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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

2. Energy and Carbon Emissions in Housing

verfasst von : Michael Gbolagade Oladokun, Clinton Ohis Aigbavboa

Erschienen in: Simulation-Based Analysis of Energy and Carbon Emissions in the Housing Sector

Verlag: Springer International Publishing

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Abstract

In this chapter, issues relating to energy and carbon emissions in housing are discussed. The chapter starts by discussing issues of energy consumption in housing. This is followed by the energy policy and emissions targets issues. Following on, the chapter discusses the trends in housing energy and carbon emissions research with specific focus on the theoretical framework underpinning energy consumption and carbon emissions in housing. This includes some sociotechnical variables influencing energy and carbon emissions in housing. The chapter also reviews the literature relating to the method of modelling energy and carbon emissions in housing. This entails issues pertaining to the epistemic modelling approaches which are the top-down and bottom-up modelling techniques as well as their benefits and limitations. Additionally, the chapter reviews some notable models for energy and carbon emissions in the UK housing sector. A critique of these modelling approaches concludes the chapter.

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Vorheriges Kapitel General Introduction
Nächstes Kapitel The Sociotechnical Systems of Energy and Carbon Emissions in Housing
Fußnoten
1
Some researchers use physical or engineering for building physics categorisation.
 
Literatur
1.
Abrahamse W, Steg L (2011) Factors related to household energy use and intention to reduce it: the role of psychological and socio-demographic variables. Hum Ecol Rev 18(1):30–40
2.
3.
Aigner D, Sorooshian C, Kerwin P (1984) Conditional demand analysis for estimating residential end-use load profiles. Energy J 5(4):81–97
4.
Ajzen I (1985) From intentions to actions: a theory of planned behaviour. In: Kuhl J, Beckman J (eds) Action control: from cognition to behaviour. Springer, Berlin, pp 11–39CrossRef
5.
Ajzen I (1991) The theory of planned behaviour. Organ Behav Hum Decisi Process 50(2):179–211CrossRef
6.
Anderson BR, Clark AJ (1985) BREDEM: BRE domestic energy model: background, philosophy and description. Building Research Establishment, Watford
7.
Aydinalp M, Ugursal VI, Fung AS (2002) Modelling of the appliance, lighting, and space cooling energy consumptions in the residential sector using neural networks. Appl Energy 72(2):87–110CrossRef
8.
Aydinalp M, Ugursal VI, Fung AS (2003) Modelling of residential energy consumption at the national level. Int J Energy Res 27(4):441–453CrossRef
9.
Aydinalp M, Ugursal VI, Fung AS (2004) Modelling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks. Appl Energy 79(2):159–178CrossRef
10.
Azar E, Menassa CC (2012) Agent-based modelling of occupants and their impact on energy use in commercial buildings. J Comput Civ Eng 26(4):506–518CrossRef
11.
Baba A, Mahjoubi L, Olomolaiye P, Colin B (2012) Insights of architects’ knowledge of the code for sustainable homes in relation to low carbon housing design and delivery in the UK. Struct Surv 30(5):443–449CrossRef
12.
Baker P (1991) A model of household gas and electricity expenditures for the UK: the IFS simulation program for energy demand (SPEND). Institute for Fiscal Studies, London
13.
Barr S, Gilg A (2006) Sustainable lifestyles: framing environmental action in and around the home. Geoforum 37:906–920CrossRef
14.
Bartiaux F, Gram-Hanssen K (2005) Socio-political factors influencing household electricity consumption: a comparison between Denmark and Belgium. In: ECEEE 2005 summer study—what works and who delivers, pp 1313–1325
15.
Bin S, Dowlatabadi H (2005) Consumer lifestyle approach to US energy use and the related CO2 emissions. Energy Policy 33:197–208CrossRef
16.
17.
Boardman B, Darby S, Killip G, Hinnels M, Jardine CN, Palmer J (2005) 40% house. University of Oxford’s Environmental Change Institute, Oxford, UK
18.
