research article investigating thermal comfort and...

Research ArticleInvestigating Thermal Comfort and User Behaviors in OutdoorSpaces A Seasonal and Spatial Perspective

Kuo-Tsang Huang1 Tzu-Ping Lin2 and Hsiao-Chi Lien3

1Department of Bioenvironmental Systems Engineering National Taiwan University 1 Section 4 Roosevelt Road Taipei 106 Taiwan2Department of Architecture National Cheng Kung University 1 University Road Tainan 701 Taiwan3Program of Landscape and Recreation National Chung Hsing University 250 Kuo Kuang Road Taichung 402 Taiwan

Correspondence should be addressed to Tzu-Ping Lin lin678gmailcom

Received 22 September 2014 Accepted 17 March 2015

Academic Editor Julio Diaz

Copyright copy 2015 Kuo-Tsang Huang et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Numerous studies have examined the correlation between the number of attendants in a given outdoor environment and thermalindices to understand how the environmental planning has an impact on the users However extensive observations should beconducted to examine the detailed static and dynamic behavior patterns of users We conducted dynamic observations at a steppedplaza to perform on-site measurements of the physical environment and observations of users behaviors including their restingpositionsmovements and stay durationsThe results indicated thatmore people rested on the steps during the cool season than hotseason Compared to neutral temperatures people demonstrated higher heat tolerance to the hot seasonThe results indicated thatmore than 75 of users preferred to remain in shaded areas and stayed longer than in the sunlight The people tended to engage instatic activities in environments that exhibit sufficient shading The shaded areas were conducive to static activities as the summergrew hotter The results verified that the people of Taiwan would avoid sunlight and desire shaded spaces based on their previousclimate experiences and expectations which can serve as a reference for outdoor space design to improve the usability and qualityof open urban spaces

1 Introduction

Requiring leisure and recreation space people in urbanenvironments use public outdoor spaces such as parks andplazas for their activities this directly exposes them to theexternal climate Thermal comfort which is governed bytemperature humidity wind speed and radiation closelyrelates to perceptions and preferences towards the way peopleuse outdoor spaces Because the success of a public space canbe judged by the number of people using it [1] numerousstudies have examined the number of people using specificspaces and how this variable relates to the thermal indicesof the environment Such studies have investigated locationsin diverse countries and climate zones such as Canada [2]UK [3] Sweden [4 5] Japan [6] Taiwan [7 8] Greece [9]Hungary [10] and Netherland [11] These findings indicatea significant relation between the number of people using

a space and the thermal environment of that space dependingon the climate conditions

Studies have analyzed and compared the numbers ofpeople and the thermal environments in locations that exhibitdistinct spatial patterns (eg various degrees of shading)within a surveyed areaThe results indicate that environmen-tal design for example shading levels would influence thethermal environments and the number of people gatheringin outdoors [12 13]

However the number of people using a space alonecannot detail how that space is being usedTherefore detailedobservations should be conducted to examine user behav-ioral patterns and describe how the thermal environmentaffects space usage These observations assess the personalattributes of users (eg age sex purpose and clothing) theirresting positions (in the shaded or unshaded area) stay-ing characteristics (location selection movement and stay

Hindawi Publishing CorporationAdvances in MeteorologyVolume 2015 Article ID 423508 11 pageshttpdxdoiorg1011552015423508

2 Advances in Meteorology

duration) and behavior patterns (eg reading discussing orresting)

To obtain detailed information regarding usersrsquo behaviorpatterns for verifying the relation between behavior andthe thermal environment researchers must firstly determineappropriate observation methods and select an appropriatesite Regarding observational methods similar studies in thepast focused on numbers of attendants and the distributionsof their locations Therefore researchers typically use visualmethods to count the number of attendants and recordtheir locations by using static photographs as supplementaryinformation sources during analyzing

However to document usersrsquo behavior patterns in detaillong-term observation is needed It is often done by meansof scrutinizing continuous dynamic images filming fromvideo camera For example Gomez-Martın and Martınez-Ibarra [14] used webcams to observe the number of peo-ple on beaches employing quantitative visual estimationto determine the number and the density of people atvarious regions and timeframes In their study only usersrsquolocation distribution and the density were analyzed due tothe limitation of webcamrsquos footage resolution therefore thebehavior patterns of users were not assessed Regarding thesite selection actual measurements must be conducted inspaces that are able to demonstrate diversifying thermalenvironments to further analyse the association between thethermal environment and the user behavior patterns Whenusing dynamic video recording the locations of positioningrecording device should be carefully selected to ensure thatan unobstructed full view of the space is captured

Digital video camera was used for dynamic observationstoward a stepped square situated at the outdoor publicrecreational garden of National Museum of Natural Sci-ence (NMNS) in Taichung City Taiwan The chosen squareexhibits diversifying thermal environments which is partiallyshrouded by various thicknesses of tree canopies and partiallysky open and is considered an ideal place to perform on-sitethermal measurements and observations The objectives ofthis study are as follows

(a) to observe the number of space users during variousseasons and determine the histogram of the numberof users against various temperature ranges

(b) to investigate the userrsquos prior selection of activity loca-tions and the amount of time that people remained attheir chosen locations

(c) to analyze the relation between the thermal environ-ment characteristics and the user behavior patterns

Thefindings elucidated space use behaviors in response tothermal environments which would help facilitate decisiondetermining of outdoor space planning and design in thefuture

2 Methods

21 Observational Subjects As previously mentioned theobservation location requires a varied thermal environmentthat comprises unobstructed observation spots for placing

video camera to elucidate howmicroclimateswould influencethe usage of recreation spaces thermal comfort and adaptivebehaviors Therefore a stepped plaza at the outdoor gardenof the NMNS was chosen for long-term observation Figure 1shows that the stepped plaza is located at 24∘081015840N 120∘401015840 Ewith an altitude of 26m The area is approximately 125min width 4m in depth and the observational height rangeof the space is approximately 27m The area comprises fourlevels of steps A lawn is positioned at the front of the stepswith the two sides being turf and shading trees The primaryusers of the space arrive after visiting the museum or attendthe NMNS park for walking or resting Most people remainin the plaza for less than 30 minutes People use the plazawith various behaviors including movements talking andreading

Taichung City exhibits a hot and humid climate Theaverage observed climate data from 1991ndash2010 recorded bythe Central Weather Bureau of Taiwan indicated that themonthlymean air temperature is highest in July at 285∘C andlowest in January at 162∘C Furthermore the mean monthlyrelative humidity is held constantly around 80 all the yearsuggesting a humid climate Since cool air temperature onlyexists from December to February this research defines thisperiod as the ldquocool seasonrdquo and the remainingmonths (MarchtoNovember) as the ldquohot seasonrdquo which is in accordancewiththe definition of previous local studies [7 12 15 16]

22 Shading Characteristics of the Stepped Plaza The shadingcharacteristics of an outdoor space would affect the thermalenvironment [15 16]Therefore the shading characteristics ofthe evaluated stepped plaza must be quantitatively describedBecause trees are mainly located at the south and north sidesof the steps the degree of shade varies along the steps Thesky view factor (SVF) was introduced herein to represent theshading level in an outdoor environment The SVF can bedefined as the percentage of free sky at specific location withthe value ranging from totally obstructed (SVF = 0) to totallyfree spaces (SVF = 1) [17 18]

