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Building and Environment 50 (2012) 76e89

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Building and Environment

journal homepage: www.elsevier .com/locate/bui ldenv

Human thermal adaptive behaviour in naturally ventilated offices for differentoutdoor air temperatures: A case study in Changsha China

Weiwei Liu a,*, Yun Zheng a, Qihong Deng a,*, Liu Yang b

a School of Energy Science & Engineering, Central South University, Changsha, Hunan, Chinab School of Software, Hunan University, Changsha, Hunan, China

a r t i c l e i n f o

Article history:Received 4 August 2011Received in revised form14 October 2011Accepted 19 October 2011

Keywords:Thermal adaptationBehaviourNatural ventilationClimate changeOutdoor air temperature

* Corresponding authors. Tel.: þ86 731 88877175.E-mail addresses: wliu@mail.csu.edu.cn (W. L

(Q. Deng).

0360-1323/$ e see front matter � 2011 Elsevier Ltd.doi:10.1016/j.buildenv.2011.10.014

a b s t r a c t

The present study gave a comprehensive insight into the relationship between human thermal adaptivebehaviour and the change of climate conditions. A long-term survey was carried out from Jan. 2010 toFeb. 2011 in two naturally ventilated offices, located in Changsha, China. During the survey, occupants’thermal adaptive behaviour (use of various controls) was investigated daily. The controls includedwindow, door, curtain, fan, hand heater and air-conditioner. Relativity analysis indicated that outdoor airtemperature is the most important climate parameter that caused the use of controls. The effects ofoutdoor air temperature on the use of each control were further analyzed from three aspects: usageproportion, usage degree and transition of control state. Based on the analysis, the characteristics of thethermal adaptive behaviour in the offices were revealed. And also, the differences between the twooffices located in different types of building were discussed. The results of this study are helpful to adaptthe built environment in naturally ventilated buildings to the change of climate conditions.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

In the era of increasing energy consumption, there is a strongincentive to reduce energy use in buildings. As indicated byprevious field studies [1e3], naturally ventilated buildings couldprovide a wider range of comfortable indoor temperature foroccupants if sufficient adaptive opportunities are afforded, withsignificant decrease in the energy consumption for cooling andheating. Human thermal adaptation is an important way toapproach thermal comfort in naturally ventilated buildings [4]. Theprinciple underlying the thermal adaptation reveals that “Ifa change occurs such as to produce discomfort, people react in wayswhich tend to restore their comfort” [5]. Obviously, occupants’thermal adaptive behaviour plays a significant role in restoringtheir comfort under the effect of climate change [6,7], whichreflects the interaction between occupants and environmentalcontrols in the buildings. Therefore, understanding human thermaladaptive behaviour is of significance for creating a comfortableindoor environment in naturally ventilated buildings.

Multiple researchers were devoted to occupants’ adaptivebehaviour in various buildings under different climates. Most of the

iu), qhdeng@mail.csu.edu.cn

All rights reserved.

researches described the use of various controls based on thecombination of data from several buildings, with a main target toestablish simulation models of occupants’ behaviour [8e13].Usually, the proportion of using a control at different outdoor/indoor air temperatures was calculated and the relation betweenthemwas described using logistic regression. However, the presentresults are not sufficient to reflect the characteristics of thermaladaptive behaviour, when only the proportion of using a controlwas investigated. With global warming, it needs a comprehensiveinsight into the relationship between human thermal adaptivebehaviour and the change of climate conditions, which can providea basis for adapting the built environment to be able to cope withdifferent climate conditions. This was the purpose of this study.

The main thought of this study was depicted as follows. First itwas supposed that the thermal adaptive behaviour is driven by theseasonal change of climate conditions, which is the original factorto cause the variation of indoor thermal environment, and theninfluence occupants’ thermal sensation, a direct element to inducethe adaptive behaviour. Then, based on this assumption, the char-acteristics of thermal adaptive behaviour under different climateconditions were revealed from three aspects: usage proportion,usage degree and transition of control state.

Changsha is the capital of Hunan province in China, witha climate of hot summer and cold winter. The variation of climate ina whole year is significant. Therefore the climatic characteristics of

Nomenclature

b regression coefficient for logistic regressionequation

c constant in logistic regression equationCLO ensemble clothing insulationp probabilityta air temperature (�C)tg globe temperature (�C)tr mean radiant temperature (�C)T outdoor temperature (�C)R2 determination coefficientq characteristic temperature (�C)

W. Liu et al. / Building and Environment 50 (2012) 76e89 77

Changsha provide a good case study. Considering the period (oneyear) of the variation in climate condition, the analysis of occu-pants’ thermal adaptive behaviour should be performed based ona period of whole year. This is different from most previous studiesthat investigate occupants’ thermal adaptive behaviour in oneseason. Therefore, a long-term (more than one year) survey wascarried out in two selected offices of two different types of naturallyventilated buildings. Occupants in the offices can use variouscontrols freely. The use of each control was recorded during thissurvey. On the basis of the survey, we tried to answer followingquestions:

� What was the trend for possibility of using a control with thechange of climate condition?

� How did people regulate the state of a control according toclimate condition when they were using it?

� Whenmight the transition of control state happen, consideringthe variation in climate condition?

� What was the thermal adaptive behaviour pattern during thelong period of survey?

In this study, the analysis was separately done for each office toinvestigate the difference between different offices.

