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doi:10.1016/j.bu

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Building and Environment 42 (2007) 3965–3973

www.elsevier.com/locate/buildenv

People’s clothing behaviour according to external weatherand indoor environment

Michele De Carlia,�, Bjarne W. Olesenb, Angelo Zarrellaa, Roberto Zecchina

aDFT—Dipartimento di Fisica Tecnica, Universita degli Studi di Padova, Via Venezia 1, 35131 Padova, ItalybDTU—Department of Mechanical Engineering, Technical University of Denmark, Nils Koppels Alle, 2800 Kgs. Lyngby, Denmark

Received 30 January 2006; accepted 29 June 2006

Abstract

In prehistoric times man wore furs of animals to protect himself from the cold. Successively over the centuries clothing has become

also a tool to distinguish ourselves in society. Clothing has in addition an important impact on people’s perception of the indoor

environment.

Clothing behaviour has been analysed by investigating the external and indoor parameters that motivate people’s choice of clothing.

Based on two existing databases, two types of buildings have been investigated: air-conditioned and naturally ventilated (NV) buildings.

The impact of outdoor temperature on people’s clothing selection has been considered. The outdoor temperature at 6 a.m. seems to affect

people’s choice of clothes the most. Gender does not significantly affect the selection of clothing insulation.

Latitude has also been investigated and a good correlation has been found between clothing insulation and external temperature in the

ranges 201–401 and �201 to �401 for NV buildings.

Indoor air temperature does not seem to influence the clothing choice early in the morning but it does seem to influence the change

of clothing during the day, if this is authorized, in workplaces in NV buildings. Such action can be termed ‘‘clothing adjustment’’ during

the day.

Some computer simulations on a test reference year have been carried out for a typical air-conditioned office to analyse a person’s

comfort when wearing different clothes. It is possible to see that in air-conditioned buildings a variation of 0.1 clo is sufficient to change

totally the comfort evaluation. It is evident that further studies are needed in this field.

r 2006 Elsevier Ltd. All rights reserved.

Keywords: Clothing; Clothing adjustment; Thermal comfort; Gender; Occupant behaviour

1. Introduction

For predicting or evaluating the indoor thermal envir-onment, clothing is an important factor. In most casesclothing is selected individually by the occupants. In somecases, however, the type of clothing is prescribed by theworkplace (e.g., clean room, uniforms and dress codes).Very little information is available, however, on the criteriapeople use for selecting their clothing. The outdoortemperature will probably have some influence, but ifdriving from home to work and remaining inside a vehicle,the outdoor temperature may have little influence. The

e front matter r 2006 Elsevier Ltd. All rights reserved.

ildenv.2006.06.038

ing author. Tel.: +3949 827 6882; fax: +39 49 827 6896.

ess: michele.decarli@unipd.it (M. De Carli).

indoor temperature at the workplace may also be a factor.If it is known that the space is conditioned and operatedat an almost constant temperature all the year round,clothing will probably be adapted accordingly. If, onthe other hand, the building is not conditioned and it hasbeen experienced that the space becomes warm withincreasing outdoor temperatures, lighter clothing will bechosen to compensate for the increased indoor tempera-tures. The indoor air temperature may affect also theclothing adjustment, i.e. the attitude of people tochange their clothes in a workplace if this is authorized,as well as the clothing selection of persons early in themorning. There may also be gender and social differencesboth in the selection and in the clothing adjustment inworkplaces.

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60°

40°

20°

0°

20° 20°

20°

40°

60° 60°

60°

80°160° 120° 80° 40°

0°

0° 40°

40°

40°

80°

80°

80°80°

120° 160°

180° 180°140° 140°100° 100°60° 60°20° 20°

Fig. 1. Location of the measuring sites for databases A and B.

M. De Carli et al. / Building and Environment 42 (2007) 3965–39733966

In existing standards and guidelines clothing is specifiedonly for design conditions. In most cases a recommendedtemperature interval for cooling conditions is based onlight summer clothing of 0.5 clo, while design heatingconditions are based on a clothing insulation of 1.0 clo[2,3]. As whole-year dynamic computer simulations ofbuildings and the indoor environment become more andmore common, there is a need to have some standardizedmethod for simulating people’s clothing habits and how itchanges with season. One possibility is to use a constantclo-value according to season, but it would be morerealistic to assume some change of clothing insulationthroughout the year.

