of 0.42H (7.56 m) width and 0.67H (12.06 m) height (Fig. 1c). These lattice cages were aligned symmetrically along the street axis with the top edge facing the roof level. Spanning the street canyon of length L, the cage was divided into 31 cells, each of 0.32H depth. A filament/fibre-like synthetic wadding material was used to fill the cells, whose purpose was to facilitate a uniform distribution of the wadding material throughout the entire length of the lattice cage. Different crown porosities were realised by filling all cells homogeneously with defined masses of wadding material. Pore volume fractions of PVol = 97.5% (loosely filled) and PVol = 96% (densely filled), typical for crown porosities of deciduous trees were modelled (Gross, 1987; Zhou et al., 2002). In this way, avenue-like planting of high and low stand densities, i.e. with interfering neighbouring tree crowns (Fig. 1b) and with trees separated by 0.32H (5.72 m) in between (Fig. 2), respectively, were modelled. The height of the branch free trunk was 1/3H (6 m) in all cases.

Table 1 Positions of measurement taps. Measurement tap Vertical position z/H Measurement tap Horizontal position y/H A-y-1/B-y-1 A-y-2/B-y-2 A-y-3/B-y-3 A-y-4/B-y-4 A-y-5/B-y-5 A-y-6/B-y-6 A-y-7/B-y-7

0.08 0.17 0.25 0.33 0.50 0.67 0.83

A-1-z/B-1-z A-2-z/B-2-z A-3-z/B-3-z A-4-z/B-4-z A-5-z/B-5-z A-6-z/B-6-z A-7-z/B-7-z

−5.00 − 3.75 − 1.25 0.00 1.25 3.75 5.00

y and z refer to the horizontal and vertical positions at wall A and wall B.

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Fig. 2. Street canyon with low stand density tree planting (from CODASC, 2008). Positions of sources and measurement taps are shown in Fig. 1.

In order to describe the aerodynamic characteristics of the realized tree models which are determined by crown porosity, internal crown structure and surface properties of the wadding material, the pressure loss coefficient λ [m− 1] was determined in forced convection conditions, according to: λ=

Δpstat p −pleeward = windward pdyn d ð1 = 2Þρu2 d

ð4Þ

with Δpstat the difference in static pressure windward and leeward of the porous obstacle in forced convection conditions, pdyn the dynamic pressure, u the mean stream velocity and d the porous obstacle thickness in streamwise direction. Measurements resulted in pressure loss coefficients of λ = 80 m− 1 and λ = 200 m− 1 for the loosely (PVol = 97.5%) and densely (PVol = 96%) filled model crowns, respectively. Table 2 summarizes all tree planting configurations investigated in the present work. 2.2. Description of FLUENT modelling 2.2.1. General flow and dispersion setup 3D simulations were performed by means of the CFD code FLUENT with the aim of reproducing the above described wind tunnel experiments focusing on fluid dynamics aspects of the effect of trees on pollutant concentration in street canyons. The computational domain was built using hexahedral elements with a finer resolution close to the ground and in those regions with large gradients. Several tests were performed to verify grid size independence with increasing number of mesh cells until further refinements gave no significant improvements. The final number of the computational cells used for all simulations was about 400,000. The smallest dimensions of the elements were δxmin = 0.04H, δymin = 0.2H, δzmin = 0.04H in the Table 2 Tree planting configurations within the street canyon of aspect ratio W/H = 2. −1

PVol (%) λ (m

region near the release and near the ground (similarly to what used in Gromke et al., 2008). The distance from the inlet plane to the first building of the street canyon is 8H, the distance from the top of the domain to the building roof is 7H and the distance from the outflow plane to the downstream building is 30H. Thus, the requirements at the computational domain size to allow for full flow development as stated in COST Action 732 are satisfied. Based on our previous investigations (Gromke et al., 2008), the RSM model was used as the preferred turbulence model. The inlet wind speed was assumed to follow a power law profile with a profile exponent α = 0.30 as in wind tunnel experiments. Turbulent kinetic energy and dissipation rate profiles were specified as follows: u2*  z ffi 1− k = qffiffiffiffiffi δ Cμ