2. Methods

2.1. Description of building

The long-term survey was carried out in two naturally venti-lated office buildings, located in Central South University, Chang-sha, China. As shown in Fig. 1(a), building A, a four-storey building,houses offices for teachers and graduated students on two floors(the second and third floor), and building B, a courtyard house, forgraduated students. In each building, one officewas selected for thesurvey (see Fig. 1(b)).

Office A, a west-facing room on the third floor of building A, hasan area of 40 m2 (7.7 � 5.2 m) and a height of 3 m. There are twooperable windows in north wall and one operable window and onedoor in west wall. For the window in west wall, a controllableinternal curtain is installed to provide the possibility to cover it. Afloor-standing air-conditioner (cooling and heating) is equipped inone corner of this office, which is only used in hot (summer) andcold (winter) weather.

Office B is a south-facing room in building B with an area of43.2 m2 (7.2 � 6 m) and a height of 4.5 m. It has one operablewindow and one door in its south wall and two windows (alwaysclosed) in north wall. All the windows can be covered with internal

controllable curtains. A floor-standing air-conditioner is equippedin themiddle place close to northwall. Different from office A, thereare four wall fans and two ceiling fans in office B, which alsoprovide a cooling strategy for human body in hot weather.

The controls consuming electric power in both offices wereshown in Fig. 1(c).

2.2. Subjects

Each office can accommodate 4e8 occupants, which was verycommon in universities of China. All occupants in both offices arehealthy graduated students, including 9 males and 6 females(mean � SEM of age: 23.9 � 0.6 years, height: 168.6 � 2.1 cm,weight: 59.9 � 2.6 kg). They mainly carried out office related work,such as reading, writing and typing in a computer. Every one haslived in the university for at least one year and is acclimatized to theclimate in Changsha. All of them participated as subjects in thelong-term survey. All protocols were approved by the university’sethics committee and conformed to the guidelines containedwithin the Declaration of Helsinki. Verbal and written informedconsent was obtained from each subject prior to the participationin the survey.

2.3. Instrumentation

Four important indoor thermal environment parameters weremonitored. Air velocity, temperature and relative humidity werecollected using a multifunctional heat line anemoscope (TSI 9545-AVELOCICALC, TSI Incorporated, USA). Globe temperature wasmeasured with a standard black-bulb (D 150 mm, KIMO, FR). Theprecision of each instrument is listed in Table 1. Mean radianttemperature obtained according to Eq. (1) [14],

tr ¼hðtg þ 273Þ4þ0:4� 108ðtg � taÞ5=4

i1=4�273 (1)

where tr is mean radiant temperature, tg globe temperature and tais air temperature.

The indoor environmental parameter measurement site waslocated near the subject at 1.1 m height, as displayed in Fig. 1(b).

2.4. Experimental protocol

The survey was conducted daily from Jan. 2010 to Feb. 2011,except for some holidays such as most days during summer andwinter vacations (Jul.eAug. and Jan.eFeb.). Every day, researcherscarried out the survey three times (morning/afternoon/night) atmost. The periods for the survey in morning, afternoon and nightwere respectively 10:30e11:30, 16:00e17:00 and 20:00e21:00.The survey was done on the subjects being in the offices for at least20 min.

The survey obtained important information about the indoorthermal environment and subjects’ thermal responses and adaptivebehaviour. During a single survey, each subject in both offices wasasked to fill out an electronic questionnaire reflecting theirsubjective responses, clothing, and activity level in the preceding20 min. At the same time, the thermal environment close to eachsubject was continuouslymonitored for 5min. Subjects’ controls onwindow, door, curtain, fan and air-conditioner were carefullyrecorded. The time spent in each office was about 30 min.

2.5. Design of questionnaire

The questionnaire was designed to provide the following maininformation:

Table 1Instruments for measurement of indoor thermal environment parameters used inthe survey.

Parameter Instrument Range Accuracy Resolution

Globe temperature Digital thermometerTR102

�100e400 �C �0.3 �C 0.1 �C

Air temperature Velocicalc TSI-9545 �10e60 �C �0.3 �C 0.1 �CAir velocity Velocicalc TSI-9545 0e30 m/s �3% 0.01 m/sRelative humidity Velocicalc TSI-9545 0e95% �3% 0.10%

Fig. 1. Pictures of naturally ventilated offices during the long-term survey.

W. Liu et al. / Building and Environment 50 (2012) 76e8978

(1) Subjective thermal responses, including thermal sensation,thermal comfort, thermal acceptability and thermalpreference.

(2) Current clothing level. The subjects were asked to record thecombination of their clothing in order from underwear toouterwear. A fairly detailed clothing garment list was providedfor reference.

(3) Activity level in the preceding 20 min. This item asked thesubjects to describe the primary activity during the last 20 minin the offices.

W. Liu et al. / Building and Environment 50 (2012) 76e89 79

(4) Other subjective responses such as feeling on air movement,humidity sensation, mood and feeling on work productivity.

The questionnaire was written in Chinese. The subjectscompleted the questionnaire on their computers in 5 min.

For the aim of this study, the indoor thermal environment andsubjects’ thermal responses were not analyzed in the paper.

2.6. Meteorological data

Meteorological data for the period of survey were obtained froma local station near the university. The data used in this studycontains outdoor air temperature, humidity and wind speed. Theywere recorded on an hourly basis.

2.7. Statistical analysis

Logistic regression and linear regression equations were appliedto quantitatively describe the change of occupants’ thermal adap-tive behaviours with different climate conditions, which was oftenused in previous studies [e.g. 8, 15].

