A review on the study of urban wind at the pedestrian level around buildings

1. Introduction

The socio-economic growth of a nation is majorly driven by urbanization, as it accommodates the increased demand for business and residential space. As an evidence of the current scenario, many cities of developed and developing nation like Japan, Hong-Kong, China, Malaysia, and India are moving towards the construction of cohesive skyline structures or mega tall buildings. On contrary to these advancements, mega tall buildings in the urban area affect the surrounding wind flow pattern and pedestrian level wind (PLW) comfort.

Presence of tall building in the urban area tends to deflect the upper-level high-speed wind to the ground, which creates conditions that could be unpleasant or even dangerous to pedestrians. There are many such incidents which are reported due to strong winds. But nowadays modern megacities are packed with the high density of high rise buildings, which influences the air movement. The reduced air movement at pedestrian level causes weak natural ventilationand allow the pollutants to be accumulated at ground level which increases air pollution. Such wind conditions are persistent in Hong Kong, Tokyo and New Delhi [1]. Many causalities have been reported due to the accumulation of air-borne SARS virus (Severe Acute Respiratory Syndrome) because of low wind speed zone at a building site in Hong Kong [2]. So it is inevitable to assess wind condition for pedestrian level comfort in the view of low wind speed as well as strong winds near buildings corners. Many urban authorities have made it is essential to study the pedestrian level wind environment for large urban projects during initial design stage [3], [4], [5], [6].

Initially, studies related to PLW speed measurement had been conducted with on-site field measurement. As it is not viable to conduct full-scale testing for the initial design of a building project site, so wind tunnel measurements on the scaled model make it feasible to investigate the effect of changes in building design at the initial stage of the urban project. During early days, wind tunnel measurement for PLWs was conducted with hot wire or film anemometry at limited measurement points [7], [8], [9], [10]. Later on, Irwin [11] devised a simple omni-direction probe for PLW speed measurement. In which pressure difference between tubes at scaled pedestrian height and surface of the tunnel is calibrated with the corresponding velocity. Recently the use of Irwin probes has been paced up due to the availability of high precision simultaneous pressure measuring sensor. Further, the use of sand erosion technique for such studies is limited as it provides qualitative information over the whole area under investigation [12]. There are other measuring techniques which have been used to evaluate PLW speed such as laser Doppler anemometry (LDA), particle image velocimetry PIV, Infrared thermography and thermistoranemometry.

Computational fluid dynamics (CFD) technique is also becoming a viable tool for PLW studies with the advent of high-performance computational resources. Till now steady Reynolds averaged Navier-Stokes (RANS) modelling approach was used successfully which requires less computing cost and time. But this technique is less accurate for predicting the flow in low wind speed region (deviation up to 5 times) as compared to other high-cost techniques such as LES and DES.

The present study comprehensively reviews the urban wind at the pedestrian level around buildings. The content of this paper is organized as follows: the second section presents the method for the assessment of PLW climate with different wind comfort criteria. The third section describes the different techniques to evaluate the pedestrian level winds. The fourth section reviews effect of the various parameter related to building design on PLW for generic building configuration. The last section presents different studies related to the actual urban environment, which comprises the effect of building design parameters and general guidelines for the urban planning in response to pedestrian comfort.

2. Assessment of PLW climate and comfort criterion

2.1. Method for assessment of PLW climate

The procedure for the assessment of favourable wind climate to pedestrians is comprised of (1) Statistical meteorological data of nearby weather station; (2) Aerodynamic information of the area and (3) Mechanical wind comfort criteria [13]. The aerodynamic information helps to compute the statistical data at particular building site obtained from the weather station. Then transformed data at this location is compared to wind comfort criterion. This procedure is schematically depicted in Fig. 1.

