Green Occupants for Green Buildings
By
MAX PAUL DEUBLE
B.A., Macquarie University, 2007
B.A. (Honours), Macquarie University, 2008
A thesis submitted in fulfilment of the requirement for the degree of
DOCTOR OF PHILOSOPHY
Department of Environment and Geography
Faculty of Science
Macquarie University
June 2012
To dearest Patti: for teaching me the gift of giving
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Table of Contents
List of Figures .................................................................................. vii
List of Tables .................................................................................... xii
List of Abbreviations and Symbols ............................................... xiii
Glossary of Terms ............................................................................ xv
Abstract .......................................................................................... xvii
Declaration ....................................................................................... xx
Statement of Contribution ............................................................. xxi
Publications List............................................................................. xxii
Acknowledgements ....................................................................... xxiv
Chapter 1. Introduction .................................................................... 1
1.1. Background ............................................................................................................... 1
1.1.1. Energy and Buildings .............................................................................................. 3
1.2. Significance................................................................................................................ 5
1.2.1. Motivation ............................................................................................................... 8
1.3. Research Aim and Objectives................................................................................ 10
1.3.1. Environmental Attitudes and Occupant Satisfaction in Green Buildings ......... 10
1.3.2. Thermal Comfort in Mixed-Mode Buildings ..................................................... 11
1.3.3. The Validity of Contemporary Post-Occupancy Evaluation Methods .............. 11
1.4. Thesis Structure ...................................................................................................... 12
1.5. Chapter Summary .................................................................................................. 13
Chapter 2. Literature Review ......................................................... 15
2.1. Air-Conditioning vs. Natural Ventilation and the Rise of Mixed-Mode ............... 15
2.1.1. Classifications of Mixed-Mode Buildings ............................................................. 17
2.1.1.1. Concurrent ...................................................................................................... 18
2.1.1.2. Change-over ................................................................................................... 19
2.1.1.3. Zoned .............................................................................................................. 20
2.1.2. Making the Business Case for Mixed-Mode .......................................................... 21
2.1.2.1. Energy ............................................................................................................ 21
2.1.2.2. Occupant Satisfaction ..................................................................................... 23
2.1.2.3. Health, Productivity and Indoor Air Quality .................................................. 24
2.2. Thermal Comfort in Mixed-Mode Buildings ........................................................... 27
2.2.1. Static vs. Adaptive Thermal Comfort .................................................................... 27
2.2.2. International Comfort Standards .......................................................................... 32
2.2.3. Thermal Comfort in Mixed-Mode Buildings: What Do We Know So Far? .......... 35
2.2.4. Overheating ........................................................................................................... 37
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2.2.5. Personal vs. Automated Control............................................................................ 43
2.2.5.1. Personal Control ............................................................................................. 44
2.2.5.2. Automated Control ......................................................................................... 48
2.3. Post-Occupancy Evaluation ....................................................................................... 51
2.3.1. Post-Occupancy Evaluation: An Evolutionary Background ................................. 52
2.3.2. Uses and Misuses of Post-Occupancy Evaluation in Buildings ............................ 54
2.3.2.1. Lack of Context: ............................................................................................. 56
2.3.2.2. Lack of Feedback (Or Has the Loop Become A Noose?): ............................. 57
2.3.2.3. Lack of Instrumental Data: ............................................................................. 58
2.3.3. The Forgiveness Factor and Occupant Satisfaction in Green Buildings .............. 60
2.4. Chapter Summary ...................................................................................................... 62
Chapter 3. Methods .......................................................................... 65
3.1. Sydney's Climatic Context ......................................................................................... 65
3.2. Case Study Buildings and Their Occupants ............................................................ 69
3.2.1. Building E4A ......................................................................................................... 69
3.2.1.1. Building Selection Rationale .......................................................................... 74
3.2.2. Building E7A ......................................................................................................... 74
3.2.2.1. Building Selection Rationale .......................................................................... 78
3.3. Questionnaires and Survey Techniques ................................................................... 78
3.3.1. Post-Occupancy Evaluation and Environmental Attitudes Questionnaires .......... 79
3.3.1.1. Justification and Design ................................................................................. 80
3.3.1.2. Survey Techniques and Protocol .................................................................... 81
3.3.2. ‘Right Here, Right Now’ Thermal Comfort Questionnaires ................................. 82
3.3.2.1. Justification and Design ................................................................................. 82
3.3.2.2. Survey Techniques and Protocol .................................................................... 84
3.4. Indoor and Outdoor Climatic Instrumentation and Measurement Protocols ...... 85
3.4.1. Indoor Climate Measurements .............................................................................. 85
3.4.2. Clothing Insulation Estimates ............................................................................... 90
3.4.2.1. Effects of Chair Insulation on Clothing Insulation......................................... 91
3.4.3. Building Management System Data ...................................................................... 92
3.4.4. Outdoor Climate Measurements............................................................................ 93
3.5. Data Analyses and Complementary Calculations ................................................... 94
3.5.1. Statistical Analyses ................................................................................................ 95
3.5.2. Thermal Comfort Indices ....................................................................................... 95
3.6. Chapter Summary ...................................................................................................... 96
Chapter 4. Results and Discussion .................................................. 97
Paper 4.1. Environmental Attitudes and Occupant Satisfaction in Green Buildings . 99
4.1.1. Paper Overview ..................................................................................................... 99
Paper 4.2. Thermal Comfort in Mixed-Mode Buildings .............................................. 107
4.2.1. Paper Overview ................................................................................................... 107
Paper 4.3. The Validity of Contemporary Post-Occupancy Evaluation Methods .... 117
4.3.1. Paper Overview ................................................................................................... 117
4.4. Results and Discussions Summary .......................................................................... 169
4.4.1. Cultivating Environmental Attitudes ................................................................... 169
4.4.2. Engineering Occupant Expectations and Perceptions of Control ...................... 175
4.4.3. Incorporating Occupants into Building Design .................................................. 181
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4.5. Synthesis .................................................................................................................... 184
4.6. Limitations ................................................................................................................ 187
4.6.1. Instrumentation and Data Collection .................................................................. 187
4.6.2. Sample Size and Response Rates ......................................................................... 188
4.6.3. Questionnaire Data ............................................................................................. 189
4.6.4. Context of the Study............................................................................................. 189
4.7. Chapter Summary .................................................................................................... 190
Chapter 5. Conclusions ................................................................. 191
5.1. Summary of Aims and Objectives Addressed in This Thesis ............................... 191
5.1.1. Environmental Attitudes and Occupant Satisfaction in Green Buildings ....... 192
5.1.2. Thermal Comfort in Mixed-Mode Buildings ................................................... 194
5.1.3. The Validity of Contemporary Post-Occupancy Evaluation Methods ............ 196
5.2. Future Research .................................................................................................... 199
References ....................................................................................... 203
Appendix ......................................................................................... 227
Appendix A: Post-Occupancy Evaluation Study Human Ethics
and Final Report Approval ........................................................... 228
Appendix B: Building Use Studies Questionnaire License
Agreement ...................................................................................... 231
Appendix C: Post-Occupancy Evaluation Occupant Consent
Email ............................................................................................... 233
Appendix D: Environmental Attitudes Questionnaire ............... 235
Appendix E: Post-Occupancy Evaluation Study Instructions
Sheet ................................................................................................ 237
Appendix F: Thermal Comfort Study Human Ethics and Final
Report Approval ............................................................................ 239
Appendix G: Thermal Comfort Study Occupant Consent Email
......................................................................................................... 243
Appendix H: Thermal Comfort Study Background Questionnaire
......................................................................................................... 245
Appendix I: Thermal Comfort ‘Right Here, Right Now’
Questionnaire (summer/winter) ................................................... 247
Appendix J: Healthy Buildings 2009 Conference Paper ............ 249
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Appendix K: ANZAScA 2009 Conference Paper ........................ 254
Appendix L: Windsor 2010 Conference Paper ........................... 263
Appendix M: Co-Author Statement of Contribution ................. 272
Appendix N: Architectural Science Review Paper ....................... 275
Appendix O: Indoor Air 2011 Conference Paper ....................... 286
Appendix P: Is It Hot In Here Or Is It Just Me? Validating the
Post-Occupancy Evaluation Journal Submission Email ............ 293
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List of Figures
Chapter 1. Introduction
Figure 1.1: Estimated economic mitigation potential by sector in 2030 from bottom-up
studies, compared to the respective baselines assumed in the sector assessments. The
potentials do not include non-technical options such as lifestyle changes. OECD represents
developed countries part of the Organisation for Economic Cooperation and Development;
EIT represents Economies in Transition, i.e. developing countries; and non-OECD/EIT
represents countries not part of the OECD and not EIT (IPCC, 2007). .................................... 2
Figure 1.2: Commercial buildings energy share by energy source (DCC, 2008). ................... 4
Figure 1.3: Commercial building greenhouse gas emissions by energy source (DCC, 2008). 4
Figure 1.4: Commercial building energy share by end-use (DCC, 2008)................................ 5
Chapter 2. Literature Review
Figure 2.1: Concurrent mixed-mode operation (CBE, 2005). ............................................... 19
Figure 2.2: Change-over mixed-mode operation (CBE, 2005). ............................................. 20
Figure 2.3: Zoned mixed-mode operation (CBE, 2005). ....................................................... 21
Figure 2.4: Actual monthly metered energy consumption used by the supplementary cooling
and heating system in University of Sydney’s Wilkinson building between December 1997
and May 1999 compared with estimates from a simulation model of a conventional AC
system (Rowe, 2003). .............................................................................................................. 23
Figure 2.5: Cumulative frequency distribution for thermal satisfaction in mixed-mode
buildings (n=12) compared to CBE database (n=358). Coloured symbols on the y-axis
represent the median satisfaction score for each building set (Brager and Baker, 2009). ...... 24
Figure 2.6: Comparison of prevalence scores for sick building syndrome symptoms from 40
office surveys. Population average symbolised by solid black line (modified from Rowe,
2003; Forwood and Rowe, 2006). ........................................................................................... 26
Figure 2.7: Fanger’s (1970) Predicted Mean Vote and Predicted Percentage Dissatisfied
indices (sourced from Solomon, 2011). .................................................................................. 29
Figure 2.8: Observed (OBS) and predicted (PMV) indoor comfort temperatures from RP-884
database for (a) HVAC buildings and (b) NV buildings (de Dear and Brager, 2002). .......... 32
Figure 2.9: The ASHRAE Standard 55-2010 adaptive comfort standard for NV buildings
(ASHRAE, 2010). ................................................................................................................... 34
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Figure 2.10: Performance projections for a mixed-mode office under the effects of future
climate change (Holmes and Hacker, 2007). ........................................................................... 39
Figure 2.11: Simulation results displaying the trade-offs between (a) comfort and (b) energy
consumption for naturally-ventilated (NV), mixed-mode (MM) and mechanical ventilation
(labelled as VAV) cooling strategies. For the mixed-mode case, comfort exceedance
predictions are bracketed using both the ASHRAE 55 adaptive model (base bar) and the PPD
model (line extension) (Borgeson and Brager, 2011). ............................................................ 42
Figure 2.12: Exceedance predictions in the mixed-mode scenario with baseline gains using
the ASHRAE 55 adaptive comfort model and the PPD model across all 16 climate zones in
California (Borgeson and Brager, 2011). ................................................................................ 43
Figure 2.13: Reasons for thermal dissatisfaction in mixed-mode buildings in the US (Brager
and Baker, 2009). .................................................................................................................... 47
Chapter 3. Methods
Figure 3.1: Location of Sydney, Australia (sourced from Google, 2012). ............................. 66
Figure 3.2: Location of Macquarie University in relation to the Sydney Central Business
District (sourced from Google, 2012). .................................................................................... 67
Figure 3.3: Climate of Macquarie University, North Ryde between 1985-2010. Data was
sourced from the Willandra Village weather station in Marsfield (33°78’ S, 151°11’ E)
located 1 km from the campus (BoM, 2011). .......................................................................... 67
Figure 3.4: New South Wales Climate Zones (modified from ABCB, 2009). ...................... 68
Figure 3.5: Macquarie University North Ryde campus (sourced from MQ, 2012). .............. 70
Figure 3.6: Macquarie University’s Building E4A as viewed from the a) north facade and b)
south façade. ............................................................................................................................ 71
Figure 3.6c: Operable windows and internal grilles in NV mode. ......................................... 71
Figure 3.6d: Air-conditioning status display located on each floor. The green light indicates
AC mode; yellow light indicates NV mode and a red light indicates when windows have been
opened and AC mode has been disabled. ................................................................................ 71
Figure 3.6e: Building E4A BMS Algorithm. ......................................................................... 72
Figure 3.6f: Floor plan of Building E4A – Level 3. ............................................................... 73
Figure 3.7: Macquarie University’s Building E7A as viewed from the a) north-west corner
and b) south-west corner. ........................................................................................................ 75
Figure 3.7c: Part of the North façade of Building E7A showing some offices with room airconditioning units installed. The photo also shows ventilation fans in the windows of the
toilets in the east-facing wall of the “dog-leg” of the north façade. ........................................ 76
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Figure 3.7d: Office on the north side of E7A showing some pedestal/portable fans that
occupants often use for additional air movement. ................................................................... 76
Figure 3.7e: Floor plan of Building E7A – Level 2. .............................................................. 77
Figure 3.8: Timeline outlining each stage of both projects. ................................................... 79
Figure 3.9: “HOBO” U12-013 Temperature and Relative Humidity Datalogger.................. 86
Figure 3.10: “HOBO” U12-013 Temperature and Relative Humidity Datalogger with 40mm
sphere painted matte black attached to TMC1-HD Water/Soil Temperature Sensor. ............ 86
Figure 3.11: “TSI VelociCalc” Anemometer. ........................................................................ 87
Figure 3.12: “Vaisala HM34C” Humidity and Temperature Meter....................................... 87
Figure 3.13: “Vaisala” HM34C Humidity and Temperature Meter with 40mm sphere painted
matte black. ............................................................................................................................. 88
Figure 3.14: Typical example of office chairs used in a) Building E4A and b) Building E7A.
................................................................................................................................................. 92
Figure 3.15: Location of nearby BoM weather stations in relation to Macquarie University
(at red square). The Terry Hills and Sydney Olympic Park weather stations are located at the
blue squares (sourced from BoM, 2011). ................................................................................ 94
Chapter 4. Results and Discussion
Paper 4.1: Environmental Attitudes and Occupant Satisfaction in Green Buildings
Figure 4.1.1: MM building (sunny/north facade) featuring operable windows with external
solar shading devices on north-facing windows. .................................................................. 102
Figure 4.1.2: NV building (north facade) featuring occupant-operated windows with some
individual air-conditioner units. ............................................................................................ 102
Figure 4.1.3: Indoor and outdoor thermal environments comparing the NV and MM
buildings for March 2009. Indoor data plots represent daily average of indoor operative
temperature during occupied office hours (0800 – 1800 hrs). .............................................. 103
Figure 4.1.4: Relationship between NEP and forgiveness factor (FF) scores for both study
buildings combined. Numbers next to data points represent sample size for weighted linear
regression model. .................................................................................................................. 104
Paper 4.2: Thermal Comfort in Mixed-Mode Buildings
Figure 4.2.1: Climatology of the case study building site (adapted from BoM, 2011)........ 111
Figure 4.2.2: Typical floor plan of the commerce building (shaded area indicates the location
of the office in Figure 4.2.4a and b). ..................................................................................... 111
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Figure 4.2.3: The case study building as viewed from the a) North facade and b) South
facade..................................................................................................................................... 112
Figure 4.2.4: a) Typical layout of occupant offices monitored throughout the study (office
located in south zone as indicated in Figure 4.2.2) and b) shows the location of the datalogger
in relation to the occupant’s workspace. ............................................................................... 112
Figure 4.2.5: Air-conditioning control panel located at the entrance of each corridor. ....... 113
Figure 4.2.6: Binned outdoor temperatures plotted against average concurrent indoor
operative temperature (Top) for AC mode (dashed line with diamonds) and NV mode (solid
line with squares). .................................................................................................................. 113
Figure 4.2.7: Indoor operative temperature plotted against individual Actual Mean Vote
(AMV) values recorded during AC mode (diamonds) and NV mode (squares). .................. 113
Figure 4.2.8: Average observed (AMV – dashed line with diamonds) and predicted (PMV –
solid line with squares) thermal sensation votes plotted against binned indoor operative
temperature for both AC and NV modes of building operation. ........................................... 113
Figure 4.2.9: Average observed (AMV – dashed line with diamonds) and predicted (PMV –
solid line with squares) thermal sensation votes plotted against binned indoor operative
temperature for a) AC mode and b) NV modes of building operation. ................................ 114
Figure 4.2.10: Average observed (AMV) thermal sensation votes plotted against binned
indoor operative temperature for AC mode (dashed line with diamonds) and NV mode (solid
line with squares). .................................................................................................................. 114
Paper 4.3: The Validity of Contemporary Post-Occupancy Evaluation Methods
Figure 4.3.1: Climatology of the case study building site (adapted from BoM, 2011). ....... 157
Figure 4.3.2a: The MM building as viewed from the north facade featuring operable
windows with external solar shading devices on north-facing windows. ............................. 158
Figure 4.3.2b: User-operated windows and internal grilles in the North and South perimeter
offices of the MM building.................................................................................................... 159
Figure 4.3.3a: The NV building as viewed from the north facade featuring occupant-operated
windows with some individual air-conditioner units. ........................................................... 160
Figure 4.3.3b: Occupants often use portable fans or heaters for additional cooling/heating
throughout the year. ............................................................................................................... 161
Figure 4.3.4: Summertime thermal environment recorded for the MM and the NV building
(October 2009 to April 2010). Each data point corresponds to days in which thermal comfort
questionnaires were administered.......................................................................................... 162
Figure 4.3.5a: Average APD and PPD recorded in the MM building. ................................ 163
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Figure 4.3.5b: Average APD and PPD recorded in the NV building. ................................. 164
Figure 4.3.6a: Percentage of thermal acceptability votes registered in the MM building. .. 165
Figure 4.3.6b: Percentage of thermal acceptability votes registered in the NV building. ... 166
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List of Tables
Chapter 3. Methods
Table 3.1: Building Descriptions and Occupant Profiles. ...................................................... 74
Table 3.2: Indoor Climate Instrument Specifications. ............................................................ 89
Table 3.3: Individual clothing garments and their effective insulation values (I clu, i (clo)).
Ensemble intrinsic insulation values were derived by summing individual garment effective
insulation values (ASHRAE, 2001; ISO, 2003; ASHRAE, 2004). ......................................... 91
Chapter 3. Methods
Paper 4.1: Environmental Attitudes and Occupant Satisfaction in Green Buildings
Table 4.1.1: A summary of POE and NEP results for the MM and NV buildings. ............. 104
Table 4.1.2: Analysis of forgiveness factor and NEP results for the MM and NV building.
............................................................................................................................................... 104
Table 4.1.3: Forgiveness scores by ventilation type: Australian BUS database (n = 45). ... 105
Paper 4.2: Thermal Comfort in Mixed-Mode Buildings
Table 4.2.1: Summary of study variables and calculated indices for AC and NV modes. .. 114
Paper 4.3: The Validity of Contemporary Post-Occupancy Evaluation Methods
Table 4.3.1: Forgiveness factor and dissatisfaction percentages of variables in the POE for
the MM and NV building. ..................................................................................................... 167
Table 4.3.2: List of keywords and phrases used to identify complaints in each category. .. 168
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List of Abbreviations and Symbols
AC
Air-Conditioned
ACS
Adaptive Comfort Standard
AMV
Actual Mean Vote
ANOVA
Analysis of Variance
APD
Actual Percentage Dissatisfied
ARC
Australian Research Council
ASHRAE
American Society of Heating, Refrigerating and Air-Conditioning Engineers
AWS
Automatic Weather Station
BMS
Building Management System
BoM
Australian Bureau of Meteorology
BUS
Building Use Studies
CBE
Center for the Built Environment
CEN
Comité Européen de Normalisation (European Committee for Standardisation)
CO2
Carbon Dioxide
CO2-eq
Carbon Dioxide Equivalent
EIT
Economies in Transition
GBCA
Green Building Council of Australia
GHG
Greenhouse Gas
Gt
Giga-tonne = 1,000,000,000 tonnes
HVAC
Heating, Ventilation and Air-Conditioning
HYBVENT
Hybrid Ventilation in New and Retrofitted Office Buildings
IAQ
Indoor Air Quality
IEA
International Energy Agency
IEQ
Indoor Environmental Quality
IPCC
Intergovernmental Panel on Climate Change
ISO
International Organisation for Standardisation
MM
Mixed-Mode
MQ
Macquarie University
MRT
Mean Radiant Temperature
Mt
Mega-tonne = 1,000,000 tonnes
NEP
New Ecological Paradigm
NV
Naturally-Ventilated
xiii
OECD
Organisation for Economic Cooperation and Development
OFM
Macquarie University Office of Facilities Management
PMV
Predicted Mean Vote
POE
Post-Occupancy Evaluation
PPD
Predicted Percentage Dissatisfied
PROBE
Post-occupancy Review of Buildings and their Engineering
RIBA
Royal Institute of British Architects
RH
Relative Humidity
SBS
Sick Building Syndrome
SCATs
Smart Controls and Thermal Comfort
°C
Degrees Celsius
clo
Clothing insulation
ɛ
Emissivity
m/s
Metres per second
met
Metabolic rate
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Glossary of Terms
Actual Mean Vote (AMV)
A subjects’ actual thermal sensation as expressed on the seven-point thermal sensation scale
from ‘cold’ (-3) through ‘neutral’ (0) to ‘hot’ (+3). Throughout this thesis, AMV is also
referred to as the ‘observed thermal sensation’.
Actual Percentage Dissatisfied (APD)
A person in comfort is taken to be one who is ‘slightly cool’ (-1), ‘neutral’ (0) or ‘slightly
warm’ (+1) on the seven-point thermal sensation scale (ASHRAE, 2010). APD is calculated
as the proportion of AMV thermal sensation votes that fall outside this range of ‘comfortable’
votes divided by the total number of votes for that sample.
Adaptive Model
The adaptive model relates indoor design temperatures or acceptable temperature ranges to
outdoor meteorological or climatological parameters (de Dear and Brager, 1998; ASHRAE,
2010). This model recognises the role of human adaptation in establishing thermal comfort,
taking into account people’s thermal perception, behaviour and expectations, allowing for a
wider range of acceptable temperatures in NV buildings.
Comfort Temperature
This is the operative temperature at which either the average person will be thermally neutral,
or at which the largest proportion of a group of people, will be comfortable (ASHRAE,
2010).
Commercial Building
This term refers to a non-residential building that contains office spaces and primarily used
for commercial use.
Green Building
A building that aims to reduce its impact on the environment and increase the quality of life
for people who live and work in them (GBCA, 2008). Also referred to as ‘green-intent’
buildings, such buildings are designed to use less energy and water and consider the life cycle
xv
of the materials used by incorporating environmentally sustainable design, construction and
operational practices.
Green Occupant
An occupant is a person who occupies a building; also known as a ‘building user’. A ‘green’
occupant is one who is in-tune with their building’s performance and understands their
building’s environmental features and energy-efficient control systems. ‘Green’ occupants
can also have high levels of pro-environmental attitudes, and as a result, actively partake in
sustainable behaviour that reduces their own energy, water and waste consumption.
Low-Energy Building
Low-energy buildings are designed to maximise the passive use of the building’s form and
fabric to collect, store and distribute energy considering gross and operational energy. These
can also be referred to as ‘high performance’ buildings.
Predicted Mean Vote and Predicted Percentage Dissatisfied (PMV-PPD) Model
Also referred to as the ‘static’ model of comfort, the PMV-PPD model is based on the
principles of the human heat-balance equation (Fanger, 1970). The model calculates thermal
comfort as the relationship between four environmental variables: air temperature, radiant
temperature, air velocity and relative humidity; and two physiological variables: clothing
insulation (clo) and metabolic activity.
Predicted Mean Vote (PMV)
Predicted Mean Vote (PMV) is the average thermal sensation vote for a large group of
subjects on the seven-point thermal sensation scale when exposed to a particular environment
(Fanger, 1970; ASHRAE, 2010).
Predicted Percentage Dissatisfied (PPD)
Predicted Percentage Dissatisfied (PPD) is derived from PMV and is defined as an index
describing the percentage of occupants that are dissatisfied with the given thermal conditions
(Fanger, 1970; ASHRAE, 2010).
xvi
Abstract
Given contemporaneous concerns of climate change and increasing fossil fuel prices,
architects and building designers are exploring mixed-mode (MM) ventilation as a way of
combining the best features of air-conditioned (AC) and naturally-ventilated (NV) buildings.
MM or ‘hybrid’ buildings utilise a ‘free-running’ NV mode whenever outdoor weather
conditions are considered favourable, but revert to mechanical systems for heating,
ventilation and air-conditioning when external conditions are deemed less favourable for
occupants. This thesis explores how occupant expectations and environmental attitudes may
influence thermal comfort and occupant satisfaction within the context of the indoor thermal
environment. In doing so, it evaluates the potential for climate change mitigation in NV and
MM buildings through occupant behavioural adaptations.
Two academic office buildings with different ventilation strategies (i.e. MM and NV) from a
university in Sydney, Australia were used as case studies for this research. Post-occupancy
evaluations (POEs) supplemented with the 15-item New Ecological Paradigm (NEP)
questionnaire, measuring strength of endorsement (from low to high) of an ecological
worldview, were conducted in both buildings to examine how environmental attitudes can
influence occupants’ tolerance of the indoor environmental performance of green buildings.
Parallel thermal comfort studies, along with continuous indoor and outdoor climate
measurements, were also conducted to investigate the differences in occupant satisfaction and
comfort perceptions between each building and between the POE and comfort questionnaires.
The POE ‘forgiveness factor’ attempts to quantify the users’ tolerance of a building’s
environmental conditions by taking into account the user’s scores for thermal, acoustic and
visual comfort. This study found a possible association between environmental beliefs and
xvii
occupants’ forgiveness factor, which suggests that despite having less-than-ideal thermal
conditions, occupants with higher NEP scores were more tolerant of their building’s
shortcomings compared to occupants with lower NEP scores. Analyses of subjects’ thermal
sensation within the MM building indicated that observed comfort votes (Actual Mean Vote
– AMV) measured in AC mode were congruent to those predicted using the Predicted Mean
Vote (PMV) equation. During NV mode, however, observed AMV values did not conform to
the PMV values, suggesting that occupants were more adaptive to indoor operative
temperatures during NV mode as opposed to when the building was in AC mode. In
comparison, whilst occupants experienced significantly warmer operative temperatures in the
NV building, observed thermal sensations were also found to differ from the predicted
values, suggesting adaptive behaviours of the occupants. Thermal satisfaction and
acceptability, along with participant comments and anecdotal evidence from each building,
were analysed to investigate the effectiveness of POE methods in evaluating building
performance. Results from this study suggest occupants can and do use POE as a vehicle for
complaint about general workplace issues, unrelated to their building.
This thesis underscores the importance of occupant expectations and attitudes within the
indoor thermal environment. Each study highlights significant differences between
occupants’ thermal responses under different indoor environmental conditions, suggesting
people’s environmental attitudes and expectations affect their perception of comfort and
satisfaction within MM and NV buildings. Furthermore, the complexity of thermal perception
and the inadequacy of static models to describe occupant comfort in MM buildings are
discussed in the context of whether such design approaches fall within the scope of
international adaptive comfort standards. This research provides evidence to support
extending the psychological dimensions of thermal comfort and building performance studies
xviii
to account for the contextual influences at play in green buildings, such as environmental
attitudes, expectations and personal control.
xix
Declaration
I certify that the work in this thesis entitled “Green Occupants for Green Buildings”
has not been submitted for a higher degree to any other university or institution.
I also certify that this thesis is an original piece of research and has been written by me. Any
help and assistance that I have received in my research work and the preparation of this thesis
itself have been appropriately acknowledged. In addition, I certify that all information
sources and literature used are indicated in this thesis.
The research presented in this thesis was approved by Macquarie University Ethics Review
Committee, reference numbers: HE22AUG2008-D06019 on 29 August 2008 and
HE26SEP2008-D06064 on 16 October 2008.
Max Paul Deuble
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Statement of Contribution
This thesis follows the structure of thesis by publication, containing peer-reviewed
journal papers that constitute the ‘Results and Discussion’ chapter. The candidate’s individual
contribution with respect to the other co-authors of each paper is stated in the introduction of
the Results and Discussion chapter.
Research Thesis by Publication (s): a preferred Macquarie University model
“…Theses may include relevant papers (including conference presentations) published or
accepted for publication during the period of candidature, together with a comprehensive and
critical introduction and an integrative conclusion. A candidate may only include published
work which is part of the distinct contribution to knowledge of the thesis if the research and
publication of the work occurred during the candidature for the degree. These papers should
form a coherent and integrated body of work, which should be focussed on a single project or
set of related questions of propositions; however, it is not necessary to reformat published
works in the thesis. These papers may be single authored or co-authored – in the case of coauthored papers the candidate must specify his/her specific contribution…The contribution of
others to the preparation of thesis or to individual parts of the thesis should be specified in the
thesis Acknowledgements and/or in relevant footnotes/endnotes. It is not necessary to
reformat published works in a thesis”.1
Macquarie University (2011) ‘Thesis by Publication Guidelines’, Retrieved 21 st December, 2011, from
http://www.mq.edu.au/policy/docs/hdr_thesis/guideline_by_publication.html
1
xxi
Publications List
This thesis is presented in accordance to Macquarie University’s guidelines for a
thesis by publication. Results from this thesis are published in, or submitted for publication,
in the following papers:
Peer-Reviewed Journal Papers
1. Drake, S., de Dear, R., Alessi, A. and Deuble, M. (2010) ‘Occupant comfort in
naturally ventilated and mixed-mode spaces within air-conditioned offices’,
Architectural Science Review, 53(3): 297-306
DOI: http://dx.doi.org/10.3763/asre.2010.0021
2. Deuble, M.P. and de Dear, R.J. (2012) ‘Mixed-mode buildings: A double standard in
occupants’ comfort expectations’, Building and Environment, 54(8): 53-60
DOI: http://dx.doi.org/10.1016/j.buildenv.2012.01.021
3. Deuble, M.P. and de Dear, R.J. (2012) ‘Green occupants for green buildings: The
missing link?, Building and Environment, 56(10): 21-27
DOI: http://dx.doi.org/10.1016/j.buildenv.2012.02.029
4. Deuble, M.P and de Dear, R.J (2012) ‘Is it hot in here or is it just me? Validating the
post-occupancy evaluation’ (submitted to Intelligent Buildings International, May
2012).
Peer-Reviewed Conference Papers
1. Deuble, M. and de Dear, R. (2009) ‘Do green buildings need green occupants’,
Proceedings of the Healthy Buildings 2009 Conference, Syracuse, NY, USA, 13-17
September 2009
xxii
2. Drake, S., de Dear, R., Alessi, A. and Deuble, M. (2009) ‘Occupant comfort in
naturally ventilated and mixed-mode spaces within air-conditioned offices’,
Proceedings of the 43rd Annual ANZAScA Conference 2009: Performative Ecologies
in the Built Environment - Sustainability Research Across Disciplines, Launceston,
Tasmania, Australia, 25-27 November 2009
3. Deuble, M. and de Dear, R. (2010) ‘Green occupants for green buildings: The missing
link?’, Proceedings of the 2010 Windsor Conference: Adapting to Change: New
Thinking on Comfort’ Windsor, London, UK, Network for Comfort and Energy Use
in Buildings, http://nceub.org.uk, 9-11 April 2010
4. Deuble, M. and de Dear, R. (2011) ‘Mixed-mode buildings: A double standard in
comfort’, Proceedings of Indoor Air 2011 Conference, Austin, TX, USA, 5-10 June
2011
xxiii
Acknowledgements
First and foremost I offer my sincerest gratitude to Professor Richard de Dear, without
whom this thesis would not have been possible. Your generous supervision and patient
guidance over the years has been an endless source of inspiration and support. You have
become one of my life’s great mentors, constantly driving me to “get more questionnaire
data...” until my legs give out and I am truly honoured to have been one of your PhD
students.
I would like to thank Associate Professor Paul Beggs for his much appreciated assistance
during this research. Upon taking the reins of the administrative duties associated with this
thesis, you have given me great advice and skills to deal with some unfortunate worst-case
budget scenarios. I cannot thank you enough for your dedicated attention and expertise, and
most of all, allowing me to travel to the Indoor Air 2011 conference which has truly been the
highlight of my candidature.
I am thankful to Associate Professor Scott Drake and Angela Alessi for our many stimulating
discussions regarding our respective projects. Thank you for your supportive and encouraging
contributions to this thesis.
I would like to thank Macquarie University’s Climate Science Laboratory staff for providing
the equipment and instruments necessary to conduct the indoor climate measurements. Many
thanks should be given to Macquarie University’s Office of Facilities Management,
especially Messrs Kerry Russell and Dennis Harrold, for their assistance in gathering the data
needed for this research. Special thanks go to the Office of Sustainability’s Leanne Denby for
xxiv
her support as well as Chris Arkins for his help in providing data and information related to
the mixed-mode building.
I am enormously grateful to Adrian Leaman for permission to use the Building Use Studies
Post-Occupancy Evaluation questionnaire under licence and his assistance in data analysis. I
would also like to express my appreciation to all the participants who gave up their time to
respond to all, and I mean ALL, of my questionnaires.
Thanks also to the staff and students of the Department of Environment and Geography,
Macquarie University. Their enthusiasm and interest in my research was greatly appreciated.
Special thanks go to Christhina Candido and Richard de Dear’s University of Sydney IEQ
crew: Thomas Parkinson, Hisham Allam, Craig Roussac, Junsoo Kim and Libby Gallagher.
Thank you for your enthusiastic comments during our discussions, especially during those
Comfort Zone Seminars.
I would like to also thank Xiaofeng Li, Mohammad Kotbi and Michelle Lakeridou for our
friendly email discussions, allowing me to value and understand my own work as well as see
things from a different perspective. Thanks also to Riley Dunlap and Michael Humphreys for
their generous feedback and encouraging comments received during this research. Many
thanks are owed to everyone I had the chance to meet and talk with at all the conferences I
attended at different stages of this research. Thank you for viewing my presentations and
your many thought-provoking questions.
This research was financially supported in part by an Australian Research Council (ARC)
Discovery Project Grant (DP0880968) from 2008 to 2011. Macquarie University also
xxv
provided annual funding for project-related costs and conference attendance between 2008
and 2011.
Lastly, but certainly not least, I would like to thank my beloved family and partner Antania
who always support me in everything I do, with everything they have. I’d personally like to
thank you for your tremendous patience and for giving me the strength to endure the journey
that was this PhD.
xxvi
Chapter 1. Introduction
“Life begins at the end of your comfort zone.” Bear Grylls
In providing an introduction to the thesis, this chapter presents a background to the
thesis topic and states the significance and motivation of this research. This is followed by the
aims and objectives of the thesis as well as an outline of the thesis structure.
1.1. Background
Fossil fuel combustion, population growth and land use change (i.e. urbanisation)
since 1750 are the primary causes for the global increases in atmospheric concentrations of
carbon dioxide, resulting in a gradual warming of the Earth’s climate. It is well documented
that the construction process and activities within buildings demand significant use of
greenhouse gas (GHG) emitting energy sources. In its Fourth Assessment Report, the
Intergovernmental Panel on Climate Change (IPCC, 2007) estimated that annual emissions
from the buildings sector through electricity use were 8.6 Giga-tonnes of carbon dioxide
(GtCO2), equivalent to a quarter of the global total in 2004 (Price et al., 2006; Levine et al.,
2007). The commonly used IPCC Special Report on Emissions Scenarios (IPCC, 2000)
projects these estimates to grow to 15.6 GtCO2 (A1 scenario2) and 11.4 GtCO2 (B2 scenario3)
by 2030 (Levine et al., 2007; Urge-Vorsatz et al., 2007), representing approximately 30% of
total CO2 emissions in both scenarios. The buildings sector has also been identified as
possessing the greatest potential for climate change mitigation (Urge-Vorsatz et al., 2007;
Levermore, 2008a). Based on GHG emission mitigation potentials for three separate
valuations per tonne of carbon dioxide equivalent (CO2-eq – the combined global warming
2
The A1 storyline and scenario family describes a future world of very rapid economic growth, global
population that peaks in mid-century and declines thereafter, with the rapid introduction of new and more
efficient technologies.
3
The B2 storyline and scenario family describes a world in which the emphasis is on local solutions to
economic, social and environmental sustainability. It is a world with continuously increasing global population,
intermediate levels of economic development, and less rapid and more diverse technological change than the A1
storyline.
1
potential for all greenhouse gases expressed in terms of carbon dioxide), Figure 1.1 estimates
the global potential to reduce projected baseline emissions in the built environment through
cost-effective engineering measures as 29% by 2030. As illustrated in Figure 1.1, from
technical options alone, the buildings sector far out-ranks the other sectors in terms of its
economic mitigation potential, i.e. taking into account social costs and benefits assuming
market efficiency is improved by policies and measures and barriers are removed
(Levermore, 2008b). According to IPCC reports, a significant portion of these reductions in
CO2 emissions can be attributed to ways that reduce a building’s life-cycle costs.
Occupant behaviour, culture and use of technologies are major determinants of energy use in
buildings and hence play a pivotal role in determining CO2 emissions. However, the potential
of lifestyle and behaviour change policies and programmes are rarely assessed and have been
omitted from Figure 1.1. It is often suggested that the greenhouse mitigation potential for the
buildings sector would be significantly higher had these non-technical options been
incorporated (Urge-Vorsatz et al., 2007).
Figure 1.1: Estimated economic mitigation potential by sector in 2030 from bottom-up
studies, compared to the respective baselines assumed in the sector assessments. The
potentials do not include non-technical options such as lifestyle changes. OECD represents
developed countries part of the Organisation for Economic Cooperation and Development;
EIT represents Economies in Transition, i.e. developing countries; and non-OECD/EIT
represents countries not part of the OECD and not EIT (IPCC, 2007).
2
1.1.1. Energy and Buildings
Within OECD countries, buildings account for up to 40% of energy end-use.
According to the US Department of Energy’s Buildings Energy Data Book, the buildings
sector accounted for 73% of total electricity consumption in 2008 (DOE, 2008) and nearly
half (47%) of US CO2 emissions (Architecture 2030, 2011). Of this energy, almost 40% is
used by buildings for space heating, ventilation and air-conditioning (HVAC) (Butera, 2010).
Similarly, in the UK, approximately 55% of the energy consumed in offices is for HVAC
building services (Perez-Lombard et al., 2009). Whilst energy conservation strategies in
developed nations present enormous scope for improvement, even more mitigation potential
is present in the developing world. Countries such as China and India are emerging as the
world’s largest carbon emitters (Zhang, 2010). China’s buildings sector accounts for 46.7%
of the country’s total energy consumption, with heating and air-conditioning end-use alone
contributing to 65% of the sector’s total energy consumption (Wang et al., 2010). In India,
the rapid expansion of Grade A, air-conditioned (AC) office buildings is a key contributor to
the country’s soaring demand for electricity (Lall et al., 2010; Thomas et al., 2010).
Within Australia, CO2 emissions from fossil fuel energy used directly or as electricity to
power equipment and condition the air (including heating and cooling) is by far the largest
source of GHG emissions in the Australian buildings sector (CIE, 2007; DCC, 2008). As
Figure 1.2 demonstrates, electricity accounts for 65% of energy usage, representing 89% of
GHG emissions (shown in Figure 1.3) (DCC, 2008). In 1990, the Australian buildings sector
was responsible for 21% of Australia’s total greenhouse emissions and 28% of the energyrelated emissions; the non-residential and residential sectors contributing 40% and 60%
respectively (AGO, 1999a; AGO, 1999b). Since 1990, reports estimate that Australian
buildings accounted for nearly 20% of Australia’s final energy end-use and were responsible
for 23% of Australia’s GHG emissions in 2005 (ABARE, 2003; ABARE, 2006b; CIE, 2007).
3
Driven mainly by its end use, and/or demand for electricity, buildings sector emissions are
projected to grow from 130 Mega-tonnes (Mt) per annum in 2005 to 210 Mt by 2030
(ABARE, 2006a). According to CIE (2007), these are projected to grow to 280 Mt by 2050
with commercial sector emissions expected to grow at a faster pace than the residential
sector.
Figure 1.2: Commercial buildings energy share by energy source (DCC, 2008).
Figure 1.3: Commercial building greenhouse gas emissions by energy source (DCC, 2008).
Globally, space heating and cooling are the dominant energy end-uses in the buildings sector
(IPCC, 2007). Within Australia’s commercial sector, climate control (HVAC) is a major
contributor to the sector’s energy needs, accounting for 61.2% in 2005, as illustrated in
4
Figure 1.4 (CIE, 2007; DCC, 2008). The basic purpose of an HVAC system is to provide
comfortable interior thermal conditions to all occupants, i.e. thermal comfort (ASHRAE,
2010). As the core concept of ‘thermal comfort’ is more of a state of mind (reflecting
different cultural, class and geographical conditions) than a technical certainty (ASHRAE,
2001), assessing the right level of thermal comfort is critical to setting building performance
standards (Cena and Clark, 1981; Kwok and Rajkovich, 2010). This requires an
understanding of the extent to which people are ready to make behavioural changes to
achieve comfort in their environment. This, in turn, affects the way building occupants
interact with their environment – from choosing to pull down external blinds to limit sun
penetration at certain times of day (rather than switching on the air-conditioning) to putting
on a sweater when the temperature drops (rather than turning up the thermostat). Typically,
green buildings require a more proactive engagement between the occupant and the built
environment, which reflects the greater reliance on the “passive” versus “active”
environmental control strategies available (Barlow and Fiala, 2007).
Figure 1.4: Commercial building energy share by end-use (DCC, 2008).
1.2. Significance
Many non-residential buildings in the second half of the 20 th century and later were
designed to be sealed envelopes heated or cooled with centralised HVAC systems. These
5
buildings were engineered to maintain fairly constant conditions throughout the interior for
all occupants, consuming excessive amounts of energy in the process. In contrast, emergent
‘green’ buildings, often with increased capability for natural ventilation and minimised
dependence on heating or cooling systems, present more sustainable, less energy-intensive
solutions. These buildings are more loosely controlled, providing greater internal
environmental variation (e.g. de Dear and Brager, 1998; Humphreys and Nicol, 1998; de
Dear and Brager, 2002; Nicol and Humphreys, 2002; Brager et al., 2004) via operable
windows, user-adjustable shade devices, etc., or by adaptive comfort algorithms that more
closely match indoor thermal conditions to temperatures prevailing outdoors. This shift
towards more variable indoor environmental conditions represents a recurring theme in
contemporary sustainable building design, providing thermal comfort while reducing energy
use and associated GHG emissions (de Dear and Brager, 2002). However, while occupants
appreciate a high degree of adaptive opportunities (Baker and Standeven, 1996), as found in
naturally-ventilated (NV) buildings, they do not necessarily appreciate the thermally
uncomfortable conditions in NV buildings during unusually hot weather (Bordass et al.,
2001b; Leaman and Bordass, 2003). In response, architects and engineers are exploring
‘mixed-mode’ (MM) ventilation as a way of combining the benefits of air-conditioning and
natural ventilation (Brager, 2006; Rijal et al., 2008; Brager and Baker, 2009).
The basic concept of MM or ‘hybrid’ ventilation is to maintain satisfactory indoor thermal
environments by alternating between and combining natural and mechanical systems, thereby
minimising the significant energy use and operating costs associated with air-conditioning.
Predominantly designed as NV structures with operable windows, MM buildings also have
the capability of switching into an AC building whenever the outdoor weather conditions
make the NV option untenable for the occupants. This design strategy allows the building to
‘change-over’ between NV and AC modes on a seasonal or even daily basis (CBE, 2005).
6
There are many variations on this theme, such as concurrent strategies that utilise airconditioning and operable windows in the same space and at the same time; and zoned
strategies whereby different zones within the same building have different cooling modes
(CBE, 2005; Brager et al., 2007).
Following the adoption of the adaptive comfort standard (ACS) in ASHRAE Standard 55
(ASHRAE, 2004) as an alternative to the PMV-based method for NV buildings, many studies
(e.g. Brager and de Dear, 1998; de Dear and Brager, 2002; Nicol and Humphreys, 2002;
Turner, 2008) believe the standard should have included MM buildings. But at the time of
ASHRAE 55-2004 going to press, insufficient comfort studies undertaken in MM buildings
meant they were excluded from the scope of the ACS (de Dear and Brager, 2002). Despite
the most recent revisions to the standard (ASHRAE, 2010), the ACS is still constrained in
scope to naturally conditioned, occupant-controlled spaces in which thermal comfort
conditions are primarily regulated by operable windows. Furthermore, ASHRAE explicitly
states that when mechanical cooling systems are provided for the space, as is the case for
MM buildings, the ACS is not applicable (Nicol and Humphreys, 2002; Turner, 2008; de
Dear, 2011). Thus, the GHG mitigation potential afforded by the standard does not extend to
the NV mode of MM buildings. Because of the presence of HVAC capabilities, MM
buildings fall under the scope of the more restrictive PMV-PPD method (de Dear and Brager,
2002; Nicol and Humphreys, 2002; Turner, 2008). The European counterpart standard,
EN15251 (CEN, 2007), however, allows the more flexible adaptive comfort standard to be
applied to NV buildings which can include MM buildings during times when they are not
employing mechanical cooling, i.e. whilst in NV or ‘free-running’ mode (Nicol and
Humphreys, 2010).
7
1.2.1. Motivation
Launched in 2002, the Green Building Council of Australia’s (GBCA) Green Star is a
comprehensive environmental rating system used to evaluate the environmental design and
construction of buildings in Australia (GBCA, 2008). However, Reed et al., (2009),
summarises some of the potential shortfalls and dangers associated with such building
sustainability indices. These tools are primarily based on building materials, energy systems
and cooling technologies, giving very little attention to the behaviour and culture of the
building occupants, and even less to their environmental attitudes. Despite being a positive
driving force in Australia’s green construction industry, Green Star building ratings are
potentially misleading if occupants do not behave in a way that complements the building’s
design intent. Thus in order to fully maximise the carbon mitigation potential of green
buildings, occupants need to be sympathetic to the building’s green design-intent. The
aphorism ‘green buildings need green occupants’ (Browne and Frame, 1999) summarises this
point.
Post-occupancy evaluation (POE) studies provide a general overview of occupant satisfaction
for any given building. Surveys done in the UK and US (e.g. Abbaszadeh et al., 2006;
Leaman and Bordass, 2007; Brager and Baker, 2009) indicate that occupants are more
favourably disposed to green buildings. As noted by Leaman and Bordass (2007) and Brager
and Baker (2009), occupant satisfaction scores for green-intent buildings tend to be better
than those in conventional AC buildings. Green buildings show greater levels of occupant
satisfaction and better ratings for perceived health and productivity compared to non-green
buildings. However, based on objective indoor environmental quality (IEQ) performance
criteria, such buildings don’t necessarily outperform conventional AC alternatives. They are
often hotter in summer, colder in winter and contain more solar glare from the sun and sky.
Recent surveys of post-occupancy literature (Leaman and Bordass, 2007; Baird, 2010)
8
however, suggest that green building users are prepared to forgive such conditions if they
possess a modicum of environmental control. The term ‘forgiveness factor’ was coined by
Leaman and Bordass (2007) to describe this phenomenon. Could this ‘forgiveness’ be due to
the occupants having more relaxed expectations for green buildings as opposed to
conventional AC settings? Or perhaps occupants’ environmental attitudes and beliefs can
influence their tolerance of green buildings? Perhaps occupants who are fully cognisant of the
role played by HVAC energy in global climate change will be more tolerant of green
buildings than those occupants who are in denial of anthropogenic climate change?
In recent decades there has been a growing awareness of the problematic relationship
between modern industrialised societies and the physical environments upon which they
depend (Oskamp, 2000; Stern, 2000; Dunlap, 2008). As such, there is an increasing focus on
the quantification of public sentiment to these issues, as well as the determinants of proenvironmental or sustainable behaviour change. Environmental attitudes are defined as ‘the
collection of beliefs, affect and behavioural intentions a person holds regarding
environmentally-related activities or issues’ (Himmelfarb, 1993; Schultz et al., 2004; Milfont
and Duckitt, 2010). Furthermore, it has been established that environmental attitudes are
powerful predictors of pro-environmental behaviour (Kaiser et al., 1999; Milfont and Duckitt,
2004).
Whereas several environmental attitudinal scales and measures have been developed since
the 1960s (e.g. Maloney and Ward, 1973; Weigel and Weigel, 1978), very few have been
successfully validated or been adapted to measure building occupants’ level of ‘greenness’.
Dunlap and van Liere’s New Environmental Paradigm (Dunlap and van Liere, 1978), later
revised as the New Ecological Paradigm (NEP) scale (Dunlap et al., 2000), has become the
most widely used index of pro-environmental attitudes. This 15-item questionnaire consists
9
of 8 pro-NEP and 7 anti-NEP items to determine whether a person’s attitudes and behaviours
are pro- or anti-environmental. As such, it represents a quick and easy metric of building
occupants’ level of ‘greenness’ based on their endorsement of an ecological worldview
(Dunlap, 2008; Hawcroft and Milfont, 2010). After extensive application across a diverse
range of studies (e.g. Stern et al., 1995; Blake, 2001; Ewert and Baker, 2001; Poortinga et al.,
2004) a broad consensus has emerged in the environmental psychology literature that the
NEP represents a valid and reliable scale for measuring levels of ecological beliefs and
attitudes (Dunlap and Jones, 2002; Cordano et al., 2003). However, prior to this research, the
NEP scale has never been used in conjunction with building occupant studies and could
potentially identify the link between successful occupancy of green buildings and
environmental attitudes.
1.3. Research Aim and Objectives
This thesis aims to evaluate how occupant expectations and environmental attitudes
influence thermal comfort and occupant satisfaction within the context of low-energy indoor
thermal environments, as found in MM and NV buildings. This aim is split into three main
studies, i.e. environmental attitudes and occupant satisfaction in green buildings; thermal
comfort in MM buildings; and the validity of contemporary POE methods. The research
objectives specific to each study, which will be addressed throughout this thesis, are as
follows:
1.3.1. Environmental Attitudes and Occupant Satisfaction in Green Buildings
1. By conducting POEs within two ‘green’ buildings, i.e. a MM and a NV building, this
study aims to evaluate the occupants’ ‘forgiveness factor’ in relation to their thermal
environment.
10
2. Through the use of the NEP questionnaire, this study investigates occupants’ levels of
environmental attitudes within the MM and NV buildings. It is hypothesised that
broadly pro-environmental attitudes are associated with the stronger ‘forgiveness
factors’ towards indoor thermal environmental performance often reported in green
building POE studies in the research literature.
1.3.2. Thermal Comfort in Mixed-Mode Buildings
1. This study aims to understand how MM ventilation affects occupant comfort by
comparing both observed and predicted thermal sensation votes recorded in AC and
NV modes. In doing so, this study will test whether the adaptive comfort model can
be applied to MM buildings, especially during times of natural ventilation.
2. By evaluating the current definition and scope of the adaptive comfort standards in
ASHRAE 55-2010 and EN15251-2007, the implications of this research are discussed
in the context of whether adaptive comfort standards for NV buildings should be
applied to MM buildings.
1.3.3. The Validity of Contemporary Post-Occupancy Evaluation Methods
1. By comparing the results from the POE and thermal comfort field studies in the MM
and NV buildings, this study aims to test the validity of assessing building
performance using the POE method.
2. Occupant satisfaction and thermal acceptability levels, along with participants’
comments and anecdotal evidence, were analysed between each method to examine
how POEs may generate over-exaggerated responses of poor building performance.
3. Finally, this study makes recommendations as to how these tools can be improved,
encouraging a more holistic approach to building performance evaluation.
11
1.4. Thesis Structure
This chapter introduced the broad context, significance and motivation for this
research, stating the key aims and objectives pursued during the development of this thesis.
Chapter 2 presents a review of the current literature related to the research questions of this
thesis. The first section of this chapter focuses on the emergence of MM ventilation in the
built environment, highlighting numerous thermal comfort studies from both the ‘static’ and
‘adaptive’ approaches. Current debates surrounding the applicability of MM buildings within
the ACS, as well as issues of overheating and occupant control are also discussed. The
second section critiques the current use of POEs in evaluating building performance in the
field of IEQ research. A brief summary of the literature review chapter is presented.
Chapter 3 explains the methods applied throughout this thesis. In describing the design and
development of each questionnaire used, the two separate projects conducted within Sydney
from March 2009 to April 2010 are presented, along with their respective data collection and
survey techniques. The instruments and resources utilised to record both the indoor and
outdoor climatic data are provided along with detailed descriptions of the site’s climatic
context, each case study building and their occupants. Documents relating to the ethical and
methodological design of this research, e.g. ethics approvals and questionnaires are presented
in Appendices A to I.
Chapter 4 presents the main results and discussions of this thesis, which includes research
papers that have been submitted to, or published in peer-reviewed journals during the course
of this research. Based on the corresponding peer-reviewed journal papers, three key topics of
analysis relating to the thesis’ research aims are presented: environmental attitudes and
occupant satisfaction in green buildings (Paper 4.1); thermal comfort in MM buildings (Paper
4.2); and the validity of contemporary POE methods (Paper 4.3). Complementary research
12
results, such as those published in peer-reviewed journals and/or conference proceedings are
presented in Appendices J to P. A summary of the main results and discussions, as well as the
limitations of this research, is also presented.
Finally, Chapter 5 presents the concluding remarks derived from the results and suggests
recommendations in which further research may be necessary.
1.5. Chapter Summary
This chapter provided an introduction to the thesis, the significance and motivation of
this research as well as the key objectives. The next chapter presents a review of the current
literature related to this thesis.
13
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14
Chapter 2. Literature Review
This chapter presents a review of the current literature related to this thesis. The first
section introduces the concept of MM ventilation, highlighting thermal comfort studies from
both the ‘static’ and ‘adaptive’ approaches. Topical debates surrounding the future inclusion
of MM buildings into international comfort standards are also discussed, along with the
issues of overheating and occupant control. The next section critiques the use of
contemporary POE methods in building performance evaluations, as well as the emerging
topic of occupant forgiveness and satisfaction in green buildings. Finally, a chapter summary
is provided.
2.1. Air-Conditioning vs. Natural Ventilation and the Rise of Mixed-Mode
The main purpose of any building is to provide a safe and comfortable environment
that neither impairs the health of its occupants nor hinders their performance. Prior to the 21st
century, office buildings were generally designed with a building-centred, energy-intensive
approach focussed on providing standardised indoor climates for all occupants through
HVAC technology (Cooper, 1998; Ackermann, 2002). Following the energy crises of the
1970s, many countries started to rethink the design of, and services, within buildings. Since
then, many governmental and professional bodies have sought to improve the energy
efficiency of buildings by reducing energy consumption without compromising occupant
comfort, health and productivity levels (e.g. Roaf, 2006; Perez-Lombard et al., 2009).
However, a central issue in the efficiency, and effectiveness, of buildings are the occupants
(Janda, 2011).
Architects are now diversifying opportunities available in buildings to provide comfort for
occupants (Roaf, 2006). This shift to more heterogeneous indoor environments, often using
15
natural ventilation as opposed to compressor-based air-conditioning, suggests occupants are
no longer passive recipients of an active environment (Forwood, 1995; de Dear, 2007).
Increasingly they expect more control over their environment and want a rapid response to
any discomfort they experience, which is difficult to achieve in AC buildings (Bordass et al.,
1993). In order to provide such behavioural, or ‘adaptive’ opportunities (Baker and
Standeven, 1996), buildings must be designed to re-engage ‘active’ occupants in the
achievement of comfort. NV buildings require a more proactive engagement between the
occupier and the environment. In offering more ‘adaptive opportunities’ (Baker and
Standeven, 1996) for the occupants, a higher degree of interaction among the occupants is
required to achieve thermally comfortable environments; active occupants for passive
buildings (Barlow and Fiala, 2007; de Dear, 2007; Cole et al., 2008).
According to the American Society of Heating, Refrigerating and Air-Conditioning
Engineers (ASHRAE, 2001), mechanical HVAC systems were purposely built to maintain
constant thermal environmental conditions throughout the interior, aiming for an optimum
‘steady-state’ temperature setting based on Fanger’s Predicted Mean Vote (PMV) and
Predicted Percentage Dissatisfied (PPD) model (Fanger, 1970). Many argue that since the
advent of air-conditioning in the early 20th century, occupant expectations of the indoor
environment have changed (Prins, 1992; Cooper, 1998; Ackermann, 2002). Countless studies
in recent decades have made the case for greater environmental variation inside buildings,
either through user operable windows and shade devices, or by other adaptive opportunities
such as control algorithms that more closely match indoor thermal conditions to prevailing
outdoor temperatures (e.g. Busch, 1992; de Dear and Brager, 1998; Humphreys and Nicol,
1998; de Dear and Brager, 2002; Brager et al., 2004; Rowe, 2004; Humphreys et al., 2007;
Rijal et al., 2007). Spatially, thermally differentiated zones can accommodate a variety of
individual thermal requirements (Kwok, 2000; Kwok and Rajkovich, 2010). Temporally,
16
indoor temperatures can gradually drift towards outdoor conditions and encourage occupant
adaptations such as clothing changes and use of operable windows (Brager and de Dear,
1998; Brager and de Dear, 2000).