A small SVF value indicates that a high amount ofshade is present and the range of the visible sky is limitedFigure 2 shows fisheye photos shot in cool season 1500 ofthe external appearance of the stepped plaza and the 10corresponding positions The SVF distribution ranged fromposition B1 which exhibited a high level of shade (SVF =009) to A4 which was relatively open (SVF = 057) Thisindicates that various locations within the stepped plazademonstrated distinct levels of solar insolation depending onthe season and the plaza exhibited varying thermal environ-mental characteristics The SVF values of each location aresimilar whether in hot or cool season due to the surroundingevergreen trees planted in the stepped plaza

23 Data Obtainment Thermal environment measurementsand user behavior observations were performed simultane-ously Physical quantities of microclimatic parameters mea-surements including the air temperature relative humidityglobe temperature and wind speed were measured with twoidentical sets of instruments with which one was placed

Advances in Meteorology 3

N0 25 50

(m)

Figure 1 Aerial photograph of the NMNS location

B1 B2 B3 B4 B5

B1 B2 B4B3 B5

A1 A2 A4A3 A5

A1 A2 A3 A4 A5

SVF = 009 SVF = 021 SVF = 057 SVF = 055 SVF = 063


Figure 2 Panorama of the steps and fisheye diagrams of themeasuring points (Cool season 1500)

under the tree shaded area and the other was placed totallyunshaded as counterpart A location with a dense tree canopywas considered a ldquoshadedrdquo location whereas a location with-out shading from nearby buildings or trees was considered asan ldquounshadedrdquo location The resolution and accuracy of theinstruments for each parameter are 01∘C and plusmn03∘C for airtemperature and globe temperature 01 and plusmn25 for rela-tive humidity and 001ms andplusmn02ms for wind speed Bothinstruments were mounted on tripods that were 11m abovethe ground and the parameters were automatically recordedonce per minute from 1400 to 1700 hours simultaneously onthe day the instruments were deployed

The shaded and unshaded locations where the twosets of instruments were placed would vary day by dayaccording to the position of the sun resulting in variousdegrees of shading levels for each duration of time andare dependent on seasons The ldquoshadedrdquo and ldquounshadedrdquolocations were not fixed and could vary according to thesunrsquos movement Nevertheless the sunlight in the ldquoshadedrdquolocations by definition must be fully blocked whereas theldquounshadedrdquo locationsmust be exposed to direct sunlight at alltimes without obstructions The method of selecting shadedand unshaded measurement locations was similar to thatused in a previous park study in Taiwan [12] The hourlymeteorological observations such as the wind directionhorizontal solar insolation and the amount of cloud wereobtained from the nearby Taichung Park weather station

To record the basic characteristics and behaviors ofusers in the observation area a high-resolution digital videocamera was deployed approximately 25m away from thesteps and 1m above ground to conduct nonstop snapshotsThe time of appearance and departure movements andadaptive behaviors of the users were documented by scruti-nizing the recorded footage Although children were presentin the observation area we did not include them in theanalysis because their activitiesbehaviors would possibly berestricted by their guarding parents

24 Thermal Comfort Index Calculation This study appliedphysiologically equivalent temperature (PET) to evaluate thethermal environment objectively PET is defined as the airtemperature at which in a typical indoor setting (air temper-ature = mean radiant temperature vapor pressure = 12 hPawind velocity = 01ms) the heat budget of the human bodyis in equilibriumwith the same core and skin temperatures asthose under complex outdoor conditions [19ndash21] To calculatePET this study adopted the RayMan model [22 23] Thevalue of mean radiant temperature was calculated from themeasured globe temperature using formulas proposed by ISO


59 60

61 62

(a) 1532

60

61 6259

(b) 1534

6061 62

59

(c) 1535

Figure 3 Image sample from the video

standard 7726 [24] initially and subsequently corrected bythe parallel measurements of both the globe thermometerand the six-direction short- and long-wave radiation fluxmeasurement system previously conducted in Taiwan [25]

25 Video Image Interpretation and Encoding To establish anobservation record table for facilitating analysis the dynamicdigital image recordings were interpreted and encoded Firstwe encoded the observed subjects assigning a number toeach individual (eg 001 and 002) Second we visuallyinterpreted the basic characteristics (gender age number ofcompanions and amount of wearing clothing) and behav-ioral characteristics of the subjects (primary activity choiceof sunny or shaded area number of people within an areathe amount of time between arriving to and departing froman area total time spent within an area and other thermalrelated adaptive behaviors) to facilitate subsequent quantita-tive statistical analyses One specific researcher interpreted allthe images to ensure consistency Finally we linked the ther-mal environmental measurements (each physical parameterand the integrated thermal comfort index PET) to each ofsubjects establishing a complete database containing recordsof the subject codes basic and behavioral characteristics andthermal environmental parameters

An example of how the video image is interpreted andencoded is expounded as follows Figure 3 shows that subjectsnumbers 59ndash62 formed a four-member group Their stayingand moving patterns can be divided into three periods (a)Subjects numbers 59 and 60 were women at 1532 theywalked into the semishaded area on the left side of the stepsand sat down Subjects numbers 61 and 62 were men they

stood and talked on the lawn approximately 2m from thestairs (b) After 2min at 1534 subjects numbers 61 and 62walked to the steps and sat in the sunlight At the same timesubjects numbers 59 and 60 stood up and considered sittingin a position covered by dense shade (c) After 1min at 1535subjects numbers 59 and 60 moved toward the shade and satSubjects numbers 61 and 62 remained sitting and talking intheir original position

In this way we were able to track the users through eachimage footage enabling us to establish a complete databaseof the association between user behavioral characteristics andthe thermal environment to facilitate subsequent analyses

26 Measurement Process This study performed a total of19 measurements and observations from April of 2012 toFebruary of 2013 All measurements were conducted between1300 and 1800 on Saturday or Sunday which is the mostvisited period for local users The observation days weredivided into two seasons hot seasons (March to November)and cool seasons (December to February) based on Taiwanrsquosclimate characteristics as stated in Section 21

To prevent the observation from influencing usersrsquo behav-ior we carefully installed the instruments in inconspicuouslocations instead of intervening in the user activities byconducting questionnaires or interviews Before themeasure-mentswere conducted the consent from theNMNSauthoritywas acquired The privacy of the filmed people duringidentification analysis and processing was also ensured

3 Results

31 Number of Users As the number of users is themost basicinformation regarding the space use the number of subjectsaccompanied with their corresponding PET thermal indexmeasurements from the 19 observations was illustrated Themean air temperature was 329∘C during the hot season and241∘C during the cool seasonThemean radiant temperaturewas 396∘C during the hot season and 306∘C during the coolseasonThe PET was 367∘C during the hot season and 271∘Cduring the cool season The relation between PET and thenumber of participants is shown in Figure 4 In June and July(hot season) the PET was as high as approximately 45∘Cand the number of users was consistently less than 10 InNovember and December (cool season) the PET decreasedto approximately 20∘C and the number of users was as highas 59This indicates that during the hot season the number ofusers decreased as the PET increased During the cool seasonthe number of users increased as the temperature increasedThese data are consistent with the results of similar studypreviously conducted in Taiwan addressing the relationbetween the thermal comfort range and number of usersAs Taiwan is located in a subtropical hot-and-humid climatezone the temperatures during the hot season are inverselyproportional to the number of plaza users [7]

