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Occupant Behavior and Building Performance

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Design and Management of Sustainable Built Environments

Abstract

People and building performance are intimately linked. This chapter focuses on the issue of occupant behavior; principally, its impact, and the influence of building performance on occupants. The early sections looked at how energy is consumed in buildings and identifies the range of occupant-interactive opportunity. The issue of post occupancy evaluation (POE) is covered, exposing the concept of the energy performance gap and why discrepancies occur. The emphasis then shifts toward building performance, particularly indoor environment, how it impinges on work productivity, and how it is measured. Later sections discuss occupant adaptation in achieving thermal comfort, in addition to, the role of energy management systems, smart-sensor networks, and data mining with occupant behavior as the backdrop. Finally, the chapter closes by looking at how occupants fit within the framework of building performance assessment. Learning outcomes: on successful completion of this chapter, readers will: (1) Appreciate the need to better understand how occupants behave in buildings due to their magnitude of impact on energy use; (2) Understand the range of occupant behavior including: interactive opportunity; (3) Understand adaptation in achieving indoor comfort and response to indoor environment and work productivity; (4) Gain insight into the role of POE and its importance in developing improvement cycles; (5) Grasp how technology and occupant behavior can be integrated to realize energy savings and increase the quality of indoor environments; and (6) Know about building performance assessment.

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References

  • Alwaer H, Clements-Croome D (2010) Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings. Build Environ 45:799–807

    Google Scholar 

  • ASHRAE (2007) ANSI/ASHRAE Standard 105–2007, standard methods of measuring, expressing and comparing building energy performance. American Society of Heating, Refrigerating and Air-conditioning Engineers, Inc., Atlanta

    Google Scholar 

  • Auliciems A (1981) Toward a psychophysiological model of thermal perception. Int J Biometeorol 25:109–122

    Article  Google Scholar 

  • Bahaj A, James P (2007) Urban energy generation: the added value of photovoltaics in social housing. Renew Sustain Energy Rev 11:2121–2136

    Article  Google Scholar 

  • Baker N, Standeven M (1994) Comfort criteria for passively cooled buildings a pascool task. Renew Energy 5:977–984

    Article  Google Scholar 

  • Baker N, Steemers K (2000) Energy and environment in architecture: a technical design guide, E & FN Spon, London

    Google Scholar 

  • Bordass B, Cohen R, Standeven M, Leaman A (2001) Assessing building performance in use 3: energy performance of probe buildings. Build Res Inf 29:114–128

    Article  Google Scholar 

  • Bordass B, Cohen R, Field J (2004) Energy performance of non-domestic buildings—closing the credibility gap. In: International conference on improving energy efficiency in commercial buildings. Frankfurt, Germany

    Google Scholar 

  • Brager GS, de Dear RJ (1998) Thermal adaptation in the built environment: a literature review. Energy Build 27:83–96

    Article  Google Scholar 

  • BRE (2011) The 40 percent symposium, building research establishment. RIBA, London

    Google Scholar 

  • Carbon Trust (2011) Closing the gap—lessons learned on realising the potential of low carbon building design. CTG047, London

    Google Scholar 

  • Choi H-H, Loftness V, Aziz A (2012) Post-occupancy evaluation of 20 office buildings as basis for future IEQ standards and guidelines. Energy Build 46:167–175

    Article  Google Scholar 

  • CIBSE (2006) CIBSE TM22, energy assessment and reporting method. The Chartered Institution of Building Services Engineers, London

    Google Scholar 

  • Clements-Croome D (2000) Creating the productive workplace. Taylor & Francis Group Ltd., Oxford

    Google Scholar 

  • Clements-Croome D (2004) Intelligent buildings. Thomas Telford Books, London

    Google Scholar 

  • Clements-Croome DJ, Li B (1995) Impact of indoor environment on productivity. Workplace comfort forum. RIBA, London

    Google Scholar 

  • Cohen J, Cohen P (1983) Applied multiple regression, correlation analysis for the behavioral sciences, 2nd edn. Lawrence Erlbaum Associates, Publishers, Hillsdale