While occupants generally prefer indoor environments with ‘adaptive opportunities’ (Baker
and Standeven, 1996), they may not appreciate the thermally uncomfortable conditions likely
to occur in NV buildings during unusually hot weather. However, they are often prepared to
forgive such conditions if they possess a modicum of environmental control (Cohen, 1997; de
Dear and Brager, 1998; de Dear and Brager, 2002; Brager et al., 2004). MM or ‘hybrid’
buildings represent a compromise that combines the best features of NV and AC buildings
(Brager, 2006; Brager and Baker, 2009; Rijal et al., 2009). It should be noted that the terms
‘hybrid’ and ‘mixed-mode’ are used interchangeably to describe any building that combines
the use of both natural and mechanical systems for cooling and ventilation.
2.1.1. Classifications of Mixed-Mode Buildings
The energy consumption of buildings depends significantly on the criteria used for the
indoor environment, which also affects health, productivity and comfort of the occupants
(Olesen, 2007). Considering HVAC systems are the single largest energy end-use in the built
environment, it is inevitable that we should look critically at our dependence on mechanically
cooled indoor climates. In a numerical analysis of strategies to adapt existing building stock
for changes in the UK climate, CIBSE (2005) discerned four basic design principles:
1. Minimise heat gains (solar shade) and ensure internal equipment is switched off when
not required (‘switch off’);
2. The impact of gains can be reduced by attenuating peaks by means of thermal mass
(‘spread out’);
17
3. Ventilation systems should be properly controlled to ensure gains are removed and
not added to, e.g. by not introducing outside air when that air is at a temperature
higher than that in the building (other than that required to maintain air quality)
(‘blow away’). To this end a mechanical system may be preferable to natural
ventilation systems; and finally,
4. If all else fails ‘peak lopping’ cooling will be required (‘cool’). This, commonly
known as a MM building, is likely to become the sustainable building of the future
(Holmes and Hacker, 2007).
MM ventilation refers to a hybrid approach to space conditioning that uses a combination of
natural ventilation from operable windows (either manually or automatically controlled), and
mechanical systems that provide air distribution and some form of cooling (Arnold, 1997;
Brager, 2006). Such buildings provide good air quality and thermal comfort using a NV or
‘free-running’ mode whenever the outdoor weather conditions are favourable, but revert to
mechanical systems for HVAC whenever external conditions make the NV option untenable
for occupants (Brager, 2006; Heiselberg, 2006; Holmes and Hacker, 2007; Lomas et al.,
2007). Whilst all MM buildings combine both elements of natural and mechanical systems
for cooling and ventilation, many variants exist (Bordass and Jaunzens, 1998; Brager et al.,
2000; Brager, 2006). In their database of over 150 MM building case studies, the Centre for
the Built Environment (CBE) at University of California, Berkeley, has identified three
distinct design strategies (CBE, 2005; IEA, 2006):
2.1.1.1. Concurrent
The most prevalent design strategy in practice today, concurrent MM operation
utilises air-conditioning and operable windows in the same space and at the same time
(illustrated in Figure 2.1) (Brager et al., 2007). In this case, fresh air is provided throughout
18
the year by operable vents in the building façade. In addition, larger quantities of fresh air can
flow through operable windows during the cooling season to reduce the cooling load on the
mechanical system (Brager, 2006). The HVAC system may serve as supplemental ventilation
and cooling while occupants are free to open windows based on individual preferences
(Rowe, 2004). In warmer climates, concurrent MM systems usually require higher set-points
such that the building is primarily in passive mode most of the time, and mechanical cooling
is only needed to control the peaks. This can be an effective and energy efficient solution if
implemented within a building designed for high thermal stability, having efficient fans, heat
recovery and night cooling (Brager et al., 2000; CBE, 2005).
Figure 2.1: Concurrent mixed-mode operation (CBE, 2005).
2.1.1.2. Change-over
Change-over designs (shown in Figure 2.2) are becoming increasingly common,
where the building ‘switches’ between NV and AC modes on a seasonal, synoptic or even
daily basis (Brager et al., 2000; Brager, 2006). Brager et al. (2007) further define the
operating parameters that dictate which timescale(s) of control are appropriate, such as
climate (from seasonal changes to current conditions), building characteristics (e.g. massing
and orientation), and microclimatic conditions. The building automation system may
determine the mode of operation based on outdoor temperature, an occupancy sensor, a
window (open or closed) sensor, or operator commands (Bordass and Jaunzens, 1998; IEA,
2006). Typical examples include individual offices with operable windows, and when a
certain temperature is exceeded during the day the building switches to mechanical cooling.
19
Such a building requires a control system that can switch automatically between natural and
mechanical modes in such a way that minimises energy consumption (Brager et al., 2007;
Henze et al., 2007) without compromising indoor air quality or occupant thermal comfort
(McCartney and Nicol, 2002).
Figure 2.2: Change-over mixed-mode operation (CBE, 2005).
2.1.1.3. Zoned
This category generally refers to when passive and mechanical strategies occur at the
same time but in different zones within the building. This is usually the case when parts of
the building differ in their requirements for ventilation and heating/cooling, either due to their
occupancy and usage, different internal loads, or to their planning and location, as Figure 2.3
illustrates (Bordass and Jaunzens, 1998; CBE, 2005). This design is quite climate-restrictive
because it assumes that natural ventilation will be able to fully handle portions of the building
throughout the year. This MM option is best suited where buildings have deep floor plates
creating large interior zones, or there are ventilation requirements in parts of the space that
cannot be met by natural ventilation, e.g. labs or kitchen areas (Drake, 2005; Brager et al.,
2007). Such a configuration may also be appropriate where there are other programmatic
differences dictating the use of different strategies, e.g. NV office buildings with operable
windows and a ducted heating/ventilation system providing heating/cooling only to
conference rooms (Brager et al., 2000; CBE, 2005).
20
Figure 2.3: Zoned mixed-mode operation (CBE, 2005).
2.1.2. Making the Business Case for Mixed-Mode
The expansion of large-scale mechanical ventilation and cooling in the 1950s, along
with other technologies such as curtain walls and fluorescent lighting, led to the more
common office building forms of today; typically all-glass, flush-skin buildings with large
floor plates and no operable windows (Brager et al., 2000; Brager, 2006). These enclosed
glass towers were designed to maintain constant, static conditions throughout the interior
(Brager and de Dear, 1998), and in doing so, shifted the locus of indoor environmental
control away from the occupants and towards a facilities manager (Cooper, 1982; Brager et
al., 2004). Many researchers have stated that these buildings miss out on the large number of
documented benefits of operable windows, such as reduced energy consumption (Rowe,
2003; Emmerich and Crum, 2005; Henze et al., 2007), fewer dissatisfied occupants (Leaman
and Bordass, 2007; Brager and Baker, 2009), and fewer sick building syndrome (SBS or
building-related) illness symptoms compared to conventional AC buildings (Mendell, 1993;
Seppanen and Fisk, 2002). In reviewing the current literature, the following sub-sections
elaborate some of the benefits of MM ventilation:
2.1.2.1. Energy
Albeit assessed through numerical simulations rather than physical monitoring, the
potential energy savings from MM buildings have been frequently documented (Daly, 2002;
21
Rowe, 2003; Emmerich and Crum, 2005; Emmerich, 2006). Through the use of building
simulations, Emmerich and Crum (2005) demonstrated that the use of MM ventilation in the
US can contribute to HVAC energy savings ranging from 13% (medium-sized office building
with a variable air volume system in Miami), to 29% (small office building with a constant
air volume system in Atlanta), to 79% (small office building with a constant air volume
system in Los Angeles) (Emmerich, 2006). Similarly in the UK, building simulations
estimated that MM buildings could reduce energy costs by over 35% when compared to allmechanically cooled alternatives (Ogden et al., 2004). A real building study undertaken by
Rowe (2003), later acknowledged in Forwood and Rowe (2006), also examined the potential
for reduced energy consumption in MM offices. Compared with estimated energy
consumption if the same spaces were enclosed and mechanically ventilated with full time airconditioning, Figure 2.4 illustrates that since the hybrid system was activated, annual
measured energy consumption was less than 25% of the simulated annual consumption.
These findings are congruent with a similar study conducted in Indonesia (Karyono, 2000).
Over a 12 month period, energy consumption data was monitored for an AC, NV and hybrid
building (wherein occupants had personal control over individual AC units). The hybrid
building was found to use 80% less energy than the AC building, while at the same time
allowing a slightly greater proportion of workers to be thermally comfortable (Karyono,
2000).
22
Figure 2.4: Actual monthly metered energy consumption used by the supplementary cooling
and heating system in University of Sydney’s Wilkinson building between December 1997
and May 1999 compared with estimates from a simulation model of a conventional AC
system (Rowe, 2003).
2.1.2.2. Occupant Satisfaction
In addition to the energy benefits of using natural ventilation in place of mechanical
cooling, MM buildings have the potential to offer occupants higher degrees of control over
their local thermal and ventilation conditions, and as a result, increase occupant satisfaction
(Rowe, 2003; Hellwig et al., 2006; Brager et al., 2007). In an analysis of CBE web-based
post-occupancy survey responses, Brager and Baker (2009) established that 8 out of 12 MM
buildings (from a CBE database of 358 buildings) ranked in the top quartile in terms of
thermal satisfaction, with two more in the upper third (as shown in Figure 2.5). Rowe (2003)
also observed that occupants in MM spaces rated better levels of thermal comfort and
occupant satisfaction. In their analysis of 177 POE studies within the UK, Leaman and
Bordass (2007) also noted that MM buildings had more satisfied occupants than conventional
AC buildings. Whilst many NV and MM buildings were perceived as hotter in summer and
cooler in winter (Baird et al., 2012), occupants of these buildings were found to be more
23
forgiving of these conditions provided they could exercise control over their own thermal
environment (Leaman and Bordass, 2007). These results were also consistent with the
findings of a study in Australian MM buildings (Leaman et al., 2007).
Figure 2.5: Cumulative frequency distribution for thermal satisfaction in mixed-mode
buildings (n=12) compared to CBE database (n=358). Coloured symbols on the y-axis
represent the median satisfaction score for each building set (Brager and Baker, 2009).
2.1.2.3. Health, Productivity and Indoor Air Quality
Very few accurate studies have been conducted on the effects of hybrid ventilation on
occupant health and productivity. However, many researchers believe that these spaces could
increase worker performance, improve occupant health and potentially reduce problems
associated with indoor air quality (IAQ) (Smith, 2008). Rowe (2003), in combining the
ratings for SBS symptoms (Figure 2.6), showed that the mean prevalence scores for hybrid
and NV settings are all at or below the whole population average. Similarly, Brager and
Baker (2009) noticed that all but two MM buildings in their study fell in the upper quartile of
air quality satisfaction. These results mirror what is already known about thermal comfort and
24
health within NV office buildings. In an extensive cross-sectional analysis, Seppanen and
Fisk (2002) highlight that relative to NV buildings, AC buildings (with or without
humidification) showed 30-200% higher incidences of SBS symptoms. Mendell’s review
(1993) of several large SBS field studies, reiterated these findings with SBS symptoms being
significantly less prevalent in NV buildings.
Rowe (2003) also estimated an 18% improvement in self-assessed productivity in offices
with MM conditioning, as compared to offices with mechanical air-conditioning. While it
seems increased worker productivity in high air temperatures would be counter-intuitive,
many argue that improvements to productivity in NV and MM buildings would be attributed
to higher degrees of occupant control in such temperatures (Leaman, 1995; Leaman and
Bordass, 1999; Boerstra, 2010; Frontczak et al., 2012). Carnegie Mellon University’s
Guidelines for High Performance Buildings (NSF/IUCRC, 2004) assessed the productivity
benefits of NV and MM buildings from eight case studies. These guidelines state that
replacement of supplemental mechanical ventilation with NV or MM conditioning systems
achieved an average reduction in health costs of 1.1% annually ($60 per employee) and that
individual productivity was improved by an average of 8.5% annually ($3900 per employee)
for an average return on investment of at least 120% (NSF/IUCRC, 2004; Brager et al.,
2007).
25
Figure 2.6: Comparison of prevalence scores for sick building syndrome symptoms from 40 office surveys. Population average symbolised by solid
black line (modified from Rowe, 2003; Forwood and Rowe, 2006).
26
2.2. Thermal Comfort in Mixed-Mode Buildings
The ‘adaptive’ thermal comfort model (de Dear and Brager, 1998; Humphreys and
Nicol, 1998; Nicol and Humphreys, 2002) advocates the shift towards variable indoor
thermal environmental conditions in support of sustainable building design. However, despite
an increasing interest in MM buildings, few thermal comfort field studies have been
conducted. Topical debates on whether the adaptive comfort standard should be applied
within buildings with MM spaces (Brager and de Dear, 2000; de Dear, 2004; Lomas et al.,
2007; Turner, 2008), the problems of overheating given future changes in climate (Holmes
and Hacker, 2007; Holmes and Hacker, 2008; Borgeson and Brager, 2011), and the use of
occupant vs. automated control algorithms (Brager et al., 2007; Borgeson and Brager, 2008;
Rijal et al., 2009) present key barriers in the uptake of MM ventilation and areas requiring
further research.
2.2.1. Static vs. Adaptive Thermal Comfort
It has often been assumed that another perceived benefit of MM buildings is enhanced
thermal comfort of its occupants. Despite countless studies documenting the improved
comfort conditions in NV buildings, as opposed to AC buildings, how occupants’ achieve
thermal comfort, or how their comfort is affected, in a building that switches from AC to NV
environments remains a key research question. Therefore, in order to understand how thermal
comfort may be affected by MM ventilation, the concepts of both thermal comfort
models/theories need to be discussed. Thermal comfort is defined as ‘a condition of the mind
which expresses satisfaction with the thermal environment’ (ASHRAE, 2010). Povl Ole
Fanger’s famous climate chamber studies of the 1960s and 1970s pioneered the conventional
theory of thermal comfort, which has shaped international standards for HVAC systems ever
since. In establishing the ideal environmental temperature at which people could maintain
their internal body temperatures based on the human heat balance equation (thermal
27
neutrality), Fanger (1970) produced a ‘comfort’ equation indentifying six factors affecting
thermal comfort: air temperature, radiant temperature, humidity, air speed, clothing insulation
and metabolic rate (Olesen, 1982). Parsons (1993) agrees that the resultant model should be
universally applicable, regardless of building type, climate zone or population, although the
weight of empirical evidence disagrees (Busch, 1992; de Dear and Brager, 1998; Humphreys
and Nicol, 1998).
The comfort equation led Fanger to develop the PMV and PPD indices (Fanger, 1970)
(illustrated in Figure 2.7). The thermal sensation index (PMV) is a standard 7-point
psychophysical rating scale for a large group of persons exposed to a given combination of
thermal environmental factors, ranging from -3 (cold) to +3 (hot) with 0 as ‘neutral’
representing the most comfortable condition (Figure 2.7). The PPD index predicts what
portion of a large group of persons will be uncomfortable with a particular set of
environmental conditions. The relationship between these two indices is shown in Figure 2.7.
Even in an ideal thermal situation, there will be a PPD of 5%, because it is impossible to
satisfy an entire group of people in a single thermal environment (Fanger, 1973). This notion
that one can determine (and maintain) an ideal, or ‘static’, temperature for most people within
a controlled environment forms the basis of modern thermal comfort standards.
28
Figure 2.7: Fanger’s (1970) Predicted Mean Vote and Predicted Percentage Dissatisfied
indices (sourced from Solomon, 2011).
This laboratory-based research, and the standards it subsequently spawned, established
acceptable indoor temperature ranges much narrower than those that have been tolerated by
human populations for millennia (Brager and de Dear, 1998). Furthermore, Nicol and
Humphreys (2002) argue this ‘one-size-fits-all’ approach was unnecessary and unsustainable.
As concern for IEQ and energy conservation grew towards the end of the 20th century, so did
the interest among researchers and practitioners to re-examine the thermal comfort
assumptions embedded in the current standards.
In contrast to the PMV-PPD model, adaptive thermal comfort theory assumes building
occupants play an active role in creating their own thermal preferences (de Dear and Brager,
1998). In other words: “if a change occurs producing discomfort, people, if given the
opportunity, will react in ways which tend to restore their comfort” (Humphreys and Nicol,
29
1998). According to Brager and de Dear (1998), this theory introduced three categories of
adaptation: behavioural (e.g. adjustment of clothing, body movement, opening windows,
adjusting thermostats, using fans, redirecting air, changing blinds), physiological (e.g. body’s
acclimatisation to long term exposure to thermally stressful environments) and psychological
(e.g. complex combinations of contextual factors, past thermal experiences and expectations).
Both de Dear (1994) and Humphreys (1995) argue that this adaptive, people-centred way of
regarding thermal comfort suggests it would be advantageous to reformulate temperature
standards for buildings to reflect the empirical relation between climate and thermal comfort,
and make due allowance for human adaptability.
Building on the work of such predecessors as Humphreys (1978) and Auliciems (1981), de
Dear and Brager (1998) studied standardised comfort survey data from over 160 office
buildings in countries spanning four continents across a variety of climate zones, including
Australia, Greece, Indonesia, North America, Pakistan, Thailand, and the UK. Buildings were
categorised into those with centrally controlled HVAC systems, in which occupants have
little to no control over their immediate thermal environment; and those that were NV with
occupant-controlled operable windows and no mechanical air-conditioning.
de Dear and Brager (1998) explain two dominant patterns emerging from their data analysis
(Figures 2.8a and 2.8b show the separate analyses for HVAC and NV buildings respectively).
The observed responses (Y variable) represent each building’s resultant ‘comfort
temperature’; calculated as the average indoor temperature within the building at which most
occupants felt comfortable, i.e. thermal sensation was zero or ‘neutral’. Firstly, the steeper
gradient, i.e. greater climate sensitivity of observed responses (‘comfort temperatures’) in NV
buildings (Figure 2.8b) compared to HVAC buildings (Figure 2.8a) suggests occupants of the
latter (HVAC buildings) become more finely attuned to the narrow, constant conditions
30
typically provided by mechanical conditioning. In contrast, occupants of NV buildings prefer
a wider range of conditions that more closely reflect outdoor climate patterns. Secondly, a
comparison of the observed (labelled as OBS) and predicted (labelled as PMV) lines within
each graph, clarifies the role of adaptation in these two building types (de Dear and Brager,
2002). In HVAC buildings, PMV was remarkably successful at predicting comfort
temperatures, demonstrating that behavioural adjustments of clothing insulation and room air
speed (both inputs to the PMV model) fully explained that relationship between indoor
comfort temperature and outdoor climatic variations. In contrast, within NV buildings (Figure
2.8b), the difference between these PMV-based predictions and the adaptive model shows
that such behavioural adjustment accounted for only half of the climatic dependence of
comfort temperature. Upon further analysis, de Dear and Brager (1998) posit that indoor
comfort temperatures within NV buildings are strongly influenced by shifting thermal
expectations resulting from a combination of higher levels of perceived control, and a greater
diversity of thermal experiences and expectation in such buildings, which are not among the
six input parameters to Fanger’s PMV-PPD model.
The work of de Dear and Brager (1998) firmly established that building occupants’
adaptations to the broader outdoor climatic setting have a profound effect on their
expectations of indoor climates (Fountain et al., 1996). It appears that thermal comfort is not
only a function of standard variables recognised by the conventional theory (PMV-PPD), but
is also affected by psychological variables ranging from people’s expectations (due to outside
conditions or cultural norms) to how much control they have over their immediate
workspaces (by being able to open windows, adjust blinds, or even move to a different
location). These adaptations, when acknowledged and understood by designers and
engineers, can bring about major energy reductions in buildings (de Dear and Brager, 2002).
31
Figure 2.8: Observed (OBS) and predicted (PMV) indoor comfort temperatures from RP-884
database for (a) HVAC buildings and (b) NV buildings (de Dear and Brager, 2002).
2.2.2. International Comfort Standards
Existing international comfort standards, such as ASHRAE’s Standard 55 ‘Thermal
environmental conditions for human occupancy’ (ASHRAE, 2010), the Comite Europeen de
32
Normalisation (CEN) Standard EN15251 ‘Indoor environmental input parameters for design
and assessment of energy performance of buildings: addressing indoor air quality, thermal
environment, lighting and acoustics’ (CEN, 2007) and the International Organization for
Standardization (ISO) Standard 7730 ‘Moderate thermal environments – calculation of the
PMV and PPD thermal comfort indices’ (ISO, 2005) specify combinations of temperature
and humidity, indoor environments and personal factors that will be deemed acceptable to
80% or more of the occupants. Following the international standardisation of Fanger’s (1970)
PMV-PPD model of thermal comfort, subsequent comfort research has been polarised into
the two fundamentally different approaches between the heat-balance and adaptive models.
As Brager and de Dear (1998) explain, the former accounts for thermal comfort in terms of
the microclimate immediately affecting the energy exchanges, i.e. heat balance of the subject,
whereas adaptive models predict comfort from broad-scale, contextual factors. One context
where these latter factors play a particularly important role is NV buildings (de Dear and
Brager, 2002).
Dating back to the 1960s, earlier versions of these standards mainly cover thermal comfort
under steady-state conditions based on laboratory experiments, such as the PMV-PPD model
(Fanger, 1970), which is still featured prominently in the most current version of ASHRAE
Standard 55 (ASHRAE, 2010). However, more recent revisions have utilised global field
study databases, e.g. ASHRAE RP-884 (de Dear, 1998) and Smart Controls and Thermal
Comfort (SCATs) (Nicol and Humphreys, 2010). This plethora of field data highlighted the
inadequacy of ‘static’ models, like PMV-PPD, for describing thermal comfort in ‘freerunning’ buildings (Busch, 1992; de Dear and Brager, 1998; Nicol and Humphreys, 2010).
These findings led to the inclusion of an adaptive comfort standard (ACS) (shown in Figure
2.9) in the 2004 edition of ASHRAE’s Standard 55 (ASHRAE, 2004) to serve as an
33
alternative to the PMV-based method for NV or ‘free-running’ buildings, i.e. buildings with
no mechanical heating or cooling (de Dear and Brager, 2002; Lomas et al., 2008; Turner,
2008; Nicol and Humphreys, 2010). However, at the time of ASHRAE 55-2004 going to
press, insufficient comfort studies undertaken in MM buildings meant they were excluded
from the scope of the ACS (de Dear and Brager, 2002).
Figure 2.9: The ASHRAE Standard 55-2010 adaptive comfort standard for NV buildings
(ASHRAE, 2010).
Despite the most recent revisions to the standard (ASHRAE, 2010), the ACS is still
constrained in scope to naturally conditioned, occupant-controlled spaces in which thermal
comfort conditions are primarily regulated by operable windows. Furthermore, ASHRAE
clarifies that when mechanical cooling systems are provided for the space, as is the case for
MM buildings, the ACS is not applicable (Nicol and Humphreys, 2002; de Dear, 2004;
Turner, 2008; Nicol and Humphreys, 2010). Thus, the potential flexibility offered by the
standard is not available to hybrid buildings, which may operate in a passive, natural
ventilation mode preferentially, equipped with only supplemental cooling/heating for peak
periods; or to spaces where operable elements are not connected to the outdoors. As a result,
such spaces or buildings fall within the scope of the more restrictive PMV-PPD method
34
(Baker and Standeven, 1996; de Dear and Brager, 2002; Nicol and Humphreys, 2002; Turner,
2008). This begs the question as to why MM buildings are precluded from applying the ACS
in their NV mode of operation.
The inclusion of the ACS in ASHRAE 55-2004 was significant in mainstreaming NV
buildings (van der Linden et al., 2006). In the years following the publication of ASHRAE’s
adaptive comfort model, a European counterpart named SCATs (McCartney and Nicol, 2002;
Nicol and Humphreys, 2002; Nicol and Humphreys, 2010) replicated the exercise in a
longitudinal design in which 26 offices located in European countries, e.g. France, Greece,
Portugal, Sweden and the UK, were surveyed over approximately one year. Originally
intended to develop a European adaptive comfort algorithm, the SCATs project was later
used in the development of the adaptive comfort annex in the European standard EN15251
(McCartney and Nicol, 2002; CEN, 2007; Nicol and Humphreys, 2010). Unlike its American
counterpart, EN15251 allows the more flexible ACS to be applied to NV buildings which can
include MM buildings during times when they are not employing mechanical cooling, i.e.
whilst in NV or ‘free-running’ mode. Currently, the International Standard ISO 7730 (ISO,
2005) has resisted the ‘adaptive trend’ altogether and makes no allowance for differences in
NV and mechanically cooled or ‘AC’ buildings.
2.2.3. Thermal Comfort in Mixed-Mode Buildings: What Do We Know So Far?
At the beginning of the 21st century, some preliminary research interest had been
focussed upon the use of natural and hybrid ventilation solutions for low-energy comfort
cooling. Under the auspices of the International Energy Agency’s (IEAs) Implementing
Agreement on Energy Conservation in Buildings and Community Systems, sixteen IEA
countries participated from 1998 to 2002 in Annex 35: a research collaborative on Hybrid
Ventilation in New and Retrofitted Office Buildings (HYBVENT) (IEA, 2006). The objective
35
of this project was to not only understand the purpose and use of hybrid ventilation systems,
but to develop suitable control strategies and analysis methods for hybrid buildings. Pilot
studies from countries such as Australia, Germany, Japan, Norway, the UK and the USA,
helped HYBVENT designate a working definition of hybrid ventilation: systems that provide
a comfortable internal environment using both natural ventilation and mechanical systems,
but using different features of these systems at different times of the day or season of the year
(i.e. mixed-mode) (Heiselberg, 2002). Underlying this definition were two chief concepts:
firstly, the recognition that under suitable conditions, natural ventilation may be satisfactory,
even preferable, for thermal comfort and IAQ, implying a potential decrease in the
environmental impact of building operations; and secondly, the acknowledgement that
supplementary mechanical systems, for fresh air distribution as well as climate control, may
well be required during the harshest of conditions (Heiselberg, 2006).
The analysis of the ASHRAE RP-884 database in de Dear and Brager (1998) indicates that
indoor temperatures falling outside ASHRAE’s Standard 55-1992 comfort zones may, in fact,
be quite acceptable, if not preferable, in NV or MM buildings (de Dear, 2004; Hellwig et al.,
2006). While very few field studies have been conducted in MM buildings, those that have
been done seem to agree with this statement. Findings from Karyono (2000) demonstrate that
thermal comfort in a hybrid building can be as good as, if not better than, that of an AC or
NV building. Over a 12 month monitoring period, the hybrid building allowed a greater
proportion of occupants, i.e. 90%, to be thermally comfortable, which was higher than that
measured in the AC and NV buildings (Karyono, 2000). From their analysis of neutral
temperatures for buildings during free-running (or NV) mode, Humphreys et al. (2010)
suggested no discomfort if the temperatures in a MM building were allowed to drift
seasonally in NV mode according to the prevailing outdoor temperature, with cooling
supplied over 28°C and heating below 18°C. However, they reiterate that these limits are
36
likely to vary depending on culture and climate (Nicol and Wilson, 2011). In principle, it is
possible to design and operate buildings that provide comfort in the free-running mode at
least within a range of prevailing mean outdoor temperatures from 10-30°C (Humphreys et
al., 2010).
Similarly, Frank et al. (2007) found that the measurement of thermal comfort parameters
within a MM building in Switzerland met the criteria for EN15251’s category I band (PMV ±
0.2) for 86% of occupied hours. Despite the onset of a heatwave during the study period for
17 consecutive days, operative temperatures were still in the category I comfort range,
reaching the upper limit of 26°C towards the end of the heat wave period. During the
daytime, relative humidity was between 40-60% and between 60-80% during night-time due
to temperature drops caused by the night cross-ventilation. From the few studies mentioned
above, it is apparent that thermal comfort conditions can be provided by a low-energy
building, including MM ventilation, provided the building has been correctly designed for the
climate (Cron et al., 2002; Rowe, 2003; Fato et al., 2004). Furthermore, for buildings
designed in accordance with acceptable temperature bands for NV mode, e.g. between 1828°C, such thresholds would need to be adaptive and shift with future increases in outdoor
temperatures, along with occupant adaptation to the indoor thermal environment.
2.2.4. Overheating
While not directly relevant to this thesis, the issue of overheating in MM buildings
presents major concerns given the likely increase in outdoor temperatures in the near future,
and as such, should be discussed. Low-energy designs, in particular natural ventilation, by
definition, tend to be more sensitive to changes in external climate conditions. Thus building
engineers and designers express concern as to how such buildings will perform throughout
their lifetime under extreme climatic conditions, and in turn, how this will impact occupant
37
comfort, e.g. the risks of overheating (CIBSE, 2005). When designing or assessing the
performance of these buildings, it is important to have criteria by which overheating may be
judged to have occurred. In order to address these issues, generated climatic data must be
representative of the future, which, for all the intents and purposes of sustainable design,
should also take into account climatic change (Holmes and Hacker, 2007). By using
computer models of the global climate system based on different GHG emission scenarios,
CIBSE (2005) presents several energy performance simulations in the UK for various
different low-energy building designs, such as natural ventilation and MM cooling.
The underlying concept of low-energy design requires that internal heat gains in summer are
minimised (Holmes and Hacker, 2007). Studies modelling different building types,
comparing different control strategies to estimate the performance of MM ventilation systems
for different climates (e.g. Cron et al., 2003; CIBSE, 2005; Holmes and Hacker, 2007; Coley
and Kershaw, 2010; de Wilde and Tian, 2010; Roetzel et al., 2010) have highlighted an
emerging focal point of many debates surrounding MM buildings, i.e. what is likely to
happen to internal temperatures when outside temperatures continue to rise? Performance
predictions for a MM office building (Figure 2.10) were based upon the number of ‘summer’
hours above the acceptable temperature predicted by the CIBSE adaptive method (CIBSE,
2005; Holmes and Hacker, 2007). The simulations were carried out with peak lopping
cooling added to ensure peak temperatures do not exceed 28°C for more than 1% (or 20
occupied hours) in any one year. Clearly visible in Figure 2.10 is the increased number of
days during which internal temperatures rise above the acceptable upper limit of NV mode
(28°C). Under all scenarios, the frequency of overheating, i.e. hours above 28°C, are set to
increase by 20% in each time slice. While additional low-energy cooling options can reduce
these occurrences by 20-85% (Figure 2.10), Holmes and Hacker (2007) conclude, as
38
reiterated by de Wilde and Tian (2009), that the risk of overheating still presents a concern by
the middle of the century.
Figure 2.10: Performance projections for a mixed-mode office under the effects of future
climate change (Holmes and Hacker, 2007).
Experts relate the risks of overheating to people’s adaptive capabilities, assuming office
occupants will need to adapt to changes in the climate over the next 40-50 years. Adaptive
comfort theory (de Dear and Brager, 1998; Nicol and Humphreys, 2002) predicts that
building occupants should gradually adapt to the temperatures that happen to occur in NV
buildings in future climates. Many studies found that for buildings without mechanical
cooling or heating, people can maintain thermal neutrality over a large interval of indoor
temperatures (e.g. de Dear and Brager, 1998; de Dear and Brager, 2002; Nicol and
Humphreys, 2002). This relationship explains that as the environmental conditions change,
the occupants will, if possible, adapt to such changes. Occupants in MM buildings are likely
to experience some degree of psychological adaptation, such as habituation and altering one’s
perceptions of, or responses to, the thermal environment through thermal experiences and
expectations. Physical adaptations can occur through changes to posture, clothing and activity
level, and possibly by adjustment of, if applicable, shading devices, operable windows, etc.
Physiological adaptation, such as acclimatisation, may also occur as people become more
39
attuned to the greater range of internal temperatures experienced throughout the building’s
lifetime (Brager and de Dear, 1998). As mentioned previously, the overheating threshold in
MM buildings should also be responsive to changes in the prevailing outdoor conditions, i.e.
adapt to changes in future climates (Nicol and Wilson, 2011).
In terms of overheating, and the subsequent risks of occupant heat stress, very few written
sources offer guidance for MM buildings (CIBSE, 2000; Heiselberg, 2002; CIBSE, 2005).
Despite the need, the current ASHRAE Standard 55-2010 offers little advice on comfort in
MM buildings. The European standard EN15251-2007, on the other hand, has recently
provided some exceedance calculations and recommendations on acceptance in its Annexes F
and G (CEN, 2007). While these may not be definitive methods (Nicol and Wilson, 2011),
Annex F on the ‘Long term evaluation of the general thermal comfort conditions’ describes
the following three exceedance metrics:
Percentage outside the range: The percentage of occupied hours when the PMV of
the operative temperature is outside a specified range.
Degree-hours criteria: The time during which the actual operative temperature
exceeds the specified comfort range during occupied hours, weighted by a factor
based on the number of degrees beyond the range.
PPD weighted criteria: The accumulated time outside the range, weighted by PPD.
Olesen (2007) explains that since the criteria are based on instantaneous values, values
outside the recommended range should be acceptable for short periods during a day.
EN15251 therefore recommends an arbitrary rule of thumb for acceptable ‘length of
deviation’ exceedance values in buildings; 3-5% of occupied time (occupied working hours)
(Olesen, 2007). Although the standard has broken new ground with the inclusion of
exceedance criteria, it is unclear whether or how the 3-5% of occupied working hours rule
40
should be applied to the weighted calculations (Borgeson and Brager, 2011). Based on this
knowledge and a selection of previous work modelling MM and radiant systems, Borgeson
and Brager (2011) developed their own exceedance criteria, i.e. the percentage of occupied
hours where conditions exceed the 20% dissatisfied threshold, weighted by the time varying
occupancy and expressed in percentage of occupied working hours. EnergyPlus models were
used to simulate a range of parametric studies to investigate the potential tradeoffs between
comfort and energy use in the context of varying climate conditions combined with a range of
passive performance attributes and internal gains.
Figure 2.11 depicts the percentage exceedance and cooling energy intensity metrics for NV,
MM and mechanical ventilation (labelled as VAV) cooling strategies across six climate zones
in California (from coastal Mediterranean climates in the north, to moderately sub-tropical
climates along the southern coast, and more continental and semi-arid climates inland). Apart
from demonstrating the reduced energy consumption of MM ventilation compared to
mechanical ventilation, Figure 2.11 illustrates the sensitivity of the comfort results to both the
conditioning strategy and comfort model being applied in the MM scenario. The NV option
alone was sufficient for maintaining comfort exceedance near or below 5% in the milder
climates (3 of the 6 representative climate zones) suggesting some form of supplemental
cooling would be required for the other climates. Assuming the ASHRAE Standard 55 ACS
applies, the analysis shows that the MM strategy would imply acceptable comfort conditions
(less than 5% exceedance) in all six climate zones (Borgeson and Brager, 2011). However,
using the PPD metric, MM buildings could only bring exceedance below 5% in two of the six
climate zones. Borgeson and Brager (2011) highlight that the choice of comfort metric used
in a MM building significantly changes the level of exceedance in this scenario. Furthermore,
these findings reveal that even under the most extreme climate zone, the sealed building with
41
a mechanical ventilation system had difficulty maintaining comfort levels within acceptable
exceedance limits, which would require significant amounts of energy.
Figure 2.11: Simulation results displaying the trade-offs between (a) comfort and (b) energy
consumption for naturally-ventilated (NV), mixed-mode (MM) and mechanical ventilation
(labelled as VAV) cooling strategies. For the mixed-mode case, comfort exceedance
predictions are bracketed using both the ASHRAE 55 adaptive model (base bar) and the PPD
model (line extension) (Borgeson and Brager, 2011).
Figure 2.12 summarises the effect of climate on this sensitivity, comparing predicted
exceedance from applying the ASHRAE 55 adaptive comfort model vs. PPD for the MM
case with baseline gains in every climate zone in California. The magnitude of the gap
between the two metrics is significant in most climates. In using adaptive comfort standards,
exceedance is less than 5% (as recommended in Annex G of EN15251) in 14 climate zones.
PPD, however, predicts exceedance below this 5% threshold in only four. This analysis
underscores the need to better understand how comfort models apply to MM buildings. All
too often the choice of the model will make the difference between whether one predicts
thermal success or failure.
42
Figure 2.12: Exceedance predictions in the mixed-mode scenario with baseline gains using
the ASHRAE 55 adaptive comfort model and the PPD model across all 16 climate zones in
California (Borgeson and Brager, 2011).
Borgeson and Brager (2011) conclude that their study correlated well with received wisdom
and observed success of NV and MM buildings in California, especially in terms of climate
sensitivity. Temperate coastal climates allowed MM configurations to deliver low
exceedance values, and warmer climates were predicted to have higher exceedance values.
The study confirms that predicting comfort using exceedance metrics is highly sensitive to
variations in shell quality, internal gains, insulation, but also which comfort model is used to
set the exceedance threshold. Furthermore, it is clear from the diversity of definitions in
circulation that there is no consensus on how to best define or apply exceedance metrics,
especially on whether such thresholds should be ‘static’ or ‘adaptive’.
2.2.5. Personal vs. Automated Control
The success of any NV or MM building design is also greatly dependent on the extent
to which it accommodates occupant behaviour (Nicol and Humphreys, 2004). To date, no
standard protocols exist for control strategies in MM buildings, nor is there consensus about
43
the optimum ratio between degrees of personal vs. automated controls. As Brager (2006)
clarifies, the ultimate objective is to optimise both comfort and energy efficiency. Whilst
numerous control algorithms for hybrid ventilation buildings have been proposed in recent
years (CIBSE, 2000; IEA, 2006; Brager et al., 2007), they typically consist of a discomfort
threshold temperature at which the transition from natural to mechanical mode is ‘triggered’
(Arnold, 1997; McCartney and Nicol, 2002; CIBSE, 2005).
What is often overlooked in this ‘trigger temperature’ approach of MM switch-over is the
fundamental concept of the adaptive thermal comfort model; that the discomfort threshold is
not a constant, but rather a function of recent outdoor weather and seasonal temperature
trends (Zhang and Barrett, 2012). In other words, people are tolerant of warmer indoor
temperatures after a spell of hot weather and cooler indoor temperatures are more acceptable
in cold weather (Brager and de Dear, 1998; de Dear and Brager, 2002). However, there are
issues regarding whether windows and vents are automated, or the establishment of
thermostat set-points that determine when mechanical heating/cooling will turn on, or
whether there are override controls for the HVAC system (Borgeson and Brager, 2008; Rijal
et al., 2009; Ackerly et al., 2011).
2.2.5.1. Personal Control
Adaptive comfort theory posits that greater personal control allows occupants to finetune their thermal environment to match their own personal preferences; creating a wider
acceptable range of temperatures in the building (de Dear and Brager, 1998; Humphreys and
Nicol, 1998; Brager et al., 2004). A typical approach to adaptive comfort is to use simpler,
manual controls that depend on educating occupants to operate the building efficiently and in
response to their own comfort needs (Karjalainen and Koistinen, 2007). Eschewing
automation is unlikely to optimise energy performance, however, it is more than likely to
44
create much higher levels of occupant satisfaction within the building (Bordass et al., 1993;
Leaman and Bordass, 2007; Brager and Baker, 2009). Additionally, Leaman and Bordass
(1999) have observed that occupants are more forgiving of discomfort if they have access to
effective remediation strategies. Extending from his research on adaptive comfort, de Dear
(2004) notes that people who know they do not have control over their air-conditioning
temperature at work have the expectation that their thermal comfort will be automatically
achieved at a constant level. On the other hand, occupants of NV buildings know that the
indoor climate will be more variable and that they need to be more actively engaged in
making their indoor environment pleasant (Leaman and Bordass, 1999; de Dear, 2004).
Occupants of a NV office building who had more control over the environmental conditions
of their workspace had a higher neutral temperature (warmer by a statistically significant
1.5°C over summer) than those with little or no control (Brager et al., 2004). Given the two
groups were broadly exposed to the same average thermal conditions, with similar clothing
insulation and metabolic rates, the group with more control shifted their neutrality closer to
their average thermal exposure. This finding confirms the hypothesis that subjects with
greater access to control are more tolerant of, and in fact may prefer conditions that deviate
from the centre of the comfort zone. The corollary of this is that people who have limited or
no control over their office environment, as witnessed in countless thermal comfort studies in
AC offices, tend to be less tolerant of sub-optimal thermal environmental conditions (Brager
et al., 2004; Leaman and Bordass, 2007).
Building users place great emphasis upon the ability to manually control their indoor
environment (Rowe, 2003; Rijal et al., 2009), especially during uncomfortable situations
(Leaman and Bordass, 2001). The control of windows is often regarded as the most preferred
adaptive opportunity (Baker and Standeven, 1996; Barlow and Fiala, 2007; Zhang and
45
Barrett, 2012). Studies in the UK reveal occupants tend to use their controls, such as
windows, more often if they perceive to have greater degrees of control are available to them
(Rijal et al., 2007; Yun et al., 2008; Rijal et al., 2012). A study in Finland showed that most
occupants changed their clothing (dress less/more) in response to thermal discomfort, but
using their window was quite popular (Karjalainen and Koistinen, 2007).
Rijal et al. (2009) found that in summer people opened their windows to decrease the indoor
air temperature and to increase the air movement. The time taken for the cool external air to
mix with the warm indoor air and cool it enough for comfort to occur was also found to
influence how long occupants left their windows open. Occupants tended to leave windows
open until they felt cold, corresponding with a drop of approximately 4°C in indoor air
temperature (Rijal et al., 2007). However, studies argue the interaction of occupants with
adaptive controls is more related to the external rather than the internal environment (e.g.
Raja et al., 2001; Haldi and Robinson, 2008; Herkel et al., 2008; Rijal et al., 2012). Based on
a study in the UK, Raja et al. (2001) showed that very few windows were opened during the
cooler Autumn and Winter months when external temperatures were below 15°C. In contrast,
when the outdoor temperature was above 25°C (from Spring to Summer), almost all windows
were open.
Research into the effects of personal control over environmental conditions suggests that
productivity and health improve when people have more control (e.g. Bordass et al., 1993;
Leaman and Bordass, 2001; Leaman and Bordass, 2007; Brager and Baker, 2009; Brown et
al., 2010; Steemers and Manchanda, 2010). Nevertheless, results from a study in Finland
suggests even when controls are made available in offices, occupants often do not know how
to operate the them, or the controls are not readily accessible, or the occupants feel the
heating/cooling system does not respond quickly enough (Karjalainen and Koistinen, 2007).
46
Based on a field study in MM buildings in the US, Figure 2.13 reiterates the main causes for
dissatisfaction with the indoor environment are related to lack of control (Brager and Baker,
2009). Guidance on MM controls (CIBSE, 2000; Bordass et al., 2007) specify that occupants
must be aware of the building control concepts as a pre-requisite to their effective operation.
CIBSE (2000) goes on to state that making control systems legible might mean adopting a
‘standard’ control solution unless there are over-riding benefits in adopting an innovative
approach. More recently, Brown and Cole (2009) commented that contemporary green
buildings seldom communicate how building systems function, and that occupants become
passive when they lack knowledge and positive feedback on the use of environmental
controls (Brown and Cole, 2009; Brown et al., 2009).
Figure 2.13: Reasons for thermal dissatisfaction in mixed-mode buildings in the US (Brager
and Baker, 2009).
The manual natural ventilation control referred to in CIBSE (2005) assumes that occupants
would begin to open windows when space temperatures reached a threshold (22°C) and then
continually open windows further, becoming fully open by a temperature limit (28°C). This
solution, however, can be problematic if the occupants have not been pre-exposed to the
thermally demanding conditions occurring within NV buildings. Within the context of MM
buildings in Sydney, Rowe (2003) deduced that a majority of occupants surveyed (n = 1550)
47
applied passive control methods preferentially; the supplementary mechanical system was left
in the off mode until passive means of control were exhausted. However, it is still uncertain
whether occupants generally prefer narrow temperature ranges, e.g. 22-25°C, and
systematically opt for mechanical cooling, while others readily welcome the wider
temperature swings of NV environments (Rowe, 2003; Bourgeois, 2005).
2.2.5.2. Automated Control
Drawing on the fundamentals of ergonomic design, Fanger (1970) contends that the
machine (building) should be adapted to the human, and not vice versa - that buildings can be
adjusted to serve people: buildings are merely the servant and occupants the master. Fanger’s
ergonomic principle does not facilitate energy conservation. The adaptive model, on the other
hand, relies on the principle that occupants can adapt to the building (de Dear and Brager,
1998; Nicol and Humphreys, 2002). The sophisticated integration of HVAC and building
fenestration systems, window sensors, actuators, and control algorithms that respond to
indoor and outdoor climatic conditions, can be employed to optimise both energy and
comfort (Brager, 2006; Brager et al., 2007). These highly engineered solutions make building
behaviour more predictable and are well suited to energy optimisation (Heiselberg, 1999).
However, as one moves towards a fully automated central control system, there is the
concomitant loss of adaptive opportunities (Brager et al., 2000; Ackerly et al., 2011).
Typical automatic control strategies assume that ventilation openings have mechanical
dampers to control ventilation areas (window openings) using a central building management
system (CIBSE, 2005; IEA, 2006). However, it is difficult to find an acceptable window
automation strategy that satisfies all occupants. CIBSE (2005) describes a typical algorithm
for automatic natural ventilation controls:
48
-
IF space is occupied AND air temperature is between 18-22.5°C, THEN modulate
the ventilation area to obtain a specified minimum ventilation rate
-
IF space air temperature is greater than 22.5°C AND lower than outside
temperature, THEN maintain the ventilation controls above
-
IF space air temperature is greater than 22.5°C AND higher than outside air
temperature, THEN fully open the dampers to maximise ventilation
-
IF a space is unoccupied and air temperature is less than 18°C, THEN start to
close vents. This prevents overcooling of the space during night cooling.
The research literature identifies window automation as best suited in multi-occupant openplan offices or meeting rooms, and outside occupied hours during night-purge cycles (Brager,
2006; IEA, 2006; Brager et al., 2007). In contrast, if windows are operated automatically
during occupied hours, and external temperatures are lower than internal temperatures, there
is a heightened risk of user dissatisfaction due to the sensation of draught (Heiselberg, 2006).
Therefore, it is important that occupants have the opportunity to override the control for
openings in the vicinity of their workstation (Borgeson and Brager, 2008). Automatic solar
shading control may also prove beneficial as it ensures action as soon as indoor temperatures
begin to increase (Johansson, 2009). But still, there are no current standards in relation to
how much or how little automated control is appropriate for MM buildings (El Mankibi and
Michel, 2009).
Buildings today are still mostly constructed with centralised mechanical and electrical
control, typically designed for the range and not the mean (Bordass, 1990). Air-conditioning
set points are usually viewed as universal settings rather than adjusted to the building or its
users (Fountain et al., 1996; Brager and de Dear, 1998). Research into the adaptive comfort
model would encourage management with central control to have a greater connection with
49
the users so they had more local control. This, in turn, would enhance occupant satisfaction
and productivity (Leaman and Bordass, 1993). Leaman and Bordass (1999) suggest the
absence of effective control adjustments to the indoor climate of a building, especially in
generic space planned offices, makes the difference between acceptable comfort and
dissatisfaction. In addition, Bordass (1990) advises the need for more appropriate, not
necessarily more advanced, technology. Buildings with complex energy management systems
don’t run themselves: they need considerable effort at the design stage to make them userfriendly, care during installation and at handover, careful training, and constant vigilance
during operation (Ackerly et al., 2011). After all, they are a management tool and not a fitand-forget item (Bordass et al., 1993).
Appropriate measurement and control of significant indoor environment factors are crucial if
technical installations in buildings are to meet the requirements for a healthy, comfortable
and productive indoor environment (Clements-Croome, 2008; Toftum, 2010). Inexpensive
sensors can be widely distributed in IEQ intelligence networks, allowing HVAC control
systems to monitor and respond to very detailed input. This development may also promote
new strategies and algorithms for HVAC component control (Toftum, 2010). To better
accommodate occupants’ needs and give greater satisfaction, such algorithms should provide
a rapid response to the indoor environment (Bordass et al., 1993; Bordass et al., 2007). As
sensor and control technology advances and becomes more complex, the user’s control
opportunities may decrease accordingly. Leaman and Bordass (2001) conclude that it is a
mistake to allow automation to remove occupants completely from the control loop.
Even if we accept the adaptive principle that occupants should have the maximum possibility
of controlling their own environment, automatic control is still required to support the users
in achieving a comfortable indoor climate and to take over during non-occupied hours. In
50
rooms for several people (e.g. open-plan offices) and in rooms occupied by different people
(e.g. meeting rooms), a higher degree of automation is appropriate (Brager et al., 2000). It is
also very important to carefully consider how user interaction is integrated within the control
system, both with regard to the type of functions that can be overruled and how and when the
automatic control regains control after being overruled by the occupant (Brager et al., 2007).
For systems with presence detection, the automatic control system usually takes over when
the occupants leave the room (Mahdavi and Kumar, 1996). For other systems, it can take over
after the normal occupant period has ended or after a certain time period, which can be
adjusted as a part of the commissioning of the hybrid ventilation system (CIBSE, 2000;
Aggerholm, 2002). The Post-occupancy Review of Buildings and their Engineering (PROBE)
studies in the UK (Leaman and Bordass, 2001) highlight both the success and failure of
combining automatic and manual control solutions within MM buildings. Findings suggest
that buildings with more automated and complex natural ventilation control solutions require
tighter management to ensure performance. However, they cite the following common
shortcomings of automated window controls (Cohen et al., 1998):
Draughts from windows opened to remove heat on sunny but cool days
The inability to close windows which were letting in fumes, noise or insects
The denial to occupants of the opportunity to trade off different types of discomfort
(noise versus overheating).
2.3. Post-Occupancy Evaluation
Buildings are primarily designed and built for their intended occupants, but in many
cases this is done without much consideration of the building’s end-users’ needs or
preferences (Vischer, 2001; Way and Bordass, 2005). As a result, many occupants do not
understand how to operate their building which can often lead to high levels of discontent
(Leaman and Bordass, 2007). As building managers and designers continually strive to
51
improve occupant satisfaction and productivity by ensuring comfortable and healthy working
conditions, POE represents a systematic quality assurance process towards these ends.
POE is a global and rather general term for a variety of types of field studies in built
environments based on assessing the responses, behaviour and perceptions of a building’s
occupants. In the past, POEs have been viewed as a means to measure the performance of a
building from the occupant’s perspective in a systematic and rigorous manner after they were
built and occupied for some time (Preiser et al., 1988; Preiser, 2001a; BCO, 2007). Used
extensively worldwide, POE studies aim to investigate whether buildings are performing as
intended/designed. In effect, they provide ‘feedback’ to the architects and building managers
on potential areas for improvement (Vischer, 2004; Bordass and Leaman, 2005b). They are
often targeted towards the users’ perception of the building rather than actual building
performance metrics, such as energy consumption, temperature and humidity, lighting, noise,
etc (Zimring and Reizenstein, 1980; Hartkopf et al., 1986; Preiser, 1995; Derbyshire, 2001;
Nicol and Roaf, 2005).
2.3.1. Post-Occupancy Evaluation: An Evolutionary Background
Before we can effectively critique POE methods it is instructive to review the context
in which they were originally developed. Up until the 1950s, systematic information on
building performance from the occupants’ perspective was not easily accessible. Following
the rapid expansion of architectural projects in the UK in the 1960s, the Royal Institute of
British Architects (RIBA, 1962) identified the need to gather and disseminate information
and experience on the requirements of building users. The RIBA called for the study of
buildings in use, from both the technical and cost points of view, as well as in terms of design
(RIBA, 1962; Cooper, 2001; Derbyshire, 2001). The RIBA’s Handbook of Architectural
Practice and Management (RIBA, 1965) was instrumental in defining the sequence of stages
52
related to building construction, including briefing/programming, design, specification,
tendering, completion and use (Cooper, 2001; Preiser and Vischer, 2005; Preiser and Nasar,
2008). This report also incorporated a final stage to the building life-cycle called ‘feedback’.
Within this stage, architects were advised to inspect their completed buildings after they had
been built as a means of improving service for future clients (Preiser, 2001b; Bordass and
Leaman, 2005a). Thus, the concept of ‘POE’ was born from this need to provide feedback to
building managers on the performance of their building after completion (Derbyshire, 2001;
BCO, 2007). Despite RIBA’s best efforts, POE was largely ignored by the design and
construction industry in the UK because of its potential to deliver evidence to clients about
under-performance or just plain building design (Cooper, 2001; Hadjri and Crozier, 2009).
Following the large number of housing studies in the 1970s and 1980s in the USA, POE has
steadily gained credibility as a mechanism of scientific inquiry for user satisfaction within
buildings (Preiser, 1995; Vischer, 2001; Bordass and Leaman, 2005a). However, it wasn’t
until the 1990s that the UK construction industry realised the true potential and value of POE
as a significant development in architectural research (Cooper, 2001).
Over the past 30 years, numerous adaptations and improvements have been made to POE
methods (Preiser and Vischer, 2005). The term POE was originally intended to reflect that
assessment taking place after the client had taken occupancy of a building (Preiser, 2001a;
Zimring and Rosenheck, 2001). Early descriptions focused on POE as a stand-alone practice
aimed at understanding a building from the users’ perspective (Preiser, 2001a; Bordass and
Leaman, 2005a; Preiser and Vischer, 2005), and often included aspects of architectural
design, technical performance, indoor climate, occupant satisfaction and environmental
impact (Zimring and Reizenstein, 1980; Hartkopf et al., 1985; Vischer and Fischer, 2005;
Loftness et al., 2006; Gonchar, 2008). POEs are generally classified into three main types, as
identified in Preiser et al., (1988): (1) Indicative POEs involve walk-through observations as
53
well as selected interviews which typically raise awareness of the major strengths and
weaknesses of a particular building’s performance; (2) Investigative POEs carry out more indepth evaluations and often comply with particular building performance standards or
guidelines on a given building type. One of the most commonly found type of POEs, these
provide a thorough understanding of the causes and effects of issues in building performance;
and (3) Diagnostic POEs provide very detailed information about the buildings performance.
These evaluations gather physical environmental data which are then correlated with
subjective occupant responses (Preiser et al., 1988; Preiser, 2001a). However, more recent
applications of POEs, especially in office buildings, fail to recognize the limitations of POE
studies. Despite more recent POE discussions having emphasized the need for a more holistic
and process-oriented approach to evaluating building performance (Preiser, 2001a; Vischer,
2001; Preiser and Vischer, 2005; Vischer, 2008a; Meir et al., 2009), such notions are yet to
be transformed into practice.
2.3.2. Uses and Misuses of Post-Occupancy Evaluation in Buildings
Over the past four decades, POE has become a widely used tool in evaluating building
performance (Preiser et al., 1988; Preiser, 1995; Riley et al., 2009). Since the early studies on
the housing needs of disadvantaged groups in the 1970s (Bechtel and Srivastava, 1978;
Vischer, 1985), POEs have broadened their scope to applications in various other building
types, such as, healthcare facilities (McLaughlin, 1975; Cooper et al., 1991; Carthey, 2006;
Leung et al., 2012), residential buildings (e.g. CABE, 2007; Gupta and Chandiwala, 2010;
Stevenson and Leaman, 2010), educational buildings (e.g. Baird, 2005; Watson, 2005;
Loftness et al., 2006; Turpin-Brooks and Viccars, 2006; Riley et al., 2010; Zhang and Barrett,
2010), and commercial/office buildings (e.g. Leaman and Bordass, 1999; Leaman and
Bordass, 2001; Zagreus et al., 2004; Bordass and Leaman, 2005c; Vischer, 2005; Abbaszadeh
et al., 2006; Leaman and Bordass, 2007; Leaman et al., 2007). Apart from providing
54
designers with feedback, numerous researchers (e.g. Preiser, 2001b; Vischer, 2001; Whyte
and Gann, 2001; Bordass and Leaman, 2005a; Loftness et al., 2006; Turpin-Brooks and
Viccars, 2006; Preiser and Nasar, 2008; Hadjri and Crozier, 2009; Loftness et al., 2009; Riley
et al., 2010) suggest a number of other plausible benefits of POE, including: (1) improving
commissioning process; (2) definition of user requirements; (3) improving management
procedures; (4) providing knowledge for design guides and regulatory processes; and (5)
targeting of refurbishment.