To elucidate the relation between the use of the steppedplaza and the PET variation in outdoor thermal environmentthe number of users observed from all 19 observations waslumped and grouped against each PET range based on


010

5

2015

3025

4035

5045

PET

(∘C)

PET (∘C)

02010

4030

6050

8070

10090

Num

bers

of p

eopl

e

15 A

pril

21 A

pril

21 M

ay16

June

21 Ju

ly29

July

16 S

epte

mbe

r23

Sep

tem

ber

14 O

ctob

er28

Oct

ober

10 N

ovem

ber

18 N

ovem

ber

09 D

ecem

ber

15 D

ecem

ber

29 D

ecem

ber

06 Ja

nuar

y19

Janu

ary

20 Ja

nuar

y23

Feb

ruar

y

Numbers of people

Hot seasons Cool seasons

Figure 4 Relation between the PET and number of participants

0

10

20

30

40

50

18 20 22 24 26 28 30 32 34 36 38 40 42 44

Cool seasonHot season

PET (∘C)

Num

bers

of p

eopl

e

Figure 5 Relation between the annual PET and mean number ofparticipants

a temperature increment of 2∘CPET as illustrated in Figure 5During the hot season the results indicate that the meannumber of space users was the highest (41 people) whenthe PET was 34∘C The number of people decreased astemperatures increased and only 5 users were present whenthe PET reached 44∘C During the cool season the meannumber of space users was the highest (30 people) whenthe PET was 22∘C The number of people decreased to 10 astemperature increased

32 Location Selection and Movement When engaging inoutdoor activities people choose a staying location basedon their past experiences of the current or a similar loca-tionspace from thermal perspective When people feel ther-mally dissatisfied with their first location choice they maymoveThese choices may be closely associated with microcli-mate perception experiences and expectations For exampleKantor and Unger [10] examined microclimate perceptionregarding plazas in Netherlands the results indicated thatpeople do not go to a location only after determining thatthe climate is suitable Instead they use their past experiencesand awareness to judge the current environment and decideFor example when users observe shade under trees theymayspeculate that the shaded area is cooler based on their pastexperiences andmove to this locationTherefore first choicesof location are psychological representations of environmen-tal experiences Subsequent movements are responses caused

by the combination of physiological exposure and psycholog-ical expectations In other words people exhibit appropriateadaptive behaviors based on their microclimate expectationsand preferences in addition to changes in physiological heatbalance caused by exposure to themicroclimateThus peoplemove to other locations because their perceptions of theheat level differ from their psychological experiences andexpectations

To explore this phenomenon we recorded the first loca-tions chosen by users when interpreting and encoding theimages These locations reflected differences in the thermalenvironment comprising (a) sunny areas (b) shaded areasand (c) boundaries between the twoThe time at which usersarrived at and departed from these locations was recordedThe location types and the arrival and departure time for thefirst and secondmovements of users were also recorded in thesame fashion Thus the stay duration for each location typeof every user movement could be calculated and recorded

This section addresses staying and moving location types(the stay duration is addressed in Section 33) We calculatedthe number and percentage of people who stayed in varioustypes of locations (sunny area shaded area and the boundaryarea between the two)within the stepped plaza during the hotand cool seasons (Figure 6) During the hot season 74 ofusers first chose shaded areas whereas 22 first chose sunnyareas Subsequently 5moved to shaded areas and 3movedto sunny areas indicating that most people first chose shadedareas as resting locations during the hot season Only aminority selected sunny areas as their resting locations Mostwho initially chose shaded areas remained in their originallocations whereas some who firstly chose sunny areas movedto shaded areas

During the cool season 87 of users first selected shadedareas whereas 13 selected sunny areas Subsequently 1moved to shaded areas and none moved to sunny areasindicating that most people initially chose shaded areas forresting during the cool season Likewise in hot seasons onlya minority selected sunny areas for resting In a statisticsregarding the second movement 99 of people stayed intheir original positions and only 1 moved to shaded areas

In both the hot and cool seasons users tended toselect shaded areas as their first choices This indicates thatpeople prefer to engage in outdoor leisure activities in areascontaining shade-providing trees or canopies avoiding directexposure to intense solar irradiance As previously describedmost people perceived that shaded areas would exhibitrelatively low temperatures based on their past experiencesand expectations and considered these places would be morecomfortable As a result most people preferred engagingin activities in shaded areas Few people had made theirsecond movement indicating that few people were affectedby increased physiological heat loads Thus people reliedon their experiences expectations and other psychologicalfactors rather than on physiological factors when displayingthermal adaptive behaviors

33 Stay Duration The amount of time that users spendon activities in outdoor spaces can reflect their satisfaction


Stay behind

92

Move to sun areas

3

Move to shaded areas

5In sun areas22

In shaded areas75

The border of sun and shadow

3

(a) Hot season

In sun areas13

In shaded areas87


0

Stay behind

99

Move to sun areas

0


1

(b) Cool season

Figure 6 User choices of resting locations and movements during the hot and cool seasons

0000

0600

1200

1800

2400

3000

3600

4200

In sun areas In shaded areas In sun areas In shaded areas

Aver

age s

tay

time (

mm

ss)

25 percentile90 percentile10 percentile

Average

Hot season Cool season

75 percentile

Figure 7 User time spent in sunny and shaded areas during the cooland hot seasons

with the environment When encoding the images werecorded the location types arrival and departure time for thefirst location choices and the subsequent movements Thisenabled calculating the amount of time users spent in sunnyand shaded areas The box plot shown in Figure 7 reveals thedistribution of the duration that users spent in sunny and

shaded areas and the differences between the twoThe resultsindicate that the mean stay duration during the hot seasonwas 5min 41 s in sunny areas and 14min 18 s in shaded areasDuring the cool season the mean stay duration was 6min45 s in sunny areas and 14min 41 s in shaded areas

Figure 7 apparently indicates that the stay duration waslonger in shaded areas than it was in sunny areas during bothseasons Despite the low air temperatures during the coolseason people did not move to sunny areas for enhancingtheir thermal comfort but rather tended to avoid solarinsolation showing a likewise preference for shaded and coolareas as in hot seasons The classical physiological thermalbalance failed to explain these behavioral patterns

It is worthy to mention that the 90th percentile of stayduration in shaded areas was 35min 55 s during the summerFew users spent approximately half an hour which is longerthan that in the cool season in shaded areas during the hotseason It suggests that userswould bewilling to increase theirstay duration in open spaces if shaded recreation areas wereprovided in hot outdoor environments

To elaborate the variations in stay duration under variousthermal comfort conditions cases observed in the hot seasonwere used as an example to calculate changes in mean staydurations under sunny and shaded areas at fixed intervalsagainst the PET thermal comfort index (eg 2∘C PET)Figure 8 shows that users in shaded areas stayed longest(17min 7 s) when the PET was 31∘C The stay duration