Logistic regression is a useful statistical method for a binaryvariable (i.e. windows/door open or closed) whose probabilityvaries with a stimulus (i.e. outdoor temperature in this study).Logistic regression equation is given as:

logitðpÞ ¼ log�

p1� p

�¼ bT þ c (2)

where

p ¼ eðbTþcÞ

1þ eðbTþcÞ (3)

p is the probability that the adaptive behaviour appeared, forexample the proportion of window opening at an outdoor airtemperature. T is the outdoor temperature, b the regression coef-ficient and c is the constant in the regression equation.

Fig. 2. The change of climate parameters (mea

To evaluate a regression equation, determination coefficient R2

was used to indicate the goodness of fit and the level of significancewas set at sig. <0.05.

3. Results and analysis

3.1. Change of climate condition during the survey

The climate condition was reflected using three main parame-ters: outdoor air temperature, air humidity and air velocity.Statistical results (hourly data) of these climate parameters in eachmonth over whole period of the longitudinal survey are shown inFig. 2. Obvious variation can be seen in outdoor air temperature.The mean of outdoor air temperature reached the highest value(30.8 �C) in Jul. 2010 and fell to the lowest (2.3 �C) in Jan. 2011. Foroutdoor air humidity and velocity, the variation inmeanswasmuchsmaller. The mean air humidity of each month ranged from 60% to80% and the mean air velocity varied between 0.5 and 1.6 m/s.However, the standard deviations of air humidity and velocity ineach month were bigger than that of air temperature.

Statistical result of climate data in a single survey (sample) wascompared with that during the whole period from Jan. 2010 to Feb.2011 (population). The total number of samples was 524 (onesample included three parameters). The result shown in Table 2indicated that there were only slight differences between thesample and population. Additionally, the variation of each climateparameter with month was similar for the sample and the pop-ulation. Therefore, the samples of the survey can well reflect theclimate change during the whole period.

3.2. Description of thermal adaptive behaviour

Thermal adaptive behaviour observed in the survey includeduse of various controls on indoor and personal environment. Thecontrols on indoor environment were window, door, curtain, fanand air-conditioner, and the controls on personal environmentwere clothing and electric hand heater (see Fig. 1(c)). In this study,

n � SD) in each month during the survey.

Table 2Comparison of climate data between a single survey (sample) and the whole period(population).

Temperature (�C) Relative humidity (%) Air velocity (m/s)

Sample Population Sample Population Sample Population

Min �1.5 �3.0 18.5 12.0 0.0 0.0Max 37.0 39.0 97.0 98.0 6.3 7.2Mean 17.3 16.3 65.9 69.8 1.3 1.0S.D. 9.4 9.8 17.4 16.8 1.2 1.2

Sample means the data of one measurement in the survey. Population means thedata in the whole period from Jan. 2010 to Feb. 2011.

W. Liu et al. / Building and Environment 50 (2012) 76e8980

the “use” means “open/on” for the controls except curtain andclothing, while for curtain it means “closed”.

In this survey, there were 2159 records for subject’s clothing andtotal 1748 records for use of other controls in offices A and B. Some-times two or more controls were used at the same time. The combi-nation of different control usage appeared in the survey is depicted inTable 3. The total records of the combination usage were 681.

Fig. 3 illustrates the distribution of use of each control and theircombination usage during the survey, respectively. As depicted inFig. 3(a) the use of window and curtain possessed the highestproportion, the frequency of door usage was slightly lower, and theproportion of fan usage was least.

For the combination usage shown in Fig. 3(b), the proportion ofdoor and window opening (DW) was highest, followed by thecombinations of air-conditioner and curtain (AC), door, windowand curtain (DWC). The records that air-conditioner and fan usedtogether were very few, taking the lowest proportion. Usually,when fan was used, window and door remained open. On thecontrary, both window and door were closed, once air-conditionerwas working. However, a small frequency for window openingwhen air-conditioner on (AW, AWC and AWCH) was still seen inFig. 3(b), due to the requirement on fresh air or forgetting to closethe window.

Fig. 3. Frequency distribution for control usage during the survey. The meanings ofabbreviations for combination of controls are listed in Table 3.

3.3. Variation in use of control with climate

3.3.1. Relativity between behaviour frequency and climateparameters

In order to determine the most important climate parameterrelated to occupants’ thermal adaptive behaviour, relativitybetween the usage percentage of various controls and each climate

Table 3Combination of use of different controls appeared in the survey.

No. Combination of controls Abbreviation

1 Air-conditioner þ Curtain AC2 Air-conditioner þ Fan AF3 Air-conditioner þ Hand heater AH4 Air-conditioner þ Window AW5 Curtain þ Hand heater CH6 Door þ Curtain DC7 Door þ Hand heater DH8 Door þ Window DW9 Window þ Curtain WC10 Window þ Hand heater WH11 Air-conditioner þ Curtain þ Hand heater ACH12 Air-conditioner þ Window þ Curtain AWC13 Door þ Curtain þ Fan DCF14 Door þ Window þ Curtain DWC15 Door þ Window þ Fan DWF16 Door þ Window þ Hand heater DWH17 Window þ Curtain þ Hand heater WCH18 Air-conditioner þ Window þ Curtain þ Hand heater AWCH19 Door þ Window þ Curtain þ Fan DWCF20 Door þ Window þ Curtain þ Hand heater DWCH

parameter was analyzed. Table 4 illustrates the result calculated onamonthly basis. Here, the percentage for use of a control means theproportion of the events that the control was used to the totalobservation number in a month.

