Journal of Heat Island Institute International Vol. 9-2 (2014)

Academic Article

Study on the Evaluation Method of Wind Environment
in the Street Canyon for the Preparation of Urban Climate Map
Hideki Takebayashi*1Keisuke Oku*2*1 Department of Architecture, Graduate School of Engineering, Kobe University*2 Kintetsu Corporation
Corresponding author: Hideki TAKEBAYASHI, thideki@kobe-u.ac.jp
ABSTRACT
Ventilation in street canyons contributes to mitigation of extremes in the thermal environment in urban areas.
In previous studies, a strong relationship between the gross building coverage ratio and the mean wind velocity atpedestrian level has been confirmed. In this study, the relationship between wind environment and street canyon
characteristics was analyzed using CFD and a GIS tool. Mean wind velocity is explained better by the open spaceratio rather than the gross building coverage ratio in grids more than 250 m square grid. Mean wind velocity
averaged in the area of about 250 to 1,250 m square grid is meaningful. Because two or more peaks of windvelocities occur in more larger scale. When the evaluation scale is less than 100 m square, the wind environment instreet canyons is best evaluated by more specific indicators (e.g., road width) rather than spatially averagedindicators (e.g., gross building coverage ratio). Ventilation in street canyons improves on wider roads parallel to themain wind direction. If the perpendicular or staggered arrangement of building heights varied in the areas ofinterest, ventilation in the street canyon would be expected to improve, even if the mean building height were low.
Key Words : Wind environment, Urban climate map, Street canyon

tunnel experiment in 22 residential Japanese neighborhoods and1. Introduction

concluded that there is a strong relationship between the gross
The urban climate map is an information and evaluation toolbuilding coverage ratio and the mean wind velocity at pedestrianused to integrate urban climate factors and town planninglevel(8). Ng has also confirmed a similar tendency in Hong(1)

considerations by presenting maps of climate analysis . Ren etKong(3).

al.(2) recently reviewed studies on urban climate map. InIn this study, the wind environment in a street canyon in Osakaprevious studies, Climatopes, which are closely related to theCity was calculated using CFD. The relationship between thethermal environment near the ground surface, were mainly

wind environment and street canyon characteristics wasdefined by land use. A spatial classification for ventilation nearanalyzed using CFD calculation results and a GIS tool, in order

the ground surface has not been established. A number ofto identify the predominant indicators of the wind environment.

features (e.g., air path, building ground coverage and building
bulks, building height/street width ratio, street orientation, layout

2. Calculation method and resultsof building disposition, open spaces and greenery areas) havebeen linked to ventilation. Some study results were also used in

The standard k- turbulence model (one of the RANS models)an air ventilation assessment of Hong Kong(3).

was selected for use in the simulation. A general purpose

Ventilation in street canyons contributes to mitigation ofcomputational fluid dynamics software (STREAM, version 8,extremes in the thermal environment in urban areas, in terms ofSoftware Cradle Co., Ltd.) was used for calculation. The

the dispersion of heat and pollutants, and the improvement ofNavier-Stokes equations were discretized using a finite volume

effective temperature. The importance of the relationshipmethod and the SIMPLE algorithm was used to handle

between urban morphology and ventilation has been pointed out

pressure-velocity coupling. The calculation conditions areby a number of researchers(4–7). Kubota et al. carried out a windshown in Table 1, referring to Tominaga et al.(9). The- 55 -applicability of this CFD software for an urban area such as

Table 1 Calculation conditions

Osaka City has been verified using a verification database

Turbulence model
Advection term
Inflow boundary

Standard k- model
Up-wind difference schemePower-law, 3.2m/s at 54m
high, power: 0.25
Outflow boundary
Zero gradient conditionUp, side boundary
Free-slip condition
Wall, ground surface Generalized log-law
Grid resolution
10 m (x), 10 m (y), 1 m (z)in the target area

provided by Tominaga et al.(9).
The area of interest was all of Osaka City (223 km2), which wasdivided into 50 target areas 2,500 m square, as shown in Figure
1. Appropriate adjustments were made near the boundary ofOsaka City. Data about individual building shapes handled usinga GIS tool, was provided by Osaka City Office. The height ofeach building was calculated by multiplying the floor heightfrom each building use by the number of stories specified in theN⑨data of each building. Smaller objects (e.g., trees, signs, cars,

6‐9human bodies) could not be reproduced. Building shape⑧

information of the adjacent city was added based on map data

⑦4‐8

and aerial photographs.