0000

0300

0600

0900

1200

1500

1800

2100

29 31 33 35 37

Aver

age s

tay

time (

mm

ss)

PET in hot seasons

In shaded areasIn sun areas

Figure 8 Changes in themean user time spent in sunny and shadedareas during the hot and cool seasons

decreased as temperatures increased or decreased Users insunny areas stayed longest when the PET was 33∘C but itstill exhibits lower stay duration in comparison to shadedareas in all PET ranges Moreover the association betweentemperature changes and stay duration in the sunny areashad similar variation trend to that in the shaded areas Thetemperature at which people stayed longest in the shadedareas (31∘C PET) was lower compared with that of thesunny areas (33∘C PET) because people hoped for decreasedtemperatures based on their expectations of thermal comfortin shaded environments

34 Behavior Patterns To some extent behavioral pat-terns indirectly reflect how users interact with microclimateenvironments A previous study of microclimate and theexploratory behaviors of lions and tigers in zoos [26] recordedthe activity patterns of animals dividing animal behaviorsinto two categories comfort (eg lying down sitting andbeing in water) and movement behaviors (eg standingwalking and running) Similarly in the current study weobserved the detailed behaviors of users from the imagesdividing them into static (eg sitting talking eating anddrinking and reading) and dynamic behaviors (eg stand-ing and walking) The frequencies of static and dynamicbehaviors were calculated based on the season (hot and cool)and location (sunny and shaded areas) It is assumed thata high frequency of static activity indicated that people feltstable and comfortable To somedegree this indicates that themicroclimate of the environment is considered comfortable

Figure 9 indicates that during both seasons more usersengaged in static behaviors compared with dynamic behav-iors in the stepped plaza During the hot season more usersadopted static behaviors than in the cool seasonThe primaryreason for this is that metabolic rates are decreased when sit-ting compared with standing or walking [27] In the attachedtable from the American Society of Heating Refrigerat-ing and Air-Conditioning Engineers [28] metabolic rateswere approximately 60Wm2 when sitting and reading andapproximately 80ndash100Wm2 when standing or slow walkingTherefore people tend to adopt static activities during the hot

34 22

3832

6678

62 68

0

20

40

60

80

100

In sun areas

In shaded areas

In sun areas

In shaded areas

Freq

uenc

ies (

)

Static behaviorDynamic behavior


Figure 9 Ratio of dynamic to static behaviors in the sunny andshaded areas during the cool and hot seasons

season producing decreased metabolic heat inside the bodyto increase comfort

Comparing behavior patterns in spaces that demonstratevaried shade indicates that users in sunny areas were morelikely to adopt dynamic behaviors than users in shaded areaswere This can be explained based on the stay durationsaddressed in the previous section Figures 7 and 8 indicatethat users stayed in sunny areas for less duration than theystayed in shaded areas In other words compared with peoplein shaded areas those in sunny areas were more likely toadopt dynamic behaviors such as leaving the plaza or movingto locations By contrast when people were in shaded areasthat provided relatively comfortable thermal environmentstheir calmmoods facilitated adopting static activities such assitting talking and reading

4 Discussion Verification throughThermal Adaptation Theory

To provide an objective discussion of the association betweenuser behaviors and the environment thermal comfort theoryand previous investigations are referenced to describe andverify the close relation between the behavior and the thermalenvironment

41 Thermal Adaptation Theory The ASHRAE defined ther-mal comfort as ldquoa state of mind expressing satisfactiontoward the thermal environment (temperature humiditywind speed and radiation) assessed through subjectiveevaluationrdquo [28] In the field of thermal comfort scholarshave attempted to combine temperature humidity windspeed radiation amount of clothing and metabolic rates torepresent thermal comfort as a single index The ASHRAEguidelines highlight that thermal comfort is a psychologicalcondition thus subjective perceptions cannot be interpreted


using a physiological index based on body heat balancesBecause psychological factors influence perceptions thesubjective perceptions of people within environments thatexhibit identical thermal comfort indices can differ sub-stantially based on their experiences expectations exposuredurations cultural characteristics perceived control andother factors This refers to ldquothermal adaptabilityrdquo whichnumerous studies have discussed and validated [29ndash35]

Seasonal changes are the most obvious experience fac-tor For example people distinctly perceive summer andwinter temperatures Spatial types (eg shaded or open)are also relevant to expectations (eg people anticipatedisparate feelings when they are exposed to the shade or hotsun) Accordingly the obtained behavioral observations wereexplored in detail based on the above two factors (seasonaland spatial behavioral differences) as followsThe results werealso validated with previous studies conducted in Taiwan

42 Verification of Seasonal Behavioral Differences Lin [7]used subjective questionnaires and objective physical envi-ronmental measurements in Taiwan to analyze neutral tem-perature (119879

119899) and preferred temperature (119879

119901) 119879119899is a temper-

ature that is perceived as neither cold nor hot thus it can beconsidered a comfortable temperature 119879

119901is a temperature

that people prefer at this temperature they do not seek tobecome cooler or warmer Thus the 119879

119901can be considered

the expected temperature In this study the 119879119899was 237∘C

and 256∘C during the cool and hot seasons respectively The119879119901was 23∘C and 245∘C during the cool and hot seasons

respectivelyIn this study our observations regarding the numbers

of participants in the PET groups (Section 31) indicate thatthe thermal index ranges in which the most people appearedduring the cool and hot seasons were 20∘C PETndash22∘C PETand 34∘C PETndash36∘C PET respectively Comparing thesevalues with the on-site measurements the 20∘C PETndash22∘CPET range in which the most people appeared during thecool season was close to the 119879

119899and 119879

119901values of the cool

season However the 34∘C PETndash36∘C PET range in whichthe most people appeared during the hot season was nearly10∘C PET higher compared with the 119879

119901(256∘C) of the hot

seasonWe can view the difference between these temperatures as

the gap between psychological feelings (119879119899or 119879119901) and actual

behaviors (the temperatures at which people attend an area)This difference was not clear during the cool season but itwas obvious during the hot season indicating that althoughpeople psychologically preferred low temperatures duringthe hot season they continued to move to the observed sitewhen temperatures were high People demonstrated a hightolerance to increased summer temperatures indicating theiradaptability to the local climate

43 Verification of Spatial Behavioral Differences The con-structed environment strongly influences the thermal con-ditions to which people are exposed in outdoor spaces [36ndash41] Among several environmental attributes of the outdoorsshading can block solar radiation and has been proven

to influence outdoor thermal environments significantlyCertain studies have examined street orientation and height-to-width ratios for representing the shading factors [42ndash48]Other studies have used SVF to represent the degree of shad-ing [49ndash52] Previous on-sitemeasurements inTaiwan [15 16]proved that areas exhibiting high levels of shadingwould pro-vide superior long-term comfort Lin [7] used questionnairesto determine that people prefer taking shade under trees orother shelters when exhibiting adaptive behaviors to relieveincreases in outdoor temperatures This explains why morethan 75 of users in this study preferred shaded areas andremained in these areas longer in comparison with those whochose sunny areas