Meteorological data from weather station consist of hourly mean wind speed ( $U_{ms}$ , measured at 10 m height) and wind direction in open terrain ( $y_{0, meteo} = 0.03 m$ ). This wind speed data obtained from weather station is analyzed statistically using Weibull distribution function [14], [15], [16] to calculate the probability of exceedance of threshold wind speed as following Eq. (1).(1) $P (> U) = \exp [- {(\frac{U}{c})}^{k}]$ Where $P (> U)$ represents the exceedance probability of the wind speed; U is the mean wind velocity magnitude at building site; c is the dispersion parameter and k is the shape parameter. These constants are obtained by fitting Eq. (1) to the meteorological data. Then statistical information has to be transformed to the area of interest by the means of aerodynamic information using amplification factor R (Eq. (2)). This amplification factor consists of design related contribution and terrain related contribution (Eq. (3)) [16]. The design related contribution comprises of modification of statistical wind climate information due to local building design. These modification can be obtained by either wind tunnel measurement or using CFD simulation. The whole research community in this area is devoted to evaluate the design related modification. The terrain related modification accounts for the differences in terrain roughness between the weather station and area of interest [17] and can be obtained using Eq. (4) and Eq. (5).(2) $R = U / U_{ms}$ (3) $R = \frac{U}{U_{ms}} = \frac{U}{U_{0}} * \frac{U_{0}}{U_{ms}},$ (4) $\frac{U_{0}}{U_{ms}} = \frac{U_{site (at 1.75 m)}}{U_{meteo (at 10 m)}} = \frac{u_{site}^{*} . \ln (\frac{1.75 m}{y_{0, site}} + 1)}{u_{meteo}^{*} . \ln (\frac{10 m}{y_{0, meteo}} + 1)}$ (5) $\frac{u_{site}^{*}}{u_{meteo}^{*}} = {(\frac{y_{0, site}}{y_{0, meteo}})}^{0.0706}$ Where $U_{0}$ is the reference wind speed at certain distance upstream of area of interest or without the presence of building or at the inlet of computational domain; $u_{sit e}^{*}$ and $u_{meteo}^{*}$ are the friction velocity at building site and meteorological station respectively; $y_{0, site}$ and $y_{0, meteo}$ are the aerodynamic surface roughness length at building site and meteorological station respectively. The dependency of the probability of exceedance and amplification factor R is given by Eq. (6) [16].(6) $P (> U) = \exp [- {(\frac{U}{R * c})}^{k}]$

2.2. Wind comfort Criteria

In wind comfort assessment, besides the wind speed, the frequency of its occurrence also matters. Therefore the criteria for wind comfort involves threshold wind speed above which pedestrian will feel discomfort and its frequency of occurrence. A wide variety of wind comfort criterion, based on threshold mean wind speed and the probability of exceedance has been proposed earlier [14], [15], [18], [19], [20], [21], [22], [23]. Details of different wind comfort criterion are shown in Fig. 2, in which threshold mean wind speed (m/s) for different activities and its corresponding exceedance probability (%) is presented. Most of the criterion is based on the same probability of exceedance and different threshold wind speed for different pedestrian activities. While NEN 8100 [23] considers same threshold mean wind speed and different exceedance probability.

The comparison of different wind comfort criterion for different activities is shown in Fig. 2, in which typical wind climate for Indian city (Palam Airport, New Delhi) is represented. It can be identified that, based on comparison with mentioned wind comfort criteria except by Melbourne, (1978) [14], this place is vulnerable to high wind speed, which causes danger to pedestrians.

Since most of these criterion reports different threshold mean wind speed and exceedance probability, so it is difficult for developers, architects and planners to choose a general guideline on comfort criterion. With regard to this, various comparative assessments of wind comfort criteria have been proposed. Based on discussion with developers and building managers, Soligo et al. [20]converted the different wind comfort criteria on the same scale of frequency of occurrence (20%) or for a particular activity. Janssen et al. [24] also focused on the standardization of different wind comfort criterion.

