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Precision and thermal comfort
Fergus Nicol
London Metropolitan University and Oxford Brookes University
Thermal comfort standards
Type of Clothing Activity Category Operative Temperature Mean Air Velocity
Building/ Cooling Heating Cooling Heating Cooling Heating
Space Season Season season Season season season
(summer) (winter) (summer) (winter) (summer) (winter)
Clo Clo met °C °C ms-1 ms-1
Office 0.5 1.0 1.2 A 24.5 ± 0.5 22.0 ± 1.0 0.18 0.15
B 24.5 ± 1.5 22.0 ± 2.0 0.22 0.18
C 24.5 ± 2.5 22.0 ± 3.0 0.25 0.21
Cafeteria/ 0.5 1.0 1.4 A 23.5 ± 1.0 20.0 ± 1.0 0.16 0.13
Restaurant B 23.5 ± 2.0 20.0 ± 2.5 0.20 0.16
C 23.5 ± 2.5 20.0 ± 3.5 0.24 0.19
Department 0.5 1.0 1.6 A 23.0 ± 1.0 19.0 ± 1.5 0.16 0.13
Store B 23.0 ± 2.0 19.0 ± 3.0 0.20 0.15
C 23.0 ± 3.0 19.0 ± 4.0 0.23 0.18
From Olesen and Parsons, Energy and Buildings 34(6)
Summer in Saidu Sharif, Pakistan (photo M Humpheys)
Winter in Saidu Sharif, Pakistan (photo M Humpheys)
Changing ourselves
• As the temperature changes so the level of clothing, the air movement (which can cool the body by convection and/or evaporation of sweat) and the moisture of the skin will change.
• It is also probable that people are less active in the heat, but because metabolic rate is measured by ‘activity’ this is not clear
Data from Pakistan
Personal variables
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
10 15 20 25 30 35 40
Indoor temperature
Clothing insulationAir velocityMetabolic rateSkin moisture
The result of these actions is shown in this graph of the level of discomfort at different indoor
temperatures among office workers in Pakistan
00.10.20.30.40.50.60.70.80.9
1
12 14 16 18 20 22 24 26 28 30 32 34 36 38
Mean indoor temperature oC
Pro
port
ion
of s
ubje
cts
com
fort
able
Little discomfort
Nicol, Raja, Allauddin & Jamy (1999) Energy and Buildings 30(3)
Use of fans as a function of outdoor temperature in Pakistan
0%
20%
40%
60%
80%
100%
5 10 15 20 25 30 35 40
Mean outdoor temperature
% r
unn
ing
Fans are available in almost all Pakistani offices this graph shows the proportion in use a different temperatures
A curve of p on To can then be drawn to show the probability that a control is being
used
Use of fans as a function of outdoor temperature in Pakistan
0%
20%
40%
60%
80%
100%
5 10 15 20 25 30 35 40
Mean outdoor temperature
% r
unn
ing
Probability control is in use is given by: p = e(a+bTo)/(1+e(a+bTo)) a and b are determined by regression analysis
Fans
0%
20%
40%
60%
80%
100%
0 10 20 30 40
Mean outdoor temperature
% r
unni
ng UKEuropePakistan
Use of fans
Details: Nicol, J.F. (2001) 7th international IBPSA conference, Rio
Windows
0%
20%
40%
60%
80%
100%
0 10 20 30 40
Mean outdoor temperature
% o
pen UK
EuropePakistan
Use of windows
Blinds or curtains
0%
20%
40%
60%
80%
100%
0 10 20 30 40
mean outdoor temperature
% d
raw
n
UKEurope
Use of blinds/curtains
Blinds in use vs illuminance
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
1.5 2 2.5 3 3.5 4 4.5 5 5.5
Log (base 10) of external illuminance
Pro
port
ion o
f blin
ds d
raw
n
Actual Ppredicted P
From data of Yannick Sutter, ENTPE, Lyons
The use of curtains is better related to the external illuminance:
Heating
0%
20%
40%
60%
80%
100%
0 10 20 30 40
mean outdoor temperature
% o
n UKEuropePakistan
Use of heating
AC on (mixed-mode buildings only)
0%
20%
40%
60%
80%
100%
0 5 10 15 20 25 30 35 40
Outdoor temperature oC
Pro
po
rtio
n r
un
nin
g
EuropePakistanEurope (actual)Pakistan (actual)
Occupant Building
Comfort is achieved by the occupants adapting to
the building
Or by the occupants adapting the building to
suit them
This has to be done within the climatic, social, economic and cultural context of the whole system
Cautionary note:
• Whilst essentially a negative feed-back system aimed at avoiding discomfort, the behaviour resulting from discomfort can lead to a positive feed-back in energy use:
Air-conditioning
Energy useGlobal warming
Occupant simulation
Building simulation
Comfort is achieved by the occupants adapting to
the building
Or by the occupants adapting the building to
suit them
This has to be done within the climatic, social, economic and cultural context of the whole system
Empirical results
New approaches
E.N. – Electricidade do Norte offices, Porto, Portugal
TOI
403020100
TG
40
30
20
10
• The temperatures were measured during office hours during a thermal comfort survey.