It could be logically assumed that users prefer directinsolation to ameliorate coldness during the cool seasonhowever Figure 6 indicates that users were more likely to goto and stayed in shaded areas during the cool season than theywere during the hot season The phenomenon that peopletended to stay in shaded areas during the cool season canbe elucidated based on a study performed in Taiwan Lin etal [53] examined four factors in the physical environmentthat influenced outdoor thermal comfort in Taiwan the airtemperature air humidity solar radiation level and windspeed The analysis indicated that air temperature was thecritical factor (643) during the hot season followed byradiation (343) During the cool season solar radiationcontributed considerably more (583) to the thermal com-fort level than the air temperature did (387) becauseair temperatures are moderate during the cool season inTaiwan When the subjects were exposed to comfortableenvironments the intensity of the sun insolation flexiblyrepresented perceptions of heat or cold (radiation couldimprove comfort) Therefore the solar radiation influencedthermal perceptions more than the air temperatures didand as a result people continued to prefer conducting theiractivities in shaded areas during the cool season

5 Conclusion

In this study physical microclimate measurements imagerecordings and dynamic behavior observations of usersin a stepped plaza at the outdoor garden of the NMNSin Taichung City Taiwan were performed We discussedwhether and how the resting location choices stay durationsand dynamic or static activities were associated with thethermal environment in seasonal and spatial type perspec-tives of a recreational field that coexist with both shaded andunshaded areas

The dynamic image recordings and user behavior obser-vations were novel for use in this field This method enabledrecording all user behaviors within the observational rangeand comparing the images with physical measurements ofthe thermal environment to determine how microclimatesaffect occupantrsquos adaptive behaviors The disadvantage ofthis method was that we could not interfere with the users(eg conducting interviews or providing questionnaires) toprecisely determine their microclimate feelings and prefer-ences In addition to recording videos subsequent studies


can design questionnaires to investigate user feelings towardthe thermal environment however care must be taken not tointerfere with the subjectsThe primary findings of this studyare as follows

(1) More people rested on the stepped plaza during thecool season compared with the hot season The num-ber of people present during the hot season decreasedas temperatures increased The temperature ranges atwhichmost people were present were 34∘CPETndash36∘CPET during the hot season and 20∘C PETndash22∘C PETduring the cool season

(2) More than 75 of users preferred shaded areas Usersalso stayed longer in shaded areas than they did insunny areas

(3) In highly shaded environments people preferredstatic activities The shaded areas were ideal for staticactivities particularly during the hot season

We also referenced thermal comfort theory and previouslocal on-site investigations to describe and verify the relationbetween behavior and the thermal environment It is provedthat the observed subjects demonstrated an extremely hightolerance to increased summer temperatures despite theirpsychological preferences for lower temperatures This wasreflected in the attendance and behavior during the hotseason demonstrating human adaptability toward the localclimate We confirmed that people psychologically dislikedhigh levels of outdoor insolation this was evidenced bytheir spatial use behaviors People substantially preferredto conduct activities in shaded areas even during the coolseason

This study elucidates the association between the thermalenvironment and adaptive behaviors of users It differs frompast studies which investigated only participant numbersand extends to assess user stay locations stay durationsand behavior patterns The findings prove that the people ofTaiwan which are living in a hot and humid region avoidsunlight and desire shaded spaces based on their previousmicroclimate experiences and expectations This is distinctfrom the trends observed in countries in the temperatezone In addition the findings proved that people oftenuse their past experiences to determine whether to moveto a space after observing the sun and shade conditions toensure their thermal comfort Because people rarely makesecond move after choosing a location designing spaces thatinclude sufficient trees or shading shelters could facilitateusersrsquo recognition of thermal comfort Furthermore by inte-grating user climate experiences and awareness to outdoorenvironmental planning and design a successful outdoorspace that is attractive to the public could be achieved

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] M Carmona T Heath T Oc and S Tiesdell Public Places-Urban Spaces The Dimensions of Urban Design ArchitecturalPress Elsevier Burlington NJ USA 2003

[2] J Zacharias T Stathopoulos and H Wu ldquoMicroclimate anddowntown open space activityrdquo Environment and Behavior vol33 no 2 pp 296ndash315 2001

[3] MNikolopoulou N Baker andK Steemers ldquoThermal comfortin outdoor urban spaces understanding the human parameterrdquoSolar Energy vol 70 no 3 pp 227ndash235 2001

[4] S Thorsson M Lindqvist and S Lindqvist ldquoThermal biocli-matic conditions and patterns of behaviour in an urban parkin Goteborg Swedenrdquo International Journal of Biometeorologyvol 48 no 3 pp 149ndash156 2004

[5] I Eliasson I Knez UWesterberg SThorsson and F LindbergldquoClimate and behaviour in a Nordic cityrdquo Landscape and UrbanPlanning vol 82 no 1-2 pp 72ndash84 2007

[6] S Thorsson T Honjo F Lindberg I Eliasson and E-MLim ldquoThermal comfort and outdoor activity in Japanese urbanpublic placesrdquoEnvironment andBehavior vol 39 no 5 pp 660ndash684 2007

[7] T-P Lin ldquoThermal perception adaptation and attendancein a public square in hot and humid regionsrdquo Building andEnvironment vol 44 no 10 pp 2017ndash2026 2009

[8] C H Lin T P Lin and R L Hwang ldquoThermal comfort forurban parks in subtropics understanding visitorrsquos perceptionsbehavior and attendancerdquo Advances in Meteorology vol 2013Article ID 640473 8 pages 2013

[9] M Nikolopoulou and S Lykoudis ldquoUse of outdoor spaces andmicroclimate in a Mediterranean urban areardquo Building andEnvironment vol 42 no 10 pp 3691ndash3707 2007

[10] N Kantor and J Unger ldquoBenefits and opportunities of adoptingGIS in thermal comfort studies in resting places an urban parkas an examplerdquo Landscape and Urban Planning vol 98 no 1pp 36ndash46 2010

[11] S Lenzholzer and J Koh ldquoImmersed in microclimatic spacemicroclimate experience and perception of spatial configura-tions in Dutch squaresrdquo Landscape and Urban Planning vol 95no 1-2 pp 1ndash15 2010

[12] T P Lin K T Tsai R L Hwang and A Matzarakis ldquoQuan-tification of the effect of thermal indices and sky view factor onpark attendancerdquo Landscape and Urban Planning vol 107 no 2pp 137ndash146 2012

[13] T-P Lin K-T Tsai C-C Liao and Y-C Huang ldquoEffects ofthermal comfort and adaptation on park attendance regardingdifferent shading levels and activity typesrdquo Building and Envi-ronment vol 59 pp 599ndash611 2013

[14] M B Gomez-Martın and E Martınez-Ibarra ldquoTourismdemand and atmospheric parameters non-intrusive observa-tion techniquesrdquo Climate Research vol 51 no 2 pp 135ndash1452012

[15] R-L Hwang T-P Lin and A Matzarakis ldquoSeasonal effects ofurban street shading on long-term outdoor thermal comfortrdquoBuilding and Environment vol 46 no 4 pp 863ndash870 2011