According to Table 4, there was moderate or strong correlationbetween the use of each control and outdoor air temperature, whileno significant correlation between the control usage and outdoorair velocity. The use of most controls had no significant relationwith outdoor air humidity. The relativity indicated that outdoor airtemperature should be the crucial climate parameter that inducedthermal adaptive behaviour. In previous studies [8,13,16], outdoorair temperature was also regarded as an important thermal stim-ulus to use of controls. Therefore, outdoor air temperature wasselected as the basis for further analysis in this study.

3.3.2. Usage proportion of controls at different outdoor airtemperatures

The quantitative relationship between the use of each controland outdoor air temperature was analyzed based on usageproportion. Usage proportion is defined as a ratio of number of

Table 4Relativity between percentages for the use of various controls and each climate parameter.

Door Window Curtain Fan Air-conditioner (cooling) Air-conditioner (heating) Hand heater

Outdoor air temperature 0.698a 0.567b 0.831a 0.791a 0.764a �0.823a �0.868a

Outdoor air velocity 0.006 0.005 0.006 0.035 0.093 �0.191 �0.252Outdoor air relative humidity 0.576b 0.421 0.221 0.398 0.085 �0.577b �0.408

The relativity was obtained on a monthly basis.a Correlation is significant at 0.01 level (2-tailed).b Correlation is significant at 0.05 level (2-tailed).

W. Liu et al. / Building and Environment 50 (2012) 76e89 81

records that a control is used to total observation number at oneoutdoor air temperature, which reflects the possibility of a controlbeing used at the outdoor air temperature.

When calculating the value of usage proportion, all records ofthermal adaptive behaviour were grouped into outdoor airtemperature bins with 1 �C interval. For example, the temperaturebin of 25 �C contains the records in the range of outdoor airtemperatures from 24.5 to 25.4 �C. In the analysis on usageproportion and degree (described in next section) of window, door,curtain, fan and hand heater, the records with air-conditioner on(taking a very small proportion) were excluded considering that theuse of air-conditioner eliminate the direct influence of climateconditions.

3.3.2.1. Proportion of single usage. The usage proportion of a controlin each outdoor air temperature bin of offices A and B was depictedin Figs. 4 and 5, respectively. As shown in Fig. 4, door opening andair-conditioner cooling events were observed in office A only whenoutdoor air temperature was higher than certain values. Theirproportions increased with outdoor air temperature rising, and

Fig. 4. Usage proportion for single control at dif

reached 1.0 at higher temperatures. Compared with door and air-conditioner (cooling), the usage proportion of air-conditioner(heating) and hand heater had opposite trend with the rise ofoutdoor air temperature. The proportion of window open alsoincreased when outdoor air temperature rose, however the trendwas not significant when outdoor air temperature higher than15 �C, because the proportion always varied between 0.8 and 1.0.For the use of curtain (closed), it always kept a higher proportion(0.8e1.0) during the survey and no clear trend with outdoor airtemperature was observed.

As shown in Fig. 5, the trends of usage proportions of door, air-conditioner and hand heater in office B were similar to those inoffice A. However, obvious difference can be seen in the variation ofthe proportion of window and curtain usage between office A andB. Both controls in office B had a clear upward trend in usageproportions with the increase in outdoor air temperature asdepicted in Fig. 5. As mentioned before, the subjects in office B usedfans in hot weather. The fan was used when the outdoor airtemperature was higher than 23 �C during the survey and theproportion of usage rose to 1.0 at 33 �C.

ferent outdoor air temperatures in office A.

Fig. 5. Usage proportion for single control at different outdoor air temperatures in office B.

W. Liu et al. / Building and Environment 50 (2012) 76e8982

The quantitative relationship between the usage proportion ofeach control and outdoor air temperature was obtained usinglogistic regression (see Eq. (2) and (3)). The results are summarizedin Table 5.

3.3.2.2. Proportion of combination usage. As depicted before,window, curtain and door were used most frequently and thecombination usage between the three controls took biggerproportion in the total records. Here, the usage proportion of thecombinations between window and door and between window,door and curtainwere investigated. Fig. 6 illustrates the variation inthe proportion of the combination usage with outdoor airtemperature in offices A and B. In office A, it was seen that the trendof the usage proportion for each combination was similar to that ofdoor open. In office B, the trend of the proportion for the

Table 5Logistic regression for the relationship between the usage proportion of each control an

Control usage Office A

b c

Single Door 0.373** �7Window 0.124** �0Curtain �0.017 3Air-conditioner (cooling) 0.683** �19Air-conditioner (heating) �0.396** 3Hand heater �0.324** 3Fan e e

Combination Door þ Window 0.348** �7Door þ Window þ Curtain 0.329** �7

**Correlation is significant at 0.01 level (2-tailed).b is the regression coefficient and c the constant given in the regression Eq. (3). R2 is the

combination usage of window and door was similar to that ofwindow open and the trend for the combination usage of window,door and curtain resembled that of curtain closed. The logisticregression results in Table 5 confirmed this observation. Thepossibly reason could be that the trend of the combination usagemainly depends on the single control usage which possessesa smaller proportion at the same outdoor temperature.