Notwithstanding these benefits, many barriers to conducting POEs have also been identified
(Cooper, 2001; Vischer, 2001; Zimmerman and Martin, 2001; Zimring and Rosenheck,
2001). The extensive discussion of these problems suggests a growing frustration with the
lack of progress towards POE becoming a mainstream activity in the process of building
procurement (Hadjri and Crozier, 2009; Meir et al., 2009). The more commonly identified
barriers to the widespread adoption of POE include cost, fragmented incentives and benefits
within the procurement and operation processes, potential liability for designers, engineers,
builders, and owners, lack of agreed and reliable indicators, time and skills (Bordass et al.,
2001a; Cooper, 2001; Vischer, 2001; Zimmerman and Martin, 2001). Moreover, Zimmerman
and Martin (2001) suggest that standard practice in the facility delivery process does not
recognise the concept of continual improvement or any ongoing involvement on the part of
the designers. Despite one of the primary goals for conducting POEs is to enable designers to
revisit their designs, improve their skills and produce more efficient buildings, the idea of
continual improvement via feedback has lacked emphasis in both the North American and
UK contexts (Derbyshire, 2001; Preiser, 2001b; Preiser and Vischer, 2005). Whilst many
agree with these barriers, there are still some challenges in the use of contemporary POE
methods (Preiser and Vischer, 2005), especially in commercial office buildings. From the
literature, three key issues in the POE method have been identified: ‘lack of context’; ‘lack of
55
feedback’ and the ‘lack of instrumental data’ (Hartkopf et al., 1986; Vischer, 2001; Jarvis,
2009; Loftness et al., 2009). It should be noted that the following issues are predominantly
focused on POE studies conducted in office buildings.
2.3.2.1. Lack of Context:
Traditionally, POE has been viewed as a final, one-off process as the term ‘post’
reflects only that time after a building was completed (Bordass and Leaman, 2005a; Preiser
and Vischer, 2005). Yet, POE is not the end phase of a building project; rather it is an integral
part of the building delivery process (Federal Facilities Council, 2001; Preiser, 2001b;
Vischer, 2001). The technique should be used more regularly to ensure buildings continue to
deliver at their intended design specifications and, in return, appropriate levels of satisfaction
among the end-users (Preiser, 2001b; Preiser and Nasar, 2008; Vischer, 2008a; Riley et al.,
2010). Much literature suggests POE should be cyclical in nature rather than simply
providing a final feedback component in the occupancy phase (e.g. Preiser, 1995; Bordass et
al., 2001a; Cohen et al., 2001; Vischer, 2001).
POE practice has mainly focused on assessing specific cases (Federal Facilities Council,
2001; Turpin-Brooks and Viccars, 2006). Even when evaluators have been able to create
databases of findings, they have often been used to benchmark single cases rather than to
develop more general conclusions (Zimring and Rosenheck, 2001; Baird, 2011a). POE
studies involving office buildings often lack the contextual information in which the building
was built and occupied. Prior to moving into their new building or space, occupants could
already harbour distrust of management (Vischer, 2001; Vischer and Fischer, 2005; Vischer,
2008b). Workers may also have high expectations that are not met when balanced against the
possible constraints of an existing building that limits the creation of effective workspace
(Schwede et al., 2008). Ultimately, the uncertainty generated by moving to a new building or
56
space affects employee’s perception of their environment (Vischer, 2005; Vischer and
Fischer, 2005). If left unresolved, these attitudes and predispositions are likely to carry
forward into the new workspace. As such, the actual impact a building has on its users
remains unaccounted for in the analysis and interpretation of the results. Many discussions
have risen for the evaluation of a building prior to occupation (Federal Facilities Council,
2001; Preiser and Vischer, 2005). Leaman et al., (2010) suggest that building performance
studies should seek and reveal the context behind the building, i.e. occupants’ personal
history and attitudes towards the building. These psychosocial factors play an important role
in determining people’s concerns with their environment (Vischer, 1986; Chigot, 2005;
Vischer and Fischer, 2005; Turpin-Brooks and Viccars, 2006) and may well affect their
perception of the building. Furthermore, the consideration of occupants’ demands and
experience in the design process helps to achieve more positive design outcomes (Vischer,
1985; Fischer et al., 2004; Vischer, 2005; Schwede et al., 2008).
2.3.2.2. Lack of Feedback (Or Has the Loop Become A Noose?):
Improvement of building performance requires the identification of positives and
negatives through rapid feedback (Cohen et al., 2001; Bordass and Leaman, 2005b). The
UK’s Building Use Studies (BUS) in the 1990s launched the Post-occupancy Review of
Buildings and their Engineering (PROBE) project (Cohen et al., 2001; Cooper, 2001;
Derbyshire, 2001; Fisk, 2001). In conducting POE studies for a wide range of non-domestic
buildings, the PROBE project helped develop a standardised POE method; accumulating a
wide range of studies around the world into a homogenized database against which future
POE studies could be benchmarked (Bordass et al., 2001a; Leaman and Bordass, 2001).
Following these landmark PROBE studies, POE advocates stressed the need to close the loop
between building managers and the building’s end-users (NCEUB, 2004; Building Research
and Information, 2005). In agreement, Leaman and Bordass (2001) suggest the provision of a
57
knowledge base of lessons learned from users in completed projects should be utilised to
either improve spaces in existing buildings or form a programming platform for future
buildings (Leaman and Bordass, 2001; Zimmerman and Martin, 2001; Preiser and Schramm,
2002). Ten years on, however, there is evidence to suggest that a lack of communication and
feedback still exists amongst these parties (Preiser and Vischer, 2005; Thomas, 2010).
POE has lost its initial aim to close the loop between building designers/managers and the
occupants (Jaunzens et al., 2003; Jarvis, 2009; Leaman et al., 2010); suggesting the loop has
now become the noose. To date, occupants still remain a largely untapped source of
information to building managers and, as such, are rarely involved in the stages of building
construction and commission (Zagreus et al., 2004). Due to this lack of involvement, many
occupants do not understand how to operate nor occupy their building, which often leads to
high levels of discontent. Consequently, as Cohen et al., (2001) suggests, occupants will
blame ‘negative’ workplace feelings on the physical environment as a way of voicing their
dissatisfaction. Furthermore, occupants will often resort to using the POE as a means to
report problems in the workplace, e.g. uncomfortable conditions, poor lighting or ventilation,
lack of control, and even bullying which is not measured in POEs (Loftness et al., 1989;
Preiser, 2001b; Vischer, 2004; Vischer and Fischer, 2005; Turpin-Brooks and Viccars, 2006).
2.3.2.3. Lack of Instrumental Data:
POEs were originally intended to provide information regarding the in-use
performance of a building using instrumental data (Hartkopf et al., 1986; Vischer, 1986;
Ventre, 1988; Loftness et al., 1989; Vischer and Fischer, 2005). The landmark PROBE
studies in the UK set the benchmark as to how such studies should be conducted (Loftness et
al., 2009; Meir et al., 2009). These studies relied on three evaluation components: Energy
Assessment and Reporting Methodology (EARM); BUS occupant questionnaire; and an air
58
pressure test (Cohen et al., 2001). Subsequent use of these tools, however, has focused more
on occupant satisfaction with the building, thereby relying on more subjective criteria
(Federal Facilities Council, 2001; Fisk, 2001; Turpin-Brooks and Viccars, 2006; Jarvis, 2009;
Leaman et al., 2010). While many agree such metrics are more easily assessed than
alternatives, such as productivity or health (Leaman and Bordass, 1999), it is often argued
that occupant satisfaction is not a meaningful measure for judging building performance
(Hartkopf et al., 1985; Hartkopf et al., 1986; Heerwagen and Diamond, 1992; Leaman et al.,
2010). Despite providing a first-hand account of how the building is affecting the occupants,
such assessments are susceptible to bias. Since POEs don’t account for any psychosocial or
contextual (non-physical) factors that may affect occupants in the workplace, participants’
responses may be either positively or negatively biased. Sometimes known as the ‘Hawthorne
effect’, the behaviour or responses of an individual or group will often change to meet the
expectations of the observer/researcher (Roethlisberger and Dickson, 1939).
The use of such measures therefore presents a specific challenge: respondents’ subjective
assessments of their environment might be affected by non-building-related factors (Ventre,
1988; Zagreus et al., 2004; Jarvis, 2009; Loftness et al., 2009). Many aspects of building
performance are readily quantifiable, such as lighting, acoustics, temperature and humidity,
durability of materials, amount and distribution of space, etc. (Hartkopf et al., 1985; Hartkopf
et al., 1986; Preiser, 2001a). Despite this, POEs typically do not obtain instrumental
measurements of indoor building environmental conditions, potentially leading to
unsubstantiated complaints against a building’s indoor environment. In order to get a
complete picture of a building’s actual performance from a technical and occupants’
perspective, the subjective data from occupant feedback surveys needs to be correlated
against the quantitative data measured from physical monitoring (Vischer, 1986; Ventre,
1988; Turpin-Brooks and Viccars, 2006; Choi et al., 2010; Gupta and Chandiwala, 2010).
59
Several researchers, however, argue there are inherent difficulties in matching user’s
subjective responses with objective environmental data (Vischer, 1986; Vischer and Fischer,
2005; Jarvis, 2009; Loftness et al., 2009). POEs often record occupant perceptions of thermal
comfort on past seasonal events occurring 3 to 12 months before the survey was
administered. In order to achieve a successful correlation between the occupants’ thermal
comfort ratings and the internal thermal environment of the building, the surveys need to be
conducted on a ‘right-here-right-now’ basis for the results to be reliable. However, Vischer
(1993) also suggests that humans draw on experience outside the immediate time-frame of
the present to make their summary judgements of comfort conditions. Instruments, on the
other hand, are temporally limited to sampling actual building conditions as a snapshot or
over a prolonged period of time. By adopting a more diagnostic approach to POEs the
temporal and calibration limitations on instrument-based data collection can be avoided.
Furthermore, measurements of building systems performance can be carried out as a followup procedure to help understand the meaning behind the feedback yielded by users on their
perceptions of building conditions (Vischer, 1986; Vischer, 2001; Vischer and Fischer,
2005).
2.3.3. The Forgiveness Factor and Occupant Satisfaction in Green Buildings
Green buildings aim to minimise their impact on the environment by reducing fossil
fuel use through energy efficiency as well as on-site use of renewable energy. Such buildings
often incorporate natural ventilation capabilities to reduce the energy consumption and
emissions associated with air-conditioning and to enhance the health and comfort of their
users. Many researchers agree that green buildings often tend to be hotter in summer, colder
in winter and contain more glare from the sun and sky than their conventional AC
alternatives (Abbaszadeh et al., 2006; Brager and Baker, 2009; Baird et al., 2012). However,
recent POE studies from the UK (Leaman and Bordass, 2007) and USA (Abbaszadeh et al.,
60
2006; Brager and Baker, 2009) suggest that occupants are favourably disposed to green
buildings. Notwithstanding occasional discomforts, occupants of green buildings tend to
forgive minor discomforts provided they can exercise a modicum of personal indoor
environmental control. Coined by BUS, the ‘forgiveness factor’ (Equation 2.1) (Leaman and
Bordass, 1999) is an index derived from specific items on the BUS post-occupancy
questionnaire. In particular it is the ratio of the occupants overall evaluation of the building’s
comfort over the average score on specific comfort ratings on thermal, lighting, air quality
and noise. So if the overall comfort rating is larger than the specific comfort scores, the
forgiveness factor comes in greater than unity. This would suggest the willingness to
overlook the specific discomforts of their building when they were casting their overall
comfort vote. Therefore, this ‘forgiveness factor’ represents an attempt at quantifying how
occupants extend their comfort zone by overlooking inadequacies of their thermal
environment (Leaman et al., 2007; Kwok and Rajkovich, 2010):
Equation 2.1
where ventilation/air in winter (AirW) and summer (AirS), temperature in winter (TempW)
and summer (TempS), lighting (Light) and noise (Noise).
Furthermore, Kwok and Rajkovich (2010) discuss this toleration of moderate discomfort and
suggest that occupants may have an understanding of, and connection with the outdoor
climate by virtue of the building’s design, suggesting that increased knowledge of the
adaptive opportunities in buildings yields a greater likelihood of reduced discomfort (Leaman
and Bordass, 2007; Baird, 2011b).
61
2.4. Chapter Summary
This chapter discussed the current knowledge and recent developments within the
fields of thermal comfort and building performance evaluation. This section provides a brief
summary of the topics covered:
MM ventilation represents a key aspect of sustainable building design; providing
comfortable work conditions whilst reducing energy consumption and associated
carbon emissions. MM buildings, especially those with change-over control strategies,
aim to provide good air quality and thermal comfort using a NV mode preferentially
and only reverting to mechanical HVAC systems when the outdoor conditions are too
harsh. Studies suggest that MM or ‘hybrid’ ventilation, as opposed to conventional
air-conditioning, generates greater occupant satisfaction, improves health and
productivity, and enhances thermal comfort.
The debate between the conventional and adaptive comfort models can be seen in
countless papers. Fanger’s PMV-based model for thermal comfort is derived from
pre-calculated temperatures and humidity levels. On the contrary, the adaptive model
recognises the role of human adaptation in establishing thermal comfort, taking into
account people’s thermal perception, behaviour and expectations, allowing for a wider
range of acceptable temperatures in NV buildings. The inclusion of the adaptive
model in international comfort standards, such as ASHRAE Standard 55 and
EN15251, has offered the application of adaptive comfort principles, i.e. operable
windows and greater indoor environmental variations, in current and future building
design.
The conflicting applicability of MM buildings between the international comfort
standards presents a key barrier to the future uptake of such buildings. Currently, MM
buildings are precluded from the scope of the ACS within ASHRAE Standard 55,
which is heavily constrained to naturally conditioned, occupant-controlled spaces in
62
which thermal comfort conditions are primarily influenced by operable windows.
Whenever mechanical cooling systems are provided for the space, regardless of
whether they are used or not, the adaptive model is not applicable. The European
standard EN15251, however, allows its ACS to be applied to NV buildings and can
include MM buildings during times they are not employing mechanical systems, i.e.
whilst in NV or ‘free-running’ mode. Many argue that occupants in MM buildings
likely experience some degree of psychological adaptation beyond the behavioural
adjustments incorporated into the PMV model. However, future field studies in these
types of buildings would provide a better understanding of how occupant comfort is
affected by MM ventilation as well as warrant their inclusion into ASHRAE’s ACS.
Given future increases in outdoor temperatures as a result of climate change and
urbanisation, it is clear that more work can and should be done to improve
quantitative models of comfort and to evaluate the risks of overheating in real world
situations, particularly in MM buildings where there is no consensus on the relative
applicability of the PMV-PPD vs. adaptive comfort standards. Currently, there is very
little guidance as to how overheating potential (exceedance) should be measured, and
even less to how much or little occupant control can be afforded to the building users.
Since the possibility to open a window inside office buildings is now considered an
important adaptive behavioural opportunity, the perception of control has shifted
away from the facilities manager and towards the occupants. However, there still
remains the question of whether use of the windows and adjustments to indoor
temperatures should be controlled by the occupants or the building. Whereas
automated control can provide optimum levels of energy efficiency, the inclusion of
individual control, such as operable windows, is more likely to create much higher
levels of occupant satisfaction within the building.
63
POE was developed in the 1970s as a means to evaluate a building’s performance
after it had been built and occupied for some time. Subsequent use of this tool
however has been more focussed on subjective criteria, such as occupant satisfaction,
rather than the instrumental measurements of actual building performance, e.g. energy
consumption, indoor temperatures, etc. Contemporary POE methods merely provide a
face-value assessment of buildings by their occupants. Despite recommendations to
close the feedback loop between occupants and building designers, building users are
continually omitted from the building design and construction stage. As a result, many
occupants use POE surveys as a vehicle to voice their dissatisfaction with the building
which may or may not be attributed to poor building performance. Since such studies
don’t typically obtain parallel instrumental measurements of these variables, e.g.
indoor climate, they lack an objective benchmark against which poor satisfaction
ratings can be verified. The combination of objective building performance data and
subjective satisfaction ratings may therefore offer a more valid and reliable evaluation
of a building’s success.
Green buildings, by design, tend to be hotter in summer and colder in winter than
their conventional AC counterparts. However, recent POE studies suggest occupants
of green buildings are more forgiving of these less-than-ideal conditions provided
they possess a modicum of environmental control. But could this ‘forgiveness’ be
attributed to more relaxed expectations of the thermal environment? Or could
occupants’ environmental attitudes boost their forgiveness of green buildings?
The next chapter presents detailed information about the case study buildings, questionnaire
design, data collection techniques and analysis methods applied throughout this thesis.
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Chapter 3. Methods
The field research design undertaken within this thesis combines several distinct
studies conducted using two different methods in two case study buildings in the same
location. Firstly, POEs, supplemented with an environmental attitudes questionnaire, were
conducted within a MM and a NV building located in Macquarie University's North Ryde
campus. Secondly, these buildings were also used in a longitudinal thermal comfort field
study (starting in March 2009 and concluding in April 2010). This chapter presents detailed
information about the research design and methods applied in each project, including the
development of each questionnaire, the data collection techniques used and the statistical
analytic approaches. Discussions regarding the indoor and outdoor climatic instrumentation
and measurement protocols are presented along with detailed descriptions of each case study
building.
3.1. Sydney's Climatic Context
The Sydney metropolitan region, located on the eastern coast of Australia (shown in
Figure 3.1) (34°S, 151°E), is characterised by a humid sub-tropical climate with warm-to-hot
summers and cool-to-cold winters with an annual rainfall of 1200mm. This weather is
influenced by the complex elevated topography to the north, west and south and by proximity
to the Tasman Sea to the east. Due to its coastal location and latitude, Sydney avoids the high
temperatures commonly associated with the more inland regions and the high humidity of
tropical coastal areas respectively (BoM, 1991). The warmest month is January, with an
average air temperature range of 18.6°C to 25.8°C. In contrast, its winters are mildly cool,
with temperatures rarely dropping below 5°C in the coastal areas. The coldest month is July,
with an average range of 8.0°C to 12.6°C (BoM, 1991; BoM, 2011). Given the city’s yearly
seasonal variations, its climate is well suited to MM buildings. For much of the year, people
65
can achieve thermal comfort indoors through passive means by way of adaptive behaviours,
such as opening/closing windows, adjusting their clothing or by change of position
(Aggerholm, 2002; Rowe, 2003).
Macquarie University (MQ), is located on a 126 hectare-site in the Sydney’s North Ryde
approximately 18km north-west of Sydney’s central business district (33°46’ S, 151°6’ E)
(Figure 3.2). As summarised in Figure 3.3, variations in the site’s climate are fairly consistent
with the city’s seasonal variability (BoM, 2011). According to the latest Building Code of
Australia climate zone maps shown in Figure 3.4, this area is classified as warm temperate
(zone 5) (ABCB, 2009).
Figure 3.1: Location of Sydney, Australia (sourced from Google, 2012).
66
Figure 3.2: Location of Macquarie University in relation to the Sydney Central Business
District (sourced from Google, 2012).
Figure 3.3: Climate of Macquarie University, North Ryde between 1985-2010. Data was
sourced from the Willandra Village weather station in Marsfield (33°78’ S, 151°11’ E)
located 1 km from the campus (BoM, 2011).
67
Figure 3.4: New South Wales Climate Zones (modified from ABCB, 2009).
68
3.2. Case Study Buildings and Their Occupants
Two academic office buildings from MQ were selected as case studies for this thesis.
These consist of a MM or ‘hybrid’ ventilation building (Building E4A) and a NV building
(Building E7A). The selection of these buildings as case studies will be explained in detail in
the following sections.
3.2.1. Building E4A
As depicted in Figure 3.5, the MM building (E4A) is located in the south-eastern
quadrant of the campus. Commissioned in 2006, this 7-storey office building is occupied by
academic and administrative staff from the departments of the Faculty of Business and
Economics. A detailed floor plan and occupant profile of this building is provided in Figure
3.6f and Table 3.1. Designed to consume approximately 40% less energy than a
conventionally AC alternative, the building operates as a change-over MM or ‘hybrid’
ventilation system that switches between natural ventilation and air-conditioning whenever
outdoor and indoor conditions are amenable (Arkins, 2007). The building’s central core
features constantly AC open-plan office space: heating is supplied when indoor temperatures
fall below 19°C, and cooling when temperatures rise above 25°C. As shown in Figures 3.6a
and b, the north and south perimeter zones consist of MM cellular offices with operable
windows. The entire façade is built on a semi-automated louvre system featuring solar
shading over the northern windows (Figure 3.6a). Automated high and low external louvres
provide natural ventilation to each floor, with adjustable internal grilles to control airflow,
supplemented by user-operable windows (Figure 3.6c).
69
Figure 3.5: Macquarie University North Ryde campus (sourced from MQ, 2012).
Indoor temperature and outdoor weather sensors prompt the building’s management system
(BMS) to switch between AC and NV mode dependent on the prevailing outdoor and indoor
conditions. Each floor of the building is split into three individual zones, i.e. North, Central
and South. Panels located at the entrance of each corridor indicate the zone’s current mode of
operation (Figure 3.6d). As outlined in Figure 3.6e, the building switches into AC mode
whenever internal temperatures in any given zone peak above 25°C. During this mode,
internal temperatures are maintained at a set-point of 24°C (±1°C). BMS switch-over to NV
mode is conditional when the external meteorological conditions and indoor thermal
environment are suitable for the occupants. During such an event, the automated external
louvres will open allowing natural airflow to the space, and occupants can then open their
windows for additional ventilation. The building can also revert to NV mode if more than
30% of windows are opened in any given zone, which automatically shuts off AC mode for
that zone.
70
Figure 3.6: Macquarie University’s Building E4A as viewed from the a) north facade and b)
south façade.
Figure 3.6c: Operable windows and internal grilles in NV mode.
Figure 3.6d: Air-conditioning status display located on each floor. The green light indicates
AC mode; yellow light indicates NV mode and a red light indicates when windows have been
opened and AC mode has been disabled.
71
Figure 3.6e: Building E4A BMS Algorithm.
72
Figure 3.6f: Floor plan of Building E4A – Level 3.
73
3.2.1.1. Building Selection Rationale
Building E4A represents the University’s only MM building. Normalised according to
the total usable floor area, the building consumes 145 kWh/m2 per annum which is far less
than conventional fully AC buildings. As such, the selection of this building allows for an
interesting comparison with the other academic office buildings on campus. The design of
this building is also unique in that each floor consists of MM offices along the north and
south facades, separated by a fully AC central zone. Moreover, since it was built, the
occupants of this building have expressed much discontent about its performance, thereby
making it a perfect candidate to undergo a POE study.
Table 3.1: Building Descriptions and Occupant Profiles.
Type of
Building:
Departments:
Usable Floor
Area:
Building E4A (MM)
Faculty of Business and
Economics; academic office
building
Accounting and Finance,
Economics, Statistics4, Business,
Actuarial Studies, and Applied
Finance Centre
6541 m2 (7 storeys – isolated office
cells with some open partitioned
cubicles)
~228 (± 10 or 4%) (as of 2011)
Number of
Occupants:
Males:
117 (51%)
Females: 111 (49%)
Occupant
28.7 m2 / occupant
Density:
Building E7A (NV)
Faculty of Science; academic office
building
Physics, Chiropractic, Mathematics,
Earth and Planetary Sciences,
Environment and Geography and
Risk Frontiers Centre
5808 m2 (8 storeys – isolated office
cells)
~206 (± 10 or 5%) (as of 2011)
107 (52%)
99 (48%)
28.2 m2 / occupant
3.2.2. Building E7A
Located in the north-eastern quadrant of MQ campus (see Figure 3.5, page 70), the
Faculty of Science building was one of the first buildings ever built for MQ when it first
opened in 1966. Typical of a large proportion of the original office buildings within MQ, this
8-storey office building was designed to be NV (see Figure 3.7e for a detailed floorplan of
4
Prior to 2010, the Statistics department was part of the Faculty of Business and Economics and hence its
occupants are located in Building E4A. This department is now affiliated with the Faculty of Science but
remains physically accommodated within the Faculty of Business and Economics building.
74
this building and Table 3.1 for its occupant profile). The building features a narrow floorplate traversed by a central corridor with single- and dual-occupant offices on either side
(Figures 3.7a and 3.7b). Each office contains at least two occupant-operated sash windows
that can be opened to create effective cross-ventilation throughout the building interior. The
building does not have any external shading along the north facade (facing towards the sun in
the Southern hemisphere) which results in increased solar heat gains in the north-facing
offices. While Building E7A has no centralised heating/cooling systems, occupant-controlled
room air-conditioners were retrospectively added to some offices (as illustrated in Figures
3.7c). Figure 3.7d reveals that many occupants use pedestal or ceiling fans to supplement
cross-ventilation and air movement during warm weather. Postgraduate students and
academic and administrative staff from various science-related departments, such as
Environment and Geography, Earth and Planetary Science, Physics, and Mathematics occupy
this building.
Figure 3.7: Macquarie University’s Building E7A as viewed from the a) north-west corner
and b) south-west corner.
75
Figure 3.7c: Part of the North façade of Building E7A showing some offices with room airconditioning units installed. The photo also shows ventilation fans in the windows of the
toilets in the east-facing wall of the “dog-leg” of the north façade.
Figure 3.7d: Office on the north side of E7A showing some pedestal/portable fans that
occupants often use for additional air movement.
76
Figure 3.7e: Floor plan of Building E7A – Level 2.
77
3.2.2.1. Building Selection Rationale
It was important to select a NV building that would contrast well with the MM
building. While the University contains several NV academic office buildings, many of these
are located in the western corner of the campus. Given potential differences between the
microclimates of these locations, Building E7A was selected due to its physical proximity to
Building E4A. Furthermore, these make for an ideal comparative case study as both buildings
are occupied by the same organisation in the same location. As Building E7A consumes less
energy per unit of usable floor area, i.e. 84 kWh/m2 per annum, it can be considered as
‘greener’ than the MM building in terms of energy performance. Nonetheless, its thermal
environment is also widely acknowledged to be uncomfortable during summer and winter.
The occupant profile of this building is also unique in that it houses many academics and
postgraduate students from environmental science departments, such as physical and human
geography, as well as non-environmental science departments, e.g. physics, astronomy and
mathematics, which enables a useful comparison to the business and economics academics
within Building E4A.
3.3. Questionnaires and Survey Techniques
The questionnaires used in this thesis use a combination of qualitative (open-ended
questions) and quantitative (structured, multiple-choice questions) methods in order to obtain
data. Each of the four different questionnaires used, i.e. the POE, environmental attitudes,
thermal comfort background and ‘right-here-right-now’ comfort questionnaires, were
carefully designed to maximise the robustness of the data collected. As all questionnaires
focussed on subject-based responses, various 7-point (Likert) scales and rank questions were
used, in which their reliability can be assessed by statistical tests. While such instruments are
considered relatively crude when it comes to accurate measurement, their chief function is to
divide people into a number of broad groups or categories (Haynes and Price, 2004). As a
78
result, the sensitivity of word choice was a major factor in the questionnaire design. Prior to
use in the major projects, all questionnaires were administered to a small pilot sample of 10
people. General feedback and suggestions from these pilot studies were considered to
enhance or alter the statements, ensuring minimal confusion with participants. The time taken
to complete these questionnaires was also recorded to allow minimal interruption with the
subject’s schedule.
3.3.1. Post-Occupancy Evaluation and Environmental Attitudes Questionnaires
Figure 3.8 presents a timeline depicting the various data collection stages throughout
this thesis. This project was initially conducted within Building E4A and levels 6 to 8 in
Building E7A between March and April 2009. A separate follow-up survey was conducted in
March 2010 using the rest of the occupants located in Building E7A (located on floors 2 to
5). Whilst undertaken one year apart, these surveys were conducted under comparable
climatic conditions, both representative of Sydney’s autumnal weather. Each questionnaire,
its design and survey techniques are outlined in the following sub-sections.
Figure 3.8: Timeline outlining each stage of both projects.
79
3.3.1.1. Justification and Design
Within the field of POE research there are many questionnaires and analysis methods
available worldwide (Leaman and Bordass, 2003). Whilst all approaches essentially contain
two components: measurement and benchmarking, no universally-standardised method exists
for conducting these studies (Peretti and Schiavon, 2011). Some urge the use of online
computer-based questionnaires while others still rely on the more traditional paper-based,
face-to-face method with its lower rejection rate. With a strong consideration towards
Australian and international benchmarking, the BUS POE questionnaire was selected and
used under licence (refer to Appendix B). Developed by Adrian Leaman and William
Bordass as part of the PROBE studies carried out from 1995-2000 (Cohen et al., 2001), the
BUS survey is one of the world’s most widely used POE instruments. As of 2011, its
database comprised over 350 building performance studies including a separate database for
international green buildings, and is used extensively to benchmark current and new studies.
With over 25 years of experience in conducting building performance studies, Leaman and
Bordass have refined their survey techniques, and therefore the techniques utilised for this
part of the research did not stray away from the guidelines recommended in BUS (2009).
The 3-page BUS POE questionnaire (BUS, 2009) features numerous 7-point Likert scales
with space for commentary covering all variables relating to occupant satisfaction, e.g.
thermal, visual and acoustic comfort, indoor air quality, perceived health and productivity, as
well as general acceptance of the workplace. Combinations of these scores enable the
calculation of various comfort and satisfaction indices unique to the BUS survey. One of the
distinguishing features of this survey is its ‘forgiveness factor’ index. This is simply
calculated as the ratio of the Overall Comfort score to the average of the scores for the six
environmental factors: Lighting Overall, Noise Overall, Temperature Overall in both winter
and summer, and Air Overall in both winter and summer. It represents an attempt to quantify
80
the users’ tolerance of the environmental conditions within the building, with values greater
than 1 taken to indicate that occupants may be more tolerant, or ‘forgiving’, of a building’s
indoor environmental conditions (Leaman and Bordass, 2007).
Accompanying the BUS occupant survey was an environmental attitudes questionnaire.
Based on the 15-item version of the NEP scale (Dunlap et al., 2000), this questionnaire was
developed to measure strength of endorsement (from low to high) of an ecological worldview
(Dunlap and van Liere, 1978; Dunlap, 2008). The NEP questionnaire uses 5-point response
scales ranging from Strongly Disagree to Strongly Agree, with higher scores on the scale
from 1 (low) to 5 (high) indicating greater levels of environmental concern. A copy of the
Environmental Attitudes/NEP questionnaire is provided in Appendix D. All scales were
converted to a NEP score by summing each item response and dividing by the total number
of items in the scale.
3.3.1.2. Survey Techniques and Protocol
After obtaining approval from the University’s Human Ethics Committee (see
Appendix A), emails were sent to all occupants within the building, informing them of the
project, when it was being conducted and what it involved should they consent to participate
(refer to Appendix C for this email consent form). Consent was recognised if a recipient
replied to the email.
Each survey was conducted over the course of one week in March to allow for comparable
outdoor climatic conditions for both buildings (Figure 3.8, page 79). Both the POE and NEP
questionnaires, along with an instruction sheet, were placed inside an envelope and handed
out to every occupant within each building on a Tuesday morning5. If at the time of delivery
5
BUS (2009) suggests studies conducted on either Tuesday or Wednesdays generate the best response rates
81
the occupant wasn’t in their office, it was placed under their door. The sheet of instructions
(see Appendix E) reiterated the aims and objectives of the project and also asked the
participants to place their completed questionnaires inside the envelope provided, which
would be collected in person at the end of the day. Should the participant not be in their
office at this time, then they were asked to leave the envelope in a prominent place for
collection. Naturally, not all questionnaires delivered were collected at the end of the day, in
which case the participants were given until Monday of the following week to complete the
questionnaires for collection. Due to time constraints, any questionnaires collected after these
dates were excluded from the final data analysis.
3.3.2. ‘Right Here, Right Now’ Thermal Comfort Questionnaires
As illustrated in Figure 3.8 (page 79), this project was conducted simultaneously in
Building E4A from March 2009 to April 2010 and Building E7A between October 2009 and
April 2010 to provide a summertime comparison. The questionnaires, their design and the
surveying techniques used are explained in detail below.
3.3.2.1. Justification and Design
A multitude of thermal comfort field studies have been conducted around the world,
each of which has used very similar questionnaire designs. The questionnaires developed by
de Dear and Fountain (1994) and Cena and de Dear (1998) have become some of the most
commonly used in thermal comfort research. While there is no universally-accepted comfort
questionnaire, several international comfort standards offer their own guidelines and
recommendations as to how they should be designed (ASHRAE, 2004; ISO, 2005; CEN,
2007). Often using very similar layouts and employing the same metrics with only minor
differences in word choice, these questionnaires represent the most widely used formats in
82
thermal comfort research. It was decided that the questionnaires used for this project would
be adapted from these examples.
Two separate questionnaires were used in this project: a background questionnaire and a
‘right here, right now’ subjective comfort questionnaire, both adapted and based on those
used for ASHRAE’s RP-702 and RP-921 projects in Australia (de Dear and Fountain, 1994;
Cena and de Dear, 1998). During the initial phases of the project, the background
questionnaire (as shown in Appendix H) was used to gather generic information about each
subject, e.g. age, demographic and contextual factors, etc. While this questionnaire consists
of slightly overlapping age categories, these did not cause any skewed results since age was
not factored into the analysis of thermal comfort data. Subjects were asked to specify their
gender, age group, how long they had occupied the building as well as the type and location
of the building they previously occupied. Participants were also required to estimate how
many hours per week they spend inside the building and how many hours they spend each
day at their workspace. A section on the use of air-conditioning away from the office was
also included. The final questions referred to a range of adaptive behaviours the subjects
could employ in their office, and how often they used them on a seasonal basis, i.e. during
summer and winter.
The other part of this project was the ‘right here, right now’ comfort questionnaire. These
were used to record occupant perceptions of the thermal environment and their workplace at
the time the questionnaire was administered. Appendix I is an amalgamated version of the
summer and winter questionnaires. Questions were formatted into columns and tables with a
variety of tick boxes to ensure occupants could complete the questionnaire quickly and easily.
Thermal sensation was rated along the ASHRAE 7-point scale, ranging from -3 (cold) to +3
(hot), with 0 as neutral. Thermal acceptability was addressed with a binary ‘acceptable’ or
83
‘unacceptable’ question, while thermal preference was assessed on the 3-point McIntyre scale
(McIntyre, 1980), wherein occupants listed if they preferred to be ‘warmer’, ‘cooler’ or ‘no
change’. Air movement questions focused on the subjects’ acceptability as it related to the air
speed. Subjects registered if the air velocity was ‘acceptable’ or ‘unacceptable’ and their
reason, whether it was ‘too low’, ‘too high’ or ‘enough’ air movement. Subjects were also
asked if they preferred ‘more’ or ‘less air movement’ or ‘no change’. Standardised clothing
and metabolic activity checklists were assessed using the current values in ASHRAE (2001)
and ISO (2003). Subjects were asked to circle the items corresponding to the clothes they
were wearing at the time the questionnaire was administered. Any items worn by the
participant but not listed were specified by the subject. Typical undergarments were assumed
to be worn by all subjects and were hence omitted from this list (Morgan and de Dear, 2003).
In regards to metabolic activity, subjects were asked to record their general activity at 10, 20,
and 30 minutes before the questionnaire was delivered, from which an overall metabolic rate
could be established. The question referring to perceived productivity was derived from the
BUS POE survey used in the previous project. The wording was modified, enabling subjects
to assess their own daily productivity based on their interpretation of an average day’s work.
Adaptive behaviours were also addressed by enquiring if subjects had used any personal
thermal environment/comfort strategies on the day the survey was conducted, such as
opening/closing windows, adjusting their clothing, or using a portable heater or fan.
3.3.2.2. Survey Techniques and Protocol
After obtaining approval from the University’s Human Ethics Committee (see
Appendix F) and attaining approval from the Dean of each building’s Faculty to survey their
staff members, a building-wide email was sent informing the occupants of the project and
what was going to be asked of them should they consent to participate (refer to Appendix G
for a copy of this occupant email consent form). Again, consent was formalised if a recipient
84
replied to the email. To ensure statistically appropriate sample sizes, 60 occupants were
recruited in each building. The field study was conducted using a longitudinal design, i.e. the
samples of subjects were surveyed across a long period of time across a wide variety of
different indoor and outdoor climatic conditions.
On each day of the project, subjects were selected based on their availability. If a subject was
in their office at the time of the survey, they were first asked if they could afford to spend 60
seconds to complete the questionnaire. During the time when subjects were filling in the
questionnaires, instrumental measurements were being made of the subjects’ thermal
environment, which will be explained in further detail in the next section.
3.4. Indoor and Outdoor Climatic Instrumentation and Measurement Protocols
Both projects used a variety of instruments to measure the indoor and outdoor
climatic conditions. These included some continuous monitoring dataloggers and weather
stations as well as some spot-readings recorded at the time questionnaires were being
completed, such as air velocity and clothing insulation. All dataloggers were calibrated
against accurate, industrial-grade mercury thermometers while the anemometers were
calibrated inside a wind tunnel. Data generated from Building E4A’s BMS was also gathered
to identify times of opening and closing of windows, indoor and outdoor temperatures as well
as the building’s modes of operation.
3.4.1. Indoor Climate Measurements
Eighteen offices in Building E4A (7 in the north; 4 in the central; and 7 in the south
zones) and five offices in Building E7A (3 in the north and 2 in the south zones) were
equipped with HOBO dataloggers to continuously record air temperature (°C) and relative
humidity (RH) (%) throughout each project. Several of these were equipped with a 40mm
85
ping pong ball painted matte black attached to an external temperature sensor to record
radiant globe temperature (°C). Each logger was placed at a height of 0.6 m within 1 metre of
the occupant’s workstation to characterise the immediate thermal environment experienced
by the occupant under normal working conditions. The data recorded by the HOBOs were
regularly uploaded every month. During each questionnaire session, air speed/velocity (m/s)
was also measured at the same height and distance from the subject. Figures 3.9-3.13 and
Table 3.2 detail each instrument used and their specifications.
Figure 3.9: “HOBO” U12-013 Temperature and Relative Humidity Datalogger.
Figure 3.10: “HOBO” U12-013 Temperature and Relative Humidity Datalogger with 40mm
sphere painted matte black attached to TMC1-HD Water/Soil Temperature Sensor.
86
Figure 3.11: “TSI VelociCalc” Anemometer.
Figure 3.12: “Vaisala HM34C” Humidity and Temperature Meter.
87
Figure 3.13: “Vaisala” HM34C Humidity and Temperature Meter with 40mm sphere painted
matte black.
88
Table 3.2: Indoor Climate Instrument Specifications.
Figure
Reference
Instrument
Figure 3.9
Figure 3.10
Figure 3.11
Figure 3.12
Figure 3.13
“HOBO” U12-013
Temperature and
Relative Humidity
Datalogger
“HOBO” U12-013
Temperature and
Relative Humidity
Datalogger
“TSI VelociCalc”
Anemometer (Model
8345)
“Vaisala HM34C”
Humidity and
Temperature Meter
“Vaisala” HM34C
Humidity and
Temperature Meter
Air Temperature (°C);
Relative Humidity (%)
40mm sphere painted
matte black (ε = 0.99)
attached to TMC1-HD
Water/Soil Temperature
Sensor
Radiant Globe
Air Speed/Velocity
Temperature (°C)
(m/s)
Attachments
Variables
(units)
Specifications
Range
Air Temperature: -20 to
+70°C;
Relative Humidity: 5 to
95%
Accuracy Air Temperature: ±
0.35°C;
Relative Humidity: ±
2.5%
Resolution Air Temperature:
0.03°C;
Relative Humidity:
0.03%
1 sample measured
Sampling
every 5 minutes
Technique
40mm sphere painted
matte black (ε = 0.99)
Air Temperature (°C);
Relative Humidity (%)
Radiant Globe
Temperature (°C)
-20 to +60°C
0.03°C (at 20°C)
Air Temperature: -20 to
+60°C
Relative Humidity: 0 to
100%
Air temperature: ±
0.3°C (at 20°C)
Relative Humidity: ±
1% (at 20°C)
Air Temperature: 0.1°C
1 sample measured
every 5 minutes
Relative Humidity:
0.1%
3-5 samples averaged
over a 1 minute period
-40 to +50°C
0 to 30 m/s
± 0.25°C (at 20°C)
± 0.015 m/s (or 3% of
reading)
Time constant: 10
seconds; 3-5 samples
averaged over a 1
minute period
89
± 0.3°C (at 20°C)
0.1°C
3-5 samples averaged
over a 10 minute period
3.4.2. Clothing Insulation Estimates
Throughout the thermal comfort project, standardised clothing garment checklists
were used to track the subjects’ clothing behaviour as it related to the concurrent indoor and
outdoor climatic variations. Based on garment checklists defined in ASHRAE’s Handbook of
Fundamentals (ASHRAE, 2001), Standard 55 (ASHRAE, 2004) and ISO 7730 (ISO, 2003),
clothing insulation (clo) values were differentiated according to those typically worn in
summer (lightweight) and those typically worn in winter (heavyweight) (as seen in Table
3.3). As defined in Equation 3.1, intrinsic clo values (Icl) were calculated for each subject by
adding the value of each article of clothing circled on the subject’s questionnaire:
Icl = Σi Iclu, i
Equation 3.1
where Iclu, i is the effective insulation value of the ith garment (ASHRAE, 2001).
Although clothing ensemble insulation values were calculated based on the subjects’ own
self-assessment, some limitations may exist in the accuracy of this data. ASHRAE (2004)
suggests that measuring ensemble insulation values from checklists of published garment
values (the method used in this project) is likely to deviate ± 25% (0.1-0.2 clo) from the
benchmark thermal manikin measurements due to differences in fabric material, construction
and fit, as well as variations in people’s different definitions of certain garments and clothing
layers. The subjective self-assessed method represents the most practical solution to the need
for high-speed observations in a real-world setting. Nonetheless, in some cases, observations
had to be made to verify the subject’s clothing matched their response on the questionnaires.
Whatever errors exist in the raw data, they are unsystematic and uniformly distributed
throughout the sample.
90
Table 3.3: Individual clothing garments and their effective insulation values (Iclu, i (clo)).
Ensemble intrinsic insulation values were derived by summing individual garment effective
insulation values (ASHRAE, 2001; ISO, 2003; ASHRAE, 2004).
Garment
Description
Bra
Iclu, i
(clo)
‘Thin’
0.01
Iclu, i
(clo)
‘Thick’
0.01
Garment
Description
Iclu, i
(clo)
‘Thin’
0.17
Iclu, i
(clo)
‘Thick’
0.19
Panties
0.03
0.03
Men’s briefs
0.04
0.04
Singlet
0.04
0.04
Half-slip
Long underwear
bottoms
Full-slip
Long underwear top
Neck-tie
Ankle-length athletic
socks
Pantyhose/stockings
Sandals/thongs
Calf-length socks
Shoes
Knee-socks
0.14
0.15
0.14
0.15
Short-sleeve dress
shirt
Short-sleeve knit
sport shirt
Long-sleeve dress
shirt
Long-sleeve
flannelette shirt
Short shorts
Walking shorts
0.19
0.22
0.22
0.25
0.25
0.34
0.06
0.08
0.08
0.12
0.16
0.20
0.05
0.02
0.16
0.20
0.05
0.03
Straight trousers
Sweatpants
Overalls
Knee-length skirt
0.15
0.28
0.30
0.14
0.24
0.28
0.30
0.23
0.02
0.02
0.03
0.02
0.06
0.02
0.02
0.03
0.02
0.06
Sleeveless dress
Short-sleeve dress
Long-sleeve dress
Suit vest
Single breasted
jacket
Double breasted
jacket
Sleeveless vest
Long-sleeve sweater
Standard office chair
0.23
0.29
0.33
0.10
0.36
0.27
0.29
0.47
0.17
0.42
Boots
0.10
0.10
0.44
0.48
Short-sleeve T-shirt
Long-sleeve T-shirt
Sleeveless/scoopneck blouse
Scarf
0.08
0.12
0.13
0.10
0.16
0.17
0.13
0.25
0.09
0.22
0.36
0.15
0.05
0.05
3.4.2.1. Effects of Chair Insulation on Clothing Insulation
It is now generally accepted that an occupant’s chair has the ability to inhibit heat loss
from the body in the area of body-chair contact. This is likely to have some effect on the
subject’s thermal balance, and hence, augment the feeling of warmth (McCullough et al.,
1994). Given that all participants answered the questionnaires while sitting in a standard
office chair, these were included in the final calculation of each subject’s clo value and
subsequent comfort indices. Figures 3.14a and b show the most frequently encountered chair
91
type in these studies, which according to ASHRAE (2001) were estimated to add between
0.09 and 0.15 clo to the occupants’ total clothing insulation.
Figure 3.14: Typical example of office chairs used in a) Building E4A and b) Building E7A.
3.4.3. Building Management System Data
Various sensors located within the interior and exterior of the MM building
continuously relay information to the BMS to determine if the building’s zones should be in
either NV or AC mode. Obtained from MQ’s Office of Facilities Management (OFM), this
BMS data was useful in gathering information about how the building performs beyond what
the dataloggers and subjective questionnaires could provide. Weather stations situated atop
Building E4A recorded outdoor air temperature, precipitation, wind direction and wind speed
every minute. Located in over 100 offices within the building, sensors recorded the internal
air temperature and current mode of operation every 5 minutes. Recorded in 15 minute
intervals, on an open or closed basis, the status of each window was also collected from the
BMS.
92
3.4.4. Outdoor Climate Measurements
Local and concurrent outdoor meteorological data was obtained from many different
sources for this thesis. Initially, it was decided that MQ’s automatic weather station (AWS),
located within the University’s sports grounds (33°46’ S, 151°7’ E) about 1 km from the
sample buildings, would be used extensively throughout both projects. However, due to
technical difficulties encountered during the data collection stages, this source of data became
unreliable and hence alternative sources were utilised. Outdoor climate data from the weather
station atop Building E4A was obtained from the BMS data collected from OFM. The data
included air temperature (°C), wind speed (m/s) and wind direction (°) at 1 minute intervals
over the duration of the project. However, since other important outdoor weather variables
were needed, additional sources of data were consulted. Two nearby weather stations
serviced and operated by Australia’s Bureau of Meteorology (BoM) were also used to gather
outdoor weather data. It should be noted that while the BoM weather station at Willandra
Village in Marsfield (33°78’ S, 151°11’ E) is located within 1 km from the University’s
campus, it is only used to record rainfall. As illustrated in Figure 3.15, the stations at Sydney
Olympic Park in Homebush (33°84’ S, 151°7’ E) and Terrey Hills (33°68’ S, 151°22’ E)
were located within a 10-13km radius of the campus. Recorded at 1 minute intervals over and
beyond the period of each project, this data offered a multitude of outdoor climatic variables,
including dry- and wet-bulb temperature (°C), relative humidity (%), wind speed (m/s), wind
direction (°) and global surface radiation measurements (W/m2).
93
Figure 3.15: Location of nearby BoM weather stations in relation to Macquarie University
(at red square). The Terry Hills and Sydney Olympic Park weather stations are located at the
blue squares (sourced from BoM, 2011).
3.5. Data Analyses and Complementary Calculations
A wide range of quantitative and qualitative data was collected for this thesis. As
such, statistical analyses were determined based on the type of data collected. For example,
Oppenheim (2000) suggests that the statistical techniques applicable to quantitative data are
means and standard deviations, two sample t-tests, F-tests, analysis of variances (ANOVA),
regression models and correlation coefficients. Since qualitative data are not always
measured along a continuum, alternative statistical methods had to be used, such as
percentages, chi-squared tests and other non-parametric devices (Oppenheim, 2000).
94
3.5.1. Statistical Analyses
To enable easy data storage, data were collated and entered into Microsoft Excel 2007
and analyses were performed using MiniTab (MiniTab versions 15.0 and 16.0 for Windows)
statistical software. Data collected from the POE questionnaires were sent to Adrian Leaman
to benchmark the scores against the BUS Australian green building database. As many of the
climatic variables are continuous in nature, they could be analysed using linear regression
models, providing the data met the appropriate assumptions for parametric tests (which they
did). The relationship between clo values and the prevailing indoor and outdoor conditions
was investigated using many techniques and methods derived from previous studies (Morgan
and de Dear, 2003; de Dear, 2006; De Carli et al., 2007). More robust techniques were
required for more complex analyses, such as probit regressions (Ballantyne et al., 1977).
Scatter plots were useful in visualising these statistical analyses. Analyses that required
comparisons among categorical variables, such as gender, mode or office location, were
analysed using two sample t-tests and graphed using comparative box plots and column
graphs.
3.5.2. Thermal Comfort Indices
Many thermal comfort indices were used throughout both projects. ASHRAE’s
WinComf program (Fountain and Huizenga, 1997) was used to calculate the PMV and PPD
values for each subject. Using these calculations and the adaptive thermal comfort model (de
Dear and Brager, 2001) enabled the comparison of PMV and PPD values with the occupants’
observed thermal sensation and acceptability, as expressed as Actual Mean Vote (AMV) and
Actual Percentage Dissatisfied (APD).
95
3.6. Chapter Summary
This chapter has outlined the methods used in this research. It introduced the study
location; provided detailed information on each case study building, the questionnaires and
survey techniques used within each project, as well as the collection of objective indoor and
outdoor climate data. Since the majority of data collected for these projects were during
Sydney’s summer months, their results (presented in Chapter 4) will primarily focus on the
use of air-conditioning for cooling purposes. The methods for data analysis and subsequent
calculations have also been described. The following chapter provides the results and
discussion of this thesis, with these largely being presented in three peer-reviewed journal
articles.
96
Chapter 4. Results and Discussion
In accordance with Macquarie University’s guidelines for a thesis by publication, this
chapter comprises peer-reviewed papers that have been published in, or submitted to journals
during the course of this candidature. Complementary publications that have been published
in peer-reviewed journals and/or conference proceedings are included in Appendices J to O.
The concept and design of each article were discussed with Professor Richard de Dear prior
to the writing of each manuscript. Data collection, statistical analyses, interpretation of the
results, and write-up of the manuscripts were all undertaken by the candidate with guidance
from Richard de Dear in his role as Adjunct Supervisor.
The main results from this thesis are organised into three topics, each corresponding to a
journal paper. Due to the varying stages of the publication of each paper, differences in their
formatting will be found throughout this chapter. A section summarising the main topics
within each paper and how they relate to the overall themes of the thesis, along with the
limitations of this research, is presented at the end of this chapter. The three topics and
corresponding publications are summarised below:
Topic 1: Environmental Attitudes and Occupant Satisfaction in Green Buildings
Deuble, M.P. and de Dear, R.J. (2012) ‘Green occupants for green buildings: The missing
link?, Building and Environment, 56(10): 21-27
DOI: http://dx.doi.org/10.1016/j.buildenv.2012.02.029
97
Topic 2: Thermal Comfort in Mixed-Mode Buildings
Deuble, M.P. and de Dear, R.J. (2012) ‘Mixed-mode buildings: A double standard in
occupants’ comfort expectations’, Building and Environment, 54(8): 53-60
DOI: http://dx.doi.org/10.1016/j.buildenv.2012.01.021
Topic 3: The Validity of Contemporary Post-Occupancy Evaluation Methods
Deuble, M.P. and de Dear, R.J. (2012) ‘Is it hot in here or is it just me? Validating the postoccupancy evaluation’ (Submitted to Intelligent Buildings International, May 2012)
98
Paper 4.1. Environmental Attitudes and Occupant Satisfaction in Green Buildings
Status: Published; Deuble, M.P. and de Dear, R.J. (2012) ‘Green occupants for green
buildings: The missing link?’, Building and Environment, 56(10): 21-27
DOI: http://dx.doi.org/10.1016/j.buildenv.2012.02.029
Journal Impact Factor (Thomson Reuters, 2012): 2.131 (Ranked 3 of 53 Construction &
Building Technology journals)
4.1.1. Paper Overview
This paper investigates how environmental attitudes and beliefs may influence
occupants’ tolerance of green buildings. POEs were conducted within the MM and NV
buildings to record the occupants’ level of forgiveness and satisfaction with the building’s
performance. These surveys were supplemented with the NEP environmental attitudes
questionnaire to measure strength of endorsement (from low to high) of an ecological
worldview. Occupants of the NV building, despite experiencing significantly warmer indoor
temperatures, were more forgiving of these conditions than their MM counterparts. Likewise,
the NV building, on average, recorded greater NEP scores than the MM building.
Furthermore, a strong positive correlation between environmental attitudes and forgiveness
factors was demonstrated within these two case study buildings. Despite their criticisms of
the building’s IEQ, the ‘green’ occupants were prepared to overlook and forgive less-thanideal conditions more so than their ‘brown’ (non-green) counterparts. These results provide
evidence to support the hypothesis that pro-environmental attitudes are closely associated
with the stronger ‘forgiveness factor’ often observed in green buildings.
99
Building and Environment 56 (2012) 21e27
Contents lists available at SciVerse ScienceDirect
Building and Environment
journal homepage: www.elsevier.com/locate/buildenv
Green occupants for green buildings: The missing link?
Max Paul Deuble a, *, Richard John de Dear b
a
b
Department of Environment and Geography, Faculty of Science, Macquarie University, Sydney, NSW 2109, Australia
Faculty of Architecture, Design and Planning, The University of Sydney, Sydney, NSW 2006, Australia
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 2 December 2011
Received in revised form
12 February 2012
Accepted 26 February 2012
Green buildings, often defined as those featuring natural ventilation capabilities, i.e. low-energy or
free-running buildings, are now at the forefront of building research and climate change mitigation
scenarios. This paper follows the results of recent post-occupancy evaluation (POE) surveys within two
academic office buildings located in sub-tropical Sydney, Australia. Supplemented with an environmental attitudes questionnaire, based upon the New Ecological Paradigm [1]), it was found that
occupant satisfaction levels on the POE were positively associated with environmental beliefs.
Occupants with higher levels of environmental concern were more forgiving of their building,
particularly those featuring aspects of green design, such as natural ventilation through operable
windows. Despite their criticisms of the building’s indoor environmental quality, the ‘green’ occupants
were prepared to overlook and forgive less-than-ideal conditions more so than their ‘brown’ (nongreen) counterparts. These results support the hypothesis that pro-environmental attitudes are closely
associated with the stronger ‘forgiveness factor’ often observed in green buildings, but the question of
causality remains moot.
Ó 2012 Elsevier Ltd. All rights reserved.
Keywords:
Green buildings
Post-occupancy evaluation (POE)
Forgiveness factor
New Ecological Paradigm (NEP)
1. Introduction
The built environment contributes greatly to global energy use
and greenhouse gas emissions [2]. Fossil fuel energy used directly,
or, as electricity to power equipment and condition the air
(including heating and cooling) within commercial buildings is by
far one of the largest source of emissions in the built environment.
Australian commercial buildings account for an estimated 27% of
the total greenhouse gas (GHG) emissions within the buildings
sector [3,4]. In energy terms, space heating, ventilation and airconditioning combined represent the largest end-use in commercial buildings, accounting for almost two-thirds (61.2%) of total
energy use; the other major end user is lighting (18.6%) and general
uses (19.2%) [4].
Contemporaneous concerns over global warming and escalating
fossil fuel prices have rapidly emerged into public consciousness.
Over the last few years the world has witnessed a momentous
change as governments, economies and businesses prepare for
a carbon constrained future. Today, architects strive towards
ambitious designs which often stretch the ability of building service
engineers to provide robust, low-energy solutions [5e9]. With
* Corresponding author. Tel.: þ612 98508396.
E-mail address: max.deuble@students.mq.edu.au (M.P. Deuble).
0360-1323/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved.
doi:10.1016/j.buildenv.2012.02.029
100
present attempts at mitigating global warming, the buildings sector
offers the greatest potential for cost-effective reductions in GHG
emissions through the application of both technical and nontechnical measures to existing building stock and new construction [2,10].
1.1. Adaptive thermal comfort
Current practices in office buildings typically provide static
thermal environments for all occupants using centralised heating,
ventilation and air-conditioning (HVAC) technology. However,
many adaptive comfort studies (e.g. [11,12]) have called for greater
indoor environmental variability, either through user adjustments
to operable windows, shade devices, etc., or automated controls
shifting HVAC set-points in sync with weather and seasonal variations outdoors. A shift towards greater indoor climatic variability
is integral to many sustainable building design solutions. Green
buildings (also referred to as green-intent buildings) by definition,
aim to reduce their environmental impact by using less energy in
both their construction and operation. Thus, buildings featuring
natural ventilation capabilities are typically defined nowadays as
green buildings. Building users will often employ a wide range
of passive cooling strategies and adaptive opportunities [13]
available to them to adjust their own comfort conditions to suit
their needs.
22
M.P. Deuble, R.J. de Dear / Building and Environment 56 (2012) 21e27
It is widely believed that occupants prefer a high degree of
adaptive opportunities [13], as can be provided within naturally
ventilated (NV) buildings as opposed to centrally controlled airconditioned (AC) designs. Many studies have found occupants
are more favorably disposed to green buildings than their
conventional energy-intensive predecessors [14e16]. Within their
extensive database of post-occupancy evaluation (POE) studies,
Leaman and Bordass [16] observed that occupant satisfaction
scores for green buildings tend to be higher than those in
conventional AC buildings. But despite occupants preferring
greater adaptive opportunities, they do not necessarily expect the
thermal excursions that sometimes occur in NV buildings, especially during heatwaves. Occupants are often prepared to “forgive”
such conditions if they possess a modicum of personal environmental control [17e20].