&

ε=

u3*  z 1− δ κz

ð5Þ

where δ is the boundary layer depth, u⁎ = 0.52 m/s the friction velocity, κ the von Kàrmàn constant (0.40) and Cμ = 0.09. Symmetry boundary conditions were specified on the top (to enforce a parallel flow) and lateral sides of the computational domain. At the boundary downwind of the obstacles, where the fluid leaves the computational domain, an outflow boundary condition was used to force all derivatives of the flow variables to vanish, corresponding to a fully developed flow. Second order upwind discretization schemes (Barth and Jespersen, 1989) were used for pressure, momentum, k and ε to increase the accuracy and reduce numerical diffusion. The SIMPLE scheme was used for the pressure–velocity coupling. FLUENT uses an iterative method to solve the algebraic system of equations. A termination criterion of 10− 6 was used for all field variables. For dispersion calculations, the advection diffusion (AD) module was used. In turbulent flows, FLUENT computes the mass diffusion as follows:
 μ J = − ρD + t ∇Y Sct

ð6Þ

) Distance between trees (m)

Tree-less street canyon Empty; reference case High crown porosity (loosely filled) 97.5 80 High stand density Interfering tree crowns Low stand density 5.76 m Low crown porosity (densely filled) 96 200 High stand density Interfering tree crowns Low stand density 5.76 m The height of the branch free trunk was 6 m in all cases.

where D is the molecular diffusion coefficient for the pollutant in the mixture, μ t the turbulent viscosity, Y the mass fraction of the pollutant, ρ the mixture density. Sct = μ t / (ρDt) is the turbulent Schmidt number and Dt the turbulent diffusivity. Based on a sensitivity analysis on the effect of the turbulent Schmidt number on pollutant concentration (Gromke et al., 2008), the standard value Sct = 0.7 was used for dispersion simulations.

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across the porous medium interface. This was used in our simulations. As a more accurate alternative, one can instruct FLUENT to use the true (physical) velocity inside the porous medium. • The effect of the porous medium on the turbulence field is only approximated. In detail, porous media are modelled by the addition of a momentum source term to the standard fluid flow equations. The source term is composed of two parts: a viscous loss term (Darcy, the first term on the right-hand side of Eq. (7)) and an inertial loss term (the second term on the right-hand side of Eq. (7)): 3 3 1 Si = − ∑ Dij μvj + ∑ Cij ρjv jvj 2 j=1 j=1

Fig. 3. Tree-less street canyon. a) Measured concentrations. b) Calculated concentrations (left side) with relative deviations (%) in respect of measurements (right side).

2.2.2. Modelling of tree crowns Tree crowns were modelled employing the FLUENT porous media conditions by assigning the pressure loss coefficient λ to those cells occupied by the crown. The porous media model incorporates an empirically determined flow resistance in a region of the computational domain defined as porous. In essence, the porous media model is nothing more than an added momentum sink in the governing momentum. As such, the following modelling assumptions should be recognized: • FLUENT uses a superficial velocity inside the porous medium based on the volumetric flow rate to ensure continuity of the mass flow

! ð7Þ

where Si is the source term for the ith (x, y, or z) momentum equation, |v| is the magnitude of the velocity and D and C are prescribed matrices. This momentum sink contributes to the pressure gradient in the porous cell, creating a pressure drop that is proportional to the fluid velocity (or velocity squared) in the cell. FLUENT, by default, solves the standard transport equations for turbulence quantities (i.e. in our case the Reynolds stresses) in the porous medium. In this default approach, turbulence in the medium is treated as though the porous medium has no effect on the turbulence generation or dissipation rates. To model tree planting, additional source terms were assigned to cells occupied by vegetation, such that the pressure loss coefficients λ of the wind tunnel model trees was matched. 3. Results 3.1. Reference case: tree-less street canyon In a first step, pollutant dispersion in a tree-less street canyon is investigated. When referring to “wall A” and “wall B”, we remind that concentrations were measured a few millimetres away from wall A and wall B as described in Section 2.1. Fig. 3a shows measured pollutant concentrations at the canyon walls. At the leeward wall A pollutant

Fig. 4. Tree-less street canyon, vectors of wind velocity magnitude (normalized by uH) obtained from CFD simulations. a) Vortex structure near the street canyon centre (y/H = 0.5), b) Flow pattern at z/H = 0.5.