[16] T-P Lin A Matzarakis and R-L Hwang ldquoShading effect onlong-term outdoor thermal comfortrdquo Building and Environ-ment vol 45 no 1 pp 213ndash221 2010


[17] T R Oke ldquoCanyon geometry and the nocturnal urban heatisland comparison of scale model and field observationsrdquoJournal of Climatology vol 1 no 3 pp 237ndash254 1981

[18] T R Oke Boundary Layer Climates Metheun London UK1987

[19] VDI Methods for the Human Biometeorological Evaluation ofClimate and Air Quality for the Urban and Regional PlanningPart I Climate VDI Guideline 3787 Part 2 Beuth BerlinGermany 1998

[20] H Mayer and P Hoppe ldquoThermal comfort of man in differenturban environmentsrdquoTheoretical and Applied Climatology vol38 no 1 pp 43ndash49 1987

[21] P Hoppe ldquoThe physiological equivalent temperaturemdasha uni-versal index for the biometeorological assessment of the ther-mal environmentrdquo International Journal of Biometeorology vol43 no 2 pp 71ndash75 1999

[22] A Matzarakis F Rutz and H Mayer ldquoModelling radiationfluxes in simple and complex environmentsmdashapplication of theRayManmodelrdquo International Journal of Biometeorology vol 51no 4 pp 323ndash334 2007

[23] A Matzarakis F Rutz and H Mayer ldquoModelling radiationfluxes in simple and complex environments basics of theRayMan modelrdquo International Journal of Biometeorology vol54 no 2 pp 131ndash139 2010

[24] ISO ldquoThermal environment-instruments and method for mea-suring physical quantitiesrdquo International Standard 7726 Inter-national Standard Organization Geneva Switzerland 1998

[25] T P Lin and A Matzarakis ldquoEstimation of outdoor meanradiant temperature by filed experiment and modelling forhuman-biometeorology userdquo in Proceedings of the 11th AnnualMeeting of the European Meteorological Society EMS2011-89Berlin Germany 2011

[26] T Young E Finegan and R D Brown ldquoEffects of summermicroclimates on behavior of lions and tigers in zoosrdquo Interna-tional Journal of Biometeorology vol 57 no 3 pp 381ndash390 2013

[27] P O Fanger Thermal Comfort McGraw Hill New York NYUSA 1972

[28] ASHRAE ASHRAE Standard 55-2010 Thermal EnvironmentalConditions for Human Occupancy American Society of Heat-ing Refrigerating and Air-Conditioning Engineers AtlantaGa USA 2010

[29] Y Fan S Lang and W Xu ldquoField study on acceptable thermalconditions for residential buildings in transition zone of Chinardquoin Proceedings of the 6th International Conference on IndoorAir Quality and limate (Indoor Air rsquo93) J J K Jaakkola RIlmarinen and O Seppanen Eds Helsinki Finland July 1993

[30] R-L Hwang and T-P Lin ldquoThermal comfort requirements foroccupants of semi-outdoor and outdoor environments in hot-humid regionsrdquo Architectural Science Review vol 50 no 4 pp357ndash364 2007

[31] D A McIntyre Indoor Climate Applied Science PublishersLondon UK 1980

[32] M Paciuk ldquoThe role of personal control of the environment inthermal comfort and satisfaction at the workplacerdquo in Comingof Age R Selby K Anthony J Choi and B Orland EdsEnvironment Design Research Association Edmond OklaUSA 1990

[33] G S Brager G Paliaga R de Dear et al ldquoOperable windowspersonal control and occupant comfortrdquo ASHRAE Transac-tions vol 110 pp 17ndash35 2004

[34] B GivoniClimate Considerations in Building andUrbanDesignVan Nostrand Reinhold New York NY USA 1997

[35] A Malama S Sharples A C Pitts and K JitkhajornwanichldquoInvestigation of the thermal comfort adaptive model in atropical upland climaterdquo in Proceedings of the 1998 ASHRAEWinter Meeting pp 1194ndash1206 January 1998

[36] T P Lin Y F Ho and Y S Huang ldquoSeasonal effect ofpavement on outdoor thermal environments in subtropicalTaiwanrdquo Building and Environment vol 42 no 12 pp 4124ndash4131 2007

[37] S-A Tan and T-F Fwa ldquoInfluence of pavement materialson the thermal environment of outdoor spacesrdquo Building andEnvironment vol 27 no 3 pp 289ndash295 1992

[38] H Taha ldquoUrban climates and heat islands albedo evapotran-spiration and anthropogenic heatrdquo Energy and Buildings vol25 no 2 pp 99ndash103 1997

[39] T Asaeda and V T Ca ldquoCharacteristics of permeable pavementduring hot summer weather and impact on the thermal envi-ronmentrdquo Building and Environment vol 35 no 4 pp 363ndash3752000

[40] N H Wong S K Jusuf A A la Win H K Thu T SNegara and X C Wu ldquoEnvironmental study of the impact ofgreenery in an institutional campus in the tropicsrdquo Building andEnvironment vol 42 no 8 pp 2949ndash2970 2007

[41] T Ichinose K Shimodozono and K Hanaki ldquoImpact ofanthropogenic heat on urban climate in Tokyordquo AtmosphericEnvironment vol 33 no 24-25 pp 3897ndash3909 1999

[42] E Johansson ldquoInfluence of urban geometry on outdoor thermalcomfort in a hot dry climate a study in Fez Moroccordquo Buildingand Environment vol 41 no 10 pp 1326ndash1338 2006

[43] E Johansson and R Emmanuel ldquoThe influence of urban designon outdoor thermal comfort in the hot humid city of ColomboSri Lankardquo International Journal of Biometeorology vol 51 no2 pp 119ndash133 2006

[44] R Emmanuel and E Johansson ldquoInfluence of urban morphol-ogy and sea breeze on hot humid microclimate the case ofColombo Sri Lankardquo Climate Research vol 30 no 3 pp 189ndash200 2006

[45] F Ali-Toudert and H Mayer ldquoThermal comfort in an east-west oriented street canyon in Freiburg (Germany) under hotsummer conditionsrdquo Theoretical and Applied Climatology vol87 no 1ndash4 pp 223ndash237 2007

[46] F Ali-Toudert and H Mayer ldquoNumerical study on the effectsof aspect ratio and orientation of an urban street canyon onoutdoor thermal comfort in hot and dry climaterdquo Building andEnvironment vol 41 no 2 pp 94ndash108 2006

[47] F Ali-Toudert and H Mayer ldquoEffects of asymmetry galleriesoverhanging facades and vegetation on thermal comfort inurban street canyonsrdquo Solar Energy vol 81 no 6 pp 742ndash7542007

[48] R Emmanuel H Rosenlund and E Johansson ldquoUrbanshadingmdasha design option for the tropics A study in ColomboSri Lankardquo International Journal of Climatology vol 27 no 14pp 1995ndash2004 2007


[49] R Giridharan S S Y Lau and S Ganesan ldquoNocturnal heatisland effect in urban residential developments of Hong KongrdquoEnergy and Buildings vol 37 no 9 pp 964ndash971 2005

