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Mitigating the Urban Heat Island Effect in Megacity Tehran

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Advances in Meteorology
Authors:
  • RUPD (Resilient Urban Planning + Development) GbR

Abstract and Figures

Cities demonstrate higher nocturnal temperatures than surrounding rural areas, which is called “urban heat island” (UHI) effect. Climate change projections also indicate increase in the frequency and intensity of heat waves, which will intensify the UHI effect. As megacity Tehran is affected by severe heatwaves in summer, this study investigates its UHI characteristics and suggests some feasible mitigation strategies in order to reduce the air temperature and save energy. Temperature monitoring in Tehran shows clear evidence of the occurrence of the UHI effect, with a peak in July, where the urban area is circa 6 K warmer than the surrounding areas. The mobile measurements show a park cool island of 6-7 K in 2 central parks, which is also confirmed by satellite images. The effectiveness of three UHI mitigation strategies high albedo material (HAM), greenery on the surface and on the roofs (VEG), and a combination of them (HYBRID) has been studied using simulation with the microscale model ENVI-met. All three strategies show higher cooling effect in the daytime. The average nocturnal cooling effect of VEG and HYBRID (0.92, 1.10 K) is much higher than HAM (0.16 K), although high-density trees show a negative effect on nocturnal cooling.
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Research Article
Mitigating the Urban Heat Island Effect in Megacity Tehran
Sahar Sodoudi,1Parisa Shahmohamadi,2Ken Vollack,1Ulrich Cubasch,1andA.I.Che-Ani
3
1Institut f ¨
ur Meteorologie, Freie Universit¨
at Berlin, Carl-Heinrich-Becker-Weg 6-10, 12165 Berlin, Germany
2Resilient Urban Planning + Development (RUPD) GbR, Eichendorstr. 1, 10115 Berlin, Germany
3Department of Architecture, Faculty of Engineering and Built Environment, University Kebangsaan Malaysia (UKM),
43600Bangi,Selangor,Malaysia
Correspondence should be addressed to Sahar Sodoudi; sodoudi@zedat.fu-berlin.de
Received  May ; Revised  July ; Accepted  July ; Published  September 
Academic Editor: Sultan Al-Yahyai
Copyright ©  Sahar Sodoudi et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cities demonstrate higher nocturnal temperatures than surrounding rural areas, which is called “urban heat island” (UHI) eect.
Climate change projections also indicate increase in the frequency and intensity of heat waves, which will intensify the UHI eect.
As megacity Tehran is aected by severe heatwaves in summer, this study investigates its UHI characteristics and suggests some
feasible mitigation strategies in order to reduce the air temperature and save energy. Temperature monitoring in Tehran shows clear
evidence of the occurrence of the UHI eect, with a peak in July, where the urban area is circa  K warmer than the surrounding
areas. e mobile measurements show a park cool island of - K in  central parks, which is also conrmed by satellite images. e
eectiveness of three UHI mitigation strategies high albedo material (HAM), greenery on the surface and on the roofs (VEG), and
a combination of them (HYBRID) has been studied using simulation with the microscale model ENVI-met. All three strategies
show higher cooling eect in the daytime. e average nocturnal cooling eect of VEG and HYBRID (., .K) is much higher
than HAM (. K), although high-density trees show a negative eect on nocturnal cooling.
1. Introduction
Tehran is Iran’s largest city, with the highest rate of urban-
ization. is megacity has a large densely-populated area of
 km2( million people during the night-time) which has a
major impact on human welfare (e.g., air and noise p ollution).
Both the concentration and the mobility of the popula-
tion, along with diverse social factors, have transformed
the infrastructure and spatial features of the metropolitan
area. According to [], urban development has directly
aected Tehran’s urban structure, which can be observed in
the metropolitan area. Previous investigations of the urban
growth processes of Tehran from  onwards show that
this city has undergone frequent transformations []. As an
eect of weak urban management, the rural population was
attractedtotheurbanareas,andthegrowingurbanization
ledtosevereenvironmentalchanges(e.g.,increasingbarren
lands).
e urban development of metropolitan areas greatly
increases urban environmental problems such as air pol-
lution, higher temperature, trac congestion and energy
consumption. As witnessed in the Tehran metropolitan area,
recent increases in the rate of urbanization deteriorate the
urban environment. One crucial problem of developing
urban areas is that of rising temperature, compared to rural
areas, known as the urban heat island (UHI). Emmanuel []
showed that the UHI is the accumulated warm air over the
high density of built-up areas. Asimakopoulos et al. []stated
that the constructions in urban areas absorb heat during the
day and re-emit it aer sunset, creating high temperature
dierences between urban and rural areas. According to Oke
[], the size and structure of the UHI vary in time and space
due to meteorological conditions and urban characteristics.
ere are various causes for the formation of the UHI in the
cities.eimportantfactorscausingtheUHIarethehigh
fraction of built-up areas (Buildings and pavements) as well
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Volume 2014, Article ID 547974, 19 pages
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Advances in Meteorology
as the lack of vegetation. e main reasons of the formation
oftheUHIarethelowalbedoandthehighheatcapacityof
built-up surfaces such as concrete or asphalt, which absorb
highamountoftheshort-waveradiationduringtheday,this
energy is then slowly released during the night as long-wave
radiation and leads to higher air temperature in the urban
areas. Evapotranspiration describes the transfer of latent heat,
from the earth’s surface to the air via evaporating water.
Urban areas tend to have less evapotranspiration relative to
natural landscapes, because of the lack of vegetation. is
reducedmoistureinbuiltupareasleadstodry,impervious
urban infrastructure reaching very high surface tempera-
tures, which contribute to higher air temperatures. With a
decreased amount of vegetation, cities also lose the shade
and cooling eect of trees. erefore greenery and using
high albedo materials are two strategies, which can mitigate
theUHI.elocationofcityhasdirectimpactonthe
formation of UHI. Dierent locations within a given region
vary greatly in their temperature, wind conditions, humidity,
precipitation, fog, and so forth. Such variations may be caused
by dierences in distance from the sea, altitude, direction of
slopes, and the general topography of the area []. Wind and
humidity are two main variables, which control the intensity
of UHI. e formation of UHI phenomenon depends upon
thesizeanddensityofthepopulation.Oke[]hascorrelated
UHI intensity to the size of the urban population. ey
have a direct relationship in which with higher population,
UHI intensity will be increased. Buildings and the density
of built-up area modify the wind, the radiative balance, and
the temperature conditions near the ground level as built-
up area have lower albedo and higher heat capacity com-
paring to natural surfaces. erefore, the fraction of built-
up area is a relevant factor in formation of UHI []. Urban
geometrycanimpedethereleaseoflong-waveradiationinto
the atmosphere. When buildings absorb incoming short-
wave radiation, they can re-radiate that energy as long-
wave energy, or heat. However, at night, due to the dense
infrastructure in some developed areas that have low sky view
factors, urban areas cannot easily release long-wave radiation
tothecooler,opensky,andthistrappedheatcontributesto
the urban heat island.
UHI intensity is greatest under stationary high-pressure
systems in stable air and clear-sky condition. It tends to
disappear if cloudiness and wind speed increases. e study
of Darand and Halabian []showsthatadominantstrong
ridge at the upper level ( hPa and  hPa, Azores high
pressure), which is associated with a thermal low pressure
on the surface over Pakistan and Iran is the most frequent
pattern from April until September in Tehran. is system is
accompanied by cloudless sky and a stable boundary layer,
which leads to a higher intensity of UHI. e ridge of
Azors high pressure in the upper level results in increased
concentration of pollution when pollutants expand to the
east and are located over north part of Iran. It blocked
the convection of surface air, reducing vertical mixing, and
thereby increasing air pollutant concentrations near the
ground. A subsidence is usually formed under the high-
pressure systems. e interactions between the low pressures
centered at the Pakistan to the north part of Iran with Azores
high pressure result in inversion occurrence in Tehran. is
patternisthemostfrequentandtheassociatedconcentration
of pollution is very high. More frequent heatwaves and stress
are projected over most regions of the densely-populated
urban areas for the next decades []. us, studying the
UHI eect and mitigation strategies is one of the major
priorities for planning the urban developments in megacities
like Tehran.
Greenery is a useful mitigation strategy to reduce the UHI
by cooling the air and providing shade and milder outdoor
boundary conditions as well as better thermal comfort. Many
researchers have studied the eects of greenery such as
green roofs [] and high albedo materials [,]on
reducingthelocaltemperatureandUHIintensity.
