Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania 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 bett 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 diff 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 patt erns in diff 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 (diff 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, Babeş-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 diff 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 aff 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 aff 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 aff ecting the 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 diff erent climatic features and thermal balance of the cities, other reasons such as the application of diff 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 Iaşi, 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 aft 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 –, Someşan 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 Someşul 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 aff 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 aft 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 diff 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 diff 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 diff 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 patt ern in diff erent Local Climate Zones (LCZ) (Stewart, I.D. and Oke, T.R. 2012) ge- nerated by diff erent urban fabric types and the nearby rural area (RP, Floreşti village). Thus, the code for the fi xed points and their corresponding LCZ are listed below: FP1 – compact high-rise (Mărăşti Neigh- bourhood); FP2 – compact high-rise (Mănăştur 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 Mureşanu Neighbourhood); FP6 – large low-rise/water (Babeş Park/ Sports Hall/Someş River side); FP7 – scatt 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. Aft 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 diff erence between tem- peratures recorded in the transect point and those recorded in the reference point (RP) located in Floreşti 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 diff 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 diff 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 aft 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. Aft 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, aft er 4.00 a.m., a cold front aff 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 (Floreşti village) and on the Someş river side (FP6). Between coolest and warmest areas, there was a diff 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 traffi 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 diff 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 diff 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 diff 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 diff erent compact high-rise areas with diff 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 diff 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 diff 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 – scatt 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 diff 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 diff 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 scatt 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. REFERENCES Akbari, H., Bell, R., Brazel, T., Cole, D., Estes, M., Heisler, G., Hitchcock, D., Johnson, B., Lewis, M., McPherson, G., Oke, T.R., Parker, D., Perrin, A., Rosenthal, J., Sailor, D., Samenow, J., Taha, S., Voogt, J., Einter, D., Wolf, K. and Zalph, B. 2016. Reducing Urban Heat Islands: Compendium of Strategies. Urban Heat Island Basics, www.epa.gov. Akbari, H., Cartalis, C., Kolokotsa, D., Muscio, A., Pisello, A.L., Rossi, F., Santamouris, M., Synnefa, A., Wong, N.H. and Zinzi, M. 2015. Local climate change and urban heat island mitigation techniques – The state of the art. Journal of Civil Engineering and Management 22. (1): 1–16. 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