Proceedings of Conference: Adapting to Change: New Thinking on Comfort Cumberland
Lodge, Windsor, UK, 9-11 April 2010. London: Network for Comfort and Energy Use in
Buildings, http://nceub.org.uk
Adaptive comfort and thermal expectations – a subjective evaluation in hot
humid climate
E. Rajasekar and A. Ramachandraiah
Building technology and construction management division, Department of Civil Engineering,
IIT Madras, Chennai 600036, India
Abstract:
Subjective and experimental evaluation of thermal comfort characteristics have been carried out
in naturally ventilated apartment buildings located in a hot humid climatic region of India.
Comfort and acceptability limits of environmental parameters under these conditions have been
evaluated on the basis of adaptive comfort theory. The residents are found to accept a wider
range of environmental conditions as being comfortable, compared to the limits suggested by
traditional thermal comfort standards. Factors like age, thermal expectation, economic status and
past experience with thermal comfort play a significant role in determining the comfort
perception. A comparative study of the thermal performance of these buildings with respect to
Fanger’s extended adaptation theory has been carried out. Constraints for adaptation like
outdoor noise levels and their influence on the thermal comfort perception have also been
examined in this study.
Key words: Thermal comfort, Adaptation, hot humid climates, experimental and subjective
evaluation, extended PMV model, noise climate
Introduction:
Multi-storeyed apartment buildings form a major stake of residential buildings in urban
areas of developing countries like India. Prescriptive comfort standards for this building type in
the Indian context have not been regulated. With an increasing number of people affording to
condition their residential spaces the energy demand has risen multifold. Residential buildings
offer a wide range of adaptive opportunities. Occupants in these buildings are found to employ a
wide range of adaptive behaviour for mitigating discomfort. A sustainable development of this
building type would be possible if the comfort requirements of the residents are properly
addressed in the building design and opportunities for adaptive behaviour are accounted for.
Some significant studies on objective evaluation of thermal characteristics include the
work of Givoni [1994], Bouchlaghe [2000], Smith et al [2001], Cheng et al [2004], Kruger and
Givoni [2004], Kontoleon et al [2005], Upadhyay [2006] and Liping et al [2007]. These studies
highlight that the thermal response of buildings are dynamic in nature and thermal discomfort
and related energy consumption can be considerably reduced through proper design. Pioneering
studies by Humphreys [1981] and Nicol [1974, 1995, 1996] have shown that people are not
passive recipients and exhibit physical behavioral adjustments to mitigate discomfort. Hence the
predictions using conventional models are associated with errors which are termed adaptive
errors [Baker, 1996] arising due to adaptive adjustments of occupants. Since adaptive
mechanism is context sensitive, establishing comfort limits based on this adaptive approach is a
key area of research. Some related studies on comfort in naturally ventilated buildings have been
carried out in various tropical countries such as Singapore [de Dear, 1990, Wong et al., 2002],
Malaysia [Zainazlan et al, 2007] and Shanghai [Xiaojiang et al., 2006]. An extensive review of
literature on adaptive thermal comfort has also been presented by Brager & De Dear [1998].
Based on the extensive subjective investigations an Adaptive thermal comfort standards for the
hot–humid tropical climates has been proposed [Nicol, 2004]. Notable studies in the Indian
scenario include those of Sharma and Ali [1986], Anupama et al [2007], Indraganti [2010] and
Manoj et al [2010] in which subjective thermal responses are analyzed for composite and cold
climates have been evaluated.
In this context, the city of Chennai in India (13 o 04’ N; 80 o 17’ E) comes under hot and
humid climate where the climatic conditions are habitual patterns of people are slightly different.
In an investigative attempt to study the adaptive comfort, the subjective and experimental studies
have been carried out for this climatic condition which is discussed further. The work is divided
into subjective and experimental studies followed by results and discussion. According to
Humphreys and Nicol [1998] if the adaptive processes are working satisfactorily, the kind of
temperatures and other thermal parameters in the buildings they are living in should have suited
their requirements. Hence the contents of this work referred above.
