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It has been shown that the spatial configuration of a green area can strongly influence its cooling effect. However, the specific correlation has not been sufficiently studied. To systematically clarify the correlation between the spatial configuration and the cooling effect of green areas, 25 idealized scenarios are designed and simulated using the microclimate model ENVI-met. These 25 scenarios represent green areas with five different spatial configurations (integrated green area, sparse dotted green areas, dense dotted green areas, belt-shaped green areas parallel to wind direction, and belt-shaped green areas vertical to wind direction) and five vegetation types (trees with big canopies, trees with small canopies, hedges and shrubs, 50 cm grass, and 10 cm grass). The human thermal comfort of each scenario is evaluated by means of physiologically equivalent temperature (PET) using Rayman. The results reveal the influence of the fragmentation degree (quantified by the patch density and edge density), shape complexity (quantified by the land shape index), orientation of green belt, and vegetation type on the cooling effect of a green area. The spatial configuration and the vegetation type of green areas were found jointly affecting the efficiency of the green areas’ cooling effect. The highest cooling effect appears at 2 pm, reaching 6.3 K in the scenario of belt-shaped green areas parallel to the wind direction and with big canopy trees. The conclusions of this paper can provide suggestions for the climate-adaptive design and planning of urban green areas in the future.
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Urban Forestry & Urban Greening
journal homepage: www.elsevier.com/locate/ufug
The inuence of spatial conguration of green areas on microclimate and
thermal comfort
Sahar Sodoudi
, Huiwen Zhang, Xiaoli Chi, Felix Müller, Huidong Li
Institut für Meteorologie, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6-10, 12165 Berlin, Germany
ARTICLE INFO
Keywords:
ENVI-met
Landscape metrics
Park cool island (PCI)
Rayman
Physiologically equivalent temperature (PET)
Vegetation type
ABSTRACT
It has been shown that the spatial conguration of a green area can strongly inuence its cooling eect.
However, the specic correlation has not been suciently studied. To systematically clarify the correlation
between the spatial conguration and the cooling eect of green areas, 25 idealized scenarios are designed and
simulated using the microclimate model ENVI-met. These 25 scenarios represent green areas with ve dierent
spatial congurations (integrated green area, sparse dotted green areas, dense dotted green areas, belt-shaped
green areas parallel to wind direction, and belt-shaped green areas vertical to wind direction) and ve vegetation
types (trees with big canopies, trees with small canopies, hedges and shrubs, 50 cm grass, and 10cm grass). The
human thermal comfort of each scenario is evaluated by means of physiologically equivalent temperature (PET)
using Rayman. The results reveal the inuence of the fragmentation degree (quantied by the patch density and
edge density), shape complexity (quantied by the land shape index), orientation of green belt, and vegetation
type on the cooling eect of a green area. The spatial conguration and the vegetation type of green areas were
found jointly aecting the eciency of the green areascooling eect. The highest cooling eect appears at
2 pm, reaching 6.3 K in the scenario of belt-shaped green areas parallel to the wind direction and with big canopy
trees. The conclusions of this paper can provide suggestions for the climate-adaptive design and planning of
urban green areas in the future.
1. Introduction
The intensity and frequency of heat waves will increase in the future
(Meehl and Tebaldi, 2004). Especially in urban areas, the heat waves
are further enhanced by growing urban heat island (UHI) eect (Li
et al., 2017, 2018). The rise of air temperature can result in many is-
sues, including the reduced urban thermal comfort and the health of
citizens (Kovats and Hajat, 2008; Bi et al., 2011;Nastos and Matzarakis,
2012;Bai et al., 2014;Hatvani-Kovacs et al., 2016), the increased
consumption of energy and power (Chang et al., 2007;Kolokotroni
et al., 2007), the increased risk of air pollution (Sarrat et al., 2006), and
the interference on the composition and distribution of urban biological
species (Niemelä, 1999).
Faced with problems caused by increasing urban heat waves, miti-
gation and adaptation strategies were extensively explored. Since being
rst proposed by Chandler in 1962 (Chandler, 1962), the cooling eects
of urban green areas have aroused considerable interest as a potential
method to mitigate urban heat waves (Park et al., 2012). A wealth of
studies has shown that green areas can lower the ambient air
temperature and adjust the humidity of surrounding areas (Spronken-
Smith and Oke, 1998;Chang et al., 2007;Bowler et al., 2010), forming
a kind of oasis eect, which is described as park cool island (PCI)
(Jauregui, 1991;Cao et al., 2010). The observed PCI amplitude ranges
from 2 K to 8 K (temperature dierence in Kelvin) (Taha, 1997;Wong
and Yu, 2005), and varies according to the properties of the green area.
The correlations between the properties of green space and the intensity
of PCI are widely reported by many studies (Jauregui, 1991;Chang
et al.,2007;Spronken-Smith and Oke, 1998).
The spatial conguration is one of the properties of a green area,
which is dened by the shape, arrangement and layout of green areas
(Wilmers, 1990). It has been found that the spatial conguration of a
green area signicantly aects the intensity of the PCI (Patton, 1975;
Cao et al., 2010;Li et al., 2012). However, the inuence of the spatial
conguration of green areas has not been suciently explored (Weng
et al., 2004;Zhang et al., 2009). It is suggested that more studies on the
inuence of green conguration should be conducted in the future
(Zhang et al., 2009;Li et al., 2012;Middel et al., 2014).
The quantication of the spatial conguration of green areas is
https://doi.org/10.1016/j.ufug.2018.06.002
Received 14 June 2017; Received in revised form 31 May 2018; Accepted 9 June 2018
Corresponding author.
E-mail addresses: sodoudi@zedat.fu-berlin.de (S. Sodoudi), zhanghuiwen@zedat.fu-berlin.de (H. Zhang), xiaoli@zedat.fu-berlin.de (X. Chi), mueller.f@fu-berlin.de (F. Müller),
huidong.li@met.fu-berlin.de (H. Li).
Urban Forestry & Urban Greening 34 (2018) 85–96
Available online 15 June 2018
1618-8667/ © 2018 Elsevier GmbH. All rights reserved.
T
mainly through the landscape metrics (Connors et al., 2013;Chen et al.,
2014a,b). The landscape metrics are concepts from landscape ecology.
They include a series of indices that quantitatively describing the spa-
tial conguration of green patches. The landscape metrics commonly
used in the studies of PCI include the land shape index (LSI) expressing
the complexity of the patch shape (Cao et al., 2010;Chen et al.,
2014a,b), and the patch density and edge density (PD & ED) re-
presenting the fragmentation of green patches (Zhang et al., 2009;
Maimaitiyiming et al., 2014).
A number of studies were conducted on the correlations between
the land surface temperature and PD & ED of green areas. However, the
results of these studies were contradictory. Some studies concluded that
the cooling eect increased as PD&ED increased (Gomez-Muñoz et al.,
2010;Maimaitiyiming et al., 2014), while others drew the reverse
conclusion (Cao et al., 2010;Zhou et al., 2011;Li et al., 2013). This
disagreement between studies is a consequence of the empirical study.
In order to provide an explanation for this disagreement, the numerical
modelling is necessary to be taken as methodology in the study of green
spatial conguration.
As a widely used model in the studies of microclimate (Wania et al.,
2012;Hedquist and Brazel, 2014;Perini and Magliocco, 2014), the
holistic three-dimensional non-hydrostatic model ENVI-met ®(EN-
VI_MET GmbH, Germany) is utilized in this study to investigate the
inuence of spatial conguration on the cooling eects of green areas.