3‐7⑥As an example, the setting method of the calculation domain andthe calculation mesh in Target area 5-4 is explained. The plan

4‐75‐76‐77‐72‐63‐64‐65‐66‐67‐62‐53‐54‐55‐56‐57‐5 8‐5⑤and cross section of the calculation domain are shown in Figures

5‐86‐88‐6④

1-4

2‐4

3‐4

4‐4

5‐4

6‐4 7‐4

reproduced in Field 2, and Field 3 is the objective area 2,500 m③1‐32‐3

3‐34‐35‐36‐3

7‐3square. The extra buildings have been reproduced 500 m to each

②1‐2 2‐23‐24‐25‐26‐27‐2 8‐24‐15‐16‐1

7‐1 8‐1④⑤⑥⑦2 and 3. Field 1 is the whole calculation area, each building isside of the objective area in Field 2, based on the preliminary①

consideration of the horizontal smooth connection method of①

mutually adjacent wind fields. So that it was not affected by the②③⑧Fig. 1 Objective area

setting of the calculation domain, a sufficiently large calculation
domain was set in Field 1. The area of the leeward side waswider (5,000 m) than the windward side (2,500 m), to avoid
Field1having the flow disturbed by leeward obstacles, according to2500ｍ(9)

Tominaga et al . The vertical height was also set sufficiently

2500ｍ

Field2large. The size of the calculation domain was 11,000 m x 8,500
m x 550 m.

Field3

Plan and cross sectional views of the calculation mesh are shown

3500ｍ

2500ｍ

Inflowin Figures 4 and 5. Grid resolution is 10 m x 10 m x 1 m in Field
2 and 3. The grid intervals increase gradually horizontally(outside of Field 2) and vertically (above the maximum buildingheight of 161 m).

2500ｍ

3500ｍ

5000ｍ
2500ｍ

YFigures 6 and 7 show a wind rose and the frequency of windXvelocity at Osaka Observatory when the sea breeze is blowing
on summer days. Osaka Observatory is located in the center ofFig. 2 Plan of calculation domain in the target area 5-4

Osaka City. The anemometer is set 54 m above the ground. The
wind direction was most often from the west-southwest and west.
The mean wind velocity was 3.2 m/s when the sea breeze wasblowing on fair summer days. Wind speed (3.2 m/s) for westerly
wind 54 m above the ground, with a power law vertical profile

Z

2500ｍ

550ｍ

3500ｍ

5000ｍ

X(power: 0.25), were the inflow boundary conditions set.
The calculated results of wind velocity 2 m above the ground areshown in Figure 8. All the wind velocities used for analysis in
this study are the result of calculations for wind at the height of
2 m above the ground. Wind velocity is higher over open spaces,such as sea, rivers and large parks, and lower inside Osaka City
where the density of buildings is great.

- 56 -Z

2500ｍ

3500ｍ

550ｍ
2500ｍ

Y

Fig. 3 Cross section of calculation domain in the target area 5-4

YX

Fig. 4 Plan of calculation mesh in the target area 5-4

ZX

0.0

Wind velocity (m/s)

5.0

Z

Fig. 8 Calculation results of wind velocity at the height of 2 m
YFig. 5 Cross section of calculation mesh in the target area 5-4

N
NNW40%30%NW
WNW

3.1 Classification of urban block components
NNE

Urban block components are generally classified as either

NE

20%

ENE

10%W

E0%WSWESESWSESSWS3. Analysis method and results

SSEFig. 6 Wind rose at Osaka observatory in summer fine days

buildings or open space. In addition, open space is classified asroad, space around buildings and independent open spaces (suchas parks or rivers). In this study, independent open space iscalled‘open space’; therefore, the urban block components wereclassified as ‘building’, ‘road’, ‘space around building’ or ‘openspace’. The classification of urban block components is shownin Figure 9. ‘Space around building’ means the open space

Frequency (%)

belonging to each building site, (e.g., approach, garage,plantings). The ratio of each urban component was calculated

20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%

based on 10 m resolution data used for the CFD calculation.
3.2 Relationship between mean wind velocity and urban
block component ratio at each evaluation scale
Calculated results for 10 m square grids were averaged for 100m, 250 m, 500 m, 1,250 m and 2,500 m square grids. Grid
Wind velocity (m/s)

partitioning at each scale is shown in Figure 10. Mean windvelocity was calculated from all calculated results of horizontal

Fig. 7 Frequency of wind velocity at Osaka observatory whenwind velocity, without the solid points (such as buildings) in

the sea breeze is blowing in summer fine days

each square grid. Therefore, in the case of a 100 m square grid,
the mean wind velocity might be calculated from an extremely
low number of wind velocity calculation results. The
relationship between the urban block component ratio and themean wind velocity averaged over grids 500 m square is shownin Figure 11. Mean wind velocity is better explained by the open
space ratio rather than the gross building coverage ratio. Here,‘building ratio’ and ‘gross building coverage ratio’ are the same.
Relationships between the gross building coverage ratio and- 57 -

mean wind velocity averaged in 500 m grid, and between grossmean wind velocity decreased with the increase of this ratio. In

space ratio was almost constant. Overall, the mean wind velocity
averaged in 500 m square grids is influenced more by the open
space ratio rather than by the gross building coverage ratio.