Table  summarized the results of some studies on mit-
igating of UHI in dierent cities. As it shows, dierent
UHI mitigation strategies have been applied. Reroong with
light colors and planting shade threes indicates the highest
cooling eect among the other strategies ( K). Applying
trees with broad canopies within residential yards led also to
, K temperature reduction, although other studies indicate
a cooling eect between ,–, K, which show the higher
cooling eect of shade trees in comparison to planting ground
level vegetation or using high albedo materials.
e UHI has a direct impact on human health due to
higher temperature, which is responsible for the morbidity
and mortality risks. Both the planning and policies for urban
environmental sustainability in the metropolitan area of
Tehran are impossible without a temperature mitigation pol-
icy. Mesoscale air ows such as sea breezes, mountain, valley
winds (slope-winds), and the urban heat-island circulations
partly control the local weather and pollutant transport
worldwide.
e main aim of this paper is to study the eects of green-
ery in connection with the high albedo materials in reducing
the UHI eect in the metropolitan area of Tehran and nding
a mitigation policy for adapting the infrastructure against the
microclimate changes. However, there is a lack of research
in the context of Tehran UHI. In this paper, we have applied
satellite data, mobile measurements and permanent stations
in order to study the UHI of Tehran.
e eect of greenery and high albedo materials on local
climate in the th district of Tehran has been simulated by
using the microclimate model ENVI-met []foratypicalhot
summer-day in Tehran. e simulations were carried out for
current situations as well as under three dierent mitigation
strategies.
2. Case Study Area
Tehran (󸀠N, 󸀠E), the fastest growing city in Iran,
with around million inhabitants and an area of  km2is
one of the largest cities in the world located on the southern
side of the Alborz mountain range and is limited to the
highlands and mountains in the North and East and to the
at plains and desert in the South and West (Figure ). e
average annual rainfall is approximately  mm, with most
precipitation falling in autumn and winter months. Due to
Advances in Meteorology
T : A review on maximum temperature in dierent cities, UHI mitigation methods, and their cooling eects as well as the percentage
of energy saving of dierent UHI mitigation strategies in dierent regions. Planting shade threes shows the highest cooling eect ( K) in Los
Angeles.
Reference Method Maximum
temperature
Reduction in
temperature Reported savings City/region
[]Reroong: lighter colors
and planting shade trees —K%LosAngeles
[]Replacing urban areas
with grass land
C (surface
temperature) . K Hong Kong
[]
New park nearby
commercial area ( km
downwind)
,C (surface temp.
Of grass eld) . K % Tokyo
[]Reducing anthropogenic
heat . K –% Tokyo
[]
Large scale increase in
surface albedo and
vegetative fraction
C .–. K %
(at peaks) USA
[]Building planting (walls
and roofs) ,C(m) .K %
[]
Tre e s w ith br oad
canopies within
residential yards
C.K
. mio l Water/year Phoenix
[]Roofs with high albedo
and vegetation ,C—,,%
Barcelona, Palermon,
Cairo
[]Low albedo, building
geometry wind eects ,C . K Singapore
T : An overview on climate data from the station Tehran-
Mehrabad (MHR), –.
Annual mean temperature .C
Annual mean precipitation  mm
Annual mean humidity %
Annual most frequent wind direction West
Mean number of clear days 
Mean number of inversion occurrences 
high elevation, aridity and latitude, the city experiences four
seasons. Climate can be extremely hot in the summer (with
midday temperatures ranging between  to C), and cold
in winter when night time temperatures can be below the
freezing point. Local precipitation is absent for  months of
theyearonthelowlyingareas.Synopticscalelowpressure
systems that originate from the Mediterranean propagate
over the region in spring and autumn, while in winter the
southward extension of the Siberian high pressure system can
advect cold temperatures over the Iranian Plateau. A large
scale easterly ow dominates the area in the summer, thought
to be associated with a circulation pattern named “the winds
ofdays”causedbyathermallowoverPakistan[].
erefore aside from the summer when large scale ow is
easterly, a westerly direction is preferred at other times but is
thoughttobemodiedbythemountains.Table  shows the
annual mean temperature, humidity, precipitation and other
variables from  to  in the station Tehran-Mehrabad
(MHR). Table  demonstrates the ideal condition for UHI
formation in Tehran (annual mean humidity of %,  clear
days per year).
Air pollution in Tehran is the biggest environmental
problem and determined even by its geographic position.
e Alborz mountain range, with an average width of about
 km. [], acts as an almost continuous wall. e altitude
of Tehran is between  to , meters above sea level
[]. ere is a major dierence in altitude between the
northern and southern par ts of the city which has a signicant
impactonthecharacteristicsofurbanspacesintheTehran
metropolitan area. In semiarid regions such as Tehran,
the climatic conditions regularly lead to cloudless weather
conditions with weak winds which can approximately be con-
sidered “ideal” as dened by Oke []. is is especially true
during summer when synoptic inuences are reduced and
depression disturbances are less frequent. e measurements
of Zawar-Reza et al. []inTehranconrmthetypicaldiurnal
cycle of an unstable, turbulent planetary boundary layer
during the day, where downward momentum ux is high
and hence wind speeds are increased. Towards the evening,
a stable boundary layer with decreased wind speeds develops
and keeps on growing throughout the night due to long-wave
radiative loss producing a sensible heat ux directed away
from the surface. is is important, as it emphasises the high
potential of a poorly ventilated nocturnal boundary layer
that contributes to urban heat island and elevated pollution
levels.
Several national studies have investigated trends in aver-
ages of maximum and minimum temperature and precipita-
tion in Iran. Alijani [], Jahadi Toroghi [], and Rasooli
[] have previously worked on some selected stations.
Advances in Meteorology
Tehran
Study area
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W02481216
5135󳰀
5130󳰀
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5135󳰀
5130󳰀
5125󳰀
5120󳰀
5115󳰀
5110󳰀
515󳰀
3555󳰀
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(km)
F :  urban districts in mega city Tehran. e dashed area
shows the th urban district.
Rahimzadeh and Asgari [,] using a set of high-quality
records showed signicant trends for minimum and maxi-
mumtemperaturesandprecipitationovermostoftheIranian
territory for the period –. ey found increasing
trends in minimum temperature for all stations under study
except Oroomieh, located in the northwest of the country.
e result for Oroomieh was conrmed by Pedram et al.
[]. In Iran, the outcome of the global warming is the
increasing frequency of extreme events such as heat waves,
torrential rains, or prolonged intensive droughts, hence
increasing danger and harm to the built environments and
people. Rahimzadeh and colleagues [] examined extreme
temperature and precipitation as indicative climatic variables
to determine recent climatic changes over Iran. ey present
the results from  synoptic stations which have been quality
controlled and tested for homogeneity and have less missing
data. For each station,  indicative climatic indices were
calculated. Marked negative trends for indices like frost days
(FD), ice days (ID), cool days (TXp), cool nights (TNp),
and diurnal temperature range (DTR) were found over most
regions of Iran. Conversely, positive trends were found for
summer days (SU), warm days (TXp), and tropical
nights (TR) over most regions of the country. For indices
such as Cold Spell Duration Index (CSDI) and Warm Spell
Duration Index (WSDI), both positive and negative trends
were obtained. Another study on coastal regions in Iran []
indicates that temperature indices are absolutely consistent
with warming. Warm nights, hot days, and hot day and night
frequencies increased, while cold spell and cool day and night
frequencies declined. Tagavi and Mohammadi []havealso
conrmedthedecreaseoffrequencyofcoldandincreaseof
warm events during the past years in Iran.
e analysis of intensity and frequency of extreme events
is a very important step in the process of planning and
designing the urban areas especially in the semiarid climate
of Iran. In these areas climate is very fragile and a sudden
change may cause destructive outcomes []. Beside the
more frequent heat waves, the rapid urbanization growth, and
the related UHI will also lead to higher temperature in the
future.
In Tehran, the change of land use from natural surfaces
to new built structures during recent decades and expansion
ofthecitysize,resultsinchangesofthenaturalsurfaceof
the earth. e changes of materials that cover the earths
surface aect the absorption of solar energy and the changes
of the shapes of the earth’s surface. Moving the large number
of population from the suburbs to the fast growing Tehran
urban area caused acceleration of urbanization, increasing
the city size and the density of built-up area, respectively.
In Tehran, the local winds are oen not strong enough to
circulate the air. Around % of the winds in Tehran have
speeds below  knots and have little impact on air circulation
in large built-up areas. Only % of the winds, which usually
blow in spring, late summer and early autumn, have speeds of
more than  knots and can clear the air []. e problem,
however, is that the major winds blow from the west, south,
andsouth-east,wheremostoftheindustriesarelocated.
Rather than cleaning the air, they can pollute the air further.
Only the winds from the northern mountains, with their
limited impact, blow in the right direction.
e on-going climate change is predicted to yield a grow-
ing number of extreme climate events which will increase
in both intensity and frequency. It will have a direct impact
on population health, morbidity, and mortality. Many studies
have previously shown that the elderly in a society are among
the most vulnerable to heat waves []. Over the past three
decades, Tehran has experienced warmer summers and high
amounts of heat-related mortality. Ahmadnezhad et al. []
showed that the total excess mortality during the last 
heatwaves in Tehran, which was about . deaths per heat
period. Figure  shows the average temperature maximum
of all recorded heat waves in Tehran from  to .
