Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania

Abstract

In the last decades, cities worldwide have experienced accelerated development, so that continuous urbanization and its impact is presently one of the most important topics in different fields of research. The main aim of this study is to identify the intensity of the atmospheric urban heat island in Cluj-Napoca city, through direct observations campaigns by using fixed points and transect measurements. The data has been collected over a period of 6 months (May–October 2015). The measurements have been performed mainly in anti-cyclonic weather condition, during the night, between 23:00 and 03:00. The profiles trajectories followed the main roads of the city on directions North–South, East–West, and Northwest–Southeast. 8 fixed points have been chosen in order to highlight best the temperature patterns in different Local Climate Zones (LCZs). The main findings of the study are the followings: the direct observations performed in three seasons (spring, summer and autumn) revealed the existence of an atmospheric urban heat island in Cluj-Napoca city; the warmest areas are compact high-rise and compact midrise, located in the eastern half of the city, where the temperature increases by more than 2.0 °C, as average value for all campaigns, but the maximum values, recorded in the summer are higher than 3.0 °C; the coolest areas are sparsely built areas and the large low-rise/water areas, where the temperature is quite similar to that recorded in the nearby rural areas (difference of 0.0-0.1 °C, as average values); local factors, such as mountain breeze and topography have a great impact on the atmospheric urban heat island configuration. © 2016, Reasearch Centre for Astronomy and Earth Sciences Hungarian Academy. All rights reserved.

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117Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.
DOI: 10.15201/hungeobull.65.2.3 Hungarian Geographical Bulletin 65 2016 (2) 117–128.
Introduction
In the last decades, cities worldwide have ex-
perienced accelerated development, so that
continuous urbanization is presently one of
the most important dimensions of contempo-
rary global change. Today 54 percent of the
world’s population lives in urban areas and
it is responsible for 76 percent of the energy
consumption and greenhouse gas emissions
(Grubler, A. et al. 2012). Moreover, the ur-
ban population is expected to increase to 66
percent by 2050 (United Nations, 2014). This
fact implies expanding urban land use and
a massive demand for built-up areas should
be anticipated in the next few decades (Seto,
K.C. et al. 2012; Song, X-P. et al. 2016). In Eu-
rope alone, at present, nearly 73 percent of the
population lives in cities and it is projected to
reach 82 percent by 2020 (European Environ-
ment Agency, 2010; Akbari, H. et al. 2016).
Beside the positive aspects of this process,
such as increasing the frost-free period or in-
come from be er paid jobs, the environmental
impact of urbanization is nowadays a major
problem discussed in urban planning and de-
velopment studies. One of the most important
consequences of the urbanisation process is
the intensifi cation of urban heat island (UHI)
(Herbel, I. et al. 2015). This phenomenon gen-
erates higher air and surface temperatures
compared to nearby rural areas and usually
Detection of atmospheric urban heat island through direct
measurements in Cluj-Napoca city, Romania
Ioana HERBEL, Adina-Eliza CROITORU, Ionu RUS, Gabriela Victoria HARPA and
Antoniu-Flavius CIUPERTEA1
Abstract
In the last decades, cities worldwide have experienced accelerated development, so that continuous urbaniza-
tion and its impact is presently one of the most important topics in di erent fi elds of research. The main aim of
this study is to identify the intensity of the atmospheric urban heat island in Cluj-Napoca city, through direct
observations campaigns by using fi xed points and transect measurements. The data has been collected over
a period of 6 months (May–October 2015). The measurements have been performed mainly in anti-cyclonic
weather condition, during the night, between 23:00 and 03:00. The profi les trajectories followed the main
roads of the city on directions North–South, East–West, and Northwest–Southeast. 8 fi xed points have been
chosen in order to highlight best the temperature pa erns in di erent Local Climate Zones (LCZs). The main
fi ndings of the study are the followings: the direct observations performed in three seasons (spring, summer
and autumn) revealed the existence of an atmospheric urban heat island in Cluj-Napoca city; the warmest
areas are compact high-rise and compact midrise, located in the eastern half of the city, where the temperature
increases by more than 2.0 °C, as average value for all campaigns, but the maximum values, recorded in the
summer are higher than 3.0 °C; the coolest areas are sparsely built areas and the large low-rise/water areas,
where the temperature is quite similar to that recorded in the nearby rural areas (di erence of 0.0–0.1 °C, as
average values); local factors, such as mountain breeze and topography have a great impact on the atmospheric
urban heat island confi guration.
Keywords: atmospheric urban heat island, direct measurements, Cluj-Napoca, Romania
1 Faculty of Geography, Babe-Bolyai University. 5–7, Clinicilor Street, 400 006 Cluj-Napoca, Romania.
E-mails: ioana.herbel@yahoo.com, croitoru@geografi e.ubbcluj.ro, rusionut22@gmail.com,
harpa_gabriela@yahoo.com, antonio3088@yahoo.com

Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.118
causes weather anomalies, a deterioration of
the living environment by increasing tempera-
tures and air pollution, by intensifying the heat
waves, and even a rise in mortality (Shepherd,
J.M. and Burian, S.M. 2003; Memon, R.A.
et al. 2008; Wong, K.V. et al. 2013; Unger, J. et
al. 2014). During heat waves, inhabitants of
urban areas may experience sustained ther-
mal stress both in day-times and night-times
whereas in rural areas people get some relief
from thermal stress at night (Unger, J. et al.
2014). Economically, an increase in energy
consumption for cooling is associated to UHI,
especially during summer time.
Under these circumstances, in the last
years, many researchers in di erent fi elds
such as climatology, urban planning or re-
mote sensing, focused on urban heat envi-
ronment and UHI (Li, J. et al. 2009; Unger, J.
et al. 2010; Kumar, D. and Shekhar, S. 2015).
The urban environment is a complex system,
involving concentrated human activities and
integrated ecosystem vulnerabilities that
could be seriously a ected by the intensity
increase of the UHI (Cohen, B. 2006; Hu, L.
et al. 2015). An UHI can be present at any lati-
tude, may occur during the day or night and
can be detected in any season as a function of
the local thermal balance. It is more intense
on calm and clear days and it is highly a ect-
ed by wind and precipitation (Santamouris,
M. 2015; Akbari, H. et al. 2016).
UHIs have been detected in many cities
of the world. Thus, by 2011, atmospheric
urban heat island (AUHI) observations on
221 cities and towns from all over the world
were reported in the literature (Stewart, I.D.
2011). The UHI intensity detected in several
European and Mediterranean cities is more
signifi cant at night and varies between 1.5 °C
and 12.0 °C, while in other cities (e.g. Athens
and Parma), maximum UHI intensity occurs
during daytime (Santamouris, M. 2007;
Founda, D. et al. 2015).
The main factors generating and a ecting
th
e UHI intensity are the urban architecture,
the type of urban materials, the population
density, the synoptic and local meteorological
conditions as well as the lack or small percent-
age of green and water surfaces inside the city.
Furthermore, artifi cial heating and cooling of
buildings, transportation and industrial proc-
esses introduce anthropogenic sources of heat
into the urban environment, causing distinct
and even enhanced UHIs, their intensities
showing an overall increase over the years
(Wilby, L.R. 2007; Akbari, H. et al. 2016).
Cities with high population density and in-
creased human activities, including intense
individual and public transportation, experi-
ence a higher UHI intensity during daytime.
In some of these cities there is a higher UHI
intensity in the summer (e.g. Rome, Madrid)
while in others in the winter (e.g. Lisbon).
Katoulis, B.D. and Theoharatos, G.A.
(1984) and Giannaros, T.M. and Melas, D.
(2012) reported a higher UHI intensity in the
night time and during the warm period in
Thessaloniki and Athens (Greece). Maximum
intensity of the daytime UHI in summer
was detected in other non-European cities
with subtropical or tropical climate, such
as Shanghai (Tan, J. et al. 2010) or Muscat
(Charabi, Y. and Bakhit, A. 2011), while in
Szeged (Hungary), during a one-year long
measurement campaign, the maximum in-
tensity was found in the night-time (Lelovics,
E. et al. 2014). It is concluded that reported
UHI varies considerably according to existing
studies in terms of maximum intensity and
season/time of occurrence. In addition to the
aforementioned reasons related to di erent
climatic features and thermal balance of the
cities, other reasons such as the application of
di erent monitoring protocols or the selection
of reference stations could largely infl uence
UHI estimations (Founda, D. et al. 2015).
Despite the large number of studies con-
ducted worldwide, in Romania only a few
studies have been performed on UHIs un-
til now. For Bucharest, several studies were
conducted by using direct measurements
data and satellite imagery (Cheval, S. et al.
2009; Cheval, S. and Dumitrescu, A. 2009,
2015). For Iai, direct measurements were
performed in the ‘60s and ‘70s (Gugiuman,
I. 1967; Erhan, E. 1971, 1979), while recently
the research topic in the same city was re-

119Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.
assumed by Apostol, L. et al. (2012). For
Cluj-Napoca only one study focused on the
surface urban heat island based on Landsat
imagery (Imbroane, A.M. et al. 2014).
The main aim of this study is to identify the
intensity of atmospheric UHI in Cluj-Napoca
city, through direct observations campaigns
by using fi xed points and transect measure-
ments.
Materials and methods
Study area
Cluj-Napoca is the second most popu-
lated city in Romania a er the capital city
Bucharest and the largest and most populat-
ed urban centre in Central Romania (Transyl-
vania). The city is located among three ma-
jor geographical units (Apuseni Mountains
– the northern part of Western Carpathians
–, Somean Plateau and Transylvania Plain).
Cluj-Napoca extends over 179.5 km2 and the
population exceeds 320,000 inhabitants.
The city is crossed over from West to East by
Someul Mic River over a length of 16 km. The
urban area (located between 300 and 400 m
a.s.l.) sprawls along its valley, generating the
dominant air fl ow inside the city. The urban
area expansion is limited by the topography
which consists mainly of hills up to 1,000 m.
The general climate of the region is conti-
nental with western oceanic infl uences. The
dominant concrete and asphalt landscape is
the result of the intense urbanization proc-
ess during the communist era, when neigh-
bourhoods with high-density blocks of fl ats
were built in the peripheral areas of the city.
However, this process did not a ect the histor-
ical centre, dominated by 18th and 19th century
buildings with massive baroque architecture.
Data used
The literature on heat islands reports five
methods commonly used for the evaluation of
this phenomenon: fi xed stations/points, mobile
transverse, remote sensing, vertical sensing,
and energy balances (Gartland, L. 2008). Air
temperature is usually measured at about 1.5
meters above the ground. In the areas where
measurements in fi xed stations are not avail-
able, the fi eld campaigns and transects stud-
ies involve the use of hand-held measurement
devices or mounting measurement equipment
on cars (Founda, D. et al. 2015).
Since each of the aforementioned methods
has its own limitations, we propose a study
based on a mixed approach that combines
observations in fi xed representative points of
the city with mobile transects along the street
network; then a comparison will be made be-
tween the recorded temperature values and
those measured in a nearby rural area chosen
as a fi xed point of reference.
Data collection
Atmospheric urban heat islands are often
weak during the late morning and throughout
the day and become more pronounced a er
sunset due to the slow release of heat from
urban infrastructure. The timing of this peak
depends on the properties of urban and rural
surfaces, the season, and prevailing weather
conditions (Akbari, H. et al. 2015). The great
majority of the measurements campaigns were
performed during the night, between 23:00 and
03:00 hours, but also a campaign of 24 hours of
continuous measurements was conducted.
The data used in this study was collected
over a period of 6 months (May–October
2015). Six di erent measurement campaigns
were conducted, two for each season, but
only one for each season was chosen to be
presented in this study. In order to obtain the
highest AUHI intensity, the measurements
were performed mainly at higher than nor-
mal pressure conditions, clear sky, and calm
weather or weak wind.
The mobile transect measurements usually
lasted about 3 hours and were performed by
car on three di erent crossing profi les with
multiple stops along the routes (Figure 1). The
profi les trajectories followed the main roads
of the city on directions North–South, East–

Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.120
West, and Northwest–Southeast. The profi le
points were chosen taking into account di er-
ent types of the urban tissue in the city and
each profi le had 17–22 measurement points.
The most representative profi le for AUHI
detection is CC’, as the altitude variation
alongside is very low (62 m). Profi le AA’ is
the least representative due to high altitude
variation along it (380 m) that could introduce
errors in AUHI intensity when no sounding
data for lapse rate are available, as is the case
in Cluj-Napoca. We chose to use profi le AA’
because it covers few important urban fabrics
and we consider that it is important to have
some measurements all over the city, even
though the results are not very accurate.
The temperature value was registered si-
multaneously every 5 minutes in the 7 fi xed
points located in the urban area, as well as in
the fi xed point in the nearby rural area.
The fi xed points used for observations were
chosen in order to best highlight the tempera-
ture pa ern in di erent Local Climate Zones
(LCZ) (Stewart, I.D. and Oke, T.R. 2012) ge-
nerated by di erent urban fabric types and
the nearby rural area (RP, Floreti village).
Thus, the code for the fi xed points and their
corresponding LCZ are listed below:
FP1 – compact high-rise (Mrti Neigh-
bourhood);
FP2 – compact high-rise (Mntur Neigh-
bourhood);
–
–
Fig. 1. Profi le points, fi xed points and reference point used in this study. AA’, BB’, CC’ = explanations are in the text

121Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.
FP3 – compact midrise (Gheorgheni Neigh-
bourhood);
FP4 – compact low-rise (city centre, Old
Town);
FP5 – open low-rise (residential area:
Andrei Mureanu Neighbourhood);
FP6 – large low-rise/water (Babe Park/
Sports Hall/Some River side);
FP7 – sca ered trees (park around Faculty
of Geography).
In order to improve the spatial resolution
of the fixed point network, we also used
the data recorded in Cluj-Napoca Weather
Station (WMO code: 15120), which is con-
sidered representative for sparsely built en-
vironment (FP8).
In order to perform measurements, we
employed 2 automatic Davis Vantage Pro2™
weather stations (for FP3 and FP7), 3 high pre-
cision Dostmann P400 mobile thermo-hygrom-
eters (for mobile transects) and 9 calibrated
normal (dry) meteorological thermometers.
In order to avoid errors in the measurement
process due to wind, a portable meteorological
shelter has been used for each point, except
for those with automatic weather stations. On
transects the data has been collected by us-
ing both a Dostmann P400 mobile thermo-hy-
grometer and a normal mercury thermometer
to improve the accuracy of the measurements.
The geographical coordinates of each measure-
ment point were recorded by using a GPS log-
ger application (GPS Logger for Android).
Data processing
For data processing the procedure previ-
ously described by Herbel, I. et al. (2015)
was used.
A er the data was collected, the altitude
corrections were performed for all the tem-
perature values recorded in fi xed and transect
points, as presented in (1). The mean lapse
rate used was 0.65 °C/100 m.
TBcor = TB + H x 0.65,
100
where TBcor is corrected temperature in point
B, located in the urban area (in °C); TB is the
–
–
–
–
–
temperature measured in point B, located in
the urban area (in °C);
ΔH = HB – HA ,
where HB is the altitude of the point B (m);
HA is the altitude of the reference point (A),
located in the nearby rural area (m);
In order to use the correct values of the
lapse rate for altitude correction, sounding
data should be used, but unfortunately this
data hasn’t been available for Cluj-Napoca
weather stations since November 2012.
Under these circumstances, we decided to
use the mean lapse rate of 0.65 °C/100 m, be-
cause during spring and summer campaigns
the air pressure was slightly above normal
pressure.
For the temperature recorded in fixed
points, only altitude corrections were per-
formed, while for transect points a time cor-
rection was also necessary.
The primary time deviation was computed
as a temperature di erence between tem-
peratures recorded in the transect point and
those recorded in the reference point (RP)
located in Floreti village.
If the temperature values were recorded at
the same time in both points (RP and point
on the profi le), the primary deviation was
obtained using
D = TPX – TR ,
where D is the di erence to be calculated for
a point X (on the profi le); TPX is the tempera-
ture measured in point (X) of the profi le at
time tx; and TR is temperature measured in
RP at time tx; tx is the time when the tempera-
ture was recorded in point X of the profi le,
given in hours and minutes.
The time corrections were computed only
for those points on the profi le for which the
measurement time did not coincide with the
one in RP.
Since the temperature value in the fi xed
points was collected every 5 minutes, in some
cases the temperature data on the profi le
points was collected between two measure-
(1)
(2)
(3)

Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.122
ments in RP. In this case, the correspond-
ing RP temperature value was obtained by
adding a time correction, calculated by us-
ing formula given in (4), to the temperature
measured in RP, for each profi le point where
the measurement time was di erent from the
fi xed point measurement time.
Ct = (T2 – T1)/n × d,
where Ct is the time correction to be added
to temperature recorded in RP; the time cor-
rected temperature is needed to get simul-
taneous values for the profi le point and for
the RP, in order to calculate the deviation be-
tween the two points; T1 is the temperature
measured in RP before the measurement in
the point on the profi le; T2 is the temperature
measured in RP a er the measurement in the
point on the profi le; n is number of minutes
between two consecutive measurements in
RP; d is the number of minutes between the
measurement in the profi le point and the
previous measurement in the RP.
A er the time correction performed on the
reference point value, the deviation of the
profi le point temperature was calculated by
using (3).
Results and discussion
Fixed points measurement
1. Spring measurements
In spring of 2015, the chosen campaign
was from May 13, 9:00 a.m. to May 14, 9:00
a.m. The measurements lasted 24 hours in
the fi xed points. During the data collection
where the followings: the sea level pressure
(SLP) was slightly above the normal values
(1,020 hPa) at the beginning of the interval
and decreased below the normal values at
the end of the interval. There was variable
convective cloudiness, especially during
daytime, covering sometimes more than 90
percent of the sky. No clouds were recorded
between midnight and 3:00 a.m. Over that
interval, the wind blew from Southwest with
a speed lower than 2 m/s; at the end of the
24 hour interval precipitation occurred. In
the second part of the night, a er 4.00 a.m.,
a cold front a ected the area with the end of
its squall line, generating important tempera-
ture variations and rainfall.
The temperature values recorded in the
fi xed points is presented in Figure 2. The in-
terval of relative thermal stability lasted about
5 hours (from 23:00 to 4:00). As expected, the
highest temperature values were recorded in
FP1 (compact high-rise), but also in FP3 (com-
pact mid-rise), while the lowest was specifi c
to the RP (Floreti village) and on the Some
river side (FP6). Between coolest and warmest
areas, there was a di erence of about 2.0 °C.
The city centre is also one of the hot-spots,
but more prominent in the daytime as a result
of high tra c in the area.
In the night, due to low elevation build-
ings of the Old City, the deviation from the
RP temperature is smaller than the one re-
corded for the compact high-rise and mid-
rise LCZ.
In the daytime, high temperature varia-
tions could be observed even for the same
point and the data collected in this interval
was inappropriate to evaluate the AUHI in-
tensity in Cluj-Napoca city. Therefore, for the
next campaigns we focused on the night-time
measurements.
2. Summer measurements
For summer of 2015, we chose to present
here the results of the fi rst campaign that
took place between July 22nd and July 23rd.
The temperature values were collected only
during the interval of relative thermal stabil-
ity: 23:00–02:00 h. As general weather con-
ditions, the SLP was slightly above normal
(1,017–1,018 hPa), there were no clouds and
the wind blew with a speed of 2 m/s from
Southwest and South-Southwest.
The temperature values decreased gradu-
ally from the beginning until the end of the
interval (Figure 3). The highest values were
identifi ed in FP1 (compact high-rise east),
followed by FP3 (compact midrise) and FP4
(compact low-rise), while the lowest ones in
the RP. In the interval of relative thermal sta-
(4)

123Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.
bility, the di erences between the tempera-
tures of the points located in the city area
and RP varied from 0.1 °C to 3.2 °C as mean
values, and from -0.4 °C to 3.8 °C, in terms of
extreme values (Table 1).
3. Autumn measurements
From the autumn measurement campaigns
for AUHI analysis, we chose to present the
one that started on October 24, 23:00 and
ended on October 25, 2:00 am. Synoptic con-
Fig. 2. Temperatures recorded in fi xed points during the spring campaign (May 13–14, 2015); hours are given
in local time (UTC + 3.00 h)
Fig. 3. Temperatures recorded in fi xed points during the summer campaign ( July 22–23, 2015); hours are given
in local time (UTC + 3.00 h)

Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.124
ditions analysis revealed that an anticyclone
was dominant in the area with SLP ranging
from 1,023 to 1,026 hPa. During the measure-
ments, the cloudiness varied from 80 percent
at the beginning of the measurements, to no
clouds at the end of the interval. The wind
blew from Southwest and South-southwest
with an average speed of 2 m/s.
The temperature decreased slowly over
the interval (Figure 4). The highest tempera-
ture values were registered, as in the other
measurement campaigns, in FP1 (compact
high-rise-east) but overall, the di erences
between the observation points from the
urban area and the RP were smaller than in
summer. In FP8 (the sparsely built type), the
temperature was lower than in RP, with an
average deviation of -1.0 °C. The di erence
between the warmest point (FP1) and RP was
smaller at the beginning (1.1 °C), due to high
cloudiness, reaching 2.3 °C at the end of the
interval. The mean deviation recorded in FP1
was 1.5 °C (Table 1).
It is worth mentioning that we chose two
fi xed points in di erent compact high-rise
areas with di erent local air circulation. The
fi rst one (FP1), located in the eastern part of
the city proved to be constantly the warmest
area in the city, situation that corresponds
to any theoretical approach. The second one
(FP2), located in the western part of the city,
is directly exposed to the mountain night
breeze blowing over the city from West
and Southwest. The cool air descends from
Western Carpathians with an almost constant
velocity of 2 m/s and it is the most common
wind blowing over the city in the night-time,
transporting the warmer air eastward. This is
the explanation for the fact that the western
compact high-rise area is cooler than the east-
ern one. During our campaigns we recorded
temperature di erences ranging from 0.4 °C
to 1.3 °C between the two compact high-rise
areas.
Profi le measurements
1. AA’ Profi le
The fi rst profi le used in this study extends
from the northern part of the study area to
the southern part over a distance of 15 km
(Figure 1) and the temperature was measured
in 17 points. Due to the topography of the
city, the altitude of the points ranges from
400 m to higher than 700 m. It is the only
profi le with such an important altitude dif-
ference. The presence of the altitude di er-
ence makes this profi le the least representa-
tive one, as presented at data collection. We
should note that the use of the altitude cor-
rections may lead to false UHI intensities in
the area of higher altitudes and under these
conditions we should be very cautious in in-
terpreting the data. Therefore, we focused
more on the segment between points 6 and
14, where the altitude variation was quite
small. As can be seen in Figure 1, the fi rst fi ve
and the last three points of the profi le are
located outside the built area of the city.
The seasonal variation of real time devia-
tion on AA’ Profi le compared to the nearby
Table 1. Altitude corrected deviation in °C compared to the rural area reference point (RP) by seasons
Fix points
Spring
(May 13–14)
9:00–9:00 h
Summer
(July 22–23)
23:00–02:00 h
Autumn
(October 24–25)
23:00–02:00 h
Overall
Av. Min. Max. Av. Min. Max. Av. Min. Max. Av. Min. Max.
FP1– compact high-rise
FP2 – compact high-rise
FP3 – compact midrise
FP4 – compact low-rise
FP5 – open low-rise
FP6 – large low-rise/water
FP7 – sca ered trees
FP8 – sparsely built
1.9
1.5
2.1
1.4
1.5
-0.1
1.2
0.4
0.9
0.5
0.9
0.8
0.5
-1.1
0.1
-0.5
3.0
2.3
3.0
2.0
2.5
0.8
2.6
1.8
3.2
2.6
2.8
2.6
2.8
0.1
2.7
0.6
2.8
1.5
2.5
1.8
2.3
-0.4
2.4
0.0
3.8
3.3
3.1
3.0
3.2
0.6
3.1
1.0
1.5
1.2
1.3
1.3
1.4
0.4
1.3
-1.0
1.1
0.8
0.8
0.7
0.6
-0.2
0.4
-1.6
2.3
1.6
2.0
2.3
2.2
1.0
2.1
-0.5
2.2
1.8
2.1
1.8
1.9
0.1
1.7
0.0
0.9
0.5
0.8
0.7
0.5
-1.1
0.1
-1.6
3.8
3.3
3.1
3.0
3.2
1.0
3.1
1.8

125Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.
rural area is shown in Figure 5. The fi nal
(southern) part of the profi le was usually
characterized by thermal inversions.
The shape of the AUHI can only be ob-
served in the fi rst part of the route for the
spring and summer measurements. In au-
tumn, thermal inversion occurred at higher
altitude. If we ignore the increased tempera-
ture values induced by thermal inversions
due to the topography and to the weather
conditions (and not by the urbanization proc-
ess) at the last three points of the route, the
highest intensity of the AUHI could be ob-
served in the summer (with deviation vary-
ing up to 3.0 °C), followed by spring (up to
2.0 °C), and autumn (up to 1.5 °C).
2. BB’ Profi le
The second profi le has a length of 18 km
(Figure 1) and lower altitude variations com-
pared to the fi rst one. The average altitude of
the profi le points is 350 m, except the two fi nal
(South-East) points where the altitude increas-
es to more than 450 m. This altitude di erence
is also associated to thermal inversion phe-
nomena developed between the southern high
hills and the city area. They generate higher
temperature deviations compared to RP at the
end of the route (Figure 6) for the campaigns
conducted in May and July. The AUHI on BB’
profi le can be clearly identifi ed in spring and
summer, but not in October, when the tem-
perature recorded in the central part of the
city was not much higher compared to that
measured in the rural area.
In terms of AUHI intensity on this profi le,
the highest deviation occurred in the sum-
mer with a value reaching up to 3.0 °C in the
central area of the city, while the lowest was
recorded in the spring (up to 1.3 °C).
3. CC’ Profi le
The third route is the most representative
for AUHI detection as it has the lowest alti-
tude variations among the points, of only 80
m. The altitude along the profi le ranges from
300 m, in the fi rst point of the profi le, to 380
m (ASL) in the fi nal point which coincided
with the RP.
CC’ Profi le extends over 20 km along the
most important road trajectory of the city
(from East to West), from Cluj-Napoca air-
port to the RP (Figure 1). Its trajectory in-
tersected three fi xed points located in the
Fig. 4. Temperatures recorded in fi xed points during the autumn campaign (October 24–25, 2015); hours are
given in local time (UTC + 3.00 h)

Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.126
Fig. 5. Temperature deviation compared to RP along
AA’ profi le. Dev = deviation; Prp = profi le point
Fig. 6. Temperature deviation compared to RP along
BB’ profi le. Dev = deviation; Prp = profi le point
Fig. 7. Temperature deviation compared to RP along
CC’ profi le. Dev = deviation; Prp = profi le point
eastern compact high-rise area (PF1), the
compact low-rise area (PF4), and the rural
area (RP). Under these circumstances, we
used this route also as a quality control of
the data measured in the fi xed points.
The AUHI can be very well emphasized
on this profi le (Figure 7) for all seasons con-
sidered, but the values for summer are the
highest, with more than 3.5°C in the eastern
compact high-rise area.
During the campaign conducted in au-
tumn, the most signifi cant deviation could
be observed on the second half of the route,
denoting the presence of a thermal inversion,
as the altitude sharply increases between
points 15 and 17.
The high values from the beginning of each
CC’ profi le correspond to “Avram Iancu”
International Airport area (point 3 is in the
very front of the airport), which became
urbanized enough in the last decade to be
considered as a non-rural area. Points 5 and
6 on this profi le are located in an open fi eld
area, as well as points 19 and 20. The temper-
ature di erences recorded in those two simi-
lar areas (open fi eld) can be also explained
by the air circulation (night breeze), which
transports the warm air from the city to the
eastern–northeastern areas.
Conclusions
The analysis of direct observations performed
in three seasons (spring, summer, and au-
tumn) revealed the existence of an AUHI in
Cluj-Napoca city.
The warmest areas are compact high-rise
and compact midrise areas located in the
eastern half of the city, where the tempera-
ture increases by more than 2 °C, as average
value for all campaigns, but the maximum
values, recorded in summer are more than
3 °C higher. They are followed by compact
high-rise areas located in the western part
of the city, compact and open low-rise and
sca ered trees areas, where the temperature
as an overall average is 1.7–1.9 °C higher,
while the coolest areas are the sparsely built
and the large low-rise/water areas, where the
temperature is quite similar to that recorded
in the nearby rural area (deviations from the
RP are between 0.0–0.1 °C, as average values)
(Table 1).

127Herbel, I. et al. Hungarian Geographical Bulletin 65 (2016) (2) 117–128.
The profi le measurements also emphasized
the AUHI dome, for all the campaigns.
Local factors, such as air circulation
(mountain breeze descending from Western
Carpathians) and topography have a great
importance to AUHI confi guration. Thus,
usually, due to mountain breeze the AUHI at
night is elongated eastward, and sometimes
isothermia or even thermal inversions can
be identifi ed.
Acknowledgements: This work was partially support-
ed by the Sectorial Operational Program for Human
Resources Development 2007-2013, co-fi nanced by
the European Social Fund, under the project number
POSDRU/159/1.5/S/132400 titled Young successful
researchers – professional development in an inter-
national and interdisciplinary environment.
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