Subjective evaluation:
Subjective surveys are administered with 295 occupants residing in 5 different residential
enclaves. Figure (1) shows the key map of Chennai city and the study locations. They are multistoreyed complexes as shown through figures 2 (a) to Fig 2 (e). Other details are provided in
table 1.
Fig. 1: Study locations highlighted in
the key map of Chennai city
Fig. 2(a): A view of JGA
Fig. 2(b): A view of some of the blocks in FSQ
Fig 2(d): A view of XLR
Fig 2(c): A view of LCS
Fig 2(e): A view of FSH
Table 1: Details of the study locations and their notation referred here forth
Notation
Location
Micro-climatic condition
Floor
area
(m2)
No. of
floors
No. of
responses
(Summer
+ Winter)
Sub-urban; gated community
encompassing 460 residences
JGA
90-120
4
53 + 40
spread in 22 apartment blocks
IIT Madras Lush green campus environment
Campus,
spread over 650 acres with
FSQ
45-130
3
65 + 45
Chennai
diverse flora and fauna
Urban; Single apartment block
Velachery
with 80 residential units;
LCS
Chennai
abutted by major traffic lanes
100-130
9
30 + 24
and a bus terminus
Urban; 86 residences spread in 4
Velachery
blocks; abutting traffic lane in
XSR
Chennai
90-120
4
25 + 19
the North
Foreshore
Urban; abutting the sea shore;
Estate,
large group of residential units
FSH
35-60
3
30
Chennai
spread over 25 acres
These enclaves exhibit considerably different micro-climatic conditions in terms of both
ambient thermal and acoustical conditions. Typical outdoor air temperature and outdoor relative
humidity obtained from representative meteorological stations located in proximity to the
Pallavaram
Chennai
locations are shown fig. 3(a) and (b). All the terms such as Ti, Tg, RH etc. referred in this text
are described in appendix 1.
Fig. 3(a): Diurnal variation of OAT
Fig 3(b): Diurnal variation of outdoor RH
With respect to subjective surveys a total of 331 responses are collected in two
phases – during summer (April-May; 203 responses) and winter (November-December; 128
responses) – in the year 2009. The surveys are conducted for 21 days during summer and 11
days during winter and are equally distributed between 07 hours to 21 hours on each day. The
respondents for the subjective surveys are intimated about the survey a week in advance through
the resident associations. They are briefed about the nature and purpose of the study before the
survey is administered.
The subjective surveys are transverse in nature and confirm to class II protocols. The
environmental variables recorded during the surveys are Ti, OAT, RH, Tg and Va (Appendix 1).
Personal variables collected are type of clothing, activity level (met), age and gender of the
respondents, nature of their job and whether they work in air conditioned work places.
Computed clothing insulation value of the ensemble in terms of ‘clo’ ranges from 0.31 to 0.58 (σ
= 0.12) during summer and 0.38 to 0.71 (σ = 0.18) during winter. Activity level in terms of
‘met’ is computed through the data collected regarding the activity that the respondents
performed during the last 30 minutes duration. The met value ranges from 1 to 1.8 which
corresponds to seated relaxed and light physical activity respectively.
The range of Ti, Tg, RH and Va (Appendix 1) recorded during the survey are shown in
Figs. 4 (a), (b), (c) and (d) respectively.
Fig. 4(a): Range of Ti studied
Fig. 4 (b): Range of Tg studied
Fig. 4 (c): Range of RH studied
Fig. 4 (d): Range of Va studied
To recorded during the study ranges from 30oC to 41.5oC during summer and 23oC to
29 C during winter. Ti ranges from 26 oC to 40oC and Tg ranges from 25.5 oC to 40oC. RH
ranges from 28% to 90% and Va ranges from 0.1m/s to 2.2m/s. Ti, Tg and RH are measured
using Extec Heat stress meter (type) and Va is measured using a hot-wire anemometer (Extec).
Fanger’s PMV is measured using Bruel & Kjaer thermal comfort meter (type 1212). The
measurements are made at a height of 1.1m above the floor level. The instruments used are
shown in fig. 5 (a-d).
o
Fig. 5 (a)
Fig.5 (b)
Fig.5 (c)
Fig. 5 (d)
Heat stress meter Hot wire anemometer Thermal comfort meter A survey being administered
Age and gender wise distribution of the subjects are shown in fig. 6(a) and (b) respectively.