Boardman B (2007) Home truths: a low carbon strategy to reduce UK housing emissions by 80% by 2050. Environmental Change Institute, University of Oxford, UK
19.
Building Research Establishment (BRE) (2011) The government’s standard assessment procedure for energy rating of dwellings. 2009 edition incorporating RdSAP 2009, Watford, UK
20.
Capaso A, Grattieri W, Lamedica R, Prudenzi A (1994) A bottom-up approach to residential load modelling. IEEE Trans Power Syst 9(2):957–964CrossRef
21.
Caves DW, Herriges JA, Train KE, Windle RJ (1987) A Bayesian approach to vombining conditional demand and engineering models of electricity usage. Rev Econ Stat 69(3):438CrossRef
22.
Chartered Institution of Building Services Engineers (CIBSE) (2013) The limits of thermal comfort: avoiding overheating in European buildings (CIBSE TM52). CIBSE, London
23.
Clarke JA, Ghauri S, Johnstone CM, Kim JM, Tuohy PG (2008) The EDEM methodology for housing upgrade analysis, carbon and energy labelling and national policy development. In: Proceedings of the IBPSA Canada, eSim conference, Quebec City, Canada, pp 135–142
24.
25.
Department of Trade and Industry - DTI (2003). Energy white paper 2003 – our energy future: creating a low carbon, TSO (The Stationery Office), Norwich
26.
Douthitt RA (1989) An economic analysis of the demand for residential space heating fuel in Canada. Energy 14(4):187–197CrossRef
27.
Elforgani MS, Rahmat I (2010) An investigation of factors influencing design team attributes in green buildings. Am J Appl Sci 7(7):976–986CrossRef
28.
29.
Farahbakhsh H, Ugursal VI, Fung AS (1998) A residential end-use energy consumption model for Canada. Int J Energy Res 22(13):1133–1143CrossRef
30.
Firth SK, Lomas KJ, Wright AJ (2010) Targeting household energy efficiency measures using sensitivity analysis. Build Res Inf 38(1):24–41CrossRef
31.
FitzGerald J, Hore J, Kearney I (2002) A model for forecasting energy demand and greenhouse gas emissions in Ireland. Working paper no 146, The Economic and Social Research Institute, Dublin
32.
Fung AS (2003) Modelling of national and regional energy consumption and associated greenhouse gas emissions. Ph.D. thesis, Dalhousie University, Halifax
33.
Gatersleben B, Steg L, Vlek C (2002) Measurement and determinants of environmentally significant consumer behavior. Environ Behav 34:335–362CrossRef
34.
Gill ZM, Tierney MJ, Pegg IM, Allan N (2010) Low-energy dwellings: the contribution of behaviours to actual performance. Build Res Inf 38(5):491–508CrossRef
35.
Goldfarb DL, Huss R (1988) Building utility scenarios for an electric utility. Long Range Plan 21(2):78–85CrossRef
36.
Gram-Hanssen, K. (2014). New needs for better understanding of household’s energy consumption – behaviour, lifestyle and practices? Architectural Engineering and Design Management, 10(1-2), 91-107.CrossRef
37.
Greening LA (1995) Use of region, life-cycle and role variables in the short-run estimation of the demand for gasoline and miles travelled. Appl Econ 27(7):643–656CrossRef
38.
Gupta R (2009) Moving towards low-carbon buildings and cities: experiences from Oxford, UK. Int J Low-Carbon Technol 4:159–168CrossRef
39.
Haas R, Schipper L (1998) Residential energy demand in OECD-countries and the role of irreversible efficiency improvements. Energy Econ 20(4):421–442CrossRef
40.
Harris DJ (2012) A guide to energy management in buildings. Spon Press, London
41.
Hart M, De Dear R (2004) Weather sensitivity in household appliance energy end-use. Energy Build 36:161–174CrossRef
42.
Hinnells M, Boardman B, Layberry R, Darby S, Killip G (2007) The UK housing stock 2005 to 2050: assumptions used in scenarios and sensitivity analysis in UKDCM2. Environmental Change Institute, University of Oxford, UK
43.
Hirst E, Lin W, Cope J (1977) A residential energy use model sensitive to demographic, economic, and technological factors. Quart Rev Econ Financ 17(2):7–22
44.
Hitchcock G (1993) An integrated framework for energy use and behaviour in the domestic sector. Energy Build 20:151–157CrossRef
45.
Hoes P, Hensen JLM, Loomans MGLC, De Vries B, Bourgeois D (2009) User behavior in whole building simulation. Energy Build 41:295–302CrossRef
46.
47.
