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Published in: Energy Efficiency 1/2019

24-07-2018 | Original Article

“Everyone has a peer in the low user tier”: the diversity of low residential energy users

Authors: Reuben Deumling, Deborah Poskanzer, Alan Meier

Published in: Energy Efficiency | Issue 1/2019

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Abstract

Low residential energy use is typically associated with undesirable characteristics, such as poverty, thermal discomfort, or small dwelling size. The association of low energy use with deprivation has been an obstacle to promoting more aggressive goals for reduction of residential use. However, there is little research on the composition of the low user population. We investigated the demographics, behavior, and satisfaction of the lowest 10% of electricity consumers in Sacramento, CA, to see what attributes best correlated with low use. California, like many other regions, has GHG emissions goals requiring drastic reductions in residential consumption. Households in Sacramento’s lowest decile of electricity consumption already live at electricity consumption levels consistent with the goals for 2050. Our investigation of 700 of these households found that diversity of low users with regard to age, income, education, appliance ownership, and dwelling characteristics is similar to that of the general population. Low-use households tend to be smaller, but not enough to explain the entirety of low usage. Surveys and interviews revealed that those in the lowest 10% typically pursued low consumption deliberately and enthusiastically and were aware of their status as low users. Conversations about energy conserving strategies were embedded in their social lives. They employed diverse and creative strategies to maintain thermal comfort without excess energy use, often exceeding expert recommendations. Finally, the distribution of self-reported quality of life was no different from that of the general population living at much higher consumption levels. Overall, the key determinants of low use were a positive engagement with improvisation and experimentation, and the salience of energy in personal or social life. The population of low users should be treated as a valuable source of peer advice and lifestyle modeling.

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Footnotes
1
See http://​gainesvillegreen​.​com/​. The opposite effect, i.e. provoking an increase in consumption by lower-use households, is of course also possible.
 
2
The full report is Reuben Deumling et al. (2013): “Identifying Determinants of Very Low Energy Consumption Rates Observed in Some California Households”. Available at https://​www.​arb.​ca.​gov/​research/​apr/​past/​09-326.​pdf .
 
4
Deumling et al. (2013), p. 7, Figures 5.1 and 5.2. Monthly usage for the overall population ranged from 50 to 1850 kWh/month. The boundary of the lowest decile lay at about 330 kWh/month.
 
5
For regression table see Deumling et al. (2013), pp. 77–73; for survey questions pp. 76–83; for interview template pp. 84–85.
 
6
For the sole purpose of the regression analysis, we compared the lowest quartile (rather than decile) of electricity customers with the general population of the SMUD service area. In contrast to the rest of the study, the goal here was to establish linear relationships between electricity usage and the variables of interest; thus, the use of the somewhat broader data set was preferable. Results from regression models are presented in Deumling et al. (2013), pp. 72–73, Table A.1.
 
7
Deumling et al. (2013), p.19, Figure 6.9.
 
8
Deumling et al. (2013), p. 17, Figure 6.6. We further compared the lowest decile with the general population as to age distribution (Figures 6.3, 6.7, and 6.8) educational attainment of household head (Figure 6.2), and ethnicity (Figure 6.4).
 
9
Deumling et al. (2013), pp. 23 ff, and Survey Questions 7 and 18.
 
10
Here and in all subsequent mention of survey questions, the document is reproduced in Deumling et al. (2013), pp. 76–83.
 
11
Deumling et al. (2013), p. 38, Figure 6.24.
 
12
Deumling et al. (2013), p. 41, Figure 6.27. Even respondents who did not believe their energy use to be lower (or their home less cooled) than that of their neighbors may still have recognized themselves as low users: given that our pool was a full 10% of the population, their neighbors could also have been low users.
 
13
Deumling et al. (2013), p. 27, Figure 6.21.
 
14
Deumling et al. (2013), p. 28, Figure 6.22.
 
15
Some respondents mentioned both constraints and voluntary pursuit of low use.
 
17
Deumling et al. (2013), pp. 39–40 and pp. 80–81 (Survey Questions 25–27).
 
18
There have been some efforts to leverage social media to target energy reduction messages more effectively. Dougherty et al. (2011) describe data-driven social norm messaging programs that target high users through information mailed to customers, including a usage comparison across demographically similar households and a series of recommended actions. Seattle City Light has studied variation among their residential customers, as well as high usage, as a way to identify opportunities for large savings (2010, also Meier 2010). An outreach campaign by the Gainesville [Florida] Regional Utility puts customer usage information on a searchable public website “to enable us all to make better decisions about our energy usage” (Gainesville Green n.d.). Although these give the appearance of targeted outreach tailored to market niches, in fact the same behavioral strategy is deployed for the entire audience. At the other end of the usage spectrum, subsidy or assistance programs are aimed at a narrow market niche (low income consumers), but these are a form of support rather than an effort to change behaviors.
 