Because of its strength in simulating the plant-air interactions (Bruse
and Fleer, 1998), ENVI-met works well in the exploration of the cooling
eect of the vegetation (Wang and Zacharias, 2015;Middel et al.,
2014).
The cooling eect of vegetation primarily comes from three eects
evapotranspiration, ventilation and shade (Boukhabl and Alkam, 2012).
ENVI-met enables the simulation of all of these processes. ENVI-met can
calculate sensible heat ux, evapotranspiration ux of liquid water on
leaves, and transpiration ux (Wania et al., 2012). Jansson (2006)
utilized ENVI-met to research water transport processes in the urban
microclimate. The eect of vegetation on wind speed and wind direc-
tion is usually studied with regard to thermal comfort and air pollution
problems (Vailshery et al., 2013;Wang and Zacharias, 2015). As ENVI-
met is a model based on computational uid mechanics (CFD) (Wania
et al., 2012), it can also work well in the investigation of the ventila-
tion. The most obvious inuence of vegetation on heat waves is as a
shelter against solar radiation. It is found that the mean radiant tem-
perature under foliage is much lower than that of the surrounding area
(Perini and Magliocco, 2014). The three- dimensional SPACES module
and the specic plant module Albero of ENVI-met enable the study on
the shade of vegetation.
As the heat waves in urban area signicantly inuence the human
thermal comfort of urban residents (Gabriel and Endlicher, 2011), the
physiologically equivalent temperature (PET) (Mayer and Höppe, 1987;
Höppe, 1999;Matzarakis et al., 1999) is used to evaluate the cooling
eect of green areas from the point of view of the human thermal
comfort in this study. Wide variety of studies were undertaken to ex-
plore human thermal comfort by PET in dierent regions and climate
zones (Ahmed, 2003;Nikolopoulou and Lykoudis, 2006;Farajzadeh
and Matzarakis, 2012;Li and Chi, 2014;Eludoyin, 2014). Because of its
comprehensive and eective assessment of thermal comfort, PET has
been widely used to evaluate the thermal environment of urban regions
(Thorsson et al., 2011;Andreou, 2013;Taleghani et al., 2014).
The origin of this study comes out of the redevelopment plan for the
former Tempelhof Airport in Berlin, Germany. After years of debate,
Berliners voted against the redevelopment of the former airport in a
public referendum in May 2014. 65% of voters voted against the
Senates plans, and secured the use of the site as a public park
(Hilbrandt, 2016). As the site of Tempelhof Airport also faces with risk
of overheating, before it is re-constructed as a green area, the following
questions should be answered: Which is the optimal layout of this green
area, one integrated green area or several smaller distributed green
areas? Which is the optimal shapes of the green areas, belt or square?
What is the optimal vegetation type of the green areas, shrubs or trees?
In order to answer these questions and further explore the sys-
tematic correlations between the cooling eects and spatial congura-
tions of green areas, in this study, 25 ideal scenarios representing green
areas with ve layouts and ve vegetation types were designed and
simulated by numerical model ENVI-met. The landscape metrics were
utilized to quantitatively describe the spatial congurations, aiming at
generalizing the results of the present study. The PET of each scenario
was calculated using Rayman model, in order to evaluate the cooling
eect from the point of human thermal comfort. The results of this
study can provide suggestions for the redevelopment plan of Tempelhof
Airport Berlin, as well as for the climate- adaptive design of urban green
areas adapting to the heat waves.
2. Methodology
2.1. Study area
The study was conducted in Berlin (52.52
°
N
, 13.38
°E
), Germany.
Berlin has large urbanized areas and displays pronounced urban heat
island (Li et al., 2017, 2018). On hot days, people living in the city
centre suered from much heat stress risk (Gabriel and Endlicher,
2011). The case study was carried out on the site of the former Berlin
Tempelhof Airport located near the city centre of Berlin. According to
the meteorological observation data on two hot and sunny days (8
th
/
9
th
June 2014) at Tempelhof meteorological station (52.27
°
N
, 13.38
°E
), the maximum air temperature on 2 m height was 31 °C with an
average of 23 °C combined with calm wind(2.06 m/s at 10 m height)
and low relative humidity (27%).
The former Airport Tempelhof was one of those free spaces, which
were in operation from 1923 to 2008. The still existing historical air-
port buildings in the site bear the meaning as a memorial for the Berlin
Airlift, which took place there during the Berlin blockade from 1948
until 1949. The area of Airport Tempelhof acts currently as an urban
park encompasses 355 ha, covered mainly by asphalt and grass. It is one
of the biggest city parks and an important local recreation area of
Berlin. It is surrounded by high-density residential areas with the tra-
ditional block pattern on west, northwest and east sides. On the south
side, a railway runs along the border of the eld. Another urban park is
located on the northeast of the area, separated by a main city road
(Fig.1).
2.2. Design of scenarios
By use of the SPACES module of ENVI-met, 25 ideal scenarios of
green areas with ve dierent congurations and ve vegetation types
were constructed (Fig. 2). The conguration types included Cong-
uration 1 eone central green area, Conguration 2 efour dotted green
areas, Conguration 3 esixteen dotted green areas, Conguration 4
efour belt-shaped green areas aligned South to North, and Congura-
tion 5 efour belt-shaped green areas aligned West to East. The whole
domain of each scenario is 10000m
2
and the total green area in all
scenarios is equal to 2500 m
2
. The ve congurations were combined
with ve dierent vegetation types: trees with big canopies (Height/
Diameter of canopy: 20 m/15 m), trees with small canopies (Height/
Diameter of canopy: 10 m/5 m), hedges and shrubs, 50 cm grass, and
10 cm grass. The spaces excepting the green areas in the scenarios were
covered by asphalt to imitate the city areas.
In order to evaluate the cooling eect of each scenario, one control
scenario completely covered by asphalt was simulated. The dierence
of the mean air temperature on 2 m height between the control scenario
and the objective scenarios was calculated.
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
86
2.3. Numerical modelling
2.3.1. Conguration of the ENVI-met
In this study, the micro-climatic conditions of the 25 green areas
were simulated using ENVI-met 4.0. The simulation was set conducted
in Berlin on 8
th
/9
th
June 2014, the same date with the observation
data. The daytime of the two days lastes for around 16 h. Based on the
meteorological condition of study area and the designed scenarios, the
conguration le of the model is shown in Table 1.
2.3.2. Evaluation of the ENVI-met
The performance of the ENVI-met model in simulating air tem-
perature at green areas in Berlin was evaluated using the measured and
simulated data of the project of Berlin-Brandenburg Academic of
Science (BBAW): The historical garden in climate change. As the
Tempelhof airport did not include dierent types of vegetation and
covered mainly by asphalt and grass, the measurement was carried out
in Tiergarten the central park of Berlin with various vegetation types
and congurations of green areas. The air temperature at 2 m height in
24 h was recorded in three measuring points respectively for the
Fig. 1. Plan of the site of Airport Tempelhof and its surrounding area (Tempelhofer Feld, 2018).
Fig. 2. 25 ideal scenarios for the simulation, with ve spatial congurations and ve vegetation types. The total green area in each scenario is equal to 2500 m
2
.