1.2. Post-occupancy evaluation (POE) and the forgiveness factor
The POE has become an important tool for the improvement of
building design and operations [21e23]. However, with clients
often broadening their interests to include indoor environments,
occupant health and productivity, gaps were often found between
client and design expectations for a specific performance level [24].
Faced with the challenge of reducing building and energy costs to
accommodate the expansion of its building industry, the UK’s
Building Use Studies (BUS) launched the PROBE project, which
consisted of a series of POE studies for a wide range of nondomestic buildings [24]. This project helped develop a standardised POE method; accumulating a wide range of studies around
the world into a BUS database against which future building POE
studies could be benchmarked [25].
Recent POE studies from the UK [16] and USA [14,15] suggest
that occupants of green buildings tend to forgive minor discomforts provided they can exercise a modicum of personal indoor
environmental control. Coined by BUS, the ‘forgiveness factor’
[16] is an attempt at quantifying how occupants extend their
comfort zone by overlooking inadequacies of their thermal
environment [26,27]. Illustrated in Eq. (1) below, this index is
derived by dividing ‘comfort overall’ scores on the BUS questionnaire by the average of the indoor environmental quality
(IEQ) variables; overall temperature in summer (TempS) and
winter (TempW), overall ventilation/air in summer (AirS) and
winter (AirW), overall noise (Noise) and overall lighting (Light).
All variables are rated along 7-point Likert scales ranging from 1
(unsatisfactory) to 7 (satisfactory). Many researchers agree that
although green buildings often tend to be hotter in summer,
colder in winter and have more glare from the sun and sky than
their conventional AC alternatives [14,15], the occupants tend to
be more forgiving. Furthermore, Kwok and Rajkovich [27] discuss
this toleration of moderate discomfort and suggest that occupants
may have an understanding of, and connection with the outdoor
climate by virtue of the building’s design, suggesting that
increased knowledge of the adaptive opportunities in buildings,
such as operable windows, individual shade control, aesthetics
and glazing area, etc. yields a greater likelihood of reduced
discomfort [16].
1.3. Environmental attitudes, behaviours and the New Ecological
Paradigm (NEP)
In recent decades there has been a growing awareness of the
problematic relationship between modern industrialised societies
and the physical environments upon which they depend [28,29].
With the emergence of pervasive environmental problems such as
climate change, many researchers have started exploring how to
quantify public sentiment on these issues. Environmental attitudes
represent a psychological tendency expressed by evaluating the
natural environment with some degree of favour or disfavour
[30,31]. Attitudes are related to other psychological and cultural
dimensions, e.g. beliefs, intentions and behaviours. Since attitudes
are a latent construct, they cannot be measured directly, and thus
need to be inferred from overt responses [32]. A proliferation of
environmental attitudinal measures has been proposed since the
1960s, the problem arises of using a reliable and valid set of
measures or scales in order to quantify the unquantifiable [30,33].
The New Ecological Paradigm (NEP) Scale [1] is a revision of the
NEP developed by Dunlap and van Liere [34]. This 15-item questionnaire consists of 8 pro-NEP and 7 anti-NEP items developed to
measure strength of endorsement (from low to high) of an ecological
worldview [29,35]. After extensive application across a diverse range
of studies, a broad consensus is emerging in the environmental
psychology literature that the NEP represents a valid and reliable scale
for measuring levels of ecological beliefs and behaviours [36]. Despite
its extensive use, the NEP scale has not been used in conjunction with
building occupant studies and could potentially identify the link
between successful occupancy of green buildings and environmental
attitudes. Thus this paper investigates the hypothesis that broad
environmental attitudes are closely associated with the stronger
‘forgiveness factor’ often observed in green buildings.
2. Methods
2.1. Sydney’s climate
The Sydney metropolitan region is located on the eastern coast
of Australia (34 S, 151 E) and is characterised by a moderately
temperate, sometimes called humid sub-tropical climate. Influenced by complex elevated topography surrounding the region to
the north, west and south and due to close proximity to the Tasman
Sea to the east, Sydney avoids the high temperatures commonly
associated with more inland regions, as well as the high humidity of
tropical coastal areas [37]. The summer months of December to
February can be described as warm-to-hot with moderate-to-high
humidity peaking in February to March. Between June and August,
Sydney experiences cool-to-cold winters. The tertiary institution is
located in Sydney’s suburbs, 16 km out of the Central Business
District of Sydney. Seasonal variations are fairly consistent with the
greater metropolitan region with a mean summer daily maximum
temperature of 26e28 C, a mean winter daily maximum of 17 C
and an annual mean daily maximum of 22e23 C. Mean minimum
daily temperatures range from 5e8 C in winter, to 17e18 C over
the summer months, with an annual daily minimum temperature
of 11e13 C [38]. Given these yearly seasonal variations, Sydney’s
AirW þ AirS þ TempW þ TempS þ Light þ Noise
Forgiveness factor ¼ Comfort overall=
6
101
(1)
M.P. Deuble, R.J. de Dear / Building and Environment 56 (2012) 21e27
23
mild climate is well suited to natural ventilation design strategies
for much of the year.
2.2. Case study buildings
Two academic office buildings were selected for this study;
a mixed-mode (MM) building commissioned in 2006 and an NV
building dating back to the 1960s. Both buildings have a comparable occupancy density of 0.03 occupants/m2. Both buildings also
have NortheSouth orientations, with North facades being directly
irradiated from the Sun, creating warmer internal temperatures
than the South-facing perimeter zones:
1. Mixed-mode building: the MM building (see Fig. 1) features
operable windows on all perimeter cellular offices arranged
along North and South facades which have separating them an
AC central open-plan office zone. Indoor temperature and
outdoor weather sensors drive the Building Management
System (BMS) to switch to AC mode when zonally averaged
indoor temperatures increase above 25 C. Around 200
academic and administrative staff from economics and finance
disciplines occupy this building. Normalised according to the
total usable floor area (the total area of all interior spaces in
a building which are leasable to tenants, i.e. not including basebuilding areas like stairways, corridors, lift-wells, etc.), the
building consumes 145 kWh/m2 per annum, which is far less
than conventional full-time AC buildings.
2. Naturally ventilated building: as illustrated in Fig. 2 below, the
NV building used in this study features occupant-operated
Fig. 2. NV building (North facade) featuring occupant-operated windows with some
individual air-conditioner units.
windows and a narrow floor-plate traversed by a central
corridor with single- and dual-occupant cellular offices on
either side. There is no centralised heating or cooling systems
inside this building. However, some exceptions have been
given to occupants with individual window air-conditioner
units, representing approximately 10% of the total building
population. The building’s total population of 200 occupants is
composed of academic and administrative staff as well as postgraduate students from a variety of science-related disciplines.
As the NV building consumes less energy per unit of usable
floor area, i.e. 84 kWh/m2 per annum, it is considered to be
‘greener’ than the MM building.
2.3. Measurements
Fig. 1. MM building (Sunny/north facade) featuring operable windows with external
solar shading devices on north-facing windows.
102
Throughout the study, dataloggers have been randomly located
throughout each building to record air temperatures and globe
temperatures at 5-min intervals. Mean radiant temperature was
calculated from the air and globe temperatures from the equation
in ASHRAE [39]. Indoor operative temperature was thus calculated
as the arithmetic average of air and mean radiant temperatures.
Dataloggers were installed within 1-m of the subjects’ workstation,
so as to characterise the immediate thermal environment experienced by the occupant whilst working. In addition to indoor
climate measurements, outdoor air temperature was also recorded
during the survey period at a nearby automatic weather station on
the same campus. Concurrent BMS data from the MM building
during the survey period was collected from the University’s Office
of Facilities Management.
24
M.P. Deuble, R.J. de Dear / Building and Environment 56 (2012) 21e27
Fig. 3. Indoor and outdoor thermal environments comparing the NV and MM buildings for March 2009. Indoor data plots represent daily average of indoor operative temperature
during occupied office hours (0800e1800 hrs).
2.4. Questionnaires
Between March and April in 2009 (the Austral autumn), two
questionnaires (the BUS POE and NEP) were distributed by hand to
all staff in both buildings. For ease of collection and data matching
purposes, questionnaires were administered together as a set. To
preserve occupant anonymity, participants placed their completed
questionnaires inside a blank, sealed envelope which was collected
at the end of each day of the survey period. The two questionnaires
used were:
1. Post-occupancy evaluation: the three-page BUS [40,41] POE is
based on 7-point Likert scales with space for commentary,
covering variables relating to occupant indoor environmental
quality (IEQ) satisfaction, e.g. thermal, visual and acoustic
comfort, indoor air quality, perceived health and productivity,
and general acceptability of the workplace. The BUS methodology is further detailed in BUS [41]. Combinations of these
Likert scores enable the calculation of BUS comfort and satisfaction indices, as well as the forgiveness factor (as defined in
(1)). These questionnaires, in accordance to the original BUS
methodology, were delivered in person to each occupant
within the building.
2. New ecological paradigm: the environmental attitudes questionnaire is a 15-item version of the NEP Scale [1], using 5-point
response scales ranging from Strongly Disagree to Strongly
Agree, with higher scores on the scale from 1 (low) to 5 (high)
indicating greater levels of environmental concern. All scales
were converted to a NEP score by summing each item response
and dividing by the total number of items in the scale. Results
were analysed using MiniTab statistical software.
3. Results
In order to show the differences between each building based on
objective measurements, i.e. internal temperature, it is instructive
to show how both buildings performed under identical weather
conditions. In order to generate congruent results under similar
climatic conditions, both studies were conducted between the
Autumn months of March and April in 2009 and 2010.
3.1. Thermal environment
From operative temperatures averaged across all dataloggers, it
was established that the NV building experienced significantly
warmer temperatures (average ¼ 23.5 C, p ¼ 0.000) than the MM
building over the same period (average ¼ 22.2 C). Fig. 3 highlights
discrepancies between the internal operative temperatures within
these buildings. Temperatures inside both buildings were far
greater than the surrounding outdoor air temperature throughout
the day (mean ¼ 16.3 C, p ¼ 0.000). As an NV building, internal
temperatures closely tracked changes in outdoor weather conditions, whereas the MM building maintained its indoor temperatures within a narrower band. Fig. 3 indicates that indoor operative
temperatures within the MM building rarely exceed 25 C due to
the BMS switching into AC mode whenever average air temperatures reached the 25 C trigger temperature. Less than 10% of
occupied office hours (i.e. 8 ame6 pm weekdays) within this
building experienced indoor operative temperatures greater than
25 C. In contrast, temperatures inside the NV building varied
between 20e28 C. Internal temperatures in the NV building
exceeded the 25 C threshold almost 50% of all occupied office
hours.
Using a 7-day running average of daily mean outdoor temperatures,1 Fig. 3 also presents the 80% thermal acceptability band
limits derived from the ASHRAE Standard 55 adaptive comfort
model [46]. These represent ASHRAE’s suggested range of internal
operative temperatures that should not be exceeded within the
occupied zone [44,45]. As illustrated in Fig. 3 below, average
temperatures inside the NV building exceeded the upper limit of
acceptable adaptive comfort on four separate occasions in March. In
contrast, the MM building never exceeds these limits; in fact indoor
temperature only exceeded the 25 C trigger temperature on three
occasions.
3.2. POE and NEP analysis
In following the BUS methodology [41], both questionnaires
were delivered to all staff in each building and were collected at the
end of the day. In total, 163 POE and NEP questionnaires were
1
Nicol and Humphreys [42] expresses a simplified version of the 7-day running
mean temperature (Trm) equation: Trm ¼ (1 a)Tod 1 þ aTrm 1 Where a is
a constant (0.8), and Tod 1 and Trm 1 are the daily mean outdoor temperature and
running mean temperature for the previous day respectively. In a detailed analysis
of 7-day running mean equations using various decay values, de Dear [43] observes
that a running mean with a ¼ 0.8, as recommended in Nicol and Humphreys [42],
shows small responses to the sudden weather transients as compared to the same
equation with a ¼ 0.6 [44,45] which more closely matches the outdoor air
temperature.
103
25
M.P. Deuble, R.J. de Dear / Building and Environment 56 (2012) 21e27
Table 1
A summary of POE and NEP results for the MM and NV buildings.
Table 2
Analysis of forgiveness factor and NEP results for the MM and NV building.
Study variable
MM (n ¼ 86)
NV (n ¼ 69)
Significance
Forgiveness factora
Comfort indexb
Satisfaction indexc
Perceived productivityd
NEPe
0.99
0.39
0.02
5.34
3.69
1.14
0.28
0.10
8.24
3.99
p ¼ 0.032
Not sig.
Not sig.
p ¼ 0.000
p ¼ 0.002
a
Forgiveness factor typically ranges from 0.8 to 1.2, with scores greater than 1
taken to indicate greater tolerance to the building’s indoor environment.
b
The Comfort Index is calculated as an aggregate of scores for temperature in
summer and winter, ventilation in summer and winter, noise, lighting and overall
comfort variables. The index scores from 3 to þ3 with 0 being regarded as the
optimal result.
c
The Satisfaction Index is derived from an aggregate of scores for design, needs,
health and productivity. This index ranges from 3 to þ3 with 0 being regarded as
the optimal result.
d
Perceived productivity scores are self-assessed by the subject along a 9-point
scale, ranging from 40% decrease to þ40% increase in overall productivity with
scores above 0 regarded as positive.
e
NEP scores range from 1 to 5 with scores greater than 3 taken to indicate proenvironmental levels of concern.
distributed in the MM building and 120 in the NV building.2 With
a 53% response rate, the MM building returned 86 completed
questionnaires (39 males, 47 females), and 69 (30 males; 39
females) were completed from the NV building (57% response rate).
Incomplete responses were omitted from the samples after basic
quality assurance. POE responses for both buildings were benchmarked against the Australian BUS database (as summarised in
Table 1). The NEP questionnaire items were tested for internal
consistency and were found to have strong coefficient alphas
(a ¼ 0.82) suggesting good internal consistency.
As shown in Table 1, both buildings generally measure poorly in
regards to the POE summary variables, such as comfort and satisfaction. As mentioned above, the NV building had internal
temperatures much closer to the acceptable upper limit (as defined
by ASHRAE 55-2010 adaptive standard) compared to the MM
building. However, it was found that this building’s average
forgiveness factor (1.14) was significantly higher than that for the
MM building (0.99, p ¼ 0.032), with scores greater than 1.0 indicating greater levels of tolerance [16]. The NV building had
a significantly higher mean NEP score (3.99, p ¼ 0.002) than the
MM building (3.69), plausible for the majority of environmentally
focussed academics occupying the NV building. Contrary to the
stereotype, the NEP score for the MM building is relatively high for
occupants associated with economics, finance and business studies
as scores greater than 3.0 generally indicate pro-environmental
attitudes.
In order to analyse environmental attitudes and their relationship to forgiveness factors within each building, it was important to
isolate a control group whose scores would not be biased towards
any pro-environmentalism, i.e. those occupants that do not teach in
any environmentally-related disciplines. Ewert and Baker [47]
suggest that environmentally based academics will often have
higher NEP scores compared to academics of non-environmental
disciplines. The NV building is occupied by academics from
a variety of science-based disciplines, including environmental
science. In order to eliminate any potential bias in the NEP
scores, these occupants were subsequently categorised according
to those who teach in the environmental sciences (labelled as the
‘Eco’ group) and those who teach in non-environmental science
2
Questionnaires were administered to all occupants located on floors 6e8 in the
NV building between March and April 2009. A separate follow-up study was conducted in March 2010 using the rest of the occupants (located on floors 2e5).
104
Study variable
Forgiveness factor
NEP
MM (n ¼ 64)
0.99
3.69
NV eco (n ¼ 29)
1.17
4.04
Significance
p ¼ 0.002
p ¼ 0.005
Study variable
Forgiveness factor
NEP
MM (n ¼ 64)
0.99
3.69
NV control (n ¼ 40)
1.04
3.62
Significance
p ¼ 0.04
Not sig.
(e.g. Mathematicians, Physicists and Astronomers were collectively
labelled as the ‘Control’ group). This group was therefore analysed
separately from the environmentally inclined or ‘Eco’ group within
the NV building (summarised in Table 2).
Table 2 indicates that the environmental (Eco) occupants of the
NV building had significantly higher NEP scores (4.04) than those
located inside the MM building (3.69, p ¼ 0.005). However, the
‘control’ occupants had very similar NEP scores (3.62) compared to
the occupants of the MM building (3.69). The levels of tolerance
measured in the MM building (0.99) was significantly lower than
those measured in both staff groups of the NV building (Eco ¼ 1.17,
p ¼ 0.002; Control ¼ 1.04, p ¼ 0.04).
Since the NEP questionnaire items are measured across a 5point Likert scale, responses were binned according to their item
response (from low to high, 1e5). Weighted according to the
number of forgiveness factor samples within each NEP bin, a linear
regression model was fitted to test any correlation between NEP
and forgiveness factor scores for these two case study buildings. As
illustrated in Fig. 4, there is a strong positive correlation between
environmental attitudes and forgiveness factors (R2 ¼ 89%,
p ¼ 0.015) suggesting higher levels of environmental beliefs yielded
higher levels of tolerance.
4. Discussion
With higher temperatures recorded in the NV building (Fig. 3), it
is reasonable to expect that productivity (self-assessed) at
temperatures up to 28 C would be lower than in the MM building
(shown in Table 1). Both case study buildings possess similar
degrees of occupant-orientated environmental control, or adaptive
opportunities [13] to control air movement/ventilation (operable
windows) and lighting (shades, artificial lighting). The only difference being the MM building uses centralised HVAC whenever
indoor temperatures exceed the 25 C trigger temperature. Despite
Fig. 4. Relationship between NEP and forgiveness factor (FF) scores for both study
buildings combined. Numbers next to data points represent sample size for weighted
linear regression model.
26
M.P. Deuble, R.J. de Dear / Building and Environment 56 (2012) 21e27
Table 3
Forgiveness scores by ventilation type: Australian BUS database (n ¼ 45).
Study variable
Forgiveness factor
n
Australian BUS database
This study
Green (NV, ANV, MM)
AC
MM
NV
1.02
22
0.99
23
0.99
1.14
Note: Higher values indicate occupants more tolerant or ‘forgiving’ of the conditions. Building types include natural ventilation (NV), advanced natural ventilation
(ANV), mixed-mode (MM) and air-conditioning (AC).
this, occupants have often complained about indoor temperatures
in summer months, particularly on the north-facing facades. This
anecdotal feedback is consistent with a trend emerging from
Australian green buildings that have undergone the BUS POE [26].
In comparing 22 green buildings against 23 conventional HVAC
office buildings, Leaman et al. [26] reported that green buildings
were perceived as hotter in summer and cooler in winter. Green
buildings, such as the NV and MM buildings in this study, are expected to perform this way. In comparing the ‘forgiveness’ scores
from Leaman et al. [26] (as summarized in Table 3 below) to those
results in Table 1, it was found that the MM building in this study is
poorly perceived by its users (forgiveness ¼ 0.99, equal to that of
conventional AC buildings in Australia). In contrast, the NV building
occupants showed greater tolerance to perceived thermal variance
(forgiveness ¼ 1.14), consistent with other green buildings already
in the BUS Australian database.
The correlation of NEP and forgiveness factors scores shown in
Fig. 4 supports the hypothesis that green building users are more
prepared to overlook and forgive less-than-ideal conditions than
their ‘brown’ (non-green) counterparts suggesting there is
a possible link between occupant satisfaction and environmental
attitudes. Whilst the NEP Scale was originally designed to measure
environmental concern of the general public, with both samples
containing tertiary-educated participants there is a limit to what
can be drawn from these results. Nonetheless, it amplifies how
occupant attitudes and expectations play an important role in the
way green buildings are designed, built and received.
5. Conclusions
It has been previously argued that in order for green buildings to
perform effectively in the context of a low-carbon future, a shift is
required from conceptualizing the occupant as a passive recipient
of indoor conditions, to the inhabitant who may play a more active
role in the maintenance and performance of their building [48,49].
Indoor environment research on thermal comfort [17,18] has shown
that users are more tolerant of conditions where they have more
control, irrespective of whether conditions are physically any
different. One would expect the MM building to have a relatively
higher forgiveness factor than AC buildings in the Australian BUS
database. But these results reflect the nature of the occupants
regardless of the degrees of control or adaptive opportunities
offered by the building. Users appear to be happier if they understand how the building is supposed to work either because the
design intent is made clear and/or because the controls are easy to
understand and work well.
Green buildings have greater thermal variations compared to
their AC counterparts, in which centralised HVAC provides static
indoor temperatures to all occupants all-year round. This paper
suggests green building users are more forgiving of their building,
consistent with the hypothesis that ‘green’ buildings work best
with ‘green’ occupants. Whilst the study only represents
two ‘green’ office buildings from a tertiary institution in Sydney,
Australia, it highlights the increasing awareness to the
psychological dimensions of occupant adaptation, such as attitudes,
expectation and control. However, future studies across a broader
sample of buildings are needed to understand how occupants’ proenvironmental attitudes influence their tolerance of green buildings. In doing so, the causality between forgiveness factor and
green buildings can be investigated further. Given the urgency to
mitigate global warming, it has become apparent that people’s
attitudes, and the behaviours they entail, can be shifted. Whilst
buildings take years to build or months to retrofit, the path to
altering people’s expectations of the built environment presents
another, potentially more accessible strategy. According to this
study, the forgiveness of green buildings can be cultivated. Given
the multitude of sustainable and pro-environmental behaviour
literature, there is great potential for occupants to be ‘re-educated’
about the role buildings play in addressing global climate change.
The emergent practical applications of adaptive building design
calls for the clear communication of intent by designers to the users
and building managers to ultimately assist in the transition to an
energy efficient, low-carbon future.
Acknowledgements
We are enormously grateful to Adrian Leaman for permission to
use the BUS questionnaire under license and his assistance in data
analysis. We would also like to thank Riley Dunlap for his valuable
comments and encouragements, and the University’s OFM, especially Kerry Russell, for their support. Finally, and most importantly,
we express our appreciation to all the building occupants who
responded to the questionnaires.
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Paper 4.2. Thermal Comfort in Mixed-Mode Buildings
Status: Published; Deuble, M.P. and de Dear, R.J. (2012) ‘Mixed-mode buildings: A double
standard in occupants’ comfort expectations’, Building and Environment, 54(8): 53-60
DOI: http://dx.doi.org/10.1016/j.buildenv.2012.01.021
Journal Impact Factor (Thomson Reuters, 2012): 2.131 (Ranked 3 of 53 Construction &
Building Technology journals)
4.2.1. Paper Overview
This paper investigates how MM ventilation affects occupant comfort. In doing so,
this study aims to test whether the adaptive comfort model can be applied to MM buildings,
especially during times of natural ventilation. Coincident indoor and outdoor climate
measurements along with 1359 subjective comfort questionnaires were collected between
March 2009 and April 2010 from the MM building. Both observed thermal sensations
(Actual Mean Vote - AMV) and those predicted using Fanger’s PMV-PPD model (PMV)
show very strong correlations with the indoor operative temperature during AC mode.
However, AMV values during natural ventilation did not conform to the predicted PMV
values suggesting occupants were able to adapt across a fairly broad range of indoor
operative temperatures. Differences in thermal perception were also apparent between these
two modes. Within AC mode, a PMV = +1 (slightly warm) environment elicited significantly
‘warmer-than-neutral’ thermal sensations than the same thermal environmental conditions
within NV mode, suggesting thermal perceptions were affected by the building’s mode of
operation over-and-above the objective indoor climatic conditions. These discrepancies
between thermal comfort during AC and NV mode emphasise the complexity of thermal
perception and the inadequacy of using PMV models to describe occupant comfort in MM
107
buildings. Results from this study shed light as to how MM buildings, especially those
featuring change-over control strategies, should be categorised in future comfort standards.
108
Building and Environment 54 (2012) 53e60
Contents lists available at SciVerse ScienceDirect
Building and Environment
journal homepage: www.elsevier.com/locate/buildenv
Mixed-mode buildings: A double standard in occupants’ comfort expectations
Max Paul Deuble a, *, Richard John de Dear b
a
b
Department of Environment and Geography, Faculty of Science, Macquarie University, Building E7A, Sydney NSW 2109, Australia
Faculty of Architecture, Design and Planning, The University of Sydney, Sydney NSW 2006, Australia
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 6 December 2011
Received in revised form
24 January 2012
Accepted 25 January 2012
This paper investigates how mixed-mode (MM) ventilation affects occupant comfort by presenting
results from a longitudinal field study within an academic office building from a tertiary educational
institution in sub-tropical Sydney, Australia. The building automatically switches into air-conditioned
(AC) mode whenever indoor temperatures exceed 25 C. Coincident indoor and outdoor climate
measurements along with 1359 subjective comfort questionnaires were collected. Thermal sensations
during natural ventilation did not conform to those predicted using Fanger’s PMV-PPD [1]. Differences in
thermal perception were also apparent between these two modes. Within AC mode, a PMV ¼ þ1
environment elicited much ‘warmer-than-neutral’ thermal sensations than the same PMV ¼ þ1 environment within naturally-ventilated (NV) mode, suggesting thermal subjective perceptions were
affected by the building’s mode of operation over and above the objective indoor climatic conditions.
These discrepancies emphasize the complexity of thermal perception and the inadequacy of using PMV
models to describe occupant comfort in MM buildings. ASHRAE’s Standard 55 [2] currently classifies MM
buildings as AC buildings, and as such, limits the operation of these buildings to the more restrictive
PMV-PPD range of indoor thermal conditions. In contrast, EN15251 [3] permits the more flexible
adaptive comfort standard to be applied to buildings operating under NV mode. Results from this study
favour EN15251’s application of the adaptive comfort model instead of PMV-PPD to MM buildings when
they are operating in NV mode.
Ó 2012 Elsevier Ltd. All rights reserved.
Keywords:
Thermal comfort
Mixed-mode ventilation
Adaptive comfort standards
Adaptive model
1. Introduction
Prior to the 21st century, office buildings were generally
designed with a building-centred, energy intensive approach
focussed on providing standardised indoor climates for all occupants by relying on heating, ventilation and cooling (HVAC) technology. Intended to minimise legal liability and maximise comfort,
the primary purpose of HVAC was to maintain constant thermal
environmental conditions throughout the interior aiming for an
optimum ‘steady-state’ temperature setting based on Fanger’s
Predicted Mean Vote and Predicted Percentage Dissatisfied (PMVPPD) model [1]. In contrast, more recent studies [e.g [4e8].] have
made the case for greater environmental variation inside buildings,
either via user adjustments to windows and shade devices or by
other adaptive opportunities that more closely match indoor
thermal conditions to prevailing outdoor temperatures. This
person-centred approach deliberately provides variability across
time and space [9e11]. Spatially, thermally differentiated zones can
accommodate a variety of individual thermal requirements.
Temporally, indoor temperatures can gradually drift towards
outdoor conditions and encourage occupant adaptations such as
clothing changes and use of operable windows. This paper investigates how MM ventilation affects occupant comfort by presenting
results from a longitudinal field study within an office building
located in sub-tropical Sydney, Australia. Both observed and predicted thermal sensation votes recorded in AC and NV modes were
compared to test whether the adaptive comfort model can be
applied to MM buildings, especially during times of natural ventilation. By evaluating the current definition and scope of the adaptive comfort standards in ASHRAE 55-2010 and EN15251-2007, the
implications of this research are discussed in the context of
whether adaptive comfort standards for NV buildings should be
applied to MM buildings.
1.1. Adaptive thermal comfort and mixed-mode ventilation
The ‘adaptive’ thermal comfort model [5,12,13] has advocated
the shift towards variable indoor thermal environmental conditions in support of sustainable building design, i.e. providing
thermal comfort while reducing energy use and associated
* Corresponding author. Tel.: þ61 2 9850 8396.
E-mail address: max.deuble@students.mq.edu.au (M.P. Deuble).
0360-1323/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved.
doi:10.1016/j.buildenv.2012.01.021
109
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M.P. Deuble, R.J. de Dear / Building and Environment 54 (2012) 53e60
greenhouse gas emissions. The move towards sustainability
involves decreasing the reliance on active systems and pursuing
more passive strategies of building thermal control. One alternative
is naturally-ventilated (NV) buildings with occupant-controlled
windows; however, while people may prefer greater “adaptive
opportunities” [4,14], they may not appreciate the thermally
uncomfortable conditions potentially occurring in such buildings
during unusually hot or cold weather conditions. ‘Mixed-Mode’
(MM) ventilation represents a way of combining the best features
of NV and AC buildings [15,16].
Over 150 MM buildings around the world have been documented in an online register [17], however despite this increasing
interest in enabling comfort whilst reducing reliance on HVAC
systems and its subsequent energy consumption, there remains
a lack of thermal comfort research conducted in these buildings.
The basic concept of MM or ‘hybrid’ ventilation is to maintain
satisfactory indoor environments whilst minimising the significant
energy use and operating costs associated with air conditioning by
alternating between and combining natural and mechanical
systems. MM buildings provide good air quality and thermal
comfort using an NV or ‘free-running’ mode whenever the outdoor
weather conditions are favourable, but revert to mechanical
systems for HVAC whenever or wherever external conditions make
the NV option untenable for occupants [15,18e20]. Such a building
requires intelligent control systems that can switch automatically
between natural and mechanical modes in such a way that minimises energy consumption [21e23], and without compromising
indoor air quality or thermal comfort of its occupants [24].
1.2. International comfort standards: ASHRAE standard 55 vs.
EN15251
Existing international comfort standards, such as the American
Society of Heating, Refrigerating and Air Conditioning Engineers
(ASHRAE) Standard 55 ‘Thermal environmental conditions for human
occupancy’ [2], the Comite Europeen de Normalisation (CEN)
Standard EN15251 ‘Indoor environmental input parameters for design
and assessment of energy performance of buildings: addressing indoor
air quality, thermal environment, lighting and acoustics’ [3] and the
International Organization for Standardization (ISO) Standard 7730
‘Moderate thermal environments e calculation of the PMV and PPD
thermal comfort indices’ [25] specify combinations of temperature
and humidity, indoor environments and personal factors that will
be deemed acceptable to 80% or more of the occupants. However,
following the international standardisation of Fanger’s [1] PMVPPD model of thermal comfort, subsequent comfort research,
along with the revision of these standards, has been met with much
political and industrial backlash. Earlier versions mainly cover
thermal comfort under steady-state conditions based on laboratory
experiments; however, more recent revisions have utilised global
field study databases, e.g. ASHRAE RP-884 [13] and Smart Controls
and Thermal Comfort (SCATS) [26]. This multitude of field data
highlighted the inadequacy of ‘static’ models, like PMV-PPD for
describing thermal comfort in ‘free-running’ buildings [13,26,27]
which led to the inclusion of an adaptive comfort standard in the
2004 edition of ASHRAE’s Standard 55 as an alternative to the PMVbased method for NV buildings [12,28]. In the years following the
publication of ASHRAE’s adaptive comfort model, a European
counterpart named SCATS [24] replicated the exercise in a longitudinal design in which 26 offices located in European countries,
such as France, Greece, Portugal, Sweden and the UK, were
surveyed over approximately one year. Originally intended to
develop a European adaptive comfort algorithm, the SCATS project
was later used in the development of the adaptive comfort annex in
the European EN15251 standard [3,24].
But at the time of ASHRAE 55-2004 going to press, insufficient
comfort studies undertaken in MM buildings meant they were
excluded from the scope of the adaptive comfort standard [28].
Despite the most recent revisions to the standard [2] the adaptive
comfort standard is still constrained in scope to naturally conditioned, occupant-controlled spaces in which thermal comfort
conditions are primarily regulated by operable windows. Furthermore, ASHRAE clarifies that when mechanical cooling systems are
provided for the space, as is the case in MM buildings, the adaptive
comfort standard is not applicable [12,29]. Thus, the potential
flexibility offered by the standard is not available to hybrid buildings, which may operate in a passive, natural ventilation mode
preferentially, equipped with only supplemental cooling/heating
for peak periods; or to spaces where operable elements are not
connected to the outdoors. As a result, such spaces or buildings
must therefore resort to the more restrictive PMV-PPD method
[4,12,28,29]. This begs the question as to why MM buildings are
precluded from applying the adaptive comfort standard in their NV
mode of operation. The European counterpart, EN15251 [3], mainly
describes non-adaptive temperature limits for various building
uses, e.g. offices, schools, etc. If certain conditions are met, i.e. (1)
having access to operable windows; and (2) no strict clothing
protocol, then the standard allows the use of the more relaxed
(upper) temperature limits stated in the adaptive model of the
standard (Annex 2) [3]. Furthermore, EN15251 allows the more
flexible adaptive comfort standard to be applied to NV buildings
which can include MM buildings during times when they are not
employing mechanical cooling, i.e. whilst in NV or ‘free-running’
mode. Currently, the International Standard ISO 7730 [25] makes
no allowance for differences in NV and mechanically cooled or ‘AC’
buildings, so it will not be discussed any further in this paper.
2. Methods
2.1. Sydney’s climate
The Sydney metropolitan region is located on the eastern coast
of Australia (34 S, 151 E) and is characterised by a moderate subtropical climate. Influenced from complex elevated topography
surrounding the region to the north, west and south and due to
close proximity to the Tasman Sea to the east, Sydney avoids the
high temperatures commonly associated with more inland regions
of the same latitude [30]. The summer months of December to
February can be described as warm-to-hot with moderate-to-high
humidity peaking in February to March. Between June and August,
Sydney experiences cool-to-cold winters. The study building site is
located in the suburbs, 16 km north-west of Sydney’s central
business district (33 460 S, 151 60 E). Seasonal variations range
from mean summer daily maximum temperatures of 26e28 C,
a mean winter daily maximum of 17 C and an annual mean daily
maximum of 22e23 C (as shown in Fig. 1). Mean minimum daily
temperatures range from 5 to 8 C in winter, to 17e18 C over the
summer months, with an annual daily minimum temperature of
11e13 C [31]. Given the city’s seasonal variations, Sydney’s climate
is well suited to MM buildings. For much of the year, thermal
comfort indoors can be easily achieved through simple passive
design principles and various adaptive behaviours employed by the
occupants, such as opening/closing windows, adjusting their
clothing or by change of position [32,33].
2.2. Case study building
The building is located within the Sydney metropolitan region.
Commissioned in 2006, the building (presented in Figs. 2, 3a, b,
4a, b and 5 below) is a 7-storey office building occupied by
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M.P. Deuble, R.J. de Dear / Building and Environment 54 (2012) 53e60
55
collected throughout this study. Dataloggers were randomly
located throughout the building to record air temperature, globe
temperature and relative humidity at 5 min intervals throughout
the study. The study was conducted over twelve months (March
2009eApril 2010) to represent the full cycle of the seasons. Air
velocity was measured during each questionnaire session using
a handheld hot-wire anemometer (TSI VelociCalc). Loggers were
placed within 1 m of the occupants’ workstation to characterise the
immediate thermal environment experienced by the occupant
under normal working conditions. Outdoor weather observations
were obtained from a nearby automatic weather station. The
building’s AC/NV mode status and indoor temperature records
were collected from the BMS after the study had finished.
Fig. 1. Climatology of the case study building site [adapted from 31].
academic and administrative staff from a university Faculty of
Business and Economics. This building forms part of a larger study
and since it is co-located with a conventionally NV building occupied by the same organisation, makes it an ideal field study. As
depicted in Fig. 2, the north and south perimeter zones consist of
MM cellular offices with operable windows separated by a central
open-plan office zone with full-time air-conditioning. Automated
high and low external louvres provide natural ventilation to each
floor, with adjustable internal grilles to control airflow, supplemented by user-operable windows with additional solar shading
features over the northern (sun-facing) windows (Fig. 3a and
b present the building as photographed from the north and south,
respectively). Indoor temperature and outdoor weather sensors
prompt the Building Management System (BMS) to switch (or
‘change-over’) into AC mode whenever a temperature greater than
25 C is sensed within any zone. During AC mode, internal
temperatures are maintained at 24 C (1 C) as defined in the
building’s algorithm. BMS switch-over to NV is conditional when
external meteorological conditions and the indoor thermal climate
fall into an acceptable zone for the occupants. Fig. 4a and b show
examples of the subjects’ offices monitored throughout the study,
indicating the location of the datalogger in relation to the occupant’s workspace. As shown in Fig. 5, panels located at the entrance
of each corridor indicate the current NV/AC mode of operation of
each zone. By viewing these panels, building users know whether
their office in their respective zone is in AC or NV mode. It should be
noted that during NV mode, occupants are able to operate their
windows. Whilst the building is in AC mode, windows can only be
opened after the AC system has been active for at least 5 min.
2.3. Data collection and analysis
Simultaneous objective (indoor and outdoor climate) and
subjective (self-assessed comfort perceptions) measurements were
2.3.1. Comfort questionnaires
Paper-based subjective comfort questionnaires were delivered
to each participant in their normal workstation. Derived from
ASHRAE-sponsored field experiments [34], the questionnaires
were used to record occupant perceptions of their thermal environment on a ‘right-here-right-now’ basis. Subjects were asked to
assess their thermal sensation along the ASHRAE 7-point scale,
which included the possibility of fractional votes placed between
two comfort categories. Thermal acceptability was addressed as
a binary ‘acceptable’ or ‘unacceptable’ response with thermal
preference being assessed on the 3-point McIntyre scale [35],
wherein occupants listed if they preferred to be ‘warmer’, ‘cooler’
or ‘no change’. The air movement questions focused on air movement acceptability as it related to the air speed. Subjects registered
if the air velocity was ‘acceptable’ or ‘unacceptable’ and their
reason, whether it was ‘too low’, ‘too high’ or ‘enough’ air movement. Subjects were also asked if they preferred ‘more’ or ‘less air
movement’ or ‘no change’. Standardised self-assessed clothing
garment (clo) and metabolic activity checklists [36,37] within the
subjective comfort questionnaires allowed the calculation of
various comfort indices using ASHRAE’s WinComf software [38],
including Predicted Mean Vote (PMV) and Predicted Percentage
Dissatisfied (PPD). Lastly, a section was added for the researcher to
identify the location and mode of operation for each participant’s
office at the time of each questionnaire.
3. Results
Due to the ethical processes involved with the project, subject
participation was purely voluntary, as is the case for many thermal
comfort field studies. Whilst the initial response rate was low, representing approximately one third of the total building population,
this is still comparable to field studies cited in the literature, such as
[8]. Any bias in the results are likely to be negligible, however should
be taken into consideration when drawing conclusions from this
Fig. 2. Typical floor plan of the commerce building (shaded area indicates the location of the office in Fig. 4a and b).
111
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M.P. Deuble, R.J. de Dear / Building and Environment 54 (2012) 53e60
Fig. 3. The case study building as viewed from the a) North facade and b) South façade.
study. Nonetheless, a sample of 60 occupants was recruited for this
study. A total of 1359 comfort questionnaires were completed (with
an average of 23 responses per subject) during normal occupied
office hours (0800e1800 h), with representative coverage of both
genders (643 males and 716 females). At the time of each survey,
the operational mode of each respective occupant’s zone was
noted, i.e. AC or NV mode via the AC display panel located at the
entrance of each corridor (see Fig. 5). These were later verified
using the building’s BMS data wherein the status of each mode was
logged in 5 min intervals across the duration of the study. The North
and South perimeter offices switch between both AC and NV modes
and the Central core is provided with constant air conditioning.
Therefore, the Central zone has not been included in the following
analyses because it does not operate under mixed-modes. It should
be noted that, since the data was binned before plotting, linear
regression analyses were therefore weighted according to the
sample size within each degree bin (Figs. 6e10).
3.1. Thermal environment
Indoor operative temperatures calculated from the workstation
dataloggers reveal the range of temperatures occupants experienced within the building. Fig. 6 below demonstrates the indoor
operative and concurrent outdoor temperatures recorded
throughout the study. It clearly demonstrates the internal environment (in both North and South zones) rarely exceeds an indoor
operative temperature of 25 C, suggesting the building’s algorithm
works well to maintain indoor temperatures within the 5 C band
(20 Ce25 C) programmed into it. The graph in Fig. 6 represents the
average indoor operative temperature plotted against each 1 C
outdoor temperature bin. All internal temperatures that were
recorded within the limits of each degree of outdoor temperature,
i.e. between 21.5 and 22.49 C, were counted and the average indoor
operative temperature was calculated and plotted against its corresponding degree bin. Despite demonstrating significant correlations with the outdoor temperature, (AC Mode: p ¼ 0.000; NV Mode:
p ¼ 0.0018), Fig. 6 suggests that outdoor temperatures only
explained half of the variability in indoor operative temperatures in
NV mode (R2 ¼ 48%) compared to those in AC mode (R2 ¼ 83%). This
is likely due to the broader range of temperatures allowed during AC
mode operation as opposed to the very narrow range of outdoor and
indoor temperature conditions required for natural ventilation.
Table 1 below summarizes the key comfort parameters
measured throughout this study. Two sample t-tests were performed to find any significant differences between each mode.
Whilst the average air velocity, indoor operative temperature and
relative humidity were relatively unchanged between the two
modes, observed thermal sensations, i.e. Actual Mean Vote (AMV),
during NV mode (0.43) were found to be significantly higher than
those in the AC mode (0.19, p ¼ 0.001). Correspondingly, the
average clo values reported within NV mode (0.50) were significantly lower than those recorded during AC mode (0.57, p ¼ 0.000)
suggesting most people found the building to be slightly warmer
during periods of natural ventilation possibly due to the increased
indoor temperatures needed for the BMS algorithm to switch into
AC mode. Due to these increases in indoor temperatures within NV
mode, PMV and PPD values were also significantly different
between the two modes. The average PMV was significantly higher
Fig. 4. a) Typical layout of occupant offices monitored throughout the study (office located in south zone as indicated in Fig. 2 above) and b) shows the location of the datalogger in
relation to the occupant’s workspace.
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M.P. Deuble, R.J. de Dear / Building and Environment 54 (2012) 53e60
57
Fig. 7. Indoor operative temperature plotted against individual Actual Mean Vote
(AMV) values recorded during AC mode (diamonds) and NV mode (squares).
Fig. 5. Air-conditioning control panel located at the entrance of each corridor.
during AC mode ( 0.15) compared to the average PMV within NV
mode ( 0.32, p ¼ 0.000). Consequently, PPD values between these
two modes were also different, with AC mode generating a slightly
lower percentage of dissatisfied peoples (12%) compared to those in
NV mode (14%, p ¼ 0.0015). Actual Percentage Dissatisfied (APD) is
derived from the ratio of occupants who found the immediate
thermal environment unacceptable over those who found it to be
acceptable. During AC mode, 27% of participants surveyed were
dissatisfied with the thermal environment, whereas only 19% of
subjects expressed dissatisfaction during times of natural ventilation. These values were found to be much higher than the calculated PPD values. Whilst these AMV and PMV results still represent
neutral thermal sensation votes (between 0.5 and þ0.5), they
suggest that the switching of the building from one mode to the
other may cause changes in how the occupants perceive their
thermal environment. Accordingly, this paper will only focus on the
results from the analysis of indoor operative temperature, and
Actual and Predicted Mean Votes between each mode.
3.2. Actual vs. Predicted Mean Votes
Fig. 7 illustrates the range of individual thermal sensations
recorded throughout the study in both modes (labelled as AMV) on
which participants rated their level of comfort across a 7-point
scale (ranging from Cold ( 3) through Neutral (0) to Hot (þ3)). It
should be noted that participants were able to register votes in
between each of the 7 comfort categories, e.g. if the subject placed
a tick half way between Neutral (0) and Slightly Warm (þ1), the
vote was regarded as þ0.5. Diamonds represent all individual
Fig. 6. Binned outdoor temperatures plotted against average concurrent indoor
operative temperature (Top) for AC mode (dashed line with diamonds) and NV mode
(solid line with squares).
113
comfort votes recorded during AC mode, and squares represent
those measured in NV mode. In order to investigate how comfort
was affected in a building that switches from AC to NV conditions
and vice versa, it was necessary to perform separate statistical
analyses for each mode. Figs. 8e10 present the average thermal
sensation votes found within each 1 C wide indoor operative
temperature bin. Indoor operative temperature represents a calculated index of air temperature, radiant temperature and air speed.
All votes that were recorded within the limits of each degree were
counted and the average response was calculated and plotted
against its corresponding degree bin. Since the data was binned,
linear regression analyses were weighted according to the sample
size in each degree bin to ensure any outliers representing small
sample sizes had relatively little effect on the slope of the model.
The graph in Fig. 8 presents weighted linear regressions of both
observed thermal sensation votes (AMV) and those predicted using
Fanger’s PMV index on indoor operative temperature [1]. There are
strong positive relationships for both AMV (R2 ¼ 95%) and PMV
(R2 ¼ 97%) responses against the indoor operative temperature
(p ¼ 0.000). AMV and PMV responses were then separated according
to mode to investigate any differences between AC and NV modes.
The graphs in Fig. 9a and b present the results for AC mode and
NV mode respectively. All correlations against the indoor operative
temperature were found to be significant (p < 0.05) showing strong
positive relationships (R2 values ranged from 76% to 97%). Whereas
the observed AMV values in Fig. 9a conform very well to the PMVPPD model, there is a clear difference between thermal sensation
and operative temperature during NV mode. The PMV model in
Fig. 9b fails to predict thermal comfort when the building is in NV
mode. Whilst eliciting strong correlations for AMV (R2 ¼ 76%,
p ¼ 0.003) and PMV (R2 ¼ 91%, p ¼ 0.000) responses, the gentle
gradient for observed AMV values suggests occupants were able to
adapt across a fairly broad range of indoor operative temperatures
Fig. 8. Average observed (AMV e dashed line with diamonds) and predicted (PMV e
solid line with squares) thermal sensation votes plotted against binned indoor operative temperature for both AC and NV modes of building operation.
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M.P. Deuble, R.J. de Dear / Building and Environment 54 (2012) 53e60
Table 1
Summary of study variables and calculated indices for AC and NV modes.
Variable
Indoor Operative
Temperature ( C)
Relative Humidity (%)
Air Velocity (m/s)
Clothing Insulation (clo)
Metabolic Rate (met)
Self-Assessed Productivity (%)
Calculated Indices
Actual Mean Vote (AMV)
Actual Percentage
Dissatisfied (APD)
Predicted Mean Vote (PMV)
Predicted Percentage
Dissatisfied (PPD)
Neutral Temperature ( C)
Effective Temperature (ET*)
Standard Effective
Temperature (SET*)
AC mode
(n ¼ 804)
NV mode
(n ¼ 294)
Significance
23.29 C
23.13 C
p ¼ 0.175
52.8%
0.09 m/s
0.57
1.20
1.16%
52.1%
0.10 m/s
0.50
1.22
0.90%
p
p
p
p
p
0.19
27%
0.43
19%
p ¼ 0.000*
NA
0.15
0.12
0.32
0.14
p ¼ 0.000*
p ¼ 0.015*
22.6 C
23.36 C
24.03 C
17.8 C
23.19 C
23.34 C
NA
p ¼ 0.158
p ¼ 0.000*
¼
¼
¼
¼
¼
0.403
0.01*
0.000*
0.05
0.000*
*Indicates a significant difference with a p-value < 0.05.
Fig. 9. Average observed (AMV e dashed lines with diamonds) and predicted (PMV e
solid line with squares) thermal sensation votes plotted against binned indoor operative temperature for a) AC mode and b) NV modes of building operation.
but their thermal sensations seem to be permanently displaced into
the ‘slightly warm’ region.
Fig. 10 below evidences the effects of adaptation during NV
mode of building operation. As the slope of the line reaches zero, i.e.
indicating negligible change in sensation across the entire range of
indoor operative temperatures, then the occupants must be
accommodating these diverse temperatures through a suite of
‘adaptive opportunities’ [4]. Consequently, as the AMV votes
recorded during AC mode were well matched with those predicted
using the PMV model and their regression coefficient is further
away from zero compared to their NV counterparts, then the
occupants are not adapting to the diverse temperatures experienced within this mode as well as their NV counterparts. Additionally, Fig. 10 also demonstrates the differences in thermal
sensations between these two modes beyond what the thermal
environmental conditions would suggest. Within AC mode, a þ1
PMV environment elicited much ‘warmer-than-neutral’ thermal
sensations compared to the same thermal environment during NV
mode, suggesting thermal perceptions were affected by the
Fig. 10. Average observed (AMV) thermal sensation votes plotted against binned
indoor operative temperature for AC mode (dashed line with diamonds) and NV mode
(solid line with squares).
building’s mode of operation beyond biophysical heat balance
differences.
4. Discussions
The MM building operates as a passive NV building between the
indoor operative temperatures of 20e25 C. Demonstrated in
Figs. 6 and 7, the BMS algorithm ensures comfortable conditions
between these extremes, with internal temperatures rarely rising
above 25 C (some exceptions due to excessive solar heat gains on
the north). If a temperature above 25 C is sensed by the building’s
BMS sensors in any particular zone, air conditioning switches on for
that zone, trimming indoor temperatures back towards the 24 C
set point (0.5 C). This is reflected in Table 1, suggesting occupants
tend to feel slightly warmer leading up to an NV-AC mode switchover event.
Figs. 8e10 present the key findings of this research, showing
fundamental differences between the observed thermal sensation
votes (AMV) and those predicted using Fanger’s PMV-PPD model
(PMV). Fig. 8 highlights the different neutral temperatures calculated
from each model. On average, the AMV neutral temperature was
2.1 C cooler than the PMV predictions. Both the observed and predicted thermal sensation votes show very strong correlations with
the indoor operative temperature during AC mode (as shown in
Fig. 9a, PMV: R2 ¼ 98%, p ¼ 0.000; AMV: R2 ¼ 97%, p ¼ 0.000). Both
models successfully describe occupant comfort within this mode.
Fig. 9b suggests that differences in thermal perception were also
apparent between these two modes. During AC mode of operation,
a þ1 PMV (slightly warm) environment elicited significantly warmerthan-neutral thermal sensations than the same thermal environmental conditions under NV mode, suggesting thermal perceptions
were affected by the building’s mode of operation over-and-above
any differences in actual thermal environmental conditions. By
viewing the AC display panel (Fig. 5) upon entering the respective
corridor to their office, occupants know the current mode of operation, either AC or NV. These findings suggest that once they are aware
that the building has switched to NV mode, their expectations of the
thermal environment change to correspond with changes in their
degree of freedom to open their windows. It is also likely that the
ratio of outdoor ventilation to air velocity would be greater under NV
mode than in AC mode, so it is possible that improved thermal
comfort under NV mode could have resulted from cross-modal
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M.P. Deuble, R.J. de Dear / Building and Environment 54 (2012) 53e60
interactions between air quality and thermal comfort. Whilst
previous studies reflect building-by-building comfort temperatures,
such as de Dear and Brager [28] and Nicol and Humphreys [12], Fig. 10
clearly shows the adaptive model is best suited to explain occupant
comfort during times of natural ventilation within the same building.
When operating in AC mode, Fanger’s PMV-PPD model shows good
correlations with observed thermal sensations.
The adaptive comfort standards defined in ASHRAE Standard 55
[2] and EN15251 [3], based on the respective works of de Dear and
Brager [28] and Nicol and Humphreys [12], were established as an
alternative to PMV-PPD for NV buildings. Ongoing debates suggest
the adaptive comfort standard should be applied as an operating
guideline for the NV mode of MM buildings. Figs. 6 and 7 clearly
show that interior temperatures can be allowed to float within the
more energy-efficient acceptability limits of the adaptive comfort
standard and still ensure comfortable conditions for the occupants.
When temperatures reach the maximum limits then HVAC systems
can be turned on in a limited way to ensure temperatures stay
within the adaptive comfort standard limits (rather than switching
to the narrow set points of a centrally-controlled AC building).
Within the context of the American and European adaptive standards, results from this study favour EN15251’s application of the
adaptive comfort model instead of the PMV-PPD to MM buildings
when they are operating in NV mode.
5. Conclusions
This paper investigates how occupant comfort is affected in
a building that switches between AC and NV environments, i.e. in
a MM building. Current international comfort standards still
embody black-and-white definitions of AC and NV buildings. If
a building is AC, then it typically doesn’t have operable windows.
According to ASHRAE Standard 55 [2] if a building is NV, then it
doesn’t have any mechanical cooling/heating systems, but typically
has operable windows. However, the real world is not so simple. The
most current version of ASHRAE Standard 55-2010 misclassifies MM
buildings as AC and in doing so, not only limits the operation of such
buildings to the more restrictive PMV-PPD range of indoor thermal
conditions, but fails to maximise the energy saving potential of MM
buildings. By comparing both observed and predicted thermal
sensation votes recorded in AC and NV modes, the adaptive comfort
model was found to be applicable to the MM building, especially
during times of natural ventilation. In evaluating the current definition and scope of the adaptive comfort standards in ASHRAE 552010 and EN15251-2007, this paper provides evidence that MM
buildings could in fact be defined as NV, with operable windows and
supplemental cooling/heating during peak periods. Whilst this
study represents one particular change-over MM case study in
Sydney, Australia, many other types of MM buildings exist around
the world, e.g. concurrent (where air-conditioning and operable
windows are utilised in the same space and at the same time) and
zoned (when passive and mechanical strategies occur at the same
time but in different zones within the building). These findings help
shed light as to how MM buildings, especially with change-over
control strategies, should be categorised in future comfort standards. However, as more MM buildings are likely to be built in the
future, more field studies (using different control strategies and in
different climates) are needed to fully understand how MM ventilation affects occupant comfort and whether a new MM comfort
standard should be established.
Acknowledgements
This project was funded in part by an Australian Research
Council Discovery Grant (DP0880968). We are enormously grateful
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to Kerry Russell and the University’s Office of Facilities Management for assistance in gathering data. We would like to express our
appreciation to all the participants who gave their time to respond
to our questionnaires.
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energy performance of buildings: addressing indoor air quality, thermal
environment, lighting and acoustics. EN15251. Brussels: Comite Europeen de
Normalisation; 2007.
[4] Baker N, Standeven M. Thermal comfort for free running buildings. Energy
and Buildings 1996;23(3):175e82.
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[8] Rowe D. Thermal comfort in a naturally-ventilated environment with
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[9] Brager GS, de Dear RJ. Thermal adaptation in the built environment: a literature review. Energy and Buildings 1998;27(1):83e96.
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[11] Kwok A 2000. Thermal Boredom, Proceedings of the 17th International
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[12] Nicol F, Humphreys MA. Adaptive thermal comfort and sustainable thermal
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[13] de Dear RJ, Brager G. Developing an adaptive model of thermal comfort and
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[15] Brager G. Mixed-mode cooling. ASHRAE Journal; 2006:4830e7.
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conditions for thermal comfort. ISO Standard 7730: Moderate Thermal Environments. Geneva, Switzerland: International Organisation for Standardisation; 2005.
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comfort in free-running buildings in European standard EN15251. Building
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naturally-ventilated offices in Thailand. Energy and Buildings 1992;18(3e4):
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revisions to ASHRAE Standard 55. Energy and Buildings 2002;34(6):
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[29] Turner S 2008. ASHRAEs Thermal Comfort Standard in America: Future steps
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averages/tables/cw_066156.shtml; 2011.
[32] Rowe D. A study of a mixed mode environment in 25 cellular offices at the
University of Sydney. International Journal of Ventilation: HybVent e Hybrid
Ventilation 2003;1(4):53e64. Special Edition.
[33] Aggerholm S. Hybrid ventilation and control strategies in the annex 35 case
studies. IEA Annex 35 Technical Report. Hertfordshire, UK: International
Energy Agency; 2002.
[34] Cena K, de Dear R. Field study of occupant comfort and office thermal environments in a hot-arid climate. Final Report RP-921. ASHRAE; 1998.
[35] McIntyre DA. Indoor climate. London, UK: Applied Science Publishers Ltd; 1980.
[36] ASHRAE. Chapter 8: thermal comfort. In: ASHRAE, editor. Handbook of
fundamentals. Atlanta, Georgia: American Society of Heating, Refrigerating
and Air-Conditioning Engineers; 2001.
[37] ISO. Ergonomics of the thermal environment: estimation of the thermal
insulation and evaporative resistance of a clothing ensemble. ISO/CD 9920.
Geneva, Switzerland: International Standards Organisation; 2003.
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profession. ASHRAE Transactions 1997;103(2):63e9.