Table  shows also the length of the each heat wave, the
number of death during its period as well as the excess
mortality in percent [] for ve dierent categories (all
mortality causes, elderly people year, cardiovascular
causes, cerebrovascular causes, and respiratory causes). As
Figure  shows, during all heat waves the average maximum
temperature exceeds C in the whole period. e largest
death ratio ( death in  days) and also excess mortality
(.%) was occurred in ’ wave, which was the hottest
wave with the average of maximum daily temperature of C
(Table ). Mortality for + years had also signicant excess
mortality. e largest number of deaths (+) also happened
in heat wave of  and was about .% related to the
total deaths of . e total number of death during all
heat waves in the last decade was about , which has
a mean value about  deaths per heat wave. e people
older than  years are the most aected category by heat
Advances in Meteorology
T : Heat waves in Tehran from  to . Em indicates the excess mortality in percent and NofD indicates the number of death from
 categories: all mortality causes, elderly people  years, with cardiovascular, cerebrovascular, and respiratory causes [].
Year (number of heat waves) Length in days All causes > years Cardiovascular Cerebrovascular Respiratory
Em (%) NofD NofD NofD NofD NofD
 () .     
 ()      
 () .     
 () .     
 () .     
 .     
 ()  .     
 () .     
 () .    
 () .     
 () .     
 () .     
 () .     
 () .     
 .     
  .     
  .     
37.5
38
38.5
39
39.5
40
40.5
Average maximum temperature
Year and number of heat wave
2001 (1)
2001 (2)
2001 (3)
2002 (1)
2002 (2)
2003
2005 (1)
2005 (2)
2006 (1)
2006 (2)
2006 (3)
2006 (4)
2008(1)
2008(2)
2009
2010
2011
F : e average maximum temperature of heat waves in
Tehran from  to . e number in parentheses indicates the
order of the heat wave during the year. As it has been shown, three
heat waves aected Tehran in .
stress (%). People with cardiovascular problems are in the
second place (%), although the percentage of death due to
cerebrovascular and respiratory causes is under %. us,
reducing the temperature through mitigating of the UHI is
an important key for the urban and landscape planners in
Tehran in order to obtain better conditions of human comfort
and human health.
Although Tehran has  districts (Figure ), the simu-
lation of the eects of UHI mitigation strategies (greenery
and high albedo surface materials) on local climate for the
wholeofTehranisnotpossibleduetothelimitationsofthe
microclimate model ENVI-met. As a result, the th urban
district of Tehran was selected for simulations. e selection
of this urban district is due to its location, which is near the
T : Fraction of impervious surface area and vegetation in the
th urban district in Tehran.
Typ e of lan d use Percentage within th
urban district Area (h)
Impervious surface area
(pavement, buildings) .% .
Vegetat i o n ( t r e e c a n opy and
ground level vegetation) .% .
centre of Tehran and surrounded by the main urban axes of
the city and its trac congestion. is urban district has the
highest concentration of important business centres which
are an important function of the city and is one of the most
polluted districts in Tehran. e topography of the district
with North-South and East-West slopes have led to the unique
diversity of the urban space and its features, especially in the
northern partsof the district, which contributes to an unequal
distribution of pollution and provides a warm air canopy over
thecentralpart.eaverageadministrativedensityofthe
th urban district is about  persons per hectares. With an
area of  hectares, the latter is about .% of Tehran’s area,
andhadapopulationof,,peoplein,whichis
alsoabout%ofthecityspopulation.emainlandusesof
the zone included .% residential, .% transport, .%
public welfare services, .% general activities, .% military,
.% vegetation and nally .% urban utilities []. e
average height of the buildings is usually less than that of
the other large cities of the world (- story building and
the mean sky view factor is about , []. Tab l e  shows the
percentage of impervious surface area and vegetation in the
th urban district []. is district with around  percent of
built-upareahasnopotentialtoactasagreenenvironment.
Advances in Meteorology
Karaj
Tehran
Mehrabad
Geophysics
(km)
45 50 55 60
26
28
30
32
34
36
38
40
Longitude
Latitude
1
23
3
4
5
6
6
78
910
0
11 12
12
13
14
15
16
17
18
18
19
20
21
22
N
F : e location of Tehran and three meteorological stations Geophysics (GEO), Mehrabad (MHR), and Karaj.
e roofs have a total area about  h and can be used as
free spaces to mitigate the UHI regarding dierent methods.
Greenery constitutes . h of this urban district, which
indicates circa . m2of green space per capita, although
the amount recommended by the United Nations is about
– m2[]. e average per capita green space within an
urban area of . m2is very low compared with its average in
other Asian cities such as  m2in Singapore,  m2in Tokyo,
and . m2in Shanghai [].
3. Methodology
In the rst part of this study, the characteristic of the UHI in
Tehran has been analyzed using measured  m temperature
data from synoptic stations and mobile measurements in
urban and rural areas as well as the derived land-surface
temperature from Landsat. e second part of the study deals
with UHI mitigation strategies (e.g., high albedo materials
and greening). e inuence of high albedo materials and
greeningonmtemperatureandtherelativehumidityof
thethurbandistrictofTehranhavebeenstudiedandtheir
application as mitigation strategies has been discussed.
3.1. THE UHI Characteristic in Tehran. All of the meteoro-
logical data used for the UHI analysis were obtained from
the Islamic Republic of Iran Meteorological Organization
(IRIMO). e data include time series of daily mean, maxi-
mum and minimum  m temperatures, as well as the  hourly
values for three stations. ese stations (Figure )include
MHR(locatedatMehrabadAirport,representingtheurban
station with an altitude of ,. m), GEO (located at Teheran
Geophysics Institute, representing another urban station with
an altitude of ,.m), and KRJ (located at Agriculture
Institute in Karaj, representing a rural station with an altitude
of ,. m). e average altitude of Tehran is , m, with
an  m altitude dierence between its lowest and highest
points. In this study, two urban stations, MEHR (lower than
rural station) and GEO (higher than rural station), have been
considered in order to show the eect of urbanization as
well as the station elevation of the air-temperature dierence
between urban and rural areas, and thus no temperature
correction has been attempted. e station Tehran Mehrabad
has the longest record from  till . e stations
KRJ and GEO were installed in  and , respectively.
us, the time range of – was determined for the
investigating of the UHI due to the availability of the data
from GEO.
e stations used in the study are at dierent altitudes.
e dierence in minimum temperature serves as the pri-
mary indicator of the UHI intensity because the dierence is
normally most pronounced at night []. Mehrabad station
(MHR) is located in western part of Tehran where the airport
is situated. e Geophysics station (GEO) is located in the
th urban district and has been used to calibrate the mobile
instruments. In Karaj station (KRJ), the major land use is
agriculture. At Mehrabad, Geophysics, and Karaj stations, the
annual maximum and minimum dr y-bulb  m temperatures
indicate a slow upward trend during the period –
(Figure ).
It is clear that stations GEO and KRJ have very similar
characteristics during the day, which is shown as time-series
of annual mean maximum temperatures. e MHR station
with a lower altitude of between  and  m shows
the highest values. It indicates that the important factor to
determine the daily temperature is the altitude dierence. e
annual mean minimum temperature of these three stations
has also been shown in Figure . e similarity between GEO
Advances in Meteorology
1991 1993 1995 1997 1999 2001 2003 2005 2007 2009
6
8
10
12
14
16
18
20
22
24
26
Ye a r
(C)
MHR-min
KRJ-min
GEO-min
MHR-max
KRJ-max
GEO-max
F : e annual mean, maximum, and minimum dry-bulb
 m temperatures of stations GEO, MHR and KRJ during the period
–.
and MHR is much more than between GEO and KRJ (urban
and rural), although they have only a circa  m dierence in
altitude. It indicates that the urbanization and built-up areas
are important factors to determine the temperature at night
(- hours aer sunset). As it has been shown in Tab l e  ,the
frequency of occurrence of frontal systems and precipitation
is about %. In order to characterize the UHI, we use
only the cloudless days without any precipitation/frontal
passage in the period of –, when the UHI or urban-
inducedwarmingisthestrongest[]. e investigation
of a -year period of urban (MHR and GEO) and rural
(KRJ) minimum temperatures in Tehran clearly shows the
temperature dierence between these two areas (Figure ).
e largest UHI intensity was in the summer (July). For
MHR-KRJandforGEO-KRJ;JulyhasapeakUHIvalueof
. and .C, respectively. For both MHR-KRJ and GEO-
KRJ, the smallest UHIs exist in winter, with minimum values
in December, . and .C, respectively. e nding of a
stronger UHI in summer is/in contradiction with Zhou and
Shepherd’s [] and Kim and Baik’s [] investigation of UHI
in Atlanta and Seoul. Zhou and Shepherd found the strongest
UHI intensity in Atlanta in spring, while Kim and Baik found
stronger UHIs in the winter and fall, rather than the spring.