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concentrations are about 3 times larger than at the windward wall B. Moreover, concentration decreases from the centre to the street ends at both walls are found. For the purpose of the comparison of the overall variations in concentrations, we averaged both measured and calculated concentrations at walls A and B according to: 1 þ ∫ c dydz areaXw areaXw

As wind velocity measurements are not available, data are interpreted using flow fields obtained from numerical simulations. The ventilation is quantified by calculating the normalized flow rate (see for instance Hang et al., 2009) through the street canyon ends and the roof level defined as: → ∫ V⋅→ ndA

ð8Þ

where area_w is the area of wall A or wall B. The normalized experimental wall-averaged concentrations are 14.8 and 5.2 at walls A and B, respectively.

q=

A

uH Atot

ð9Þ

→ where V is the velocity vector, → n is the normal direction of street canyon side or the street top (positive pointing outward), A is the area of street

Fig. 5. TKE (normalized by u2H) at y/H = 0.5 (a) and at z/H = 0.5 (b) for tree-less street canyon and for street canyon with tree planting of high crown porosity (c, d).

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side or street top and Atot the total area given by 2WH+WL. The normalized flow rate through the street roof level is +0.018 and that through each sidewise end is −0.009. This means that air leaves the street through the street roof level, while it enters through the sides (Fig. 4). Larger concentrations at the leeward wall can be understood by looking at the dominating vortex structure in the street canyon centre shown in Fig. 4a that transports pollutant towards the leeward side. The effect of concentration decrease towards the street ends can be explained by the enhanced natural ventilation at the street canyon ends, where both vertical and lateral exchanges shown by vectors in Fig. 4b are present and quantified by the flow rates discussed above. Fig. 5a,b shows contours of the normalized Turbulent Kinetic Energy (TKE/u2H) in the street canyon. Large values of TKE are found near the street roof level due to a combination of large production by strong wind shear and TKE advection in this region. In the single vortex regime shown in Fig. 4a, TKE increases towards the upper part of the street canyon in the shear layer region created by the interaction of the canyon vortex and the above roof flow. In the horizontal plane at z/H = 0.5, TKE increases towards the street ends are found due to the shear between the corner eddies and outer canyon flow. The comparison between FLUENT and wind tunnel concentrations in Fig. 3b shows that the overall FLUENT concentrations are similar to those obtained in the wind tunnel, even if there is a slight underestimation of the measured concentrations at wall A. This is also reflected by the normalized wall-averaged concentrations (12.1 at wall A and 5.4 at wall B). It should be noted that the largest relative deviations in concentration at wall A of about 40 to 60% (Fig. 3b) occur at the canyon ends where the absolute pollutant concentration is smallest (Fig. 3a). Consequently, only little differences in absolute concentrations resulting from measurements and numerical simulations are present. At wall B, negative as well as positive relative deviations in concentrations in the range of −20 to 10% are found. With respect to the low concentrations, a good agreement between numerical and experimental absolute concentrations is given.

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3.2. Street canyon with tree planting of high crown porosity (PVol = 97.5%, λ = 80 m− 1) 3.2.1. Tree planting of high stand density As in the tree-less reference case, FLUENT simulations show downward and upward directed flows in front of the windward and leeward wall, respectively. The flow near the centre part of the street canyon is still dominated by a vortex or vortex-like structure (Fig. 6). Slightly smaller flow velocities in the upward but significantly lower velocities in the downward moving part are found when compared to the tree-less street canyon (Fig. 4). In this case, flow rates through the street roof level, +0.014, and sidewise ends, −0.007, are reduced by about 25% with respect to the tree-less canyon. The TKE distribution shown in Fig. 5c,d is similar to that found in reference case and shown in Fig. 5a,b. However, some discrepancies exist due to the presence of trees. In fact, as suggested by the smaller velocities as discussed above, also lower values of TKE are observed inside the canyon close to the leeward wall. Tree planting inside the street canyon do not yield to an increased production of TKE as might be expected because of additional shear layers resulting from the air flowing through the porous vegetation. The implications of these differences in velocity and TKE on pollutant concentration are shown in Fig. 7. In comparison to the reference street canyon (Fig. 3), increases in concentrations at wall A and decreases at wall B are found in the wind tunnel measurements, but the pattern of pollutant concentration distribution remains overall unchanged (Fig. 7a). The normalized wall-averaged concentration at wall A is 20.7 and at wall B is 3.9. Maximum concentrations are present at pedestrian level at wall A. The pollutants released at ground level are in fact advected towards the leeward wall A, but, since the circulating fluid mass is reduced in the presence of tree planting, the concentrations in the uprising part of the canyon vortex in front of wall A are larger. Differently to the tree-less case, the direct transport of pollutants from wall A to wall B is hindered by the tree crowns. The uprising canyon vortex is intruded into the flow above the roof level more directly, where it is diluted