To compensate for individual differences in the preferredambient temperature, clothing is a powerful factor, but thispresupposes that people choose a clothing ensemble whereit is possible to change some parts (jacket, sweater etc.). Itis also interesting to analyse the way people change theirclothing during the day (clothing adjustment), e.g., bytaking on/off a jacket or sweater and how much thisinfluences the energy need of buildings.

The present work is based on existing databases andanalyses people clothing behaviour by investigating theexternal parameters (outside temperature, mean weeklyoutside temperature, latitude) and the indoor parameters(space temperature) that motivate people’s choices. Thedata will also be analysed for differences between gender.Clothing adjustment in the workplace will also be analysed.Some computer simulations on a test reference year (TRY)will be presented in order to understand the importance ofclothing in long-term comfort evaluation.

2. Methods

The analysis of clothing data was based on previous fieldinvestigations with databases that could be accessed orprovided by the authors. Two databases have beenanalysed: data from 28 cities all over the world, calledgroup A [1,4,5], and data from Singapore and Indonesia[6], called group B. In the works presented by the authorsof these publications no specific analysis has been carriedout for investigating the variability of clothing as afunction of the external temperature.

Locations for group A are reported in Fig. 1. Data fromthree types of office buildings were investigated: air-conditioned systems (HVAC), naturally ventilated (NV)and mixed systems (MIX). Data of group B (Fig. 1) refer toNV residential buildings. In the databases, the authorsevaluated clothing resistance (clo-value) by observingpeople. The average clo-value for the occupants at thetime of measurement is available. This means that nospecific information concerning the clo-value for eachperson is given in the database, and the standard deviationbetween persons is not listed. The number of peopleobserved may vary during the day. The way in which theminimum and maximum average clo-values vary will beinvestigated. This may be useful when simulating a

building based on a TRY in order to allow for a certainrange in indoor temperature conditions.For database B the outdoor temperature was not

available, but, as suggested by the authors, the indoortemperature may be considered equal to the externaltemperature because of the very high rate of infiltrationdue to natural ventilation.In the analysis shown in this work for each day and for

each group of subjects in the single building of databases,average, minimum and maximum clothing resistances havebeen investigated in order to obtain the daily mean,minimum and maximum clothing resistances. In thisoperation, in group A an admissible minimum clothingresistance of 0.4 clo (for ethical aspects) and an admissiblemaximum value of 1.6 clo have been included; for group Bno restrictions on clothing resistances have been made.These values have been analysed as a function of somevariables as can be seen in the next paragraph.Male and female distinction has been made for group A,

while for group B no such distinction has been considered.For group A the small number of subjects for mixed-modebuildings was not sufficient to reach any significant result.The basic question is why people choose a certain

clothing. Some authors say that it is due to the expectedindoor environment in buildings [7]. Others suggest thatthe clothing may be a function also of the external weather[8,9,15]. At an intuitive level both parameters would beimportant.In this work, various external temperatures have been

considered:

(a)

temperature at 6 a.m., thus simulating that people basetheir clothing insulation on the external temperaturewhen they go out in the morning [10];

(b)

mean daily temperature (average between minimumand maximum), thus taking into account the meanweather conditions during a day;

(c)

mean temperature during the period investigated, thussimulating the variability of clothing according toexternal mean monthly temperature;

(d)

weighted value on the temperature over the last 4 days,thus taking into account an adaptation of the persons

ARTICLE IN PRESSC

LO

Fig.

outd

Clo mean female Clo mean male

M. De Carli et al. / Building and Environment 42 (2007) 3965–3973 3967

to the external climate [9]:

clomean male = -0.019x + 0.95

R2 = 0.39 p<0.01

clomean female = -0.02x + 1

R2 = 0.25 p<0.01

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Outdoor Temperature 6 a.m. [°C]

CL

O

Fig. 3. Daily mean clothing resistance for males and females in relation to

outdoor temperature at 6 a.m. in NV buildings.

clomax = -0.009x + 0.863

R2 = 0.18 p<0.011.6

1.8

2.0Clo min Clo max Linear (Clo mean)

T e;ref ¼ð1Tout; today þ 0:8Tout; yesterday þ 0:4Tout; 2 d ago þ 0:2Tout; 3 d agoÞ

ð1þ 0:8þ 0:4þ 0:2Þ,

(1)

where Tout is the mean daily temperature (average betweenminimum and maximum).