19
Deumling et al. (2013), p. 58, Figure 7.6.
 
20
For further explanation of the unhappily low energy estimate, see Deumling et al. (2013), pp. 62–64.
 
Literature
go back to reference Boardman, B. (1991). Fuel poverty: from cold homes to affordable warmth. Pinter Pub Limited, Belhaven Press, London. Boardman, B. (1991). Fuel poverty: from cold homes to affordable warmth. Pinter Pub Limited, Belhaven Press, London.
go back to reference Boardman, B. (2012). ‘Fuel poverty synthesis: lessons learnt, actions needed’. Energy Policy, 49, 143–148.CrossRef Boardman, B. (2012). ‘Fuel poverty synthesis: lessons learnt, actions needed’. Energy Policy, 49, 143–148.CrossRef
go back to reference California. (2006). Global Warming Solutions Act of 2006 (AB32). California. (2006). Global Warming Solutions Act of 2006 (AB32).
go back to reference Cialdini, Robert. (1984). Influence: the psychology of persuasion. New York: Collins Business. Cialdini, Robert. (1984). Influence: the psychology of persuasion. New York: Collins Business.
go back to reference Cialdini, Robert. (2016). Pre-suasion : a revolutionary way to influence and persuade. New York: Simon & Schuster. Cialdini, Robert. (2016). Pre-suasion : a revolutionary way to influence and persuade. New York: Simon & Schuster.
go back to reference Dietz, T., Gardner, G., Gilligan, J., Stern, P., & Vandenbergh, M. (2009). Household actions can provide a behavioral wedge to rapidly reduce U.S. carbon emissions. PNAS, 106(44), 18452–18456.CrossRef Dietz, T., Gardner, G., Gilligan, J., Stern, P., & Vandenbergh, M. (2009). Household actions can provide a behavioral wedge to rapidly reduce U.S. carbon emissions. PNAS, 106(44), 18452–18456.CrossRef
go back to reference Diamond, R. (1984). ‘Energy and housing for the elderly’. In B. Morrison & W. Kempton (Eds.). Families and energy: coping with uncertainty (pp. 331–345). Proceedings of the Conference on Families and Energy, Michigan State University. Diamond, R. (1984). ‘Energy and housing for the elderly’. In B. Morrison & W. Kempton (Eds.). Families and energy: coping with uncertainty (pp. 331–345). Proceedings of the Conference on Families and Energy, Michigan State University.
go back to reference Dougherty, A., Dwelley, A., Henschel, R., and Hastings, R. (2011). ‘Moving beyond econometrics to examine the behavioral changes behind impacts’. IEPEC Conference Paper. Dougherty, A., Dwelley, A., Henschel, R., and Hastings, R. (2011). ‘Moving beyond econometrics to examine the behavioral changes behind impacts’. IEPEC Conference Paper.
go back to reference European Parliament, Directorate-General for Internal Policies, Committee on Industry, Research, and Energy (ITRE). 2016. “Energy efficiency for low-income households.” European Parliament, Directorate-General for Internal Policies, Committee on Industry, Research, and Energy (ITRE). 2016. “Energy efficiency for low-income households.”
go back to reference Hackett, B. 1980. "Energy conservation and rural alternative lifestyles”. Social Problems 28(2), 165–178. Hackett, B. 1980. "Energy conservation and rural alternative lifestyles”. Social Problems 28(2), 165–178.
go back to reference Hackett, B., & Lutzenhiser, L. (1991). Social structures and economic conduct: interpreting variations in household energy consumption. Sociological Forum, 6, 449–470.CrossRef Hackett, B., & Lutzenhiser, L. (1991). Social structures and economic conduct: interpreting variations in household energy consumption. Sociological Forum, 6, 449–470.CrossRef
go back to reference Hernandez, D. (2013). Energy insecurity: a framework for understanding energy, the built environment and health among vulnerable populations in the context of climate change. American Journal of Public Health., 104(3). Hernandez, D. (2013). Energy insecurity: a framework for understanding energy, the built environment and health among vulnerable populations in the context of climate change. American Journal of Public Health., 104(3).
go back to reference Johnson, W. A., Stoltzfus, V., Craumer, D. (1977). “Energy conservation in Amish agriculture : Amish farmers can cut energy use without reducing yields, but this cannot be achieved everywhere.” Science 198(4315), 373–378. Johnson, W. A., Stoltzfus, V., Craumer, D. (1977). “Energy conservation in Amish agriculture : Amish farmers can cut energy use without reducing yields, but this cannot be achieved everywhere.” Science 198(4315), 373–378.