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Paper 4.3. The Validity of Contemporary Post-Occupancy Evaluation Methods
Status: Submitted May 2012; Deuble, M.P and de Dear, R.J. (2012) ‘Is it hot in here or is it
just me? Validating the post-occupancy evaluation’, Intelligent Buildings International (Refer
to Appendix P for corresponding emails)
Journal Impact Factor: Not applicable – new journal (started in 2009)
4.3.1. Paper Overview
Data gathered from the preceding studies (Papers 4.1 and 4.2) were used to
investigate the differences in occupant satisfaction and comfort perceptions between each
case study building, as well as between the POE and comfort questionnaires. Results from the
POE surveys presented in Paper 4.1 suggest high levels of occupant dissatisfaction, especially
in the MM building. In order to test the validity of these results, parallel thermal comfort
studies were conducted to investigate the differences in occupant satisfaction and comfort
perceptions between these two questionnaires. Instrumental measurements of each building’s
indoor environment reveal that occupants tended to over-exaggerate their POE comfort
responses. Analysis of thermal satisfaction and acceptability in each building indicate that
occupants of the NV building were more tolerant of their thermal environment despite
experiencing significantly warmer temperatures than their MM counterparts. In discussing
these results, along with participant comments and anecdotal evidence from each building,
this paper contends that POE does not accurately evaluate building performance, suggesting
occupants can and do use POE as a vehicle for complaint about general workplace issues,
unrelated to their building. In providing a critical review of current POE methods, this paper
aims to provide recommendations as to how they can be improved, encouraging a more
holistic approach to building performance evaluation.
117
Is It Hot In Here Or Is It Just Me? Validating the Post-Occupancy
Evaluation
Authors: Max Paul Deuble1* and Richard John de Dear2
1
Department of Environment and Geography, Faculty of Science, Macquarie University,
Sydney, NSW 2109, Australia, Email: max.deuble@students.mq.edu.au
2
Faculty of Architecture, Design and Planning, The University of Sydney, Sydney, NSW
2006, Australia
Corresponding Author’s Telephone: +61(2) 9850 8396
*
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Submission to Intelligent Buildings International
Is It Hot In Here Or Is It Just Me? Validating the PostOccupancy Evaluation
Journal:
Intelligent Buildings International
Manuscript ID:
12-IB046-RA.R1
Manuscript Type:
Research Article
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Keywords:
Post-Occupancy Evaluation, Thermal Comfort, Performance Evaluation,
Occupant Comfort, Indoor Environmental Quality
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Abstract
Historically, post-occupancy evaluation (POE) was developed to evaluate
actual building performance, providing feedback for architects and building managers
to potentially improve the quality and operation of the building. Whilst useful in
gathering information based on user satisfaction, POE studies have typically lacked
contextual information, continued feedback and physical measurements of the
building’s indoor climate. They therefore sometimes over-exaggerate poor building
performance. POEs conducted in two academic office buildings: a mixed-mode (MM)
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and a naturally-ventilated (NV) building located within a university in Sydney
Australia, suggest high levels of occupant dissatisfaction, especially in the MM
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building. In order to test the validity of the POE results, parallel thermal comfort
studies were conducted to investigate the differences in occupant satisfaction and
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comfort perceptions between these two questionnaires. Instrumental measurements of
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each building’s indoor environment reveal that occupants tended to over-exaggerate
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their POE comfort responses. Analysis of thermal satisfaction and acceptability in
each building indicate that occupants of the NV building were more tolerant of their
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thermal environment despite experiencing significantly warmer temperatures than
their MM counterparts. In discussing these results, along with participant comments
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and anecdotal evidence from each building, this paper contends that POE does not
accurately evaluate building performance, suggesting occupants can and do use POE
as a vehicle for complaint about general workplace issues, unrelated to their building.
In providing a critical review of current POE methods, this paper aims to provide
recommendations as to how they can be improved, encouraging a more holistic
approach to building performance evaluation.
Keywords: Post-occupancy evaluation (POE), occupant satisfaction, adaptive thermal
comfort, forgiveness factor, thermal acceptability
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1. Introduction
“Two buildings much alike in dignity, in fair Sydney, where we lay our scene...1”
The main purpose of any building is to provide a safe and comfortable
environment that neither impairs the health of its occupants nor hinders their
performance. Buildings are primarily designed and built for their intended occupants,
but in many cases this is done without much consideration of the buildings end-users’
needs or preferences (Vischer, 2001; Way and Bordass, 2005). As a result, many
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occupants do not understand how to operate their building which can often lead to
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high levels of discontent (Leaman and Bordass, 2007). As building managers and
designers continually strive to improve occupant satisfaction and productivity by
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ensuring comfortable and healthy working conditions, post-occupancy evaluation
(POE) represents a systematic quality assurance process towards these ends.
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POE is a global and rather general term for a variety of types of field studies in
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built environments based on assessing the responses, behaviour and perceptions of a
building’s occupants. In the past, POEs have been viewed as a means to measure the
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performance of a building from the occupant’s perspective in a systematic and
rigorous manner after they were built and occupied for some time (Preiser et al., 1988;
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Preiser, 2001a; BCO, 2007). Used extensively worldwide, POE studies aim to
investigate whether buildings are performing as intended/designed. In effect, they
provide ‘feedback’ to the architects and building managers on potential areas for
improvement (Vischer, 2004; Bordass and Leaman, 2005b). They are often targeted
towards the users’ perception of the building rather than actual building performance
metrics, such as energy consumption, temperature and humidity, lighting, noise, etc
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Adapted from William Shakespeare’s Romeo and Juliet, Act 1, Prologue
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(Zimring and Reizenstein, 1980; Hartkopf et al., 1986; Preiser, 1995; Derbyshire,
2001; Nicol and Roaf, 2005). There are, however, many differing definitions of what
constitutes POE. Within this paper, the authors define POE as a process of evaluating
the performance of a building after it has been built and occupied for some time
(Preiser et al., 1988). However, this paper argues that POEs should not only involve
feedback from the building users, but also include the use of instrumental data, such
as the measurement of indoor environmental quality (IEQ) indicators. Therefore, this
paper aims to critically examine the validity of POE as a measure of a building’s
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performance through user perceptions by comparing the results from POEs and
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thermal comfort studies conducted in two academic office buildings in Sydney,
Australia. In analysing forgiveness factors and thermal sensation votes, along with
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occupants’ comments, these results suggest that participants use POE surveys as a
conduit for general complaint which may have nothing to do with the building in
question.
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1.1. Post-Occupancy Evaluation: An Evolutionary Background
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Before we can effectively critique POE methods it is instructive to review the
context in which they were originally developed. Up until the 1950s, systematic
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information on building performance from the occupants’ perspective was not easily
accessible. Following the rapid expansion of architectural projects in the UK in the
1960s, the Royal Institute of British Architects (RIBA, 1962) identified the need to
gather and disseminate information and experience on the requirements of building
users. The RIBA called for the study of buildings in use, from both the technical and
cost points of view, as well as in terms of design (RIBA, 1962; Cooper, 2001;
Derbyshire, 2001). The RIBA’s Handbook of Architectural Practice and Management
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(1965) was instrumental in defining the sequence of stages related to building
construction, including briefing/programming, design, specification, tendering,
completion and use (Cooper, 2001; Preiser and Vischer, 2005; Preiser and Nasar,
2008). This report also incorporated a final stage to the building life-cycle called
‘feedback’. Within this stage, architects were advised to inspect their completed
buildings after they had been built as a means of improving service for future clients
(Preiser, 2001b; Bordass and Leaman, 2005a). Thus, the concept of ‘POE’ was born
from this need to provide feedback to building managers on the performance of their
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building after completion (Derbyshire, 2001; BCO, 2007). Despite RIBA’s best
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efforts, POE was largely ignored by the design and construction industry in the UK
because of its potential to deliver evidence to clients about under-performance or just
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plain building design (Cooper, 2001; Hadjri and Crozier, 2009). Following the large
number of housing studies in the 1970s and 1980s in the USA, POE has steadily
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gained credibility as a mechanism of scientific inquiry for user satisfaction within
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buildings (Preiser, 1995; Vischer, 2001; Bordass and Leaman, 2005a). However, it
wasn’t until the 1990s that the UK construction industry realised the true potential and
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value of POE as a significant development in architectural research (Cooper, 2001).
Over the past 30 years, numerous adaptations and improvements have been
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made to POE methods (Preiser and Vischer, 2005). The term POE was originally
intended to reflect that assessment taking place after the client had taken occupancy of
a building (Preiser, 2001a; Zimring and Rosenheck, 2001). Early descriptions focused
on POE as a stand-alone practice aimed at understanding a building from the users’
perspective (Preiser, 2001a; Bordass and Leaman, 2005a; Preiser and Vischer, 2005),
and often included aspects of architectural design, technical performance, indoor
climate, occupant satisfaction and environmental impact (Zimring and Reizenstein,
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1980; Hartkopf et al., 1985; Vischer and Fischer, 2005; Loftness et al., 2006;
Gonchar, 2008). POEs are generally classified into three main types, as identified in
Preiser et al., (1988): (1) Indicative POEs involve walk-through observations as well
as selected interviews which typically raise awareness of the major strengths and
weaknesses of a particular building’s performance; (2) Investigative POEs carry out
more in-depth evaluations and often comply with particular building performance
standards or guidelines on a given building type. One of the most commonly found
type of POEs, these provide a thorough understanding of the causes and effects of
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issues in building performance; and (3) Diagnostic POEs provide very detailed
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information about the buildings performance. These evaluations gather physical
environmental data which are then correlated with subjective occupant responses
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(Preiser et al., 1988; Preiser, 2001a). However, more recent applications of POEs,
especially in office buildings, fail to recognize the limitations of POE studies. Despite
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more recent POE discussions having emphasized the need for a more holistic and
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process-oriented approach to evaluating building performance (Preiser, 2001a;
Vischer, 2001; Preiser and Vischer, 2005; Vischer, 2008a; Meir et al., 2009), such
notions are yet to be transformed into practice.
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1.2. Uses and Misuses of Post-Occupancy Evaluations in Buildings
Over the past four decades, POE has become a widely used tool in evaluating
building performance (Preiser et al., 1988; Preiser, 1995; Riley et al., 2009). Since the
early studies on the housing needs of disadvantaged groups in the 1970s (Bechtel and
Srivastava, 1978; Vischer, 1985), POEs have broadened their scope to applications in
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other building types, such as, healthcare facilities (McLaughlin, 1975;
Cooper et al., 1991; Carthey, 2006; Leung et al., 2012), residential buildings (e.g.
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CABE, 2007; Gupta and Chandiwala, 2010; Stevenson and Leaman, 2010),
educational buildings (e.g. Baird, 2005; Watson, 2005; Loftness et al., 2006; TurpinBrooks and Viccars, 2006; Riley et al., 2010; Zhang and Barrett, 2010), and
commercial/office buildings (e.g. Leaman and Bordass, 1999; Leaman and Bordass,
2001; Zagreus et al., 2004; Bordass and Leaman, 2005c; Vischer, 2005; Abbaszadeh
et al., 2006; Leaman and Bordass, 2007; Leaman et al., 2007). Apart from providing
designers with feedback, numerous researchers (e.g. Preiser, 2001b; Vischer, 2001;
Whyte and Gann, 2001; Bordass and Leaman, 2005a; Loftness et al., 2006; Turpin-
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Loftness et al., 2009; Riley et al., 2010) suggest a number of other plausible benefits
of POE, including: (1) improving commissioning process; (2) definition of user
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requirements; (3) improving management procedures; (4) providing knowledge for
design guides and regulatory processes; and (5) targeting of refurbishment.
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Notwithstanding these benefits, many barriers to conducting POEs have also
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been identified (Cooper, 2001; Vischer, 2001; Zimmerman and Martin, 2001; Zimring
and Rosenheck, 2001). The extensive discussion of these problems suggests a
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growing frustration with the lack of progress towards POE becoming a mainstream
activity in the process of building procurement (Hadjri and Crozier, 2009; Meir et al.,
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2009). The more commonly identified barriers to the widespread adoption of POE
include cost, fragmented incentives and benefits within the procurement and operation
processes, potential liability for designers, engineers, builders, and owners, lack of
agreed and reliable indicators, time and skills (Bordass et al., 2001; Cooper, 2001;
Vischer, 2001; Zimmerman and Martin, 2001). Moreover, Zimmerman and Martin
(2001) suggest that standard practice in the facility delivery process does not
recognise the concept of continual improvement or any ongoing involvement on the
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part of the designers. Despite one of the primary goals for conducting POEs is to
enable designers to revisit their designs, improve their skills and produce more
efficient buildings, the idea of continual improvement via feedback has lacked
emphasis in both the North American and UK contexts (Derbyshire, 2001; Preiser,
2001b; Preiser and Vischer, 2005). Whilst many agree with these barriers, there are
still some challenges in the use of contemporary POE methods (Preiser and Vischer,
2005), especially in commercial office buildings. From the literature, three key issues
in the POE method have been identified: ‘lack of context’; ‘lack of feedback’ and the
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Loftness et al., 2009). It should be noted that the following issues are predominantly
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‘post’ reflects only that time after a building was completed (Bordass and Leaman,
2005a; Preiser and Vischer, 2005). Yet, POE is not the end phase of a building
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project; rather it is an integral part of the building delivery process (Federal Facilities
Council, 2001; Preiser, 2001b; Vischer, 2001). The technique should be used more
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regularly to ensure buildings continue to deliver at their intended design specifications
and, in return, appropriate levels of satisfaction among the end-users (Preiser, 2001b;
Preiser and Nasar, 2008; Vischer, 2008a; Riley et al., 2010). Much literature suggests
POE should be cyclical in nature rather than simply providing a final feedback
component in the occupancy phase (e.g. Preiser, 1995; Bordass et al., 2001; Cohen et
al., 2001; Vischer, 2001).
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POE practice has mainly focused on assessing specific cases (Federal
Facilities Council, 2001; Turpin-Brooks and Viccars, 2006). Even when evaluators
have been able to create databases of findings, they have often been used to
benchmark single cases rather than to develop more general conclusions (Zimring and
Rosenheck, 2001; Baird, 2011). POE studies involving office buildings often lack the
contextual information in which the building was built and occupied. Prior to moving
into their new building or space, occupants could already harbour distrust of
management (Vischer, 2001; Vischer and Fischer, 2005; Vischer, 2008b). Workers
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may also have high expectations that are not met when balanced against the possible
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constraints of an existing building that limits the creation of effective workspace
(Schwede et al., 2008). Ultimately, the uncertainty generated by moving to a new
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building or space affects employee’s perception of their environment (Vischer, 2005;
Vischer and Fischer, 2005). If left unresolved, these attitudes and predispositions are
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likely to carry forward into the new workspace. As such, the actual impact a building
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has on its users remains unaccounted for in the analysis and interpretation of the
results. Many discussions have risen for the evaluation of a building prior to
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occupation (Federal Facilities Council, 2001; Preiser and Vischer, 2005). Leaman et
al., (2010) suggest that building performance studies should seek and reveal the
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context behind the building, i.e. occupants’ personal history and attitudes towards the
building. These psychosocial factors play an important role in determining people’s
concerns with their environment (Vischer, 1986; Chigot, 2005; Vischer and Fischer,
2005; Turpin-Brooks and Viccars, 2006) and may well affect their perception of the
building. Furthermore, the consideration of occupants’ demands and experience in the
design process helps to achieve more positive design outcomes (Vischer, 1985;
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1.2.2. Lack of Feedback (Or Has the Loop Become A Noose?):
Improvement of building performance requires the identification of positives
and negatives through rapid feedback (Cohen et al., 2001; Bordass and Leaman,
2005b). The UK’s Building Use Studies (BUS) in the 1990s launched the Postoccupancy Review of Buildings and their Engineering (PROBE) project (Cohen et al.,
2001; Cooper, 2001; Derbyshire, 2001; Fisk, 2001). In conducting POE studies for a
wide range of non-domestic buildings, the PROBE project helped develop a
standardised POE method; accumulating a wide range of studies around the world
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into a homogenized database against which future POE studies could be benchmarked
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(Bordass et al., 2001; Leaman and Bordass, 2001). Following these landmark PROBE
studies, POE advocates stressed the need to close the loop between building managers
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and the building’s end-users (NCEUB, 2004; Building Research and Information,
2005). In agreement, Leaman and Bordass (2001) suggest the provision of a
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knowledge base of lessons learned from users in completed projects should be utilised
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to either improve spaces in existing buildings or form a programming platform for
future buildings (Leaman and Bordass, 2001; Zimmerman and Martin, 2001; Preiser
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and Schramm, 2002). Ten years on, however, there is evidence to suggest that a lack
of communication and feedback still exists amongst these parties (Preiser and
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Vischer, 2005; Thomas, 2010).
POE has lost its initial aim to close the loop between building
designers/managers and the occupants (Jaunzens et al., 2003; Jarvis, 2009; Leaman et
al., 2010); suggesting the loop has now become the noose. To date, occupants still
remain a largely untapped source of information to building managers and, as such,
are rarely involved in the stages of building construction and commission (Zagreus et
al., 2004). Due to this lack of involvement, many occupants do not understand how to
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operate nor occupy their building, which often leads to high levels of discontent.
Consequently, as Cohen et al., (2001) suggests, occupants will blame ‘negative’
workplace feelings on the physical environment as a way of voicing their
dissatisfaction. Furthermore, occupants will often resort to using the POE as a means
to report problems in the workplace, e.g. uncomfortable conditions, poor lighting or
ventilation, lack of control, and even bullying which is not measured in POEs
(Loftness et al., 1989; Preiser, 2001b; Vischer, 2004; Vischer and Fischer, 2005;
Turpin-Brooks and Viccars, 2006).
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1.2.3. Lack of Instrumental Data:
POEs were originally intended to provide information regarding the in-use
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performance of a building using instrumental data (Hartkopf et al., 1986; Vischer,
1986; Ventre, 1988; Loftness et al., 1989; Vischer and Fischer, 2005). The landmark
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PROBE studies in the UK set the benchmark as to how such studies should be
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conducted (Loftness et al., 2009; Meir et al., 2009). These studies relied on three
evaluation components: Energy Assessment and Reporting Methodology (EARM);
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BUS occupant questionnaire; and an air pressure test (Cohen et al., 2001). Subsequent
use of these tools, however, has focused more on occupant satisfaction with the
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building, thereby relying on more subjective criteria (Federal Facilities Council, 2001;
Fisk, 2001; Turpin-Brooks and Viccars, 2006; Jarvis, 2009; Leaman et al., 2010).
While many agree such metrics are more easily assessed than alternatives, such as
productivity or health (Leaman and Bordass, 1999), it is often argued that occupant
satisfaction is not a meaningful measure for judging building performance (Hartkopf
et al., 1985; Hartkopf et al., 1986; Heerwagen and Diamond, 1992; Leaman et al.,
2010). Despite providing a first-hand account of how the building is affecting the
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occupants, such assessments are susceptible to bias. Since POEs don’t account for any
psychosocial or contextual (non-physical) factors that may affect occupants in the
workplace, participants’ responses may be either positively or negatively biased.
Sometimes known as the ‘Hawthorne effect’, the behaviour or responses of an
individual or group will often change to meet the expectations of the
observer/researcher (Roethlisberger and Dickson, 1939).
The use of such measures therefore presents a specific challenge: respondents’
subjective assessments of their environment might be affected by non-building-related
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factors (Ventre, 1988; Zagreus et al., 2004; Jarvis, 2009; Loftness et al., 2009). Many
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aspects of building performance are readily quantifiable, such as lighting, acoustics,
temperature and humidity, durability of materials, amount and distribution of space,
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etc. (Hartkopf et al., 1985; Hartkopf et al., 1986; Preiser, 2001a). Despite this, POEs
typically do not obtain instrumental measurements of indoor building environmental
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conditions, potentially leading to unsubstantiated complaints against a building’s
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indoor environment. In order to get a complete picture of a building’s actual
performance from a technical and occupants’ perspective, the subjective data from
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occupant feedback surveys needs to be correlated against the quantitative data
measured from physical monitoring (Vischer, 1986; Ventre, 1988; Turpin-Brooks and
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Viccars, 2006; Choi et al., 2010; Gupta and Chandiwala, 2010). Several researchers,
however, argue there are inherent difficulties in matching user’s subjective responses
with objective environmental data (Vischer, 1986; Vischer and Fischer, 2005; Jarvis,
2009; Loftness et al., 2009). POEs often record occupant perceptions of thermal
comfort on past seasonal events occurring 3 to 12 months before the survey was
administered. In order to achieve a successful correlation between the occupants’
thermal comfort ratings and the internal thermal environment of the building, the
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surveys need to be conducted on a ‘right-here-right-now’ basis for the results to be
reliable. However, Vischer (1993) also suggests that humans draw on experience
outside the immediate time-frame of the present to make their summary judgements
of comfort conditions. Instruments, on the other hand, are temporally limited to
sampling actual building conditions as a snapshot or over a prolonged period of time.
By adopting a more diagnostic approach to POEs the temporal and calibration
limitations on instrument-based data collection can be avoided. Furthermore,
measurements of building systems performance can be carried out as a follow-up
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procedure to help understand the meaning behind the feedback yielded by users on
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their perceptions of building conditions (Vischer, 1986; Vischer, 2001; Vischer and
Fischer, 2005).
2.
Methods
2.1. Sydney’s Climate
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Located on the eastern coast of Australia, the Sydney metropolitan region
(34°S, 151°E) is characterised by a moderate sub-tropical climate. Influenced from
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complex elevated topography surrounding the region to the north, west and south and
due to close proximity to the Tasman Sea to the east, Sydney avoids the high
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temperatures commonly associated with more inland regions of the same latitude
(BoM, 1991). In regards to summer, the months of December to February can be
described as warm-to-hot with moderate-to-high humidity peaking in February to
March. Within the winter months of June to August, Sydney experiences cool-to-cold
winters. The two case study buildings are located within a suburban tertiary
educational institution, approximately 16km north-west of Sydney’s central business
district (33° 46’ S, 151° 6’ E). As shown in Figure 1, seasonal variations range from
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mean summer daily maximum temperatures of 26-28°C, a mean winter daily
maximum of 17°C and an annual mean daily maximum of 22-23°C. Mean minimum
daily temperatures range from 5-8°C in winter, to 17-18°C over the summer months,
with an annual daily minimum temperature of 11-13°C (BoM, 2011). Given the city’s
seasonal variations, Sydney’s climate is well suited to natural ventilation. For much of
the year, thermal comfort indoors can be easily achieved through simple passive
design principles and various adaptive behaviours employed by the occupants, such as
opening/closing windows, adjusting their clothing or by change of position
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(Aggerholm, 2002; Rowe, 2003).
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Figure 1. Climatology of the case study building site (adapted from BoM, 2011)
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2.2. Case Study Buildings
Two academic office buildings were selected for this study. The mixed-mode
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(MM) building was commissioned in 2006 and has a total usable floor area of 6541
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m2. The naturally-ventilated (NV) building was built in the 1960s and covers an area
of approximately 5808 m2. Since both buildings were located on the same university
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campus, occupied by the same organisation with comparable occupancy densities of
0.03 occupants/m2, they make for an ideal field study. Due to both buildings having
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North-South orientations, the North-facing facades are directly irradiated from the
Sun, creating warmer internal temperatures than the South-facing perimeter zones:
1. Mixed-Mode Building: presented in Figures 2a and 2b, this 7-storey academic
office building features operable windows on all North and South perimeter
cellular offices. These are separated with an air-conditioned (AC) central
open-plan office zone. Automated high and low external louvres provide
natural ventilation to each floor, with adjustable internal grilles to control
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airflow, supplemented with user-operable windows (Figure 2b). As depicted in
Figure 2a, the building also features additional solar shading over the northern
(sun-facing) windows. Indoor temperature and outdoor weather sensors
prompt the Building Management System (BMS) to switch into AC mode
whenever a temperature greater than 25°C is sensed within any zone. During
AC mode, internal temperatures are maintained at 24°C (+ 1°C) as defined in
the building’s algorithm. BMS switch-over to NV mode is conditional when
external meteorological conditions and the indoor thermal climate fall into an
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acceptable zone for the occupants. Around 200 academic and administrative
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staff from economics and finance disciplines occupy this building.
Figure 2a) The MM building as viewed from the north facade featuring operable
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windows with external solar shading devices on north-facing windows
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Figure 2b) User-operated windows and internal grilles in the North and South
perimeter offices of the MM building
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2. Naturally-Ventilated Building: illustrated in Figures 3a and 3b, the NV
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building features occupant-operated windows with a narrow floor plate
traversed by a central corridor with single- and dual-occupant cellular offices
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on either side. Unlike the MM building, there is no centralised heating or
cooling systems, with the exception to those offices with individual window
air-conditioner units (as seen in Figure 3a). Figure 3b illustrates that occupants
often resort to using portable fans and heaters throughout the year for
additional cooling in summer and/or heating in winter. The building’s total
population of 200 occupants is composed of academic and administrative staff
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as well as post-graduate students from a variety of science-related disciplines,
such as environmental science, physics, geology and mathematics.
Figure 3a) The NV building as viewed from the north facade featuring occupantoperated windows with some individual air-conditioner units
Figure 3b) Occupants often use portable fans or heaters in conjunction with operable
windows for additional cooling/heating throughout the year
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2.3. Measurements
Simultaneous objective (indoor and outdoor climate) and subjective (self-
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assessed comfort perceptions) measurements were collected throughout this study.
Dataloggers were randomly located throughout each building to record air
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temperature, globe temperature and relative humidity at 5 minute intervals throughout
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the study. The study was conducted over twelve months (from March 2009 to April
2010) to represent the full cycle of the seasons. Air velocity was measured during
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each questionnaire session using a handheld thermal anemometer (TSI VelociCalc).
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Loggers were placed within 1 m of the occupants’ workstation to characterise the
immediate thermal environment experienced by the occupant under normal working
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conditions. Outdoor weather observations were obtained from a nearby automatic
weather station. The building’s AC/NV mode status and indoor temperature records
were collected from the BMS after the field campaign had finished.
2.4. Questionnaires and Data Analysis
Two separate questionnaires were used in this study, i.e. the BUS postoccupancy evaluation and ‘right-here-right-now’ thermal comfort questionnaire:
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1. Post-Occupancy Evaluation: The 3-page BUS POE questionnaire (Usable
Buildings Trust, 2008; BUS, 2009) features numerous 7-point scales with
space for commentary covering all variables relating to occupant satisfaction,
e.g. thermal, visual and acoustic comfort, indoor air quality, perceived health
and productivity, as well as overall satisfaction with the workplace.
Combinations of these scores enable the calculation of various comfort and
satisfaction indices, including the ‘forgiveness factor’, unique to the BUS
survey. The forgiveness factor is derived as a ratio of Overall Comfort score to
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Noise Overall, Temperature Overall in both winter and summer, and Air
Overall in both winter and summer. This index purports to quantify the user’s
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tolerance of the environmental conditions in the building, with values greater
than unity taken to indicate occupants being more tolerant, or ‘forgiving’, of a
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building’s thermal environmental conditions (Leaman and Bordass, 2007).
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These questionnaires, in accordance to the original BUS methodology, were
delivered in person to each occupant within the building. To preserve occupant
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anonymity, participants placed their completed questionnaires inside a blank,
sealed envelope which was collected at the end of the same day.
2. Thermal
Comfort
Questionnaires:
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Paper-based
subjective
comfort
questionnaires were used to record occupant perceptions of their thermal
environment on a ‘right-here-right-now’ basis. Subjects were asked to assess
their thermal sensation (Actual Mean Vote) on the ASHRAE 7-point scale,
which included the possibility of fractional votes placed between two comfort
categories. Thermal acceptability was addressed as a binary ‘acceptable’ or
‘unacceptable’ response whereas thermal preference was assessed on the 3-
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point McIntyre scale (McIntyre, 1980), on which occupants listed if they
preferred to feel ‘warmer’, ‘cooler’ or ‘no change’. In terms of air movement,
subjects registered if the air velocity was ‘acceptable’ or ‘unacceptable’ and
their reason: whether it was ‘too low’, ‘too high’ or ‘enough’ air movement.
Subjects were also asked if they preferred ‘no change’, ‘more’ or ‘less’ air
movement. Standardised self-assessed clothing garment (clo) and metabolic
activity checklists (ASHRAE, 2001; ISO, 2003) within the subjective comfort
questionnaires allowed the calculation of various comfort indices using
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ASHRAE’s WinComf software (Fountain and Huizenga, 1997), including
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Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD).
Lastly, a section was added for the researcher to identify the respondents’
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location and mode of operation for each participant’s office at the time of each
questionnaire. This information was used to match the questionnaire responses
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with the instrumental measurements.
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3.
Results
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In order to show the differences between each building based on both
subjective (occupant satisfaction) and objective measurements (instrumental
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measurements), it is instructive to compare both buildings’ performance under similar
weather conditions. POEs were conducted in each building between March and April
2009 and 2010 to reflect occupants’ perceptions of thermal comfort and other IEQ
performance through the previous winter-summer cycle. Thermal comfort field
studies were conducted simultaneously in both buildings from October 2009 to April
2010 in which the outdoor weather conditions were comparable to those from the
previous summer period (2008-2009).
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3.1. Summertime Thermal Environment
Presented in Figure 4 are the concurrent indoor temperatures recorded at the
time when each comfort questionnaire was administered across both buildings
throughout the study (October 2009 to April 2010). As illustrated, the data in Figure 4
highlights discrepancies between the internal operative temperatures within these
buildings during the study period. The NV building experienced significantly warmer
indoor temperatures (average = 25.4°C, p = 0.000) compared to the MM building over
the same period (average = 23.8°C). Recorded during occupied office hours (8am to
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6pm), the average daily outdoor air temperature of 24.4°C was typical for Sydney’s
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summer months. Figure 4 indicates internal temperatures within the NV building
tracking changes in the outdoor weather conditions. Temperatures in the MM building
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ranged from 21-25°C in accordance with the BMS algorithm switching into AC mode
whenever average indoor air temperatures reach a 25°C trigger temperature. In
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contrast, temperatures inside the NV building varied between 20-30°C. Internal
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temperatures in the NV building exceed the 25°C threshold on 27 days during the
study, which equates to over 50% of all occupied office hours. Thus, objectively, the
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NV building is significantly warmer than the MM building during summer months.
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Figure 4. Summertime thermal environment recorded for the MM and the NV
building (October 2009 to April 2010). Each data point corresponds to days in which
thermal comfort questionnaires were administered
3.2. Occupant Satisfaction: POE vs. Thermal Comfort
POEs were delivered face-to-face on a Tuesday morning to all occupants
within each building, as recommended by the BUS (2009) methodology. This was
done to ensure the best possible response rates. In total, 163 POE questionnaires were
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distributed in the MM building and 120 in the NV building2. With a 53% response
rate, the MM building returned 86 completed questionnaires (39 male, 47 female), and
81 (38 male; 43 female) were completed from the NV building (68% response rate).
Incomplete responses were omitted from the subsequent analysis. The thermal
comfort variables are measured using a 7-point scale with 4 as the mid-point; scores
greater than 4 express satisfaction and scores lower than 4 express dissatisfaction.
Calculated as the percentage of scores less than 4 to the total number of scores
recorded, Table 1 shows the percentage of dissatisfaction votes for each of the thermal
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comfort variables, i.e. temperature in summer, ventilation in summer, noise, lighting,
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perceived productivity, comfort overall and forgiveness factor.
The values in Table 1 demonstrate that occupants of the MM building rated
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their building quite poorly in terms of thermal comfort with over half the study
population (55%) registering dissatisfaction with overall comfort. Similarly, 58% and
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unacceptable respectively. Fewer people were dissatisfied with temperature and
ventilation in the NV building (28% and 25% respectively). In terms of overall
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lighting, noise and perceived productivity, both buildings scored similar percentages
of occupant satisfaction. Values greater than 1 on the forgiveness factor index are
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taken to indicate that occupants may be more tolerant, or ‘forgiving’ of the conditions
(Leaman and Bordass, 2007). Therefore, the forgiveness factor of the NV building
(1.14) suggests that occupants were more prepared to forgive the buildings’ less-thanideal conditions, as opposed to their MM counterparts (forgiveness factor = 0.99).
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rest of the occupants (located on floors 2 to 5).
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Table 1. Forgiveness factor and dissatisfaction percentages of variables in the POE
for the MM and NV building
Sixty subjects were recruited from each building for the summer thermal
comfort field studies. In total, 713 ‘right-here-right-now’ questionnaires were
collected from the MM building (average of 15 per day), and 607 were collected from
the NV building (average of 13 per survey day). In order to analyse these results
against comparable conditions in each building, Actual Percentage Dissatisfied (APD)
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and Predicted Percentage Dissatisfied (PPD) based on Fanger’s heat-balance comfort
model (1970) were plotted against binned indoor operative temperature. As mentioned
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previously, PPD values were calculated based on the PMV equation using ASHRAE’s
WinComf software (Fountain and Huizenga, 1997). APD was derived as the
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percentage of thermal sensation votes greater than +1.5 and less than -1.5 recorded
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within the limits of a 1°C indoor operative temperature bin, e.g. 21.5 to 22.49°C,
against the total number of votes for each corresponding bin. Those votes registered
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outside ±1.5 were regarded as expressing dissatisfaction (as described by (Fanger,
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1970)). Figures 5a and 5b below show the results of these analyses for the MM and
NV building respectively. Since the central zone in the MM building is constantly AC
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and does not have the capability to operate under natural ventilation, it was not
included in the following analyses. Furthermore, when APD equals 100% this
indicates that all subjects surveyed voted their thermal sensation to be greater than
±1.5 units outside thermal neutrality. Conversely, APD is ‘zero’ when all subjects’
thermal sensations were between the votes of slightly warm (+1) to slightly cool (+2)
on the ASHRAE 7-point scale of thermal sensation.
As illustrated in Figure 5a, occupants of the MM building were found to be
quite dissatisfied with the thermal environment. Observed levels of thermal
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dissatisfaction (APD) were greater than or equal to those predicted on the basis of
actual environmental conditions using the PMV-PPD model at modest indoor
temperatures, i.e. 22 to 26°C. This suggests that occupants found these temperatures
to be overwhelmingly unacceptable despite PPD values falling at or below the 1020% dissatisfied threshold. In contrast, the NV building results indicate PPD levels,
on average, higher than the APD values registered by occupants (Figure 5b). Fewer
occupants expressed dissatisfaction compared to the PPD levels for temperatures
ranging from 19 to 25°C, indicating that, despite the much warmer indoor
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environmental conditions with PPD levels well above the recommended 20% margin,
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occupants still voted these temperatures as acceptable.
These results also highlight fundamental differences between occupants of
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these two buildings. Even under similar thermal conditions, occupants of the NV
building, on average, registered lower APD values compared to those in the MM
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building. For instance, at an indoor operative temperature of 23°C, 15% of occupants
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in the MM building were thermally dissatisfied, whereas all subjects surveyed in the
NV building at the same temperature voted the indoor thermal environment as
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satisfactory. Again, at an indoor operative of 25°C, only 8% of the subjects surveyed
in the NV building recorded thermal sensations outside the band of thermal
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acceptability (±1.5), whereas in the MM building, 18% of occupants surveyed
expressed thermal dissatisfaction.
Figure 5. Average APD and PPD recorded in a) the MM building (above) and b) the
NV building (below)
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3.3. Thermal Acceptability
The preceding analyses inferred acceptability from the sensation scale, and in
doing so, afforded comparisons between observed thermal dissatisfaction and that
predicted in the same setting by Fanger’s PPD (1970). A more direct approach on our
subjective comfort questionnaires used a binary item, i.e. was the thermal
environment simply ‘acceptable’ or ‘unacceptable’? The numbers of ‘acceptable’ and
‘unacceptable’ votes recorded in each indoor operative temperature bin were tallied
(Figures 6a and 6b). As shown in Figure 6a, a higher percentage of occupants in the
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MM building voted the thermal environment as ‘unacceptable’ compared to those in
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the NV building (shown in Figure 6b). Within the MM building, over 20% of
occupants surveyed found the indoor temperature to be unacceptable, even at
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moderate temperatures, e.g. 20-26°C. In contrast, Figure 6b demonstrates that fewer
occupants (as low as 5%) in the NV building found the indoor temperature to be
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unacceptable. Between temperatures of 20-25°C, over 80% of the study population in
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the NV building found these temperatures to be acceptable. Not surprisingly, the
number of ‘unacceptable’ votes recorded in both buildings increased under warmer
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indoor conditions. Interestingly, even at similar indoor temperatures of 26°C, the NV
building recorded 90% acceptability (grey bars), whereas the MM building recorded
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just over 70%.
Figure 6. Percentage of thermal acceptability votes registered in a) the MM building
(above) and b) the NV building (below)
4.
Discussion
Despite indoor operative temperatures in the MM building being significantly
cooler than the NV building (Figure 4), the subjects’ POE responses reflect lower
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levels of satisfaction (40-50%) with the thermal environment. Objectively, the thermal
environment in the NV building appears significantly worse than the adjacent MM
building. On average, temperatures in the NV building during the summer months
were 2°C warmer than the MM building. As shown in Figure 4, the MM building
rarely exceeds the 25°C threshold due to the building switching into AC mode when
indoor temperatures are greater than 25°C. But despite these less-than-ideal
conditions, occupants of the NV building reported moderate levels of satisfaction
(around 80%) and this was borne out by their forgiveness levels (1.14) compared to
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their MM counterparts (0.99).
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In regards to the results from the thermal comfort studies, occupants’
perceptions of comfort and thermal acceptability were quite different between these
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buildings. Even though indoor environmental conditions experienced within the NV
building were less-than-ideal, Actual Percentage Dissatisfied (APD) were, on average,
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lower than the predicted PPD values. In comparison, occupants of the MM building
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registered much higher APD levels than the PPD values predicted using Fanger’s
heat-balance model. Despite temperatures within the MM building being constrained
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during summer between 20-25°C, occupants expressed significantly greater levels of
thermal discomfort.
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Although outside the stated scope of this paper, the results also highlight
another important issue regarding the use of subjective and objective building
performance metrics. According to ASHRAE Standard 55 (2010), the PMV-PPD
model is used to evaluate the thermal environment of AC buildings. The adaptive
comfort standard, as an alternative to the PMV-PPD model, is restricted in scope to
NV or ‘free-running’ buildings (de Dear and Brager, 2002; Nicol and Humphreys,
2010). This paper demonstrates the complexities of relying solely on subjective
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indicators of building performance, e.g. APD and acceptability or POE in general.
Many building guidelines and comfort standards recommend the use of objective
criteria, such as temperature and PMV-PPD to assess a building’s thermal
environment. However, this study has shown that PPD results significantly
underestimated the observed levels of thermal dissatisfaction in one building (MM
case study), and overestimated them in another (NV building). If purely assessed
using Fanger’s PMV-PPD model (1970), as expressed in ASHRAE 55-2010, the MM
building would be deemed comfortable as indoor operative temperatures fell within
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the 80% acceptability PPD limits. The NV building, however, would be deemed
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uncomfortable as indoor operative temperatures were well above the upper limit of
25°C. Despite this, the APD results in Figure 5b suggest the NV occupants found the
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thermal environment to be quite acceptable across a broad range of indoor operative
temperatures (20-25°C). Occupants of the MM building expressed greater levels of
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thermal dissatisfaction (i.e. higher APD values in Figure 5a) across the same range of
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temperatures. The better than predicted acceptability scores in the NV building have
been discussed in terms of forgiveness factors and adaptive opportunities, suggesting
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occupants of both buildings are exhibiting some degree of thermal adaptation to their
indoor environment (de Dear and Brager, 1998; de Dear and Brager, 2002). However,
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both case study buildings possess similar degrees of occupant-orientated
environmental control, or adaptive opportunities (Baker and Standeven, 1996) to
control air movement/ventilation (operable windows) and lighting (shades, artificial
lighting). The only difference is that the MM building uses centralised HVAC
whenever indoor temperatures exceed the 25°C trigger temperature. From these
findings, it is apparent that occupants’ acceptability of the thermal environment is
influenced by their expectations as suggested by the adaptive hypothesis (de Dear and
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Brager, 2002). Considering only 71% of occupants in the MM building found the
thermal environment to be acceptable as opposed to 85% of occupants surveyed in the
NV building, it therefore seems that something extra other than thermal adaptation
(Brager and de Dear, 1998) is required to explain the worse-than-expected
acceptability in the MM building.
4.1. Analysis of Occupants’ Comments and Anecdotal Evidence
Occupant-based comments and anecdotal evidence are considered important
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contextual information in POE studies (Bordass and Leaman, 2005b; Moezzi and
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Goins, 2011). Since the comparison of quantitative IEQ survey data often lacks the
context and complexity of user experiences, text responses can be analysed to provide
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a deeper understanding of the POE results (Baird, 2011; Moezzi and Goins, 2011;
Baird et al., 2012). Especially in situations when the results of the POE may not
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match the physical environmental data, as is the case presented in the MM building,
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such data can be used to verify the validity and reliability of both the subjective and
objective results. Many POE questionnaires, such as the BUS POE, offer subjects the
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option to give their own comments regarding particular IEQ variables. Other surveys,
such as the Occupant IEQ Satisfaction Survey developed by CBE (Zagreus et al.,
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2004; CBE, 2012), offer a more detailed response from the participants. Using similar
keyword and phrase extraction methods employed by Moezzi and Goins (2011), text
responses were analysed and compared between each building to validate their
respective POE results in Table 1.
Occupants’ comments from the POE were grouped according to those
featuring keywords or phrases related to temperature, ventilation, noise and lighting.
The results and list of words used to identify negative comments, or ‘complaints’,
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relating to each category across both case study buildings are presented in Table 2. In
total, 167 complaints were recorded for the MM building and 108 for the NV
building. Since the NV building predominantly relies on natural ventilation, its users
are prone to complain about uncomfortable working conditions, especially during
summer and winter. As expected, ‘temperature’ was the most common complaint
within the NV building with 56% of comments using phrases such as: “too hot” and
“too cold”. However, within the MM building, temperature was the second most
reported problem with 31% of the comments. “Noise from outside” and “from
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colleagues” was frequently reported within both buildings, especially in the MM
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building wherein it was the most common complaint (38% of the total; 64 comments).
Noise complaints were only mentioned 25 times (23%) within the NV building. The
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MM building, in comparison to the NV building, also recorded more comments
relating to lighting, i.e. “too much glare” (15% and 9% respectively) and ventilation,
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i.e. “ventilation” and “draught” (MM: 16%; NV: 12%).
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Table 2. List of keywords and phrases used to identify complaints in each category.
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These results shed light on a common theme evident in many recent POE studies
in NV and MM buildings. Buildings with natural ventilation capabilities are often
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hotter in summer, colder in winter and contain more glare (Leaman and Bordass,
2007). Many studies reveal air movement, temperature, glare and noise as the most
common causes for dissatisfaction in green buildings (Abbaszadeh et al., 2006; Brager
and Baker, 2009; Moezzi and Goins, 2011; Baird and Dykes, 2012). However, while
these results demonstrate potential areas of improvement and lessons to be learned in
future green building construction, they also illustrate that occupants can potentially
use POE as a conduit to complain. Participants in both buildings expressed lengthy
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complaints, often incorporating emotional language into their responses. Occupants
predisposed to complain, either due to contextual (e.g. work-related) or physical (e.g.
temperature) factors will exaggerate poor building performance (Loftness et al., 2009;
Vischer, 2009; Baird and Dykes, 2012; Baird et al., 2012). Whereas the MM case
study building was deemed comfortable on objective criteria, its occupants felt
compelled to complain about the building’s performance, particularly its thermal
environment. Furthermore, the discrepancies between occupants’ thermal satisfaction
and acceptability and the POE results suggest the building may not be the problem.
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This begs the question: how much does the POE get influenced by non-building
contextual factors?
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Whilst purely based on anecdotal evidence and occupants’ comments, it is
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interesting to note the faculty occupying this contentious MM building. While both
buildings are occupied by staff from the same organisation at the same location, there
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are clearly differences in the occupants’ expectations and attitudes of the thermal
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environment. We speculate that the occupants of the MM building are dissatisfied due
to a number of non-building-related factors. The building is occupied by academic
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and administrative staff from a variety of business and economics departments,
including accounting and finance, actuarial studies, and business studies. Responsible
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for one of the University’s largest student populations, the staff to student ratio for
this faculty is the lowest in the entire University. As a result of these high teaching
workloads, staff morale within this building is commonly acknowledged to be quite
low compared to the NV building which is occupied by various science departments,
such as geology, physics, environmental sciences and astronomy. Prior to moving into
their new MM building, the business and economics departments occupied a
conventional AC building. They were deeply distrustful of management and
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suspicious of the motives behind the new building’s partial air conditioning (mixedmode). Additionally, given the initial teething problems with the MM building due to
deficient commissioning, these occupants were predisposed to respond to the POE
questionnaire in a strongly negative mood. Figure 4 suggests these initial technical
glitches in the MM system had been corrected. Nonetheless, the occupants’
perceptions of their MM building remain coloured by their negative first impressions.
4.2. Recommending an Improved Methodology for Conducting Building
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Performance Studies
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Since inception, POE has taken several approaches varying from highly
technological methodologies involving physical environmental data (e.g. Hartkopf et
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al., 1986; Sanders and Collins, 1995; Vischer and Fischer, 2005; Turpin-Brooks and
Viccars, 2006; Loftness et al., 2009; Choi et al., 2010), to socio-psychological
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interests where more subjective parameters are employed to evaluate building
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performance (e.g. Vischer and Fischer, 2005; Abbaszadeh et al., 2006; Leaman et al.,
2007; Brown and Cole, 2009). However, such studies are more commonly based on
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an ‘investigative’ approach utilising qualitative interviews and questionnaires (Preiser,
1995; Preiser, 2001a). The POE results from this paper raise concerns about the
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validity of adopting a single approach. When compared with more objective data
collected in each building, i.e. temperature, thermal satisfaction and acceptability, the
different results from each building were inconsistent. Therefore, POEs alone do not
adequately evaluate the overall performance of a building, nor the extent to which the
building meets the needs of its end-users (Vischer, 2009). In order to provide a better
understanding of how occupants use and interact with their building, this paper
recommends more holistic and robust performance evaluations that incorporate
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physical environmental data with subjective occupant responses (Ventre, 1988;
Preiser, 2001a; Vischer, 2001; Loftness et al., 2009).
Because POEs have commonly focused on building user feedback, much of
the information received is negative in nature (Vischer, 2001). Hence, one of the
challenges of POEs going forward is to identify a reasonable system of informed
weighting of user feedback; allowing data to be interpreted according to balanced
positive and negative categories (Preiser, 2001b; Vischer, 2001). Preiser (2001a)
suggests more ‘diagnostic’ POE approaches can combat this problem. These types of
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POE provide a highly sophisticated and detailed assessment enabling the correlation
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between physical environmental measures with subjective occupant response
measures (Hartkopf et al., 1986; Preiser, 2001a; Preiser and Vischer, 2005). Socio-
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cultural observation and functional comfort surveys would be further enhanced by the
monitoring and analysis of scientific data on ‘real-time’ workplace environmental
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conditions, e.g. thermal, acoustic and visual comfort; occupants’ satisfaction and
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behaviour; as well as, physiological and psychological comfort (Preiser and Vischer,
2005; Turpin-Brooks and Viccars, 2006; Vischer, 2008b; Meir et al., 2009). This
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information could be used to gauge any adjustments needed in the controls or
environmental settings of the workplace, but also verify users’ problems with the
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indoor environment/building performance; thus enabling systematic and reliable
feedback (Vischer, 2008a; Loftness et al., 2009).
In summary, whilst a number of alternative methods are available, it is clear
that ‘one size does not fit all’ especially in regards to the physical, psychological and
psychosocial influences on workplace satisfaction. Several studies have demonstrated
that a combined approach POE using more than one tool of assessment can enhance
the understanding of a building’s performance (Hartkopf et al., 1986; Vischer and
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Fischer, 2005; Turpin-Brooks and Viccars, 2006; Loftness et al., 2009; Choi et al.,
2010). A more holistic POE, combining objective building performance data and
subjective satisfaction ratings, may in fact offer a more valid and reliable evaluation
of a building’s success.
5.
Conclusions
Over the last four decades, a large number of POEs have been conducted in a
variety of different building types, using a wide range of methods, goals and
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frameworks. However, despite the potential of POE to have a positive effect on
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subsequent building delivery and management, the full potential has not yet been
realised. In its current form, POE remains a superficial assessment of building
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performance; merely providing a face-value assessment of buildings by their
occupants. Used in isolation, POE surveys may not be a fair reflection of the
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building’s actual performance, i.e. energy consumption/efficiency and IEQ indicators.
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Since such studies don’t typically obtain parallel instrumental measurements of these
variables, e.g. indoor climate, they lack an objective benchmark against which poor
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satisfaction ratings can be verified.
The aim of this paper was intended to illustrate how supplementary
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instrumental measurements of a building’s indoor climate could lead to a fundamental
reinterpretation of POE results in office environments. Whilst the study only looked at
two office buildings from a tertiary education institution in Sydney, Australia, it
highlights the need for a more robust and holistic approach to building performance
evaluation that includes both objective and subjective data. However, this does not
require a re-invention of the wheel. POE is simply one of a suite of tools to measure
building performance and should be used in conjunction with other methods to
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evaluate all aspects of a building; including the social, psychological and physical. It
is the authors view that the combination of objective building performance data and
subjective satisfaction ratings may offer a more valid and reliable evaluation of a
building’s success.
6.
Acknowledgements
7.
References
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Abbaszadeh, S., Zagreus, L., Lehrer, D. and Huizenga, C. (2006), 'Occupant
satisfaction with indoor environmental quality in green buildings',
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Indoor Environment for People, Lisbon, Portugal, 4-8 June 2006
Aggerholm, S. (2002), 'Hybrid Ventilation and Control Strategies in the Annex 35
Case Studies', IEA Annex 35 Technical Report, Hertfordshire, UK,
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ASHRAE (2001), Chapter 8: Thermal Comfort, in Handbook of Fundamentals,
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and Air-Conditioning Engineers
ASHRAE (2010), 'Thermal Environmental Conditions for Human Occupancy',
ASHRAE Standard 55-2010, Atlanta, Georgia, American Society of Heating,
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Baird, G. (2005), 'Responses to sustainable design - User perceptions of eight
academic and library buildings', The 2005 World Sustainable Buildings
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Baird, G. (2011), 'Did that building feel good for you? Or - Isn't it just as important to
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Baird, G. and Dykes, C. (2012), 'The potential for the use of the occupants' comments
in the analysis and prediction of building performance', Buildings, 2(1): 33-42
Baird, G., Leaman, A. and Thompson, J. (2012), 'A comparison of the performance of
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Baker, N. and Standeven, M. (1996), 'Thermal comfort for free running buildings',
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BCO (2007), 'Guide to Post Occupancy Evaluation', London, UK, British Council for
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Bechtel, R. and Srivastava, R. (1978), 'Post-occupancy evaluation of housing',
Washington, D.C., USA., US Department of Housing and Urban Development
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Acknowledgements
This project was funded in part by an Australian Research Council Discovery
Grant (DP0880968). We are enormously grateful to Adrian Leaman for permission to
use the BUS questionnaire under license and his assistance in data analysis. We would
also like to thank the University s Office of Facilities Management for their support.
Finally, and most importantly, we express our appreciation to all the building
occupants who responded to the questionnaires.
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Figure 1. Climatology of the case study building site (adapted from BoM, 2011)
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Figure 2a) The MM building as viewed from the north facade featuring operable windows
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with external solar shading devices on north-facing windows
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Figure 2b) User-operated windows and internal grilles in the North and South perimeter
offices of the MM building
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Figure 3a) The NV building as viewed from the north facade featuring occupant-operated
windows with some individual air-conditioner units
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Figure 3b) Occupants often use portable fans or heaters for additional cooling/heating
throughout the year
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Figure 4. Summertime thermal environment recorded for the MM and the NV building (October 2009 to April 2010). Each data point
corresponds to days in which thermal comfort questionnaires were administered
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Figure 5a) Average APD and PPD recorded in the MM building
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Figure 5b) Average APD and PPD recorded in the NV building
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Figure 6a) Percentage of thermal acceptability votes registered in the MM building
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Figure 6b) Percentage of thermal acceptability votes registered in the NV building
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Table 1. Forgiveness factor and dissatisfaction percentages of variables in the POE for the
MM and NV building
Variable
Temperature in summer
Ventilation in summer
Comfort overall
Lighting overall
Noise overall
Perceived productivity
Dissatisfaction (%)
MM (n = 86) NV (n = 81)
58
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0.99
Forgiveness factor
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Table 2. List of keywords and phrases used to identify complaints in each category.
Category
Temperature
Ventilation
Noise
Lighting
Keywords and Phrases
MM Building
(n = 167)
Hot, cold, heat, temperature,
51 (31%)
air-conditioning
Air, ventilation, draught,
27 (16%)
humidity
Noise, outside, students,
64 (38%)
talking
Glare, lighting, window,
25 (15%)
blinds,
NV Building
(n = 108)
60 (56%)
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13 (12%)
25 (23%)
10 (9%)
4.4. Results and Discussions Summary
The preceding sections of this chapter, i.e. Paper 4.1, Paper 4.2 and Paper 4.3, present
the results, as well as the discussions and conclusions of each study in turn. Whereas each
study, and its resulting paper, covers specific aims and objectives related to its topic, several
overarching themes emerge from this ensemble. These themes: cultivating environmental
attitudes in green buildings (i.e. the ‘green occupant’ phenomenon), engineering comfort
expectations, and incorporating occupants into building design, are interrelated across each
paper. In highlighting these themes, this section discusses the key findings of each paper and
how they fit within the broader context of the thesis.
4.4.1. Cultivating Environmental Attitudes
The first paper in this thesis (Paper 4.1) investigates how environmental attitudes
relate to occupants’ forgiveness of green buildings. Substantial savings in terms of energy
consumption and GHG emissions can be realised through the construction of ‘green’
buildings (GBCA, 2008). However, the difficulty in optimising energy efficiency within
green buildings involves the attitudes or behaviour of the occupants. Browne and Frame
(1999) suggest that in order for green buildings to work effectively and maximise their
climate change mitigation potential, their occupants need to think and act in a way that
complements the buildings’ green design intent. In other words, green buildings need green
occupants (Browne and Frame, 1999). Prior to this study, the level of pro-environmentalism
within buildings had never been investigated; this study was the first to use the NEP scale
(Dunlap and van Liere, 1978; Dunlap et al., 2000) in conjunction with the BUS POE
questionnaires (BUS, 2009) to explore the relationship between environmental attitudes and
occupant satisfaction within MM and NV buildings.
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Green buildings are often promoted as offering higher quality, more comfortable and more
productive environments for their occupants (e.g. Huizenga et al., 2003). Whilst there is little
empirical evidence in the literature to support this notion, previous studies suggest green
buildings lead to higher levels of occupant satisfaction (e.g. Abbaszadeh et al., 2006; Leaman
and Bordass, 2007; Paul and Taylor, 2008; Brager and Baker, 2009). Paul and Taylor (2008)
compared occupants’ comfort perceptions and overall satisfaction with the workplace
between a green (NV) and conventional (AC) building located in Australia’s south-eastern
region of Albury-Wodonga. This region’s climate is characterised as having hot dry summers
and cool winters. Their study, conducted across an Australian summer season (December
2000 to February 2001), revealed that thermal environments perceived to be warm, i.e. those
occurring in the green building, caused lower levels of satisfaction that those environments
perceived as cool or thermally comfortable (typical of conventional AC buildings) (Paul and
Taylor, 2008). On this basis, the warmer summertime thermal environment of the NV
building, compared to the cooler indoor temperatures found in the MM building (Figure 4.1.3
in Paper 4.1, page 103) should have elicited warmer comfort perceptions and lower occupant
satisfaction. However, both buildings were, in general, poorly received by their occupants in
terms of occupant satisfaction, thermal comfort and perceived productivity (Deuble and de
Dear, 2010). Despite the differences between each buildings’ physical thermal environment,
the average forgiveness factor for occupants in the NV building was significantly higher than
that of their MM counterparts (Table 4.1.1 in Paper 4.1, page 104). This is consistent with an
emerging trend in Australian green buildings noted by Leaman et al. (2007), and suggests that
occupants of the NV building were more tolerant of the less-than-ideal conditions
experienced in their building than their MM building counterparts.
Leaman and Bordass (1999) interpret the ‘forgiveness factor’ as a measure of how far people
can stretch their comfort zone by overlooking and accepting inadequacies of their building’s
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thermal, acoustic and visual environments. The higher forgiveness scores typically found in
‘green-intent’ or ‘green’ buildings are often attributed to their occupants having some degree
of personal environmental control (Leaman and Bordass, 2007). Furthermore, this tolerance
of less-than-ideal indoor environments could also indicate that occupants may have an
understanding of, and connection with, the outdoor climate by virtue of the building’s design
(Kwok and Rajkovich, 2010; Baird, 2011b). Both case study buildings in this thesis afforded
their occupants similar degrees of occupant-orientated environmental control, or ‘adaptive
opportunities’ (Baker and Standeven, 1996) to control air movement/ventilation (operable
windows) and lighting (shades, artificial lighting). The only difference was that the MM
building resorted to centralised HVAC whenever and wherever indoor temperatures exceeded
the 25°C trigger temperature.