Mean wind velocity (m/s)

30%, mean wind velocity was almost constant and the open

Road ratio (%)

Building ratio (%)

contrast, when the gross building coverage ratio was more thanSpace around building

Space around building ratio (%)

The determination coefficient for each urban block component

Road

Mean wind velocity (m/s)

When the gross building coverage ratio was less than 30%, theMean wind velocity (m/s)

ratios in 500 m square grids are shown in Figures 12 and 13.

Building

Mean wind velocity (m/s)

building coverage ratio and the other urban block component

Open space

Open space ratio (%)

ratio to the mean wind velocity averaged at each evaluation scaleFig. 11 Relationship between urban block component ratio andis shown in Table 2. Determination coefficients by grossmean wind velocity at the height of 2 m, averaged over grids

building coverage ratio and open space ratio were as large as,

500 m square

and almost the same in 2,500 m and 1,250 m square grids; thoseby open space ratio were larger than those in 500 m and 250 m
Mean wind velocity (m/s)

square grids. The relationship between any urban block
component ratio and mean wind velocity was not confirmed in
100 m square grids. Overall, the mean wind velocity wasexplained by the open space ratio in grids more than 250 msquare.

Building

Gross building coverage ratio (%)

Road
Building
Building

Park

Building

Building

Fig. 12 Relationship between gross building coverage ratio andBuilding

mean wind velocity at the height of 2 m, averaged over grids

Road

Building

Road
Building

Building

500 m square

Building

ParkBuilding

Space around building

Each component ratio (%)

道路Open space (park, river, etc.)

Fig. 9 Classification of urban block components

Open space
Space aroundbuilding
RoadBuilding

Gross building coverage ratio (%)

Fig. 13 Relationship between gross building coverage ratio and2,500 m square grid

1,250 m square grid

500 m square grid

the other urban block component ratios in grids 500 m square
Table 2 Determination coefficient by each urban block
component ratio to mean wind velocity averaged in each scale

250 m square grid

Gross building coverage ratio
Road ratio
Space around building ratio
Open space ratio

100 m square gridFig. 10 Grid partitioning in each scale- 58 -

2,500 m 1,250 m 500 m 250 m 100 m
0.83
0.79
0.53 0.40 0.16
0.56
0.54
0.31 0.17 0.01
0.12
0.01
0.00 0.00 0.01
0.76
0.74
0.64 0.46 0.16

4. Validity of spatial mean wind velocity

40%

Frequency

30%

The frequency distribution of the calculated results and theirapproximation in 500 m and 2,500 m square grids, are shown in

R2＝0.91, approximated byNormal distribution

20%
10%0%

Figure 14. The accuracy of the approximation by normal

0123
Wind velocity (m/s)4(a) 500 m square grid

distribution in 2,500 m square grids was reduced in regions

40%

where wind velocity was greater, such as rivers and parks. The

R2＝0.92, approximated by
Weibull distribution

30%
Frequency

ratio of the number of areas where the determination coefficient
was approximated by the Normal and Weibull distribution was

20%

R2＝0.66, approximated by
Normal distribution

10%

Wind velocity (m/s)
at the height of 2 m0%

more than 0.7 (Table 3). This ratio was approximated more

0123
Wind velocity (m/s)

4appropriately by the Weibull distribution. Both methods are(b) 2,500 m square grid

inappropriate in 100 m square grids. The ratio of inappropriate

Fig. 14 Frequency distribution of wind velocity at the height of 2

areas is a little larger in 2,500 m square grids, because there is am, and its approximation in grids 500 m and 2,500 m squarepossibility that there were two or more wind velocity peaks inthe area. Approximation may be worse in the case of larger

Table 3 The ratio of areas where the determination coefficientevaluation areas. After all, the mean wind velocity averaged overapproximated by Normal, Weibull distribution is more than 0.7

an area of about 250 to 1,250 square meters is meaningful.
approximated by Normal distribution
approximated by Weibull distribution

