Energy Conversion and Management 86 (2014) 250–258

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Energy Conversion and Management

journal homepage: www.elsevier .com/locate /enconman

Evaluation of comfort conditions in urban open spaces. Applicationin the island of Crete

http://dx.doi.org/10.1016/j.enconman.2014.04.0590196-8904/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +30 2821037825.E-mail address: theocharis.tsoutsos@enveng.tuc.gr (T. Tsoutsos).

Marianna Tsitoura, Theocharis Tsoutsos ⇑, Tryfon DarasSchool of Environmental Engineering, Technical University of Crete, GR-73100 Chania, Greece

a r t i c l e i n f o

Article history:Received 23 September 2013Accepted 20 April 2014Available online 27 May 2014

Keywords:Sustainable urban designOutdoor thermal comfortMicroclimatic monitoring

a b s t r a c t

The thermal environment in outdoor public spaces and their level of use are strongly connected. Thedesign of outdoor spaces, especially in urban areas, is very critical in Southern Europe due to theirextended use during summertime where the urban heat island phenomenon deteriorates the microcli-matic conditions.

In this paper the main outcomes of outdoor spaces field surveys are presented, which were carried outin four different urban open spaces in Crete. On site measurements were implemented and a question-naire was used in order to estimate the thermal comfort of visitors. Thermal indices like Predicted MeanVote, Physiologically Equivalent Temperature, Standard Effective Temperature, Wet Bulb Globe Temper-ature are used to evaluate the features of urban microclimate and then are being compared in order tofind the most suitable for the Mediterranean microclimate. This suggests another way of approach tothe researcher and provides essential tools to the designer.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

It is well known that the urban open space is directly affectedby the habitants and vice versa the habitants’ quality of life andsocial status is related with the open urban space design [1].

The major determinants of the use and viability of an open placethat are analysed in the survey are: (1) the climate conditions inthe micro-scale environment [2,3]. Humidity levels, especially inhot climates and coastal regions [4,5]; (2) the mean radiant tem-perature, as well as (3) the cold air supply within the urban space[6]. All these features have multiple effects not only in health andwell-being of the citizens, tourism and local market but also to theresidences and the energy consumption of the surrounding build-ings [7–10]. This relationship is more evident, especially in islands,because the majority of the open spaces is in the form of a largecentral square in the city centre; in this way every interventionto the open space may have beneficial results in the sustainabilityof the whole urban system; obviously a large scale integration ofsolar applications in urban areas could improve this sustainabilityand self-efficiency dramatically [11].

Studying the microclimatic factors in relation with the comfortfactors of people using them, the basic parameters of sustainabledesign could be determined [12–14]. The initial findings of this

study aim to implement additional information about the correla-tion between the microclimatic characteristics of open urbanspaces and the comfort votes of people using them.

After the calculation and comparison of a variety of indices andclimatic parameters, the most crucial for the sense of comfort inthe outdoor environment are being determined [15–17]. Similarstudies that either include interviews or only simulation scenariosuse other indices that are not taken into account in this study likeCOMFA method, Thermal sensation (TS), mean radiant tempera-ture, Temperature Equivalent Perception (TEP), MENEX modeland Potential Storage Index [18,19].

This paper focuses on the way microclimatic conditions, suchas air temperature, solar radiation, relative humidity and windspeed and direction affect the use of urban open spaces in a Med-iterranean island climate, with the use of field surveys conductedin four different cities in Crete, Greece [20]. The influence ofthese factors can be measured and quantitatively evaluated. Inthe final results, psychological factors and non measurableparameters like aesthetic and personal preferences are notincluded.

The aim of the paper is to provide basic rules critical for a sus-tainable design of open urban spaces in every type of Mediterra-nean island, such as:

� Classification based on the hierarchy of the climate parame-ters, to calculate their contribution to the overall comfortlevels;

M. Tsitoura et al. / Energy Conversion and Management 86 (2014) 250–258 251

� Determination of the comfort levels of every microclimateparameter according to the answers given, both in winter andin summer time;� Determination of the basic human parameters that affect the

comfort levels;� Valuation of these parameters depending on the different uses

of the four squares.