In acknowledging that neither overall occupant satisfaction nor personal environmental
control can explain these findings, we are left to consider another covariate to this
relationship; environmental attitudes as measured with the NEP (Dunlap et al., 2000). The
NV building’s occupants had significantly higher mean NEP scores than their counterparts in
the MM building (Table 4.1.1 in Paper 4.1, page 104). Employment in environmentallyinclined disciplines is considered a major determinant of NEP scores (Ewert and Baker,
2001). When categorised into either environmental or non-environmental science academic
disciplines, the non-environmental science academics of the NV building measured similar
levels of environmental attitudes (NEP scores) as the occupants of the MM building. Despite
this, however, the forgiveness factors of occupants in the MM building remained significantly
lower than that of the non-environmental occupants in the NV building (Table 4.1.2, page
104). These results suggest that occupants of the NV building, regardless of their academic
discipline or environmental orientation, were more forgiving of their building. The linear
regression model shown in Figure 4.1.4 (Paper 4.1, page 104) supports the hypothesis that the
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‘green’ building users were more prepared to overlook and forgive less-than-ideal conditions
than their ‘brown’ (non-green) counterparts.
This correlation could be the result of what environmental psychologists refer to as place
identity: the conception of the self or personal identity that has been constructed on the basis
of the place to which the individual belongs (Proshansky et al., 1983; Lalli, 1992; Bonaiuto et
al., 1996; Devine-Wright and Clayton, 2010). This concept is not to be confused with place
attachment, which is a person’s emotional or affective bonds to a place caused by the longterm connection with a certain environment within which that person becomes accustomed to
its surroundings (Hidalgo and Hernandez, 2001; Lewicka, 2011). Place identity theory
predicts that those people who feel empathetic towards the environment would be more likely
to identify with a green building and, therefore, more likely to have a positive evaluation of
the building’s indoor environmental conditions (McCunn and Gifford, 2012). On the other
hand, environmental empathy would be negatively correlated with place identity in
conventional AC buildings, and, in turn, result in a less positive evaluation of the workplace
environment in such a building. In support of this notion, Monfared and Sharples (2011)
suggest that occupants’ disengagement with the building’s green identity can affect their
satisfaction with the building. Given the higher levels of pro-environmental attitudes and
forgiveness factors observed in the ‘greener’ NV building (Paper 4.1), these occupants are
more likely to identify themselves as being ‘green’, and therefore form a connection with the
‘greenness’ of their building.
The findings from Paper 4.1 highlight how occupant attitudes and expectations play an
important role in the way green buildings are designed, built and received. Whilst it has not
been determined if occupants of green buildings are more actively engaged in sustainable
behaviours than those in conventional AC buildings, this study suggests that green occupants
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are best suited to green buildings. Given the study presented in Paper 4.1 did not focus on
pro-environmental behaviour but rather the attitudes that presumably drive them, it is
nonetheless important to understand the key aspects of the physical environment or
behavioural context which influence individuals to participate in pro-environmental
behaviours. Currently, there is little evidence to suggest that green design in office buildings
has a positive effect on employee engagement (i.e. job satisfaction, perceived productivity
and organisational commitment) or on environmental attitudes and behaviours (McCunn and
Gifford, 2012). Needless to say, the results from Paper 4.1 indicate that occupants’
environmental attitudes can and do affect their forgiveness of green buildings.
It is suggested that occupants with greater environmental beliefs and concern are able to
appreciate and tolerate green buildings if their design-intent matches their own altruistic
behaviour and pro-environmental motivations. In other words, green occupants are able to
forgive the less-than-ideal conditions inside green buildings because they perceive
themselves, and the building, as a co-operative partnership working towards a common
solution to environmental problems, such as climate change mitigation. Already we are
seeing successful examples of these strategies working in different ways. Many multinational corporations have established themselves as being committed to environmental
issues and green building designs. These companies understand the role buildings must play
to counteract climate change and preserve the environment for future generations. As a means
of broadcasting their company’s ‘green’ reputation, headquarters are often accommodated
within some of the world’s iconic green buildings (as rated by rating tools, e.g. LEED in the
US, BREEAM in the UK, and Green Star in Australia). Such corporations maintain their
‘green image’ through the selective employment of occupants pre-disposed to work in green
buildings because of their environmental attitudes. By understanding how their
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environmental attitudes match the building’s green design features, such occupants can
achieve high levels of satisfaction and forgiveness for the building.
Given the urgency to mitigate climate change, it has become apparent that people’s attitudes,
and the behaviours associated with them, can be shifted. Whilst buildings take years to build
or months to retrofit, the path to altering people’s expectations of the built environment
presents another, potentially more accessible strategy. Many behaviour change programs
within the US and Canada have discovered the power of social norms, i.e. the customary
rules that govern behaviour in groups and societies, to induce energy conservative and proenvironmental behaviours (Schultz et al., 2007). This study acknowledges that the
forgiveness of green buildings can be cultivated, and given the multitude of sustainable and
pro-environmental behaviour literature, there is great potential for occupants to be ‘reeducated’ about the role buildings play in addressing global climate change (e.g. Berkhout et
al., 2006; Schultz et al., 2007; Griskevicius et al., 2008; Nolan et al., 2008; Allcott, 2011;
McKenzie-Mohr, 2011; Stern, 2011). Perhaps the most notable example of this is Japan’s
Cool Biz campaign. In their attempts to help mitigate climate change and reduce the
country’s GHG emissions by 6% by 2010, Japan’s Ministry of the Environment (MOE, 2006)
widely encouraged businesses and the general public to set office air-conditioners at 28°C
during summer (Koike, 2006). As a part of this campaign, the MOE promoted ‘Cool Biz’,
encouraging business people to wear cool and comfortable clothes to work efficiently in
offices where thermostats were set at around 28°C. Following acceptance by the majority of
companies and people, it was estimated that during the summer months of June through to
August 2005, electricity demand was reduced by 210 million kWh; and accordingly,
emissions were reduced by 460,000 t CO2 (Koike, 2006; IPCC, 2007).
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The need to develop sustainable lifestyles and attitudinal and behaviour change is central to
achieving sustainability in the built environment (Jackson, 2005). Environmental psychology,
sociology, occupational psychology, and marketing can all play a role in understanding the
drivers for pro-environmental behaviours (Kollmuss and Agyeman, 2002; McKenzie-Mohr,
2011). Clearly there is ample scope for further research in this area, with multidisciplinary
teams of psychologists, building and environmental scientists, facility managers, and
marketing experts collaborating to identify, design, implement and test interventions for proenvironmental attitudes and behaviours by building occupants. In doing so, such initiatives
will not only communicate the necessity of creating a culture of sustainability and resource
conservation among a building’s occupants, but also develop the building’s true ‘green’
potential.
4.4.2. Engineering Occupant Expectations and Perceptions of Control
In investigating how MM ventilation affects occupant comfort, Paper 4.2 represents
one of only a handful of thermal comfort field studies conducted within MM buildings. MM
buildings represent a combination of both AC and NV buildings: reduced energy
consumption compared with centrally-controlled HVAC systems and the greater range of
acceptable temperatures associated with natural ventilation through occupant-controlled
windows. Despite increasing interest in such ventilation strategies, little is known about the
effects of MM ventilation on thermal comfort, especially in commercial office settings.
Furthermore, topical debates regarding whether international adaptive comfort standards
should be applicable to MM buildings remain unresolved. Whereas the global ACS in
ASHRAE Standard 55 (ASHRAE, 2010) precludes MM buildings, its European counterpart,
EN15251 (CEN, 2007) allows the more flexible ACS to be applied to MM buildings during
times when they are employing natural ventilation. This study, therefore, aimed to test
whether the adaptive comfort model can be applied to MM buildings during NV mode.
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Thermal sensations registered by the occupants (AMV) and those predicted based on
Fanger’s heat-balance equation (PMV) (1970) recorded in both AC and NV modes were
compared. As illustrated in Figure 4.2.9a in Paper 4.2 (page 114), the thermal sensation votes
show very strong correlations with the indoor operative temperature during AC mode. This
suggests that within this mode, occupants act as passive recipients of the thermal
environment; when operative temperature increases, they tend to feel warmer. It should be
noted that these results were compatible to when all thermal sensations (predicted and
observed) recorded in both modes were combined (Figure 4.2.8 in Paper 4.2, page 113). In
addition, the range of thermal sensations was equal amongst the observed and predicted
values. However, whereas the PMV values in NV mode again show high correlation with the
indoor operative temperature, the observed AMV values do not match this correlation (Figure
4.2.9b in Paper 4.2, page 114). The gentler gradient found between the AMV values and
indoor operative temperature suggests that occupants were more adapted to the thermal
environment. Moreover, the thermal sensations predicted by the PMV model ranged from -1
(slightly cool) as the lowest to +1.5 (slightly warm to warm) as the highest. Across the same
range of temperatures, the occupants’ thermal sensations registered between the regions of 0
(neutral) to +1 (slightly warm) suggesting they were able to adapt to the indoor environment
by availing themselves of the adaptive opportunities, such as opening/closing their window;
adjusting their clothing, and/or shifting their expectations (Brager and de Dear, 1998).
Adaptive comfort theory predicts that the gradient of the relationship between thermal
sensation and indoor operative temperature is inversely related to the adaptability of the
subjects. In other words, as adaptability increases the gradient approaches zero (horizontal).
Figure 4.2.10 in Paper 4.2 (page 114) demonstrates the role of occupants’ psychological and
behavioural adaptations in manipulating thermal perceptions between AC and NV mode.
During times when the building was employing air-conditioning, an indoor operative
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temperature of 27°C (a PMV = +1 (slightly warm) environment) elicited significantly
‘warmer-than-neutral’ thermal sensations than the same thermal environmental conditions
within NV mode. Even at a temperature of 21°C, the average AMV value recorded by
occupants in NV mode was neutral (0.16) whereas in AC mode, the average observed thermal
sensation was significantly cooler (-0.42). Whereas this difference (0.58) is only about half of
a thermal sensation unit (0.5), these findings suggest that thermal perceptions were affected
by the building’s mode of operation over-and-above the objective indoor climatic conditions.
Comparable to previous studies reflecting differences in comfort temperatures on a buildingby-building basis (e.g. Busch, 1992; de Dear and Brager, 2002; Nicol and Humphreys, 2002),
the resulting linear regression model fitted to observed thermal sensations (AMV) (Figure
4.2.10 in Paper 4.2, page 114) clearly shows the adaptive model is best suited to explain
occupant comfort during times of natural ventilation within the same building. In relation to
the differences in scope between the ASHRAE and European comfort standards, the findings
presented in Paper 4.2 favour EN15251’s application of the adaptive comfort model instead
of PMV-PPD to MM buildings when they are operating in NV mode. During AC mode,
Fanger’s PMV-PPD model (1970) displayed good correlations with observed thermal
sensations (AMV).
Apart from justifying the inclusion of MM buildings within the ACS of ASHRAE’s Standard
55-2010, this study further highlights the complexity of comfort perception and psychological
adaptations in MM environments. According to Table 4.2.1 in Paper 4.2 (page 114), there
were no significant differences between the thermal environments of each mode. Across the
entire 12 months in which this study was conducted, the average indoor operative
temperature recorded in AC mode (23.3 ± 1.8°C) was, in fact, very close to that for NV mode
(23.1 ± 1.2°C). Additionally, the average air velocity during both modes remained very
similar as well (0.10 ± 0.05 m/s) (Table 4.2.1, Paper 4.2, page 114). Despite the limitation in
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expressing differences between two modes on the basis of average values, the only physical
variable that changed appreciably was clothing insulation. Occupants, on average, wore
significantly less clothing (clo = 0.50) during natural ventilation than when the building was
in AC mode (clo = 0.57). This difference of 0.07 clo (equivalent to a short sleeve T-shirt; or
the difference between long trousers and shorts for men, or between a dress and knee-length
skirt for women) suggests occupants felt warmer in NV mode and cooler in AC mode. This
finding is further supported by the significantly warmer AMV value recorded in NV mode
(0.43) compared to AC mode (0.19). Understandably, as indoor temperatures are allowed to
rise during NV mode to prompt switch-over to AC mode (shown in Figure 4.2.6 in Paper 4.2,
page 113), occupants would actively remove items of clothing in order to maintain thermal
neutrality. Considering the negligible differences in the thermal environment of each mode,
there is no reason to suggest the occupants would sense the need to remove or add clothing
during these events. Nonetheless, while these differences are possibly reflected in the
discrepancy between observed (AMV) and predicted (PMV) thermal sensations in both
modes (Figures 4.2.9a and 4.2.9b, Paper 4.2, page 114), it is suggesting that contextual
effects, such as shifting expectations and perceived control may indeed influence thermal
comfort.
Despite negligible difference in the actual indoor environment, the occupants’ thermal
sensations/perceptions within the MM building differed between AC and NV modes of
operation (Table 4.2.1 in Paper 4.2, page 114). Whilst difficult to pinpoint the actual cause of
this phenomenon, it is speculated that the occupants’ expectations and the ability to control
their windows (or at least knowledge of this ability once the building was in NV mode) are
the reasons why thermal sensations during NV mode were more adaptive compared to those
in AC mode (Figure 4.2.10 in Paper 4.2, page 114). By viewing the AC display panel (Figure
4.2.5 in Paper 4.2, page 113) upon entering their respective corridor to their office, occupants
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are aware of their office’s current mode of operation, either AC or NV. When the building
switched into NV mode occupants located in the North and South perimeter zones are then
able to open their windows for additional ventilation. Once the occupants knew they had
control of their windows during NV mode, their expectations of the thermal environment
shifted to allow for a greater range of acceptable indoor temperatures which could be
accommodated through use of their operable windows. It is also likely that the ratio of
outdoor ventilation to air velocity would be greater during natural ventilation than airconditioning; so it is entirely possible that improved thermal comfort under NV mode
resulted from cross-modal interactions between air quality and thermal comfort (Deuble and
de Dear, 2011). However, since these variables were not recorded during this study, this
potential relationship could not be confirmed.
Within the present study (Paper 4.2), there is evidence to support the effects of psychological
adaptation, i.e. expectations and perceived control, on thermal comfort. Psychological
adaptation refers to an altered perception of, or response to, the thermal environment,
resulting from one’s thermal experiences and expectations (Auliciems, 1981; Fountain et al.,
1996). Brager et al. (2004) suggest that subjects with greater access to control actively shift
their expectations to become more tolerant of, and potentially prefer, conditions previously
considered to be thermally uncomfortable. Similarly, Pacuik (1989) proposed that perceived
control (expectation) was one of the strongest predictors of thermal comfort and satisfaction.
The resulting divergence between observed and PMV-predicted comfort found within NV
mode (Figures 4.2.9b and 4.2.10 in Paper 4.2, page 114) can be ascribed to shifting comfort
expectations (de Dear and Brager, 2002). Indeed, the role of personal control on expectation
and thermal response has important implications in MM buildings. Within the context of the
AC mode, it is plausible that occupants have come to expect thermal constancy and even the
slightest departure away from that expectation is sufficient to prompt complaint (de Dear,
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2007). Given the indoor temperatures prevailing during times of natural ventilation are more
closely correlated with outdoor climatic conditions than in centrally AC buildings, occupants
come to expect the indoor thermal environment to match the outdoor weather conditions,
especially during NV mode. Considering the NV mode affords greater degrees of thermal
control to its occupants than to those of AC buildings, it is this sense of control that leads to
more relaxed expectations and greater tolerance of the thermal excursions typical of buildings
featuring natural ventilation and operable windows (Brager et al., 2004).
Certainly, the maintenance of indoor climates accounts for a substantial component of energy
end-use, and therefore, GHG emissions in the buildings sector. However, when building
occupants are offered adequate adaptive opportunities, e.g. operable windows, the
psychological dimensions of comfort (i.e. expectation and control) hold as much promise for
mitigating climate change in the buildings sector as the more frequently mentioned technical
GHG abatement options of the building envelope and HVAC systems found in the literature
(IPCC, 2007; Levine et al., 2007; Urge-Vorsatz et al., 2007). Although the potential of human
thermal adaptation to indoor climates was recognised as highly relevant to energy savings,
the IPCC (2007) focused its attention on market transformation that didn’t account for
adjustments to lifestyles or comfort levels. Nonetheless, it is becoming increasingly clear that
simply shifting building thermostat settings to be closer to outdoor temperatures, without
resorting to expensive retrofits to the building envelope or HVAC systems, can have a
profound effect on energy consumption and the associated GHG emissions. For example, by
shifting the thermostat set-point in a conventionally AC office building in Melbourne one
degree higher (from 22°C to 23°C), Ward and White (2007) measured a 14% reduction in
HVAC energy consumption on identical summer days. These findings are significant
considering HVAC energy typically accounts for up to 40-50% of total commercial building
energy end-use. Therefore, by changing comfort expectations of the building occupants away
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from static HVAC set-points to more adaptive indoor temperatures that follow the natural
swings in the prevailing outdoor weather, such efficiency measures can be readily applied
across much of the existing building stock, and not just new construction and refurbishments.
However, the time taken for occupants to adapt to variable indoor temperatures after they
have been acclimatised to static HVAC environments remains to be seen.
4.4.3. Incorporating Occupants into Building Design
The complexity of occupant expectations and attitudes with respect to indoor thermal
environments are also echoed in the final paper of this thesis (Paper 4.3). This study tested
the validity of contemporary POE methods through comparisons with thermal comfort
studies conducted in the MM and NV buildings, and in doing so, provides recommendations
as to how occupant-centred building performance evaluations can be enhanced. The POE has
been taken as a means to evaluate actual building performance. However, recent applications
of these tools have relied on more subjective criteria, such as occupant satisfaction, to
evaluate building performance. This paper argues that due to a lack of contextual
information, continued feedback and physical (instrumental) measurements of the building’s
indoor environment, contemporary POE methods potentially over-exaggerate poor building
performance and as such, provide a superficial assessment of the buildings’ occupants.
The indoor and outdoor climates for each building were measured over the duration of this
study (between March 2009 and April 2010). Not surprisingly, the NV building experienced
significantly warmer indoor temperatures than the MM building during Sydney’s summer
months (Figure 4.3.4 in Paper 4.3, page 162). On average, temperatures in the MM building
were 2°C cooler than in the NV building, emphasising the effect of the MM building’s AC
switch-over trigger temperature. Although more modest temperatures were recorded in the
MM building, results from the POEs conducted in both buildings (outlined in Paper 4.1)
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demonstrate higher levels of occupant dissatisfaction in the MM building compared to the
NV building (Table 4.3.1 in Paper 4.3, page 167). Previous studies indicate that building
users often perceive NV buildings as too hot and AC buildings as too cold, in summer
(Leaman and Bordass, 2007; Baird et al., 2012). Despite the less-than-ideal conditions
experienced in the NV building, its occupants reported moderate levels of satisfaction
(around 80%) and this can be understood with reference to their higher forgiveness factor
compared to their MM counterparts (Table 4.3.1 in Paper 4.3, page 167).
From parallel ‘right here, right now’ thermal comfort studies conducted in both buildings, it
was found that occupants’ perceptions of comfort and thermal acceptability not only differed
between these buildings but so too did their POE and thermal comfort results. According to
Fanger’s PMV-PPD model (1970), as expressed in ASHRAE 55-2010, the indoor
environmental conditions experienced in the NV building would be deemed uncomfortable as
indoor operative temperatures were well above the upper limit of 25°C (Figure 4.3.4 in Paper
4.3, page 162). Despite this, the occupants’ actual percentage dissatisfied (APD) in the NV
building was, on average, lower than the PPD values predicted using Fanger’s heat-balance
model (Figure 4.3.5b in Paper 4.3, page 164). In comparison, occupants of the MM building
registered greater levels of thermal dissatisfaction (i.e. higher APD values in Figure 4.3.5a in
Paper 4.3, page 163) than those predicted using PMV-PPD across the same range of
temperatures. Despite summertime temperatures within the MM building being constrained
between 20-25°C, occupants expressed significantly greater levels of thermal discomfort.
According to the analyses shown in Figure 4.3.6a in Paper 4.3 (page 165), within the MM
building, over 20% of occupants surveyed found the indoor temperature to be unacceptable,
even at moderate temperatures, e.g. 20-25°C. In contrast, Figure 4.3.6b in Paper 4.3 (page
166) demonstrates that under similar environmental conditions, fewer occupants (as low as
5%) in the NV building found the indoor temperature to be unacceptable. In agreement with
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other POE studies, these findings suggest that the NV occupants were more tolerant and
accepting of the thermal environment, despite experiencing significantly warmer
temperatures than their MM counterparts (Leaman and Bordass, 2007; Baird, 2011b).
It is evident from this paper that objective criteria, such as temperature and PMV-PPD, are
not the only determinants of comfort. Occupants can be a useful and inexpensive source of
information about IEQ (Peretti and Schiavon, 2011). The comparison of occupant-based
comments and anecdotal evidence offer the invaluable, but often overlooked context and
complexity of user experiences (Bordass and Leaman, 2005b; Moezzi and Goins, 2011).
From the list of keywords and phrases related to temperature, ventilation, noise and lighting
(Table 4.3.2 in Paper 4.3, page 168), 167 complaints were recorded for the MM building and
108 for the NV building. As reinforced by the physical instrumental measurements (Figure
4.3.4 in Paper 4.3, page 162), over 50% of comments gathered from the NV building
complained about the “temperature”. Within the MM building, “temperature” was the second
most reported problem (31%), with “noise from outside” and “from colleagues” as the most
common complaints (38%). These results shed light on a common theme emerging from
many recent POE studies in NV and MM buildings. Many studies reveal air movement,
temperature, glare and noise as the most common causes for dissatisfaction in green buildings
(Abbaszadeh et al., 2006; Brager and Baker, 2009; Moezzi and Goins, 2011; Baird et al.,
2012). From their analysis of occupants’ comments and satisfaction scores across 47 POE
studies, Baird and Dykes (2012) found that negative comments (i.e. complaints) were
moderately correlated with lower satisfaction scores and positive comments were correlated
with higher satisfaction scores. While the results in Paper 4.3 demonstrate potential areas of
improvement and lessons to be learned in future green building construction, they also
suggest that the building may not be the problem. This begs the question: how much does the
POE get influenced by non-building contextual factors?
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Within building performance studies, it is not uncommon to find gaps between the designer’s
expectations and built outcomes (Leaman et al., 2010). Whereas the MM case study building
was deemed comfortable on objective criteria, its occupants felt the need to complain about
the building’s performance. These results indicate that occupants predisposed to complain,
either due to contextual (e.g. work-related) or physical (e.g. temperature) factors will overexaggerate poor building performance. The discrepancies between thermal satisfaction and
acceptability between the POE and thermal comfort results (in Paper 4.3) further supports the
hypothesis that occupants can and do use POEs as a vehicle for complaint about general
workplace issues, unrelated to their building. Much of the information generated by POE is
inherently subjective and often negative (Vischer, 2002; Baird and Dykes, 2012). Many
researchers have advocated more robust POE approaches, thereby providing a highly
sophisticated and detailed assessment that enables the triangulation between physical
environmental measures and subjective occupant appraisals (Preiser, 2002; Preiser and
Vischer, 2005; Turpin-Brooks and Viccars, 2006). More importantly, Paper 4.3 stresses the
importance of educating occupants about design decisions and intent, comfort provision, as
well as the environmental consequences of their actions (Brown and Cole, 2009). In doing so,
such induction programs may play a valuable role in improving comfort and calibrating green
building occupants’ expectations.
4.5. Synthesis
In light of findings from Papers 4.1, 4.2 and 4.3, it is apparent that green buildings,
i.e. MM and NV buildings, can perform well. However, the success (or failure) of these
buildings, and their performance, are ultimately determined by their occupants. Buildings are
primarily designed and built for their intended occupants, however in many cases this is done
without explicit consideration of the buildings end-users’ needs or preferences (Way and
Bordass, 2005). As a result, many occupants do not understand how to operate their building,
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which can often lead to high levels of discontent (Leaman and Bordass, 2007). In order for
green buildings to perform effectively in the context of a low-carbon future, a shift is required
from conceptualising the occupant as a passive recipient of the indoor thermal environment,
to the inhabitant that interacts and plays a more active role in the maintenance and
performance of their building (Brager and de Dear, 1998; Cole et al., 2008; Brown and Cole,
2009).
Within this thesis, the term ‘green’ occupant is used to describe building users who are intune with their building’s performance and understand the role green buildings can play in
mitigating climate change. Collectively, the overarching themes of environmental attitudes,
occupant comfort expectations, and incorporating occupants into building design, underscore
the importance of occupant engagement within commercial office buildings. At its pinnacle,
occupant engagement describes a building-wide culture in which empowered building
occupants are aware of and accountable for their own energy and water use, and waste
disposal. However, occupant engagement can also encompass the process of creating that
culture – including decisions made by architects and engineers as well as building managers,
employers, and other stakeholders. The findings from Papers 4.1, 4.2 and 4.3 clearly identify
the need to change people’s attitudes, expectations and behaviours towards green buildings to
better reflect the design-intent of the building. Furthermore, these studies suggest that the use
of occupant engagement strategies, such as, providing feedback, transforming social norms,
occupant education and empowerment, will enable building users to become ‘green’
occupants.
There are many reasons why buildings don’t perform as well as expected, however, the
hardest-to-manage reason for longer-term performance gaps is the way people live and work
in their buildings. Individual occupants and the choices they make, such as opening/closing
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windows, overriding automated systems, leaving appliances on, etc directly affect the
building’s energy performance. While it is estimated that 20-50% of energy use in buildings
can be attributable to occupant behaviour (Janda, 2011), building users are unaware of the
energy they use and its overall impact on the building’s energy consumption. Within each of
the papers presented, it is apparent that building designers need to incorporate features that
allow the building to be operated properly. The use of adequate feedback systems and
effective communication can provide meaningful real-time consumption information which
helps the building managers and occupants understand how their choices affect energy use.
Constant communication between the building owners, their managers and occupants is
another important part of occupant engagement. However, in order to be effective, such
communication needs to be contextualised, direct and visually engaging. All three papers
hinge on the idea that environmental attitudes can be cultivated using a variety of
environmental psychology and behaviour change principles, e.g. changing social norms
through community-based social marketing (CBSM) (McKenzie-Mohr, 2011). CBSM
involves intensive, interactive work and two-way feedback at the community level and
focuses on simple and incremental changes in habits, setting measurable short- and long-term
goals and tracking progress (McKenzie-Mohr, 2000). The connection of energy consumption
data and daily habits through visual displays can be a powerful tool in transforming social
norms within the context of commercial buildings. Moreover, competitions and financial
incentives can also provide a social context in which people will track their energy and water
use and make public commitments to changing habits (Driedger, 2011).
As organisations begin closely tracking occupants’ habits and occupants start to be more
aware of their own energy consumption, people can start to be held accountable for less
sustainable behaviours. At its core, occupant engagement is about occupant empowerment.
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As building owners begin to set energy performance goals through green building rating
tools, such as NABERS and Energy Star (both of which are based on actual measured
building performance), tenant companies and their employees also need to be on board with
building-wide goals. Each paper highlights the need for occupants to be more involved with
their building’s performance and operation. While education campaigns and seminars were
held for the occupants of the MM building upon its completion, these were largely
unattended. As such, the occupants did not know how to effectively and efficiently use the
building. Considering the high levels of occupant dissatisfaction within this building, the
papers provide an impetus for greater educational and empowerment strategies within green
buildings. If these buildings are contracted to sustain high levels of energy, water, IEQ or
IAQ performance, the occupants need to feel empowered and connected with their building.
Greater knowledge of the building’s design features and how they operate will achieve
effective, long-term occupant engagement programs and strategies, thus creating a buildingwide culture of sustainability and ‘green’ occupants.
4.6. Limitations
This chapter presented the main results in the form of three papers that have been
published in, or submitted to peer-reviewed journals. Limitations of the methods used in this
thesis can now be discussed.
4.6.1. Instrumentation and Data Collection
Dataloggers were placed within one metre of the subject’s workstation to accurately
measure the immediate thermal environment. Occupant’s desks were typically located next to
the window (with their back being in direct sunlight, especially for offices on the Northern
façade). Every attempt was made to ensure the black globe sensors attached to the
dataloggers were not in direct sunlight; any erroneous indoor temperature measurements were
187
hence attributed to sunlight directly hitting the sensor. The heights and location of the
dataloggers were repeatedly checked during questionnaire sessions and HOBO data uploads.
However, there is no guarantee that the dataloggers were not mishandled over the course of
the study, which may have influenced the indoor climate measurements.
4.6.2. Sample Size and Response Rates
Considering both case study buildings used in this thesis have populations of over 200
occupants it was important to recruit a large number of participants for each study.
Notwithstanding attempts to ensure statistically significant sample sizes and response rates
within each building, it is plausible that the results may not accurately describe the entire
building population. In regards to the thermal comfort studies, 60 participants were recruited
from each building, representing approximately 30% of the total occupant population in each
building. These limited participant sample sizes can be attributed to difficulties in obtaining
permission from the building occupants to participate in the study. As such, thermal comfort
responses reported in this research may not be representative of the entire building.
In total, 163 POE and NEP questionnaires were distributed in the MM building with 86
completed questionnaire sets (39 male, 47 female) being collected, representing a response
rate of 53%. Within the NV building, 120 POE and NEP questionnaires were delivered 6 and
69 were completed (30 male, 39 female) to achieve a 57% response rate. Incomplete
responses were omitted from the samples during routine quality assurance processing. While
the POE methodology calls for at least 50% of the building population (BUS, 2009), these
response rates were sufficient for the purposes of benchmarking the results against the
Australian green building BUS database.
6
Questionnaires were administered to all occupants located on floors 6, 7 and 8 in the NV building between
March and April 2009. A separate follow-up study was conducted in March 2010 using the rest of the occupants
(located on floors 2 to 5).
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4.6.3. Questionnaire Data
Subjective questionnaires such as the POE, NEP and thermal comfort questionnaires
are potentially prone to bias, depending on the methods and context in which the
questionnaires are conducted. Since there was no way to directly influence or control for
psychosocial or contextual (non-physical) factors that affect occupants in the workplace,
participants’ responses may be either positively or negatively biased due to their high
susceptibility to observation-bias, otherwise known as the ‘Hawthorne effect’ (Franke and
Kaul, 1978; Sonnenfeld, 1985). In this regard, the Hawthorne effect would be considered
when the behaviour or responses of an individual or group change to meet the expectations of
the observer/researcher (Roethlisberger and Dickson, 1939; Landsberger, 1958; Parsons,
1974).
The subjective thermal comfort questionnaires were used to record occupant perceptions of
thermal comfort within their workspace. Considering these questionnaires were initially
piloted to reduce participant confusion, the researcher was on-hand to answer any questions.
As standardised clothing and metabolic activity checklists were simplified to include typical
office-based work garments, it is possible that deviations around these values may exist due
to the varying definitions of clothing garments and metabolic activity.
4.6.4. Context of the Study
Given that the case studies used in this research were academic office buildings
located at MQ, the results and conclusions presented in this chapter (Papers 4.1, 4.2 and 4.3)
are limited to these particular buildings in the context of Sydney, Australia. Whilst it is
plausible that some results may be applicable to non-academic MM and NV office buildings
and their occupants, by no means can the results of these studies be regarded as universal.
189
Furthermore, since the majority of data collected was during Sydney’s summer months, the
results were mainly focused on the use of air-conditioning for cooling purposes.
4.7. Chapter Summary
Comprised of three papers that have been published in, or submitted to, peer-reviewed
journals, this chapter presented the key findings and discussions from each study (i.e. Papers
4.1, 4.2 and 4.3) within the broader context of the thesis. In discussing the overarching
themes of these papers, i.e. cultivating environmental attitudes, engineering comfort
expectations and incorporating occupants into building design, their findings clearly
demonstrate the need for greater occupant engagement and involvement within commercial
buildings. Each study highlighted significant differences between occupants’ thermal
responses
under
different
indoor
environmental
conditions,
suggesting
people’s
environmental attitudes and expectations affect their perception of thermal comfort and
satisfaction. The development of ‘green’ occupants, especially in green buildings,
necessitates that building users are more in-tune with their building’s performance and
function. Through the use of feedback and energy tracking mechanisms, communication and
social norms, occupant empowerment and knowledge, the process of and result of engaging
occupants with their buildings will not only communicate the necessity of creating a culture
of sustainability and resource conservation among building occupants, but also highlight the
building’s true ‘green’ potential. The final chapter presents some concluding remarks and
recommendations for future research.
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Chapter 5. Conclusions
In order to maximise the climate change mitigation potential within commercial
buildings, the right balance between building design, occupants, their comfort expectations
and environmental attitudes is paramount. This thesis provides evidence to further support
expanding the scope of comfort provision and building performance evaluation in green
buildings to encompass a wide range of behavioural, psychological and contextual aspects.
Building on previous work in the field, the research extends the psychological dimensions of
thermal comfort and building occupancy studies to account for the contextual influences at
play in NV and MM buildings, such as attitudes, expectations, and personal control. In doing
so, this research provides evidence of how pro-environmental attitudes and comfort
expectations are associated with occupants’ satisfaction, experience and interaction with
buildings and their indoor environmental conditions. This final chapter addresses the aims
and objectives of each study and how they were achieved, and also, makes recommendations
for future research.
5.1. Summary of Aims and Objectives Addressed in This Thesis
This thesis evaluated how occupant expectations and environmental attitudes relate to
thermal comfort and occupant satisfaction within the context of low-energy indoor thermal
environments, as found in MM and NV buildings. Corresponding to a specific study and
journal paper, three main topics were covered in this thesis, i.e. environmental attitudes and
occupant satisfaction in green buildings (Paper 4.1); thermal comfort in MM buildings (Paper
4.2); and, the validity of contemporary POE methods (Paper 4.3). The research objectives of
each study and how they were addressed throughout this thesis are summarised below:
191
5.1.1. Environmental Attitudes and Occupant Satisfaction in Green Buildings
The study presented in Paper 4.1 addressed each of the following research objectives:
1. By conducting POEs within two ‘green’ buildings, i.e. a MM and a NV building, this
study aims to evaluate the occupants’ ‘forgiveness factor’ in relation to their thermal
environment.
Upon analysing the indoor climatic and outdoor weather conditions for the MM building
(identified as Building E4A in Section 3.2.1) and the NV building (identified as Building
E7A in Section 3.2.2), both buildings were found to exhibit some degree of dependence of
their indoor temperature on outdoor weather conditions. However, in comparison to the MM
building, the NV building experienced significantly warmer indoor temperatures throughout
the study. Furthermore, the range of temperatures experienced in the NV building was far
greater than in the MM building due to the latter’s BMS algorithm switching to AC mode
whenever indoor temperatures reached 25°C. The BUS POE questionnaires were used to
measure the levels of occupant satisfaction and ‘forgiveness factor’ within each building.
Both buildings were generally rated poorly by the occupants on the POE, especially the MM
building; however a higher forgiveness factor was recorded in the NV building. Considering
the forgiveness factor quantifies the extent to which building occupants can accept the
building’s indoor environmental conditions, this suggests that occupants of the NV building
were more forgiving of their building’s less-than-ideal indoor climatic conditions than their
counterparts in the MM building. From these case studies, it would seem that objective
thermal conditions within a building are not the sole determinants of occupant satisfaction
with thermal conditions, and that contextual factors may also be relevant. Earlier published
building occupancy studies have alluded to occupants’ ability to control their indoor
environmental conditions as the primary cause for the higher forgiveness scores found in
‘green’ buildings. However, given both case study buildings offer their occupants similar
192
degrees of adaptive opportunities, i.e. operable windows, we are left to explore another
possible factor that may be associated with the higher forgiveness factors observed in the
‘greener’ NV building.
2. Through the use of the NEP questionnaire, this study investigates occupants’ levels of
environmental attitudes within the MM and NV buildings. It is hypothesised that
broadly pro-environmental attitudes are associated with the stronger ‘forgiveness
factors’ towards indoor thermal environmental performance often reported in green
building POE studies in the research literature.
The NEP environmental attitude scale was supplemented with the POE to measure the
occupants’ level of pro-environmental attitudes within both buildings (outlined in Section
3.3.1). Occupants of the NV building had significantly higher levels of environmental
attitudes (NEP) than the occupants of the MM building. To eliminate any potential bias in the
NEP scores, occupants from the NV building were separated according to academic
discipline, i.e. those associated with environmental science (labelled the ‘Eco’ group) and
those associated with non-environmental science, e.g. Physics, Mathematics, Astronomy, etc.
(labelled the ‘Control’ group). Whilst the average NEP score for the ‘Eco’ group was
significantly higher compared to occupants of the MM building, the ‘Control’ occupants
measured similar NEP scores to their MM counterparts. Subsequently, occupants in the MM
building recorded significantly lower levels of forgiveness than those recorded in both staff
groups of the NV building. Therefore, it appears that pro-environmental attitudes are related
to occupants’ satisfaction and tolerance of the thermal environments found within green
buildings. Furthermore, in order for green buildings to maximise their climate change
mitigation potential, their occupants need to think and act consistently with the building’s
193
design-intent; the aphorism that green buildings need green occupants has been supported by
these case studies.
Paper 4.1 demonstrated a strong positive relationship between environmental attitudes and
forgiveness factors, suggesting that pro-environmental or ‘green’ occupants were more
forgiving of their building, especially those featuring aspects of green design. Despite
criticisms of their building’s IEQ, the ‘green’ building users were more prepared to forgive
less-than-ideal indoor conditions than their ‘brown’ (or ‘less green’) counterparts. As the NV
building is ‘greener’ than the MM building, the occupants of the former share a higher
tolerance of their building’s performance, supporting the hypothesis that pro-environmental
attitudes are closely associated with the stronger ‘forgiveness factor’ often observed in green
buildings. Admittedly, the direction of causality remains moot and requires further
investigation, but this study nonetheless amplifies how occupants’ environmental attitudes
play an important role in the way green buildings are perceived by their occupants.
5.1.2. Thermal Comfort in Mixed-Mode Buildings
The research objectives listed below were addressed in Paper 4.2:
1. This study aims to understand how MM ventilation affects occupant comfort by
comparing both observed and predicted thermal sensation votes recorded in AC and
NV modes. In doing so, this study will test whether the adaptive comfort model can
be applied to MM buildings, especially during times of natural ventilation.
Between March 2009 and April 2010, a longitudinal thermal comfort field study was
conducted within the MM building using a variety of objective (indoor and outdoor climate
conditions) and subjective (‘right here, right now’ comfort questionnaires) methods (outlined
in Section 3.3.2). Within AC mode, the relationship between observed (AMV) thermal
194
sensations and indoor operative temperature was strongly consistent with the PMV values.
However, during times of natural ventilation, the occupants’ AMV values did not conform to
the PMV values, suggesting occupants were more adaptive to the building’s indoor thermal
environment when the building was operating under NV mode. During AC mode, warmer
indoor operative temperatures were found to elicit much ‘warmer-than-neutral’ thermal
sensations than the same environmental conditions experienced during NV mode, suggesting
the occupants’ subjective thermal comfort perceptions were affected by the building’s mode
of operation over and above the objective indoor climatic conditions. These discrepancies
suggest that psychological adaptations, such as attitudes, expectations and control, may
influence occupants’ comfort perceptions, especially within a building that switches between
AC and NV environments. Given the opportunity to control their windows more readily
during NV mode, occupants’ expectations of the thermal environment apparently relaxed to
accept a greater range of indoor temperatures. Hence, the engineering of comfort expectations
away from conventional AC environments and towards more weather and seasonallyresponsive indoor temperatures, along with occupant-operated control strategies, hold great
promise for the successful mitigation of climate change and enhanced energy efficiency of
both new and existing commercial buildings.
2. In evaluating the current definition and scope of the adaptive comfort standards in
ASHRAE 55-2010 and EN15251-2007, the implications of this research are discussed
in the context of whether adaptive comfort standards for NV buildings should be
applied to MM buildings.
Despite its most recent revisions, ASHRAE’s Standard 55 (ASHRAE, 2010) still restricts the
application of the ACS to MM buildings, even if they are operating under a ‘free-running’ or
NV mode. According to ASHRAE, buildings using/equipped with mechanical cooling
195
systems, as is the case for MM buildings, are currently (mis)classified as AC. The strict
interpretation of this standard in MM buildings not only limits their operation to the more
restrictive PMV-PPD range of indoor thermal conditions, but also fails to maximise their
energy saving and GHG mitigation potential. On the other hand, the European standard
EN15251 (CEN, 2007) permits the more flexible adaptive comfort model to be applied to
MM buildings when they are operating under a NV mode. This study’s comparison of both
observed and predicted thermal sensation votes recorded in AC and NV modes found that the
adaptive comfort model was applicable to the MM building, especially during times of
natural ventilation. The findings provide evidence that MM buildings should be defined as
NV buildings, with operable windows and supplemental cooling/heating during peak periods,
favouring EN15251’s scope of applying the adaptive comfort model instead of PMV-PPD to
MM buildings whilst operating in NV mode. Not only does this study illustrate the
inadequacy of relying on PMV-PPD models to describe occupant comfort in MM buildings,
but it sheds light on how MM buildings, especially those featuring change-over control
strategies, should be categorised in future revisions to the relevant thermal comfort standards,
in particular ASHRAE 55-2010.
5.1.3. The Validity of Contemporary Post-Occupancy Evaluation Methods
The third study, outlined in Paper 4.3, addressed each of the following objectives:
1. By comparing the results from the POE and thermal comfort field studies in the MM
and NV buildings, this study aims to test the validity of assessing building
performance using the POE method.
Following the POE results in the first study (Paper 4.1), simultaneous thermal comfort field
studies were conducted during the summer months (between October 2009 and April 2010)
in the MM and NV buildings. Occupant satisfaction results from the POEs and thermal
196
comfort studies were compared and analysed to test the effectiveness of POE methods in
evaluating building performance. Upon comparison, indoor operative temperatures within the
NV building, recorded at the time thermal comfort questionnaires were delivered, were
significantly warmer than the MM building during the summer months. Despite experiencing
cooler, theoretically more comfortable temperatures, POE responses for subjects of the latter
reflect lower overall levels of satisfaction with the thermal environment. In contrast,
occupants of the NV building reported higher levels of overall satisfaction, and forgiveness
factors, towards the thermal environment, compared to their MM counterparts. This ‘groundtruthing’ research design suggests that contemporary POE methods, such as BUS and CBE,
do not provide reliable evaluations of actual building performance. Instead, they generate a
face-value assessment of the occupant’s subjective satisfaction ratings towards the building,
which can be biased by factors exogenous to the building and its services. In the present
study, additional statistical analyses were performed by triangulating instrumental objective
and subjective POE measurements.
2. Occupant satisfaction and thermal acceptability levels, along with participants’
comments and anecdotal evidence, were analysed between each method to examine
how POEs may generate over-exaggerated responses of poor building performance.
In contrast to the subjective POE results mentioned above, APD and PPD values from the
thermal comfort studies were analysed to compare thermal satisfaction and acceptability
within both buildings during exposure to comparable indoor operative temperatures.
Observed levels of thermal dissatisfaction (APD) in the MM building were greater than those
predicted on the basis of actual environmental conditions after transformation with the PMVPPD model (PPD). In contrast, occupants of the NV building recorded significantly lower
APD values than the PPD values predicted from the instrumental data. It also appears that
197
occupant perceptions of comfort and thermal acceptability differed between these two
buildings. Despite experiencing much warmer indoor environmental conditions, occupants of
the NV building expressed higher levels of satisfaction and acceptability with their thermal
environment across a broad range of indoor temperatures (i.e. 22 to 26°C) compared to
occupants of the MM building.
Since completion of the MM building, many of its occupants have expressed discontent with
the building’s performance. The analysis of occupants’ POE comments found that
‘temperature’, ‘noise’ and ‘ventilation’ were the most common complaints among the
occupants of both buildings, especially those in the MM building. When interpreted alongside
concurrent instrumental measurements of each building’s indoor climate, this evidence
suggests that these occupants were using the POE as a conduit to complain about general
workplace issues. The discrepancies between the MM and NV buildings, as well as the POE
and thermal comfort results, further exemplifies how non-building related factors, e.g. staff
morale and job (dis)satisfaction, may influence occupants’ comfort perceptions of, and
satisfaction with, their workplace’s thermal environment. Furthermore, this study emphasises
the importance of using a combination of both objective and subjective building performance
metrics to evaluate a building.
3. Finally, this study makes recommendations as to how these tools can be improved,
encouraging a more holistic approach to building performance evaluation.
Based on a critical review of the POE literature, this study identified three key issues relating
to the validity of typical POE methods: their omission of contextual information, lack of
feedback, and lack of instrumental data (Section 2.3.2). It is apparent that POE surveys in
isolation do not provide a true reflection of a building’s actual performance, but rather a
198
superficial assessment of its occupants. Considering typical POE studies do not obtain
parallel instrumental measurements of the buildings’ indoor climate, they lack an objective
benchmark against which poor satisfaction ratings can be validated. Despite encouragements
from the POE research literature to include occupants into every facet of the building lifecycle (from planning to commission), building users are routinely omitted from these stages
which can potentially lead to feelings of mistrust and discontent towards their building and its
managers. Moreover, the orientation/education of occupants on building design, thermal
comfort and environmental control, as well as the environmental consequences of their
actions, can play a valuable role in improving occupant comfort and “calibrating”
expectations of green buildings.
5.2. Future Research
This thesis addressed many topical issues in the fields of thermal comfort and building
performance. Specifically, it has presented findings that have increased our understanding of
how occupants’ environmental attitudes are associated with their tolerance of, and
satisfaction with, green buildings; thermal comfort during different modes of operation in
MM buildings; as well as the validation of contemporary POE methods. Answering the
research questions of this thesis leads to asking several new questions which prompt the need
for future research to further expand our understanding of these issues within the context of
occupants’ attitudes and expectations to the indoor thermal environment:
The aphorism that green buildings work best with green occupants opens up new avenues of
research enquiry. This thesis was the first to use the NEP questionnaire in conjunction with a
POE to analyse the correlation between the levels of pro-environmentalism and occupant
satisfaction in a green building. However, one other study has very recently presented similar
findings focusing on occupants’ environmental attitudes and forgiveness factors (Lakeridou
199
et al., 2012). Bearing in mind that both of these studies were conducted in specific contexts,
future studies across a wider range of different buildings (‘green’ and ‘non-green’) located in
different climates are needed to confirm the link between environmental attitudes and
forgiveness factors. Future studies should aim to measure building occupants’ environmental
attitudes using psychologically-based questionnaires, surveys and interviews, the level of
occupant satisfaction and forgiveness towards the building’s performance, as well as physical
measurements of the building’s performance. In doing so, the causal direction of the
relationship between environmental attitudes and occupant satisfaction in buildings can be
better understood. However, the big research question left begging by these tantalising results
is whether attitude change can lead to behavioural change within green buildings? The
exploration of this issue might also extend to other aspects of IEQ, e.g. thermal comfort, air
quality and productivity, as the link between pro-environmentalism and occupant satisfaction
within green buildings is further explored. More research would also be needed to investigate
the differences between occupants of ‘green’ vs. ‘non-green’ buildings.
One of the key barriers to the uptake of MM ventilation has been the contradiction of
international comfort standards. This research provides an impetus towards changing the
current scope and definition of the ACS in ASHRAE Standard 55-2010 to include MM
buildings when they are operating in natural ventilation mode; following the adaptive
standard in EN15251-2007. In doing so, the application of adaptive BMS control algorithms
within both existing and future MM buildings will help reduce energy consumption in
buildings and allows the variation of comfort temperatures during times of natural
ventilation. However, more research still needs to be carried out to bring about a more
justified revision of the standard to include MM buildings into ASHRAE’s ACS instead of
relying on the more conventional black-and-white definitions of ‘AC’ vs. ‘non-AC’. As more
MM buildings are likely to be built in the future, more field studies sampled from a variety of
200
different climate zones, and across all possible MM design/control strategies, i.e. changeover, concurrent and zoned systems, are essential to understanding how MM ventilation
affects occupant comfort and whether a new MM comfort standard should be established.
Further research addressing the limitations in current POE methods is required to develop
more robust and holistic building performance evaluations. Future building occupancy
studies should encourage the use of POE tools in conjunction with other methods to evaluate
all aspects of building performance, such as the social, psychological and physical aspects.
Collaboration is therefore needed among building owners, managers and academia to resolve
this complex issue with a view to creating a more holistic method for conducting these
studies in future buildings. This, however, requires studies to be conducted in many buildings
from many different climates and contexts to ensure the creation of a validated and reliable
set of building performance measures and metrics. Only then can more reliable building
performance studies, wherein assessments of occupant satisfaction along with energy
consumption, indoor temperature, thermal comfort, psychosocial factors and forgiveness, be
undertaken.
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Appendix
227
Appendix A: Post-Occupancy Evaluation Study Human Ethics
and Final Report Approval
228
229
230
Appendix B: Building Use Studies Questionnaire License
Agreement
231
232
Appendix C: Post-Occupancy Evaluation Occupant Consent
Email
233
Name of Project: Building E4A and E7A Post-Occupancy Evaluation Study
Dear occupants,
You have been invited to participate in a Post-Occupancy Evaluation (POE) study of your building. This study
forms part of my PhD studies and will be conducted in Buildings E4A and E7A to provide a comparison between
green office buildings. It is well known that the thermal environment within Building E7A can be quite uncomfortable
throughout the year, especially in summer and winter. Since the completion of Building E4A, many occupants have
expressed discontent with the building’s performance. After talks with the University’s Office of Facilities
Management (OFM) and Sustainability Office, we have been encouraged to conduct a POE of these buildings to
identify the cause, strength and solutions to these problems. Some of you may be aware that your building is
currently undergoing another study – the Thermal Comfort Study, focussing on occupant thermal comfort within
mixed-mode and naturally-ventilated buildings. This POE is entirely independent of the Thermal Comfort Study and is
in no way related.
These types of studies have been conducted all around the world, including Australia, and their results have
been widely collected and collated into a database often used to benchmark new studies against other building
performance studies. The results from this study will in turn help demonstrate how the occupants feel about their
building. These responses are used to generate an overall occupant evaluation on the performance of this building
and will be benchmarked across a wide range of national and international studies, with specific consideration given
to how your building rates in comparison to other green buildings, particularly within Australia. Participation is strictly
voluntary, however the more participants the better the results. This study will help Macquarie University highlight any
problems the building occupants have with the building, which can be used for the design and planning of current and
future building projects.
This study is being conducted by the following researcher to meet the requirements for the Doctor of Philosophy
degree:
Max Deuble, PhD student,
Department of Environment and Geography (Faculty of Science)
Phone: 02 9850 8396 Email: max.deuble@students.mq.edu.au
Under the supervision of:
Paul Beggs, Senior Lecturer,
Department of Environment and Geography (Faculty of Science)
Phone: 02 9850 8399
Email: pbeggs@els.mq.edu.au
Associate Investigator:
Adrian Leaman, Managing Director,
Building Use Studies, Ltd
Phone: +44 20 7287 1147
Email: adrianleaman@usablebuildings.co.uk
The questionnaires will be handed out to all occupants in the morning of Tuesday the 23rd of March. The
questionnaires will take 5 MINUTES to fill in (longer if you add comments). The surveys will be collected, in person,
by Max Deuble at the end of the day at 4:30pm. Thank you in advance for your help.
This is an anonymous survey, so any information or personal details gathered in the course of this study are
confidential. No individual will be identified in any publication of the results and only the researchers listed above will
have access to the data. The results obtained from this research will be made into a report which will be emailed to
all building occupants in the form of a PDF attachment. If you have any questions or concerns please contact any of
the researchers above.
The ethical aspects of this study have been approved by the Macquarie University Ethics Review Committee
(Human Research). If you have any complaints or reservations about any ethical aspect of your participation in this
research, you may contact the Committee through the Research Ethics Officer (telephone [02] 9850 7854, fax [02]
9850 8799, email: ethics@mq.edu.au). Any complaint you make will be treated in confidence and investigated, and
you will be informed of the outcome.
234
Appendix D: Environmental Attitudes Questionnaire
235
Environmental Attitude Questionnaire
Listed below are statements about the relationship between humans and the environment. For each one,
please indicate whether you STRONGLY DISAGREE, MILDLY DISAGREE, are UNSURE, MILDLY
AGREE or STRONGLY AGREE with it:
Strongly Mildly Unsure Mildly Strongly
Disagree Disagree
Agree
Agree
1. We are approaching the limit of the number
of people the earth can support
2. Humans have the right to modify the natural
environment to suit their needs
3. When humans interfere with nature it often
produces disastrous consequences
4. Human ingenuity will ensure that we do
NOT make the earth unliveable
5. Humans are severely abusing the
environment
6. The earth has plenty of natural resources if
we just learn how to develop them
7. Plants and animals have as much right as
humans to coexist
8. The balance of nature is strong enough to
cope with the impacts of modern industrial
nations
9. Despite our special abilities humans are still
subject to the laws of nature
10. The so-called ‘ecological crisis’ facing
humankind has been greatly exaggerated
11. The earth is like a spaceship with very
limited room and resources
12. Humans were meant to rule over the rest of
nature
13. The balance of nature is very delicate and
easily upset
14. Humans will eventually learn enough about
how nature works to be able to control it
15. If things continue on their present course,
we will soon experience major ecological
catastrophe
236
Appendix E: Post-Occupancy Evaluation Study Instructions
Sheet
237
BUILDING E4A AND E7A POST-OCCUPANCY EVALUATION
STUDY
Thank you for participating in the Building E4A and E7A Post-Occupancy
Evaluation (POE) study.
As you may know, building E7A is one of Macquarie University’s oldest
buildings. Being a naturally-ventilated building, the thermal environment can be quite
uncomfortable throughout the year, especially during summer and winter. Building E4A,
on the other hand, is a newly built building for Macquarie University determined to
promote itself as the way of the future, i.e. green buildings. However, since completion,
many occupants have expressed discontent with the building’s performance, but as yet
the University cannot understand the cause of these problems. The University’s Office of
Facilities Management (OFM) and Sustainability Office have encouraged that both these
buildings undergo an occupancy evaluation to identify the strength of this discontent and
possible solutions.
Post-occupancy evaluation studies are conducted all around the world and their
results are used to help demonstrate how the occupants feel about their building. The
responses are used to generate an overall occupant evaluation on the performance of this
building, which will be benchmarked across a wide range of national and international
studies, with specific consideration given to how building E4A and E7A rate in
comparison to other green buildings, particularly within Australia. This study will in turn
help Macquarie University highlight any problems the building occupants have with the
building, which can be used for the design and planning of future building projects.
This survey is strictly anonymous, and no individual will be identified in any
publication of the results. The results obtained from this research will be made into a
report which will be emailed to the building occupants in the form of a PDF attachment.
Please read and follow the instructions written below carefully:
1. Please fill out the Post-Occupancy Evaluation and Environmental Attitude
questionnaires. These should only take 5 MINUTES to complete (longer if you
add comments).
2. Once you have completed the questionnaires, please place them into the envelope
provided and seal it off.
3. Leave the envelope in a prominent place so the researcher, Max Deuble, can
collect it at 4:30pm TODAY. If you will not be in your office at this time then
please leave the envelope under your door and he can collect it at the end of the
day.
4. Thank you in advance for your help.
Sincerely,
Max Deuble
238
Appendix F: Thermal Comfort Study Human Ethics and Final
Report Approval
239
240
241
MAX DEUBLE <max.deuble@students.mq.edu.au>
Final Report Approved - Deuble (HE26SEP2008-D06064)
1 message
Ethics Secretariat <ethics.secretariat@mq.edu.au>
To: max.deuble@students.mq.edu.au
Cc: paul.beggs@mq.edu.au
Wed, Nov 24, 2010 at 3:25 PM
Dear Mr Deuble,
FINAL REPORT APPROVED
Title of project: 'Occupant Comfort in Naturally-Ventilated and Mixed-Mode
Spaces Within Air-Conditioned Office Buildings' (RefHE26SEP2008-D06064)
Your final report has been received and approved, effective 24 November
2010. The Committee is grateful for your cooperation and would like to
wish you success in future research endeavours.
Yours sincerely
Dr Karolyn White
Director of Research Ethics
Chair, Human Research Ethics Committee
242
Appendix G: Thermal Comfort Study Occupant Consent Email
243
Participant Information/Consent Email
Name of Project: Occupant Comfort within Mixed-Mode and Naturally-Ventilated Office Buildings
Within Australia, energy used for heating, ventilation and air-conditioning (HVAC) still accounts for 50% of
greenhouse gas emissions within the commercial building sector. Low-energy, green buildings are rapidly emerging
because they can provide comfortable working conditions for the occupants whilst reducing energy consumption, and
hence greenhouse gas emissions. As Building E7A predominantly uses natural ventilation it consumes less energy than
the conventional air-conditioned buildings on campus. However, whilst occupants prefer having control over their own
thermal environment by using operable windows, they often do not appreciate the uncomfortable conditions likely to
occur during extreme conditions. Building E4A, on the other hand, utilises mixed-mode ventilation; working as a naturally
ventilated structure with operable windows, the building is capable of switching into an air-conditioned building when
outdoor weather conditions make the naturally ventilated option untenable for the occupants. After talks with the
University’s Deputy Vice-Chancellor, Paul Bowler, under encouragement from the University’s Office of Facilities
Management (OFM) and the University’s Sustainability Office, approval has been obtained from the Dean and Heads of
Departments within this building to invite you to participate in a study investigating how occupants achieve thermal
comfort within mixed-mode and naturally-ventilated buildings.