However,KimandBaikdidnotethatthetrendinUHIover
a -year period was greatest during the spring.
e emergence of spring vegetation may result in a
larger albedo gradient with the urban area, which would
cause a larger UHI. According to Unger et al. [], the
seasonal UHI pattern may be determined to a high degree by
urban surface factors. Cloudiness and wind speed may play
a negative role in the development of UHI. Liu et al. []
stated that the seasonal UHI variation tended to be negatively
correlated with the seasonal variation of relative humidity
and vapour pressure. Tehran is located in the semiarid,
continental climate. It has hot and dry summers, and cold
winters. e precipitation period is from November to May,
followed by a dry period from May to October with rare or
2
3
4
5
6
7
Januar y
Februar y
March
Apri l
May
June
July
August
September
October
November
December
(K)
MHR-KRJ
GEO-KRJ
F : e dierence between minimum temperatures of sta-
tions MHR and GEO and the rural station KRJ in the period of –
.
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
15
15.5
16
16.5
17
17.5
18
18.5
19
19.5
20
Ye a r
Tehran-Mehrabad
Trend
(C)
F : Mean annual  m Temperature from – in Tehran
Mehrabad station.
little precipitation []. e seasonal UHI pattern may be
aected by seasonal cloudiness in Tehran. e analysis of
mean wind speed from  to  in the Tehran Mehrabad
station shows that, in this period, the percentage of calm wind
increased and led to a reduction of the mean wind speed [].
Figure  shows the mean annual  m temperature from 
to  in the Tehran Mehrabad station. As has been shown,
the mean annual temperature increased in this  year period.
eredlineshowsthepositivetemperaturetrend.erapid
increase of  m temperature in Tehran is due to the rapid
growth of the population, which led to an increase in built-up
areas with low albedo materials and reduced sky view factors.
e number of private cars (per , people) changed from
intheyear,tointheyear[]. Besides this
quick change in the number of cars being used, the energy
consumption and resulting heat from new built-up areas
caused the high concentration of air pollutants in Tehran,
whichabsorbsandreemitslong-waveradiationandleadsto
stronger UHI. A comparison between Mehrabad/GEO and
Advances in Meteorology
Karaj in terms of climatic changes and physical development
over the period – reveals that the warming in the
urbanstationsisstronglyattributedtotheincreaseintheUHI
eect.
3.2. Satellite Images. A satellite image was employed to
map out the surface temperature in Tehran, to verify local
boundaries of urban and rural areas, and to identify hot spots.
ALandsatETM
+satellite image obtained on  July 
(due to limitations of the data in Tehran, only this map was
available) with spatial resolution of  m in panchromatic
band,  m in  visible bands, and  m in thermal band was
selected, which was provided by the Iranian Space Agency.
e image was radiometrically calibrated and geometrically
corrected to obtain the detected radiance data. e detected
radiance in thermal band was converted to the equivalent
surface temperatures using Planck’s blackbody formula. Land
cover was classied into several classes using the visible, NIR,
and SWIR bands. Instead of ambient temperature, the relative
surfacetemperaturecanbeseenfromthesatelliteimage.
Within the urban canyon canopy layer in the morning or
where wind velocity is low, the surface temperature is deter-
mined by adjacent surfaces. us, the surface temperature
map is acceptable for studying the UHI eect in the early
partoftheday.ereasonforusingthesatelliteimagesisto
acquire the urban-rural visual dierence at mesoscale rather
than to provide absolute values. Time limitations and the lack
of a traverse observational approach to ascertain the UHI
intensity limit the use of satellite imagery for exploring UHI.
us, in order to trace the gradual inuence of urbanization
on local climate, historical weather data were examined.
Figure  shows the rst observation of the clear surface
temperature boundary that coincides with land use in Tehran
and Urban District . e warm regions, represented by the
redandyellowcolours,aremostlylocatedinthecentral,
western, and southern parts of Tehran where the central
business district (CBD), industrial area(s), and airport are
located, respectively. On the other hand, the northern parts of
Tehranarerelativelycool,showningreen.isisduetothe
concentration of greenery and water bodies as well as having
less impact from the high-density urban developments. e
contrast between urban and rural areas hints at the prevalence
of the UHI eect in Tehran, although the satellite image only
provides the instantaneous observation during the daytime.
e surface temperature of study area (Urban District
) reveals some areas with either high or low surface
temperature. In Figure , Region  experiences the highest
temperature during the daytime, especially in the north and
west parts of the region mainly because of the lack of extensive
landscape and because it is close to the two main highways
(Hemat in the north and Chamran in the west). Similarly,
higher temperatures are observed in the east and northeast
parts of Region . is is also reasonable since the exposed
runway absorbs a lot of incident solar radiation during the
daytime and incurs high surface temperature. It might be
due to the bus station terminal located nearby. Regions 
and  are close to the central business district of Tehran
and neighbour with the Enghelab Street, the most crowded
Tehran
Study area
N
E
S
W01.5 369 12
5130󳰀
5120󳰀
5110󳰀
5130󳰀
5120󳰀
5110󳰀
3550󳰀
3550󳰀
3540󳰀
3530󳰀
(km)
Surface temperature (C)
High
Low
F : : Land surface temperature from Landsat on July th
.
street. In Regions  and , the eects of two parks (Saai and
Laleh) on surface temperature can be observed (park cool
island, PCI). e worst scenarios occur in some parts in
northeast and northwest of the district. e satellite image
showsabroadpictureoftemperaturevariancebetweenurban
and rural areas. is indicates the occurrence of UHI eect
during daytime in Tehran. e hot spots are observed on hard
surfaces in the urban context, since hard surfaces absorb lots
of solar radiation and cause high surface temperatures which
contribute to the increase in the ambient temperatures.
3.3. Mobile Measurements. e  hourly meteorological data
derived from the local weather station network can remedy
the temporal limitation of the satellite images, but, due to
the low number of stations in the urban area, it is dicult
to recognize the spatial distribution of  m temperature,
especially the  m temperature dierence between dierent
points which are located in parks and green areas as well as
within or between residential developments. As a result, eld
survey was carried out in order to complete the observations
derived from the satellite image and the weather stations.
e eld survey was done by persons holding the mobile
measuring instrument “Lutron LM-” at  designated
locations  m above the ground throughout the th urban
district of Tehran on a hot summer day,  July . is
professional measuring instrument has a tiny bone shape and
is lightweight, small in size, and is suitable for handling with
one hand. e instrument has a resolution of .Candthe
accuracy of ±(%rdg+
C).
Before starting measurement, the instruments were cal-
ibrated against the weather station “Geophysics,” which is
locatedinthethurbandistrict.emeasurementswere
Advances in Meteorology
(a) (b)
F : Mobile measurement in th urban district on July th , (a) :–: h; (b) :–: h.
carriedoutbypersons,everyminutes.emeasure-
ments covered dierent land uses such as parks, residential,
commercial, and industrial areas and public services. ey
were taken simultaneously at all locations in two sessions:
the day session between : and : h local time and the
night session between : and : h. For every particular
point, the temperature was calculated by averaging three
measurements in the same point. It should be noted that,
during the measurements, the instruments were shaded.
e temperature distribution at various locations dur-
ing the night- and day-times is shown in Figure .e
highest temperatures were observed mainly in industrial
and commercial land uses in the south of the district. e
industrial land uses generally have low-rise buildings and
the high temperature recorded in these areas is related to
the extensive usage of low albedo material in the buildings.
e high temperature of commercial buildings is related to
the use of concrete and dark stone which absorb most of
the solar radiation and later release it into the atmosphere.
A maximum daily temperature of .Cwasobservedat
theindustriallanduselocatedinEnghelabStreet.eother
areas, which had high temperatures (–.C), included
mainly the west, east, and north borders of the district
where the main highways (Chamran, Modares, and Hemat)
are located with high trac congestion, air pollution, and
the lack of vegetation cover. e lowest temperatures of
.Cand
CwereobservedintheSaaiandLalehparks
(park cool island, PCI). e central part (high density built-
up area) showed lower temperatures than the borders of
the district. Smaller sky view factor in this region leads to
cooler temperatures than the border area. e night-time
temperatures varied between .Cand.
C, and it was
found that the central part of the district was around -
C hotter than the other locations with greenery. is also
indicates the centre of the nocturnal UHI, which has shied
from the borders during the daytime to the central area. e
high density of buildings and air conditions (anthropogenic
heat) in this area leads to higher nocturnal temperatures. e
average temperature of .C was recorded in Laleh Park,
the large green area located in this district. e maximum
temperature of .C was still noted in industrial land use
inEnghelabStreet.eresultsoftheeldsurveyshowsclear
evidence of higher temperatures in the city centre than in
the green areas in th urban district of Tehran, with the
high density residential, commercial, and industrial land uses
showing around -C higher temperatures.