Given the prior experience, this research implements the find-ings into a particular type of climate, the Mediterranean climate[21]. This way the basic indices can be validated and if possiblerecalculated in a different scale that is constructed by real votesand real data. No model can be properly implemented to a specificsituation unless it has been properly adjusted first to the specificsof the given situation.

2. Methodology

In order to examine the variety of the several urban climatesand design parameters within Crete, all selected sites have differ-ent characteristics considering their vegetation, their locationand their use. The first one is on the coastal zone within the histor-ical center of Chania, the second one is between the shopping cen-ter and the port in Rethymnon the third one is a nearlyreconstructed square within the shopping center area of Iraklionand the fourth is located on a mountainous village near Iraklioncalled Archanes.

In every square studied two surveys were conducted, one in thewinter (February 2009) and one in the summer (July 2009). Theywere conducted from 10 a.m. to 4 p.m, and 200 questionnaireswere carried out, 100 each time. This number of responses is min-imally sufficient to conduct valid and reliable conclusions and itwas pre-calculated by tests in significance level 0.05 [22]. All thestatistical tests run for the need of the survey (e.g. linear regres-sion, significance of coefficients, etc.) were statistically significantin 0.05 significance level. It was used simple random sampling asthe method of collecting the data (there was no need for stratifiedsampling, since the groups of interest were residents and visitorsto the squares, and not the age or sex groups). The selection ofthe specific dates of the measurements was done by followingobservations of the general climate, in every city during the wholemonth so as the climatic data collected would be realistic replica of

Fig. 1. Mean temperatures in the survey cities for the years 2006–2

the microclimatic environment of the square the day of the mea-surement (Fig. 1). The comfort votes for the evaluation of all themicroclimatic parameters and also for the total state of comfortobtained through questions in a 5 or 3 point scale. The 5 or 3 pointscale included the comfort votes in the middle (0), and two levelsof discomfort, tolerable discomfort (±1) and intolerable discomfort(±2). The parameters thermal comfort and wind tolerance werestudied in a 5 point scale while the parameters of sun tolerance,humidity tolerance and traffic sound annoyance were studied ina 3 point scale. The questionnaire also included questions aboutthe user’s preferences in general and his/hers additional opinionabout the meaning and type of the ideal open urban space. Allthe answers were afterwards linked with the microclimatic datameasured at the time of the interview.

The questionnaire included information about (Fig. 2):

(A) Observations (apparel; consumption of cold drinks; kineticstatus -at rest or in motion; residence time in the square).

(B) Questions (criteria for comfort in the heat, wind, sun, mois-ture, acoustic environment).

(C) Other criteria (naturalness of the area; expectations basedon proposed changes pictured; experience – impressionsfrom their stay in the square; reasons of visiting and using;aesthetics of the area).

The survey tried to take into consideration the majority of thefactors that affect comfort, which include microclimate factors,physical and psychological parameters. This paper focuses moreon the microclimate factors like air temperature, solar radiation,relative humidity and wind speed. Other parameters that mayaffect thermal sensation like health issues, alcohol consumption,consumption of food or cold drinks before the interview, etc. arealso being included.

The data measured were afterwards compared to the mean cli-matic conditions of the relative city in order to confirm their qual-ity (Fig. 1). The site monitoring included the use of a portableweather station (HOBO weather station) and all the sensors werecalibrated in order to conform to ISO 7726 [23]. The portableweather station, which was put in the middle of every square,saved values of air temperature (�C), air velocity (m/s), relativehumidity (%) and sun radiation (W/m2) whereas the additionalequipment that could easily be transported around in the exact

009 in relation with the temperature in the days of the survey.

Fig. 2. The questionnaire of the study.

252 M. Tsitoura et al. / Energy Conversion and Management 86 (2014) 250–258

place of the interview (Frederiksen hand pyranometer, Mastechsound level meter) measured sun radiation, temperature, humidityand sound levels. The station was scheduled to save measurementsevery five minutes in order to have sufficient amount of data col-lected, whereas the data from the interviews were collected (inthe exact place of the interview) about every fifteen minutes,depending on the time between the two interviews.

All the thermal indices calculated were based both in the valuesmeasured and the answers given by each person separately. Thequestionnaires were completed only by the people who actuallyused the squares and remained in them for at least 5 min. Thermalsensation and comfort votes were recorded by face-to-face inter-views while demographic background, clothing and activities wererecorded by observation. The interviewees were studied in place, inthe exact spot where they sat or stood within the square so as toinvestigate them together with the environmental factors that con-tributed to their votes.