However, all of the above-discussed criteria did not consider pedestrian discomfort due to weak wind conditions for the densely-built urban areas. Du et al. [25] proposed the wind comfort criteria for the urban areas of poor wind conditions such as Hong Kong, where the wind comfort becomes worst in hot and humid season. In this criterion overall mean velocity ratio (OMVR) is used as threshold parameter (Table 1), which represents the integration of direction values of mean velocity ratio ( ${MVR = U}_{P} / U_{r}$ ), Where $U_{P}$ is wind velocity at pedestrian level and $U_{r}$ is wind velocity measured at 200 m height.

Table 1. Wind comfort criteria based on overall mean velocity ratio (OMVR) representing weak wind conditions by [25].

Category	Threshold Velocity (Jun-Aug)	Threshold Velocity (Dec-Feb)	Exceedance Probability (%)	Activity	Remark
Unfavorable	$OMVR < \frac{1.5}{U_{r}}$		50	N/A	No Noticeable Wind
Acceptable	$OMVR < \frac{1.8}{U_{r}}$	$OMVR < \frac{1.8}{U_{r}}$	2	Sitting long	Light Breeze
	$OMVR < \frac{3.6}{U_{r}}$	$OMVR < \frac{3.6}{U_{r}}$	2	Sitting sort	Gentle Breeze
	$OMVR < \frac{5.3}{U_{r}}$	$OMVR < \frac{5.3}{U_{r}}$	2	Strolling	Moderate breeze
Tolerable	$OMVR < \frac{7.6}{U_{r}}$	$OMVR < \frac{7.6}{U_{r}}$	2	Walking fast	Fresh breeze
Intolerable	$OMVR > \frac{7.6}{U_{r}}$	$OMVR > \frac{7.6}{U_{r}}$	2	No suitable Activity	Strong breeze
Danger	$OMVR > \frac{15}{U_{r}}$	$OMVR > \frac{15}{U_{r}}$	0.05	Dangerous	Gale

3. Measurement techniques for pedestrian level wind speed

To obtain design related contribution for the assessment of pedestrian level wind environment, generally field measurement on the real urban environment, wind tunnel testing on the scaled model of the urban area and CFD simulation are employed. But to make changes in the early design stage, it is not possible to conduct field measurement for urban developmental projects. The following sections describe the details of each method and comparison based on the accuracy of each method.

3.1. Different measurement techniques

3.1.1. Field measurement techniques

This technique is regarded as a robust method to evaluate wind speed at limited points and was used successfully by several researchers [26], [27], [28], [29], [30]. Generally, a portable three cup-anemometer with wind vane system is used for this purpose. This instrument has very low onset-speed of 0.1 m/s and light in weight [28]. The output of this instrument is in the form of one electrical pulse per revolution of the rotor and this pulse rate is calibrated against the wind speed. A comparison of this technique with others is provided in the later section.

3.1.2. Wind tunnel techniques

In wind tunnel, the PLW measurements are conducted by using hot-wire/film anemometry (HWA, HFA), Irwin probes, thermistor anemometer, sand erosion, laser Doppler anemometry (LDA), infrared thermography, and particle image velocimetry (PIV). Each of the mentioned technique is based on different working principle and unique experimental setup. Since it is beyond the scope of this paper to discuss the working principle of each technique, only their application and capability is discussed in Table 2.

Table 2. Use of different wind tunnel measurement technique by various authors and their pros. and cons.