Fig. 6: (a) Age distribution of subjects
6(b): Gender distribution of subjects
The questionnaire consists of 27 questions relating to subjective thermal sensation,
comfort, and acceptability, perception of humidity, air movement and ambient noise climate and
satisfaction with the physical environmental parameters. The scales presented to the respondents
and the parameters obtained are listed in table 2.
Table 2: Details of the scales used and parameters obtained
Parameter
Scales used in the subjective evaluation
obtained
Thermal
ASHRAE Scale
sensation Vote
(TSV)
Thermal comfort
Vote
(TCV)
Bedford Scale
Comfort
sensation
(Comf)
General comfort scale
Thermal
acceptability
McIntyre Scale
The respondents are asked to list the primary adaptive strategies from a list of 8 choices
and the constraints for such adaptive measures. A questionnaire template is shown in appendix
2. For ease of understanding for some of the respondents who were comfortable with Tamil –
the regional language in the region, a Tamil version of the questionnaire is used wherever
required.
Experimental studies:
In order to relate the adaptive behaviour with the experimental data thirty representative
residences are chosen from the 5 study locations and detailed long duration experimental
investigation of diurnal spatial variations of Ti, Tg, Va, RH, inside and outside surface
temperatures of the exposed walls, heat flow through envelope surfaces, vertical temperature
stratification (at 0.1m, 0.6m, 1.1m, 1.8m, 2.9m), radiant temperature asymmetry and Fanger’s
PMV is carried out. The instruments used for this purpose are shown in fig. 7(a, b).
Fig 7(a):LSI Lastem Indoor environmental
quality monitoring system
Fig7(b):Thermal comfort meter and thermocouples
connected with HP Bench link data logger
Typical values of indoor Mean radiant temperature (TMRT) obtained are shown in figs. 8 – 10.
Figure 8: Diurnal variation of spatial average TMRT for sold block (density: 1900 kg/m3) and
aerocon block (density: 650 kg/m3) masonry construction
Figure 9: Vertical temperature variation in solid block construction with exposed roof
Figure 10: Vertical temperature variation in solid block construction with unexposed roof
Typical values of Fanger’s PMV and air velocity (natural ventilation) are shown in figs.
11 and 12. On a typical summer day the Fanger’s PMV varies from 2 to >3 which correspond to
“warm” and “hot” thermal sensation of the occupants.
Figure 11: Diurnal variation of PMV in a solid block construction
Figure 12: Diurnal variation of Air velocity in a residential unit
Up to 1 m/s air velocities are obtained through natural ventilation in residences which had
effective cross ventilation. Air velocities of the order of 2 m/s are generated through the use of
ceiling fans. The residences with exposed roof in this study are found to lie within thermally
acceptable temperature limits of 32oC as proposed by Givoni [Givoni, 1992] as well. However
in residences with exposed roofs greater vertical temperature stratification is found.
Results and discussion:
Thermo-neutrality is calculated based on the subjective responses answered on the
ASHRAE thermal sensation scale. It is found from the analysis that thermo-neutrality
corresponds to a globe temperature of 29oC. Fig. 13 shows the variation of the TSV with respect
to Tg.
Fig. 13: Variation of TSV based on Tg
For every 3oC rise in Tg an unit increase in TSV is observed. The comfort band
(corresponding to 0 ± 0.5 TSV) ranges from 27.6oC to 30.5oC and the thermal acceptability
(corresponding to 0 ± 1 TSV) ranges from 26oC to 31.8oC. TSV can be expressed in terms of Tg
through equation (1).
TSV = 0.34 * Tg – 9.72
r2 = 0.58
- Eq. (1)
The correlation of TSV with various momentary indoor (Ta, Tg, WBT, Va and RH) and
outdoor (OAT) environmental factors is analyzed. Table 3 shows TSV expressed in terms of
various indoor/outdoor environmental variables and the correlation coefficients obtained.
