Cities of wind:
natural ventilation access in urban design
M. GROSSO AND G. BANCHIO
Department of Human Settlement Sciences (DINSE)
Polytechnic University of Turin
Viale Mattioli 39, 10125 Torino, ITALY
grosso@archi.polito.it
banchio@archi.polito.it
Abstract
Wind access/protection in cities can be affected by the morphological characteristics of the built environment.
Town-planning legislation, building codes and city plan regulations influence those characteristics.
Substantial climate-responsive changes of such laws and by-laws as well as simplified environmental
performance evaluation tools can contribute to the reduction of mechanical ventilation and air conditioning
energy loads through natural ventilation-proned urban design. The effects of urban form on wind-driven
natural ventilation potential of buildings have been investigated by the authors, in collaboration to the
Municipality of Grugliasco – a city neighbouring Turin (Italy) – within the CE-funded research project
PRECis (assessing the Potential of Renewable Energy in Cities). The present paper describes the main results
of this work. Although not yet exhaustive, these results are encouraging in regard with the possibility of using
simplified procedures – easy to be applied by designers and planners – for evaluating wind-driven ventilation
potential of alternative urban form configurations.
THEORETICAL BACKGROUND – MODELLING
THE URBAN WIND ENVIRONMENT
Ancient urban planners were aware of the relationships
between wind exposure/protection and urban layout
patterns. A paradigmatic example is Malta’s capital City of
La Valletta, whose orthogonal layout follows the wind rose,
thus allowing for efficient street ventilation (See Figure 1).
Figure 1. Malta’s capital City of La Valletta
However, the effects of urban fabric on the wind
characteristics have never been analytically investigated and
modelled until this century due to the stochastic behaviour
of air movement around obstacles.
The knowledge of air movement patterns around
buildings and within the urban fabric is important in relation
to various aspects. High wind speed can generate outdoor
discomfort; wind velocity and direction affect outdoor and
indoor natural ventilation cooling; cold wind protection in
winter reduces energy consumption; urban wind
characteristics influence the spread of air pollution from
traffic, industrial, and heating systems sources as well as the
exposure to noise pollution.
The effects of the general urban environment on the wind
characteristics - namely, wind velocity and turbulence
gradients - are well known and were modelled on the basis
of boundary layer wind tunnel tests [1] [2] [3] [4]. Less
experimental work has been carried out with reference to the
urban canopy, i.e., the layer of atmosphere enclosed within
the street canyons up to the buildings’ roof height [5]. A
new morphometric method was recently proposed in order
to derive aerodynamic properties of urban areas from
analysis of surface form [6].
At the building scale, the effects of varying geometric
and environmental characteristics on the envelop pressure
coefficient distribution were modelled using a parametrical
correlation-based approach [7] [8] [9].
A detailed accurate simulation of wind flow around a
cluster of buildings can be performed using a CFD model,
although it requires specific expertise and is time
consuming. The work presented here is related to a userfriendly simplified procedure developed as an urban design
tool for evaluating the effect of urban form on wind-driven
ventilation potential.
A PROCEDURE TO ASSESS THE INFLUENCE OF
URBAN FORM ON WIND-DRIVEN VENTILATION
POTENTIAL
PRECis (assessing the Potential of Renewable Energy in
Cities) is a CE-funded Project, co-ordinated by the Martin
Centre for Architectural and Urban Studies, School of
Architecture, University of Cambridge, aimed at
characterising the microclimate within cities in relation to
urban form. The central purpose of the authors’ contribution
was to develop a procedure to evaluate the effects of urban
form on wind-driven natural ventilation through buildings.
Urban form parameters
Urban drag coefficient
The developed procedure is based on an ‘urban’
extension of the program CpCalc+ [8], whose reference
database is related to block-shaped buildings laid out in a
normal layout pattern. Environmental and geometric input
parameters are: wind direction, wind velocity profile
exponent as a characteristic of terrain roughness, plan area
density – i.e., the ratio of built area to whole area – azimuth
angle of buildings, frontal and side aspect ratios, average
buildings’ height, and buildings’ dimension co-ordinates.