Measurement Technique	Authors	Comments
HWA	[7], [8], [9], [10], [12], [31], [32], [33]	Pros: High-frequency response and high spatial resolution.
HWA	[7], [8], [9], [10], [12], [31], [32], [33]	Cons: Intrusive technique, only suitable for moderate turbulence intensity, insensitive to directional changes [33], [34].
HFA	[7], [9], [13], [26], [35], [36], [37], [38]	Pros: less susceptible to fouling and fragility, easy to clean, shorter sensing length, The agreement between wind tunnel and full-scale measurement is within 10% [26].
HFA	[7], [9], [13], [26], [35], [36], [37], [38]	Cons: Intrusive technique, only suitable for moderate turbulence intensity, insensitive to direction changes.
LDA	[37], [39]	Pros: Non-intrusive point-wise technique, allows measurement of high-turbulence intensity and calibration is not required. [40]
LDA	[37], [39]	Cons: This technique is costlier than HFA and HWA.
Infrared thermography	[10], [32], [37]	Pros: Non-intrusive Area technique, RMS, peak and spectrum value can be measured [37]
Infrared thermography	[10], [32], [37]	Cons: Due to convection wind flow gets disturbed, sturdy and non-standard experimental set-up. No perfect correlation is obtained for temperature drop and wind speed [10]
PIV	[41], [42]	Pros: Non-intrusive area technique, high spatial resolution and directional sensitivity.
PIV	[41], [42]	Cons: Very expensive, sometimes dangerous, laser light shielding and reflection from buildings, not suitable for the cluster of buildings.
Erosion Technique	[12], [34], [42], [43], [44], [45]	Pros: Area technique, results are comparable to HWA for high wind speed [12]. For high turbulent flow, this technique agrees well with PIV measurements of mean wind speed [42].
Erosion Technique	[12], [34], [42], [43], [44], [45]	Cons: It is non-quantitative technique and difficult to ensure the repeatability.
Irwin Probes	[3], [46], [47], [48], [49], [50]	Pros: Allows measurements at numerous locations. No re-alignment for different wind direction. Simple in design and easy to operate [11].
Irwin Probes	[3], [46], [47], [48], [49], [50]	Cons: Less accurate for high turbulence intensity, it cannot accurately measure wind speed below 1.5 m/s [47].
Thermistor Anemometer	[51]	Pros: Small sensor size, susceptible to wind direction. The simple circuitry and low cost of thermistors make it economically feasible to operate the probes in large numbers.
Thermistor Anemometer	[51]	Cons: Only suitable for mean velocity measurements, fragile, require alignment for change in wind direction; nonlinear calibration of velocity.

3.1.3. CFD techniques for PLW speed

To simulate PLW environment, CFD methods are gaining much popularity among researchers and industrialists recently owing to the development of the computer hardware and software. One of the major advantages of CFD over wind tunnel testing is that it gives detailed flow field data of associated parameters over the entire computational domain. In addition, similarity law requirements associated with wind tunnel testing is not a limitation of CFD simulation. Most of the studies, to simulate wind environment are based on the use of different RANS turbulence models e.g. Std. $k - ε$ , Realizable $k - ε$ and RNG $k - ε$ model with default values of model closure coefficients in CFD tools. However, the major issue for the acceptance of CFD results is related to the accuracy, which suffers badly in predicting the flow on leeward side of building. Therefore CFD simulation results require verification and validation [40]. Zahid Iqbal et al. [2] mentioned that the simulation results for PLW speed obtained by std. $k - ε$ are also affected for different model closure coefficients.

The accuracy of CFD simulation largely depends on the selection of turbulence model. The capability of each turbulence model and their accuracy is discussed in Table 3.

Table 3. Use of different CFD technique by various authors and their pros. and cons.