4. Numerical Modelling with ENVI-Met
ENVI-met [], a three-dimensional numerical model, was
employed to study the basic pattern of the urban eects on
microclimatic factors such as temperature, wind speed, and
humidity in the current situation of the th district of Tehran,
as well as under some UHI mitigation strategies. ENVI-
met is a tool for studying the surface-plant-air interaction at
microscale. We applied the ... version to simulate the
microclimate in this study. A user-specied area input le
dening the three-dimensional geometry of the investigated
area is required for each ENVI-met simulation. It includes
geocoded building dimensions (e.g., width and height), soil
(e.g., type and texture), surface (e.g., concrete or asphalt),
and vegetation types. e numerical model simulates aero-
dynamics, thermodynamics, and the radiation balance in
complex urban structures. It is designed for microscale
with a typical horizontal resolution from . to  m and
a typical time-frame of  to  hours with a time step of
 to  secs. is resolution allows small-scale interactions
between individual buildings, surfaces, and plants to be
analyzed. Typical domains are between a single street canyon
up to a few hundred meters. e model is designed for
microscale modeling due to the domain’s and the model’s
time limitations. Despite these limitations, ENVI-met has
been widely applied in dierent studies on UHI mitigation,
which demonstrates the model’s capability. Ng and colleagues
[]usedENVI-mettoestimatethecoolingeectsofgreen-
ing in a densely built-up area in Hong Kong. ey found out
 Advances in Meteorology
F : e location of study area in Tehran th urban district.
that roof greening was ineective for human thermal comfort
near the ground, due to the high building-height-to-street-
width (H/W). ey also found out that the amount of tree
planting needed to lower pedestrian-level air temperature
by around C was approximately  per cent of the urban
area. Another study investigated the eect of xeriscaping on
near-surface temperatures and outdoor thermal comfort for
two dierent areas in Phoenix []. Xerophytic trees have
strong UHI mitigation potential in existing xeric residential
areas in Phoenix, with greater cooling at microscales (.C)
versus local scales (.C)andduringnocturnal(:)versus
daytime periods (:). Yang et al. []evaluatedENVI-
met with eld data in terms of the thermal behavior of
dierent types of ground surface. e results show that
the model is capable of reasonably modeling the diurnal
thermal behavior of dierent ground surfaces and their
eect on air temperature and humidity. e simulated air
temperature and humidity were generally consistent with the
observations.
5. UHI Mitigation Strategies and Results
A densely built-up area in “urban district ” with higher UHI
intensity, as shown in Figure , was selected for simulation
(Figure ). e model area has a size of  m × m,
resulting in  × × cells with a resolution of  m. e
selected area has a dense residential building morphology,
quitecommoninTehran,withanaverageheightofm.e
geographic co-ordinates of the model area were set to .
latitude and .longitude.
ENVI-met simulations also require a conguration le
containing local soil, meteorological, and building input data
for model initialization in the study area. ese include  m
temperature and relative humidity,  m wind direction and
speed, specic humidity at  m, soil temperature and
relative humidity, building interior temperatures, thermal
conductivity divided by mean wall or roof-width mean, heat
transmission, and mean albedo for walls and roofs. ese
data were obtained from the measured data at Geophysics
station (GEO), which is located near the study area and
from the mobile measurements, respectively. Based upon
the preliminary analyses of temperature, wind, and relative
humidity obtained from GEO, a clear hot day ( July )
was selected for the simulation. On this day, the measured
data from GEO showed a maximum temperature of .C
and a minimum of .C, the mean  m temperature was
.Cwithclearsky,presentinghoursofsunshine.e
measured wind data conrmed the calm wind (. m/s)
from West. e relative humidity was  percent, which
is typical for a semiarid urban area such as Tehran in
summer.ebuildinginformationwasobtainedfromtypical
thermophysical properties of typical building materials in
this part of the th district.
In order to study the UHI, the simulations of : h
(approximate maximum temperature timing) and : h
(approximate minimum temperature timing) local time were
selected for the analysis. e model was simulated for  h
starting at  am on July th and ending at  am on July th.
is is because the best time to start is at sunrise and the total
runtime should be longer than  hours in order to overcome
theinuenceoftheinitializationandallowthemodeltospin
up. e weather parameters on July th were very similar
to  July . e main dierence is .K higher mini-
mum temperature and .K higher maximum temperature.
Advances in Meteorology 
CS HAM
VEG HYBRID
F : e current situation of the study area (CS) as well as with consideration of three mentioned UHI mitigation strategies; HAM:
high albedo materials; VEG: greenery; HYBRID: HAM+VEG.
e ENVI-met model was run for the simulation of the
current situation (CS) of “urban district ” of Tehran as well
as for three UHI mitigation scenarios.
Using ENVI-met,  dierent UHI mitigation strategies
were applied and their cooling eects and feasibility are
discussed as follows.
(i) Scenario : change current low albedo materials to
high albedo materials (HAM).
(ii) Scenario : cover the model area with greenery
(vegetation and green roofs, VEG).
(iii) Scenario : cover the model area with greenery along
with high albedo materials (HYBRID).
Figure  shows the current situation of the investigated
area (CS) as well as consideration of the three above-
mentioned UHI mitigation strategies. Greenery and vege-
tation reduced solar radiation and lowered near-surface air
temperatureduetoevapotranspirationandshadingandled
to better thermal comfort conditions. Due to the already
mentioned facts that greenery is the most widely applied
mitigation measure, which could achieve huge energy-saving
through temperature reduction in urban areas [,], it
has been applied in this study. Changing the albedo of
roofs, fac¸ades, and pavements is the other applied mitigation
method in this study, which is more feasible due to the
water shortage in some summers in Tehran. e last scenario
(Hybrid) combines the eect of high albedo materials and
greenery (green roofs and more vegetation).
e current material used in buildings in the investigated
area is concrete with an albedo of .. the material of roofs
and roads are asphalt with an albedo of .–., and some
parts of the study area are covered by soil with an albedo
of .–.. ere is a lack of vegetation cover in this area
(part of vegetation of whole model area: .%). In the rst
scenario, low albedo materials were changed to high albedo
ones, asphalt to bright asphalt with albedo of ., concrete
was covered with white coating with albedo of ., and soil
waschangedtolightcolouredsoilwithanalbedoof..Using
high albedo materials reduces the amount of incoming solar
radiation absorbed through building envelopes and urban
structures and thus keeps their surfaces cooler. e rst
scenario was selected because of the high value of sunshine
duration in Tehran. In the second scenario, .% of the
simulated area is covered by vegetation (grass and shade trees
with middle density canopies with a Leaf Area Index (LAI) of
). Aroung each building is covered by shrubs (Buxus hyrcana
hedges). Due to the fact that the cooling eect depends on
the size of the vegetated area, each free cell in the study area
has been covered by vegetation (grass) in order to obtain
the maximum potential cooling eect. e vegetation on the
roofsisconsideredasgrassandshrubs.esimulationisonly
for summer, therefore no perennial plant has been considered
for the simulation.
In the third scenario (HYBRID), the rst two UHI
mitigation scenarios were combined.
Figure , shows the  m potential temperature distri-
bution in the study area in the current situation (CS) on
a hot summer day (July ) at : and at : h local
time,respectively.Ashasbeenshown,maximumtemper-
ature in the current situation (circa C) occurs in roads
with low albedo materials (asphalt) and the areas with less
greenerylocatedinthewestandsouthwestoftheareaat
: h. e simulation results show that, in green areas
 Advances in Meteorology
CS
18.07.2009-15:00 [LT]
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0 50 100 150
x(m)
y(m)
CS
19.07.2009-03:00 [LT]
25 30 35 25 30 35
2m potential temperature (C) 2m potential temperature (C)
F :  m potential temperature distribution in the study area in current situation (CS) on a hot summer day (July th) at : and
: h loc al time.
(the points represent the trees), lower temperatures (circa
C) were observed. e residential area also shows a lower
temperature due to shading and the higher albedo of the
pavement. e maximum temperature decreased from C
at : h to .Cat:handoccurredintheeastern
part of the site in the current situation at : h due to the
wind advection from the west. It shows that advection and
near-surface turbulence can inuence the spatial distribution
ofmtemperatureinthisareaandsothemicroscale
warming or cooling eect can be expanded and reaches the
surrounding area.
Figure  shows the  m potential temperature dierence
between CS and each UHI mitigation scenario at : and
: h, respectively. In the rst scenario (HAM), the cooling
eect of high albedo materials can be seen especially in the
built-up area and over the roads at : h. In comparison
with the current situation, the temperature was decreased
between . and . K in the built-up area due to reected
incoming solar radiation. e temperature reduction is
higher over roads, which had an albedo increase of about
.(asphalttobrightasphalt)and,inthecurrentsituation,
showed the maximum temperature. In addition, maximum
and minimum temperatures decreased by . and . K,
respectively.
At : h, built-up areas started to cool slowly, and,
in comparison with the current situation, the temperature
decreased by . and . K. In addition, the middle part of
the site (the residential area) was cooler than other parts
when compared to current situation. It is clearly due to higher
albedo change in this part (circa .).
