Understanding high-emitting households in the UK through a cluster analysis
Xinfang WANG1(), Ming MENG2
1. School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK 2. Department of Economics and Management, North China Electric Power University, Baoding 071003, China
Anthropogenic climate change is a global problem that affects every country and each individual. It is largely caused by human beings emitting greenhouse gases into the atmosphere. In general, a small percentage of the population is responsible for a large amount of emissions. This paper focuses on high emitters and their CO2 emissions from energy use in UK homes. It applies a cluster approach, aiming to identify whether the high emitters comprise clusters where households in each cluster share similar characteristics but are different from the others. The data are mainly based on the Living Cost and Food survey in the UK. The results show that after equivalising both household emissions and income, the high emitters can be clustered into six groups which share similar characteristics within each group, but are different from the others in terms of income, age, household composition, category and size of the dwelling, and tenure type. The clustering results indicate that various combinations of socioeconomic factors, such as low-income single female living in an at least six-room property, or high-income retired couple owning a large detached house, could all lead to high CO2 emissions from energy use at home. Policymakers should target each high-emitter cluster differently to reduce CO2 emissions from energy consumption at home more effectively.
王欣芳, 明孟. 通过聚类分析了解英国的高碳排放家庭[J]. Frontiers in Energy, 2019, 13(4): 612-625.
Xinfang WANG, Ming MENG. Understanding high-emitting households in the UK through a cluster analysis. Front. Energy, 2019, 13(4): 612-625.
28% two adults, no children; 46% two adults with children; 23% at least three adults
23% one adult with children; 39% two adults with children; 12% two adults, no children
34% single female; 30% two adults, no children; 25% at least three adults
18% two adults, no children; 51% two adults with children; 21% at least three adults
56% two adults, no children; 38% at least three adults
Category of dwelling
95% detached
99% detached
61% semi-detached or terraced; 12% flat
38% detached; 57% semi-detached or terraced
91% semi-detached or terraced
81% semi-detached or terraced
Tenure type
98% own outright
91% own with a mortgage
64% rent; 37%own with a mortgage
64% own outright; 30% own with a mortgage
33% rent; 63% own with a mortgage
92% own outright
Second dwelling in the UK
–
–
–
–
–
-
Sex of HRP
91% male
99% male
96% female
100% female
100% male
100% male
Mean equivalised disposable household Income/(£•week–1)
703
758
291
448
396
391
Mean number of cars and vans
2
2
1
2
1
1
Mean number of rooms
8
9
6
7
6
7
Age of the oldest person
73% over 60
82% under 59
96% under 59
57% over 60; 29% between 50 and 59
87% under 59
71% over 60
Government office region
–
–
–
–
–
–
Mean equivalised household CO2 emissions from energy use at home (tonnes CO2/year)
14.45
11.77
9.97
12.88
10.23
11.54
Tab.7
ECO
Energy company obligation
FIT
Feed-in Tariffs
GORs
Government office regions
GHG
Greenhouse gas
HRP
Household reference person
LCF
Living cost and food
LESA
Landlord’s energy saving allowance
LIHC
Low income high cost
OECD
Organisation for Economic Co-operation and Development
ONS
Office for National Statistics
UNFCCC
United Nations Framework Convention on Climate Change
1
Intergovernmental Panel on Climate Change (IPCC). AR5 climate change 2014: impacts, adaptation and vulnerability. 2017–01–09, available at IPCC website
2
United Nations. Paris Agreement. 2017–04–28, available at unfccc website
Her Majesty’s Stationary Office (HMSO). The Carbon Budget Order 2009. Statutory instruments Number 1259. London: HMSO, 2009