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
87
vegetation types of grass, tree-grass and tree-shrub-grass. The corre-
sponding simulated air temperature using ENVI-met has been compared
with the measured data.
Fig. 3 shows the diurnal variations of the simulated and measured
air temperature (left), and the corresponding linear tting (right). It can
be observed that the simulated air temperature consists with the mea-
sured air temperature well, with the correlation coecient of 0.92(P
0.05), RMSE = 1.26. With the relative low RMSE and high correlation
coecient, the simulation model ENVI-met in the study of green areas
can be evaluated as reliable.
2.4. Analysis of the simulated data
The simulated data of the 25 scenarios were analyzed at three time
point: 2 pm, 10 pm, and 5 a.m. As the greenery is well known as a
strategy to mitigate the urban heat island, these three time points were
selected as samples because of their representativeness in the mitigation
of urban heat island. At 2 pm of noon, the cooling inuence of the
shades and evapotranspiration are the highest. At 10 pm after sunset,
there is no more cooling eect from shades in the 25 scenarios, while
the urban heat island intensity of the reference asphalt scenario is still
high. At 5 pm before sunrise, there is also no cooling eect from shades
in the 25 scenarios, but the reference asphalt scenario has been cooled
down because of the heat dissipation. These times points were also used
as samples in the previous studies. (Lehmann et al., 2014;Mathey et al.,
2015).
The cooling intensities of the scenarios were demonstrated by the
mean cooling eect and the maximum cooling eect. The mean cooling
eect was the dierence of the mean air temperatures at 2 m height
between each green area scenario and the control area (covered by
asphalt). The maximum cooling eect was the dierence between the
coolest 2 m air temperature point in the scenario and the 2 m air tem-
perature in the control scenario covered by asphalt.
2.5. Quantication of the spatial conguration through the landscape
metrics
The green spaces in the scenarios were quantied by three land-
scape metrics: patch density (PD), edge density (ED) and land shape
index (LSI).
PD & ED are the signicant landscape metrics describing the frag-
mentation of green spaces. PD represents the number of green patches
divided by total landscape area, while ED represents the total length of
edges per unit area (Table 2)(Liu and Weng, 2008;Li et al., 2013).
LSI, which is designed by McGarigal and Marks (1995) based on the
habit diversity index proposed by Patton (1975), describes the com-
plexity and compactness degree of the patch shape. It is known as a
factor aecting the park cool island (PCI) (Liu and Weng, 2008;Cao
et al., 2010). A concentrated shape has a low LSI value, while a com-
plicated shape has a high LSI value (Liu and Weng, 2008). The equation
for LSI is shown as below.
=×
LSI P
A
t
(1)
Pt is the total perimeter, and A is the total area.
2.6. Assessment of human thermal comfort
In this study, the physiologically equivalent temperature (PET) is
taken as thermal index to assess the cooling eect of green areas from
the point of view of the human thermal comfort. PET is dened to be
equivalent to the air temperature that is required to reproduce in a
standardised indoor setting and for a standardised person the core and
Table 1
The conguration of ENVI-MET for the simulation.
city Berlin
longitude, Latitude 52.52
°
N, 13.38
°E
elevation (m) 34
simulation date 08-09.06.2014
wind speed at 2 m (m/s) 2.06
wind Direction (0: N 90: E 180:S 270:W) 210 (Southwest)
roughness length (m) 0.01
initial temperature atmosphere (K) 298.5
whole domain (m
2
) 10,000
vegetation domain (m
2
) 2,500
vegetation types 5
conguration types 5
Fig. 3. (a). The mean hourly 2 m-air temperature measured on the walkway surrounded by three vegetation types in Tiergarten (lled circles) and the corresponding
simulated air temperature (squares). (b). The scatter diagram showing the correlation between the measurement and the simulation.
Table 2
Descriptions and equations for patch density and edge density.
Abbreviation Denition Equation Unit
Patch density PD Densities of
patches PD=
n
A
×
1
04
n = total number of
patches
A = total area
number/ha
Edge density ED Total length
of all edge
segments of
green space
per hectare.
ED=
×∑
=
e
10000
Ai1
n
i
n = number of
segment
e
i
=edge length
A = total area
m/ha
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
88
skin temperature that are observed under the conditions being assessed
(Höppe, 1999). PET applied in this study assessed human thermal
comfort (Table 3) by considering the meteorological condition of each
scenario, human metabolic heat exchange rate, and other individual-
related parameters such as age, gender, height, weight and clothing,
allowing a comprehensive assessment of the eectiveness of adaptation
measures.
The model RayMan Pro version 2.1 was used to calculate PET in this
study (Matzarakis et al., 2010;Lee et al., 2016). RayMan is well suited
for determining microclimatic changes in dierent urban structures, as
it calculates the radiation uxes of dierent surfaces and their changes
(Gulyás et al., 2006). In this study, the RayMan model was driven by
the meteorological data, which are exported from ENVI-met, including
air temperature, relative humidity, mean radiant temperature and wind
velocity.
3. Results and discussion
3.1. General conditions of cooling eects in 25 scenarios
Fig. 4 shows the diurnal variation of the mean cooling eect of 25
scenarios at 2 pm, 10 pm, and 5 a.m. In every scenario, the mean
cooling eect decreases as the time goes on from 2 pm to 5 a.m. The
cooling value is the greatest at 2 pm in all scenarios. Cooling eects at
10 pm are greater than that at 5 a.m. The highest mean cooling value
appears at 2 pm, reaching 6.3K in the scenario of Conguration 4 with
tree-big canopy, while the lowest one appears at 5 a.m., with 1.2 K for
Conguration 1 with 10 cm grass.
The dierences in cooling eects between dierent scenarios were
greater in daytime than that at night time (Fig. 4). The dierence in
cooling eects between dierent scenarios decreased after sunset.
Every scenario exerted obvious diurnal variation. This was because of
the strong daytime radiation, which leads to greater evapotranspiration
and a larger dierence between shaded area and un-shaded area. At
nighttime, the stomata close due to the lack of radiation, and vegetation
has almost no cooling eect from transpiration. Naturally, there is no
shades to distinguish green and impervious area at nighttime. Trees also
inhibit nocturnal long-wave radiative cooling because of smaller sky
view factor, while excess moisture increases the thermal capacity of the
soil and slows down surface cooling. As shown in Fig. 4, the dierence
in cooling between 10 cm and 50 cm grass is negligible.
In every scenario, the total green area was equal (Fig. 2), although
the conguration and vegetation type were dierent. In order to com-
pare the cooling eect of dierent scenarios, the size of areas with
cooling in excess of 1.5 K was estimated. Fig. 5 shows the percentage of
the total cooled down area featuring cooling in excess of 1.5 K.
In Fig. 5, most of the percentages greater than 50% are related to
scenarios with trees with canopies and scenarios with scattered or belt-
shaped conguration at 2 pm. The other secenarios are not able to cool
down more than 50% of the investigated area.
3.2. Eect of the patch density and edge density (PD&ED) of green areas on
cooling eects
Congurations 13 are congurations with dierent patch density
(PD) and edge density (ED). As the number of patches raised from 1 to
16, the PD increased from 1/ha to 16/ha, and the ED increased from
200 m/ha to 800 m/ha (Table 4). In order to concisely illustrate the
inuence of PD & ED on the cooling eect, the mean cooling eect and
maximum cooling eect of Tree- big canopy, Tree- small canopy and
50 cm Grass scenarios, which are the most representative vegetation
types, were compared (Fig. 6).