In order to apply the procedure to real urban fabric, a
method for determining a reference model array from urban
areas with irregular layout was developed. This model
comprises buildings of equal dimensions and azimuth,
derived from averaging the actual ones, and has the same
plan area density of the real urban area. An example
application was carried out on an area of Grugliasco - a city
neighbouring Turin and participating to the PRECis project
as an associated partner (See Figure 2).
The urban drag coefficient Cd, represents the relative
wind pressure force acting upon the vertical surfaces of a
considered urban area along the wind flow. It was chosen as
a lump parameter able to characterise the effect of urban
form on wind-driven ventilation, independently on building
volume and window opening area.
Cd was obtained using the following equation:
Cd = D / (1/2 Vref2 Aref)
(1)
where Aref and Vref are, respectively, the reference area and
the reference wind velocity, D is the aerodynamic drag of
the urban fabric – calculated as an integrated sum of the
drag values of each building included in the area – and  is
the air density. Aref is the wind-facing frontal projected area
for a given wind direction.
The calculated results were compared to the ones
obtained by simulations performed using a CFD model
developed by CFD-Norway (Trondheim) as well as to wind
tunnel tests carried out at Norwegian University of Science
and Technology [10], for given conditions of boundary layer
and wind direction. As shown in Table 1 and Figure 3,
results are within a reasonable range for the boundary layer
typical of a flat terrain, while the CpCalc+-based procedure
underestimates the drag if the terrain roughness is higher.
Although this trend characterises all wind directions, slanted
angles are more critical.
The above urban drag procedure showed to be promising
but will need further testing, particular for high terrain
roughness and oblique wind.
Thermal effect of urban drag
Figure 2. Layout of the reference model array (below)
extrapolated from an actual urban form (above) - City of
Grugliasco (Turin, Italy)
An assumption is made that the differences amid the
aerodynamic characteristics of all buildings will be levelled
out when considering the drag of the whole area. The
relevant standard deviation can be evaluated by using the
procedure described in the following sections.
A set of simulations was carried out using the thermal
model ESP-r [11] on a monozone cube-shaped building cell
in order to evaluate the effect of urban drag on heating
infiltration losses as well as on cooling energy savings due
to wind-driven cross ventilation.
Five locations were simulated for the coldest day of a
typical year – Trondheim, London (Kew), Turin, Catania,
and Athens – representing a typical climate variation range
for Europe, from N-W to S-E. An analogous procedure was
followed for the hottest day on three locations (Turin,
Catania, and Athens). Meteonorm reference data were used,
changing the values related to wind velocity in order to
perform the parametrical analysis. Constant direction (0° N),
four wind velocities (0.5, 1, 2, and 3 m/s), two air leakage
conditions (0.5 and 3 mm of crack thickness), and three wall
insulation values (0.4, 0.75, 1.5 W/m2K) were considered as
input parameters.
The following output parameters were obtained in
correlation to the urban drag coefficient:
 ACH = Air volumes Changed per Hour, averaged within
24 hours in winter, and for the number of hours with open
windows, in summer;
 CLref = Cooling reference load, i.e., the cooling energy
calculated for the hottest day with closed windows,
related to a set point indoor temperature of 26 °C;
 TUFnv(H) = Heating Thermal Urban Factor, i.e., air
infiltration winter losses (Tiset-point = 20°C);
 TUFnv(C) = Cooling Thermal Urban Factor, i.e., cooling
energy (Tiset-point = 26°C, open windows for To<26°C).