    Google Scholar 

  • Darby S (2006) The effectiveness of feedback on energy consumption: a review for DEFRA of the literature on metering, billing and direct displays. Environmental Change Institute, Oxford

    Google Scholar 

  • DECC (2006) The carbon emissions reduction target (CERT). HM Government Department of Energy and Climate Change, HMSO, London

    Google Scholar 

  • de Dear RJ, Brager GS (1998) Developing an adaptive model of thermal comfort and preference. ASHRAE Trans 104:145–167

    Google Scholar 

  • Demanuele C, Tweddell T, Davies M (2010) Bridging the gap between predicted and actual energy performance in schools. In: World renewable energy congress XI, Abu Dhabi, 25–30 Sept 2010

    Google Scholar 

  • Dempster AP (1968) Upper and lower probabilities generated by a random closed interval. Ann Math Stat 39:145–167

    Article  Google Scholar 

  • Farshchi MA, Fisher N (2000) Emotion and the environment: the forgotten dimension. In: Clements-Croome D (ed) Creating the productive workplace. E & FN Spon, London

    Google Scholar 

  • Fayyad UM, Piatetsky-Shapiro G, Smyth P (1996) From Data Mining to Knowledge discovery. Advances in knowledge discovery and Data Mining. AAAI/MIT Press, Menlo Park

    Google Scholar 

  • Fanger PO (1970) Thermal comfort. Danish Technical Press, Copenhagen

    Google Scholar 

  • Gagge AP, Stolwijk JAJ, Hardy JD (1967) Comfort and thermal sensation and associated physiological responses at various ambient temperatures. Environ Res 1:1–20

    Google Scholar 

  • Haldi F, Robinson D (2009) Interactions with window openings by office occupants. Build Environ 44(12):2378–2395

    Article  Google Scholar 

  • Heerwagen JH (1998) Productivity and well-being: what are the links? In: Proceedings of the American institute of architects conference on highly effective facilities, Cincinnati 12–14 March 1998

    Google Scholar 

  • Humphreys MA (1978) Outdoor temperatures and comfort indoors. Build Res Pract 6(2):92–105

    Google Scholar 

  • Ilgen DR, Schneider J (1991) In: Cooper C, Robertson A (eds), International review of industrial and organisational psychology, vol 6. Wiley, London Chapter 3, 71–108

    Google Scholar 

  • Li B (1998) Assessing the influence of indoor environment on self-reported productivity in offices. Ph.D. thesis, The University of Reading, Reading

    Google Scholar 

  • Lim D, Yao R (2012) A combined engineering and statistical model of UK domestic appliance loads. In: proceedings Western load research association Spring conference 2012, Boise, Idaho, 7–9 March 2012

    Google Scholar 

  • Liu J, Yao R, Wang J, Li B (2012a) Occupants’ behavioral adaptation in workplaces with non-central heating and cooling systems. Appl Therm Eng 35:40–54. doi:10.1016/j.applthermaleng.2011.09.037

    Article  Google Scholar 

  • Liu J, Yao R, McCloy R (2012b) A method to weight three categories of adaptive thermal comfort. Energy Build 47:312–320

    Article  Google Scholar 

  • Mansouri I, Newborough M, Probert D (1996) Energy-consumption in UK households: impact of domestic electrical appliances. Appl Energy 54(3):211–285

    Article  Google Scholar 

  • Menezes AC, Cripps A, Bouchlaghem D, Buswell R (2011) Predicted vs. actual energy performance of non-domestic buildings: using post-occupancy evaluation data to reduce the performance gap. Appl Energy. doi:10.1016/j.apenergy.2011.11.075

    Google Scholar 

  • Nishiara N, Yamamoto Y, Tanabe S (2002) Effect of thermal environment on productivity evaluated by task peformances, fatigue feelings and cerebral blood oxygenation changes, In: Proceedings: 9th international conference in indoor air quality and climate, vol 1. Monterey, 30 June–5 July 2002, pp 828–833