Approximate Forms	Authors	Comments
Std. $k - ε$	[2], [44], [52], [53], [54], [55], [56], [57], [58]	Pros: Computationally efficient and economically viable. Agreement with wind tunnel measurement of wind speed is within 10% for regions with high wind speed ratio ( $U / U_{0} > 1)$ [59]
Std. $k - ε$	[2], [44], [52], [53], [54], [55], [56], [57], [58]	Cons: Underestimates wind speed notably five times or more for low wind speed regions [59]. It cannot reproduce the reverse flow on the roof [60] and overpredicts turbulent kinetic energy in separated flows around windward corners of buildings [55].
Realizable $k - ε$	[6], [17], [50], [61], [62], [63], [64]	Pros: Sensitive to flow separation, reattachment and recirculation. For high wind speed region accuracy further improves as compared to std. $k - ε$ model [17].
Realizable $k - ε$	[6], [17], [50], [61], [62], [63], [64]	Cons: Less accurate compared to std. $k - ε$ model for low wind speed region due to underestimation of TKE in the wake region [17]
RNG $k - ε$	[65], [66], [67], [68]	Pros: For high wind speed region, accuracy improves as compared to std. $k - ε$ model. [59]
RNG $k - ε$	[65], [66], [67], [68]	Cons: Less accurate compared to std. $k - ε$ model for low wind speed region due to underestimation of TKE in the wake region [59].
LES	[69], [70], [71], [72]	Pros: Superiority of this method over steady RANS is clearly reported [60]. It can reproduce turbulence intensity and gustiness.
LES	[69], [70], [71], [72]	Cons: Computationally very expensive as it requires more time and sensitive to many parameters such as sub-grid scale model, mesh resolution and time step size [73].
DES	[67]	Pros: Capable of producing similar results as LES with less computing time and lower mesh size.[74]
DES	[67]	Cons: Sensitive to parameters such as sub-grid scale model, mesh resolution and time step size and sampling time. [74]

3.2. Comparison of Different Techniques

3.2.1. Field measurement and wind tunnel measurement

To evaluate PLW environment on existing project site, it is suitable to conduct field measurements. But to assess the effect of changes in the initial design of developmental projects, wind tunnel measurements are preferred. Comparison of these techniques is generally associated with practical difficulties such as variability inherent to the atmospheric phenomena, obstructions due to automobiles etc. Isyumov and Davenport [26] obtained full-scale and wind tunnel measurement for mean wind speed at a site project in Toronto, Canada. They reported the agreement between full-scale and wind tunnel measurement within 10% for windy locations. Dye [28] compared the same in a sheltered urban area and found that wind tunnel test generally underpredicts the mean speed of 20% at most severe locations. While Visser et al. [30] reported the comparison of these two techniques to be dependent on the duration of full-scale data measurement, as the wind speed data of longer period will agree well with the model test.

3.2.2. Field measurement and CFD simulation

The use of CFD technique provides entire flow field data, whereas field measurement can be performed for few location only. However, it is a challenging task to simulate wind environment using CFD techniques accurately. Blocken et al. [6] compared the results of CFD simulation at a university campus. The simulation was performed using a realizable $k - ε$ model with standard wall function and field measurement was performed with 3D ultrasonic anemometers. The authors clearly indicate that the short term measurement for few hours cannot serve as a validation data because the data suffers from intrinsic variability of meteorological conditions. Large deviation of 25% between measured and simulated mean wind speed was reported at the locations where the gradient of wind speed is high. In addition, the comparison of the wind speed in the regions of high gradients can yield large deviation by a small shift in location.

3.2.3. Wind tunnel measurement and CFD simulation

The CFD technique has attracted wide acceptability and strong support due to the establishment of several best practice guidelines [75]. Wind tunnel testing is often used to benchmark CFD models and simulation results. The use of RANS was found to provide quite accurate results for wind speed ratio, however, it significantly underestimates wind speed in the regions of lower wind speed ratios [6]. A possible reason for high wind speed ratio is characterized by lower turbulence intensities and lower wind direction fluctuation, therefore better modelled by the statistically RANS approach.

Richards et al. [44] adopted erosion technique to investigate the PLW environment downtown area of Auckland and compared erosion contour with CFD simulation using std. $k - ε$ model. The authors observed the difference at the location of highest wind contours. Using CFD simulation, this location was immediately around the corner of the buildings, whereas the wind tunnel shows that the earliest erosion emanates from the corner and sweeps across the buildings.