In terms of the mean cooling eect, when the vegetation type is
Tree-big canopy, there is a clear increase in cooling eect as PD & ED
increase. At 2 pm, the cooling of conguration 1 is signicant lower
Table 3
The comfort/sensation scale of the physiologically equivalent temperature
(PET) according to Matzarakis and Mayer (1997) developed for specic basic
conditions.
PET/°C Thermal perception Grade of physiological stress
4.0 Very cold Extreme cold stress
4.1-8.0 Cold Strong cold stress
8.1-13.0 Cool Moderate cold stress
13.1-18.0 Slightly cool Slight cold stress
18.1-23.0 Comfortable/Neutral No thermal stress
23.1-29.0 Slightly warm Slight heat stress
29.1-35.0 Warm Moderate heat stress
35.1-41.0 Hot Strong heat stress
41.1Very hot Extreme heat stress
Fig. 4. Mean cooling eect by dierent scenarios at 2 pm, 10 pm, and 5 a.m.
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
89
(1.96 K) than conguration 3, for trees with big canopy. However,
when the vegetation type changes, the trend starts to turn. When the
vegetation type is changed to Tree-small canopy, the stronger cooling
eect of Conguration 3 is no longer obvious. The dierence between
Congurations 1 and 3 is only 0.13 K at 2 pm. This slight dierence is
barely noticeable at 10 pm and 5am. When the vegetation type is Grass
50 cm, a reverse trend can be observed: the cooling eect decreases as
PD & ED increases. The cooling eect of Conguration 1 at 2 pm is
0.04 K higher than Conguration 3. These reversed dierences expand
to 0.1 K at 10 pm and 0.9 K at 5am.
The previous study (Forman, 1995) indicated that an increase in the
PD & ED of a green space enhanced the shade and the interactions
between the green space and its surrounding area. Therefore, more
scattered green spaces leaded to greater cooling eects. The results of
this study indicate that this conclusion is only valid when the vegeta-
tion type contains trees with big canopies. When the vegetation type
includes trees with small canopies, or even hedges and grass, this trend
tends to reverse.
It can be estimated that when the cooling ability and shade of a
single green patch is large enough, more scattered green spaces perform
better in terms of mean cooling eects. This is because the scattered
Fig. 5. The percentage of the area cooled down more than 1.5 K at three dierent simulation time steps.
Table 4
Patch density and Edge density (ED) of Congurations 13.
Conguration1 Conguration2 Conguration3
Patch density (PD)
(number/ha)
1416
Edge density (ED)
(m/ha)
200 400 800
Fig. 6. Mean cooling eect and Max cooling eect of Congurations 13.
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
90
green spaces provide more shade, and interact more with the sur-
rounding impervious area. On the contrary, when the cooling ability
and shade of a single patch is too small, the more scattered green spaces
have worse mean cooling eect, due to the reduction of the area of a
single patch.
In terms of the maximum cooling eect, green spaces with lower PD
& ED perform better in most cases. The maximum cooling eect of
Conguration 1 is always higher than that of Conguration 3. This is to
say, when total area is constant, green spaces with a more centralised
conguration have lower central air temperature (Fig. 7).
3.3. Eect of the land shape index (LSI) of green areas on cooling eects
In the comparison of congurations with vegetation types Tree-big
canopy,Tree-small canopyand Grass 50 cm(Fig. 8), Congura-
tions 4 and 5 always show clear advantages in terms of mean cooling
eect. The green areas in Congurations 4 and 5 both indicated the belt
shape. This greater cooling eect probably comes from the stretched
green space shape and the higher land shape index (LSI).
Studies in ecology have claimed that green patches with higher LSI
lead to greater ecological benets, because of better interactions with
the surrounding area (Vos et al., 2008). In a similar way, in this study,
green spaces with more complex shapes can provide greater cooling
eects.
To analyse the inuence of LSI, Congurations 2 and 4 were com-
pared. As shown in Table 5, despite having the same patch density and
total area, the LSI of Conguration 4 is much higher than that of
Conguration 2. This phenomenon is caused by the more stretched
shape of Conguration 4. According to the simulation data (Fig. 8, 9),
Conguration 4 always performs better in terms of mean cooling eect.
This advantage is clearer when the vegetation type is Trees-big canopy.
Therefore, it can be concluded that when the area and patch density are
constant, belt patterns with higher LSI perform better than those with
dotted patterns, in terms of cooling eects. This result is in agreement
with previous studies (Liu and Weng, 2008;Cao et al., 2010). When the
total area and vegetation type are xed, the longer the perimeter a
single patch has, the more shade is provided, and the greater the in-
teractions with the surrounding areas. In another words, high LSI in-
creases the cooling eciency of an integrated patch (Zhou et al., 2011).
3.4. Eect of the direction of greenbelts on cooling eects
In the comparison shown in Fig. 8, the mean cooling eect of
Conguration 4 is always higher than that of Conguration 5. The only
dierence between these two congurations is the direction of tree
Fig. 7. Simulated air temperature of Congurations13 at 2 pm (vegetation type: tree-big canopy).
Fig. 8. Mean cooling eect of three selected vegetation types.
Table 5
Patch density and Land shape Index (LSI) of Conguration 2 and Conguration
4.
Conguration 2 Conguration 4
Patch Density
(number/ha)
44
Land Shape Index 0.16 0.4
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
91
belts, which directly aects the ventilation conditions. The wind di-
rection was set blowing from South-West (210°). Conguration4, with
North-South (180°) tree belts, is closer to parallel with the wind di-
rection than Conguration 5 with West-East (90°) tree belts.
According to former research, vegetation with big canopies can
substantially aect ventilation (Wania et al., 2012). As shown in the
simulated wind eld, the ventilation conditions of Conguration 4 are
better than those of Conguration 5, out of the direction of green belts
(Fig.10). The maximum wind speed in Conguration 4 is 2.45 m/s and
the maximum wind speed in Conguration 5 is 2.20 m/s. The mean
wind speed in the canyon of Conguration 4 is 1.65 m/s, and the mean
wind speed in the canyon of Conguration 5 is 1.33 m/s. Green belts
which are close to parallel to the wind direction tend to form straight-
forward air channels. On the contrary, green belts which are closer to
perpendicular to the wind direction are more likely to block the airow.
As ventilation is critical to heat dissipation, congurations with less
ventilation store more heat internally. In addition, as shown in Table 6,
higher winds in the green belts in Conguration 4 carry heat (sensible
heat) and moisture (latent heat) away from the surface, and increase
these heat uxes. It results in the lower mean air temperature in
Conguration 4.
3.5. Eect of vegetation type on cooling eects
There were ve common vegetation types in the simulated sce-
narios. The mean cooling eect of dierent vegetation types in each
scenario were compared at 2 pm, 10 pm and 5am.The results shows that
Tree-big canopyvegetation type generates the largest cooling eect,
followed in descending order by Tree-small canopy, Hedges-shrubs,
Grass 50 cm and Grass 10 cm (Fig. 11).
Fig. 9. Simulated air temperature of Congurations 2 and 4 at 2 pm (vegetation type: tree-big canopy).
Fig. 10. Wind speed and direction in Congurations 4 and 5. The color indicates the wind speed in m/s and the wind direction is shown by arrows.
Table 6
Comparison of conguration 4 and 5 in terms of turbulent uxes.