3.3.2.3. Variation rate of usage proportion. Based on the logisticregression in Table 5, three characteristic temperatures, i.e., q5, q50and q95 for each control were obtained as given in Table 6, whichwere the outdoor air temperatures corresponding to usageproportions of 5%, 50% and 95%, respectively. The values of windowand curtain for office Aweremissing because the logistic regressionequations were insignificant (P > 0.05) and R2 was very low.

d outdoor air temperature.

Office B

R2 b c R2

.933** 0.549 0.382** �4.206** 0.566

.199 0.115 0.288** �4.853** 0.522

.039** 0.004 0.403** �10.52** 0.573

.35** 0.783 0.852** �27.721** 0.75

.114** 0.712 �0.666** 3.505** 0.787

.427** 0.465 �0.342** 2.114** 0.418e 0.621** �16.792** 0.683

.597** 0.517 0.337** �5.915** 0.597

.384** 0.486 0.385** �10.183** 0.557

determination coefficient.

Fig. 6. Usage proportion for combination of controls at different outdoor air temperatures.

W. Liu et al. / Building and Environment 50 (2012) 76e89 83

As indicated by the values of regression coefficient b list inTable 5, the variation rate of the proportion of air-conditioner usagewas biggest, while that of window open was least, which reflecteddistinct sensitivity of different control usage to outdoor airtemperature around the corresponding characteristic temperatureq50.

Further, the variation rate was quantitatively estimated usingthe corresponding average in the temperature range from q5 to q95,which was calculated by the ratio of the change of usage proportion(90%) to the difference between q5 and q95 (see Table 6). Clearly, theaverage variation rates of window, door and curtain (about 5%/�C)were smaller than those of fan and air-conditioner (about 10%/�C),meaning that the variation in usage proportion of the latter wasmuch faster though they were only used in hot or cold weather.

3.3.3. Usage degree of controls at different outdoor air temperaturesUsage degree was proposed to evaluate how occupants regulate

the state of a control to adapt to the change of climate conditionswhen they are using the control. It is a more refined index to reflect

Table 6Characteristic temperatures for each control usage and variation rate of usage proportio

Control Office A

q5 (�C) q50 (�C) q95 (�C) Variation r

Door 13.4 21.3 29.2 5.7Window e e e e

Curtain e e e e

Air-conditioner (cooling) 24.0 28.3 32.6 10.5Air-conditioner (heating) 15.3 7.9 0.4 �6.0Hand heater 19.7 10.6 1.5 �4.9Fan e e e e

q5, q50 and q95 were the outdoor air temperatures corresponding to usage proportions o

the thermal adaptive behaviour. Calculation of usage degreemay bedifferent for different type of controls.

3.3.3.1. Usage degree for window, door and curtain. For window,door and curtain, usage degree was defined as a ratio of the area ofwindow/door open or curtain closed to the total. During the survey,values of the area were estimated by the researchers. Fig. 7 displaysthe change of usage degree (Mean in 1 �C temperature bin) withoutdoor air temperature for window, door and curtain in offices Aand B, respectively.

As shown in Fig. 7, the change of the usage degree of door ineach office was small, which means the effect of outdoor airtemperature on opening area of door was weak, though its effect onthe usage proportion of door was significant as described in the lastsection.

The usage degrees of window and curtain were found to berelated to outdoor air temperature. However, the trends of usagedegree in offices A and B were different. For window, the usagedegree in office A increased with the increase in outdoor air

n with outdoor air temperature.

Office B

ate (%/�C) q5 (�C) q50 (�C) q95 (�C) Variation rate (%/�C)

3.3 11.0 18.7 5.86.6 16.9 27.1 4.4

18.8 26.1 33.4 6.229.1 32.5 36.0 13.09.7 5.3 0.8 �10.1

14.8 6.2 �2.4 �5.222.3 27.0 31.8 9.5

f 5%, 50% and 95%, respectively.

Fig. 7. Usage degree for door, window and curtain at different outdoor air temperatures. y means the usage degree and To the outdoor air temperature. R2 is the determinationcoefficient.

W. Liu et al. / Building and Environment 50 (2012) 76e8984

temperature, while that in office B first increased, and thendecreased when the outdoor air temperature was higher than23 �C. As to curtain, the usage degree in office A reduced whenoutdoor air temperature increased. Interestingly, an opposite trendcan be observed for the variation in the usage degree of curtain inoffice B, and the variation rate was smaller.

3.3.3.2. Usage degree for hand heater and fan. In offices A and Bmost students used hand heaters in winter and in office B each fanwas controlled independently. Therefore, usage degree of handheater or fan was calculated as the proportion of the number ofhand heaters or fans which were using to the total number. Theresults are shown in Fig. 8.

It can be seen that both offices had similar trend of usage degreefor hand heater, though its value in office A was higher at the sameoutdoor air temperature. Unexpectedly, the usage degree of handheater reached the maximum under middle outdoor air tempera-tures (6e8 �C in office A and 10e13 �C in office B) instead of lowertemperatures,meaning that less occupants used hand heaterswhenthe climate became colder. We checked the indoor thermal envi-ronment data and found that the indoor air temperatures under themiddle outdoor air temperatureswere almost lowest in both offices.This may be amain reason to the trend of hand heater usage degree.

Fans were used in office B. Fig. 8 demonstrates that the usagedegree of fan gradually rose to the maximum of 1.0, when theoutdoor air temperature increased from 23 �C to 34 �C, whichindicated that more and more students in office B used fans whenthe climate getting hotter.