The sample of the survey was chosen, as we mentioned, in sucha random way to be representative of the targeting population (dif-ferent age groups, sex and also the special characteristics and useof the different squares) In Fig. 3 we can see its age and sex distri-bution. number of interviews, male/female-age groups).

This paper focuses on issues related to the use of space, asopposed to people’s evaluation of the comfort conditions. All the

Fig. 3. Profile of interviews.

interviews, as we mentioned, considered not only the comfortvotes but also physical parameters that might affected these votes.

3. Results

3.1. Microclimatic data

A summary of the different climatic data for the different inter-view times, in the different Cretan cities appears in Table 1 (aver-age temperature, relative humidity, wind velocity and direction,solar radiation intensity for the different squares). Weather resultshave been obtained as described from the portable weather stationsensors that were installed in each interview area, as well as fromthe portable measuring instruments (thermometer, pyranometer,decibel meter with measurement uncertainty ±0.01) in order torecord the comfort conditions in the exact spot where the answerswere given. The validation of the microclimatic data measured bythe portable weather station was carried though their comparisonwith the corresponding data measured by the local weather sta-tion. The values had small differences which came as a result ofthe urban development and vegetation. There were big differencesin wind speed which were mainly due to difference in altitudemeasurement. The results of the portable weather station wereobtained from a level of 2.00 m from the ground surface of thesquare, and in the area there were obstacles or vegetation whichcertainly affected the outcome results, while the location of theweather station in each city was clearly higher, and its place hadbeen carefully chosen so as there will not be any obstacles. Theplacement and its height was intentionally made exactly in themiddle of every square (without taking into account the vegetationor any obstacles that may cause different conditions), in order torecord the real weather data that affect the comfort conditionsexamined.

3.2. Human population data

The analysis of the sample answered the questions will give cer-tain evidence about the type of people who use each one of thesquares and also the site-specific characteristics of the squares

Table 1Mean values of weather data from the portable weather station.

Air temperature (�C) Wind speed (m/s) rh (%) Dewpt (�C) Solar radiation (W/m2) Place sound (dB)

Summer CHANIA 27.44 0.93 61.51 19.38 869.56 54.21RETHYMNON 26.21 1.78 64.55 19.03 908.94 59.79IRACLION 31.19 1.15 46.21 18.28 976.93 57.23ARCHANES 29.21 0.72 42.87 15.30 902.37 62.01

Winter CHANIA 15.44 2.19 49.88 5.01 720.96 50.01RETHYMNON 15.91 1.75 46.83 4.33 455.79 55.05IRACLION 17.33 1.05 69.52 11.71 626.25 49.52ARCHANES 13.58 0.00 87.98 11.66 91.87 65.02

Fig. 4. Plan of the squares.

M. Tsitoura et al. / Energy Conversion and Management 86 (2014) 250–258 253

which are crucial for the further study. In all the squares about 70%of the people lived or worked nearby and 30% were foreign visitors.

Fig. 4 shows the frequency of use of each square and provides aclear picture of the preference of residents and visitors to the area.

Fig. 5. Answers to the question ‘‘what do you consider most important when youchose a place to sit in a square?’’.

Fig. 6. Thermal comfort in the summer and winter.

254 M. Tsitoura et al. / Energy Conversion and Management 86 (2014) 250–258

In Fig. 4 the plans of the squares appear coloured ranging from red1

to yellow according to the number of questionnaires that were con-ducted in that point. They reveal the basic routes and the most pre-ferred sitting areas of the residents and visitors. From the answers tothe questions ‘‘how often do you visit the area?’’ and ‘‘do you live orwork in the neighbourhood?’’ we can conclude that in Chania, Ret-hymnon and Heraklion, the percentage of local residents is larger(70%) than those who visited the site a minimum per week (30%),meaning that some people do not choose the site for daily or weeklyuse even if they live or work nearby. Unlike, in Archanes the reverseeffect is observed; many visitors use very often the square. Thisresult may however not be very representative of the square, bearingin mind the fact that Archanes is a nearby destination from Herak-lion and many people visit the restaurants and cafes that are aroundthe square.