Fig. 6. Street canyon with tree planting of high crown porosity, vectors of wind velocity magnitude. Vortex-like structure near the street canyon centre (y/H = 0.5) (a) and flow pattern at z/H = 0.5 (b) obtained from CFD simulations.

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and 4.8 at wall B) show a slight underestimation in respect to experimental data at the leeward wall. Overall, the relative deviations between the numerical simulations and the wind tunnel measurements are of the same order as before at the tree-less street canyon. 3.3. Street canyon with tree planting of low crown porosity (PVol = 96%, λ = 200 m− 1)

Fig. 7. Street canyon with tree planting of high crown porosity and high stand density. a) Measured concentrations (left side) with relative deviations in respect of tree-less street canyon (right side). b) Calculated concentrations (left side) with relative deviations in respect of measurements (right side).

before partially re-entrained into the canyon. As a consequence, lower traffic exhaust concentrations are present at wall B. FLUENT simulations were successful in predicting an increase in concentrations at wall A and an overall decrease near wall B (Fig. 7b). They were also successful in predicting the relative deviations in respect of the tree-less street canyon. However, from the normalized wall-averaged traffic pollutant concentrations (15.8 at wall A and 4.3 at wall B) we note that, as in the tree-less case, FLUENT slightly underestimated experimental data at the leeward wall. Overall, the relative deviations between the numerical simulations and the wind tunnel measurements are of the same order as before at the tree-less street canyon.

3.3.1. Tree planting of high and low stand FLUENT velocity patterns (not shown here) of downward and upward directed flow in front of the windward and leeward walls generally remain unaltered and only marginal changes can be noticed in comparison to the tree planting of high crown porosity (Figs. 5 and 6). This is due to the fact that the degree of crown porosity is of minor relevance for flow and dispersion processes inside the street canyon as the tree planting is arranged in a sheltered position with wind speeds being relatively small. This is also confirmed by the flow rates of the high stand density planting with +0.012 and − 0.006 through the roof level and the sides, respectively (+0.014 and − 0.007 for high crown porosity). This is in agreement with previous results from Gromke and Ruck (2009), who showed a similar impact of a tree planting with low crown porosity (PVol = 96%) and an impermeable model tree crown (PVol = 0%), on the flow and concentration fields inside an urban street canyon. The minor impact of crown porosity is also reflected in the concentration plots of Fig. 9. When compared to the concentrations found in the street canyon with the tree planting of high crown porosity (Figs. 7 and 8), no considerable changes can be found, neither in the experimental results nor in the numerical simulations.

3.2.2. Tree planting of low stand density Tree planting in street canyons consist also of trees arranged at a certain distance. With the aim of clarifying the effect of tree arrangement in mind, we considered a further tree planting configuration by investigating the case shown in Fig. 2. Both qualitative and quantitative similar increases in concentrations at wall A and decreases at wall B in respect to the high stand density configuration were found from experimental results as shown in Fig. 8. Looking at the figure it is evident that the pattern of pollutant concentration distribution remains overall unchanged and wall-averaged traffic pollutant concentration at wall A is 20.0 and at wall B is 4.1. These trends were also found in FLUENT simulations, which predicted an increase in concentrations at wall A and an overall decrease at wall B. Again, the normalized wall-averaged concentrations (16.0 at wall A

Fig. 8. Street canyon with tree planting of high crown porosity and low stand density (experimental results).