Some main latitude zones have been specially selectedtaking into account the climate zones, and in each zone thepossible relation between clothing resistance and outdoortemperature has been investigated.

Successively, the probable link between clothingresistance and indoor climate has been investigated; atfirst the influence of indoor air temperature has beenanalysed and then the clothing adjustment at theworkplace has been investigated in order to show theextent to which people change their clothing duringthe day.

Finally, with the obtained results a case study has beencarried out.

clomin = -0.008x + 0.684

R2 = 0.23 p<0.01

clomean = -0.01x + 0.766

R2 = 0.3 p<0.010.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Outdoor Temperature 6 a.m. [°C]

CL

O

Fig. 4. HVAC clo-value vs. temperature at 6 a.m.

1.2

1.4

1.6

1.8

2.0

O

Clo min Clo max Linear (Clo mean)

clomax = -0.024x+ 1.1

R2 = 0.3 p<0.01

3. Results

3.1. Influence of gender

The influence of gender in HVAC buildings of groupA can be seen in Fig. 2; the difference between males andfemales is very limited and is therefore considerednegligible. Also for NV buildings in group A the differencebetween genders can be disregarded (Fig. 3), although inthis group of data there is a slight difference between menand women when considering the minimum values ofclothing resistance during a day; this is mainly due tocultural aspects, since majority of the data is derived fromPakistan.

As previously mentioned, no gender evaluation has beencarried out for Group B.

clomean female = -0.009x + 0.743

R2 = 0.26 p<0.01

clomean male = -0.01x + 0.791

R2 = 0.35 p<0.01

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Outdoor Temperature 6 a.m. [°C]

Clo mean female Clo mean male

2. Daily mean clothing resistance for males and females in relation to

oor temperature at 6 a.m. in HVAC buildings.

0.0

0.2

0.4

0.6

0.8

1.0

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Outdoor Temperature 6a.m. [°C]

CL

clomean = -0.02x + 0.98

R2 = 0.31 p<0.01

clomin = -0.015x + 0.83

R2 = 0.22p<0.01

Fig. 5. NV clo-value vs. temperature at 6 a.m.

3.2. External temperature

Variation of clo-values in relationship to outside airtemperature (6 a.m., mean daily, average in the periodconsidered, and weighted weekly value) has been investi-gated only for group A where no distinction between malesand females has been considered. In Figs. 4 and 5 the

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clomin = -0.007x + 0.690

R2 = 0.23 p<0.01

clomax =-0.01x + 0.893

R2 = 0.23 p<0.01

clomean = -0.009x + 0.785

R2 = 0.33 p<0.010.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Mean Monthly OutdoorTemperature [°C]

CL

O

Clo min Clo max Linear (Clo mean)

Fig. 8. HVAC clo-value vs. mean monthly temperature.

clomax = -0.015x+ 0.917

R2 = 0.12 p<0.01

clomean = -0.016x+ 0.883

R2 = 0.17 p<0.01

1.2

1.4

1.6

1.8

2.0O

Clo min Clo max Linear (Clo mean)

M. De Carli et al. / Building and Environment 42 (2007) 3965–39733968

relationship between resistance of clothing and minimumoutside temperature (outdoor temperature at 6 a.m.) forHVAC and NV buildings, respectively, can be seen. InFigs. 6 and 7 the same results refer to outside mean dailytemperature, and in Figs. 8 and 9 to the mean monthlytemperature.

The correlations are low. For HVAC buildings theR2-value does not depend on the type of outsidetemperature used (6 a.m., mean daily or mean monthly).For NV buildings the highest correlation is obtained usingthe outdoor temperature at 6 a.m.