Variable
(W/m
2
)
Conf. Sensible heat Latent heat
Conguration 4 187.81 105.66
Conguration 5 162.80 97.44
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
92
It is notable that the dierence in mean cooling eect between Tree-
big canopy and the other vegetation types is particularly large. In
comparison, the dierence between the other four vegetation types is
not obvious enough. In particular, at 2 pm in Conguration 4, the mean
cooling eect of Tree-big canopy is three times larger than the other
vegetation types. This result indicates that when it comes to the inu-
ence of vegetation type on cooling eect, canopy is the most eective
factor, directly blocking incoming short-wave radiation, thereby redu-
cing the absorbed heat.
On the other hand, when there is no signicant dierence in ca-
nopy, as the total leaf area increases, the cooling eects of vegetation
increase. Quite an amount of research has observed this positive cor-
relation between cooling eect and leaf area index (LAI). Because the
increased LAI of vegetation lead to increased shade and evapo-
transpiration (Hardin and Jensen, 2007;Shashua-Bar and Homan,
2000;Li et al., 2016). At 10 pm and 5 a.m. (Fig. 12,13), the cooling
ranking of dierent congurations is the same as at 2 pm. Due to the
lack of shade and transpiration, the dierences between dierent con-
gurations decrease.
3.6. Summary on the human thermal comfort
The mean physiologically equivalent temperature (PET) values of
each scenario at three representative times are shown in Fig. 14. The
PET values of 2 pm, 10 pm and 5 a.m. are distributed in the range of
38.353 °C, 2326.8 °C, and 20.122.7 °C. According to Table 3, PET
values from 13 °C to 29 °C are classed as pleasant, 35 °C to 41 °C as
strong heat stress, and greater than 41 °C as extreme heat stress. The
variation of PET values at 10 pm and 5 a.m. are very small; the values
are between 20.7 °C and 26.8 °C, which are all pleasant. At 2 pm, the
PET values are very high (average value is 50.6 °C); all of them are in
the heat stress range. The lowest PET values appear in Tree-big ca-
nopies scenarios, particularly at 2 pm. Tree-big canopy scenarios clearly
show cooler PET values. Fig. 14 shows that vegetation type Tree-big
canopy can improve PET by more than 15 K, conrming the importance
of using shade trees in urban green areas.
The PET dierences (D-value) of 25 scenarios, compared with a
surface covered by asphalt, were calculated (Fig. 16). The PET dier-
ences at 5 a.m. and 10 pm are very small, in every scenario at any time,
except for the scenarios with Tree-big canopies at 2 pm. At that time,
the D-value is much higher than other times. These results also high-
light the importance of shade in improving thermal comfort.
As shown in the Fig. 15, the dierence value of PET in Tree-big
canopy scenarios is clearer at 2 pm than at any other time. The PET
dierence between Tree-big canopy scenarios and an asphalt surface
varies between 5.3 K and 15.9 K at 2 pm. At other time, the dierence
range is lower than that at 2 pm (ranging from 2.1 to 4.9 K), but still
higher than in other scenarios. The trend of PET dierence in every
scenario with Tree-big canopy, shows the rising tendency at 2 pm. The
range is from 5.4 K (Conguration1 with tree-big canopy) to 15.9k
Fig. 11. Mean cooling eect of dierent vegetation types at 2 pm.
Fig. 12. Mean cooling eect of dierent vegetation types at 10 pm.
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
93
(Conguration5 with tree small canopy) (Fig. 16). According to Fig. 16,
the highest PET dierence is shown in Conguration 5, although the
highest temperature dierence is seen in Conguration 4 (Fig. 8, left) at
2 pm. At other times, PET dierences show a similar result as for
temperature (Fig. 16, Fig. 8, left).
This is due to the jointly eect of shade and ventilation. The pre-
vailing wind in every scenario blows from the South-West (210°) di-
rection, providing better ventilation in Conguration 4. As good ven-
tilation helps to reduce heat, in every Tree-big canopy scenario, almost
at every time, the Conguration 4 scenario is the best in terms of both
PET and temperature. At 2 pm, although the cooling eect of
Conguration 4 is higher than Conguration 5 (Fig. 1012), the PET of
Conguration 5 is higher than Conguration 4(Fig. 15).This is due to
another inuence factor shade. The sun is in the South at 2 pm.
Conguration 4 has a smaller amount of shade than Conguration 5,
xing the disparity induced by wind direction. At 2 pm, Conguration 5
has 196 m
2
(about 2%) more shade than Conguration 4. The shade
reduces the incoming short wave radiation and the mean radiant tem-
perature. Mean radiant temperature shows a direct relationship with
thermal comfort (Thorsson et al., 2007;Höppe, 1999).
4. Conclusions and Outlook
This study investigated the inuence of spatial congurations of
green areas on the microclimate and thermal comfort. The major
conclusions are summarized as follows:
Green areas can generate cooling eects and improve the thermal
comfort, especially at the daytime of hot summer days. The shade of
vegetation is the dominate factor of the cooling eect. In addition, the
ventilation and leaf area index (LAI) of green areas also inuence the
cooling eect obviously. By aecting the shade, ventilation and leaf
area index, the spatial conguration inuences the cooling eect of
green areas on microclimate and human thermal comfort.
The inuence of fragmentation of green areas depends on the ve-
getation type. When the vegetation type is Tree-big canopy, the cooling
capacity of each green patch is large enough. At this time, the mean
cooling eect grows as the fragmentation of green areas increases,
because more shade and interactions can be generated. When the ve-
getation types are Hedges-Shrubs and Grass, the cooling capacity of a
single patch is not large enough. In this case, the mean cooling eect
decreases as the fragmentation of green areas increases, due to the re-
duction of the area of a single patch.
In terms of the maximum cooling eect, green spaces with lower
fragmentation performs better in most cases. Because green spaces with
more integrated layout could achieve lower central air temperature.
The belt-shaped green area with the orientation parallel to the di-
rection of the wind produces the strongest cooling eect. The trees with
big canopy has the best cooling eect. The combination of trees with
big canopy and belt-shaped green areas along wind direction could
achieve the largest improvement of the microclimate and thermal
Fig. 13. Mean cooling eect of dierent vegetation types at 5 pm.
Fig. 14. The mean PET values of 25 scenarios at 2 pm, 10 pm and 5 a.m.
S. Sodoudi et al. Urban Forestry & Urban Greening 34 (2018) 85–96
94
comfort. The belt-shaped green area with higher shape complexity
forms lower mean air temperature, compared with the dotted green
area with lower shape complexity. Because the green areas with more
complex shape provided more interactions with the surrounding city
area.
The ventilation of green areas aected the microclimate and human
thermal comfort, because of its eect on the heat dissipation. The di-
rection of the belt-shaped green areas can inuence the ventilation.
When the direction of the green belt was parallel to the prevailing
winds, the ventilation condition was better, wind channels were more
likely to be formed. On the contrary, when the green belt was per-
pendicular to the prevailing winds, the ventilation condition was worse,
as more air ow was blocked by the canopy of vegetation.