3.3. Comfort data

Before going any further, a more detailed analysis of the repliesof the respondents about the comfort conditions related to thermalcomfort, annoyance from the sun, wind, humidity, and acousticcomfort is necessary. All responses to these questions were ana-lysed in a 5 point scale (thermal comfort, wind tolerance) or in a3 point scale (sun tolerance, humidity tolerance, traffic soundannoyance) and the possible responses range from tolerable dis-comfort (±1) to intolerable discomfort (±2). The index ASV (ActualSensation Vote) is a result of all the responses together, with thesummary question, ‘‘Are you comfortable?’’ and gives a clear pic-ture of comfort conditions in each square. Initially it is importantto see which one of these parameters is considered according tothe interviewees to be most crucial for the feeling of comfort.The answers to the question ‘‘what do you consider most impor-tant when you chose a place to sit in a square?’’ appears inFig. 5. This question can be very helpful when designing a squarebecause it makes possible to regulate all aspects of comfort, as wellas to calibrate the factors affecting the comfort and with the use ofstatistical analysis to determine the parameter that mostly affectsthe comfort conditions (temperature, sunshine, acoustic environ-ment). The main result for this question is that sunshine has thegreatest percentage of answers in all the squares 58.45%, conclud-ing that sun control is an important factor which influences thecomfort vote and is decisive for the viability of the square. It shouldalso be noted that the other two factors, namely the acoustic envi-

1 For interpretation of color in Fig. 4, the reader is referred to the web version ofthis article.

ronment 24.86% and temperature 16.69% are also important for thesustainability of the square (Fig. 5).

Fig. 6a and b shows the responses to thermal comfort (heat),respectively in summer and winter and Table 2 shows the averagetemperature prevailing in the squares when the vote of comfortwas positive (OK). Talo square in Chania has the highest percentageof thermal comfort (OK vote) both in summer (37%) with averageair temperature 27.7 �C and in winter (73.1%) with average air tem-perature 15.4 �C. In Rethymnon the percentages of extreme votes(too little, too much), both in summer and winter, appear increasedeven though the air temperature both in summer (26.1 �C) and inwinter (16.3 �C) stays between the comfort levels (according tothe ISO 7730). This phenomenon is mainly due to the lack of veg-etation that could protect the pedestrians from the radiation of thesun, combined with high reflective materials that maximized it inthe summer and also the lack of any kind of protection from thetemperature, the rain or the humidity within the square in thewinter that make the habitants feel uncomfortable while usingthe space.

The answers about the sun tolerance are shown in Fig. 7. In win-ter the measurements of the sun radiation were from 350 W/m2 to550 W/m2 whereas in the summer the radiation increased signifi-cantly from 850 W/m2 to 950 W/m2. Only in Archanes the resultsfrom the measurements of the sun radiation are very low becauseof the high density trees that covered the square, factor that pre-vented the sun penetration. Despite the very low amount of sun,the mean value of the sun radiation measurements is 25.6 W/m2,during the interviews for sun tolerance in Archanes (Table 2). Inwinter all squares had a good response rate (OK). On the contrary,in the summer the (OK) answers about the comfort increased inChania (44.4%) and Archanes (91.3%) although the average solarradiation, as it was measured from the weather station, did notvary so much in relation to the other two squares (Rethymnonand Heraklion) (Table 2). These responses were mainly determinedby the ground material as well as the naturalness of the place. Boththe squares in Archanes and in Chania have large areas of tall treesand vegetation and as a result, the amount of the received radia-tion measured was limited (not more than 500 W/m2 as measured

Table 2Mean values of microclimatic data for the comfort votes (OK) of the questionnaires.

Air temperature (�C) Wind speed (m/s) rh (%) Solar radiation (W/m2)

Summer CHANIA 27.70 0.90 61.50 855.40RETHYMNON 26.10 1.80 64.40 902.10IRACLION 31.10 1.20 46.30 968.10ARCHANES 29.10 0.70 42.90 894.30

Winter CHANIA 15.40 3.00 50.20 749.40RETHYMNON 16.30 1.90 47.10 511.50IRACLION 17.30 1.10 69.60 309.10ARCHANES 13.40 1.00 86.80 25.60

Fig. 7. Answers for the sun tolerance.