• It will be noticed that there is a tendency for the indoor temperature to be above the outdoor temperature in cold weather and often below it in warmer weather.
• There is also structure in the distribution of indoor temperatures at any given outdoor temperature
TG
35.0
34.0
33.0
32.0
31.0
30.0
29.0
28.0
27.0
26.0
25.0
24.0
23.0
22.0
21.0
20.0
19.0
18.0
17.0
16.0
15.0
TOIRND: 2.00300
250
200
150
100
50
0
Std. Dev = 1.86
Mean = 19.1
N = 28.00
TG
35.0
34.0
33.0
32.0
31.0
30.0
29.0
28.0
27.0
26.0
25.0
24.0
23.0
22.0
21.0
20.0
19.0
18.0
17.0
16.0
15.0
TOIRND: 4.00300
250
200
150
100
50
0
Std. Dev = 2.74
Mean = 18.5
N = 60.00
TG
35.0
34.0
33.0
32.0
31.0
30.0
29.0
28.0
27.0
26.0
25.0
24.0
23.0
22.0
21.0
20.0
19.0
18.0
17.0
16.0
15.0
TOIRND: 6.00300
250
200
150
100
50
0
Std. Dev = 2.53
Mean = 19.3
N = 101.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 8.00300
250
200
150
100
50
0
Std. Dev = 2.72
Mean = 20.09
N = 207.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 10.00300
250
200
150
100
50
0
Std. Dev = 2.50
Mean = 20.83
N = 456.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 12.00300
250
200
150
100
50
0
Std. Dev = 2.44
Mean = 21.51
N = 807.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 14.00300
250
200
150
100
50
0
Std. Dev = 2.04
Mean = 22.31
N = 974.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 16.00300
250
200
150
100
50
0
Std. Dev = 1.95
Mean = 23.22
N = 985.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 18.00300
250
200
150
100
50
0
Std. Dev = 1.81
Mean = 24.31
N = 849.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 20.00300
250
200
150
100
50
0
Std. Dev = 1.88
Mean = 24.86
N = 575.00
TG
35.0033.00
31.0029.00
27.0025.00
23.0021.00
19.0017.00
15.00
TOIRND: 22.00300
250
200
150
100
50
0
Std. Dev = 1.85
Mean = 25.29
N = 468.00
TG
35.0034.00
33.0032.00
31.0030.00
29.0028.00
27.0026.00
25.0024.00
23.0022.00
21.0020.00
19.0018.00
17.0016.00
15.00
TOIRND: 24.00300
250
200
150
100
50
0
Std. Dev = 1.75
Mean = 25.92
N = 257.00
TG
35.0034.00
33.0032.00
31.0030.00
29.0028.00
27.0026.00
25.0024.00
23.0022.00
21.0020.00
19.0018.00
17.0016.00
15.00
TOIRND: 26.00300
250
200
150
100
50
0
Std. Dev = 1.60
Mean = 26.28
N = 103.00
TG
35.0
34.0
33.0
32.0
31.0
30.0
29.0
28.0
27.0
26.0
25.0
24.0
23.0
22.0
21.0
20.0
19.0
18.0
17.0
16.0
15.0
TOIRND: 28.00300
250
200
150
100
50
0
Std. Dev = 1.86
Mean = 26.3
N = 67.00
TG
35.0034.00
33.0032.00
31.0030.00
29.0028.00
27.0026.00
25.0024.00
23.0022.00
21.0020.00
19.0018.00
17.0016.00
15.00
TOIRND: 30.00300
250
200
150
100
50
0
Std. Dev = 1.44
Mean = 26.60
N = 16.00
Comfort and preference
• How do you feel? How would you prefer to feel?
• Cold
• Cool Much warmer
• Slightly cool A bit warmer
• Neutral No change
• Slightly warm A bit cooler
• Warm Much cooler• Hot
0
20
40
60
80
100
19 21 23 25 27
Indoor temperature
% o
f o
ccu
pan
ts w
anti
ng
no
ch
ang
e
AllPoly. (All)
Most occupants want no change in indoor temperature
Mean outdoor temp.
0
20
40
60
80
100
19 21 23 25 27
Indoor temperature
% o
f o
ccu
pan
ts w
anti
ng
no
ch
ang
e
11.215.620.7AllPoly. (11.2)Poly. (20.7)Poly. (15.6)Poly. (All)
The effect of separating the outdoor temperatures
Conclusions• Comfort is a psychological, not a physiological
one
• Buildings must enable occupants to be comfortable
• AC is one way to do this but it is expensive in equipment and energy
• Buildings behave stochastically and not precisely, particularly when occupied
• Sustainable solutions need risk assessment not comfort prescriptions