Table 3: TSV expressed in terms of various indoor/outdoor environmental factors
Comfort Equation
R2
TSV = 0.33*Tg + 0.04*WBT - 1.47*√Va - 9.37
TSV = 0.34*Tg + 0.004*RH - 1.46*√Va - 9.02
TSV = 0.32*Tg - 1.44*√Va - 8.21
TSV = 0.31*Ta - 1.42*√Va - 8.21
TSV = 0.2*OAT - 1.43*√Va - 4.71
TSV = 0.34*Tg - 9.72
TSV = 0.33*Ta - 9.73
TSV = 0.21*OAT - 6.08
0.700
0.697
0.697
0.691
0.667
0.579
0.577
0.552
It is seen that a comfort equation involving Tg, wet bulb temperature (WBT) and Va has
the highest correlation coefficient (r2 = 0.7). This equation closely corresponds to the tropical
summer index (TSI) proposed by Sharma and Ali [Sharma and Ali, 1986]. TSI is determined
using equation (2) from the environmental parameters measured during the survey.
TSI = 0.308*WBT + 0.745*Tg - 2.06*√Va + 0.841
- Eq. (2)
The fig. 14 (a) shows the relationship between TSV and TSI. TSV correlates well with
TSI (r =0.66). The range of TSV recorded with respect to TSI bins is shown in fig.14 (b).
2
Fig. 14(a):Variation of TSV with respect to TSI
Fig 14(b): TSV range registered against TSI
TSI value corresponding to thermo-neutrality is 28.8oC. This is 0.8oC higher than the
TSI value for thermo-neutrality reported by Sharma and Ali [Sharma and Ali, 1986]. Thermal
acceptability ranges from 26.8oC to 31oC (between -1 and +1 TSV). TSV can be expressed in
terms of TSI through equation (3).
TSV = 0.46 * TSI - 13.41
- Eq. (3)
An increase of air velocity by 1m/s corresponds to unit reduction in TSV. The thermoneutral temperature corresponds well with the values reported by De Dear [De Dear et al, 1990],
Mallic [Mallic, 1996], Feriadi [Feriadi et al, 2003] and Indraganti [Indraganti, 2010]. Based on
this thermal acceptability limit, the residences in which experimental investigation has been
carried out, lie within the acceptability limit during the night while they fall in the “slightly
warm” category during the day. Since air velocities above 2.2 m/s have been reported to cause
discomfort [Tanabe (1994) and Srivajana (2003)], the discomfort in these building need to be
mitigated by means of proper controls.
Based on the findings by Nicol [Nicol et al, 2010], the exponentially weighted running
mean outdoor temperature (Trm) is calculated for the earlier week before the subjective responses
are collected. Fig. 15 shows the relationship between the subjective thermal sensation and Trm.
It can be seen that a robust correlation exists between the Trm and the thermal sensation of the
residents.
Fig. 15: Relationship between TSV and Trm
This indicates that the momentary thermal response of the subjects strongly depends on
their recent thermal history compared to the momentary outdoor temperature conditions.
Analysis of thermal acceptability is carried out using the McIntyre’s 3-point
acceptability. The relationship between the preferred thermal state and the TSI is shown in fig.
16. The preferred temperature obtained through this study is 27oC.
Fig. 16: Preferred temperature based on TSI
The preferred temperature lies closer to the lower limit of the comfort obtained through
the ASHRAE scale. From the analysis of thermal sensation response (TSV) and thermal
preference it is observed that though subjects preferred a temperature of 27oC they acclimatized
themselves for temperatures up to 31.8oC through adaptive behaviour.
The data obtained from the study is further categorized based on seasonal variation, age,
gender, nature of work, whether or not the work place is air conditioned and the thermal
experience during the earlier years. Significant difference is found in the neutral temperature
obtained during summer and winter months. The values are listed in table 4.
Table 4: Neutral temperature during summer and winter in terms of Tg and TSI
Neutral Temperature
Classification Tg (oC)
TSI (oC)
Summer
Winter
26.1
29.5
26.8
29.2
A considerable variation (1.6oC) is found in neutral temperatures recorded by male and
female subjects. Subjects working in air conditioned offices reported a neutral temperature
which is 1.8oC less than that of subjects who either stay at home or work at places that are non
air conditioned. The neutral temperature values obtained in these cases are shown in table 5.