5. Analysis of wind velocity by more specific indicators in

2,500 m 1,250 m 500 m 250 m 100 m
25%
50%
55% 51% 29%
75%
81%
83% 78% 37%

grids less than 100 m square
5.1 Influence of road width on wind velocity in street
canyons
CFD calculation is carried out as intended for the city center ofOsaka. The region enclosed by the bold line in Figure 15, wassubjected to analysis. The research area was 3,600 m (east towest) by 2,700 m (north to south), and the horizontal gridinterval was 2.5 m. The other calculation conditions are the sameas described in Section 2. The relationship between road width

Nand wind velocity ratio of upper level wind, is shown in Figure
16. The left side indicates a road parallel, and right side a roadFig. 15 Analysis area

perpendicular, to the main wind direction. Since these figures(East-west: 3,600 m, North-south: 2,700 m)

0.4
0.2
0.0

Road width (m)

0.8
0.6
0.4
0.2
0.0

15-20
20-25
25-30
30-35
35-40
40-45
45-50
50-55
55-60
60-65
65-

5.2 Influence of building height on wind velocity in street

0.6

1.0

5-10
10-15

wind direction.

0.8

15-20
20-25
25-30
30-35
35-40
40-45
45-50
50-55
55-60
60-65
65-street canyons improved on wider roads parallel to the main

1.0

5-10
10-15

Wind velocity ratio to upper wind

there are road widths with no calculation results. Ventilation inWind velocity ratio to upper wind

were made from the calculations for the city center of Osaka,

Road width (m)(Error range means standard deviation)

canyons
A supplemental calculation was carried out using the Aligned

Fig. 16 Relationship between road width and wind velocity ratio

Urban Block Model with uniform heights of the windward andat 2 m, to upper level wind at 54 m (Left: parallel to main windobjective areas. Here, the urban block was 80 m square, roaddirection, Right: perpendicular to main wind direction)

width was 15 m, building height was changed from 20 to 80 m,in every 10 m, in reference to the city center of Osaka. The

the mean wind velocity ratio was large. The mean wind velocity

settings of the research area and the windward area are shown in

was much higher due to downdrafts when the building height inFigure 17.

the research area was higher than that in the windward area. The

The relationship between the difference of building heights

relationship between the mean building height and mean wind(between research and windward areas) and the mean windvelocity (upper level) ratios is shown in Figure 19. The left side

velocity ratio for upper level wind in the research area is shown

shows results when building height in the research objective areain Figure 18. When the difference in building heights was large,changes, right side is in the case that building height in- 59 -windward area changes. Buildings arrangement is shown in
400m

figure 20. If there is a variation in perpendicular or staggered
arrangement of building heights in objective area, ventilation inBuffer area
Inflow

the street canyon is improved even if mean building height iswindward area

objective area

low. Influence of building height in windward area on wind

840m

velocity in street canyons was not large.

15m
80m

6. Conclusions

80m15m
1125m

400m

The relationship between wind environment and street canyon

800m
400m

Fig. 17 Setting of the research (objective) and windward areas

characteristics was analyzed using CFD and a GIS tool. Mean
0.30

Wind velocity ratio to upper wind

wind velocity is explained better by the open space ratio ratherthan the gross building coverage ratio in grids more than 250 msquare grid.
Mean wind velocity averaged in the area of about 250 to 1,250
m square grid is meaningful. Because two or more peaks ofwind velocities occur in more larger scale.

0.25
0.20
0.15
0.10
0.05

When the evaluation scale is less than 100 m square, the wind

0.00
-60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60
Difference of building heights (objective area – windward area) (m)environment in street canyons is best evaluated by more specificFig. 18 Relationship between the difference in building heights

indicators (e.g., building height and road width) rather thanand mean wind velocity ratio at 2 m, to upper level wind at 54 m
Wind velocity ratio to upper wind

Ventilation in street canyons improves on wider roads parallel tothe main wind direction. If the perpendicular or staggered
arrangement of building heights varied in the areas of interest,
ventilation in the street canyon would be expected to improve,even if the mean building height were low.

0.35
0.30
0.25
0.20
0.15
0.100.05
0.00

01020 30 40 50 60 70
Mean building height (m)Uniform

0.30
0.25
0.20
0.15
0.10
0.05
0.00

010

Perpendicular

2030 40 50 60 70
Mean building height (m)8090

Staggeredwind velocity ratio at 2 m, to upper level wind at 54 m (Left:(1) J. Baumueller, U. Hoffmann and U. Reuter, Climate booklet
urban

Parallel

90

0.35

Fig. 19 Relationship between mean building height and meanReferencesfor80

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(Received Nov. 9, 2014, Accepted Dec. 27, 2014)- 60 -

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