Fig. 9. Street canyon with tree planting of low crown porosity — a) high stand density, measured concentrations (left side) with relative deviations in respect of tree-less street canyon (right side). b) High stand density, calculated concentrations (left side) with relative deviations in respect of measurements (right side). c) Low stand density (experimental results).

R. Buccolieri et al. / Science of the Total Environment 407 (2009) 5247–5256 Table 3 Results of statistical analysis with BOOT.

Tree-less street canyon High crown porosity (loosely filled) High stand density Low stand density Low crown porosity (densely filled) High stand density Low stand density

NMSE

R

FAC2

FB

0.06

0.96

0.97

0.15

0.13 0.09

0.98 0.98

1.00 0.99

0.21 0.16

0.09 0.07

0.99 0.99

1.00 1.00

0.14 0.13

3.4. Statistical analysis Contour plots of relative deviations in concentrations (Figs. 3, 7 and 9) show maximum differences of − 60 to +60% between experimental and numerical results. Pollutant concentrations at the leeward wall were slightly underestimated in the numerical simulations, while at the windward wall both slightly over- and underestimations were present. Several statistical methods were used to quantify numerical model performance. In particular we calculated for all simulations the normalized mean square error (NMSE), the correlation coefficient (R), the fraction of predictions within a factor of two of observations (FAC2) and the fractional bias (FB) (Chang and Hanna, 2004). Recommendations for model acceptance criteria have been summarized and are given by: NMSE ≤ 4; FAC2 ≥ 0.5; −0.3 ≤ FB ≤ 0.3. All statistical measures are within the accepted values for satisfactory model performance (Table 3). 4. Discussion Experimental as well as numerical results showed that the incanyon air quality can be significantly altered by avenue-like tree planting. In all cases considered, tree planting lead to a large increase in pollutant concentrations within the street canyon when compared to the tree-less case. In particular, significant increases at the leeward wall and slight to moderate decreases at the windward wall were found. Concentration results of this study are in general agreement with previous experimental and numerical investigations summarized in the Introduction section. The analysis carried out in this paper shows that the degree of crown porosity and stand density are not crucial factors in affecting wall-average concentrations inside the street canyon. As underlined in the experimental study of Gromke and Ruck (2009), when the pore volume fraction falls below a certain threshold, no further changes in pollutant concentrations are observed. Moreover, the maximum concentrations in the canyon centre are not strongly affected as well. It is clear that concentration fields within street canyon depend crucially upon street canyon aspect ratios rather than on tree planting

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configuration. In fact, the dispersion study of aerodynamic effect of tree planting located in a single row along the axis of a street canyon of aspect ratio W/H = 1 (Gromke et al., 2008) showed that the overall level of pollutant concentrations was higher. This can be attributed to less ventilation, reduced dispersion and dilution. In order to better understand the influence of the aspect ratio, Fig. 10 shows relative deviations in wall-averaged concentrations for both W/H = 1 and W/H = 2 cases. Those deviations are expressed as ½ðCdense −Cref Þ × 100 = Cref , where Cdense is the wall-averaged measured concentration in the street canyon with tree planting of low crown porosity (and high stand density) and Cref is the wall-averaged measured concentration in the empty street canyon (reference case). From the figure, we note that overall the increase in concentration due to tree planting was lower in the W/H = 2 case. This result is due to the relative higher “blockage” effect caused by the trees in the W/H = 1 case. As a measure for the air masses rotating with the canyon vortex, we found that the flow rate through the horizontal plane z/H = 0.7 was reduced by 35% with respect to the tree-less canyon in the W/H = 2 case and by 72% in the W/H = 1 case. This means that relatively less air rotates inside the street canyon in the W/H = 1 case when tree planting is present. Overall, the analysis of flow rates in the W/H = 1 case shows that the presence of tree planting reduced the flow through the street top level and sidewise ends by 62%. This value is much larger than that found in the W/H = 2 case, where flow rates were reduced by 33% (see Section 3.3.1). For this reason, a wider street canyon with two parallel aligned rows of trees is the preferable configuration which should be taken into account by urban planners rather than a narrow street canyon with only a single row of trees. It should be noted that results presented in this work were obtained by considering a relative high wind velocity at canyon height (4.70 m/s). Sensitivity tests were also performed in the wind tunnel by using different values of uH ranging from 3 to 7 m/s. No changes in the normalized concentrations were found. In order to investigate the implication of wind velocity in calm situations and especially to apply the methodology set up in the present work to new cases not investigated in wind tunnel, preliminary 3D CFD simulations were performed by employing a wind velocity uH = 2 m/s. We considered the W/H = 2 reference case and the low crown porosity (and high stand density) case (see Fig.10). Due to small changes in the flow fields around and within street canyons, we found a relative deviation in wallaveraged concentrations equal to about +6% at the leeward side, while a very little decrease of about 2% was found at the windward side. Similarly to what was found in the aspect ratio sensitivity study, the analysis of flow rates showed that relatively less air rotates inside the street canyon with tree planting at lower wind speed. These preliminary results indicate that the effect of tree planting depends slightly on approaching wind velocity but it may be stronger in calm wind condition. Although a further analysis is required to better assess this aspect, the effect of trees in calm situations should be critically taken into