For the origin of this studythe redevelopment plan for the
Tempelhof Airport in Berlin, the proposed questions can be answered
with these conclusions. In the green area that will be constructed in the
site of Tempelhof Airport, the preferred trees should be with big canopy
and high LAI, e.g. the broad leaved trees adapting to the climate in
Berlin as Quercus petraea, Fraxinus excelsior and Fagus sylvatica
(Vitasse et al., 2009;Zerbe, 2002). Based on the trees with strong
cooling capacity, the preferred layout of the green area could be more
scattered. The shape of each green patch is better to be more complex. If
the green area is designed as belt-shape, the optimal orientation of the
green belt is West-East, parallel to the prevailing wind direction of
Berlin.
In addition to the application on the Tempelhof Airport, the results
of this study can also be widely used in the climate-adaptive design and
planning of green areas, especially in the adaptation to the heat waves.
It should be noticed that, the results of the present study only provide
suggestions on the point of view of climate change adaptation and
urban heat island mitigation. However, in the practical urban landscape
design and planning, many other factors must be considered by the
designers. In order to be utilized in the practical design, the results of
climatological studies should be combined with the other factors con-
sidered in the design. The study of applying the results of climatological
studies into the practical landscape design and planning is going to be
conducted in our next study.
Acknowledgments
This study contributes to the research program Urban Climate
Under Change ([UC]
2
), funded by the German Ministry of Research
and Education (FKZ01LP1602 A). The authors are grateful to the pro-
ject Cooling eect of the historical garden Tiergartenin Berlin-
nanced by Berlin-Brandenburg Academy of Science (BBAW), German
Weather Service (DWD) for the data of the station Tempelhof, and
China Scholarship Council (CSC) for the nancial support. They also
thank David Mottram for his valuable proofreading of this paper.
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... [27,30,31,36,46,59]. Consequently there has been an increasing attention regarding the microclimatic benefits of UGI in terms of their forms and distribution [49,58]. However, the typical green design of public squares varies widely to accommodate different uses and the design is guided by aesthetic preferences whereas climatic considerations usually have not been a prime concern [8]. ...
... Refs. [49,58]. They showed that trees planted with sufficient distance to each other and not overlapping crowns have larger cooling effects as the area shaded by the trees is maximised. ...
... Thus, for night time cooling it is important to ensure sufficient ventilation as also suggested by Refs. [5,49]. ...
Article
People living in cities are experiencing summerly heat stress situations with severe consequences for their health, especially under climate change. Urban planning needs to address this problem focusing on areas where people are exposed to heat such as in public squares. Typical square designs include green infrastructure which can positively affect outdoor thermal comfort by providing regulating ecosystem services, but knowledge on the effectiveness of different design approaches is still limited. The present study assessed typical greening designs of rectangular public squares and their microclimatic influences during a hot summer day both during day and night-time conditions. By using a validated ENVI-met V4 model, thermal comfort values expressed by the physiologically equivalent temperature (PET) index were compared. Moreover, a novel greening design was developed and tested with the model. The results showed that at 3pm the greening design with most trees and trees placed in the sunlit areas of the square provided 5.2% higher cooling effect compared to the current greening, whereas for 4am the design without trees, but with meadow areas performed best (4.2% heat reduction). This led to the conclusion that for a comfortable thermal situation a climate adapted design has to include trees to maximize the shaded surface areas, while the main wind channel is kept free from trees, but planted with grass to minimize the heat storage. The number of trees and their placement together with the extent and placement of grass areas can thus serve as indicators for designing climate adapted public squares.
... In the discussion of improvement strategies, urban models are mostly complex blocks, and the simulation parameter settings are based on the actual urban situation's investigation and research data [15,[33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. The main strategies discussed are: (1) street tree planting [33][34][35][36][37][38][39][40], (2) improvement of albedo on pavement/wall surfaces [41][42][43], (3) increase of roof greening [44][45][46], and (4) changing planting species or LAD(Leaf Area Density) [25,; the main thermal environment exploration project is also temperature and comfort (PMV). ...
... In the discussion of improvement strategies, urban models are mostly complex blocks, and the simulation parameter settings are based on the actual urban situation's investigation and research data [15,[33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. The main strategies discussed are: (1) street tree planting [33][34][35][36][37][38][39][40], (2) improvement of albedo on pavement/wall surfaces [41][42][43], (3) increase of roof greening [44][45][46], and (4) changing planting species or LAD(Leaf Area Density) [25,; the main thermal environment exploration project is also temperature and comfort (PMV). In addition, simulations of the thermal environment before and after urban development can be performed [43], or simulation analysis can be done of the current urban thermal environment [48,49]. ...
... Based on the fundamental laws of fluid dynamics and thermodynamics, it can reproduce the outdoor microclimatic and physical situation of urban or rural spaces by accounting for the interaction of surface, plants, and air to evaluate the thermal conditions [51,52]. Several studies have shown that ENVI-met can simulate both spatial and temporal temperature and wind speed for the evaluation of microclimate in both simple and complex urban areas [20][21][22][23][24][25][26][27][28][29][30][31][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48]. A recent review by Tsoka et al. [53] also provided evidence of its suitability for urban climate analysis and examined mitigation strategies. ...
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In recent years, with the rapid increase in global warming and urbanization, urban heat island effects (UHI) have become an important environmental issue. Taiwan is no exception, with previous studies demonstrating serious UHIs in megacities. Although existing UHI research has utilized computer simulations to analyze improvement scenarios, there are few cooling strategy studies in actual blocks of Taiwan. Therefore, this study selected a block of a megacity in a tropical region of Taiwan as a case study by ENVI-met. Five improvement strategies were tested and compared to the current situation (B0): (1) Case C1 changed to permeable pavement, (2) Case C2 increased the green coverage ratio (GCR) of the street to 60%, (3) Case C3 changed to permeable pavement and increased the GCR in the street to 60%, (4) Case C4 changed to permeable pavement, increased the GCR in the street to 60%, and increased the GCR in the parks to 80%, and (5) Case C5 changed to permeable pavement, increased GCR in the street to 60% and parks to 80%, and set the GCR on the roof of public buildings to 100%. The results showed that the average temperature of the current thermal environment is 36.0 °C, with the comfort level described as very hot. Among the five improvement schemes, C5 had the greatest effect, cooling the area by an average of 2.00 °C. Further analysis of the relationship between the different GCRs of streets (SGCR) and the cooling effects revealed that for every 10% increase in the SGCR, the temperature of the pedestrian layer was reduced by 0.15 °C.
... In urban environments where such surfaces and materials are used to absorb more light, and where the amount of green space and shade in the environment is low, the highest number of thermal stress is observed (Lee, Mayer, & Chen, 2016). Some of the features of planting such as planting density (Unal, Uslu, Cilek, & Altunkasa, 2018), tree arrangement and location (Lee, Mayer, & Kuttler, 2020;Milosevic, Bajsanski, & Savic, 2017), tree planting pattern (Su, Zhang, Yang, & Ye, 2014) and orientation (Sodoudi, Zhang, Chi, Müller, & Li, 2018) are factors influencing the modification of micrometeorological conditions. ...
... As compared to similar studies, this reduction is relatively low; the cluster planting pattern exhibits a better cooling performance in hot and dry climates. When the direction of planting the green belt is parallel to wind direction, it helps reduce T a and improve thermal comfort due to ventilation and heat dissipation (Sodoudi et al., 2018). Trees affect micrometeorological conditions by controlling air flows, reducing wind speed and changing direction (Perini et al., 2018). ...