Hsiao C, Mountain C, Illman KH (1995) A Bayesian integration of end-use metering and conditional-demand analysis. J Bus Econ Stat 13(3):315
48.
Huang Y, Broderick J (2000) A bottom-up engineering estimate of the aggregate heating and cooling loads of the entire US building stock. Lawrence Berkeley National Laboratory, Report LBNL-46303
49.
Hughes M (2011) A guide to the Cambridge housing model. DECC, London
50.
Hughes M, Palmer J (2012) The Cambridge housing model. DECC, London
51.
International Energy Agency (IEA) (1998) Mapping the energy future: energy modelling and climate change policy. Paris
52.
International Energy Agency (IEA) (2012) World energy outlook 2012. IEA, Paris, France
53.
Intergovernmental Panel on Climate Change (IPCC) (2007) Climate change 2007: mitigation. In: Metz B, Davidson O, Bosch P, Dave R, Meyer L (eds) Contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change, Technical report, IPCC
54.
Ironmonger DS, Aitken CK, Erbas B (1995) Economies of scale in energy use in adult-only households. In: Stevens P (ed) The economics of energy, vol 1, pp 318–327. Elgar reference collection. International library of critical writings in economics, vol 119CrossRef
55.
Ironmonger DS, Aitken CK, Erbas B (1995) Economies of scale in energy use in adult-only households. Energy Econ 17(4):301–310CrossRef
56.
Isaacs N, Saville-Smith K, Camilleri M, Burrough L (2010) Energy in New Zealand houses: comfort, physics and consumption. Build Res Inf 38(5):470–480CrossRef
57.
Issa RRA, Flood I, Asmus M (2001) Development of a neural network to predict residential energy consumption. In: Proceedings of the sixth international conference on the application of artificial intelligence to civil & structural engineering computing, held in Eisenstadt, Austria, from 19 to 21 Sept 2001, pp 65–66
58.
Jaccard M, Baille A (1996) CO2 emission reduction costs in the residential sector: behavioural parameters in a bottom-up simulation model. Energy J 17(4):107–135CrossRef
59.
Jenkins D (2008) Energy modelling in traditional Scottish houses (EMITSH): Heriot-Watt University analysis of potential CO2 savings of building variants. Tarbase Group Report for Historical Scotland—Technical paper, Nov 2008
60.
Jennings M, Hirst N, Gambhir A (2011) Reduction of carbon dioxide emissions in the global building sector to 2050. Report GR3. Grantham Institute for Climate Change, Imperial College London
61.
Johnston D (2003) A physically based energy and carbon dioxide emission model of the UK housing stock. Ph.D. thesis, Leeds Metropolitan University, UK
62.
Kadian R, Dahiya RP, Garg HP (2007) Energy-related emissions and mitigation opportunities from the household sector in Delhi. Energy Policy 35(12):6195–6211CrossRef
63.
Kashyap M, Khalfan M, Zainul-Abidin N (2003) A proposal for achieving sustainability in construction projects through concurrent engineering. In: Proceedings of the RICS foundation construction and building research conference. School of Engineering and the Built Environment, University of Wolverhampton, 1–2 Sept 2003
64.
Kavgic M, Mavrogianni A, Mumovic D, Summerfield A, Stevanovic Z, Djurovic-Petrovic M (2010) A review of bottom-up building stock models for energy consumption in the residential sector. Build Environ 45:1683–1697CrossRef
65.
Kavousian A, Rajagopal R, Fischer M (2012) A method to analyse large data sets of residential electricity consumption to inform data-driven energy efficiency. Centre for integrated facility engineering (CIFE) working paper #WP130, Standford University, June
66.
67.
Kelly S (2011) Do homes that are more energy efficient consume less energy? A structural equation model for England’s residential sector. EPRG working paper, electricity policy research group, University of Cambridge
68.
Ko J, Fenner R (2008) Adoption of energy efficiency innovations in new UK housing. In: Proceedings of the institution of civil engineers energy, Nov 2008, pp 151–163CrossRef
69.
Kohler N, Hassler U (2002) The building stock as a research project. Build Res Inf 30(4):226–236CrossRef
70.
Larsen BM, Nesbakken R (2004) Household electricity end-use consumption: results from econometric and engineering models. Energy Econ 26(2):179–200CrossRef