As for weighted temperature, no correlation has beenshown since very few data are available and it has not beenpossible to make a direct correlation. However, acomparison has been made by calculating the theoreticalclothing resistance when considering the correlationexpressed in Figs. 4 and 5 (i.e., temperature at 6 a.m. asreference) and when using the weighted temperaturecorrelation [9]. The comparison has been made by takingas reference the real data of clothing from the database.Results of this comparison can be seen in Figs. 10 and 11.As can be observed, there is no difference when consideringHVAC buildings. On the other hand, in NV buildings thetemperature at 6 a.m. determines in a better way the real

clomin = -0.008x + 0.705

R2 = 0.23 p<0.01

clomax = -0.009x + 0.888

R2 = 0.19p<0.01

R2 = 0.31 p<0.010.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

-35 -30 -25 -20 -15 -10 0 5 10 15 20 25 30 35

Mean Daily Outdoor Temperature [°C]

CL

O

Clo min Clo max Linear (Clo mean)

-5

clomean = -0.009x + 0.791

Fig. 6. HVAC clo-value vs. mean daily temperature.

clomin = -0.014x + 0.852

R2 = 0.16p<0.01

clomax = -0.021x + 1.115

R2 = 0.19 p<0.01

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Mean Daily Outdoor Temperature [°C]

CL

O

Clo min Clo max Linear (Clo mean)

clomean = -0.018x+ 1.0

R2 = 0.2 p<0.01

Fig. 7. NV clo-value vs. mean daily temperature.

clomean = -0.014x+ 0.816

R2 = 0.16 p<0.01

0.0

0.2

0.4

0.6

0.8

1.0

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Mean Monthly Outdoor Temperature [°C]

CL

Fig. 9. NV clo-value vs. mean monthly temperature.

clomean Teref = 0.260x + 0.459

R2 = 0.26

clomean T6am = 0.288x + 0.442

R2 = 0.29

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

CLO real

CL

O c

alc

ula

ted

Clo mean Te ref Clo mean T6am

Fig. 10. HVAC: calculated vs. real mean clothing resistance.

ARTICLE IN PRESSM. De Carli et al. / Building and Environment 42 (2007) 3965–3973 3969

clothing resistance than does weighted temperature. Thismeans that temperatures of the previous days weigh less onthe resistance of clothing, at least for persons in this type ofbuilding.

3.3. Latitude

The influence of latitude on clothing has been analysedto examine also social and cultural factors. The zonesconsidered and the related results are reported in Table 1,

clomean Te ref= 0.385x + 0.416

R2 = 0.38

clomean T6am= 0.496x + 0.340

R2 = 0.49

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

CLO real

CL

O c

alc

ula

ted

Clo mean Te ref Clo mean T6am

Fig. 11. NV: calculated vs. real mean clothing resistance.

Table 1

Correlation taking into account latitude

Latitude zones Maximum clothing

Equation

HVAC �0.005T6 a.m.+0.894

401–501 F ¼ 39.03; dF ¼ 1, 1070;

�401 to �501 p-valueo0.01

�0.007T6 a.m.+0.788

F ¼ 43.28; dF ¼ 1, 815;

201–401 p-valueo0.01

�201 to �401 �0.016T6 a.m.+1.008

F ¼ 96.68; dF ¼ 1, 600;

�201 to �201 p-valueo0.01

NV �0.013T6 a.m.+0.81

401–501 F ¼ 14.84; dF ¼ 1, 616;

�401 to �501 p-value ¼ 0.00013

�0.039T6 a.m.+1.428

201–401 F ¼ 1038; dF ¼ 1, 771

�201 to �401 p-valueo0.01

0.008T6 a.m.+0.35

�201 to 201 F ¼ 0.23; dF ¼ 1, 64;

p-value ¼ 0.6357 (no significance)

where the temperature at 6 a.m. has been considered. It canbe observed that correlations for HVAC buildings are low:between �201 and 201 latitudes for minimum clothingit can be seen that there is no statistical significance. ForNV buildings in latitudes between 201 and 401, and �201and �401, where this type of system is more frequent,correlations are sufficiently high; moreover, between �201and 201 latitudes, the amount of data is small and thecorrelations have no statistical significance.