3.3.3.3. Usage degree for clothing. For clothing usage degree isevaluated using ensemble clothing insulation (CLO). According tothe records of subjects’ clothing in the survey, CLO was estimatedbased on procedures in ASHRAE Standard 55 [17].

Fig. 9 gives mean CLO at different outdoor air temperatures. Asrevealed by Fig. 9, the trends of mean CLO were very similar in bothoffices. First, the CLO varied between 0.2 and 1.7 during the wholesurvey period. Second, the CLO decreased with increasing outdoorair temperature when it was not higher than about 33 �C. After thattemperature, variation in the CLOwas tiny because the clothing cannot be reduced any more. The regression analysis indicated that thecorrelation between CLO and outdoor air temperature was veryhigh with R2 higher than 0.93. These results agreed with the find-ings in some earlier studies [18,19].

3.3.4. Transition of control state due to outdoor temperaturevariation

Transition of control statemeans the change froma previous stateto a different state, such as a shift of window from open to closed.Table 7 illustrates the frequency of control state change and corre-sponding outdoor air temperatures (atwhich the transition had beenfinished). It can be shown that the transition events of differentcontrols occurred in different temperature ranges and the frequen-cies varied between 0 and 0.4 under most temperatures, which re-flected occupants’ thermal adaptation by changing the state of eachcontrol. This value is higher than the value found in a previous studycarried out in UK [9], in which the observed probability of a windowstate change in naturally ventilated offices (just for one or twopeople) varied between 0 and 0.3 during intermittent hours.

Further investigationwas conducted on the variation in outdoorair temperature (temperature variation) when the transition ofcontrol state occurred. The temperature variation (Mean in 1 �Cinterval) at different outdoor air temperatures were shown inFigs. 10 and 11 (the result of curtain in office B was not givenbecause of only three points). Here, the outdoor air temperaturewas the value corresponding to previous control state and thetemperature variationwas calculated as the difference between the

Fig. 8. Usage degree for hand heater and fan at different outdoor air temperatures. ymeans the usage degree and To the outdoor air temperature. R2 is the determinationcoefficient.

W. Liu et al. / Building and Environment 50 (2012) 76e89 85

outdoor air temperature for current control state and that forprevious control state. As illustrated by Figs. 10 and 11, for door,window, air-conditioner (cooling) and fan, in most cases the tran-sition from closed/off to open/on occurred as the variation inoutdoor air temperature was positive, whereas the transition fromopen/on to closed/off usually happened when the variation inoutdoor air temperature was negative. While for air-conditioner(heating) and hand heater, reversed relation between state transi-tion and temperature variation can be observed in Figs. 10 and 11.As to curtain, the relation was not clear.

The link between the temperature variation and the outdoor airtemperature was revealed using linear regression. It can be seenthat the value of R2 was very low (<0.1) for the state shift of somecontrols such as the window and air-conditioner (heating) in officeA, which indicates a less significant relation between temperaturevariation and outdoor air temperature. However, a clearlydecreasing trend of the temperature variation can still be observedfor most of the control state transition, with negative values ofslope for regression lines.

For door, window, air-conditioner (cooling) and fan, it is alsointeresting to find that the regression line corresponding to thetransition from closed/off to open/on was above the line for thetransition from open/on to closed/off in the whole temperaturerange. In contrast, air-conditioner (heating) and hand heaterpossessed contrary situation on the regression lines for differentstate transition. This can be explained by the above describedrelation between the state transition and temperature variation.

4. Discussion

The change of climate conditions was assumed to be the originalthermal stimuli to drive human thermal adaptive behaviour innatural ventilation buildings in this study. Among the climateparameters, outdoor air temperature, as indicated by the relativityanalysis, was the most important one to describe the thermaladaptive behaviour. Therefore, the characteristics of occupants’adaptive behaviour to climate change were revealed by linking thebehaviour with the variation of outdoor air temperature. To betterqualitatively understand their relationship, we analyzed usageproportion, usage degree and state transition of each control.

The usage proportion provided a basis to find out the thermaladaptive behaviour pattern during the long period of survey. Firstthe characteristic temperatures q5 and q95 (see Table 6), calculatedbased on the usage proportion, were supposed as the lowerthreshold at which a control began to be used and the upperthreshold at which a control was sure to be used, separately. As canbe known in Figs. 4 and 5, both threshold temperatures were closeto the corresponding observed values in the survey.

According to the lower thresholds (q5), with the outdoor airtemperature rising, occupants in offices A and B began to use thecontrols with no energy consumption (window, door and curtain)at first, and then fan (low energy consumption) and cooling air-conditioner (high energy consumption) at last. On the otherhand, only when the outdoor air temperature decreased to a lowervalue, occupants began to use hand heater and heating air-conditioner in sequence. The same trend was observed on theorder of the values of q50 and q95 for different controls. Therefore, itseems that occupants in naturally ventilation buildings couldadjust the use of various controls according to different outdoor airtemperatures, when they adapted to the change of climate condi-tions. This was supported by the investigation carried out in someEuropean [15] and Asian countries [20e22]. In addition, thethermal adaptive behaviour pattern might affect building energyconsumption due to the use of different types of controls.

Fig. 9. Occupants’ clothing insulation (Mean) at different outdoor air temperatures. clo means the mean clothing insulation and To the outdoor air temperature. R2 is the deter-mination coefficient.