go back to reference Kempton, W. & Krabacher, S. (1986). ‘Thermostat management: intensive interviewing used to interpret instrumentation data,’ pp. 245–262. In W.Kempton and M. Neiman (editors), Energy Efficiency: Perspectives on Individual Behavior. Washington, DC: ACEEE Press. Kempton, W. & Krabacher, S. (1986). ‘Thermostat management: intensive interviewing used to interpret instrumentation data,’ pp. 245–262. In W.Kempton and M. Neiman (editors), Energy Efficiency: Perspectives on Individual Behavior. Washington, DC: ACEEE Press.
go back to reference Lutzenhiser, L. (1993). Social and behavioral aspects of energy use. Annual Review of Energy and the Environment, 18, 247–289.CrossRef Lutzenhiser, L. (1993). Social and behavioral aspects of energy use. Annual Review of Energy and the Environment, 18, 247–289.CrossRef
go back to reference Lutzenhiser, L. (2002). ‘An exploratory analysis of residential electricity conservation survey and billing data: Southern California Edison, summer 2001’ Sacramento, CA: California Energy Commission, report 400-02-006F. Lutzenhiser, L. (2002). ‘An exploratory analysis of residential electricity conservation survey and billing data: Southern California Edison, summer 2001’ Sacramento, CA: California Energy Commission, report 400-02-006F.
go back to reference Lutzenhiser, L., & Gossard, M. (2000). ‘Lifestyle, status and energy consumption’. Proceedings, ACEEE. Washington, DC: ACEEE Press, 8, 207–222. Lutzenhiser, L., & Gossard, M. (2000). ‘Lifestyle, status and energy consumption’. Proceedings, ACEEE. Washington, DC: ACEEE Press, 8, 207–222.
go back to reference McKenzie-Mohr, D. (2011). Fostering sustainable behavior: An introduction to community-based social marketing. Gabriola Island: New Society Publishers. McKenzie-Mohr, D. (2011). Fostering sustainable behavior: An introduction to community-based social marketing. Gabriola Island: New Society Publishers.
go back to reference Neiman, M. (1989). ‘Government directed change of everyday life and coproduction: the case of home energy use’ The Western Political Quarterly, 42(3):365–389. September. Neiman, M. (1989). ‘Government directed change of everyday life and coproduction: the case of home energy use’ The Western Political Quarterly, 42(3):365–389. September.
go back to reference Pacala, S., & Socolow, R. (2004). ‘Stabilization wedges: solving the climate problem for the next 50 years with current technologies’. Science, 305(13), 968–972.CrossRef Pacala, S., & Socolow, R. (2004). ‘Stabilization wedges: solving the climate problem for the next 50 years with current technologies’. Science, 305(13), 968–972.CrossRef
go back to reference Schipper, L., Bartlett, S., Hawk, D., & Vine, E. (1989). ‘Linking lifestyles and energy use: A matter of time’. Annual Review of Energy, 14, 273–320. Schipper, L., Bartlett, S., Hawk, D., & Vine, E. (1989). ‘Linking lifestyles and energy use: A matter of time’. Annual Review of Energy, 14, 273–320.
go back to reference Seattle City Light. (2010). Residential customer characteristics survey. February. Seattle City Light. (2010). Residential customer characteristics survey. February.
go back to reference Shove, E. (2003). Comfort, Cleanliness and Convenience: The social organization of normality. Oxford: Berg Publishers. Shove, E. (2003). Comfort, Cleanliness and Convenience: The social organization of normality. Oxford: Berg Publishers.
go back to reference Socolow, R. H. (1978). The rwin rivers program on energy conservation in housing: Highlights and conclusions. In Saving energy in the home: Princeton’s experiments at Twin Rivers. Cambridge: Ballinger. Socolow, R. H. (1978). The rwin rivers program on energy conservation in housing: Highlights and conclusions. In Saving energy in the home: Princeton’s experiments at Twin Rivers. Cambridge: Ballinger.
go back to reference Sovacool, B. (2015). Fuel poverty, affordability, and energy justice in England: policy insights from the Warm Front Program. Energy, 93, 361–371.CrossRef Sovacool, B. (2015). Fuel poverty, affordability, and energy justice in England: policy insights from the Warm Front Program. Energy, 93, 361–371.CrossRef
go back to reference Thomson, H., & Snell, C. (2013). Quantifying the prevalence of fuel poverty across the European Union. Energy Policy, 52(2013), 563–572.CrossRef Thomson, H., & Snell, C. (2013). Quantifying the prevalence of fuel poverty across the European Union. Energy Policy, 52(2013), 563–572.CrossRef
Metadata
Title
“Everyone has a peer in the low user tier”: the diversity of low residential energy users
Authors
Reuben Deumling
Deborah Poskanzer
Alan Meier
Publication date
24-07-2018
Publisher
Springer Netherlands
Published in
Energy Efficiency / Issue 1/2019
Print ISSN: 1570-646X
Electronic ISSN: 1570-6478
DOI
https://doi.org/10.1007/s12053-018-9703-z

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