When greeneries (green roofs/more vegetated areas with
middle density canopy trees) were added in the second
scenario (Figure , VEG-CS), the temperature of urban areas
was reduced by about - K in daytime (: h). While the
greenery decreased the temperature due to shading (in case
of trees) and evapotranspiration (in the case of all vegetation
types), there was still higher temperature on the roads. Green
roofs and Buxus hyrcana hedges contributed to decrease the
temperature in the housing areas (local eect) by about . K
at : h, which is similar to the cooling eect of middle
density canopy trees in the northeastern part of study area in
thedaytime.ereductionoftheairtemperatureinthearea
by more vegetation cover is smaller at night-time compared
to daytime. Although the trees in consideration have a middle
density canopy with a LAI of , they reduce the long wave
radiation loss due to the smaller sky view factor and are
responsible for a lower rate of cooling in the night-time. e
temperature reduction in the housing area can reach . K at
night-time, which is in agreement/line with the other studies
[,]. In this scenario, all free spaces including roofs are
covered by vegetation in order to estimate the maximum
cooling eect of vegetation for a typical hot summer day in
a semiarid climate.
In the third scenario (HYBRID), the combination of
greenery and high albedo material was examined in order
to test how these two strategies together can aect the near
surface potential temperature (Figure , HYBRID-CS). e
temperaturewasreducedupto.Kinthiscase.eresults
show that HYBRID strategy leads to an overall cooling in
thewholestudyareaat:h,whilethecoolingisfocused
Advances in Meteorology 
HAM-CS
18.07.2009-15:00 [LT]
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18.07.2009-15:00 [LT]
HYBRID-CS
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050 100 150
x(m)
−4 2024
HAM-CS
19.07.2009-03:00 [LT]
VEG-CS
19.07.2009-03:00 [LT]
HYBRID-CS
19.07.2009-03:00 [LT]
050 100 150
x(m)
−4 −2 0 2 4
Dierence: 2m potential temperature (K) Dierence: 2m potential temperature (K)
F : Potential temperature dierence between CS and each UHI mitigation scenario at : and : h local time.
 Advances in Meteorology
Local time (h)
9 12151821 0 3
20
24
28
32
36
CS
HAM
VEG
HYBRID
2m potential temperature (C)
F :  m potential temperature time series simulated by
ENVI-met from : July th  till : th  for the
current situation, as well as under consideration of three mentioned
UHI mitigation strategies.
in the middle part at : h. Figure  shows that the park
coolislandintensityishigherinthedaytimethaninthe
night-time. It is due to the radiation trapped in the northern
park, where middle density canopy trees are packed and lead
to a reduction of long-wave radiation loss during the night.
e rst and second scenarios also contribute to reduce the
temperature singly, while the third scenario makes a strong
contribution to reduce the ambient temperature.
Figure  shows the  m potential temperature time series
simulated by ENVI-met from : July   till :
forthecurrentsituation,aswellastakingthethree
above-mentioned UHI mitigation strategies into considera-
tion. In this gure, the mean value over the whole simulated
areaisplotted.eresultsshowthatthemeantemperaturein
the current situation is under-estimated by ENVI-met. As has
been mentioned, the minimum and maximum temperatures
of the Geophysics station, which is near the study area,
were recorded at .Cand.
C, although Figure 
shows a maximum of C and a minimum of .Cin
the current situation. e cooling eect of scenario HAM
is eective only from : to : h (about . K); aer
: h there was no eective cooling. e VEG scenario
shows a cooling of about Conaverage,whichdecreasesin
the night-time. e HYBRID scenario had the same shape
as the last two scenarios, but it leads to greater cooling
(onaverage.K)withamaximuminthedaytime.Asthe
Figure  demonstrates, the last two scenarios can bring about
nocturnal cooling and can mitigate the UHI eect.
In order to understand the local eect of trees and bushes,
as well as higher albedo buildings and pavements, three
dierent points in the study area have been selected and their
temperaturetimeseriesplotted.Figure  shows the location
1
2
3
F : e location of three dierent points in the study area.
Point 1
Local time (h)
9 12151821 0 3
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CS
HAM
VEG
HYBRID
2m potential temperature (C)
F :  m potential temperature time series at Point .
ofthesethreepointsinthestudyarea.erstpointislocated
on the sidewalk between two buildings in the residential area.
Point  is located in the northern park, and Point  is located
in a low-density build-up area, surrounded by some trees.
Figure  shows the  m potential temperature time series
of Point . Although the point is located in the densely built-
up area, changing the albedo has little cooling eect, with a
minimum at night-time. e VEG and HYBRID scenarios
have a much greater cooling eect, especially aer : h.
e maximum cooling is at : h with a value more than
K with the HYBRID scenario. e temperature time series
of Point  is shown in Figure .eHAMscenarioshows
no inuence on the  m potential temperature. A signicant
similarity can be seen between the temperature time series
under the VEG and HYBRID scenarios. ey both show a
maximum cooling of . K between :–:, then cooling
strongly decreases and shows a value of . K at : h, what
is due to the dense trees in the northern park, which trap the
heat due to the smaller sky view factor.
Figure  shows the temperature time series of Point .
It is quite similar to the time series of Point . e single
Advances in Meteorology 
Point 2
Local time (h)
9 12151821 0 3
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CS
HAM
VEG
HYBRID
2m potential temperature (C)
F :  m potential temperature time series at Point .
Point 3
Local time (h)
9 12151821 0 3
20
24
28
32
36
CS
HAM
VEG
HYBRID
2m potential temperature (C)
F :  m potential temperature time series at Point .
dierence is the smaller nocturnal cooling under VEG and
HYBRID scenarios at Point , which shows the positive eect
of greenery in the residential area, where Point  is located.
As Figure  shows, relative humidity of . percent
was observed in the built-up area of the current situation in
daytime, while it increased by between  and  percent in the
last two scenarios (shown only for VEG). Evapotranspiration
in the northern park brings about an increase in the dew point
temperatureandraisestherelativehumidity.Italsoincreased
between  and  percent when the last two scenarios are taken
into consideration in comparison with the current situation
at night-time (not shown). is increase in relative humidity
leads to better human comfort conditions (optimal level
%–%). e vegetation reduced wind speed in the second
and third scenarios is due to the tree density in the northern
part. In the cross-comparison of the three scenarios for wind
speed, the wind speed became high in the rst scenario with
no vegetation. Higher wind speed zones appear in the street
canyon due to the channel eect from the two sides of the
blocks.
e ENVI-met simulation supported the data generated
from eld measurement. It indicates that greenery along with
high albedo material has a signicant cooling eect of up
to . K on the surroundings during both, day- and night-
time, which can save a huge amount of energy, which is
normally used for air conditioning. In addition, ENVI-met
simulation shows that the lack of greenery and materials
with high albedo may cause bad thermal condition (higher
temperature and lower relative humidity) especially in urban
areas with hard and low albedo surfaces. Wind strength and
direction can aect the size of the cooled area around a green
space, which has to be investigated in further studies using
mesoscalemodels.DuetothelimitationofENVI-met,itwas
notpossibletosimulatethewholeofTehran.
6. Discussion and Conclusion
isstudyhasinvestigatedtheUHIcharacteristicinmegacity
Tehran and suggested some mitigation strategies regard-
ing their feasibility. Population growth, the increase in the
number of cars, energy consumption, and the resulting heat
from new built-up areas have all caused stronger UHI and
a high concentration of air pollutants in Tehran. e largest
UHI intensity was recorded in summer (July) with a mean
valueof.Koveryears()andthesmallestone
was recorded in winter, with an average minimum value in
December about . K. A Landsat  ETM+ satellite image
from a hot summer day was employed to map the surface
temperature in Tehran, to identify hot spots. For the study,
a high density built-up district with low albedo materials
was selected (Urban District ). Mobile temperature mea-
surement in this area in  time sessions (:–: h and
:–: h) on a typical hot day ( July ) was carried
out. A maximum daily temperature of .Cwasobservedat
industrial land use located in Enghelab Street and the lowest
one (.C) was observed in the Saai and Laleh parks, which
shows the local eect of low albedo materials and greenery
on the temperature. e mobile measurement shows higher
temperatures compared to the permanent station GEO in this
district. e results of the eld survey shows clear evidence
of higher temperatures in the middle part when compared to
the green areas in th/urban district of Tehran, with the high
density residential, commercial, and industrial land use areas
showing a higher temperature of circa - K.
In the last part, three dierent UHI mitigation strategies
(high albedo materials, green roofs and vegetation, and
hybrid) were simulated for a high density built-up area in the
 Advances in Meteorology
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18.07.2009-15:00 [LT]
−6 −4 −2 0 2 4 6
Dierence: 2m relative humidity (%)
(b)
F : m relative humidity on July th  (a) in current situation and (b) its dierence from the case under VEG scenario.
th urban district of Tehran. e key result from this study
is the estimation of the cooling potential of these strategies
as UHI mitigation methods, especially in residential areas in
themegacityofTehranonahotsummerday(July).
e results from the ENVI-met simulations presented in this
study clearly show that using high albedo materials (HAM)
leads to a cooling of . K in daytime (: h), although
it is much lower (. K) in the night-time (: h). So it
brings only slight cooling in residential area during the night
and cannot be considered as an eective mitigation strategy,
although, due to the high number of hours of sunshine per
day in Tehran, reduction in the heat storage of sunlit surfaces
seems to be important. White roof coatings could also be
applied over asphalt shingles. When rst applied, these can
provideanalbedoupto.,whichmeansthatonlyper
cent of the suns energy is being absorbed as heat, which leads
to higher cooling compared to our results. However they
do become dirty due to critical air pollution in Tehran and
aer, a short time, their reectance may be reduced to about
..