Table 1. Global drag coefficient for area “A”
 = 0,14 (modelling),  = 0.149 (Wind tunnel test)
Aref = Frontal Area
0
150,6
345
30
330
45
315
0,4
60
300
0,2
75
285
90
0
270
105
255
120
240
135
225
150
210
165
195
180
Wind Tunnel
CFD
CpCalc+
= 0,28 (modelling),  = 0.244 (Wind tunnel test)
Aref = Frontal Area
0
150.3
345
330
45
315
0.2
60
300
0.1
75
285
90
0
270
105
255
120
240
135
225
150
210
165
195
180
30
Wind Tunnel
CFD
CpCalc+
Figure 3. Polar chart of Cd values comparing experimental
(Vref = Vext) and modelling (Vref = VBdz) results.
Regarding winter conditions, TUFnv(H) and ACH values
were found to be very close in all locations, for each wind
velocity. Location-averaged values, related to the higher air
leakage characteristics, are shown in Table 2, and the
relevant fitting curves in Figure 4a and 4b. Airflow rate and
thermal losses increase with drag coefficient, i.e., with
decreasing plan area density. The correlation is represented
by a power law function and the rate of increase is
progressively higher in relation to growing wind velocities.
TUFnv(H) values are fairly small, even for a relatively
high leakage parameter as the one on which data are based.
However, the seasonal thermal losses due to infiltration
could become significantly high, even in moderately cold
winter zones with yearly heating degree-hours around
60,000 as in Turin. In such zones, , as can be derived from
Table 2, the overall theoretical winter thermal losses
(referred to a constant wind velocity along the entire period)
might range from: 0.9 kWh/m2, in high-density urban areas
with low wind velocity (0.5 m/s), to 39.36 kWh/m2, in
isolated buildings with moderately high wind speed (3 m/s).
Furthermore, thermal simulation included calculation of the
solar shading effect due to obstructions, which were found
to be increasingly influential for value of PAD25%.
As far as airflow rates are concerned, data show that only
in practically isolated buildings and at v  3 m/sec, the
minimum air change per hour for residential indoor air
quality (ACH = 0.5) could be reached (See Table 2).
With regard to summer conditions, both CLref and
TUFnv(C) values were averaged amid the considered
locations, being of the same order of magnitude (See Table
3). Given the negligible influence of infiltration and
convective wall exchange on the overall cooling loads, CLref
values were averaged amid all wind velocities as well. For
the same reason, as Table 3 shows, the variation of Cd does
not affect CLref, which, instead, decreases slightly in relation
to the effect of shading for Cd < 0.25 (PAD > 16%).
TUFnv(C) values increase with decreasing Cd, i.e.,
increasing PAD, following an exponential fitting trend,
which is dependent on wind velocity. As Fig. 5a shows, this
trend, strongly apparent at v = 0.5 m/s, declines
progressively with increasing wind velocity and almost
disappears at v = 2 m/s, while it is even reversed at v = 3
m/s, meaning that the shading effect over-compensates the
decreased airflow rate. Hence, v = 2 m/s can be considered a
threshold wind velocity above which the effect of urban
drag, i.e., of urban form, becomes non-influential on
potential cooling energy savings due to ventilation.
Summer ACH follow the same exponential trend
dependent on wind velocity as winter air infiltration, but,
obviously, with much higher absolute values (See Figure
5b).
Drag
Coefficient
Pad
0
2.8
4
6.25
11.2
16
25
30
35
40
1.125
0.901
0.811
0.658
0.398
0.241
0.122
0.102
0.082
0.044
Clref
[W/dh m2]
0.5
5.575
5.738
5.738
5.857
6.099
6.424
6.584
6.663
6.706
7.107
23.853
23.853
23.853
23.853
23.853
23.853
22.877
22.504
22.179
21.891
TUFNV(C)
ACH
[W/dh m2]
[V/h]
1
5.059
5.178
5.178
5.135
5.298
5.460
5.415
5.415
5.454
5.657
2
4.617
4.617
4.617
4.617
4.736
4.815
4.772
4.729
4.689
4.772
Wind velocity (m/sec)
3
0.5
4.418
16.422
4.418
14.657
4.418
13.892
4.418
12.498
4.375
9.732
4.495
7.559
4.411
5.348
4.368
4.911
4.368
4.401
4.368
3.225
1
31.704
28.375
27.064
24.240
19.448
14.228
10.441
9.546
8.565
6.265
2
65.462
58.520
55.550
51.067
40.095
30.234
21.538
19.687
17.664
12.937
Table 2. Heating Thermal Urban Factor and Air Changes per Hour for various wind velocities,
PAD, and Cd (location-averaged values);U value = 0,76 W/m2K; 3 mm crack thickness as air leakage parameter.