Table 5: Neutral temperature in terms of Tg for various sub-categories of subjects
Neutral Temperature % represented in the
Sub category
(Tg oC)
overall responses
Male
29.7
54.4%
Female
28.1
45.6%
Work place a/c
25.4
42.3%
Work place non a/c
27.2
57.7%
Fanger’s PMV measured during the field study is also compared with the subjective
thermal response. There exists a significant different between the predicted thermal sensation
through Fanger’s model. The results reinforce the argument that the traditional PMV model
predicts a higher level of discomfort than is actually felt by the occupants. Fig. 17 shows the
difference between the PMV and TSV with respect to TSI. A thermo-neutral temperature of
24.9oC is obtained using the PMV model which is 4oC less than the actual thermo-neutrality
obtained through the subjective survey.
Fig. 17: Variation of TSV and PMV with respect to TSI
Using an expectancy factor Fanger’s extended PMV model [Fanger et al, 2002] is
studied. The PMV obtained with such an expectancy factor of “0.7” shows a better correlation
(Fig 18).
Fig. 18: Variation of TSV and extended PMV with respect to TSI
A comparison of the responses registered on ASHRAE scale (ASH_comf), Bedford
comfort scale (Bed_comf) and by the PMV model (PMV_comf) are shown in fig. 19.
Fig. 19: Comparison of responses in various comfort scales
It is found that at temperatures below thermo-neutrality the prediction by Fanger’s model
corresponds well with the thermal comfort votes recorded on Bedford scale. PMV scale predicts
an excessive discomfort at higher temperatures. It is also found that the respondents express a
greater degree of comfort on the Bedford scale in all of the temperature ranges.
Adaptive behavior and constraints for adaptation:
The respondents are asked to rank the common behavioral practices adapted to mitigate
thermal discomfort. A list of six adaptive practices that are determined from the pilot studies are
presented to the subjects. They are also asked to rank the major constraints for their adaptive
practices from a list of 8 common constraints in urban residential spaces. Figure 20 (a) shows
the common adaptive practices in three of the study locations which offer similar adaptive
opportunities to the residents and exhibit differences mainly in the intensity of the constraining
factors. Fig. 20 (b) shows the major constraints for the adaptive behaviour.
Fig. 20 (a): Common Adaptive strategies
Fig. 20(b): Major constraints for adaptation
Ambient micro climatic conditions are found to play a vital role in determining the
adaptive behavior of the subjects in residential environments. For instance, it can be seen that a
higher percentage (13%) of respondents in JGA, which is a gated community, make use of the
balconies during the instance of thermal discomfort and about 5% higher use of windows is
observed. On the other hand respondents at LCS is located in a busy urban locality, report a
minimum use of their balconies and windows. It is noted from fig. 20 (b) that the disturbance
due to noise is highest in LCS. Dust and air pollution are also seen as major constraints by
residents of LCS and XLR. Disturbance due to noise, dust and air pollution are found to be the
major limitations for the adaptive behavior. Preference for usage of ceiling fans (which is a
common practice during summer in hot and humid climates) and air conditioners is found to be
similar in the three cases.
Ambient noise levels around the study locations are listed in table 6.
Table 6: Ambient noise levels measured around the study locations
Ambient noise levels
Notation
(LAeq)
JGA
55 – 65
FSQ
45 – 55
LCS
58 – 70
XSR
56 – 70
FSH
55 – 65
The influence of noise on the adaptive behavior and the thermal response is investigated
by carrying out a comparative study of responses collected from two micro climatic settings.
FSQ which is located inside a residential campus and LCS which is located in a busy urban
setting are considered in this analysis. Noise climate around the building is investigated by
measuring the noise spectrum at 8 cardinal directions around the buildings concerned, with a
sampling period of 15 minutes, during peak and non-peak hours. Variation of noise levels at
different floor levels is also studied. These studies are carried out using 01 dB Solo integrating
precision sound level meter. Day time noise levels (LD: 6:00 AM to 6:00 PM) and night time
levels (LN: 6:00 PM to 6:00 AM) are monitored at representative residential units in various
floors. Some of the ambient noise data obtained around the study locations are shown in fig 21
(a-c). Fig. 21 (d) shows the comparison of noise spectrum between LCS and FSQ.