5
Her Majesty’s Stationary Office (HMSO). The Carbon Budget Order 2011. Statutory instruments Number 1603. London: HMSO, 2011
6
Her Majesty’s Stationary Office (HMSO). The Carbon Budget Order 2016. Statutory instruments Number 785. London: HMSO, 2016
7
K Anderson. Talks in the city of light generate more heat. Nature, 2015, 528(7583): 437 doi:10.1038/528437a
8
S Pye, F G N Li, J Price, B Fais. Achieving net-zero emissions through the reframing of UK national targets in the post-Paris Agreement era. Nature Energy, 2017, 2(3): 17024 https://doi.org/10.1038/nenergy.2017.24
9
Department for Business, Energy and Industrial Strategy (BEIS). Final UK greenhouse gas emissions national statistics: final estimates of UK greenhouse gas emissions from 1990. London: BEIS, 2018
10
Department for Business, Energy and Industrial Strategy (BEIS). Energy consumption in the UK. London: BEIS, 2016
11
E Ares. Feed-in Tariffs. London: House of Commons. 2012
12
Her Majesty’s Stationary Office (HMSO). The Electricity and Gas (Energy Companies Obligation) (Amendment) Order 2014. Statutory instruments Number 1131. London: HMSO, 2014
13
Department of Energy and Climate Change (DECC). The Green Deal: A Summary of the Government’s Proposals. URN: 10D/996. London: DECC, 2010
14
C Foulds, J Powell. Using the Homes Energy Efficiency Database as a research resource for residential insulation improvements. Energy Policy, 2014, 69: 57–72 https://doi.org/10.1016/j.enpol.2014.01.015
15
M Dowson, A Poole, D Harrison, G Susman. Domestic UK retrofit challenge: barriers, incentives and current performance leading into the Green Deal. Energy Policy, 2012, 50: 294–305 https://doi.org/10.1016/j.enpol.2012.07.019
16
P Balcombe, D Rigby, A Azapagic. Investigating the importance of motivations and barriers related to micro-generation uptake in the UK. Applied Energy, 2014, 130: 403–418 https://doi.org/10.1016/j.apenergy.2014.05.047
17
A Druckman, T Jackson. Household energy consumption in the UK: a highly geographically and socio-economically disaggregated model. Energy Policy, 2008, 36(8): 3177–3192 https://doi.org/10.1016/j.enpol.2008.03.021
18
A Druckman, T Jackson. The carbon footprint of UK households 1990–2004: a socio-economically disaggregated, quasi-multi-regional input-output model. Ecological Economics, 2009, 68(7): 2066–2077 https://doi.org/10.1016/j.ecolecon.2009.01.013
19
G Baiocchi, J Minx, L Hubacek. The impact of social factors and consumer behaviour on carbon dioxide emissions in the United Kingdom: a regression based on input-output and geo-demographic consumer segmentation data. Journal of Industrial Ecology, 2010, 14: 50–72 https://doi.org/10.1111/j.1530-9290.2009.00216.x
20
M Büchs, S Schnepf. Who emits most? Association between socio-economic factors and UK households’ home energy, transport, indirect and total CO2 emissions. Ecological Economics, 2013, 90: 114–123 https://doi.org/10.1016/j.ecolecon.2013.03.007
21
M Lenzen, S A Murray. The ecological footprint–issues and trends. ISA Research Paper 01–03. Sydney: University of Sydney, 2003
22
T Kenny, N F Gray. A preliminary survey of household and personal carbon dioxide emissions in Ireland. Environment International, 2009, 35(2): 259–272 https://doi.org/10.1016/j.envint.2008.06.008
23
C M Jones, D M Kammen. Quantifying carbon footprint reduction opportunities for US households and communities. Environmental Science & Technology, 2011, 45(9): 4088–4095 https://doi.org/10.1021/es102221h
24
K Vringer, K Blok. The direct and indirect energy requirements of households in the Netherlands. Energy Policy, 1995, 23(10): 893–910 https://doi.org/10.1016/0301-4215(95)00072-Q
25
S Bhattacharjee, G Reichard. Socio-economic factors affecting individual household energy consumption: a systematic review. In: The ASME 5th International Conference on Energy Sustainability, Washington, D.C., USA, 2011