... In previous studies, the value of R2 lay between 0.52 and 0.96 and the amount of RMSE between 0.26 and 4.83 (López-Cabeza et al., 2018), so the model of ENVI-met was found to be valid in this study. In this study, empirical measurement was used to validate the software, but to evaluate the cooling potential of each of the planting patterns that did not exist in this real environment but were designed as scenarios, previous studies (El-Bardisy et al., 2016;Sodoudi et al., 2018) used this method to simulate the effects of different tree layouts and arrangements on thermal comfort. Other studies (Duarte, Shinzato, Gusson, dos, & Alves, 2015;Unal et al., 2018;Wang & Akbari, 2016) also evaluated the micrometeorological effects of vegetation using simulations of scenarios with various configurations that were different from the validated environment. ...
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The issues of local climate change, urban heat islands and improving outdoor thermal comfort in cities demand special attention in urban planning. This paper examines the effect of various plant arrangements, plant type, and the direction of the rows of trees against the prevailing wind on micrometeorological conditions and thermal comfort. The study area was simulated using the ENVI-met model. It was validated by comparing the values of the output parameters of the model with field measurements. Finally, the proposed scenarios were simulated in the model and identified after analyzing scenarios that displayed better performance in improving outdoor thermal comfort. The results indicated that the rectangular planting of evergreen trees in the outer rows and deciduous trees in the inner rows in a direction perpendicular to the prevailing wind produced the most optimal condition in improving outdoor thermal comfort (1.3 Predicted Mean Vote (PMV) reduction). Also, triangular patterns perpendicular to wind direction with evergreen trees brought out the weakest performance in improving thermal comfort (0.2 PMV reduction). The findings of the research can be used by landscape designers and urban planners to enhance green space designs, develop sustainable cities, and improve thermal comfort in residential areas.
... Forests 2020, 11, 825 2 of 18 phenomenon, which not only reduces the comfort level of the urban population, endangers their health, but also reduces urban biodiversity [6]. It is predicted that urbanization will continue to increase globally [7]. ...
... Urban trees can improve urban microclimate by reducing summer temperature [33]. Different planting and arrangement of trees may have diverse effects on air temperature modification [6,34]. We conducted a study on the regulating microclimate effect of 10 urban tree species of three configuration modes in Xi'an. ...
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Research Highlights: To demonstrate the effectiveness of configuration modes and tree types in regulating local microclimate. Background and Objectives: Urban trees play an essential role in reducing the city’s heat load. However, the influence of urban trees with different configurations on the urban thermal environment has not received enough attention. Herein we show how spatial arrangement and foliage longevity, deciduous versus evergreen, affect transpiration and the urban microclimate. Materials and Methods: We analyzed the differences between physiological parameters (transpiration rate, stomatal conductance) and meteorological parameters (air temperature, relative humidity, vapor pressure deficit) of 10 different species of urban trees (five evergreen and five deciduous tree species), each of which had been planted in three configuration modes in a park and the campus green space in Xi’an. By manipulating physiological parameters, crown morphology, and plant configurations, we explored how local urban microclimate could be altered. Results: (1) Microclimate regulation capacity: group planting (GP) > linear planting (LP) > individual planting (IP). (2) Deciduous trees (DT) regulated microclimate better than evergreen trees (ET). Significant differences between all planting configurations during 8 to 16 h were noted for evergreen trees whereas for deciduous trees, all measurement times were significantly different. (3) Transpiration characteristics: GP > LP > IP. The transpiration rate (E) and stomatal conductance (Gs) of GP were the highest. Total daily transpiration was ranked as group planting of deciduous (DGP) > linear planting of deciduous (DLP) > group planting of evergreen (EGP) > linear planting of evergreen (ELP) > isolated planting of deciduous (DIP) > isolated planting of evergreen (EIP). (4) The microclimate effects of different tree species and configuration modes were positively correlated with E, Gs, and three dimensional green quantity (3DGQ), but weakly correlated with vapor pressure deficit (VpdL). (5) A microclimate regulation capability model of urban trees was developed. E, Gs, and 3DGQ could explain 93% variation of cooling effect, while E, Gs, VpdL, and 3DGQ could explain 85% variation of humidifying effect. Conclusions: This study demonstrated that the urban heat island could be mitigated by selecting deciduous broadleaf tree species and planting them in groups.
... Moreover, the impacts of the spatial arrangement and features of green space on urban thermal environment are complex and should be further investigated. The warming and cooling effects of land cover and their characteristics can be explored using climate and statistical model simulations for the building of sustainable and resilient urban landscapes [77][78][79]. ...
Article
Urban heat islands (UHI) can lead to multiple adverse impacts, including increased air pollution, morbidity, and energy consumption. The association between UHI effects and land cover characteristics has been extensively studied but is insufficiently understood in inland cities due to their unique urban environments. This study sought to investigate the spatiotemporal variations of the thermal environment and their relationships with land cover composition and configuration in Xi’an, the largest city in northwestern China. Land cover maps were classified and land surface temperature (LST) was estimated using Landsat imagery in six time periods from 1995 to 2020. The variations of surface heat island were captured using multi-temporal LST data and a surface urban heat island intensity (SUHII) indicator. The relationship between land cover features and land surface temperature was analyzed through multi-resolution grids and correlation analysis. The results showed that mean SUHII in the study area increased from 0.683 °C in 1995 to 2.759 °C in 2020. The densities of impervious surfaces had a stronger impact on LST than green space, with Pearson’s correlation coefficient r ranging from 0.59 to 0.97. The correlation between normalized difference impervious surface index and LST was enhanced with the enlargement of the grid cell size. The correlations between normalized difference vegetation index and LST reached maxima and stabilized at grid cell sizes of 210 and 240 m. Increasing the total area and aggregation level of urban green space alleviated the negative impacts of UHI in the study area. Our results also highlight the necessity of multi-scale analysis for examining the relationships between landscape configuration metrics and LST. These findings improved our understanding of the spatiotemporal variation of the surface urban heat island effect and its relationship with land cover features in a major inland city of China.
... In Algeciras et al. (2016), the authors analyzed the contribution of street configuration toward the improvement of thermal comfort at pedestrian level, in the Old Town of Camaguey in Cuba. In Sodoudi et al. (2018), the authors investigated the influence of spatial configurations of green areas on the micro-climate and thermal comfort. In Tapias and Schmitt (2014), the authors proposed an automated tool to explore design spaces of urban forms according to measurements and empirical findings on the relationship between the outdoor thermal comfort, the micro-climate conditions and the building geometries. ...
Article
We develop a novel statistical decision-theoretic framework for urban design from an outdoor thermal comfort (OTC), social and economic perspectives. We combine those aspects into spatio-temporal risk measures which provide a compact representation of the overall quality of an urban design scenarios (UDS) set. We then formulate the selection of the optimal design as an optimization problem which is easy to solve and has a clear interpretation. To illustrate how our framework can be used in practice, we present a real-world study, which is based on a set of UDS that aim to improve the OTC of a specific site in Singapore. We show how our framework provides decision makers the flexibility to make choices relevant to their design objectives, leading to informed and interpretable design option selection.
... Urban areas are often overheated, which negatively affects the urban microclimate. One of the ways to cope with the problem of overheating is to adjust the built environment and greenery so as to achieve the minimal level of insolation or outdoor thermal discomfort during the summer months (Taleghani et al., 2014;De Abreu-Harbich et al., 2015Sodoudi et al., 2018Battista et al., 2019). ...