[50] Z Bottyan and J Unger ldquoA multiple linear statistical model forestimating the mean maximum urban heat islandrdquo Theoreticaland Applied Climatology vol 75 no 3-4 pp 233ndash243 2003

[51] R Hamdi and G Schayes ldquoSensitivity study of the urban heatisland intensity to urban characteristicsrdquo International Journalof Climatology vol 28 no 7 pp 973ndash982 2008

[52] R Giridharan S S Y Lau S Ganesan and B Givoni ldquoUrbandesign factors influencing heat island intensity in high-risehigh-density environments of Hong Kongrdquo Building and Envi-ronment vol 42 no 10 pp 3669ndash3684 2007

[53] T-P Lin R de Dear and R-L Hwang ldquoEffect of thermaladaptation on seasonal outdoor thermal comfortrdquo InternationalJournal of Climatology vol 31 no 2 pp 302ndash312 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

EcologyInternational Journal of


EarthquakesJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Mining


Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

OceanographyInternational Journal of


Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal ofPetroleum Engineering


GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Atmospheric SciencesInternational Journal of


OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in


MineralogyInternational Journal of


MeteorologyAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geological ResearchJournal of


Geology Advances in


duration) and behavior patterns (eg reading discussing orresting)

To obtain detailed information regarding usersrsquo behaviorpatterns for verifying the relation between behavior andthe thermal environment researchers must firstly determineappropriate observation methods and select an appropriatesite Regarding observational methods similar studies in thepast focused on numbers of attendants and the distributionsof their locations Therefore researchers typically use visualmethods to count the number of attendants and recordtheir locations by using static photographs as supplementaryinformation sources during analyzing

However to document usersrsquo behavior patterns in detaillong-term observation is needed It is often done by meansof scrutinizing continuous dynamic images filming fromvideo camera For example Gomez-Martın and Martınez-Ibarra [14] used webcams to observe the number of peo-ple on beaches employing quantitative visual estimationto determine the number and the density of people atvarious regions and timeframes In their study only usersrsquolocation distribution and the density were analyzed due tothe limitation of webcamrsquos footage resolution therefore thebehavior patterns of users were not assessed Regarding thesite selection actual measurements must be conducted inspaces that are able to demonstrate diversifying thermalenvironments to further analyse the association between thethermal environment and the user behavior patterns Whenusing dynamic video recording the locations of positioningrecording device should be carefully selected to ensure thatan unobstructed full view of the space is captured

Digital video camera was used for dynamic observationstoward a stepped square situated at the outdoor publicrecreational garden of National Museum of Natural Sci-ence (NMNS) in Taichung City Taiwan The chosen squareexhibits diversifying thermal environments which is partiallyshrouded by various thicknesses of tree canopies and partiallysky open and is considered an ideal place to perform on-sitethermal measurements and observations The objectives ofthis study are as follows

(a) to observe the number of space users during variousseasons and determine the histogram of the numberof users against various temperature ranges

(b) to investigate the userrsquos prior selection of activity loca-tions and the amount of time that people remained attheir chosen locations

(c) to analyze the relation between the thermal environ-ment characteristics and the user behavior patterns

Thefindings elucidated space use behaviors in response tothermal environments which would help facilitate decisiondetermining of outdoor space planning and design in thefuture

2 Methods

21 Observational Subjects As previously mentioned theobservation location requires a varied thermal environmentthat comprises unobstructed observation spots for placing

video camera to elucidate howmicroclimateswould influencethe usage of recreation spaces thermal comfort and adaptivebehaviors Therefore a stepped plaza at the outdoor gardenof the NMNS was chosen for long-term observation Figure 1shows that the stepped plaza is located at 24∘081015840N 120∘401015840 Ewith an altitude of 26m The area is approximately 125min width 4m in depth and the observational height rangeof the space is approximately 27m The area comprises fourlevels of steps A lawn is positioned at the front of the stepswith the two sides being turf and shading trees The primaryusers of the space arrive after visiting the museum or attendthe NMNS park for walking or resting Most people remainin the plaza for less than 30 minutes People use the plazawith various behaviors including movements talking andreading

Taichung City exhibits a hot and humid climate Theaverage observed climate data from 1991ndash2010 recorded bythe Central Weather Bureau of Taiwan indicated that themonthlymean air temperature is highest in July at 285∘C andlowest in January at 162∘C Furthermore the mean monthlyrelative humidity is held constantly around 80 all the yearsuggesting a humid climate Since cool air temperature onlyexists from December to February this research defines thisperiod as the ldquocool seasonrdquo and the remainingmonths (MarchtoNovember) as the ldquohot seasonrdquo which is in accordancewiththe definition of previous local studies [7 12 15 16]

22 Shading Characteristics of the Stepped Plaza The shadingcharacteristics of an outdoor space would affect the thermalenvironment [15 16]Therefore the shading characteristics ofthe evaluated stepped plaza must be quantitatively describedBecause trees are mainly located at the south and north sidesof the steps the degree of shade varies along the steps Thesky view factor (SVF) was introduced herein to represent theshading level in an outdoor environment The SVF can bedefined as the percentage of free sky at specific location withthe value ranging from totally obstructed (SVF = 0) to totallyfree spaces (SVF = 1) [17 18]

A small SVF value indicates that a high amount ofshade is present and the range of the visible sky is limitedFigure 2 shows fisheye photos shot in cool season 1500 ofthe external appearance of the stepped plaza and the 10corresponding positions The SVF distribution ranged fromposition B1 which exhibited a high level of shade (SVF =009) to A4 which was relatively open (SVF = 057) Thisindicates that various locations within the stepped plazademonstrated distinct levels of solar insolation depending onthe season and the plaza exhibited varying thermal environ-mental characteristics The SVF values of each location aresimilar whether in hot or cool season due to the surroundingevergreen trees planted in the stepped plaza

23 Data Obtainment Thermal environment measurementsand user behavior observations were performed simultane-ously Physical quantities of microclimatic parameters mea-surements including the air temperature relative humidityglobe temperature and wind speed were measured with twoidentical sets of instruments with which one was placed


N0 25 50

(m)


B1 B2 B3 B4 B5

B1 B2 B4B3 B5

A1 A2 A4A3 A5

A1 A2 A3 A4 A5









59 60

61 62

(a) 1532

60

61 6259

(b) 1534

6061 62

59

(c) 1535









3 Results




010

5

2015

3025

4035

5045

PET

(∘C)

PET (∘C)

02010

4030

6050

8070

10090

Num

bers

of p

eopl

e

15 A

pril

21 A

pril

21 M

ay16

June

21 Ju

ly29

July

16 S

epte

mbe

r23

Sep

tem

ber

14 O

ctob

er28

Oct

ober

10 N

ovem

ber

18 N

ovem

ber

09 D

ecem

ber

15 D

ecem

ber

29 D

ecem

ber

06 Ja

nuar

y19

Janu

ary

20 Ja

nuar

y23

Feb

ruar

y

Numbers of people



0

10

20

30

40

50

18 20 22 24 26 28 30 32 34 36 38 40 42 44


PET (∘C)