Fig. 8. Answers for the wind tolerance in summer and winter.

Fig. 9. Humidity levels tolerance in summer and winter.

Fig. 10. Traffic sound annoyance.

M. Tsitoura et al. / Energy Conversion and Management 86 (2014) 250–258 255

the portable pyranometer) unlike the other two squares where thereflective materials on the ground multiplied the received solarradiation (about 700–950 W/m2 as measured by the portablepyranometer).

Fig. 8a and b shows the percentage of responses for windtolerance. The wind votes are strongly influenced by wind speedrather than by other factors that influence mostly solar and

thermal comfort. In all squares both in summer and winter therewas no measurement of wind speed above the 2 m/s, for this rea-son the majority of the responses given were in favour of the littlewind that existed.

The relative humidity (Fig. 9) was measured very high in bothwinter and summer in all regions, realistic phenomenon if we takeinto account the Mediterranean climate of the island. The answersabout the humidity were not equivalent to the RH measured,except in Archanes where the amount of the humidity especiallyin winter was very high the people were able to quantify their dis-comfort due to the humidity levels.

Finally, Fig. 10 presents the responses to the traffic soundannoyance. The responses ‘‘silence’’ and ‘‘very quiet’’ cannot beconsidered negative and on the charts were included in the OKvote. It is clear that Chania had the largest percentage of positiveresponses about the traffic sound levels in both winter and sum-mer, even though the sound level did not vary much from regionto region. The significant difference of the Talo square is the sea,which produces enough noise (the decibel meter near the sea

Table 3Comfort limits of the indices reviewed according to the references.

WBGT (�C) PMV PET (�C) OUT_SET (�C) Comfort state

>29 >4 >32 >30 Hot26–29 2–4 25–32 23–30 Hot enough23–25 1–(�1) 20–25 18–23 Comfort<22 (�2)–(�4) 10–20 13–18 Cold enough

256 M. Tsitoura et al. / Energy Conversion and Management 86 (2014) 250–258

measured noise around 60 dB) but also absorbs most negative traf-fic noise.

4. Discussion

Results from the analysis, of all factors relating to comfort in thesquares led us to some general conclusions that allow any designto be feasible and furthermore affect the viability of the corre-sponding square. Each individual square had good comfort votesin specific parameters (Chania on the heat, Archanes in the sun,etc.) and not so good in others (Rethymnon in the sun, etc.). To con-struct a general model that can be applied all over the island abasic rate of all results is essential and a calibration of all the casestudies over the same scale [24].

To achieve that goal several comfort indices are used. At first wetried to find the one more suitable to describe the comfort votesand afterwards we adjusted this index for better compliance withthe actual answers.

Table 4Mean values for all the squares of every index in summer and winter separately (in bold

Air temperature

Summer Chania 27.61Rethymnon 26.27Heraclion 31.19Archanes 29.23

Winter Chania 15.44Rethymnon 15.90Heraclion 17.31Archanes 13.57

Fig. 11. Thermal indices value for Talo squ

The comfort indices that are used in the current study are:

� WBGT takes only climatic data into account such as air temper-ature, radiant heat, solar radiation and air movement.� PMV has solid base in the indoor environment but takes into

account relevant factors and the affect thermal sensation.� PET and out SET are for outdoor environments. PET does not cal-

culate individual parameters and out SET takes personal param-eters for one standard type of person.

Table 3 describes the comfort limits for each one of these indi-ces according to the references, while Table 4 shows the mean val-ues for all the squares of every index in summer and winterseparately. The mean values that are beyond comfort limits in eachseason [25,26] are being mentioned with bold numbers. Accordingto the calculated indices outdoor comfort during summer is quitedifficult to achieve in all the squares while during winter periodmost of the squares had ideal comfort conditions. The comparisonbetween the actual comfort votes measured from the site and theindices calculated shows that although the indices indicate condi-tions of great discomfort during summer the percentage of actualcomfort votes in all the squares is quite high. This fact identifiesthe need of a site specific comfort model that takes into accountthe Mediterranean microclimate parameters.

In order to find the most suitable index for the correlation withthe actual votes the value of every index was calculated for the

the higher values of WBGT, PET and OUT_SET).