The purpose of this study is to examine thermal comfort issues in an accurate and conclusive fashion within both
buildings. In comparing both buildings, this project will highlight recommendations of such spaces and the justification of
their design into new buildings and for the refurbishment of existing building stock.
Secondly, as there are no international thermal comfort guidelines for mixed-mode spaces due to a lack of empirical
research on which such guidelines could be based, this study will help develop a model of thermal comfort that takes
account of occupant behaviour, as people utilise spaces of different comfort conditions within the same building.
This study is being conducted by the following researcher to meet the requirements for the Doctor of Philosophy degree.
If you have any questions or concerns please contact any of the researchers below:
Max Deuble, PhD student
Department of Environment and Geography (Faculty of Science)
Phone: 02 9850 8396 Email: max.deuble@students.mq.edu.au
Under the supervision of:
Paul Beggs, Senior Lecturer,
Department of Environment and Geography (Faculty of Science)
Phone: 02 9850 8399 Email: pbeggs@els.mq.edu.au
The approach of this project is to select 30-60 participants from a series of typical locations from different zones
within both buildings: North, South and Central. Upon participation, office spaces will be equipped with unobtrusive
sensors to record indoor climatic data such as temperature, mean radiant temperature, humidity and air speed
throughout the year (these instruments SHOULD NOT interfere with the daily activities of the occupants). This data will
be matched with questionnaire responses to stationary indoor climate data (measured using a mobile thermal comfort
‘Sputnik’ instrument periodically throughout the year, i.e. a couple of visits per week) and concurrent outdoor weather
data. Questionnaires are designed to record the occupants’ perceptions of thermal comfort within their office spaces and
SHOULD NOT take longer than ONE MINUTE to complete.
Any information or personal details gathered in the course of this study are confidential and no individual will be
identified in any publication of the results. Only the researchers listed above will have access to the data.
Reply to this email will be regarded as consent. All those involved in this study will be emailed an executive
summary (maximum length 5 pages) of the research findings.
The ethical aspects of this study have been approved by the Macquarie University Ethics Review Committee
(Human Research). If you have any complaints or reservations about any ethical aspect of your participation in this
research, you may contact the Committee through the Research Ethics Officer (telephone [02] 9850 7854, fax [02] 9850
8799, email: ethics@.mq.edu.au). Any complaint you make will be treated in confidence and investigated, and you will
be informed of the outcome.
244
Appendix H: Thermal Comfort Study Background Questionnaire
245
THE COMFORT STUDY
Gender: Male
Age: < 20
Female
20-30
30-40
40-50
50-60
60-70
70+
1. How long have you been working in building E4A?
< 3 months
3 to 6 months
6 months to 1 year
> 1 year
2. What type of building did you work in prior to this one?
Air-Conditioned
Naturally Ventilated (operable windows)
3a) Was this building located in Sydney? Yes
No
3b) If ‘No’, where was it located?
__________________________________________________________
4. On average, how many hours per week do you work at this job? ______Hours at work
5. On average, how many hours per day do you sit at your work area? _____Hours per day
6a) Please tick where you are presently using air-conditioning? 6b) If selecting ‘Other’, please specify
where: __________________________________________________
At home, bedroom
At home, living room
In car
Other
7. During the summer season, please tick how often you use each of the following in your office:
Frequently
Occasionally
Rarely
Never
N/A
Portable fan
Open/close window
Open/close door
Draw blinds/shades
Remove clothing
Open/close air vent
Other (please specify):
_________________
8. During the winter season, please tick how often you use each of the following in your office:
Frequently
Occasionally
Portable heater
Open/close window
Open/close door
Draw blinds/shades
Add clothing
Open/close air vent
Other (please specify):
_________________
246
Rarely
Never
N/A
Appendix I: Thermal Comfort ‘Right Here, Right Now’
Questionnaire (summer/winter)
247
COMFORT STUDY – RIGHT HERE, RIGHT NOW
1. Please tick the scale below at the place that best represents how YOU FEEL RIGHT NOW? You may tick
between two categories, if you wish.
Cold
Cool
Slightly
Cool
Neutral
Slightly
Warm
Warm
Hot
2. Is the thermal environment acceptable to you?
3. Right now I would prefer to be:
Acceptable
Warmer
Unacceptable
4. How do you feel right now about the air
movement in your room?
No Change
Cooler
5. Right now I would prefer:
More Air Movement
No Change
Less Air Movement
If unacceptable, why?
Low air movement
High air movement
6. Has your window been opened today?
If acceptable, why?
Yes
Less air movement
No
Enough air movement
High air movement
7. What activities have you been engaged in during the preceding hour?
Sitting
quietly
Sitting
typing
Standing
still
On your feet
working
Walking
around
Driving a
car
Last 10 minutes
The 10 minutes preceding that?
The 10 minutes before that?
The half hour before that?
8. Compared to normal, please estimate how you feel your productivity has increased or decreased today, by
ticking where you feel appropriate on the scale below?
-40%
or more
-30%
-20%
-10%
0
+10%
+20%
+30%
+40%
or more
9. Have you made any adjustments to your clothing ensemble within the last 15 minutes? Yes
No
10. As you know, the amount of clothing we wear affects our thermal comfort. Please indicate whether you are
wearing any of the items listed below (0 = not wearing item; 1 = summer/light-weight item; 2 = winter/heavyweight item):
Footwear:
Midlayer:
Outerlayers:
Other items:
Socks
Short-sleeved shirt
Pants or slacks
Sweater
0 - 1- 2
0 - 1- 2
0 - 1- 2
0 - 1- 2
0 - 1- 2
Shoes
Long-sleeved shirt
Shorts
Vest
0 - 1- 2
0 - 1- 2
0 - 1- 2
0 - 1- 2
0 - 1- 2
Pantyhose
Dress
Skirt
Jacket
0 - 1- 2
0 - 1- 2
0 - 1- 2
0 - 1- 2
0 - 1- 2
11. Which of the following have you used today to control the thermal environment within your office? For
those you have used can you please list the order in which they were used?
Device
Portable fan/heater
Open/close window
Open/close door
Draw blinds/shades
Remove/Add clothing
Open/close air vent
Other
Yes
No
Order
THANK YOU FOR YOUR TIME
248
For Office Use
D:
T:
0
1
G:
0
1
W:
0
1
C:
N S C
L:
E
W
AC
NV
M:
Appendix J: Healthy Buildings 2009 Conference Paper
Deuble, M. and de Dear, R. (2009) ‘Do green buildings need green occupants’, Proceedings
of the Healthy Buildings 2009 Conference, Syracuse, NY, USA, 13-17 September 2009
249
Proceedings of Healthy Buildings 2009
Paper 229
Do Green Buildings Need Green Occupants?
Max Deuble1* and Richard de Dear2
1
2
*
Macquarie University, Sydney NSW 2109, Australia
University of Sydney, Sydney NSW 2006, Australia
Corresponding author’s email: mdeuble@els.mq.edu.au
SUMMARY
Mixed-mode: these words are synonymous with the world’s emergent ‘green’ buildings,
heralded as low carbon buildings of the future. While the technical efficiency of such
buildings is important, the well-being, productivity, (dis)comfort, general satisfaction of the
occupants, as well as environmental attitudes and beliefs, is in itself, necessarily important.
Post-occupancy evaluations for occupant satisfaction, and New Ecological Paradigm
questionnaires, measuring levels of environmental concern, were conducted between March
and April 2009 in two academic office buildings at Macquarie University. Upon analysis,
significantly higher environmental attitudes were present for occupants possessing greater
tolerance of their building’s thermal environment. This paper hypothesises that occupants
valuing their building highly possess greater pro-environmental attitudes compared to those
valuing their building poorly, and thus provides evidence supporting the link between
environmental attitudes and occupant satisfaction within green buildings.
KEYWORDS
Green buildings, Post-occupancy evaluation, New Ecological Paradigm, Environmental
attitudes
INTRODUCTION
Twentieth century office buildings generally provided static temperatures for all occupants
using centralised heating, ventilation and cooling (HVAC) technology. Adaptive comfort
studies (de Dear and Brager, 1998; de Dear and Brager, 2002) have identified the need for
greater occupant control in personal preferences of their thermal environment, thus widening
the acceptable range of temperatures, and ultimately achieving higher levels of occupant
satisfaction (Leaman and Bordass, 2007). Low-energy green buildings advocate this shift of
environmental control towards the occupants (Brager et al., 2004). Whereas occupants prefer
the adaptive opportunities provided by green-intent buildings, i.e. those with natural
ventilation capabilities, opposed to the sealed façade and air-conditioned (AC) alternative,
they do not expect the thermally variable and sometimes uncomfortable conditions during
unusually hot weather. Notwithstanding occasional discomforts, many post-occupancy
evaluation (POE) studies suggest that green building users are prepared to forgive such
conditions provided they possess a modicum of environmental control (de Dear and Brager,
2002; Leaman and Bordass, 2007; Brager and Baker, 2008).
The New Ecological Paradigm (NEP) (a revision of the New Environmental Paradigm) Scale
is a 15-item questionnaire, consisting of 8 pro-NEP and 7 anti-NEP items, that simply
measures degrees of endorsement (from low to high) of an ecological worldview (Dunlap et
al., 2000; Dunlap, 2008). After worldwide applications into environmental psychology, there
is broad consensus that the NEP represents a valid and reliable scale for measuring levels of
ecological beliefs (Cordano et al., 2003). Despite its extensive use, the scale has not been used
in conjunction with POE studies and could potentially identify the link between successful
occupancy of green buildings and environmental attitudes. Thus this paper investigates the
hypothesis that green buildings need green occupants by comparing POE and NEP results of
two green buildings at Macquarie University (MQ).
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Proceedings of Healthy Buildings 2009
Paper 229
METHODS
Sydney (34°S, 151°E), located on the southeast coast of Australia, can be described as having
a humid sub-tropical climate, experiencing warm-to-hot summers combined with moderateto-high humidity, peaking in February to March. Winters are mild and temperate, and an
annual rainfall of 1200mm, distributed evenly throughout the year. Sydney’s climate is ideally
suited to mixed-mode (MM) buildings.
In this study, two academic staff buildings from MQ were selected, both having North-South
orientations, whereby North facades are directly irradiated from the Sun during the day,
indicating warmer temperatures than the South. The buildings used were E4A, a MM building
(in Photo 1) commissioned in 2006, and NV building E7A (in Photo 2), built in the late 1960s.
Building E4A consists of operable windows with MM cellular offices along north and south
perimeter zones separated by AC central open-plan office space. Indoor temperature and
outdoor weather sensors prompt the Building Management System (BMS) to switch to AC
mode when the average temperature increases above 25°C. Occupants are mainly academics
and administrative staff from various Economic and Finance departments. Correspondingly,
building E7A features occupant-operated windows with narrow floor plate consisting of a
central corridor with single and dual occupant cellular offices on either side. Academic staff,
post-graduate students and administrative staff from a variety of Environment and Geography
disciplines, occupy this building.
Photo 1. MQ, Building E4A (North facade)
Photo 2. MQ, Building E7A (North facade)
Between March and April 2009, two questionnaires were distributed to all staff in both
buildings. Firstly, the three-page Building Use Studies (BUS, 2009) POE using 7-point Likert
scales with space for commentary, covers variables relating to occupant satisfaction, e.g.
thermal, visual and acoustic comfort, indoor air quality, perceived health and productivity,
and general acceptance of the workplace. BUS (2009) further details the BUS methodology.
Secondly, the Environmental Attitudes questionnaire is a 15-item version of the NEP Scale,
using 5-point response scales ranging from Strongly Disagree to Strongly Agree, with higher
scores on the scale from 1 (low) to 5 (high) indicating greater levels of environmental
concern. All scales were converted to a NEP score by summing each item response and
dividing by the total number of items in the scale. Results were analysed using MiniTab
statistical software.
Dataloggers randomly located throughout each building recorded air temperature at 5 minute
intervals throughout the study. Outdoor air temperature was measured over the same period at
a nearby automatic weather station, with BMS data from the survey period was collected from
the Office of Facilities Management (OFM).
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Proceedings of Healthy Buildings 2009
Paper 229
RESULTS
From temperatures averaged across all dataloggers, it was established that building E7A
experienced significantly warmer temperatures (mean = 24.5°C, p = 0.000) over the study
period than building E4A (mean = 24.1°C) (Figure 1). Temperatures inside each building
were far greater than the surrounding outdoor air temperature (mean = 20.6°C). As a NV
building, temperatures inside E7A closely match changes in outdoor weather conditions,
whereas building E4A, experienced a narrower temperature range, possibly due to the use of
HVAC as temperatures rose towards the 25°C cooling set-point.
Figure 1. Indoor and outdoor thermal environments measured over the study period.
In total, 180 POE and NEP questionnaires were distributed in building E4A and 40 in building
E7A. 95 (43 male, 52 female) were completed from E4A (53% response rate), and 28 (11
male; 17 female) from E7A (70% response rate). To ensure quality assurance, incomplete or
fraudulent responses were omitted from the samples. POE responses were benchmarked
against the Australian BUS database (as summarised in Table 1). Both buildings generally
measure poorly, ranking well below Australian benchmarks. While E7A appears worse than
E4A, the only significantly different variable in the study was perceived productivity (p =
0.000).
Table 1. A summary of POE and NEP results for buildings E4A and E7A.
Study Variable
E4A (n = 92) E7A (n = 28) Significance
Forgiveness Factor
0.99
1.04
p > 0.05
Comfort Index
-0.39
-0.70
p > 0.05
Satisfaction Index
0.02
-0.10
p > 0.05
Perceived Productivity
-5.34
-10.71
p = 0.000
NEP
3.69
4.04
p = 0.005
NEP questionnaire items were tested for internal consistency and were found to have strong
coefficient alphas (a= 0.82) suggesting good internal consistency. E7A had a significantly
higher mean NEP score (4.04, p = 0.005) than E4A (3.96), plausible for environmentally
educated academics. Interestingly, the NEP score for E4A is relatively high for occupants
associated with economics, finance and business studies.
DISCUSSION
Upon comparison, with higher temperatures recorded in E7A, it is reasonable to assess that
perception of productivity at temperatures up to 28°C was significantly lower than E4A.
Nonetheless, occupants in both buildings have often complained about indoor temperatures in
the summer months, particularly on the north facade. This anecdotal feedback is consistent
with a more systematic pattern emerging in Australian green buildings that have undergone
the BUS POE (Leaman et al., 2007). In comparing 22 green-intent buildings against 23
conventional HVAC office buildings, Leaman et al (2007) reported that green buildings were
perceived as hotter in summer and cooler in winter. Green-intent buildings, such as E4A and
E7A, are designed to perform this way. In comparing ‘forgiveness’ scores, a variable derived
by dividing scores for the variable ‘comfort overall’ by the average of the summary variables
for temperature in summer and winter, ventilation/air in summer and winter, noise and
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Proceedings of Healthy Buildings 2009
Paper 229
lighting, it was possible to compare the results in Table 2, from Leaman et al., (2007), to find
that E4A is poorly received by its users (forgiveness = 0.99). Comparatively, building E7A
measured significantly higher NEP scores indicating greater tolerance to perceived thermal
variance (forgiveness = 1.04), concluding consistency with green-intent buildings in the BUS
database.
Table 2. Forgiveness scores by ventilation type: Australian BUS building database (n = 45).
Study Variable
Green-intent (NV, ANV, MM)
AC
E4A (MM) E7A (NV)
Forgiveness Factor
1.02
0.99
0.99
1.04
n
22
23
Note: Higher values indicate occupants more tolerant or ‘forgiving’ of the conditions. Building types include
natural ventilation (NV), advanced natural ventilation (ANV), mixed-mode (MM) and air-conditioning (AC).
CONCLUSIONS
POE instruments appear to measure building occupants as much as they evaluate the quality
of a building’s indoor environments. Green buildings have greater thermal variations than
their AC counterparts, in which centralised HVAC provides static indoor temperatures to all
occupants all-year round. This paper suggests green building users are more forgiving of their
building, consistent with the hypothesis that green occupants are needed for green buildings.
While this study only represents two green buildings at MQ, with current focus being directed
towards the well-being and satisfaction of green building users, more research is needed to
identify the link between occupant satisfaction and environmental attitudes.
ACKNOWLEDGEMENTS
We are enormously grateful to Adrian Leaman for permission to use the BUS questionnaire
under license and his assistance in data analysis. We would also like to thank Riley Dunlap
for his valuable comments and encouragements, and Macquarie University’s OFM, especially
Kerry Russell, for their support. Finally, and most importantly, we express our appreciation to
all the building occupants who responded to the questionnaires.
REFERENCES
Brager, G. and Baker, L. 2008. Occupant satisfaction in mixed-mode buildings, In:
Proceedings of the 5th Windsor Conference 2008 - Air-Conditioning and the Low
Carbon Cooling Challenge, Cumberland Lodge, Windsor, UK.
Brager, G. S., Paliaga, G. and de Dear, R. 2004. Operable windows, personal control and
occupant comfort. ASHRAE Transactions, 110(Part 2): 17-35.
BUS. 2009. "Usable Buildings Trust." Retrieved 27th June, 2008, from
http://www.usablebuildings.co.uk/WebGuideOSM/index.html.
Cordano, M., Welcomer, S. A. and Scherer, R. F. 2003. An analysis of the predictive validity
of the New Ecological Paradigm Scale. Journal of Environmental Education, 34(3):
22-28.
de Dear, R. J. and Brager, G. 1998. Developing an adaptive model of thermal comfort and
preference. ASHRAE Transactions, 104: 145-167.
de Dear, R. J. and Brager, G. S. 2002. Thermal comfort in naturally ventilated buildings:
revisions to ASHRAE Standard 55. Energy and Buildings, 34: 549-561.
Dunlap, R. E. 2008. The New Environmental Paradigm Scale: From Marginality to
Worldwide Use. Journal of Environmental Education, 40(1): 3-18.
Dunlap, R. E., Van Liere, K. D., Mertig, A. D. and Jones, R. E. 2000. Measuring endorsement
of the New Ecological Paradigm: a revised NEP scale. Journal of Social Issues, 56(3):
425-442.
Leaman, A. and Bordass, B. 2007. Are users more tolerant of 'green' buildings? Building
Research and Information, 35(6): 662-673.
Leaman, A., Thomas, L. and Vandenberg, M. 2007. 'Green' Buildings: What Australian Users
are Saying. In Press.
253
Appendix K: ANZAScA 2009 Conference Paper
Drake, S., de Dear, R., Alessi, A. and Deuble, M. (2009) ‘Occupant comfort in naturally
ventilated and mixed-mode spaces within air-conditioned offices’, Proceedings of the 43rd
Annual ANZAScA Conference 2009: Performative Ecologies in the Built Environment Sustainability Research Across Disciplines, Launceston, Tasmania, Australia, 25-27
November 2009
254
Occupant comfort in naturally ventilated and mixedmode spaces within air-conditioned offices
Scott Drake1, Richard de Dear2, Angela Alessi1 and Max Deuble3
1
University of Melbourne, Melbourne, Australia
2
University of Sydney, Sydney, Australia
3
Macquarie University, Sydney, Australia
ABSTRACT:
Contemporary concerns for improving environmental performance in buildings have led to an
increased interest in natural ventilation either on its own (NV) or in combination with air-conditioning
(mixed mode – MM) as an alternative to traditional HVAC systems. HVAC systems are widely used
because they avoid many of the problems encountered with NV or MM – noise, dust, insects, odours,
temperature extremes – and readily conform to steady state conditions of thermal comfort. However it
is possible that NV or MM can provide improved indoor air quality precisely through variations
associated with external climate conditions. This paper introduces an ARC funded project evaluating
comfort conditions in MM spaces, using field studies from two buildings. The first, a University campus
building in Sydney, offers MM perimeter offices with air-conditioned central spaces, while the second, a
commercial building in Melbourne, offers a series of MM spaces that can be used by workers from
adjacent air-conditioned office spaces. The aim of the project is to evaluate the feasibility of using MM
either in place of or in association with traditional HVAC systems. The outcomes of the project will be
used to elaborate the justifications for inclusion of NV spaces and/or NV periods within contemporary
office environments. This paper presents preliminary results of the field work at each location.
Conference theme: Human
Keywords: Thermal comfort, Mixed-mode buildings, Hybrid ventilation
INTRODUCTION
Current practices in office buildings generally provide standardised indoor climates for all occupants using heating,
ventilation and cooling (HVAC) technology. Typically adopting a building-centred, energy-consuming approach
focused on creating constant, uniform-neutrality conditions, the primary purpose of HVAC systems is to provide
acceptable indoor air quality and thermal comfort aiming for an optimum ‘steady-state’ temperature setting based
upon Fanger’s PMV-PPD model (Fanger 1970). This ‘static’ approach to thermal comfort was intended to maximise
safety and comfort. In contrast, a person-centred approach would purposely provide variability across time and space
(Brager and de Dear 1998). Spatially, thermally differentiated areas would be designed to allow for individual thermal
requirements. Temporally, indoor temperatures would gradually drift towards outdoor conditions in a way that would
enable and encourage adaptations such as clothing changes and use of operable windows.
Recent studies (Baker and Standeven 1996; Humphreys and Nicol 1998; Rowe 2004; Humphreys et al. 2007; Rijal et
al. 2007) have made the case for greater environmental variation inside buildings, either via user adjustments to
windows, shade devices, etc or by adaptive algorithms that more closely match HVAC set-points to prevailing
outdoor temperatures. The ‘adaptive’ thermal comfort model (Humphreys and Nicol 1998; Humphreys et al. 2007)
has advocated the shift towards variable indoor environmental conditions, underlying an essential aspect of
sustainable building design, i.e. providing thermal comfort while reducing energy use and associated greenhouse gas
emissions. Within conventional air-conditioned (AC) buildings, the HVAC system contributes to over half the energy
and emissions required for building operation (AGO 1999). The move towards sustainability involves decreasing the
reliance on active systems and pursuing more passive strategies of building design. One alternative is natural
ventilation (NV) with occupant-controlled windows, however, while people may prefer a high degree of ‘adaptive’
opportunities (Baker and Standeven 1996; Brager et al. 2004) they do not appreciate the thermally uncomfortable
conditions likely to occur in NV buildings during unusually hot or cold weather conditions . As a result, building
architects and engineers are exploring ‘mixed-mode’ (MM) ventilation as a way of combining the best features of NV
and AC buildings (Brager 2006; Brager and Baker 2008).
Mixed-mode Buildings
The basic philosophy of MM or ‘hybrid’ ventilation is to maintain a satisfactory indoor environment by alternating
between and combining natural and mechanical systems to avoid the cost, energy penalty and consequential
environmental effects of full year-round air conditioning (Brager 2006; Lomas et al. 2007). These buildings provide
good air quality and thermal comfort using NV and operable windows whenever the outdoor weather conditions are
favourable but revert to mechanical systems for HVAC whenever external conditions make the NV option untenable
for occupants.
Existing international comfort standards, e.g. the American Society of Heating, Refrigerating and Air-Conditioning
Engineers (ASHRAE) Standard-55 (ASHRAE 2004), ISO 7730 (ISO 2006) and pr-EN 15251 (CEN 2007) mainly
cover thermal comfort conditions under steady state conditions based on laboratory experiments. Field studies
(Humphreys and Nicol 1998; Nicol and Humphreys 2002; Rowe 2004; Nicol and Humphreys 2009) have led to the
inclusion of an Adaptive Comfort Standard (ACS) serving as an alternative to the PMV-based method for freerd
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running, i.e. NV buildings (ASHRAE 2004). However, the scope of the ACS option is heavily constrained to naturally
conditioned, occupant-controlled spaces in which thermal comfort conditions of the space may be heavily influenced
primarily by operable windows which open to the outdoors and which can be readily adjusted by the occupants of the
space. When mechanical cooling systems are provided for the space, the ACS is not applicable (Nicol and
Humphreys 2002; Turner 2008). The potential flexibility offered by the standard is not available to hybrid buildings,
which may operate in a passive, natural ventilation mode preferentially, and equipped with only supplemental cooling
and heating for peak periods; or that control airflow using a building energy management system (BEMS) rather than
occupant intervention; or to spaces where operable elements are not connected to the outdoors, must therefore
resort to the more restrictive PMV-PPD method as a result (Turner 2008).
By comparing field studies in two recent commercial and institutional buildings from Melbourne and Sydney, this
paper investigates thermal comfort conditions within NV or MM spaces located within traditionally AC buildings. The
buildings used for this study are Macquarie University’s (MQ) Commerce building (Building E4A) at North Ryde in
Sydney and the National Australia Bank (NAB) building at Docklands in Melbourne.
Thermal Comfort: The Adaptive Concept and Mixed Mode Spaces
Thermal comfort is currently defined within two internationally recognized standards, the ASHRAE and British
Standard BS EN ISO 7730 as “that condition of mind which expresses satisfaction with the thermal environment”
(ASHRAE 2004). So the term describes a person’s psychological state taking into account a range of environmental
and personal factors. Generally air temperature, humidity, air velocity clothing and metabolic activity are the common
variables to be considered, however other comfort factors like a sense of relaxation and freedom from worry and pain
should be considered (Darby and White 2005). These aspects represent a major impact on a person’s thermal
comfort, what de Dear defines as “perceptual relativity”, i.e. when people interact with their environment (de Dear
2004). Established by ASHRAE Standard 55 (2004), “reasonable comfort” considers 80% of occupant satisfaction as
a reasonable limit for the minimum number of people who should be thermally comfortable in an environment.
However, occupant comfort complaints are the biggest routine operational problem in business administration, “if one
person is too hot, someone else nearby is too cold, and tomorrow both complaints may be reversed” (Opitz 2008). In
fact people employ adaptive strategies to cope with their thermal environment like removing clothing, change in
posture, choice of heating, opening windows or moving to non-AC areas.
The debate between the heat-balance and the adaptive approach has dominated the development of thermal comfort
science in recent years (Nicol and Humphreys 2002). The thermal comfort standard used by ASHRAE is based on
experiments in climate chambers initiated by Fanger in the 60s. This approach combines the theory of heat transfer
with physiological thermoregulation to determine different comfort temperatures for people in a specific environment:
individuals studied in tight controlled situations. The adaptive approach, on the other hand, is based on field studies
demonstrating that people are more tolerant of temperature changes than laboratory studies suggest. In fact, people
act consciously and unconsciously to affect the heat balance of the body, what is called behavioural
thermoregulation. In this way, comfort is normally achieved in a wider range of temperatures than predicted by
ASHRAE standards (Heschong 1979; Nicol and Humphreys 2002). As Heschong (1979) interestingly points out
comfort is a relationship between thermal content and human imagination. As humans we are capable of adapting to
most thermal experiences but mostly we are in need of variations to avoid “thermal boredom” (Kwok 2000).
According to Humphreys and Nicol (1998), straightforward applications of the Fanger equation underestimates
human adaptability to indoor climate by about 50% leading to excessive energy use and inappropriate design
(Humphreys and Nicol 1998). The adaptive approach to thermal comfort is based on the findings of surveys that
focus on gathering data about the thermal environment and the simultaneous thermal response of the individuals in
real situations, keeping researcher intervention to a minimum, as achieved in our Melbourne and Sydney case
studies. The fundamental assumption of this approach is expressed by the adaptive principle: “if a change occurs
such as to produce discomfort, people react in ways which tend to restore their comfort” (Nicol and Humphreys
2002). Both Angela and Max are conducting observations that have already given indications related to people’s
adjustments to their environment. For example, at the NAB, there is a frequency of people entering the tea pot room
indicating the need for a break from their work but also that the need to enter a different thermal environment; hence
seeking relaxation as well as fresh air. There is a clear association between the comfort conditions and people’s
actions that links comfort temperatures to the context in which individuals find themselves. Research at the NAB
looks into people’s behaviour and how they move into the NV tea pot area from their AC office space, what they do
and where they come there. Patterns of movement and various chosen activity will reveal physical and psychological
adaptations providing indications about the space and its comfort acceptability.
Comfort has both a spatial and a temporal dimension, as users respond to different weather or different activities by
adjusting clothing levels, temperature settings, window openings or by moving to another space (Hawkes 1997). The
option for people to react to a specific thermal situation reflects the opportunities to adapt to their environment and
the possibility to achieve good levels of comfort. Well designed spaces should be able to provide different thermal
conditions in the one location (Ong 1997). Ong suggests the need for heterogeneous conditions reflecting the
complexity of our sensory experience, allowing users to seek various environmental conditions according to their
particular needs at a given time. In this respect, the NAB is the only building in Australia that includes a key
1
innovative design, the MM space , and integrating natural ventilation within AC commercial buildings.
1
Mixed-mode refers to a hybrid approach to space conditioning using a combination of natural ventilation from
operable windows, manually or automatically controlled, and mechanical systems, i.e. air distribution and refrigeration
equipment for cooling. The NAB is the only one in Australia with this particular system (CBE, 2005).
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CASE STUDY 1: NATIONAL AUSTRALIA BANK, DOCKLANDS, MELBOURNE
The National Australia Bank (NAB) building was the first new commercial building built as part of the reconstruction of
2
Melbourne’s Docklands. As one of the largest single tenant commercial buildings in Australia, with 140,000 m of
office space suitable for around 4000 employees, the building features a series of MM spaces along the Northern
façade, giving users the possibility to choose between active mechanical air-conditioning (AC) or natural ventilation
(NV), depending on outdoor weather conditions.
Figure 1: Plan, National Australia Bank Melbourne
Figure 2: Plan of the North End Tea Point, Level 6
The study at NAB focussed on a single space, level 6 Northern Tea point (figure 2), as part of the MM north façade.
In this zone the hybrid ventilation system allows workers to switch between air-conditioning and MM using the control
panel (figure 3). The MM spaces provide a unique setting to investigate people’s response to NV within AC
environments.
Figure 3: The control panel
Figure 4: Overview of the room and the instruments
The methodology used includes quantitative data collection, with instruments monitoring temperature, mean radiant
temperature, relative humidity (RH), air-velocity and radiation (Figure 4). Two people counters were used to
determine the population of the room at 5 minute intervals. This data will be complemented by qualitative data from
questionnaires and field work observations of user behaviour in the space, to be conducted for a period of one week
four times throughout the year (corresponding to the seasons).
CASE STUDY 2: MACQUARIE UNIVERSITY COMMERCE BUILDING, SYDNEY
.
Figure 5: Commerce Building Typical Floor Plan
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Macquarie University's (MQ) North Ryde campus is located within the Sydney metropolitan region. Commissioned in
2006, the Commerce building is a 7-storey office building occupied by academic and administrative staff. Consisting
of MM cellular offices with operable windows along north and south perimeter zones separated by AC central openplan office space, the entire façade is built on a louvre system featuring external solar shading over the northern
windows (Figure 5). Automated high and low external louvres provide natural ventilation to each floor, with adjustable
internal grilles to control airflow, supplemented by user-operable windows. Indoor temperature and outdoor weather
sensors prompt the Building Management System (BMS) to switch into AC mode whenever a peak temperature
greater than 25°C is sensed in any zone. During AC mode, internal temperatures are maintained at 24°C (±1.5°C) as
defined in the building’s algorithm. BMS switch-over to NV is conditional when external meteorological conditions and
the indoor thermal climate fall into an acceptable zone for the occupants
Dataloggers randomly located throughout the building record air temperature and relative
humidity at 5 minute intervals throughout the study. Outdoor weather conditions were
collected from a nearby automatic weather station, and BMS data was collected from the
University’s Office of Facilities Management (OFM). Field studies used mobile observations
to supplement continuous monitoring of occupant workplaces, using the thermal comfort
‘sputnik’ system (Figure 6). These provided detailed thermal comfort measurements for air
temperature; mean radiant temperature, relative humidity, and air speed at a height of 0.6m
within each occupied zone. Standardised comfort questionnaires were used to record
occupant perceptions of thermal comfort within their workspace, including standardised
clothing garment and metabolic activity check lists allowing the calculation of various
comfort indices, e.g. Predicted Mean Vote (PMV), Effective Temperature (ET*) and
Standard Effective Temperature (SET*), etc. (ASHRAE 2004). Statistical analyses were
performed using Minitab statistical software.
Figure 6: ‘Sputnik’ thermal comfort system used for the Sydney MM field study
1A) PRELIMINARY RESULTS: NATIONAL AUSTRALIA BANK, MELBOURNE
The survey was conducted on the 29th April 2009 between 10:30 am and 3 pm. The people counters established that
an average of 200 entries per day with 100 occurring between morning tea and lunch time. Most people entered the
room at least twice per day, which means that only 66 people (33%) were in the room at the time of surveying. Thirty
people volunteered to answer the survey, a response rate of just below half. The average age of respondents was 33
years with 43% females and 56% males. The majority of people surveyed, 73%, have been working at NAB for more
than one year and 97% of them worked previously in an AC office mainly in Melbourne.
Throughout April, outdoor temperatures ranged between a minimum of 7°C and a maximum of 32°C. During the
th
th
week of observations, from the 20 to 24 April, the average outdoor temperature was 16°C, quite typical for autumn
in Melbourne as temperatures were often in the mid-20s (Figure 7). Internal temperatures during this same period
ranged between 23-25°C.
Temperatures In & Out
30
25
20
15
10
5
0
20/04/2009
21/04/2009
Min Out
22/04/2009
Max Out
23/04/2009
24/04/2009
Inside
Figure 7: Outside temperature maximum and minimum and inside temperature
As seen in Figure 8 workers declared on average that they were neutral to slightly cool (4.34). However for all of
them the thermal environment was acceptable and for 87% there was no need for change even if 13% would have
liked the room to be warmer. Furthermore, 70% declared that there was no need for any change in the air-movement
but 26% would have liked more air movement. However 94% didn’t open the window during the day of the survey.
When people were asked how the temperature was at that particular moment, 70% answered that it was ok and for
23% it was perfect. The majority of people surveyed declared they didn’t adjust their clothing level 15 minutes prior to
answering the survey. Only 13% stated they did. Most subjects wore similar clothing ensembles, 60% wore
pants/skirt, shirt, socks/pantyhose and shoes. The addition of a vest/cardigan was declared by 40% of respondents.
When asked to describe the room, half of respondents indicated that the room was full of light, while nearly a quarter
stated that the room was full of fresh air and a good place to work. Interestingly, 33% of the answers pointed out that
the room was warmer than the rest of the office while 16% of the answers indicated that it was cooler than the rest of
the office. The predominant activity conducted in the space is simply having a break or getting away from the work
desk. 10% of respondents indicated that they were there to enjoy the view. Use of the kitchen facilities is also
significant, with many respondents having lunch or coffee.
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How do you feel right now in this room?
45%
40%
100%
Acceptable
35%
30%
25%
87%
No change
20%
15%
No change in
the air
10%
70%
5%
0%
Series1
Hot
Warm
Slightly
warm
Neutral
Slightly
cool
Cool
Cold
0%
6%
10%
40%
26%
10%
6%
No window
opened
Figure 8: Likert scale analysis: How do you feel now in this room?
94%
Figure 9: Response rates
Right now this room is...?
How is the temprature right now?
70%
A good place to relax
60%
A good place to work
50%
Cooler than the rest of the office
40%
Essential in everyday work
30%
Full of fresh air
20%
Full of light
10%
More noisy than the rest of the office
0%
Series1
perfect
ok
too hot
too cold
window to
be opened
23%
70%
0
3%
3%
Not relevant to the office
13%
23%
50%
13%
10%
33%
Figure 11: Response rates
What am I doing here...?
What I like when I am here
60%
Having a break
73%
The view
10%
Enjoying the view
Working
0%
Making a phone call
0%
Having a business meeting
3%
Meeting people socially
3%
33%
The fresh air
36%
Getting away from my desk
It is warmer than the rest of the office
10%
It is coller than the rest of the office
10%
23%
To meet people
23%
Having a coffee
33%
Eating
70%
To get away from my desk
23%
Warming up my lunch
Other
16%
Warmer than the rest of the office
Figure 10: Response rates
Breating fresh air
43%
23%
to work but feeling relaxed
10%
3%
Feeling relaxed
3%
Figure 12: Response rates
23%
Figure 13: Response rates
When asked about the qualities of the space, the view was the most frequent response, followed closely by the fact
that the room was simply an alternative to their usual work station. One third of respondents indicated that they liked
the fresh air, while nearly a quarter appreciated the social aspect of meeting other workers. Several indicated that the
space provided a place where they could feel more relaxed, either with or without bringing work. Interestingly, ten
percent of respondents considered the space warmer than the rest of the office, while the same number considered
the space cooler. This is above what would be expected of a normal PMV/PPD response, possibly indicating
responses to the different mix of air and mean radiant temperature.
The benefits of the MM system in this space is difficult to separate from other qualities of the space; the view, the
kitchen facilities, the social aspect, the chance to relax somewhere away from the pressures of work at the desk.
However, since many respondents regarded the room as being slightly warmer or slightly cooler than at their desk
indicates that the variation from desk temperatures is important, giving workers a break from the constant conditions
of AC, and possibly encountering a different mix of air and mean radiant temperatures. That many respondents
regarded the air as being ‘fresh’ indicates a perception of qualitative difference in the nature of air being breathed,
whether due to its temperature, humidity, air speed, oxygen content, or other (e.g. odours). What may be significant
here is the opportunity to enjoy indoor air quality conditions that are different to those encountered at the workstation.
1B) PRELIMINARY RESULTS: MACQUARIE UNIVERSITY COMMERCE BUILDING, SYDNEY
Figure 14 below shows daily outdoor temperatures recorded during this period plotted against internal temperatures
measured from the HOBO dataloggers and averaged across each zone. Between March to June there was a steadily
decline in outdoor temperatures as the study shifted from autumn into the winter months, and each zone mirrors
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these changes (typical for a NV building). Based on one-way ANOVA statistical analyses, the average outdoor
temperature of 14.7°C was significantly cooler (p = 0.000) than average temperatures for the North (22.6°C), Central
(22.4°C) and South (20.9°C) zones. As expected, the north façade experienced significantly warmer temperatures
than Central and South zones, whereas temperatures in the South zone were significantly less than in Central
offices. The variability of these temperatures is also worth noting. The Central zone experienced less variability than
the perimeter due to constant air-conditioning throughout these zones. In contrast, the variability in northern offices
was greater than the southern zone. These temperature ranges are due to the use of HVAC when temperatures rise
towards the 25°C cooling set-point and drop towards the 18°C heating set-point, which explains why temperatures
rarely exceed these extremes. The northern façade is also susceptible to high solar heat gains from office windows,
suggesting the blips present in the data.
Figure 14: Internal Temperatures for the Sydney field study (Weekdays between March and June 2009)
Figure 15: Internal temperatures for the Sydney study showing effects of AC to NV switch-over
In order to show what happens to indoor temperatures during AC to NV switch-over, a typical week in the study
period was chosen (as shown in Figure 15 above). During NV mode, temperatures are allowed to rise towards the
25°C cooling set-point at which time; AC mode turns on, automatically shutting the windows and stabilises the
internal temperatures to around 24°C (±1.5°C). These events are present in Figure 15 when the temperatures peak
at 25°C during the middle of the day.
Over 100 questionnaires have been conducted with representative samples of both genders (37 males and 63
females) for Sydney’s field study. Clothing insulation (clo) values were recorded using a standardised check-list of
typical office clothing items (ASHRAE 2004). The average clo value for females (0.78) was significantly higher than
males (0.62, p = 0.002). Clo values were also plotted against outdoor and indoor temperatures for any significant
relationships. This data was binned into degrees and thus analysed using weighted linear regressions. The clo
relationship with outdoor temperatures was non-significant (p > 0.05), however, Figure 16 below illustrates a
2
significant negative clo relationship with indoor temperatures (p = 0.000). With R = 89.1%, this suggests that indoor
temperatures have a strong influence on the amount of clothing insulation worn by the building occupants. As indoor
temperatures increase, occupants will remove items of clothing.
Figure 16: Clothing insulation relationship against indoor temperature for Sydney MM field study
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On the basis of AC/NV mode at the time of the questionnaire, it was possible to compare responses during each
mode of operation, i.e. AC and NV modes. Table 1 below highlights some of the key study variables being
investigated throughout this study. The only significant difference found was Actual Mean Vote (AMV) wherein
participants rated their level of comfort across a 7-point Likert Scale (ranging from Cold (-3) through Neutral (0) to Hot
(+3)). Within AC mode, the average AMV was neutral (-0.02), which is significantly cooler (p = 0.01) than the average
AMV during NV mode (0.80). This suggests most people found the building to be slightly warmer during NV mode
compared to AC mode, possibly due to the increased indoor temperatures needed for the NV algorithm to start. Other
variables did not achieve any significant levels of difference. Thermal preference was significantly different. People
did not want the thermal environment changed during AC mode (2.16) whereas during NV mode, occupants
preferred to be cooler (1.73). Temperatures were significantly different which can be verified by Figure 15 above
which demonstrates that when the building is in NV mode, indoor temperatures will rise until the 25°C cooling setpoint.
Table 1: Comfort data summaries for Sydney MM field study
Study Variable
AC Mode (n = 81)
NV Mode (n = 25)
Significance
AMV
-0.02
0.80
p = 0.01
Acceptability
1.75
1.73
p > 0.05
Preference
2.16
1.73
p = 0.02
Clo
0.73
0.68
p > 0.05
Productivity
-0.5%
0%
p > 0.05
PMV
-0.25
0.19
p > 0.05
Temperature
21.9
24.0
p = 0.03
DISCUSSIONS
As shown in Figures 16 and 17, internal temperatures are clipped at 25°C as this is the peak temperature zones can
experience before the BMS switches into AC mode. Before this transition, office spaces will gradually increase in
temperature due to increased solar loads, particularly in the North zone, which experiences significantly warmer
temperatures than both the Central and South zones. Up till this point, occupant comfort is said to be neutral, as
judging from the summary data present in Table 1 above. However, what isn’t clear is what happens when the
building activates the HVAC system. Currently the building’s MM ventilation algorithm, upon a temperature greater
than 25°C has been sensed; the air-conditioning system will lower and maintain temperatures around 24°C (± 1.5°C
depending on concurrent outdoor weather). As can be illustrated in Figure 15 above, there is a lag effect after an AC
mode switch-over event. This may be due to inconsistencies depending on the position of the BMS sensors, but
overall it takes 30 minutes to reach optimal temperature. Comfort votes taken before and after these periods propose
that occupants tend to feel warmer leading up to AC mode operation as internal temperatures are allowed to rise
towards the 25°C set-point. Correspondingly, as highlighted in Table 1, the average AMV when the building was in
NV mode is slightly warmer than neutral (1.17).
When the building switches into AC mode, internal temperatures are maintained at around 24°C. Contrastingly, the
average AMV whilst AC mode was in operation was neutral (0.00) which suggests that occupants preferred these
conditions (Rowe 2004; Brager and Baker 2008). However, while PMV values during both these modes do not
suggest any significant differences (both -0.25 and 0.19 are within the limits of a Neutral vote), more conclusive
evidence is needed to define occupant perceptions of the thermal environment whilst the building switches between
AC and NV mode. A meaningful analysis would be to investigate any differences in clo values through both operation
modes. The Sydney field study relies heavily on the temporal effects of thermal comfort, especially as this building is
capable of switching between modes various times during a day. While the majority of the data presented here was
collected in typical winter months, i.e. Figure 14 shows that outdoor temperatures rarely rose above 20°C between
April and June, what can be expected during summer months occurred during March in Figure 15, in which high
outdoor temperatures, often above 20°C will force the building into AC mode as internal temperatures during these
periods exceed the building’s natural ventilation limits.
Not only do indoor environments influence clothing choices but so too does the outdoor weather (Morgan and de
Dear 2003; De Carli et al. 2007). For NV buildings, occupants tend to change their clothing according to external
conditions as the building more closely matches the prevailing outdoor temperatures. However, as Figure 16
demonstrates, occupant clo values are only moderately related to indoor temperatures and not outdoor conditions.
Perhaps there is a difference in these relationships when the building is in AC mode and when it is in NV mode. As
yet, there is not enough conclusive data to suggest these correlations, but this may be highlighted later on in the
study.
CONCLUSION
The two case studies presented here adopt different approaches to mixed mode ventilation, with the NAB building
offering mixed mode ventilation in a break-out area adjacent to workspaces, and the Commerce building using mixed
mode ventilation within workspaces. While these two approaches have necessitated slightly different methodologies
for evaluating thermal comfort, it is clear that there are benefits in each of these approaches over a traditional airconditioning system. Of particular interest are the points of change from one mode to another, either spatially, as
with the NAB building, or temporally, as with the Commerce building. Comparison between the different comfort
conditions in each case study will form a future component of this project, but for now what is evident is that steadystate models are inadequate for describing thermal comfort conditions in mixed mode buildings, and that new
temporal and spatial models need to be developed.
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ACKNOWLEDGEMENTS
The project has been funded by an ARC (Australian Research Council) Discovery Grant. We are grateful to Kerry
Russell and Macquarie University’s Office of Facilities Management (OFM) and to Angelina Andonovski and John
Hurren at NAB Docklands for their support and assistance in gathering data for these projects. We would like to
extend our appreciation to all participants who have given their time to complete surveys and questionnaires.
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from
www.fmlink.com/ProfResources/Sustainability/Articles/
Rijal, H. B., Tuohy, P., Humphreys, M. A., Nicol, J. F., Samuel, A. and Clarke, J. (2007) 'Using results from field
surveys to predict the effects of open windows on thermal comfort and energy use in buildings', Energy and
Buildings, 39: 823-836
Rowe, D. (2004) 'Thermal comfort in a naturally-ventilated environment with supplementary cooling and heating',
Architectural Science Review, 47(2): 131-140
Turner, S. (2008) 'ASHRAEs Thermal Comfort Standard in America: Future steps away from energy intensive
design', Proceedings of the 5th Windsor Conference - Air-Conditioning and the Low Carbon Cooling
Challenge, Cumberland Lodge, Windsor, UK
rd
43 Annual Conference of the Architectural Science Association, ANZAScA 2009, University of Tasmania
262
Appendix L: Windsor 2010 Conference Paper
Deuble, M. and de Dear, R. (2010) ‘Green occupants for green buildings: The missing link?’,
Proceedings of the 2010 Windsor Conference: Adapting to Change: New Thinking on
Comfort’
Windsor, London, UK, Network for Comfort and Energy Use in Buildings,
http://nceub.org.uk, 9-11 April 2010
263
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
Green Occupants for Green Buildings: The Missing Link?
Max Deuble1* and Richard de Dear2
1
2
Macquarie University, North Ryde, NSW 2109, Australia
University of Sydney, Sydney, NSW 2006, Australia
*
Corresponding email: mdeuble@els.mq.edu.au
Summary
This paper follows the results of recent post-occupancy evaluation surveys within two
office buildings at Macquarie University, Sydney Australia. Supplemented with an
environmental attitudes questionnaire, based upon the New Ecological Paradigm
(Dunlap et al. 2000), it was found that occupant satisfaction levels are positively
associated with environmental beliefs. Occupants with higher levels of environmental
concern were more tolerant of their building, particularly those featuring aspects of
green design, such as naturally-ventilated façades and operable windows. Despite
their criticisms of the building’s indoor environmental quality, the ‘green’ occupants
were prepared to overlook and forgive less-than-ideal conditions more so than their
‘brown’ (non-green) counterparts. Drawing upon these results, statistical analyses of
the association between environmental beliefs and occupant satisfaction in this paper
support the hypothesis that broad environmental attitudes are closely associated with
the stronger ‘forgiveness factor’ often observed in green-intent buildings.
Keywords
Green buildings, Post-occupancy evaluation (POE), Forgiveness factor, New
Ecological Paradigm (NEP)
Introduction
Many adaptive comfort studies (Humphreys and Nicol 1998; Nicol and Humphreys
2002) have called for greater indoor environmental variability, either via user
adjustments to operable windows, shade devices, etc or automated controls shifting
heating, ventilation and air-conditioning (HVAC) set-points in sync with weather and
seasonal variations outdoors. This shift towards greater indoor climatic variability is
integral to many sustainable building designs. Buildings featuring natural ventilation
capabilities are typically defined nowadays as green-intent buildings. Many studies
(Abbaszadeh et al. 2006; Leaman and Bordass 2007; Brager and Baker 2009) have
found occupants are more favourably disposed to green buildings than their
conventional energy-intensive predecessors. It is now widely accepted that occupants
prefer more adaptive opportunities inside their buildings than the sealed façade, airconditioned (AC) designs of last century (Baker and Standeven 1996). Leaman and
Bordass (2007) observed in their extensive database of post-occupancy evaluation
(POE) studies that occupant satisfaction scores for green-intent buildings tend to be
higher than those in conventional AC buildings. Despite occupants preferring greater
adaptive opportunities, they do not necessarily expect the thermal excursions that
sometimes occur in naturally-ventilated (NV) buildings, especially in hot weather.
Recent POE studies suggest that, notwithstanding occasional discomforts, occupants
264
of green buildings tend to forgive these shortcomings provided they can exercise a
modicum of indoor environmental control (Leaman and Bordass 2007). Coined as the
‘forgiveness factor’, derived by dividing ‘comfort overall’ scores by the average of
the variables for temperature in summer and winter, ventilation/air in summer and
winter, noise and lighting, this variable describes how people extend their comfort
zone by overlooking and allowing for inadequacies of their thermal environment
(Leaman et al. 2007). Although many green buildings tend to be hotter in summer,
colder in winter and contain more glare from the sun and sky than their conventional
AC alternatives, the occupants tend to be more forgiving. This toleration of moderate
discomfort suggests that people may have an understanding of and a connection to the
outdoor climate by virtue of the buildings design. Leaman and Bordass (2007) suggest
increased knowledge of the adaptive opportunities in buildings yields a greater
likelihood of reduced discomfort.
Environmental Attitudes, Behaviours and The New Ecological Paradigm (NEP)
In recent decades, there has been a growing awareness of the problematic relationship
between modern industrialised societies and the physical environments on which they
depend (Dunlap 2008). With the emergence of pervasive environmental problems
such as climate change, researchers have started exploring how to quantify public
sentiment on these issues. The New Ecological Paradigm (NEP) scale, a revision of
the New Environmental Paradigm, is a 15-item questionnaire consisting of 8 pro-NEP
and 7 anti-NEP items. It measures strength of endorsement (from low to high) of an
ecological worldview (Dunlap et al. 2000). After extensive application across diverse
studies, a broad consensus is emerging in the environmental psychology literature that
the NEP represents a valid and reliable scale for measuring levels of ecological beliefs
and behaviours (Cordano et al. 2003). To date, however, the NEP scale has not been
used in building occupant studies.
Methods
Sydney’s Climate
The Sydney metropolitan region is located on the eastern coast of Australia (34°S,
151°E) and is characterised by a moderately temperate climate. Influenced from
complex elevated topography surrounding the region to the north, west and south and
due to close proximity to the Tasman Sea to the east, Sydney avoids the high
temperatures commonly associated with more inland regions as well as the high
humidity of tropical coastal areas (BoM 1991). The summer months of December to
February can be described as warm-to-hot with moderate-to-high humidity peaking in
February to March. Between June and August, Sydney experiences cool-to-cold
winters. Macquarie University (MQ) is located in Sydney’s North Ryde, 16km northwest of Sydney’s CBD (33° 46’ S, 151° 6’ E). Seasonal variations are fairly consistent
with the greater metropolitan region with a mean summer daily maximum temperature
of 26-28°C, a mean winter daily maximum of 17°C and an annual mean daily
maximum of 22-23°C. Mean minimum daily temperatures range from 5-8°C in
winter, to 17-18°C over the summer months, with an annual daily minimum
temperature of 11-13°C (BoM 2007). Given the city’s yearly seasonal variations,
Sydney’s climate is well suited to mixed-mode (MM) buildings.
Case Study Buildings
Two academic staff buildings from MQ were selected for this study, both having
North-South orientations, with North facades directly irradiated from the Sun,
creating warmer internal temperatures than the South-facing perimeter zones. The
265
sample buildings consisted of a MM building (see Photo 1) commissioned in 2006,
and a NV building (see Photo 2) built in the late 1960s.
The MM building features operable windows on all perimeter cellular offices along
North and South facades separated by an AC central open-plan office zone. Indoor
temperature and outdoor weather sensors drive the Building Management System
(BMS) to switch to AC mode when average indoor temperatures increase above 25°C.
Occupants are mainly academics and administrative staff from economics and finance
departments. The NV building features occupant-operated windows and a narrow
floor-plate traversed by a central corridor with single- and dual-occupant cellular
offices on either side. Academic staff, administrative staff and post-graduate students
from a variety of environment-related disciplines occupy this NV building.
Photo 1: MQ, MM building (North façade) Photo 2: MQ, NV building (North façade)
featuring operable windows with external featuring occupant-operated windows with
solar shading devices on north-facing some individual air-conditioner units
windows
Measurements
Throughout the study, dataloggers have been randomly located within each building
to record air temperatures, globe temperatures and relative humidity at 5 minute
intervals. These were placed within 1 metre of the occupants’ workstation to
characterise the immediate thermal environment experienced by the occupant whilst
working. In addition to indoor climate measurements, outdoor air temperature was
also recorded over the same period at a nearby automatic weather station. Concurrent
BMS data from the survey period was collected from the University’s Office of
Facilities Management (OFM).
266
Questionnaires
Between March and April 2009 (the Austral autumn), two questionnaires were
distributed to all staff in both buildings:
1. The three-page Building Use Studies (BUS 2009) POE uses 7-point Likert
scales with space for commentary, covering variables relating to occupant
satisfaction, e.g. thermal, visual and acoustic comfort, indoor air quality,
perceived health and productivity, and general acceptance of the workplace.
BUS (2009) further details the BUS methodology. Combinations of these
scores enable the calculation of BUS comfort and satisfaction indices, as well
as the forgiveness factor (defined earlier).
2. The Environmental Attitudes questionnaire is a 15-item version of the NEP
Scale (Dunlap et al. 2000), using 5-point response scales ranging from
Strongly Disagree to Strongly Agree, with higher scores on the scale from 1
(low) to 5 (high) indicating greater levels of environmental concern. All scales
were converted to a NEP score by summing each item response and dividing
by the total number of items in the scale. Results were analysed using MiniTab
statistical software.
Results
Thermal Environment
In order to show the differences between each building based on objective
measurements, i.e. internal temperature, it is instructive to show how both buildings
perform under the same weather conditions. Building occupant studies are generally
conducted in summer, hence it was necessary to obtain temperature data from
September 2009 to reflect similar conditions to when the questionnaires were
administered 6 months prior. From temperatures averaged across all dataloggers, it
was established that the NV building experienced significantly warmer temperatures
(average = 23.5°C, p = 0.000) than the MM building over the same period (average =
22.2°C). Figure 1 below highlights the discrepancies between the internal
temperatures within these buildings. Temperatures inside each building were far
greater than the surrounding outdoor air temperature throughout the day (mean =
16.3°C, p = 0.000). As a NV building, internal temperatures closely match changes in
outdoor weather conditions, whereas the MM building contained its indoor
temperatures within a narrower band.
Figure 1 indicates that internal temperatures within the MM building rarely exceed
25°C due to the BMS switching into AC mode whenever average temperatures
reached the 25°C trigger temperature. Less than 10% of occupied office hours (i.e.
8am-6pm weekdays) within this building experienced indoor temperatures greater
than 25°C. In contrast, temperatures inside the NV building varied between 20-28°C.
Internal temperatures in the NV building exceeded the 25°C threshold almost 50% of
all occupied office hours.
Using a 7-day running average of daily mean outdoor temperatures, Figure 1 also
presents the 80% thermal acceptability band limits derived from the ASHRAE
Standard 55 adaptive comfort model (ASHRAE 2004). These indicate the suggested
range of internal operative temperatures that should not be exceeded within the
occupied zone (de Dear 2007). As seen in Figure 1 below, average temperatures
inside the NV building exceeded the upper limit of acceptable adaptive comfort on
four separate occasions in September. In contrast, the MM building never exceeds
these limits; in fact indoor temperature only exceeded the 25°C trigger temperature on
one occasion.
267
Figure 1: Indoor and outdoor thermal environments comparing the NV and MM
buildings (September 2009)
POE and NEP Analysis
In total, 163 POE and NEP questionnaires were distributed in the MM building and
40 in the NV building. With a 53% response rate, the MM building returned 86
completed questionnaires (39 male, 47 female), and 29 (13 male; 16 female) were
completed from the NV building (73% response rate). Incomplete or suspect
responses were omitted from the samples in a basic quality assurance check. POE
responses for both buildings were benchmarked against the Australian BUS database
(as summarised in Table 1). The NEP questionnaire items were tested for internal
consistency and were found to have strong coefficient alphas (a= 0.82) suggesting
good internal consistency.
As shown in Table 1 (below), both buildings generally measure poorly in regards to
the POE summary variables. The NV building appears worse than the MM building in
most summary variables; it was found that the average forgiveness factor (FF) was
significantly higher than that for the MM building, with FF scores greater than 1.0
indicating greater levels of tolerance. The NV building had a significantly higher
mean NEP score (4.04, p = 0.005) than the MM building (3.69), plausible for
environmentally educated academics. Interestingly, the NEP score for the MM
building is relatively high for occupants associated with economics, finance and
business studies as scores greater than 3.0 generally indicate pro-environmental
attitudes.