26
S Pachauri. An analysis of cross-sectional variations in total household energy requirements in India using micro survey data. Energy Policy, 2004, 32(15): 1723–1735 https://doi.org/10.1016/S0301-4215(03)00162-9
27
R Kadian, R P Dahiya, H P Garg. Energy-related emissions and mitigation opportunities from the household sector in Delhi. Energy Policy, 2007, 35(12): 6195–6211 https://doi.org/10.1016/j.enpol.2007.07.014
28
I Gough, S Abdallah, V Johnson, J Ryan-Collins, C Smith. The distribution of total greenhouse gas emissions by households in the UK, and some implications for social policy. London: Centre for Analysis of Social Exclusion, 2012
29
J Palmer, N Terry, P Armitage, D Godoy-Shimizu. Savings, beliefs and demographic change. Cambridge Architectural Research Limited, Element Energy, and Loughborough University, 2014
30
J Thumim, V White. Distributional impacts of personal carbon trading: a report to the department for environment, food and rural affairs. London: Department for Environment, Food and Rural Affairs, 2008
31
E Fahmy, J Thumim, V White. The distribution of UK household CO2 emissions. Interim Report. JRF programme paper: Climate change and social justice, York, 2011
32
L Chancel, T Piketty. Carbon and inequality: from Kyoto to Paris. Paris: Paris School of Economics, 2015
33
Oxfam. Carbon emissions and income inequality. Technical Note. Oxford, 2015
34
Element Energy. Further analysis of data from the household electricity usage study: consumer archetypes. Final Report for DECC and Defra. Cambridge: Element Energy limited, 2013
35
B M Morrison, P M Gladhart. Energy and families: the crisis and the response. Journal of Home Economics, 1976, 68: 15–18
36
N Kaza. Understanding the spectrum of residential energy consumption: a quantile regression approach. Energy Policy, 2010, 38(11): 6574–6585 https://doi.org/10.1016/j.enpol.2010.06.028
S Sultana, N Pourebrahim, H Kim. Household energy expenditures in North Carolina: a geographically weighted regression approach. Sustainability, 2018, 10(5): 1511 https://doi.org/10.3390/su10051511
39
HM Revenue and Customs. Deductions: General rules: main types of expenses: Landlord’s Energy Savings Allowance (LESA). 2017–04–28, available at gov.uk website
40
Office for National Statistics (ONS). Living cost and food survey volume A: introduction January-December 2012. London: ONS, 2013
41
Office for National Statistics (ONS). Input-output supply and use tables for 1997 to 2013. London: ONS, 2013
42
I Gough. Carbon mitigation policies, distributional dilemmas and social policies. Journal of Social Policy, 2013, 42(2): 191–213 https://doi.org/10.1017/S0047279412001018
43
C Brand. Transport and carbon emissions analysis. Project Paper Number 2. Oxford: Environmental Change Institute, University of Oxford, 2013
44
OECD. OECD framework for statistics on the distribution of household income, consumption and wealth. OECD publishing. 2017–04–28, available at keepeek.com website
45
Y G Yohanis, J D Mondol, A Wright, B Norton. Real-life energy use in the UK: how occupancy and dwelling characteristics affect domestic electricity use. Energy and Building, 2008, 40(6): 1053–1059 https://doi.org/10.1016/j.enbuild.2007.09.001
46
J I Utley, L D Shorrock. Domestic energy fact file 2008. BRE Environment, DECC and EST, 2008
47
The Scottish Government. Scottish house condition survey: key findings 2010. Edinburgh: The Scottish Government, 2010
48
M Pullinger, A Browne, B Anderson, W Medd. Patterns of water: the water related practices of households in southern England, and their influence on water consumption and demand management. Final Report of the ARCC-Water/ SPRG Patterns of Water Projects. Lancaster: Lancaster University, 2013
49