Fig. 21(a): LAeq around the LCS Fig21(b): LAeq around the LCS Fig21(c): LAeq around a block
Ground level
8th floor level
in FSQ (Ground level)
Fig. 21(d): Comparison of noise spectrum
Fig21(e): 01 dB Solo Sound Level Meter
A comparison of heat discomfort reported in these two locations on the Bedford scale is
shown in fig. 22 (a). The analysis is done by categorizing the TSI into 1oC bins and the
responses >+1 are accounted as discomfort due to heat. It is found that a higher percentage of
respondents belonging to LCS voted to be under discomfort for the same TSI values compared to
the respondents in FSQ. This is true for all the cases above thermal neutrality (28.8oC).
Fig. 22 (a): Reported heat discomfort
Fig. 22 (b): Reported TSV
On the other hand it is found from figure 22 (b) that there is a minor difference in the
percentage of respondents reporting the thermal sensation to be warmer or more on the ASHRAE
scale. This could be due to the fact that noise climate forms a major constraint for employing
adaptive strategies like use of balconies, opening the window for increased ventilation, etc. due
to which a higher discomfort is reported in spite of similar thermal sensation votes being
reported. Further studies are in progress with respect to tolerance towards ambient noise
conditions.
Conclusion:
Based on the subjective studies it is found that occupants in naturally ventilated
residential spaces belonging to hot humid climates show acceptability to a wider range of
environmental conditions than specified by ASHRAE and ISO standards. The adaptive approach
in this study indicates the acceptable temperatures range from 31oC to 26.8oC respectively and a
thermo-neutral temperature of 28.8oC in terms of TSI. In terms of Tg this corresponds to upper
and lower limit value of 31.8oC and 26oC and thermo-neutral temperature of 29oC. The study
shows that people prefer to stay in a temperature lower than thermal neutrality. This is indicated
by a preferred temperature of 27oC which is 1.8oC less than the thermo neutral temperature
(fig.16). From the analysis of thermal sensation vote (TSV) and thermal preference it is
observed that though subjects preferred a temperature of 27oC they acclimatized themselves for
temperatures up to 31.8oC through adaptive behaviour. The thermal response of the subjects is
determined by their thermal experience of the earlier week, which is evident from a strong
correlation between the exponential running mean outdoor temperature and the subjective
response. It is found that the neutral temperature recorded during summer is 3.4oC less than that
of the winter neutral temperature (table 4). Gender and nature of the work environment are also
found to have a significant influence on the neutral temperature of the respondents. Investigation
of adaptive behavior indicates that the ambient environmental constraints like noise and air
pollution form a major constraint for adaptation in the urban environments. Analysis shows that
for similar thermal conditions, residents living in localities with higher noise levels experience a
higher degree of discomfort compared to people living in quieter areas.
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Acknowledgements:
We thankfully acknowledge Jain Housing Pvt. Ltd. and The Engineering Unit, IIT Madras for
providing us the permission to conduct the experimental studies and the residents who extended
their cooperation during the experimental studies and subjective surveys.
Appendix 1: Nomenclature
Ti
: Indoor dry bulb temperature (oC)
WBT : Wet bulb temperature (oC)
Tg
: Indoor black globe temperature (oC)
TMRT : Indoor mean radiant temperature (oC)
Trm
: Running mean outdoor temperature (oC)
OAT : Outdoor air temperature (oC)
Tn
: Neutral temperature (oC)
TSI
: Tropical summer index (oC)
RH
: Relative humidity (%)
Va
: Air velocity (m/s)
PMV : Fanger’s predicted mean vote
TSV
: Thermal sensation Vote (ASHRAE)
TCV : Thermal comfort Vote (Bedford)
LAeq
: Equivalent sound pressure (dB A)
Appendix 2: Questionnaire used for subjective evaluation of thermal comfort