3.4. Clothing behaviour and indoor environment

In Figs. 12 and 13 the indoor air temperature, when themaximum clo-value has been recorded, is plotted againstoutdoor temperature at 6 a.m. It can be observed that inHVAC buildings indoor air temperature does not influenceclothing resistance; in NV buildings, on the other hand,indoor air temperature depends on outdoor temperature(R2¼ 0.72). This means that if indoor air temperature is

also considered, the correlation does not increase consis-tently, therefore in NV buildings indoor air temperaturedoes not seem to influence particularly the clothing choice.It is intuitive that adaptation of clothing in a workplace,

during a day, if this is authorized, depends on the indoorclimate of a building as well. This action can be termed‘‘clothing adjustment’’. With a daily maximum average clo-value and an hourly average clo-value, the clothingadjustment has been investigated: it is the daily maximumaverage clo-value minus the hourly average clo-value.In buildings of group A, the hourly average clothinginsulation was estimated by means of a questionnaire atintervals during a day [4]. In Figs. 14 and 15 the clothingadjustment of males and females in NV buildings is plotted

Minimum clothing

R2 Equation R2

0.04 �0.006T6 a.m.+0.684 0.08

F ¼ 93.34; dF ¼ 1, 1070;

p-valueo0.01

0.05 �0.012T6 a.m.+0.722 0.181

F ¼ 179.5; dF ¼ 1, 815;

p-valueo0.01

0.138 0.001T6 a.m.+0.44 0.003

F ¼ 1.91; dF ¼ 1, 600;

p-value ¼ 0.1683 (no significance)

0.02 �0.009T6 a.m.+0.704 0.02

F ¼ 9.971; dF ¼ 1, 616;

p-value ¼ 0.00168

0.574 �0.02T6 a.m.+0.935 0.328

F ¼ 376.7; dF ¼ 1, 771;

p-valueo0.01

0.003 �0.025T6 a.m.+1.041 0.082

F ¼ 5.725; dF ¼ 1, 64;

p-value ¼ 0.0197

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y = 0.032x + 22.727

R2 = 0.07 p<0.01

0

5

10

15

20

25

30

35

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Outdoor Temperature 6 a.m. [°C]

Ind

oo

r A

ir T

em

pera

ture

[°C

]

Fig. 12. HVAC: indoor air temperature vs. outdoor temperature at 6 a.m.

y = 0.626x + 14.645

R2 = 0.72 p<0.01

0

5

10

15

20

25

30

35

-35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35

Outdoor Temperature 6 a.m. [°C]

Ind

oo

r A

ir T

em

pera

ture

[°C

]

Fig. 13. NV: indoor air temperature vs. outdoor temperature at 6 a.m.

clothing adjustment = -0.024x + 0.804

R2 = 0.38 p<0.01

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 5 10 15 20 25 30 35

Indoor Air Temperature [°C]

CL

O

Males

Fig. 14. NV: clothing adjustment of males vs. indoor air temperature.

clothing adjustment = -0.005x +0.323

R2 = 0.02 p<0.01

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 5 10 15 20 25 30 35

Indoor Air Temperature [°C]

CL

O

Females

Fig. 15. NV: clothing adjustment of females vs. indoor air temperature.

M. De Carli et al. / Building and Environment 42 (2007) 3965–39733970

against indoor air temperature; it can be seen that thisparameter in NV buildings depends on gender.

For females the clothing adjustment is not related toindoor air temperature and it has an almost constant value.It is necessary to consider that a greater quantity of datafor these buildings comes from Pakistan with culturalfactors exerting an overriding constraint on the clothingcustoms of women.

In HVAC buildings there is a clothing adjustment but itis not related to indoor air temperature for either males orfemales, and therefore no diagram is presented for thistype of building: the clothing adjustment seems to be apsychological effect.