Pad
TUF NV(H)
Drag
Coefficient
0
2.8
4
6.25
11.2
16
25
30
35
40
0.5
0.072
0.063
0.059
0.055
0.038
0.030
0.023
0.022
0.019
0.015
1.125
0.901
0.811
0.658
0.398
0.241
0.122
0.102
0.082
0.044
ACH
[V/h]
[W/dh m2]
1
0.170
0.150
0.139
0.124
0.091
0.065
0.045
0.040
0.036
0.024
Wind velocity (m/sec)
3
0.5
0.656
0.064
0.573
0.059
0.537
0.052
0.472
0.047
0.345
0.033
0.251
0.026
0.165
0.019
0.152
0.018
0.132
0.014
0.090
0.012
2
0.398
0.348
0.325
0.288
0.210
0.155
0.103
0.093
0.081
0.055
1
0.151
0.132
0.117
0.109
0.079
0.056
0.039
0.036
0.032
0.021
2
0.351
0.309
0.291
0.254
0.187
0.137
0.090
0.082
0.072
0.049
3
0.577
0.503
0.474
0.415
0.308
0.225
0.143
0.132
0.117
0.079
Table 3. Cooling Thermal Urban Factor and Air Changes per Hour for various wind velocities, PAD, and C d
(location-averaged values); U value = 0,76 W/m2K; 3 mm crack thickness as air leakage parameter
0.700
0.600
TUF
(v=3) =
0.6087x 0.6126
TUF
(v=2) =
0.3706x 0.6102
TUF
NV(H) Average Value
0.500
0.400
0.300
0.200
TUF (v=1) = 0.1583x 0.6025
0.100
TUF
(v=0.5) =
0.0651x 0.4858
0.000
0
0.2
0.4
0.6
0.8
1
1.2
Drag Coefficient
Figure 4a. Fitting curves of location-averaged TUFnv(H) as a
function of Cd, for various wind velocities .
0.700
0.600
0.6167
ACH (v=3) = 0.5382x
0.500
Figure 4b. Fitting curves of location-averaged winter ACH
(closed windows) as a function of Cd, for various wind
velocities.
ACH [ V/h]
0.400
0.300
ACH (v=2) = 0.3278x0.6072
0.200
0.6022
ACH (v=1) = 0.1382x
0.100
c) = 0.0585x0.5314
0.000
0
0.2
0.4
0.6
Drag Coefficient
0.8
1
1.2
3
98.270
87.882
83.372
75.098
58.361
45.435
32.306
29.538
26.481
19.398
8.000
7.000
6.000
-0.0712
TUF(v=0.5) = 5.6801x
-0.0287
TUFNV (C) Average value
TUF(v=1) = 5.1279x
5.000
TUF(v=2) = 4.7703e-0.0343x
TUF(v=3) = 4.4255x0.0034
4.000
3.000
Where:
CLref = reference cooling load (W/dh m2)
TUF = thermal urban factor as above defined
Dh(H)= annual heating degree hours of the considered
location
Dh(C) = annual cooling degree hours of the considered
location
Dh*(C) =annual cooling degree hours corrected in order to
take the amount of ventilation hours into account
The assignment of VenUS is done according to a
classification of energy saving values ranging within a span
derived from the above-described regression analysis.