4. Parametric studies and their impact on generic building configuration

In past decade, various parametric studies related to the evaluation of pedestrian level wind environment around generic building configuration have been conducted, which considered the effect of building height, shape and pattern of a group of buildings. These studies are listed in Table 4. In this section brief discussion about the effect of parameters related to the design of building configuration on pedestrian level flow is presented.

Table 4. Various parametric studies to evaluate PLW around different building configuration.

Author	Parameter	Effect of Key parameter
Generic Building Configurations
Lam, [39](WT)	Permeable floor at mid-height of CAARC building	The spatial extent of high wind speed reduces by using the permeable intermediate floor.
Uematsu et al. [8] (WT)	Corner modification of building	Reduces the high wind speed zone near building corners.
To & Lam [31] (WT)	Representation of PLW speed	Quartile level (a) wind speed descriptor found to be a suitable indicator for evaluating PLW, as it avoids the problem of choosing gust factor.
Zhang et al. [65](WT/CFD)	Different building arrangement	The arrangement with higher frontal aspect ratio and plan area density found to be suitable for natural ventilation.
Asfour [53](CFD)	Different grouping pattern of housing blocks	The configuration in which buildings are arranged around a central space windward opened side facing the prevailing wind direction offer better ventilation.
Tsang et al. [47] (WT)	Different building width and height for a single and row of buildings and use of podium	Taller building improves ventilation near the building, Use of podium and width of building adversely affect ventilation.
Hang et al. [55] (CFD)	Use of urban canopy layer	Urban canopy layer worsens the ventilation than open street due to decrease roof ventilation.
Kuo et al. [48] (WT)	Different street widths and podium heights	High wind speed inside canyon for taller podiums.
Xu et al. [51](WT)	Super tall buildings with unconventional shapes	High-speed up ratio for super tall (400 m) buildings and mostly influenced by a change in building width at one-third level from the ground.
Fan et al. [54] (CFD)	Building openings at pedestrian level of street canyon	Buildings with permeability of 10% is adequate to improve PLW
Hong & Lin [56] (CFD)	Different layout of building pattern	Configuration with square central space offers better PLW environment.
Tse et al. [78](WT)	Wind twist angle, isolated building, wind incidence angle	Displaced flow features and increased area of low wind speed at downstream of buildings. LWS region gets intensified with the increase of wind twist angle.
Tse et al. [49](WT)	Wind twist angle, building dimensions and passage width	Wind environment is asymmetric near the building, wind speed in the passage decreases with wind twist angle.
Passage between Two Buildings
Stathopoulos & storms [7](WT)	Passage width and height of one of the building	Buildings with different height create most critical wind velocity condition.
Blocken et al. [57] (CFD)	Effect of wall function, Passage width between parallel buildings	Horizontal inhomogeneity of wind profile affects the simulation results. Wind speed within the passages is only pronounced at the pedestrian level.
Blocken et al. [38] (WT)	Passage width between two perpendicular buildings and building height	Wind speed amplification in the diverging passage is often more than the converging passage.
Li et al. [58](CFD)	Converging and diverging passage with 15° interval	Converging passage with 15° for cold and temperate climate and diverging passage with 150° for the highly dense urban area in sub-tropical climates.
Allegrini & Lopez [41](WT)	Converging and diverging passage for different angle 60°, 90° and 120°	From ground to roof wind speed increases for converging case with increasing angle between buildings and decreases for the diverging case.
Lift up Building Design
Tse et al. [1](WT)	Lift up central core height and width.	Increase in the lift up core height mostly influences the area percentage of acceptable wind speed.
Zhang et al. [3] (WT)	Lift up central core shape and building aspect ratio.	Speed-up ratio increases with building height, corner modification of central core controls the HWS zone.
Du et al. [79](CFD)	Different building configuration (-, L, U, Square).	Better PLW comfort than non-lift up building for oblique wind direction.
Zahid Iqbal et al. [2](WT/CFD)	Building shape, separation orientation and turbulence model closure coefficients	Square-shape arrangement yields higher average acceptable wind speed area, higher $C_{μ}$ b and lower values for turbulent Prandtl numbers is suggested for accurate simulation.

a: Quartile-level Wind speed- it is defined as wind speed that is being exceeded for 10% of the observation time.
b: Model closure coefficient for Std. $k - ε$ model.