Fig. 10. Relative deviation (%) in wall-averaged measured concentrations at the leeward and windward for both W/H = 1 (Gromke et al., 2008) and W/H = 2 cases.

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account in urban planning. In this situation, for example, buoyancy may affect the dispersion of pollutants in the street canyon as the flow is significantly modified (Xie et al., 2007), leading to an extra accumulation of pollutants in a specific region. 5. Conclusions Flow and dispersion of traffic exhausts in urban street canyons of aspect ratio W/H = 2 with tree planting were investigated by means of wind tunnel experiments and CFD investigations. Several tree planting configurations were analysed in order to clarify the aerodynamic influence of stand density, crown porosity, street canyon aspect ratio and approaching wind velocity. Overall, this study confirms previous findings (Gromke and Ruck 2007, 2009; Gromke et al., 2008) that the in-canyon air quality can be significantly altered by avenue-like tree planting, with an increase at the leeward wall and a moderate pollutant concentration decrease near the windward wall. However, neither significant impacts of crown porosity nor of stand density on pollutant levels and distributions were found. On the other hand, the street canyon aspect ratio and the approaching wind velocity were found to be the most crucial parameters in affecting pollutant accumulation at pedestrian level. In particular, we found that for larger values of W/H the effect of trees on pedestrian level concentration is smaller. Moreover, at low wind speeds the effect of trees on traffic exhaust concentrations is slightly enhanced than at higher speeds. The methodology used in the present work, in particular the modelling approach for taking the effects of crown porosity into account by employing the porous media model in the RSM turbulence model, can be used to predict traffic-released pollutant concentrations inside street canyon with tree planting in an operational context. This study gives further evidence that the combination of experimental and numerical approaches in a novel aspect of research can provide a strategy for planning and re-development of urban areas taking into account the most suitable tree arrangement suitable for the considered city layout and local meteorology. Acknowledgements The authors wish to thank the Deutsche Forschungsgemeinschaft DFG for financial support of wind tunnel experiments by grant Ru 345/28. Thanks also go to three anonymous referees for carefully examining our paper and providing a number of important comments to improve it. References Akbari H, Shea Rose L, Haider T. Analyzing the land cover of an urban environment using high resolution orthophotos. Landscape and Urban Planning 2003;63:1-14. Baik JJ, Kang YS, Kim JJ. Modeling reactive pollutant dispersion in an urban street canyon. Atmospheric Environment 2007;41:934–49. Balczó M, Gromke C, Ruck B. Numerical modeling of flow and pollutant dispersion in street canyons with tree planting. Meteorologische Zeitschrift 2009;18:197–206. Barth TJ, Jespersen D. The design and application of upwind schemes on unstructured meshes. Technical Report AIAA-89-0366. In: AIAA 27th Aerospace Sciences Meeting, Reno, Nevada; 1989. Britter R, Hanna S. Flow and dispersion in urban areas. Ann. Rev. Fluid Mech. 2003;35: 469–96.

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