Num

bers

of p

eopl

e











Stay behind

92

Move to sun areas

3


5In sun areas22

In shaded areas75


3

(a) Hot season

In sun areas13

In shaded areas87


0

Stay behind

99

Move to sun areas

0


1

(b) Cool season


0000

0600

1200

1800

2400

3000

3600

4200


Aver

age s

tay

time (

mm

ss)


Average


75 percentile








0000

0300

0600

0900

1200

1500

1800

2100

29 31 33 35 37

Aver

age s

tay

time (

mm

ss)

PET in hot seasons






34 22

3832

6678

62 68

0

20

40

60

80

100

In sun areas

In shaded areas

In sun areas

In shaded areas

Freq

uenc

ies (

)














119901) 119879119899is a temper-









119899and 119879



119901(256∘C) of the hot







5 Conclusion












References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


N0 25 50

(m)


B1 B2 B3 B4 B5

B1 B2 B4B3 B5

A1 A2 A4A3 A5

A1 A2 A3 A4 A5









59 60

61 62

(a) 1532

60

61 6259

(b) 1534

6061 62

59

(c) 1535









3 Results




010

5

2015

3025

4035

5045

PET

(∘C)

PET (∘C)

02010

4030

6050

8070

10090

Num

bers

of p

eopl

e

15 A

pril

21 A

pril

21 M

ay16

June

21 Ju

ly29

July

16 S

epte

mbe

r23

Sep

tem

ber

14 O

ctob

er28

Oct

ober

10 N

ovem

ber

18 N

ovem

ber

09 D

ecem

ber

15 D

ecem

ber

29 D

ecem

ber

06 Ja

nuar

y19

Janu

ary

20 Ja

nuar

y23

Feb

ruar

y

Numbers of people



0

10

20

30

40

50

18 20 22 24 26 28 30 32 34 36 38 40 42 44


PET (∘C)

Num

bers

of p

eopl

e











Stay behind

92

Move to sun areas

3


5In sun areas22

In shaded areas75


3

(a) Hot season

In sun areas13

In shaded areas87


0

Stay behind

99

Move to sun areas

0


1

(b) Cool season


0000

0600

1200

1800

2400

3000

3600

4200


Aver

age s

tay

time (

mm

ss)


Average


75 percentile








0000

0300

0600

0900

1200

1500

1800

2100

29 31 33 35 37

Aver

age s

tay

time (

mm

ss)

PET in hot seasons






34 22

3832

6678

62 68

0

20

40

60

80

100

In sun areas

In shaded areas

In sun areas

In shaded areas

Freq

uenc

ies (

)














119901) 119879119899is a temper-









119899and 119879



119901(256∘C) of the hot







5 Conclusion












References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


59 60

61 62

(a) 1532

60

61 6259

(b) 1534

6061 62

59

(c) 1535









3 Results




010

5

2015

3025

4035

5045

PET

(∘C)

PET (∘C)

02010

4030

6050

8070

10090

Num

bers

of p

eopl

e

15 A

pril

21 A

pril

21 M

ay16

June

21 Ju

ly29

July

16 S

epte

mbe

r23

Sep

tem

ber

14 O

ctob

er28

Oct

ober

10 N

ovem

ber

18 N

ovem

ber

09 D

ecem

ber

15 D

ecem

ber

29 D

ecem

ber

06 Ja

nuar

y19

Janu

ary

20 Ja

nuar

y23

Feb

ruar

y

Numbers of people



0

10

20

30

40

50

18 20 22 24 26 28 30 32 34 36 38 40 42 44


PET (∘C)

Num

bers

of p

eopl

e











Stay behind

92

Move to sun areas

3


5In sun areas22

In shaded areas75


3

(a) Hot season

In sun areas13

In shaded areas87


0

Stay behind

99

Move to sun areas

0


1

(b) Cool season


0000

0600

1200

1800

2400

3000

3600

4200


Aver

age s

tay

time (

mm

ss)


Average


75 percentile








0000

0300

0600

0900

1200

1500

1800

2100

29 31 33 35 37

Aver

age s

tay

time (

mm

ss)

PET in hot seasons






34 22

3832

6678

62 68

0

20

40

60

80

100

In sun areas

In shaded areas

In sun areas

In shaded areas

Freq

uenc

ies (

)














119901) 119879119899is a temper-









119899and 119879



119901(256∘C) of the hot







5 Conclusion












References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


010

5

2015

3025

4035

5045

PET

(∘C)

PET (∘C)

02010

4030

6050

8070

10090

Num

bers

of p

eopl

e

15 A

pril

21 A

pril

21 M

ay16

June

21 Ju

ly29

July

16 S

epte

mbe

r23

Sep

tem

ber

14 O

ctob

er28

Oct

ober

10 N

ovem

ber

18 N

ovem

ber

09 D

ecem

ber

15 D

ecem

ber

29 D

ecem

ber

06 Ja

nuar

y19

Janu

ary

20 Ja

nuar

y23

Feb

ruar

y

Numbers of people



0

10

20

30

40

50

18 20 22 24 26 28 30 32 34 36 38 40 42 44


PET (∘C)

Num

bers

of p

eopl

e











Stay behind

92

Move to sun areas

3


5In sun areas22

In shaded areas75


3

(a) Hot season

In sun areas13

In shaded areas87


0

Stay behind

99

Move to sun areas

0


1

(b) Cool season


0000

0600

1200

1800

2400

3000

3600

4200


Aver

age s

tay

time (

mm

ss)


Average


75 percentile








0000

0300

0600

0900

1200

1500

1800

2100

29 31 33 35 37

Aver

age s

tay

time (

mm

ss)

PET in hot seasons






34 22

3832

6678

62 68

0

20

40

60

80

100

In sun areas

In shaded areas

In sun areas

In shaded areas

Freq

uenc

ies (

)














119901) 119879119899is a temper-









119899and 119879



119901(256∘C) of the hot







5 Conclusion












References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


Stay behind

92

Move to sun areas

3


5In sun areas22

In shaded areas75


3

(a) Hot season

In sun areas13

In shaded areas87


0

Stay behind

99

Move to sun areas

0


1

(b) Cool season


0000

0600

1200

1800

2400

3000

3600

4200


Aver

age s

tay

time (

mm

ss)


Average


75 percentile








0000

0300

0600

0900

1200

1500

1800

2100

29 31 33 35 37

Aver

age s

tay

time (

mm

ss)

PET in hot seasons






34 22

3832

6678

62 68

0

20

40

60

80

100

In sun areas

In shaded areas

In sun areas

In shaded areas

Freq

uenc

ies (

)














119901) 119879119899is a temper-









119899and 119879



119901(256∘C) of the hot







5 Conclusion












References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0000

0300

0600

0900

1200

1500

1800

2100

29 31 33 35 37

Aver

age s

tay

time (

mm

ss)

PET in hot seasons






34 22

3832

6678

62 68

0

20

40

60

80

100

In sun areas

In shaded areas

In sun areas

In shaded areas

Freq

uenc

ies (

)














119901) 119879119899is a temper-









119899and 119879



119901(256∘C) of the hot







5 Conclusion












References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in






119901) 119879119899is a temper-









119899and 119879



119901(256∘C) of the hot







5 Conclusion












References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in










References

































































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

















































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

research article investigating thermal comfort and...

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