WBGT PET OUT_SET PMV

28.49 40.87 35.30 4.3027.47 36.06 30.22 3.5029.85 45.69 37.34 4.7827.32 44.28 36.37 4.24

16.12 18.82 16.96 �0.6816.24 21.24 18.41 �0.8019.14 22.58 19.13 �0.6916.99 9.28 7.31 �2.49

are in Chania for winter and summer.

Fig. 12. Scatterplot of linear regression of Predicted Mean Votes and ActualSensation Votes.

M. Tsitoura et al. / Energy Conversion and Management 86 (2014) 250–258 257

exact time and place of every interview. Fig. 11 shows the exactvalue of each one of those indices in summer and winter for thehours of the interview, for Talo square in Chania. From the compar-ison of the indices with the actual sensation votes (Fig. 10) we canconclude that:

– Out SET index is directly affected by the solar environment thatis why appears so unstable and cannot describe the users’ toler-ance of the climatic conditions.

– WBGT index is quite close to the air temperature but the com-fort levels seem not to follow the temperature variations.

– PET index is affected by the air temperature and the resultsespecially in the summer cannot describe the comfort votes.

– PMV index, cannot describe the comfort during summer but itcan predict the increase or the fall of the comfort votes quiterealistically in all the squares both in winter and summer.

Fitting linear regression models, with the use of SPSS software,for each one of these indices with respect to the actual sensationvotes from the interviews of all the squares, is found that thePMV index can better predict the comfort votes with the implica-tion of the model: Actual Sensation Votes = PMV � 0.16 + 0.22 withR2 = 0.72. The size of the coefficient of determination (for themodel) R2 = 0.72 shows close relationship between the votes frominterviews and the PMV index (Fig. 12).

5. Conclusions and recommendations

This paper identified the climatic factors which affect themajority of the responses of comfort and their interaction; fieldsurveys also revealed various issues regarding adaptation of usersto the outdoor environment.

The study was executed in four squares in Crete, two seasons ayear (winter, summer). The days of the interviews were carefullyselected, after meteorological evaluation of the weather parame-ters, with the help of specialized weather forecast, so as to repre-sent the typical weather conditions of the season. The study isbased on monitoring weather data in each square in conjunctionwith answering a total of 200 questionnaires on the amenity ofpeople using them.

A basic assumption of this survey is that the comfort conditionsin each square come as a result of the interaction of all the micro-climatic parameters. Especially for Crete, the result, from the studyshowed that air temperature and solar radiation are the most crit-ical determinants of comfort votes (R2 = 0.87 for temperature andR2 = 0.82 for solar radiation) taking into account both physicaland physiological factors that were included in the questionnaires;

also humidity and wind speed affect the comfort vote only whentemperature conditions are not natural. The share of people whofelt comfortable during the interview in Crete was about 67%,which is lower than the results from RUROS project showing over75% annually [27]. This requires a differentiation for the islandsand the construction of a skilled comfort model so that any formof intervention into the island open spaces can have a positiveeffect on the viability of the city. It is worth noticing that allsquares in the study have been redesigned over the last threeyears, so can assume that the design solutions were made withoutany study of the comfort conditions prevailing in them. This factcan boost the basic purpose of this study as it is obvious that everyattempt on designing open urban space must take into account thesite specifications, people habits and local weather parameters inorder to assure that will become an alive open place of socialinteraction.

All the basic thermal indices like PMV, WBGT, PET and SET havebeen calculated for each one interviews separately and then becompared with the actual comfort votes but they do not reflectin a great degree the vote for comfort of the interviews. The indexmore suitable to predict not the comfort value but the change ofvote is found to be PMV index and furthermore the PPD index asdescribed by the ISO 7730.

Obviously, in order to conclude with a basic model of comfortwhich could predict the comfort vote of the users, it is essentiala reorientation of the basic thermal indices and a more specializedmodel that takes into account the special features of the Mediter-ranean climate. For the effectiveness of this model, further mea-surements are needed as well as a specialized analysis of fullrepresentation of climatic behaviour of each square. This combina-tion could lead to an optimum design of the urban open space thatmatches all types of expectations and the best comfort votes. Thissuggests another kind of approach to the researcher and givesanother palette of tools to the designer.

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