Inthesecondscenario(VEG),allfreespaceswithin
the study–including roofs–are covered by vegetation (grass,
Buxus hyrcana, and trees with middle density canopy), in
order to obtain maximal cooling, which is generated only
by vegetation. e results show that the average cooling for
the whole area is about . K at : and . K at : h.
e nocturnal temperature decreased by about  K in the
residential area, which is much greater than the slight cooling
in the northern park. e results of this scenario conrmed
the results of Ng. [], which demonstrated that green areas
should constitute at least  per cent of the urban area to lower
the temperature by about C. In our case, the greenery covers
about  percent of the whole area.
e third scenario combines the last two scenarios
(HYBRID) and shows the greatest cooling. e average
cooling of this scenario is about . K at : h and . K at
: h, although the maximum cooling is about . K in the
green area between the buildings in daytime and night-time,
respectively.
is paper demonstrates the inuence of greenery com-
pared to high albedo materials in order to mitigate the urban
heat island intensity in megacity Tehran. As is shown, the
last two scenarios give promising insights into the benets
of urban green planning. Developing green spaces reduces
the air pollution and lters the particulate matter, on the
onehand,andreducesthenear-surfaceairtemperatureand
prevents the overheating of sunlit surfaces, on the other.
Although the eect of  m green roofs on the  m temper-
ature is smaller than the eect of surface greenery, their air
pollution ltering potentials are the same. If regular irrigation
is applied, then evapotranspiration should also be taken into
account, although, due to the lack of water in the soil in hot
summer, the evapotranspiration rate is low in Tehran. Trees
also present some disadvantages. ey reduce the wind speed
and lead to trap heat and humidity inside the urban canopy
layer, which causes warmer nocturnal temperatures as well
as cooler daily temperatures, when compared to free spaces
without vegetation, as has been shown for the Point , which
is located in the northern park.
Tehran is a part of a semiarid region in the world and
hasencounteredacutecrisesduebothtotheincreasein
the population and the corresponding increase in the need
Advances in Meteorology 
of water resources. e per capita water consumption rate
for Tehran was more than  litres per day in , which
is twice the international and even national level []. is
shortage is due to the low annual precipitation (ca.  mm,
[]) as well as low available water resources. Due to this
lack of water, especially during summers in Tehran, the
feasibility of the mentioned UHI mitigation strategies (e.g.,
the irrigation of green roofs by treated waste water) should
be considered and discussed by stakeholders.
AkbarifoundthatpeakenergydemandintheUSArises
circa – per cent for every  K increase in maximum air
temperature []. is means that if we are able to reduce the
maximum temperature by about -K (by cooling residential
areas with the VEG and HYBRID scenarios), then we can
reduce energy consumption by about – per cent, which
would be a huge saving in energy and would also lead to
better conditions of human comfort and serve to oset global
warming.
It should be further noted that, due to the limitation of
ENVI-met, it is not possible to make the simulation for the
whole city in order to investigate the size of the area which
would be aected by the increased cooling, although the
mesoscale models are able to simulate it, but, due to lower
resolution, are not able to show the localised or microscale
impact of the vegetation, for example, the eect of bushes
or trees near buildings. Coupling meso- microscale model
couldbeusefultoinvestigatethepotentialcoolingeectof
dierent strategies on dierent scales of climate change under
consideration.
Conflict of Interests
e authors declare that there is no conict of interests
regarding the publication of this paper.
Acknowledgments
e nancial support of the Ministry of Education and
Research in Germany as well as German Academic Exchange
Service (DAAD) within the frame of the project “Young
Cities-Developing Energy-Ecient Urban Fabric in the
Tehran-Karaj Region” is gratefully acknowledged. Authors
also acknowledge IR of Iran Meteorological Organization for
providing the data. Authors are grateful to Dr. Ahmadnezhad
from the department of Epidemiology and Biostatistics of
Tehran University for providing the mortality data.
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... This means that trees play a major and dominant role in improving the surface temperature of urban areas [27]. In Tehran, a study revealed that the maximum mitigation results occurred in the combined scenario and reached 1.5˚C on average, providing similar results to the urban tree scenario [28]. When five greenery planning scenarios were applied on three typical street canyons in Balbo, trees with green surfaces exhibited the best effect, reducing the PET by 2 °C. ...
... The performance of trees in urban areas includes providing shade and evapotranspiration [6,18,19]. Shade is more important than evapotranspiration for trees because it sets them apart from other types of vegetation that do not provide shade [25][26][27][28][29]. Numerous studies have shown that the physical characteristics of tree species, such as their shape, size, density, and leaf features, affect their shading and cooling effects [32][33][34][35]. ...
... The maximum PET reduction of 6.5˚C is quite similar to the PET reduction values between 1 and 6 ℃ for case studies conducted in Ho Chi Minh and Spain [26,29]. The slight enhancements in air temperature are also similar to case studies conducted in Dubai, Tehran, and Phoenix [27,28,31]. Additionally, the overall results and improvements in the PET values are similar to those of the two prior case studies conducted in downtown Cairo (although this study presents more promising microclimate enhancements during some hours) [66,67]. ...
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This study aims to develop an efficient urban tree strategy (UTS) to enhance the microclimate conditions of cities that suffer from heat stress and strong solar radiation, such as the metropolitan area of Greater Cairo. Cairo recently lost its limited greenery to enhance traffic. The proposed UTS aims to achieve a balance between enhancing microclimate conditions and considering the city’s water scarcity. It seeks to consider all strategic factors suitable for local conditions, including the selection of tree species (Step 1), the utilization of new technologies for irrigation (Step 2), and the optimization of the usage of an efficient number of trees (Step 3). When applying the strategy’s recommendations to a study area within Cairo’s downtown center and when testing different tree coverage percentages within urban canyons of various aspect ratios and orientations using ENVI-met, the microclimate conditions are significantly enhanced in certain streets during summertime compared to wintertime. Applying the UTS not only enhances thermal comfort but also helps to create a better comfort zone during certain hours. In one street, for example, there are average physiological equivalent temperature (PET) reductions of − 5.18° and − 6.36° at 16:00 and 17:00, respectively, which also changes the thermal comfort zone from extreme heat stress to very heat stress. The results show a strong positive correlation between thermal comfort enhancement and a reduction in the total mean radiant temperature (TMRT), verifying that shading plays a primary role in enhancing the microclimate conditions of urban canyons. Applying the UTS to the study area significantly enhances the microclimate conditions. Furthermore, through the implementation of irrigation technologies that are part of the UTS, water demand is reduced to only 15% when trees with larger canopies are used. Additionally, when the tree coverage percentage reaches 35 to 50% in some streets, it results in a significant enhancement in the PET.
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... Based on several UHI-related mitigation actions, the most effective methods are those with vegetation-based actions commonly observed as GOS, such as parks (Algretawee et al., 2019;Sodoudi et al., 2014). Semenzato and Bortolini (2023) even argued that this was the most effective approach. ...
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Purpose The potential for massive economic growth exists in Samarinda City due to the intensification of activities in built-up areas. This suggests the potential for increased urban disease in the relocation of Indonesia’s new capital city to a location adjacent to Samarinda. One of the most striking impacts is the urban heat island (UHI). The increase in this phenomenon can be addressed effectively and efficiently through the provision and arrangement of appropriate vegetation-based actions. Therefore, this study aims to identify priority areas of green open space (GOS) based on UHI levels. In addition, this study also aims to present alternative mitigation measures to reduce the risk of disasters due to UHI. Design/methodology/approach A mixed-method approach was used in this research, involving an initial land surface temperature analysis to identify the UHI class. This analysis was complemented by quantitative spatial analyses, such as scoring, overlay and intersect methods, to determine the priority level class and the typology of GOS priority. A qualitative analysis was also conducted through data triangulation or comparison methods, such as examining existing land use, GOS priority maps and spatial plan policies. Findings The findings show that the total UHI area in Samarinda City was 6,936.4 ha in 2019 and is divided into three classifications. In Class 1, the UHI area is very dominant, reaching 87% of the total area. Meanwhile, the main results identified two priority classes of GOS in Samarinda, namely, the medium and high categories with an area of 960.43 ha and 113.57 ha, respectively. The results also showed that there were 17 typologies associated with five alternative mitigation measures: green industry, greening parking lots, improving urban green infrastructure and buildings, urban greening and mining restoration. Research limitations/implications Specific to assessing UHI, image data were available only in medium spatial resolution, leading to a consequence of detailed accuracy. In addition, since the determination of mitigation considered local policies, the method should be used in other locations requiring adjustments to existing regulations, specifically those related to spatial planning. Originality/value This study makes a significant contribution to the understanding of the UHI phenomenon in Indonesia, especially in the urban areas of Kalimantan Island. In addition, the study presents new insights into alternative mitigation actions to reduce the risk of UHI. Innovatively, this study introduces a typology of regions associated with appropriate alternative mitigation actions, making it an important achievement for the first time in the context of this study.