... The outputs of single-variable simulations show that tree quantities provide notable temperature reduction in LCZ-4, LCZ-5, and LCZ-6. The result agrees with some previous research results, which show that increasing tree coverage in open and bare urban areas can effectively mitigate thermal conditions significantly [77,78]. Comparing between Scenario A and Scenario B, it can be found that adding 60% more trees outweighs a 30% increase during the selected three hours. ...
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By exploring the cooling potential of tree quantity, ground albedo, green roofs and their combinations in local climate zone (LCZ)-4, LCZ-5, and LCZ-6, this study focuses on the optimum cooling level that can be achieved in open residential regions in Changsha. It designs and models 39 scenarios by integrating in situ measurement and ENVI-met numerical simulation and further compares cooling effects of various combinations of the cooling factors. The results show that (1) an increased number of trees and higher albedo are more effective compared to green roofs in reducing summer potential temperatures at street level (2 m high) in three LCZs. Negative correlations are observed in the pedestrian air temperature with trees and ground albedo; (2) the effects of cooling factors vary among different LCZ classes, with the increased 60% more trees leading to lower outdoor temperatures for LCZ-4 (0.28 °C), LCZ-5 (0.39 °C), and LCZ-6 (0.54 °C), while higher albedo of asphalt surface (increased by 0.4) is more effective in LCZ-4 (reaches to 0.68 °C) 14:00, compare to LCZ-5 (0.49 °C) and LCZ-6 (0.38 °C); (3) applying combined cooling methods can provoke air temperature reduction (up to 0.96 °C), especially when higher levels of tree quantities (increased by 60%) are coupled with cool ground materials (albedo increased by 0.4). The results can contribute useful information for improving thermal environment in existing residential regions and future residential planning.
... In (Algeciras et al., 2016) the authors analyse the contribution of street configuration towards the improvement of thermal comfort at pedestrian level, in the Old Town of Camaguey in Cuba. In (Sodoudi et al., 2018) the authors investigated the influence of spatial configurations of green areas on the micro-climate and thermal comfort. In (Tapias and Schmitt, 2014) the authors proposed an automated tool to explore design spaces of urban forms according to measurements and empirical findings on the relationship between the outdoor thermal comfort, the micro-climate conditions and the building geometries. ...
Article
We develop a novel recommendation system for optimal urban design from a socio-economic and Outdoor Thermal Comfort (OTC) perspectives. Currently, urban planners and designers do not have quantitative tools or methods at their disposal to incorporate various important effects into consideration in a systematic way. Our framework is based on risk measures which quantify and take into account various important design criteria such as OTC, spatial use in the form of exposure maps and the investment cost of the design. Our framework combines those criteria into a spatio-temporal risk measure to assess the performance of candidate urban design options. This is used as the basis for our optimal design problem formulation. We then formulate the problem as an optimisation problem which is easy to solve and has a clear interpretation. The objective of this paper is therefore twofold: on the one hand, we develop technical knowledge and methodologies to assist urban planners develop and prioritize competing urban design strategies. On the other hand, we demonstrate the importance of incorporating the uncertainty in climate models into the utility function when making policy decisions. To illustrate how our framework can be used in practice we present a real-world study, which is based on a set of urban design strategies that aim to improve the OTC of a specific site in Singapore. The ENVI-met micro-climate model has been used in order to calculate the spatio-temporal OTC process. We show how our framework can assist decision-makers make more informed and interpretable choices on how to select the optimal design option and where to allocate best their investment/resources.
Preprint
Human comfort and healthy environments lie at the core of every debate about outdoor spaces nowadays. Thermal comfort is a vital concern for planners and designers in order to produce a healthy and thermally comfortable environment, since the influence of different climates and user groups has been found to greatly alter the range of responses for thermal comfort calculations. This requires Post-Occupancy Evaluation (POE) with an integration of the appropriate outdoor thermal comfort (OTC) index. This paper presents the results of a detailed assessment for the OTC in hot arid zone (HAZ) using the most suitable thermal index. A case study was selected from Effat Campus, Jeddah, Saudi Arabia, to represent the HAZ. Subjective assessment employed the physiological equivalent temperature (PET) and the predictive mean vote (PMV) thermal indices in analysing the results of online and self-directed questionnaires while objective assessment employed a hand-held anemometer that was used to measure wind speed, whereas the wet bulb globe temperature (WBGT) SD Card Logger with a black globe thermometer 75 mm in diameter and emissivity of 0.95 was used to measure the globe temperature. The physical measurements were later used to calculate the mean radiant temperature (MRT) and consequently the PET index using RayMan Software. The results confirmed the significance of the shading strategy on OTC. The study revealed that there is no percentage as shading is permitting people to use the space; otherwise, in hot arid zone, the space would be completely unusable under the sun while the PET is more suitable than the PMV index.
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Reliable quantification of urban heat island (UHI) can contribute to the effective evaluation of potential heat risk. Traditional methods for the quantification of UHI intensity (UHII) using pairs-measurements are sensitive to the choice of stations or grids. In order to get rid of the limitation of urban/rural divisions, this paper proposes a new approach to quantify surface UHII (SUHII) using the relationship between MODIS land surface temperature (LST) and impervious surface areas (ISA). Given the footprint of LST measurement, the ISA was regionalized to include the information of neighborhood pixels using a Kernel Density Estimation (KDE) method. Considering the footprint improves the LST-ISA relationship. The LST shows highly positive correlation with the KDE regionalized ISA (ISAKDE). The linear functions of LST are well fitted by the ISAKDE in both annual and daily scales for the city of Berlin. The slope of the linear function represents the increase in LST from the natural surface in rural regions to the impervious surface in urban regions, and is defined as SUHII in this study. The calculated SUHII show high values in summer and during the day than in winter and at night. The new method is also verified using finer resolution Landset data, and the results further prove its reliability.
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Urban-rural difference of land cover is the key determinant of urban heat island (UHI). In order to evaluate the impact of land cover data on the simulation of UHI, a comparative study between up-to-date CORINE land cover (CLC) and Urban Atlas (UA) with fine resolution (100 and 10 m) and old US Geological Survey (USGS) data with coarse resolution (30 s) was conducted using the Weather Research and Forecasting model (WRF) coupled with bulk approach of Noah-LSM for Berlin. The comparison between old data and new data partly reveals the effect of urbanization on UHI and the historical evolution of UHI, while the comparison between different resolution data reveals the impact of resolution of land cover on the simulation of UHI. Given the high heterogeneity of urban surface and the fine-resolution land cover data, the mosaic approach was implemented in this study to calculate the sub-grid variability in land cover compositions. Results showed that the simulations using UA and CLC data perform better than that using USGS data for both air and land surface temperatures. USGS-based simulation underestimates the temperature, especially in rural areas. The longitudinal variations of both temperature and land surface temperature show good agreement with urban fraction for all the three simulations. To better study the comprehensive characteristic of UHI over Berlin, the UHI curves (UHIC) are developed for all the three simulations based on the relationship between temperature and urban fraction. CLC- and UA-based simulations show smoother UHICs than USGS-based simulation. The simulation with old USGS data obviously underestimates the extent of UHI, while the up-to-date CLC and UA data better reflect the real urbanization and simulate the spatial distribution of UHI more accurately. However, the intensity of UHI simulated by CLC and UA data is not higher than that simulated by USGS data. The simulated air temperature is not dominated by the land cover as much as the land surface temperature, as air temperature is also affected by air advection.
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