4.1. Height and width variation

As the height of building increases, the maximum wind speed ratio increases due to strong downwash effect, as taller building catches the more upper-level wind and directs it to pedestrian level. Hence it poses high wind speed conditions but improves near-field air ventilation conditions as shown in Fig. 3.(a) [35], [47], [51]. Whereas turbulence intensity is not influenced by height variation of building significantly [35]. Wider buildings increases the sheltering effect to the incoming wind, which enlarges the extent of low wind speed zone in the downstream side of the building.

4.2. Modification of cross-section

Changes in cross-section of the building, such as tapering, rounding, and corner cut improve the wind environment around the building corners, as it reduces the extent of high wind speed zone near building corners due to less deviation of separated flow in comparison to the square building as shown in Fig. 3(b) [8], [35]. But root mean square value of wind speed distribution remains unaffected due to corner modification [8]. Circular and polygon shaped cross-section of the building also tends to have better wind climate in terms of reduced high wind speed zone as compared to the square-shaped building due to reduced downwash [35].

4.3. Modification along the height

Till now this modification is investigated in detail by Xu et al. [51] for various building models and it was proposed that the change of building width at one-third height from the ground, majorly influences the PLW environment. Whereas the use of permeable floor at mid-height of the building reduces the extent of high wind speed zone. However, it does not lower the maximum wind speed ratio [39], as this permeable floor provides a way for upper-level wind to pass through the building before reaching it to ground level.

4.4. Lift up building design

This design consists elevated main structure of the building from the ground by the central core and has a potential solution to improve wind conditions near the building. This design modification increases area averaged high wind speed ratio but decreases area averaged low wind speed zone on the leeward side of the building because of weak downwash [1], [3].

To illustrate the effect of this building design, numerical simulation using CFD software Ansys/Fluent 17.0 was conducted. The governing equations of the flow are 3D steady-state Reynolds-averaged Navier-Stokes with standard $k - ε$ turbulence model. Numerical Simulation has been conducted using best practice guidelines [75] for pedestrian level wind flow. All the details related to CFD simulation is not included as it is beyond the scope of this paper. The result of this simulation is presented in Fig. 4, which represent the contours of mean wind speed at pedestrian height for lift-up and conventional square buildings. The qualitative results of the present simulation are similar to the experimental study by Tse et al. [1] which shows high wind speed near the lift up area and further lower values of low wind speed as compared to conventional building design. Which helps in improving ventilation near the building

In addition to this lift up area can be used for other purposes as the recreational area, parking, or shelter for pedestrians. Besides this, use of lift up building design is limited due to unacceptable or high wind speed zone near the lift- up area [76]. This unacceptable wind condition arises due to flow through openings of positive and negative pressure faces of the building.

4.5. Use of podium structure

Podium structure creates a sheltering effect at pedestrian level wind flow near the building and results in undesirable low wind speed zone at pedestrian level [47], as podium structure enhances the spatial extent of low wind speed zone near upstream and downstream of the building. In general podium structure is not recommended where the conditions for natural ventilation are required. Besides this, it is believed that podium structure is used to protect pedestrians from high wind speed.

4.6. Different passages between two buildings

The orientation of two buildings such as side by side, parallel, angular (converging, diverging and perpendicular) creates an adverse effect on PLW speed differently as shown in Fig. 5. When wind flow is perpendicular to the row of buildings, the windiest condition occurs in the upstream corners due to flow channelling and suppressed horse-shoe vortices [31]. As the separation between the buildings increases, channelling effect gets minimized and flow tends to be independent of the further increase in separation.