W. Liu et al. / Building and Environment 50 (2012) 76e8986

As reflected by the thresholds, there were two importantoutdoor air temperature ranges for the use of the controls on indoorenvironment. One was the range within which only window anddoor were used, determined by the difference between lowerthreshold for cooling air-conditioner (or fan) and that for heatingair-conditioner. This temperature rangewas from 15.3 to 24 �Cwitha span of 8.7 �C in office A and from 9.7 to 22.3 �C with a span of12.6 �C in office B. Obviously, within this range the use of windowand door was sufficient to make occupants adapt the climatechangewell. Considering that the use of window and door consumeno energy, extension of the temperature range is significant forbuilding energy conservation.

Another range contains the outdoor air temperatures higherthan the upper thresholds for the use of air-conditioner (coolingand heating). Occupants must switch air-conditioner on to obtainacceptable thermal environment in this range. Clearly, thetemperature range implied high energy consumption. As seen inTable 6, both the lower and upper thresholds of air-conditioner(cooling) in office B were higher than those in office A with

Table 7Statistic result of proportion for transition of control state and the corresponding outdoo

Transition of control state Office A

Temperature range (�C) Tpeak (�C)

Door closed / open 16e30 19, 22, 23open / closed 8e29 16

Window closed / open 2e33 8open / closed 2e32 9

Curtain open / closed 5e30 30closed / open 15e32 15, 19, 20

Hand heater off / on 3e22 3on / off 3e23 10

Air-conditioner (heating) off / on �1e18 4on / off 1e22 7

Air-conditioner (cooling) off / on 25e33 31on / off 17e28 27

Fan off / on e e

on / off e e

Temperature range included the outdoor air temperatures at which the transition of cohighest proportion for the transition of control state.

a difference of about 5 �C. As we know, fan plays an important rolein reducing the heat stress by increasing air movement. Therefore,the use of fan in office B elevated both thresholds of air-conditioner(cooling) usage, in other words, reduced the temperature range foruse of cooling air-conditioner. That means the use of fan in natu-rally ventilated buildings can save energy in hot weather, since fanconsumes much smaller energy than air-conditioner.

It is of interest to compare the values of the characteristictemperatures in this study with those in some existing referenceslisted in Table 8 [8,10,11,20,23]. For the use of door, window andcurtain/blind, compared with the values of this study, the char-acteristic temperature q5 for the surveys in European countrieswas lower, while the characteristic temperature q95 in thosecountries was higher. For the use of fan, the similar trend can beseen. This indicated that in offices of these European countries, theoutdoor air temperature ranges for the use of door, window,curtain/blind and fan were wider and the variation in the usageproportion was slower. As to Asian countries, the difference wasstill clear between the survey in Pakistan [23] and this survey,

r air temperatures.

Office B

Mean S.D. Temperature range (�C) Tpeak (�C) Mean S.D.

, 28 0.12 0.16 8e27 13 0.12 0.090.07 0.07 4e20 8 0.11 0.120.17 0.15 7e27 7 0.15 0.160.09 0.10 8e30 30 0.05 0.070.18 0.11 23e27 23 0.12 0.130.13 0.09 24e30 30 0.22 0.200.08 0.09 3e15 3 0.11 0.120.07 0.11 4e21 4, 7 0.08 0.080.05 0.08 �1e11 1 0.05 0.050.04 0.06 �1e14 7 0.06 0.100.09 0.09 29e5 33 0.13 0.170.09 0.10 23e33 33 0.07 0.08e e 23e32 31 0.26 0.29e e 21e32 31 0.11 0.16

ntrol state occurred. Tpeak means the outdoor air temperature corresponding to the

Fig. 10. Variation of outdoor air temperature (Temperature variation) when the transition of control state occurred in office A. y means the temperature variation and To theoutdoor air temperature. R2 is the determination coefficient.

W. Liu et al. / Building and Environment 50 (2012) 76e89 87

though the values of q5 for window open were almost the same.The distinct climate conditions in these countries should be themain reason to the difference. For people living in differentclimate, the thermal experiences and thermal expectations aredifferent, which might affect their adaptive thermal behaviour.However, the characteristic temperatures for the use of fan, asrevealed by the summer survey in Japan [20], were close to thecorresponding values in this survey, because of the similar climatein summer. Unexpectedly, for air-conditioner (cooling), the char-acteristic temperatures of the survey in Japan were almost thesame with those of office A (without fan), but lower than thevalues of office B (with fan). This may be explained by that thesurvey in Japan was carried out in residences, where occupantsexhibited a higher mean metabolic rate (1.3 met [20]) than that inoffices A and B (1.02 met).

Different from the usage proportion, the usage degree proposedin this study, qualitatively described the trend of regulatinga control with the variation in outdoor air temperature. Accordingto the results of the usage degree shown in Figs. 7 and 8, there wasa clear characteristic for the regulation on each control whenoccupants using it at different outdoor air temperatures, though theusage proportion for some controls had no clear trend with thechange of outdoor air temperature. The use of curtain in office Awas an example. For different controls, the trends of usage degreewere distinct. Additionally, the difference in the usage degreebetween offices A and B also existed for some controls. For example,it is interesting to find that the trend (decreasing) for the usagedegree of curtain in office A was opposite to that (increasing) in

office B, when outdoor air temperature rose. In brief, these char-acteristics can not be revealed just using the usage proportion.Regretfully, up to now few studies investigated the regulation onthe state of controls like the usage degree in this study. Toadequately discover the characteristics of thermal adaptivebehaviour, the usage degree was suggested as an important indexconsidered in studies on thermal adaptation.