2.000
1.000
0.000
0
0.2
0.4
0.6
0.8
1
1.2
Drag Coefficient
Figure 5a. Fitting curves of locations-averaged TUFnv(C) as
a function of Cd, for various wind velocities .
120.000
100.000
ACH
(v=3)
= 92.599x
0.5005
ACH (open window)
80.000
60.000
ACH (v=2) = 62.185x0.5026
40.000
ACH
(v=1)
= 29.977x
0.5018
20.000
ACH
(v=0.5)
= 15.444x0.5021
0.000
0
0.2
0.4
0.6
0.8
1
1.2
Drag Coefficient
Figure 5b. Fitting curves of location-averaged summer
ACH (open windows) as a function of Cd, for various
wind velocities.
Comparison between CLref and TUFnv(C) allows for
deriving the cooling energy saving per degree-hour as a
function of Cd.
The VenUS procedure
VenUS (Ventilation Urban Score) is a procedure aimed at
assigning a score related to wind driven natural ventilation
potential, to the form configuration of an existing or planned
urban area.
A two-step sequence is foreseen:
calculation of the Theoretical Annual Energy Saving
Potential (TAESPnv) due to wind driven natural
ventilation for a considered area;
 assignment of a Ventilation Urban Score (VenUS) on the
basis of a classification of TAESPnv values.
The TAESPnv of a given urban form represent the annual
net energy savings, i.e., cooling savings balanced with
heating losses, based on hourly temperature reference data
(hottest and coldest days of a typical year) and averaged
annual wind velocity of the considered location. TAESPnv is
a wind drag related factor based on the analysis above
described and can be calculated by the following
expression:
*
TAESPnv = (CLref × Dh( C ) ) - ( TUFnv(C) × Dh(C)
) - TUFnv(H) × Dh(H)

[
][
]
ENVIRONMENTAL MANAGEMENT SYSTEM FOR
MUNICIPALITIES
The above described evaluation procedure is imbedded in
a more general Environmental Management System (EMS),
based on the methodology set up by the standards ISO
14000. It was proposed to the Municipality of Grugliasco,
but can be generalised to all Italian and European
Municipalities. Its scope comprises procedures, office
organisation, and tools aimed at:
 passing through environment-based knowledge to urban
and building designers;
 evaluating urban and building design proposals according
to a climate-responsive and energy-conscious approach;
 changing and updating accordingly town-planning laws
and by-laws;
 training Municipalities technicians for that evaluation;
 setting
up an interactive/iterative process for
environmental checking of urban and building design
proposals within the approval/rejection process,
including incentives for renewable energy applications.
A flow-chart of the environmental performance
evaluation process characterising the proposed EMS is
shown in Figure 6.
The VenUS procedure outlined above is used in the
phase assessment of potential use of the energy source wind
and related to the environmental control system ventilation.
Output of the VenUS application to case study areas can be
used for defining wind-related morphological rules within
the climate-responsive urban design guidelines.
In addition to the VenUS procedure, a qualitative preassessment graphical method can be used in order to
evaluate alternative urban plan configurations against
summer wind access.
This method, based on "Boutet's" experimental results
from wind tunnel tests [12], is applied by drawing downwind wakes for the buildings which are deemed to represent
airflow barrier for other buildings, with respect to a given
wind direction. Each drawn wake represents the core of a
fully developed wake, i.e., an area of calm, wherein the
wind velocity is decreased below 50% of the upstream
velocity. The summer prevailing wind direction is
considered.
This technique was applied to a case study area of
Grugliasco for a master plan configuration supplied by the
Municipality technical staff. Results of this application were
used by the urban designers to draw an alternative solution,
more valuable in relation to wind access for ventilative
cooling. Figure 7 shows both configurations, before and
after the application of the assessment method.
Figure 6. Flow-chart of the environmental performance evaluation process
Figure 7. Application of the graphical wind access assessment method to a case study area of Grugliasco Left: first master plan configuration; right: alternative solution after the wake analysis
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