... Their findings indicated that the InVEST UCM successfully identified some variations in Wuhan's surface-temperature responses. Sodoudi et al. [12] tested the HMI they developed for three urban areas with distinct structural layouts in Tehran, Iran. They achieved this by comparing linear regression analysis with land surface temperature (LST) data. ...
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Urban heat poses significant challenges in rapidly developing cities, particularly in countries like Bangladesh. This study investigates the cooling effects of urban green spaces in Rajshahi city, addressing a critical research gap in developing urban contexts. We examined the relationships among urban vegetation, heat mitigation, and temperature variables using the InVEST Urban Cooling Model and spatial analysis techniques. This study focused on three key relationships: Normalized Difference Vegetation Index (NDVI) and Heat Mitigation Index (HMI), HMI and Land Sur face Temperature (LST), and HMI and Air Temperature (AT). Analysis revealed a strong positive correlation between NDVI and HMI, indicating the effectiveness of vegetation in enhancing urban cooling. A robust inverse relationship between HMI and LST was observed (R2 = 0.78, r = −0.88), with every 0.1 unit increase in HMI corresponding to a 0.53 °C decrease in LST. The HMI−AT relationship showed an even stronger correlation (R2 = 0.84, r = −0.87), with each unit increase in HMI associated with a 2.80 °C decrease in air temperature. These findings quantify the significant role of urban green spaces in mitigating heat and provide valuable insights for urban planning in developing cities, underscoring the importance of integrating green infrastructure into urban-development strategies to combat urban heat and improve livability.
... The urban green area mitigates the UHI by lowering the temperature and providing shading. Several studies show that the maximum temperature difference between the inside and outside of the small green area can be 3 K [30]. After modeling, Section 4 possessed the highest area of vegetation cover among all sections. ...
... In this way, heat accumulation in urban areas can be prevented by reflecting more of the incoming solar radiation (Rosenfeld et al., 1998;Synnefa et al., 2008), even though more reflected sunlight from walls and the road can actually increase the perceived temperature of humans during the day. The second method is to reduce the heat island intensity by cooling the surrounding of the built-up areas and providing milder surface boundary conditions by changing the partition of the surface energy balance components in which latent heat fluxes are increased and sensible heat fluxes are reduced (Sodoudi et al., 2014). The cooling effect of green space on urban heat islands was investigated in many studies (Cui et al., 2021;Li et al., 2018;Rigolon et al., 2018;Deilami et al., 2018). ...
... This increase in stored thermal energy leads to a higher surface temperature and stronger thermal radiation of the materials leading to higher ambient temperatures. [12] The temperature rise has adverse effects on the materials themselves [15,16] as well as negative 42 ecological [17] and health effects for people living within the UHIE-affected area [18,19] The Institute of Transportation Infrastructure Engineering (ITIE) of the Technical University of Darmstadt has conducted research on the characterisation of the vertical permeability of porous asphalt by asphalt petrology methods in lieu of the more laborious methods currently in use. ...
Chapter
Stewart and Oke introduced the local climate zone (LCZ) scheme that has over the past decade garnered global recognition for being the most meticulous land classification system yet. LCZ illustrates classes and sub-classes that are local in scale, climatic in nature and zonal in representation. The LCZ framework comprehensively analyses the influence of morphological parameters and anthropogenic activities on the urban environment. The immensely disturbed environment is the aftermath of human-induced (mostly irreversible) alterations across micro, local and meso scales. Extensive land use and land cover transformations coupled with mushrooming population are rapidly transforming cityscapes and the climatic regime globally. A growing body of literature has established multifarious impacts of intensifying heat in urban areas. This has led the researchers to invent and hone systems that categorize land, interpret the climatic variabilities and thus combat vulnerabilities. This chapter deliberates upon three key aspects: (1) urban configuration and the magnitude of UHI in high-density cities; (2) various spatial classification frameworks and (3) applicability of LCZ scheme through multiple investigations conducted globally. Congested LCZs experience elevated temperatures at the canopy and surface level during the night whereas the sparsely-built LCZs record much lower temperature both during the day and night.
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Urban greenery is a strategy to improve the thermal environment in urban areas affected by heat islands and global warming. These phenomena can harm the citizens’ quality of life. Researchers have investigated the thermal benefits of urban vegetation, but only a few have explored its complexities across diverse urban scales. Understanding these variations is critical for precise analysis, customized solutions, efficient resource allocation, and enhancing urban living quality while promoting sustainability and climate resilience. This paper reviews 250 scientific articles about the relationship between greenspace and the urban thermal environment published between 2010 and 2023 through urban scales. It summarizes the parameters and findings of greenery’s contribution to cooling the urban environment. The data reveal that most studies concentrated on the block scale, public open spaces, neighborhoods, parks, grouped vegetation, mixed arrangements, high vegetation, spatial parameters, and the use of air temperature data to report their findings. The cooling-effect evidence shows that the block scale has an average mitigation range of 0.7–2.7 °C, the neighborhood scale of 1.1–2.9 °C, and the city scale of 0.5–2.2 °C. Furthermore, it is critical to define reliable research methods and perform thorough software validation to assess model performance and establish guidelines for urban-landscape design accurately.
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Ozone and nitrogen pollution of the urban outdoor air in Tehran, a megacity of 10 million inhabitants with heavy urban traffic, strongly affects the health of its citizens. Therefore, monitoring of ozone (O3) and nitrogen (NO2) pollutants is crucial. The aim of this study is to investigate the seasonality of ground-level and the total column O3, the ground-level NO2, and their interactions. For this purpose, in 14 air quality measurement stations of Tehran Air Quality Control Company (AQCC), the OMI/MODIS Aqua products were used for a period of 10 years (2010–2019) as well as the TROPOspheric Monitoring Instrument (TROPOMI) data (2019–2022). The results of the stations analysis show that the monthly mean surface O3 concentration presents a maximum level in June and a minimum in December. The maximum amount of shortwave radiation flux and UV index was also in June and July. The minimum and maximum of the total O3 concentration column are located north of Tehran and southwest of the province, respectively, with a difference of 9DU between the two. Comparison of the total column and surface ozone data shows high concentration during the spring months. It was not possible to determine the overall relationship between nitrogen and ozone at the station scale. However, the total vertical column of the atmosphere and the tropopause height are mainly negatively correlated based on IMO/MODIS Aqua products. Finally, the analysis of TROPOMI data (2019–2022) confirmed the seasonal variability of NO2 and O3 over Iran while identifying correlation areas of O3 and NO2 over Iran, suggesting potential areas of O3 generation such as urban areas, oil/gas refineries, and natural barrier for pollutant dispersion such as mountains.
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In order to study the climate hazards, daily rainfall and temperature data of 61 weather stations over the country were obtained from the Meteorological Organization of Iran for the 1951-2007 period. The following indices are defined as indications of climate hazards: sultriness of the air or the heat index, cold days with minimum temperature below −5 • C, warm days with maximum temperature above 32 • C, the share of extreme rain days from the annual rainfall. The annual frequencies of these indices are analyzed and the overall hazard index is computed using the Analytical Hierarchical Process method. The results show that the southern coastal areas and central deserts are the most hazardous parts of the country, whereas, the northern Caspian coastal lands and mountainous regions experience lower hazard alerts. The problem of the northern parts is the cold days and that of the southern areas is the hot and humid days. Despite the relatively equal occurrence of torrential rains over the country, they are more harmful in the south than in the other parts of the country.
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Under the same urbanization pressure, the local climate in large metropolitan areas is also altered. This is especially apparent when certain climatic characteristics are considered, e.g. temperature, humidity and wind. In fact, all the main meteorological parameters are severely affected, resulting in the development of a local climatic regime, which is characterized by increases in temperature (the heat-island effect) and reduction of humidity and wind. Furthermore, in central areas particularly, the continuous replacement of vegetation with buildings and roads severely affects the radiation balance and this further influences the temperature regime of the environment. Under these circumstances the comfort index for those living in big cities is quite different from that for those living in suburban and rural areas.
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The need to respond to the rapidly changing city climate is particularly urgent in the tropics where the urban transition is currently at its peak. While the need is clearly felt by the tropical urban dwellers, texts that provide an overview of the problem and indicate possible design solutions are rare. This comprehensive reference will be welcomed by student and practising architects as well as other built envronment professionals engaged with the environmental effects of building in worldwide warm and humid climates.