4. TRY simulations: A case study

In order to analyse the comfort of persons with differentclothing throughout the year a typical office has beensimulated. The office is located in Venice (latitude 451North) and it has been modelled as one zone (Fig. 16).South and North fac-ades and a portion of the West sideare glazed with a U-value of 1.5W/(m2K); shadingcoefficients are 0.15 for South, 0.3 for North and 0.2for West fac-ades. Vertical external opaque walls have aU-value of 0.41W/(m2K); the floor and ceiling are internalwalls with a U-value of 0.34W/(m2K).A convective system provides heating and cooling. In

summer and winter the supply air (40m3/h/person) will beconditioned as regards supply temperature and humidityventilation. In mid-season (part of April and May in thespring and part of September and October in the autumn)the supply air will be non-conditioned outside air (outdoortemperature and humidity).Five persons are daily present in the workplace for 10 h

(8 a.m.�6 p.m.) from Monday to Friday. An internal gainof 15W/m2 has been considered.For TRY simulations the model DIGITHON [11,12] has

been used; it is based on the resolution of thermal balanceequations in the room and on transfer functions for solvingthe problem of thermal conductivity through walls.In order to evaluate comfort conditions in the office,

indexes predicted vote mean (PMV) and predicted percen-tage of dissatisfied (PPD) [13] have been considered since itis a HVAC building. As for long-term comfort conditions,comfort deviation has been quantified by the parameter wf

(weighting factor) [14] defined as

wf ¼PPD

PPDL, (2)

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0

10

20

30

40

50

60

70

80

90

100

Janu

ary

Febru

ary

Mar

chApr

il

May

June

July

Aug

ust

Sep

tem

ber

Octob

er

Nov

embe

r

Dec

embe

r

Annual WTcool = 51

Fig. 17. Evaluation of WTcool using daily maximum clothing.

80

90

100

M. De Carli et al. / Building and Environment 42 (2007) 3965–3973 3971

where PPD is calculated in the hour under consideration,while PPDL is the reference limit for comfort (here 10%has been considered).

The sum of the weighting factors throughout theinvestigated period allows for calculation of the parameterweighted time (WT), defined as

WTwarm ¼Xn

1

wf Dt whenPMV4PMVL, (3)

WTcool ¼Xn

1

wf Dt whenPMVoPMVL, (4)

where n is the step number of simulation in which thepersons are present and Dt is the time step of simulation(hourly in this work). Some authors assert that anappropriate value of comfort conditions may be100–150 h/yr out of the comfort zone. In existing standardsthere is still no limit value for this parameter but it isnecessary to consider the procedure to understand where togo for the optimization of comfort conditions withoutincreasing the energy need of buildings too much.

Maximum, mean and minimum clothing resistances havebeen taken into account using the equations shown aboveas a function of outdoor temperature at 6 a.m. in HVACbuildings (Fig. 4).

In Table 2 a summary of the indoor conditions withdifferent clothing insulations is reported.

In Figs. 17–19, the WTcool value with different clothingvalues is plotted throughout the year. Similarly inFigs. 20–22, the WTwarm value is reported. The upper limitof the scale of the ordinate is 100: if the monthly value isgreater than 100 it is marked on the relevant column.

Table 2

Yearly indoor conditions

Yearly working hours: 2610 h Daily maximum clothing

Number of cool hours (h) 42

Number of warm hours (h) 771

Number of comfort hours (h) 1797

Fig. 16. Case study (dimension in metres).

The difference between maximum and mean clothing isabout 0.1 clo which is also the difference between mean andminimum clothing. It is interesting to see, in both warmand cool periods, that a variation of 0.1 clo is sufficient tobring about a remarkable change in comfort evaluation.This analysis shows that considering the daily mean

value of clothing is not totally correct. The appropriatevalue of clothing is between maximum and minimumvalues and it varies during the year.

Daily mean clothing Daily minimum clothing

245 579

340 267

2025 1764

10

2

10

1

0

10

20

30

40

50

60

70

Janu

ary

Febru

ary

Mar

chApr

il

May

June

July

Aug

ust

Sep

tem

ber

Octob

er

Nov

embe

r

Dec

embe

r

Annual WTcool = 316

Fig. 18. Evaluation of WTcool using daily mean clothing.