71.
Lee T, Yao R (2013) Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis. Energy Policy 52:363–372CrossRef
72.
Levine M, Ürge-Vorsatz D, Blok K, Geng L, Harvey D, Lang S, Levermore G, Mongameli Mehlwana A, Mirasgedis S, Novikova A, Rilling J, Yoshino H (2007) Residential and commercial buildings. In: Metz B, Davidson OR, Bosch PR, Dave R, Meyer LA (eds) Climate change 2007: mitigation. Contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK
73.
Lins M, DaSilva A, Rosa L (2002) Regional variations in energy consumption of appliances: conditional demand analysis applied to Brazilian households. Ann Oper Res 117(1–4):235–246CrossRef
74.
Lutzenhiser L (1992) A cultural model of household energy consumption. Energy 17(1):47–60CrossRef
75.
Lutzenhiser L, Hackett B (1993) Social stratification and environmental degradation: understanding household CO2 production. Soc Probl 40(1):50–73CrossRef
76.
Mcmanus A, Gaterell M, Coates L (2010) The potential of the code for sustainable homes to deliver genuine ‘sustainable energy’ in the UK social housing sector. Energy Policy 38(4):2013–2019CrossRef
77.
Mhalas A, Kassem M, Crosbie T, Dawood N (2013) A visual energy performance assessment and decision support tool for dwellings. Visual Eng 1:7CrossRef
78.
Mihalakakou G, Santamouris M, Tsangrassoulis A (2002) On the energy consumption in residential buildings. Energy Build 34(7):727–736CrossRef
79.
Massachusetts Institute of Technology (MIT) (1997) Energy technology availability: review of longer term scenarios for development and deployment of climate-friendly technologies. Massachusetts Institute of Technology Energy Laboratory, Cambridge, MA, USA
80.
Mohmed A, Ugursal VI, Beausoleil-Morrison I. (2008). A new methodology to predict the GHG emission reductions due to electricity savings in the residential sector. In: Proceedings of the third Canadian solar buildings conference, Fredericton, 20th–22nd August.
81.
Moll HC, Noorman KJ, Kok R, Engström R, Throne-Holst H, Clark C (2005) Pursuing more sustainable consumption by analyzing household metabolism in European countries and cities. J Ind Ecol 9:259–275CrossRef
82.
Motawa IA, Banfill PF (2010) Energy-efficient practices in housing—a system dynamics approach. In: Proceedings of 18th CIB world building congress: TG62—built environment complexity, Salford, UK, May, pp 44–56
83.
Natarajan S, Levermore GJ (2007) Domestic futures–which way to a low carbon housing stock? Energy Policy 35(11):5728–5736CrossRef
84.
Natarajan S, Levermore GJ (2007) Predicting future UK housing stock and carbon emissions. Energy Policy 35(11):5719–5727CrossRef
85.
Natarajan S, Padget J, Elliott L (2011) Modelling UK domestic energy and carbon emissions: an agent-based approach. Energy Build 43:2602–2612CrossRef
86.
87.
Palmer J, Cooper I (2012) United Kingdom housing energy fact file. DECC, London
88.
Parekh A (2005) Development of archetypes of building characteristics libraries for simplified energy use evaluation of houses. In: Proceedings of the ninth international IBPSA conference, Montreal, Canada, pp 921–8
89.
Parti M, Parti C (1980) The total and appliance-specific conditional demand for electricity in the household sector. Bell J Econ 11(1):309–321CrossRef
90.
Petersdorff C, Boermans T, Harnisch J (2006) Mitigation of CO2 emissions from the EU-15 building stock. Environ Sci Pollut Res 13(5):350–358CrossRef
91.
Poortinga W, Steg L, Vlek C (2004) Values, environmental concern and environmental behavior: a study into household energy use. Environ Behav 36:70–93CrossRef
92.
Ruffell RJ (1977) An econometric analysis of the household demand for electricity in Great Britain. Scottish Academic Press, Scotland
93.
Saidur R, Masjuki HH, Jamaluddin MY (2007) An application of energy and exergy analysis in residential sector of Malaysia. Energy Policy 35(2):1050–1063CrossRef
94.
95.
Shipworth D (2005) Synergies and conflicts on the landscape of domestic energy consumption: beyond metaphor. Paper presented at the ECEEE summer study, Mandelieu La Napoule, France, pp 1381–1391
96.