Table 1: A summary of POE and NEP results for the MM and NV buildings
Study Variable
MM (n = 86) NV (n = 29) Significance
Forgiveness Factor
0.99
1.17
p = 0.019
Comfort Index
-0.39
-0.70
Not sig.
Satisfaction Index
0.02
-0.10
Not sig.
Perceived Productivity
-5.34
-10.71
p = 0.000
NEP
3.69
4.04
p = 0.005
In order to analyse environmental attitudes and their relation with forgiveness factors
within each building, it was important to isolate a control group that would not be
biased towards any environmental or building-related concepts. Administrative staff
within both buildings undertake various clerical duties and management aspects for
268
their respective faculties. Since they are not considered to have academically inclined
responsibilities, these groups were considered separate from the buildings’ academic
staff (summarised in Table 2).
Within the NV and MM buildings, administrative staff had slightly lower levels
environmental concern compared to the academic staff within the building. Also, both
groups were significantly different in regards to their FF, with the academics scoring
higher levels of tolerance for each building. Table 2 indicates that the administrative
staff of the NV building had significantly higher NEP scores (3.21) than those located
inside the MM building (2.66, p = 0.016). Correspondingly, the same group measured
higher degrees of forgiveness (NV = 0.89, MM = 0.74, p = 0.004).
Table 2: Analysis
buildings
Study Variable
Forgiveness Factor
NEP
of Forgiveness Factor and NEP results for the MM and NV
MM Academic (n = 64)
1.02
3.80
NV Academic (n = 22)
1.14
4.20
Significance
p = 0.017
p = 0.000
Study Variable
Forgiveness Factor
NEP
MM Admin (n = 13)
0.74
2.66
NV Admin (n = 7)
0.89
3.21
Significance
p = 0.004
p = 0.016
Since the NEP questionnaire items are measured across a 5-point Likert scale,
responses were binned according to their item response (from low to high, 1 to 5).
Weighted according to the number of FF samples within each NEP bin, a linear
regression model was fitted to test any correlation between NEP and FF scores for
these two case study buildings. As illustrated in Figure 2, there is a strong positive
relationship between environmental attitudes and forgiveness factors (R2 = 98.9%, p =
0.001) suggesting higher levels of environmental beliefs yielded higher levels of
tolerance.
Figure 2: Relationship between NEP and FF scores for both study buildings.
Discussions
With higher temperatures recorded in the NV building (Figure 1), it is reasonable to
expect that perception of productivity at temperatures up to 28°C would be
significantly lower than a MM building. Occupants in both buildings have often
269
complained about indoor temperatures in summer months, particularly on the north
façade. This anecdotal feedback is consistent with a trend emerging from Australian
green buildings that have undergone the BUS POE (Leaman et al. 2007). In
comparing 22 green-intent buildings against 23 conventional HVAC office buildings,
Leaman et al (2007) reported that green buildings were perceived as hotter in summer
and cooler in winter. Green-intent buildings, such as the NV and MM buildings in this
study, are expected to perform this way. In comparing the ‘forgiveness’ scores from
Leaman et al (2007) (summarised in Table 3 below) to those results in Table 1
(above), it was found that the MM building is poorly received by its users
(forgiveness = 0.99, equal to that of conventional AC buildings in Australia).
Contrastingly, the NV building measured significantly higher NEP scores indicating
greater tolerance to perceived thermal variance (forgiveness = 1.17), consistent with
other green-intent buildings already in the BUS database.
Table 3: Forgiveness scores by ventilation type: Australian BUS building database (n
= 45)
Study Variable
Green-intent (NV, ANV, MM) AC
MM (MQ)
NV (MQ)
Forgiveness Factor 1.02
0.99 0.99
1.17
n
22
23
Note: Higher values indicate occupants more tolerant or ‘forgiving’ of the conditions. Building types
include natural ventilation (NV), advanced natural ventilation (ANV), mixed-mode (MM) and airconditioning (AC).
The correlation of NEP and FF scores shown in Figure 2 supports the hypothesis that
green building users are more prepared to overlook and forgive less-than-ideal
conditions than their ‘brown’ (non-green) counterparts suggesting there is a possible
link between occupant satisfaction and environmental attitudes. Whilst the NEP Scale
was originally designed to measure environmental concern of the general public, with
both samples containing tertiary-educated participants there is a limit to what can be
drawn from these results. Nonetheless, it amplifies how occupant attitudes and
expectations play an important role in the way green-intent buildings are designed,
built and received.
Conclusions
Green buildings have greater thermal variations than their AC counterparts, in which
centralised HVAC provides static indoor temperatures to all occupants all-year round.
This paper suggests green building users are more forgiving of their building,
consistent with the hypothesis that green buildings need green occupants. Whilst the
study only represents two green buildings at MQ, it highlights the increasing
awareness to the psychological dimensions of occupant adaptation, such as attitudes,
expectation and control. Given the urgency to mitigate global warming, it has become
apparent that people’s attitudes, and the behaviours they entail, can be manipulated.
Whilst buildings take years to build and even months to retrofit, the path to altering
people’s expectations of the built environment presents the low-lying fruit. According
to this study, the forgiveness of green buildings can be cultivated. Given the multitude
of sustainable and pro-environmental behaviour literature, there is great potential for
occupants to be ‘re-educated’ about the role buildings play in addressing global
climate change. The emergent practical applications of adaptive building design calls
for the clear communication of intent by designers to the users and building managers
to ultimately assist in the transition to an energy efficient, low-carbon future.
270
Acknowledgements
We are enormously grateful to Adrian Leaman for permission to use the BUS
questionnaire under license and his assistance in data analysis. We would also like to
thank Riley Dunlap for his valuable comments and encouragements, and Macquarie
University’s OFM, especially Kerry Russell, for their support. Finally, and most
importantly, we express our appreciation to all the building occupants who responded
to the questionnaires.
References
Abbaszadeh, S., Zagreus, L., Leher, D. and Huizenga, C. (2006), 'Occupant
satisfaction with indoor environmental quality in green buildings',
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Conditions for Human Occupancy, Atlanta, Georgia, American Society of
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Building Research and Information, 37(4): 369-380
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http://www.usablebuildings.co.uk/WebGuideOSM/index.html
Cordano, M., Welcomer, S. A. and Scherer, R. F. (2003), 'An analysis of the
predictive validity of the New Ecological Paradigm Scale', Journal of
Environmental Education, 34(3): 22-28
de Dear, R. J. (2007), 'Adaptive comfort applications in Australia and impacts on
building energy consumption', Proceedings of the Sixth International
Conference on Indoor Air Quality, Ventilation and Energy Conservation in
Buildings: Sustainable Built Environment, Sendai, Japan
Dunlap, R. E. (2008), 'The New Environmental Paradigm Scale: From Marginality to
Worldwide Use', Journal of Environmental Education, 40(1): 3-18
Dunlap, R. E., Van Liere, K. D., Mertig, A. D. and Jones, R. E. (2000), 'Measuring
endorsement of the New Ecological Paradigm: a revised NEP scale', Journal
of Social Issues, 56(3): 425-442
Humphreys, M. A. and Nicol, F. (1998), 'Understanding the adaptive approach to
thermal comfort', ASHRAE Transactions, 104(1): 991-1004
Leaman, A. and Bordass, B. (2007), 'Are users more tolerant of 'green' buildings?',
Building Research and Information, 35(6): 662-673
Leaman, A., Thomas, L. and Vandenberg, M. (2007), ''Green' Buildings: What
Australian Users are Saying', EcoLibrium, 6(10): 22-30
Nicol, F. J. and Humphreys, M. A. (2002), 'Adaptive thermal comfort and sustainable
thermal standards for buildings', Energy and Buildings, 34: 563-572
271
Appendix M: Co-Author Statement of Contribution
272
273
274
Appendix N: Architectural Science Review Paper
Status: Published; Drake, S., de Dear, R., Alessi, A. and Deuble, M. (2010) ‘Occupant
comfort in naturally ventilated and mixed-mode spaces within air-conditioned offices’,
Architectural Science Review, 53(3): 297-306
DOI: http://dx.doi.org/10.3763/asre.2010.0021
Journal Impact Factor: Not applicable: All research papers, research notes and review
articles are double-blind refereed.
275
Occupant comfort in naturally ventilated
and mixed-mode spaces within
air-conditioned offices
Scott Drake1*, Richard de Dear2, Angela Alessi1 and Max Deuble3
1
University of Melbourne, Melbourne, Australia
University of Sydney, Sydney, Australia
3
Macquarie University, Sydney, Australia
2
Contemporary concerns for improving environmental performance in buildings have led to an increased interest in natural
ventilation (NV) either on its own or in combination with air-conditioning (mixed mode (MM)) as an alternative to traditional
heating, ventilation and cooling (HVAC) systems. HVAC systems are widely used because they avoid many of the problems
encountered with NV or MM – noise, dust, insects, odours, temperature extremes – and readily conform to steady-state conditions of thermal comfort. However, it is possible that NV or MM can provide improved indoor air quality precisely through
variations associated with external climatic conditions. This article introduces an ARC (Australian Research Council) funded
project evaluating comfort conditions in MM spaces, using field studies from two buildings. The first, a University campus
building in Sydney, offers MM perimeter offices with air-conditioned central spaces, while the second, a commercial building
in Melbourne, offers a series of MM spaces that can be used by workers from adjacent air-conditioned office spaces. The aim
of the project is to evaluate the feasibility of using MM either in place of or in association with traditional HVAC systems. The
outcomes of the project will be used to elaborate the justifications for inclusion of NV spaces and/or NV periods within contemporary office environments. This article presents preliminary results of the fieldwork at each location.
Keywords: Hybrid ventilation; mixed-mode buildings; thermal comfort
INTRODUCTION
Current practices in office buildings generally provide standardized indoor climates for all occupants using heating, ventilation and cooling (HVAC) technology. Typically adopting
a building-centred, energy-consuming approach focused on
creating constant, uniform-neutrality conditions, the primary
purpose of HVAC systems is to provide acceptable indoor
air quality and thermal comfort aiming for an optimum
‘steady-state’ temperature setting based on Fanger’s predicted
mean vote–predicted percentage of dissatisfied (PMV–PPD)
model (Fanger, 1970). This ‘static’ approach to thermal
comfort was intended to maximize safety and comfort. In contrast, a person-centred approach would purposely provide
variability across time and space (Brager and de Dear, 1998).
Spatially, thermally differentiated areas would be designed to
allow for individual thermal requirements. Temporally,
indoor temperatures would gradually drift towards outdoor
conditions in a way that would enable and encourage adaptations such as clothing changes and use of operable windows.
Recent studies (Baker and Standeven, 1996; Humphreys
and Nicol, 1998; Rowe, 2004; Humphreys et al., 2007;
Rijal et al., 2007) have made the case for greater environmental variation inside buildings, either via user adjustments
to windows, shade devices and so on or by adaptive algorithms that more closely match HVAC set-points to prevailing outdoor temperatures. The ‘adaptive’ thermal comfort
model (Humphreys and Nicol, 1998; Humphreys et al.,
2007) has advocated the shift towards variable indoor
environmental conditions, underlying an essential aspect of
sustainable building design, that is, providing thermal
comfort while reducing energy use and associated greenhouse gas emissions. Within conventional air-conditioned
(AC) buildings, the HVAC system contributes to over half
the energy and emissions required for building operation
(AGO, 1999). The move towards sustainability involves
decreasing the reliance on active systems and pursuing
more passive strategies of building design. One alternative
is natural ventilation (NV) with occupant-controlled
windows; however, while people may prefer a high degree
*Corresponding author: Email: sdrake@unimelb.edu.au
ARCHITECTURAL SCIENCE REVIEW 53 | 2010 | 297–306
doi:10.3763/asre.2010.0021 #2010 Earthscan ISSN: 0003-8628 (print), 1758-9622 (online) www.earthscan.co.uk/journals/asre
276
298 Drake et al.
of ‘adaptive’ opportunities (Baker and Standeven, 1996;
Brager et al., 2004), they do not appreciate the thermally
uncomfortable conditions likely to occur in NV buildings
during unusually hot or cold weather conditions. As a
result, building architects and engineers are exploring
‘mixed-mode’ (MM) ventilation as a way of combining the
best features of NV and AC buildings (Brager, 2006;
Brager and Baker, 2008).
MM BUILDINGS
The basic philosophy of MM or ‘hybrid’ ventilation is to
maintain a satisfactory indoor environment by alternating
between and combining natural and mechanical systems
to avoid the cost, energy penalty and consequential
environmental effects of full year-round AC (Brager,
2006; Lomas et al., 2007). These buildings provide good
air quality and thermal comfort using NV and operable
windows whenever the outdoor weather conditions are
favourable but revert to mechanical systems for HVAC
whenever external conditions make the NV option untenable for occupants.
Existing international comfort standards, for example,
the American Society of Heating, Refrigerating and
Air-Conditioning Engineers (ASHRAE) Standard-55
(ASHRAE, 2004), ISO 7730 (ISO, 2006) and pr-EN
15251 (CEN, 2007), mainly cover thermal comfort conditions under steady-state conditions based on laboratory
experiments. Field studies (Humphreys and Nicol, 1998;
Nicol and Humphreys, 2002, 2009; Rowe, 2004) have led
to the inclusion of an adaptive comfort standard (ACS)
serving as an alternative to the PMV-based method for freerunning, that is, NV buildings (ASHRAE, 2004). However,
the scope of the ACS option is heavily constrained to naturally conditioned, occupant-controlled spaces in which
thermal comfort conditions of the space may be heavily
influenced primarily by operable windows that open to
the outdoors and that can be readily adjusted by the occupants of the space. When mechanical cooling systems are
provided for the space, the ACS is not applicable (Nicol
and Humphreys, 2002; Turner, 2008). The potential flexibility offered by the standard is not available to hybrid
buildings, which may operate in a passive NV mode preferentially, equipped with only supplemental cooling and
heating for peak periods; or that control airflow using a
building energy management system (BEMS) rather than
occupant intervention; or spaces where operable elements
are not connected to the outdoors. As a result, these must
therefore resort to the more restrictive PMV – PPD
method (Turner, 2008). By comparing field studies in two
recent commercial and institutional buildings from Melbourne and Sydney, this article investigates thermal
comfort conditions within NV or MM spaces located
within traditionally AC buildings. The buildings used for
this study are Macquarie University’s (MQ) Commerce
building (building E4A) at North Ryde in Sydney and the
National Australia Bank (NAB) building at Docklands in
Melbourne.
THERMAL COMFORT: THE ADAPTIVE CONCEPT AND MM
SPACES
Thermal comfort is currently defined within two internationally recognized standards, the ASHRAE and British Standard BS EN ISO 7730, as ‘that condition of mind which
expresses satisfaction with the thermal environment’
(ASHRAE, 2004). So the term describes a person’s psychological state taking into account a range of environmental
and personal factors. Generally, air temperature, humidity,
air velocity, clothing and metabolic activity are the
common variables to be considered; however, other
comfort factors like a sense of relaxation and freedom
from worry and pain should also be considered (Darby and
White, 2005). These aspects represent a major impact on a
person’s thermal comfort, what de Dear defines as ‘perceptual relativity’, that is, when people interact with their
environment (de Dear, 2004). Established by ASHRAE
Standard 55 (2004), ‘reasonable comfort’ considers 80% of
occupant satisfaction as a reasonable limit for the
minimum number of people who should be thermally comfortable in an environment. However, occupant comfort
complaints are the biggest routine operational problem in
business administration: ‘if one person is too hot, someone
else nearby is too cold, and tomorrow both complaints
may be reversed’ (Opitz, 2008). In fact, people employ adaptive strategies to cope with their thermal environment like
removing clothing, change in posture, choice of heating,
opening windows or moving to non-AC areas.
The debate between the heat balance and the adaptive
approach has dominated the development of thermal
comfort science in recent years (Nicol and Humphreys,
2002). The thermal comfort standard used by ASHRAE is
based on experiments in climate chambers initiated by
Fanger in the 1960s. This approach combines the theory of
heat transfer with physiological thermoregulation to determine different comfort temperatures for people in a specific
environment: individuals studied in tightly controlled situations. The adaptive approach, on the other hand, is based
on field studies demonstrating that people are more tolerant
of temperature changes than laboratory studies suggest. In
fact, people act consciously and unconsciously to affect the
heat balance of the body, which is called behavioural thermoregulation. In this way, comfort is normally achieved in
a wider range of temperatures than predicted by ASHRAE
standards (Heschong, 1979; Nicol and Humphreys, 2002).
As Heschong (1979) interestingly points out, comfort is a
relationship between thermal content and human imagination. As humans we are capable of adapting to most
thermal experiences, but mostly we are in need of variations
to avoid ‘thermal boredom’ (Kwok, 2000).
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Occupant comfort in mixed-mode spaces 299
According to Humphreys and Nicol (1998), straightforward application of the Fanger equation underestimates
human adaptability to indoor climate by about 50%,
leading to excessive energy use and inappropriate design
(Humphreys and Nicol, 1998). The adaptive approach to
thermal comfort is based on the findings of surveys that
focus on gathering data about the thermal environment and
the simultaneous thermal response of the individuals in
real situations, keeping researcher intervention to a
minimum, as achieved in our Melbourne and Sydney case
studies. The fundamental assumption of this approach is
expressed by the adaptive principle: ‘if a change occurs
such as to produce discomfort, people react in ways which
tend to restore their comfort’ (Nicol and Humphreys,
2002). Both Angela and Max are conducting observations
that have already given indications related to people’s adjustments to their environment. For example, at the NAB, there
is a frequency of people entering the teapot room, indicating
the need for a break from their work but also the need to enter
a different thermal environment, hence seeking relaxation as
well as fresh air. There is a clear association between comfort
conditions and people’s actions that links comfort temperatures to the context in which individuals find themselves.
Research at the NAB looks into people’s behaviour and
how they move into the NV teapot area from their AC
office space, what they do and why they come there. Patterns
of movement and various chosen activities will reveal physical and psychological adaptations providing indications
about the space and its comfort acceptability.
Comfort has both a spatial and a temporal dimension, as
users respond to different weather or different activities by
adjusting clothing levels, temperature settings and window
openings or by moving to another space (Hawkes, 1997).
The option for people to react to a specific thermal situation
reflects the opportunities to adapt to their environment and
the possibility to achieve good levels of comfort. Welldesigned spaces should be able to provide different thermal
conditions in one location (Ong, 1997). Ong suggests the
need for heterogeneous conditions reflecting the complexity
of our sensory experience, allowing users to seek various
environmental conditions according to their particular
needs at a given time. In this respect, the NAB is the only
building in Australia that includes a key innovative design,
the MM space,1 and integrating NV within AC commercial
buildings.
Figure 1 | Plan, National Australia Bank, Melbourne
possibility to choose between active mechanical AC or
NV, depending on outdoor weather conditions (Figure 1).
The study at NAB focused on a single space, level 6
North-End Tea Point (Figure 2), as part of the MM north
façade. In this zone, the hybrid ventilation system allows
workers to switch between AC and MM using the control
panel (Figure 3). The MM spaces provide a unique setting
to investigate people’s response to NV within AC
environments.
The methodology used includes quantitative data collection, with instruments monitoring temperature, mean
radiant temperature, relative humidity (RH), air velocity
and radiation (Figures 4 and 5a –e). Two people counters
were used to determine the population of the room at
5-min intervals. These data will be complemented by qualitative data from questionnaires and fieldwork observations of
user behaviour in the space, to be conducted for a period
of one week four times throughout the year (corresponding
to the seasons).
CASE STUDY 1: NATIONAL AUSTRALIA BANK, DOCKLANDS,
MELBOURNE
The NAB building was the first new commercial building
built as part of the reconstruction of Melbourne’s Docklands.
As one of the largest single tenant commercial buildings in
Australia, with 140,000m2 of office space suitable for
around 4000 employees, the building features a series of
MM spaces along the northern façade, giving users the
Figure 2 | Plan of the North-End Tea Point, level 6
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300 Drake et al.
Figure 3 | The control panel
Figure 5 | (a) Hygrometer (RH), (b) mean radiant temperature,
(c) thermistor (temperature), (d) hot wire anemometer (wind
speed) and (e) pyranometer (radiation)
Figure 4 | Overview of the room and the instruments
CASE STUDY 2: MACQUARIE UNIVERSITY COMMERCE
BUILDING, SYDNEY
Macquarie University’s (MQ) North Ryde campus is located
within the Sydney metropolitan region. Commissioned in
2006, the Commerce building is a seven-storey office building occupied by academic and administrative staff. Consisting of MM cellular offices with operable windows along
north and south perimeter zones separated by AC central
open-plan office space, the entire façade is built on a
louvre system featuring external solar shading over the
northern windows. Figure 6 below shows the typical
layout of the buildings floor plan. Automated high and low
external louvres provide NV to each floor, with adjustable
internal grilles to control airflow, supplemented by useroperable windows. Indoor temperature and outdoor
weather sensors prompt the Building Management System
(BMS) to switch into AC mode whenever a peak temperature
greater than 258C is sensed in any zone. During AC mode,
internal temperatures are maintained at 248C (+1.58C) as
defined in the building’s algorithm. BMS switch-over to
NV is conditional when external meteorological conditions
and the indoor thermal climate fall into an acceptable zone
for the occupants. Figures 7a and 7b show the northern
and southern façades of Commerce building.
Dataloggers randomly located throughout the building
record air temperature and RH at 5-min intervals throughout
the study. Outdoor weather conditions were collected from a
nearby automatic weather station, and BMS data were collected from the University’s Office of Facilities Management. Field studies used mobile observations to
supplement continuous monitoring of occupant workplaces,
using the thermal comfort ‘sputnik’ system (Figure 8). These
provided detailed thermal comfort measurements for air
temperature, mean radiant temperature, RH and air speed
at a height of 0.6m within each occupied zone. Standardized
comfort questionnaires were used to record occupant perceptions of thermal comfort within their workspace, including
standardized clothing garment and metabolic activity checklists allowing the calculation of various comfort indices, for
example, PMV, effective temperature (ET*) and standard
effective temperature (SET*) (ASHRAE, 2004). Statistical
analyses were performed using Minitab statistical software.
PRELIMINARY RESULTS, CASE STUDY 1
The survey was conducted on 29th April 2009 between
10:30 am and 3 pm. The people counters established an
average of 200 entries per day, with 100 occurring
between morning tea and lunchtime. Most people entered
the room at least twice per day, which means that only 66
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Occupant comfort in mixed-mode spaces 301
Figure 6 | Commerce building typical floor plan
Figure 7 | (a) Commerce building, North façade and (b) commerce building, South façade
people (33%) were in the room at the time of surveying.
Thirty people volunteered to answer the survey, a response
rate of just below half. The average age of respondents
was 33 years with 43% females and 56% males. The
majority of people surveyed, 73%, have been working at
NAB for more than one year and 97% of them worked previously in an AC office mainly in Melbourne.
Throughout April, outdoor temperatures ranged between
a minimum of 78C and a maximum of 328C. During the
week of observations, from 20th to 24th April, the average
outdoor temperature was 168C, quite typical for autumn in
Melbourne as temperatures were often in the mid-20s
(Figure 9). Internal temperatures during this same period
ranged between 23 and 258C.
As seen in Figure 10, workers declared on average that they
were neutral to slightly cool (4.34). However, for all of them
the thermal environment was acceptable and for 87% there
was no need for change even if 13% would have liked the
room to be warmer. Furthermore, 70% declared that there
was no need for any change in the air movement but 26%
would have liked more air movement. However, 94% did
not open the window during the day of the survey.
When people were asked how the temperature was at that
particular moment, 70% answered that it was ok and 23%
that it was perfect. The majority of people surveyed declared
they did not adjust their clothing level 15min prior to answering the survey. Only 13% stated they did. Most subjects wore
Figure 8 | ‘Sputnik’ thermal comfort system used for the Sydney MM field study
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302 Drake et al.
Figure 9 | Outside temperature maximum and minimum and
inside temperature
similar clothing ensembles; 60% wore pants/skirt, shirt,
socks/pantyhose and shoes. The addition of a vest/cardigan
was declared by 40% of respondents.
When asked to describe the room, half of the respondents
indicated that the room was full of light, while nearly a
quarter stated that the room was full of fresh air and a
good place to work. Interestingly, 33% of the answers
pointed out that the room was warmer than the rest of the
office, while 16% of the answers indicated that it was
cooler than the rest of the office. The predominant activity
conducted in the space is simply having a break or getting
away from the work desk. In all, 10% of respondents indicated that they were there to enjoy the view. Use of the
kitchen facilities is also significant, with many respondents
having lunch or coffee.
When asked about the qualities of the space, the view was
the most frequent response, followed closely by the fact
that the room was simply an alternative to their usual workstation. One third of respondents indicated that they liked the
fresh air, while nearly a quarter appreciated the social aspect
of meeting other workers. Several indicated that the space
Figure 10 | Likert scale analysis
provided a place where they could feel more relaxed,
either with or without bringing work. Interestingly, 10% of
respondents considered the space warmer than the rest of
the office, while the same number considered the space
cooler. This is above what would be expected of a normal
PMV – PPD response, possibly indicating responses to the
different mix of air and mean radiant temperature
(Figures 11– 15).
The benefits of the MM system in this space are difficult
to separate from other qualities of the space: the view, the
kitchen facilities, the social aspect, the chance to relax somewhere away from the pressures of work at the desk.
However, since many respondents regarded the room as
being slightly warmer or slightly cooler than at their desk
indicates that the variation from desk temperatures is
Figure 11 | Response rates
Figure 12 | Response rates
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Occupant comfort in mixed-mode spaces 303
Figure 13 | Response rates
Figure 15 | Response rates
Figure 14 | Response rates
from the HOBO dataloggers and averaged across each
zone. Between March and June there was a steady decline
in outdoor temperatures as the study shifted from autumn
into the winter months, and each zone mirrors these
changes (typical for an NV building). Based on one-way
ANOVA statistical analyses, the average outdoor temperature of 14.78C was significantly cooler ( p ¼ 0.000) than
average temperatures for the North (22.68C), Central
(22.48C) and South (20.98C) zones. As expected, the North
façade experienced significantly warmer temperatures than
Central and South zones, whereas temperatures in the
South zone were significantly less than in Central offices.
The variability of these temperatures is also worth noting.
The Central zone experienced less variability than the perimeter due to constant AC throughout these zones. In contrast, the variability in northern offices was greater than in
the southern zone. These temperature ranges are due to the
use of HVAC when temperatures rise towards the 258C
cooling set-point and drop towards the 188C heating setpoint, which explains why temperatures rarely exceed
these extremes. The northern façade is also susceptible to
high solar heat gains from office windows, suggesting the
blips present in the data.
In order to show what happens to indoor temperatures
during AC to NV switch-over, a typical week in the study
period was chosen (as shown in Figure 17). During NV
mode, temperatures are allowed to rise towards the 258C
cooling set-point at which time AC mode turns on, automatically shutting the windows, and stabilizes the internal temperatures to around 248C (+1.58C). These events are
present in Figure 17 when the temperatures peak at 258C
during the middle of the day.
Over 100 questionnaires have been conducted with
representative samples of both genders (37 males and 63
females) for Sydney’s field study. Clothing insulation (clo)
values were recorded using a standardized checklist of
typical office clothing items (ASHRAE, 2004). The
important, giving workers a break from the constant conditions of AC, and possibly encountering a different mix
of air and mean radiant temperatures. That many respondents
regarded the air as being ‘fresh’ indicates a perception of
qualitative difference in the nature of air being breathed,
whether due to its temperature, humidity, air speed,
oxygen content or other (e.g. odours). What may be significant here is the opportunity to enjoy indoor air quality conditions that are different from those encountered at the
workstation.
PRELIMINARY RESULTS, CASE STUDY 2
Figure 16 shows daily outdoor temperatures recorded during
this period plotted against internal temperatures measured
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304 Drake et al.
Figure 16 | Internal temperatures for the Sydney field study (weekdays between March and June 2009)
Figure 17 | Internal temperatures for the Sydney study showing effects of AC to NV switch-over
average clo value for females (0.78) was significantly higher
than for males (0.62, p ¼ 0.002). Clo values were also
plotted against outdoor and indoor temperatures for any significant relationships. These data were binned into degrees
and thus analysed using weighted linear regressions. The
clo relationship with outdoor temperatures was nonsignificant ( p . 0.05); however, Figure 18 illustrates a significant negative clo relationship with indoor temperatures
( p ¼ 0.000). With R 2 ¼ 89.1%, this suggests that indoor
temperatures have a strong influence on the amount of clothing insulation worn by the building occupants. As indoor
temperatures increase, occupants will remove items of
clothing.
rated their level of comfort across a seven-point Likert
scale (ranging from cold (23) through neutral (0) to hot
(þ3)). Within AC mode, the average AMV was neutral
MM FIELD STUDY
On the basis of AC/NV mode at the time of the questionnaire, it was possible to compare responses during each
mode of operation, that is, AC and NV modes. Table 1 highlights some of the key study variables being investigated
throughout this study. The only significant difference
found was actual mean vote (AMV), wherein participants
Figure 18 | Clothing insulation relationship against indoor
temperature for Sydney
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Occupant comfort in mixed-mode spaces 305
Table 1 | Comfort data summaries for Sydney MM field study
Study
variable
AC mode
(n 5 81)
AMV
20.02
0.80
p ¼ 0.01
Acceptability
1.75
1.73
p . 0.05
Preference
2.16
1.73
p ¼ 0.02
Clo
0.73
0.68
p . 0.05
Productivity
20.5%
0%
p . 0.05
PMV
20.25
0.19
p . 0.05
Temperature
21.9
NV mode
(n 5 25)
24.0
Significance
p ¼ 0.03
(20.02), which is significantly cooler ( p ¼ 0.01) than the
average AMV during NV mode (0.80). This suggests that
most people found the building to be slightly warmer
during NV mode compared to AC mode, possibly due to
the increased indoor temperatures needed for the NV algorithm to start. Other variables did not achieve any significant
levels of difference. Thermal preference was significantly
different. People did not want the thermal environment
changed during AC mode (2.16), whereas during NV
mode occupants preferred to be cooler (1.73). Temperatures
were significantly different: this can be verified by Figure 17,
which demonstrates that when the building is in NV mode,
indoor temperatures will rise until the 258C cooling
set-point.
DISCUSSION
As shown in Figures 16 and 17, internal temperatures are
clipped at 258C as this is the peak temperature zones can
experience before the BMS switches into AC mode.
Before this transition, office spaces will gradually increase
in temperature due to increased solar loads, particularly in
the North zone, which experiences significantly warmer
temperatures than both the Central and South zones. Up till
this point, occupant comfort is said to be neutral, as
judging from the summary data present in Table 1.
However, what is not clear is what happens when the building activates the HVAC system. Currently, the building’s
MM ventilation algorithm, upon a temperature greater than
258C, has been sensed; the AC system will lower and maintain temperatures around 248C (+1.58C depending on concurrent outdoor weather). As can be illustrated in Figure 17,
there is a lag effect after an AC mode switch-over event. This
may be due to inconsistencies depending on the position of
the BMS sensors, but overall it takes 30min to reach
optimal temperature. Comfort votes taken before and after
these periods propose that occupants tend to feel warmer
leading up to AC mode operation as internal temperatures
are allowed to rise towards the 258C set-point.
Correspondingly, as highlighted in Table 1, the average
AMV when the building was in NV mode is slightly
warmer than neutral (1.17).
When the building switches into AC mode, internal temperatures are maintained at around 248C. In contrast, the
average AMV while AC mode was in operation was
neutral (0.00), which suggests that occupants preferred
these conditions (Rowe, 2004; Brager and Baker, 2008).
However, while PMV values during both these modes do
not suggest any significant differences (both 20.25 and
0.19 are within the limits of a neutral vote), more conclusive
evidence is needed to define occupant perceptions of the
thermal environment while the building switches between
AC and NV mode. A meaningful analysis would be to investigate any differences in clo values through both operation
modes. The Sydney field study relies heavily on the temporal
effects of thermal comfort, especially as this building is
capable of switching between modes various times during
a day. While the majority of the data presented here were collected in typical winter months, that is, Figure 16 shows that
outdoor temperatures rarely rose above 208C between April
and June, what can be expected during summer months
occurred during March in Figure 17, in which high
outdoor temperatures, often above 208C, will force the building into AC mode as internal temperatures during these
periods exceed the building’s NV limits.
Not only do indoor environments influence clothing
choices, but so too does the outdoor weather (Morgan and
de Dear, 2003; De Carli et al., 2007). For NV buildings,
occupants tend to change their clothing according to external
conditions as the building more closely matches the prevailing outdoor temperatures. However, as Figure 18 demonstrates, occupant clo values are only moderately related to
indoor temperatures and not outdoor conditions. Perhaps
there is a difference in these relationships when the building
is in AC mode and when it is in NV mode. As yet, there are
not enough conclusive data to suggest these correlations, but
this may be highlighted later on in the study.
CONCLUSION
The two case studies presented here adopt different
approaches to MM ventilation, with the NAB building offering MM ventilation in a break-out area adjacent to workspaces, and the Commerce building using MM ventilation
within workspaces. While these two approaches have
necessitated slightly different methodologies for evaluating
thermal comfort, it is clear that there are benefits in each of
these approaches over a traditional AC system. Of particular
interest are the points of change from one mode to another,
either spatially, as with the NAB building, or temporally,
as with the Commerce building. Comparison between the
different comfort conditions in each case study will form a
future component of this project, but for now what is
evident is that steady-state models are inadequate for
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306 Drake et al.
describing thermal comfort conditions in MM buildings,
and that new temporal and spatial models need to be
developed.
extend our appreciation to all participants who have given
their time to complete surveys and questionnaires.
NOTE
ACKNOWLEDGEMENTS
The project has been funded by an ARC (Australian
Research Council) Discovery Grant. We are grateful to
Kerry Russell and Macquarie University’s Office of Facilities Management (OFM) and to Angelina Andonovski and
John Hurren at NAB Docklands for their support and assistance in gathering data for these projects. We would like to
1 Mixed-mode refers to a hybrid approach to space
conditioning using a combination of NV from operable
windows, manually or automatically controlled, and
mechanical systems, that is, air distribution and
refrigeration equipment for cooling. The NAB is the
only one in Australia with this particular system (CBE,
2005).
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Appendix O: Indoor Air 2011 Conference Paper
Deuble, M. and de Dear, R. (2011) ‘Mixed-mode buildings: A double standard in comfort’,
Proceedings of Indoor Air 2011 Conference, Austin, TX, USA, 5-10 June 2011
286
Mixed-Mode Buildings: A Double Standard in Comfort
Max Deuble1,* and Richard de Dear2
1
2
*
Macquarie University, North Ryde NSW 2109 Australia
University of Sydney, Sydney NSW 2006, Australia
Corresponding email: max.deuble@mq.edu.au
SUMMARY
This paper investigates how mixed-mode (MM) ventilation affects occupant comfort by
presenting results from a longitudinal field study within an office building located in sub-tropical
Sydney, Australia. The building automatically switches into air-conditioned (AC) mode whenever
indoor temperatures exceed 25°C. Coincident indoor and outdoor climate measurements along
with 1359 subjective comfort questionnaires were collected. Thermal sensations during natural
ventilation were, on average, 2.1°C warmer than those predicted using Fanger’s PMV-PPD
(Fanger 1970). Differences in thermal perception were also apparent between these two modes.
Within AC mode, a +1 PMV environment elicited much ‘warmer-than-neutral’ thermal sensations
than the same environment within naturally-ventilated (NV) mode, suggesting thermal perceptions
were affected by the building’s mode of operation over and above the indoor climatic conditions.
These discrepancies emphasize the complexity of thermal perception and the inadequacy of using
PMV models to describe occupant comfort in MM buildings.
IMPLICATIONS
ASHRAE’s Standard 55 (2010) classifies MM buildings as AC buildings, and as such, limits the
operation of these buildings to the more restrictive PMV-PPD range of indoor thermal conditions.
EN 15251 (CEN 2007) however, allows the more flexible adaptive comfort standard to be applied
to buildings operating under NV mode. Results from this study favor EN15251’s application of
the adaptive comfort model instead of PMV-PPD to MM buildings when they are operating in NV
mode.
KEYWORDS
Thermal comfort, mixed-mode ventilation, comfort standards
INTRODUCTION
The basic concept of mixed-mode (MM) or ‘hybrid’ ventilation is to maintain satisfactory indoor
environments by alternating between and combining natural and mechanical systems. Utilizing a
naturally-ventilated (NV) or ‘free-running’ mode providing good air quality and thermal comfort,
these buildings will revert to mechanical systems for heating, ventilation and air-conditioning
(HVAC) whenever external conditions make the NV option untenable for occupants (Brager
2006). Previous studies document the disparities between steady-state and adaptive comfort
models in air-conditioned (AC) and NV buildings (Humphreys and Nicol 1998), highlighting the
inadequacy of static models for describing thermal comfort in ‘free-running’ buildings (Nicol and
Humphreys 2010). However, in a building that switches between AC and NV environments which
comfort model should be applied?
Comfort Standards
International comfort standards, e.g. ASHRAE Standard 55 (ASHRAE 2010) and EN 15251
(CEN 2007) provide guidelines produced from combinations of air temperature, thermal radiation,
humidity, air speed, metabolic activity and clothing to ensure thermal environmental conditions
that will be acceptable to 80% or more of the occupants within a space. Earlier versions cover
287
thermal comfort under steady-state conditions based on laboratory experiments; however more
recent revisions have utilised global field study databases, e.g. ASHRAE and SCATS (Nicol and
Humphreys 2010). Following detailed field studies from around the world, the 2004 edition of
ASHRAE’s Standard 55 (2010) included an Adaptive Comfort Standard (ACS) as an alternative
to the Predicted Mean Vote (PMV)-based method for free-running, i.e. NV buildings (de Dear and
Brager 2002; Nicol and Humphreys 2002). At the time of ASHRAE 55-2004 going to press,
insufficient studies undertaken in MM buildings meant they were excluded from the scope of the
ACS (de Dear and Brager 2002). ASHRAE clarifies that when mechanical cooling systems are
provided for the space, as is the case for many MM buildings, the ACS is not applicable. Thus, the
potential flexibility offered by the standard is not available to MM buildings, which may operate
in a passive, NV mode preferentially, equipped with only supplemental cooling and heating for
peak periods; or that control airflow using a building energy management system rather than
occupant intervention; or to spaces where operable elements are not connected to the outdoors,
must therefore resort to the more restrictive PMV-PPD method regardless of which mode they
happen to be operating under (Turner 2008).
METHODS
Sydney’s Climate
The Sydney metropolitan region, located on the eastern coast of Australia (34°S, 151°E), is often
characterised by a moderately temperate climate. Influenced from complex elevated topography
surrounding the region to the north, west and south, and due to close proximity to the Tasman Sea
to the east, Sydney avoids the high temperatures commonly associated with more inland regions
as well as the high humidity of tropical coastal areas (Bureau of Meteorology 1991). Given the
city’s very moderate yearly seasonal variations, Sydney’s climate is well suited to MM buildings.
Case Study Building
Macquarie University's (MQ) North Ryde campus is located within the Sydney metropolitan
region. Commissioned in 2006, the Commerce building (pictured below) is a 7-storey office
building occupied by academic and administrative staff from the Faculty of Business and
Economics. Figure 1 below depicts the north and south perimeter zones consist of MM cellular
offices with operable windows separated by a central open-plan office zone with full-time AC.
Automated high and low external louvres provide natural ventilation to each floor, with adjustable
internal grilles to control airflow, supplemented by user-operable windows with additional solar
shading features over the northern (sun-facing) windows (Photos 1 and 2). Indoor temperature and
outdoor weather sensors prompt the Building Management System (BMS) to switch into AC
mode whenever a temperature greater than 25°C is sensed within any zone. During AC mode,
internal temperatures are maintained at 24°C (±1.5°C) as defined in the building’s algorithm.
BMS switch-over to NV is conditional when external meteorological conditions and the indoor
thermal climate fall into an acceptable zone for the occupants. As shown in Photo 3, panels
located at the entrance of each corridor indicate the current operation of each zone.
Photo 1. MQ, Commerce
building (North/sunny facade)
Photo 2. MQ, Commerce
building (South facade)
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Photo 3. AC Control Panel
Figure 1. MQ, Commerce building, typical floor plan
Data Collection and Analysis
Dataloggers were randomly located throughout the building to record air temperature, globe
temperature and relative humidity at 5 minute intervals throughout the study (March 2009 to April
2010). Loggers were placed within 1 m of the occupants’ workstation to characterise the
immediate thermal environment experienced by the occupant under normal working conditions.
Outdoor weather observations were obtained from the University’s nearby automatic weather
station, with AC/NV mode operations and indoor temperatures collected from the University’s
Office of Facilities Management. During the study comfort questionnaires were used to record
occupant perceptions of thermal comfort within their workplace on a ‘right-here-right-now’ basis,
which included standardized clothing garment (clo) and metabolic activity checklists. Air velocity
measurements were taken using a handheld anemometer during each survey to enable the
calculation of various comfort indices, including PMV, PPD, ET* and SET* (ASHRAE 2010).
RESULTS
Throughout this study, a total of 1359 comfort questionnaires were administered during University
occupied office hours, with representative coverage of both genders (643 males and 716 females).
At the time of each survey, the operational mode of each respective occupant’s zone was noted,
i.e. AC or NV mode. The North and South perimeter offices switch between both AC and NV
modes and the Central core is provided with constant air conditioning. Therefore, the Central zone
has not been included in the following analyses because it does not operate under mixed-modes.
Thermal Environment
Operative temperatures calculated from the dataloggers reveal the range of temperatures
occupants experienced within the building. As shown in Figure 2 below, the building’s algorithm
works well to maintain indoor temperatures within a comfortable 5°C band (20°C to 25°C).
Deviations from these limits may be due to increased solar heat gains on the north façade. Figure
2 also illustrates the range of thermal sensations (labeled as Actual Mean Vote (AMV)) wherein
participants rated their level of comfort across a 7-point Likert Scale (ranging from Cold (-3)
through Neutral (0) to Hot (+3)).
Figure 2. Relationship between Actual Mean Vote (AMV) against indoor operative temperature
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Table 1 below summarizes the key comfort parameters. Two sample t-tests were performed to find
any significant differences between each mode. During both modes, average AMV remained
unchanged (0.4) however, average clo values reported within NV mode (0.50) were significantly
lower than those recorded during AC mode (0.57, p = 0.000) suggesting most people found the
building to be slightly warmer during periods of natural ventilation possibly due to the increased
indoor temperatures needed for the BMS algorithm to switch into AC mode. In contrast, PMV
values were significantly lower during NV mode (-0.32) compared to those in AC mode (-0.15, p
= 0.000). Air velocities during NV mode were slightly higher (0.10m/s) than those recorded
during AC mode (0.08m/s) likely due to occupants using their windows and increased air flow
from the external louvres. All other variables, such as operative temperature, relative humidity and
metabolic rate were not significantly different between the building’s two modes of operation.
Table 1. Summary of study variables for AC and NV modes
Variable
AC Mode (n = 804)
Operative temperature
23.2°C
Relative humidity
53%
Air velocity
0.08m/s
Clothing insulation
0.57
Metabolic rate
1.2
AMV
0.4
PMV
-0.15
NV Mode (n = 294)
23.1°C
52%
0.1m/s
0.5
1.2
0.4
-0.32
Significance
p > 0.05
p > 0.05
p = 0.008
p = 0.000
p > 0.05
p > 0.05
p = 0.000
Adaptive versus PMV-PPD Models
Separate statistical analyses were performed for each mode to investigate how comfort was
affected in a building that switches from AC to NV conditions and vice versa. The graph in Figure
3 presents weighted linear regressions of both observed thermal sensation votes (AMV) and those
predicted using Fanger’s PMV (1970). There are strong positive relationships for both AMV (R2 =
95%) and PMV (R2 = 97%) responses against the indoor operative temperature, both yielding
significant correlations (p = 0.000). AMV and PMV responses were then separated according to
mode to investigate any effects between each mode. The graphs in Figures 4 and 5 present the
results for AC mode and NV mode respectively. All correlations against the indoor operative
temperature were found to be significant (p < 0.05) showing strong positive relationships.
Figure 3. Observed and predicted comfort votes against indoor operative temperature
There is a clear difference among the relationships between thermal sensation and operative
temperature during NV mode. As illustrated in Figure 5, the PMV model fails to predict thermal
comfort whilst the building is in NV mode. Whilst eliciting strong correlations for AMV (R2 =
76%, p = 0.003) and PMV (R2 = 91%, p = 0.000) responses, the gentle gradient for observed
AMV values suggests occupants were able to adapt across a fairly broad range of indoor operative
temperatures but their thermal sensations seem to be permanently displaced into the ‘slightly
warm’ region.
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Figure 4. Observed and predicted comfort votes against indoor operative temperature for AC mode.
Figure 5. Observed and predicted comfort votes against indoor operative temperature for NV mode
DISCUSSIONS
The MM building operates as a passive NV building between the indoor operative temperatures of
20-25°C. Demonstrated in Figure 2, the BMS algorithm ensures comfortable conditions between
these extremes, with internal temperatures rarely rising above 25°C (some exceptions due to
excessive solar heat gains on the north). If a temperature above 25°C is sensed by the building’s
BMS sensors in any particular zone, air conditioning switches on for that zone, trimming indoor
temperatures back towards the 24°C set point (±0.5°C). This is reflected in Table 1, suggesting
occupants tend to feel slightly warmer leading up to an NV-AC mode switch-over event.
Figures 3 to 5 present the key findings of this research, showing fundamental differences between
the observed thermal sensation votes (AMV) and those predicted using Fanger’s PMV-PPD model
(PMV). Figure 3 highlights the different neutral temperatures calculated from each model. On
average, AMV responses were 2.1°C warmer than the PMV predictions. Both the observed and
predicted thermal sensation votes show very strong correlations with the indoor operative
temperature during AC mode (as shown in Figure 4, PMV: R 2 = 98%, p = 0.000; AMV: R2 =
97%, p = 0.000). Both models successfully describe occupant comfort within this mode. Figures
4 and 5 highlight differences in thermal perception were also apparent between these two modes.
During AC mode of operation, a +1 PMV (slightly warm) environment elicited significantly
warmer-than-neutral thermal sensations than the same thermal environmental conditions under
NV mode, suggesting thermal perceptions were affected by the building’s mode of operation overand-above any differences in actual thermal environmental conditions. It is likely that the ratio of
outdoor ventilation to air velocity would be greater under NV mode than in AC mode, so it is
possible that improved thermal comfort under NV mode resulted from cross-modal interactions
between air quality and thermal comfort. Whilst previous studies reflect building-by-building
comfort temperatures, such as de Dear and Brager (2002) and Nicol and Humphreys (2002),
Figures 4 and 5 clearly show the adaptive model is best suited to explain occupant comfort during
times of natural ventilation within the same building. When operating in AC mode, Fanger’s
PMV-PPD model shows good correlations with observed thermal sensations.
291
Current standards establish the ACS as an alternative to PMV-PPD for NV buildings. The ACS, as
defined in ASHRAE Standard 55 (2010) and EN 15251 (2007), was based on the works of de
Dear and Brager (2002) and Nicol and Humphreys (2002). Ongoing debates suggest the ACS
should be applied as an operating guideline for the NV mode of MM buildings. Figures 4 and 5
clearly show that interior temperatures can be allowed to float within the more energy-efficient
acceptability limits of the ACS. When temperatures reach the maximum limits then HVAC
systems can be turned on in a limited way to ensure temperatures stay within the ACS limits
(rather than switching to the narrow set points of a centrally-controlled AC building).
CONCLUSIONS
If a building is AC, then it typically doesn’t have operable windows. According to ASHRAE
Standard 55 (2010) if a building is NV, then it doesn’t have any mechanical cooling/heating
systems, but typically has operable windows. These black-and-white definitions express the
current view embodied in international comfort standards; however, the real world is not so
simple. Current standards misclassify MM buildings as AC and in doing so, fail to maximise the
energy saving potential of MM buildings. This paper provides evidence that MM buildings could
in fact be defined as NV, with operable windows and supplemental cooling/heating during peak
periods. Whilst this study represents one particular MM building at MQ, these findings provide an
insight as to how MM buildings should be categorised in future comfort standards. However,
more studies are needed to determine whether a new MM comfort standard should be established.
ACKNOWLEDGEMENTS
This project was funded in part by an Australian Research Council Discovery Grant (DP0880968).
We are enormously grateful to Kerry Russell and Macquarie University’s Office of Facilities
Management for assistance in gathering data. We would like to express our appreciation to all the
participants who gave their time to respond to our questionnaires.
REFERENCES
ASHRAE 2010. Thermal Environmental Conditions for Human Occupancy, ASHRAE Standard
55-2010, Atlanta, Georgia, American Society of Heating, Refrigerating and AirConditioning Engineers
Brager, G. 2006. Mixed-mode cooling, ASHRAE Journal, 48: 30-37
Bureau of Meteorology 1991. Sydney, New South Wales, Canberra, Australian Government
Publishing Service
CEN 2007. Indoor environmental input parameters for design and assessment of energy
performance of buildings: addressing indoor air quality, thermal environment, lighting and
acoustics, EN15251, Brussels, Comite Europeen de Normalisation
de Dear, R. J. and Brager, G. S. 2002. Thermal comfort in naturally ventilated buildings: revisions
to ASHRAE Standard 55, Energy and Buildings, 34: 549-561
Fanger, P. O. 1970. Thermal Comfort, Copenhagen, Danish Technical Press
Humphreys, M. A. and Nicol, F. 1998. Understanding the adaptive approach to thermal comfort,
ASHRAE Transactions, 104(1): 991-1004
Nicol, F. and Humphreys, M. A. 2002. Adaptive thermal comfort and sustainable thermal
standards for buildings, Energy and Buildings, 34: 563-572
Nicol, F. and Humphreys, M. A. 2010. Derivation of the adaptive equations for thermal comfort in
free-running buildings in European standard EN15251, Building and Environment, 45(1):
11-17
Turner, S. 2008. ASHRAEs Thermal Comfort Standard in America: Future steps away from
energy intensive design, Proceedings of the Proceedings of the 5th Windsor Conference Air-Conditioning and the Low Carbon Cooling Challenge, Cumberland Lodge, Windsor,
UK
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Appendix P: Is It Hot In Here Or Is It Just Me? Validating the
Post-Occupancy Evaluation Journal Submission Email
Status: Submitted May 2012; Deuble, M.P and de Dear, R.J. (2012) ‘Is it hot in here or is it
just me? Validating the post-occupancy evaluation’, Intelligent Buildings International
Journal Impact Factor: Not applicable – new journal (started in 2009)
293
MAX DEUBLE <max.deuble@students.mq.edu.au>
Intelligent Buildings International - Manuscript ID 12-IB046-RA.R1
1 message
sirinath.jamieson@live.co.uk <sirinath.jamieson@live.co.uk>
Mon, Feb 11, 2013 at 2:17
PM
To: max.deuble@students.mq.edu.au
10-Feb-2013
Dear Mr. Deuble:
The revised version of your manuscript entitled "Is It Hot In Here Or Is It Just Me? Validating the
Post-Occupancy Evaluation" has been successfully submitted online and is presently being given
full consideration for publication in Intelligent Buildings International .
Your manuscript ID is 12-IB046-RA.R1.
Please mention the above manuscript ID in all future correspondence or when calling the office
for questions. If there are any changes in your street address or e-mail address, please log in to
ScholarOne Manuscripts at http://mc.manuscriptcentral.com/inbi and edit your user information
as appropriate.
You can also view the status of your manuscript at any time by checking your Author Center after
logging in to http://mc.manuscriptcentral.com/inbi .
Thank you for submitting your manuscript to Intelligent Buildings International .
Sincerely,
Intelligent Buildings International Editorial Office
294
MAX DEUBLE <max.deuble@students.mq.edu.au>
Intelligent Buildings International - Manuscript ID 12-IB046-RA
1 message
d.j.clements-croome@reading.ac.uk <d.j.clementscroome@reading.ac.uk>
To: max.deuble@students.mq.edu.au
Fri, May 11, 2012 at 4:19
PM
11-May-2012
Dear Mr. Deuble:
Your manuscript entitled "Is It Hot In Here Or Is It Just Me? Validating the Post-Occupancy
Evaluation" has been successfully submitted online and is presently being given full consideration
for publication in the journal, Intelligent Buildings International .
Your manuscript ID is 12-IB046-RA.
The email address for questions regarding your submission is inbi@earthscan.c.o.uk. Please
make sure that you mention the above manuscript ID in all future correspondence. If there are
any changes in your street address or e-mail address, please log in to e-submission site at
http://mc.manuscriptcentral.com/inbi and edit your user information as appropriate.
You can also view the status of your manuscript at any time by checking your Author Center after
logging in to http://mc.manuscriptcentral.com/inbi .
Thank you for submitting your manuscript to Intelligent Buildings International .
Sincerely,
Intelligent Buildings International Editorial Office
295
MAX DEUBLE <max.deuble@students.mq.edu.au>
Fwd: Intelligent Buildings International Special POE Issue Call For
Papers
Ying Hua <yh294@cornell.edu>
To: MAX DEUBLE <max.deuble@students.mq.edu.au>
Cc: "Derek J. Croome" <d.j.clements-croome@reading.ac.uk>
Fri, May 11, 2012 at 1:12 PM
Dear Max:
I’d like to invite you to develop your abstract, titled “ Is It Hot In Here Or Is It Just Me? Validating
the Post-Occupancy Evaluation”, into a full paper.
Here are some important requirements for the full paper development and submission:
1. Go to the Journal website: http://www.tandfonline.com/tibi where you will find more details of
the journal and instructions for authors.
2. Length of full paper: 3000-5000 words.
3. The papers will need to be submitted through the Journal’s online submission system:
http://mc.manuscriptcentral.com/inbi.
4. Your full paper is due by July 31st, 2012.
5. All papers will undergo a double-blind refereeing process. When submitting your paper, please
declare 3 preferred reviewers (editors will decide whether to use these referees).
Feel free to contact me if you have questions.
Best
Ying
-Ying Hua, Ph.D.
Assistant Professor
Department of Design and Environmental Analysis
Co-Director
International Workplace Studies Program (IWSP)
Cornell University
Ithaca, NY 14853, USA
TEL: +1 607.254.6415
FAX: +1 607.255.0305
On Thu, Apr 26, 2012 at 4:48 AM, MAX DEUBLE
<max.deuble@students.mq.edu.au> wrote:
> Dear Ying Hua,
>
> I was wondering if its still possible to submit abstracts of papers for the upcoming special issue
of Intelligent Buildings International on Post-Occupancy Evaluation? I am aware the due date was
20th April 2012 however I only just received the call for papers email. I have provided a copy of
the abstract of my paper in this email just in case you allow it to be accepted. If my abstract can
be accepted as a paper for this special issue please let me know, because this paper is ready to
be submitted to another journal before knowledge of this special POE issue of Intelligent Buildings
International.
>
> Paper Title: Is It Hot In Here Or Is It Just Me? Validating the Post-Occupancy Evaluation
> Authors: Max Deuble and Richard de Dear
> Abstract: Historically, post-occupancy evaluation (POE) was developed to evaluate actual
building performance, providing feedback for architects and building managers to potentially
improve the quality and operation of the building. Whilst useful in gathering information based on
296
user satisfaction, POE studies have typically lacked contextual information, continued feedback
and physical measurements of the building’s indoor climate. They therefore sometimes overexaggerate poor building performance. POEs conducted in two academic office buildings: a
mixed-mode (MM) and a naturally-ventilated (NV) building located within a university in Sydney
Australia, suggest high levels of occupant dissatisfaction, especially in the MM building. In order
to test the validity of the POE results, parallel thermal comfort studies were conducted to
investigate the differences in occupant satisfaction and comfort perceptions between these two
questionnaires. Instrumental measurements of each building’s indoor environment reveal that
occupants tended to over-exaggerate their POE comfort responses. Analysis of thermal
satisfaction and acceptability in each building indicate that occupants of the NV building were
more tolerant of their thermal environment despite experiencing significantly warmer temperatures
than their MM counterparts. In discussing these results, along with participant comments and
anecdotal evidence from each building, this paper contends that POE does not accurately
evaluate building performance, suggesting occupants can and do use POE as a vehicle for
complaint about general workplace issues, unrelated to their building. In providing a critical review
of current POE methods, this paper aims to provide recommendations as to how they can be
improved, encouraging a more holistic approach to building performance evaluation
>
>
> Thanks,
> --Max
>
> ========================================================================
> Max Deuble
Phone: + 61 (0)2 9850 8396
> PhD student, Department of Environment and Geography
> Faculty of Science
> Macquarie University
> Sydney NSW 2109 AUSTRALIA
Email: max.deuble@students.mq.edu.au
> ========================================================================
297