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23

7

17

3

10

1

23

9

0

10

20

30

40

50

60

70

80

90

100

Janu

ary

Febru

ary

Mar

chApr

il

May

June Ju

ly

Aug

ust

Sep

tem

ber

Octob

er

Nov

embe

r

Dec

embe

r

Annual WTcool = 840

Fig. 19. Evaluation of WTcool using daily minimum clothing.

13

7

18

4

12

9

50

7

0

10

20

30

40

50

60

70

80

90

100

Janu

ary

Febru

ary

Mar

chApr

il

May

June

July

Aug

ust

Sep

tem

ber

Octob

er

Nov

embe

r

Dec

embe

r

Annual WTwarm = 1303

Fig. 20. Evaluation of WTwarm using daily maximum clothing.

443

0

10

20

30

40

50

60

70

80

90

100

Janu

ary

Febru

ary

Mar

chApr

il

May

June Ju

ly

Aug

ust

Sep

tem

ber

Octob

er

Nov

embe

r

Dec

embe

r

Annual WTwarm = 725

Fig. 21. Evaluation of WTwarm using daily mean clothing.

397

0

10

20

30

40

50

60

70

80

90

100

Janu

ary

Febru

ary

Mar

chApr

il

May

June

July

Aug

ust

Sep

tem

ber

Octob

er

Nov

embe

r

Dec

embe

r

Annual WTwarm = 599

Fig. 22. Evaluation of WTwarm using daily minimum clothing.

M. De Carli et al. / Building and Environment 42 (2007) 3965–39733972

5. Discussion and conclusions

In the present work, the clothing behaviour has beeninvestigated by considering two existing databases.A possible correlation between external air temperatureand clo-value has been found. There is a change in the clo-value during the day (difference maximum-minimum, seeFigs. 4 and 5), in both HVAC and NV buildings. ForHVAC buildings the difference is around 0.2 clo and it isnot dependent on outside temperature. This corresponds tothe insulation of a jacket or sweater. For NV buildings thedifference between maximum and minimum varies between0.2 and 0 clo, as it becomes lower at higher outsidetemperatures (Fig. 5). This means that in HVAC buildingsan average clothing insulation between 0.5 and 1.0 clo, witha variation of+0.1 clo, can be assumed.As regards the influence of external temperature, the

investigation on gender has not shown significant differ-ences between males and females in the choice of clothing;therefore it seems that a unique value for the clo-value canbe considered for a building.For HVAC buildings it seems that there is no appreci-

able difference when considering the minimum dailytemperature, the mean daily temperature, the meanmonthly temperature or the weighted temperature; forNV buildings, the use of the minimum daily temperaturegives better correlations. From this study it seems to comeout that ‘‘weather memory’’ [15] is not so profound to havean effect on clothing behaviour. Probably people are moresensible to minimum or maximum external temperature.Maybe this effect is reduced when mean (both daily andmonthly) outdoor temperature is taken into account.When considering latitude there is no influence regarding

HVAC buildings but a good correlation is found in theranges 201–401 and �201 to �401 for NV buildings.In the present work the correlation has been carried out

considering only the external temperature. It does not seemlikely that by including also indoor temperature the results

ARTICLE IN PRESSM. De Carli et al. / Building and Environment 42 (2007) 3965–3973 3973

would be better, since the outdoor temperature influencesthe indoor temperature in NV buildings and does not affectit very much in HVAC systems, according to previousstudies [15].

As regards clothing adjustment in NV buildings,research has shown differences between males and females.On the other hand, in HVAC buildings, the clothingadjustment seems to be a psychological result.

To evaluate indoor comfort based on whole-yeardynamic simulations of buildings and clothing, theassumed clo-value is a very important parameter. TRYcomputer simulations for a HVAC building have shownthat a variation of 0.1 clo is sufficient to change totally thecomfort evaluations.

Further studies are needed to consider the clothing ofpersons in NV buildings. It will be interesting to see theinfluence of clothing adjustment on the energy need ofbuildings. Further research is needed to establish a limitvalue for WT for long-term period comfort evaluations andother studies are needed to consider the clothing itemsselected individually. It is essential to come to some kind ofagreement on ‘‘standard’’ clothing behaviour when analys-ing comfort and energy use.

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