    Google Scholar 

  • Ouyang J, Hokao K (2009) Energy-saving potential by improving occupants’ behavior in urban residential sector in Hangzhou City, China. Energy Build 41:711–720

    Article  Google Scholar 

  • Probe (2011) Archive held by the usable buildings trust (UBT). http://www.usablebuildings.co.uk/Pages/UBProbePublications1.html. Accessed 17 Feb 2012

  • Saaty TL (1972) The analytic hierarchy process. McGraw-Hill, New York

    Google Scholar 

  • Seligman C, Darley JM, Becker LJ (1978) Behavioral approaches to residential energy conservation. Energy Build 1:325–337

    Article  Google Scholar 

  • Shafer G (1976) A mathematical theory of evidence. Princeton University Press, Princeton

    MATH  Google Scholar 

  • Shiomi K, Hirose S (2000) Fatigue and drowsiness predictor for pilots and air traffic controllers. In: Proceedings 45th annual ACTA conference, pp 1–4

    Google Scholar 

  • Soclow R (1978) Saving energy in the home: Princeton’s experiments at Twin Rivers. Ballinger Publishing Company, Cambridge

    Google Scholar 

  • Van Dam SS, Bakker CA, van Hal JDM, Keyson DV (2010) Knowledge and Learning for sustainable innovation. In: ERSCP-EMSU conference, Delft, The Netherlands, 25–29 Oct 2010

    Google Scholar 

  • Van Raaij WF, Verhallen TMM (1982) A behavioral model of residential energy use. J Econ Psychol 3:39–63

    Article  Google Scholar 

  • VDI (2007) VDI 3807, Part 1, characteristic values of energy and water consumption values in buildings—fundamentals. The Association of German Engineers, Dussseldorf (Verein Deutscher Ingenieure e.V)

    Google Scholar 

  • Wong NH, Jan WLS (2003) Total building performance evaluation of academic institution in Singapore. Build Environ 38:161–176

    Article  Google Scholar 

  • Wood G, Newborough M (2003) Dynamic energy-consumption indicators for domestic appliances: environment, behavior and design. Energy Build 35:821–841

    Article  Google Scholar 

  • World Business Council for Sustainable Development (2008) Global trends in energy efficient buildings. http://www.wbcsd.org. Accessed 13 Feb 2012

  • Wu S, Clements-Croome D (2007) Understanding the indoor environment through mining sensory data—a case study. Energy Build 39:1183–1191

    Article  Google Scholar 

  • Wyon DP (1996) Indoor environmental effects on productivity. In: Proceedings of IAQ’96, ASHRAE, Atlanta

    Google Scholar 

  • Yao R, Steemers K (2005) A method of formulating energy load profile for domestic buildings in the UK. Energy Build 37:663–671

    Article  Google Scholar 

  • Yao R, Li B, Liu J (2009) A theoretical adaptive model of thermal comfort—adaptive predicted mean vote (aPMV). Build Environ 44:2089–2096

    Article  Google Scholar 

  • Yao R, Zheng J (2010) A model of intelligent building energy management for the indoor environment. Intell Build Int 2:72–80

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Urban Construction and Environmental Engineering, Chongqing University, Campus B, Shapingba, Chongqing, China

    Baizhan Li

  2. School of Construction Management and Engineering, The University of Reading, Whiteknights, PO Box 219, Reading, RG6 6AW, UK

    David Lim

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  1. Baizhan Li
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  2. David Lim
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Correspondence to Baizhan Li .

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  1. The Crescent 9, Reading, RG6 7NW, United Kingdom

    Runming Yao

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Li, B., Lim, D. (2013). Occupant Behavior and Building Performance. In: Yao, R. (eds) Design and Management of Sustainable Built Environments. Springer, London. https://doi.org/10.1007/978-1-4471-4781-7_14

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  • DOI: https://doi.org/10.1007/978-1-4471-4781-7_14

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4780-0

  • Online ISBN: 978-1-4471-4781-7

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