The state transition of a control was the third aspect to reflectthe characteristics of thermal adaptive behaviour in this study.Variation of outdoor air temperaturewas supposed as an importantfactor to the occurrence of control state transition. For mostcontrols, the results shown in Figs. 10 and 11 indicated a clearlynegative relation between the variation in outdoor air temperaturewhen the state transition appeared and the outdoor air tempera-ture prior to the state transition. The trend implied that thetemperature variation which causes the control state transitionmay be distinct at different outdoor air temperatures.

As revealed by this study, there were significant differences inthe thermal adaptive behaviour between offices A and B. Thedifferences between different buildings can also be observed insome studies [9,21]. The distinct building structures should bea main reason. Office A was on the third floor of a box building(see Fig. 1(a)), while office B located in a courtyard house (seeFig. 1(b)). In addition, the orientation was different between thetwo offices. These differences can lead to different variation inindoor thermal conditions with climate, which in turn affect theoccupants’ thermal comfort and their thermal adaptive behaviour,according to the principle of thermal adaption [5]. It is necessary

Table 8Characteristic temperatures obtained using logistic regression in previous studies.

Adaptive behaviour b c R2 q5 (�C) q50 (�C) q95 (�C) Season Building Location Reference

Door open 0.026 �0.35 0.01 �99.8 13.5 126.7 Summer Office Lausanne, Switzerland [10]Window open 0.118 �3.73 e 6.7 31.6 56.6 Year-round Residence & office Pakistan [23]

0.169 �2.65 e �1.7 15.7 33.1 Year-round Office UK [23]0.104 �2.31 e �6.1 22.2 50.5 Year-round Office Sweden, UK, France,

Portugal and Greece[23]

0.157 �2.92 e �0.2 18.6 37.4 Year-round Office Oxford and Aberdeen, UK(transverse survey)

[8]

0.181 �2.76 e �1.0 15.2 31.5 Year-round Office Oxford and Aberdeen, UK(longitudinal survey)

[8]

0.7 �19.4 0.80 23.5 27.7 31.9 Summer & autumn Residence Hyogo and Osaka, Japan [20]0.08 �3.13 e 2.3 39.1 75.9 Year-round Office Freiburg, Germany [11]

Blind or curtain drawn 0.139 �3.54 0.14 4.3 25.5 46.7 Summer Office Lausanne, Switzerland [10]Fan switch-on 0.301 �7.09 e 13.8 23.6 33.3 Year-round Residence & office Pakistan [23]

0.22 �5.37 e 11.0 24.4 37.8 Year-round Office UK [23]0.311 �8.18 0.39 16.8 26.3 35.8 Summer Office Lausanne, Switzerland [10]0.69 �19.8 0.83 24.4 28.7 33.0 Summer & autumn Residence Hyogo and Osaka, Japan [20]

Air-conditioner switch-on 0.75 �21.6 0.81 24.9 28.8 32.7 Summer & autumn Residence Hyogo and Osaka, Japan [20]

q5, q50 and q95 were the outdoor air temperatures corresponding to usage proportions of 5%, 50% and 95%, respectively. b is the regression coefficient and c the constant given inthe regression Eq. (3). R2 is the determination coefficient.

Fig. 11. Variation of outdoor air temperature (Temperature variation) when the transition of control state occurred in office B. y means the temperature variation and To the outdoorair temperature. R2 is the determination coefficient.

W. Liu et al. / Building and Environment 50 (2012) 76e8988

to carefully compare these differences between different build-ings when investigating and simulating the thermal adaptivebehaviour.

5. Conclusion

This study analyzed the characteristics of thermal adaptivebehaviour in naturally ventilated offices during a long-term survey,

based on the assumption that the thermal adaptive behaviour isdriven by the change of climate conditions. Following mainconclusions can be obtained.

(1) There was a significant correlation between the use of eachcontrol and outdoor air temperature, indicating the outdoor airtemperature is the most important climate parameter thatcauses the thermal adaptive behaviour.

W. Liu et al. / Building and Environment 50 (2012) 76e89 89

(2) Window, curtain and door were used most frequently. For thecombination usage, the use of window and door possessed thehighest proportion. The buildings should provide enoughoperable windows for occupants.

(3) For window, curtain, fan in office B and door, air-conditioner(cooling) in both offices, the usage proportion increased from0 to 1 with the rising of outdoor air temperature, while theusage proportion of air-conditioner (heating) and hand heaterhad opposite trend.

(4) For each control, the trend of the usage degreewith outdoor airtemperaturewas different. Even for the same control, the trendmay be distinct in offices A and B. The usage degree was sug-gested as an important index considered in studies on thermaladaptation.

(5) The transition events of different controls occurred withindifferent outdoor temperature ranges and the frequenciesusually varied between 0 and 0.4. The outdoor temperaturevariation that causes the control state transition may bedistinct at different outdoor air temperatures.

(6) Compared with office A, the use of fan in office B elevated thelower and upper thresholds of air-conditioner (cooling) usage,which reduced the temperature range for use of cooling air-conditioner in hot weather. Therefore the use of fan shouldbe encouraged in hot weather.

Acknowledgements

The project was financially supported by National NaturalScience Foundation of China (No. 51178466) and the freedomexplore Program of Central South University (No. 2011QNZT094).The authors would like to acknowledge the subjects who vol-unteered for this survey. And also, the authors want to expressthanks to Dr Li Lan for her improvement on language of this paper.

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