Shipworth D (2006) Qualitative modelling of sustainable energy scenarios: an extension of the Bon qualitative input–output model. Constr Manage Econ 24(7):695–703CrossRef
97.
Shorrock LD, Dunster JE (1997) The physically-based model BREHOMES and its use in deriving scenarios for the energy use and carbon dioxide emissions of the UK housing stock. Energy Policy 25(12):1027–1037CrossRef
98.
Shorrock LD, Henderson J, Utley JI (2005) Reducing carbon emissions from the UK housing stock. BRE report BR480. BRE Press, Watford
99.
Stokes M, Rylatt M, Lomas KJ (2004) A simple model of domestic lighting demand. Energy Build 36:103–116CrossRef
100.
Stevenson F, Leaman A (2010) Evaluating housing performance in relation to human behaviour: new challenges. Build Res Inf 38(5):437–441CrossRef
101.
Stevenson F, Rijal HB (2010) Developing occupancy feedback from a prototype to improve housing production. Build Res Inf 38(5):549–563CrossRef
102.
Strachan N, Kannan R (2008) Hybrid modelling of long-term carbon reduction scenarios for the UK. Energy Econ 30:2947–2963CrossRef
103.
Summerfield AJ, Lowe RJ, Oreszczyn T (2010) Two models for benchmarking UK domestic delivered energy. Build Res Inf 38(1):12–24CrossRef
104.
Swan LG, Ugursal VI (2009) Modelling of end-use energy consumption in the residential sector: a review of modelling techniques. Renew Sustain Energy Rev 13:1819–1835CrossRef
105.
Swan L, Ugursal VI, Beausoleil-Morrison I (2008) A new hybrid end-use energy and emissions model of the Canadian housing stock. In: Proceedings of the COBEE conference, Dalian, China
106.
Terry N (2011) Energy and carbon emissions: the way we live today. UIT, Cambridge
107.
Tonn BE, White DL (1988) Residential electricity use, wood use, and indoor temperature: an econometric model. Energy Syst Policy 12(3):151–165
108.
Tuladhar SD, Yuan M, Bernstein P, Montgomery WD, Smith A (2009) A top–down bottom–up modeling approach to climate change policy analysis. Energy Econ 31:S223–S234CrossRef
109.
Tweed C, Dixon D, Hinton E, Bickerstaff K (2014) Thermal comfort practices in the home and their impact on energy consumption. Arch Eng Des Manage 10(1–2):1–24
110.
United Nations Environment Programme (UNEP) (2011) Buildings: investing in energy and resource efficiency. United Nations Environment Programme
111.
Urge-Vorsatz D, Eyre N, Graham P, Harvey D, Hertwich E, Jiang Y, Kornevall C, Majumdar M, McMahon JE, Mirasgedis S, Murakami S, Novikova A (2012) Chapter 10—Energy end-use: building. Global energy assessment—toward a sustainable future. Cambridge University Press, The International Institute for Applied Systems Analysis, Cambridge, UK, pp 649–760
112.
Van Raaij WF, Verhallen TM (1983) A behavioral model of residential energy use. J Econ Psychol 3(1):39–63CrossRef
113.
Wheelock J, Oughton E (1994) The household as a focus for comparative research. Centre for Rural Economy, Department of Agricultural Economics and Food Marketing, University of Newcastle-upon-Tyne, Newcastle
114.
Williamson T, Soebarto V, Radford A (2010) Comfort and energy use in five Australian award-winning houses: regulated, measured and perceived. Build Res Inf 38(5):509–529CrossRef
115.
Wilson D, Swisher J (1993) Exploring the gap: top-down versus bottom-up analyses of the cost of mitigating global warming. Energy Policy 21(3):249–263CrossRef
116.
Yang J, Rivard H, Zmeureanu R (2005) Building energy prediction with adaptive artificial neural networks. In: Proceedings of the IBPSA ninth international conference, Montreal, Canada, 1401–1408
117.
Yu Z, Fung BCM, Haghighat F, Yoshino H, Morofsky E (2011) A systematic procedure to study the influence of occupant behaviour on building energy consumption. Energy Build 43(6):1409–1417CrossRef
118.
Yun GY, Steemers K (2011) Behavioural, physical and socio-economic factors in household cooling energy consumption. Appl Energy 88:2191–2200CrossRef
Metadaten
Titel
Energy and Carbon Emissions in Housing
verfasst von
Michael Gbolagade Oladokun
Clinton Ohis Aigbavboa
Copyright-Jahr
2018
Buch
Simulation-Based Analysis of Energy and Carbon Emissions in the Housing Sector

Print ISBN: 978-3-319-75345-4

Electronic ISBN: 978-3-319-75346-1

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-75346-1_2