W F Lamb, J K Steinberger, A Bows-Larkin, G P Peters, J T Roberts, F R Wood. Transitions in pathways of human development and carbon emissions. Environmental Research Letters, 2014, 9(1): 014011 https://doi.org/10.1088/1748-9326/9/1/014011
50
A Field. Cluster analysis. 2017–04–28, available at website of statisticshell.com
51
B S Everitt, S Landau, M Leese, D Stahl. Cluster Analysis. 5th ed. Chichester: John Wiley & Sons Ltd., 2011
52
AEA. 2012 Guidelines to Defra/DECC’s GHG conversion factors for company reporting. Produced for the Department for Environment, Food and Rural Affairs (Defra) and the Department of Energy and Climate Change (DECC) (Version 1.0), London, 2012
53
Department of Energy and Climate Change (DECC). Quarterly energy prices. URN: 12D/276D. London: DECC, 2012
54
The Consumer Council. Comparative domestic cost of gas v oil report. Belfast: The Consumer Council, 2013
55
Department of Energy and Climate Change (DECC). Quarterly energy prices. URN: 14D/276C. London: DECC, 2014
56
Department of Energy and Climate Change (DECC). Annual fuel poverty statistics report. URN: 14D/146 . London: DECC, 2014
57
E Mooi, M Sarstedt. A concise guide to market research: the process, data and methods using IBM SPSS statistics. Berlin Heidelberg: Springer-Verlag, 2011
58
IBM Knowledge Centre. SPSS statistics two-step cluster algorithms. 2017–04–28, available at ibm.com website
59
S Okazaki. What do we know about mobile Internet adopters? A cluster analysis. Information & Management, 2006, 43(2): 127–141 https://doi.org/10.1016/j.im.2005.05.001
60
A Druckman, M Chitnis, S Sorrell, T Jackson. Missing carbon reductions? Exploring rebound and backfire effects in UK households. Energy Policy, 2011, 39(6): 3572–3581 https://doi.org/10.1016/j.enpol.2011.03.058
61
T R Oke. Inadvertent climate modification. In: Boundary Layer Climates. London: Routledge, 1987
62
C P Lo, D A Quattrochi, J C Luvall. Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing, 1997, 18(2): 287–304 https://doi.org/10.1080/014311697219079
63
E Shove. Comfort, Cleanliness and Convenience: the Organisation of Normality. Oxford and New York: Berg, 2003
64
K Gram-Hanssen. Standby consumption in households analyzed with a practice theory approach. Journal of Industrial Ecology, 2010, 14(1): 150–165 https://doi.org/10.1111/j.1530-9290.2009.00194.x
65
C Maller, R Horne, T Dalton. Green renovations: Intersections of daily routines, housing aspirations and narratives of environmental sustainability. Theory and Society, 2012, 29: 255–275
66
Y Strengers, L Nicholls, C Maller. Curious energy consumers: humans and nonhumans in assemblages of household practice. Journal of Consumer Culture, 2016, 16(3): 761–780 https://doi.org/10.1177/1469540514536194
67
C Butler, K A Parkhill, F Shirani, K Henwood, N Pidgeon. Exploring the dynamics of energy demand through a biographical lens. Nature and Culture, 2014, 9(2): 164–182 https://doi.org/10.3167/nc.2014.090204
68
S Sorrell, J Dimitropoulos. The rebound effect: microeconomic definitions, limitations and extensions. Ecological Economics, 2008, 65(3): 636–649 https://doi.org/10.1016/j.ecolecon.2007.08.013
69
M Chitnis, S Sorrell, A Druckman, S K Firth, T Jackson. Who rebounds most? Estimating direct and indirect rebound effects for different UK socioeconomic groups. Ecological Economics, 2014, 106: 12–32 https://doi.org/10.1016/j.ecolecon.2014.07.003
70
S Sorrell, J Dimitropoulos, M Sommerville. Empirical estimates of the direct rebound effect: a review. Energy Policy, 2009, 37(4): 1356–1371 https://doi.org/10.1016/j.enpol.2008.11.026
71
B Boardman. Home truths: a low-carbon strategy to reduce UK housing emissions by 80% by 2050. ECI Research Report 34. Oxford: Environmental Change Unit, University of Oxford, 2007
72
UK Government. Winter fuel payment. 2019–03–01, available at website of gov.ukeligibility
