The International Journal of Life Cycle Assessment

, Volume 19, Issue 12, pp 1933–1947 | Cite as

The rebound effect through industrial ecology’s eyes: a review of LCA-based studies

LCI METHODOLOGY AND DATABASES

Abstract

Purpose

Industrial ecology academics have embraced with great interest the rebound effect principle operationalised within energy economics. By pursuing more comprehensive assessments, they applied tools such as life cycle assessment (LCA) to appraise the environmental consequences of the rebound effect. As a result, the mainstream rebound mechanism was broadened and a diversity of (sometimes inconsistent) definitions and approaches unveiled. To depict the state of play, a comprehensive literature review is needed.

Methods

A literature review has been carried out by targeting scientific documents relevant for the integration of the rebound effect into LCA-based studies. The search was conducted using two approaches: (1) via online catalogues using a defined search criterion and (2) via cross-citation analysis from the documents identified through the first approach.

Results and discussion

By analysing a total of 42 works yielded during our review, it was possible to bring together the various advantages of the life cycle perspective, as well as to identify the main inconsistencies and uninformed claims present in literature. Concretely, three main advantages have been identified and are discussed: (1) the representation of the rebound effect as a multi-dimensional, life cycle estimate, (2) the improvement of the technology explicitness and (3) the broadening of the consumption and production factors leading to the rebound effect. Also, inconsistencies on the definition and classification of the rebound effect have been found among studies.

Conclusions

The review contributes a number of valuable insights to understand how the rebound effect has been treated within the industrial ecology and LCA fields. For instance, the conceptual and methodological refinements introduced by these fields represent a step forward from traditional viewpoints, making the study of the rebound effect more comprehensive and meaningful for environmental assessment and policy making. However, the broadened scope of this new approach unveiled some conceptual inconsistencies, which calls for a common framework. This framework would help the LCA community to consistently integrate the rebound effect as well as to create a common language with other disciplines, favouring learning and co-evolution. We believe that our findings can serve as a starting point in order to delineate such a common framework.

Keywords

Industrial ecology Life cycle assessment Literature review Rebound effect Secondary effects Sustainable consumption 

References

  1. Alfredsson EC (2004) Green consumption: no solution for climate change. Energy 29(4):513–524CrossRefGoogle Scholar
  2. Becker GS (1965) A theory of the allocation of time. Econ J 75(299):493–517CrossRefGoogle Scholar
  3. Berkhout PHG, Muskens JC, Velthuijsen W (2000) Defining the rebound effect. Energ Policy 28(6–7):425–432CrossRefGoogle Scholar
  4. Binswanger M (2001) Technological progress and sustainable development: what about the rebound effect? Ecol Econ 36(1):119–132CrossRefGoogle Scholar
  5. Briceno T, Peters G, Solli C, Hertwich E (2004) Using life cycle approaches to evaluate sustainable consumption programs: car-sharing, reports and working papers from Norwegian University of Science and Technology (NTNU), Industrial Ecology Programme (IndEcol). Working Papers no.2/2005Google Scholar
  6. Britz W, Domínguez I, Heckelei T (2010) A comparison of CAPRI and SEAMLESS-IF as Integrated Modelling Systems. In: Ittersum MK, Brouwer FM (eds) Environmental and agricultural modelling. Springer, NetherlandsGoogle Scholar
  7. Brookes L (1990) The greenhouse effect: the fallacies in the energy efficiency solution. Energ Policy 18(2):199–201CrossRefGoogle Scholar
  8. Cellura M, Di Gangi A, Longo S, Orioli A (2013a) An Italian input–output model for the assessment of energy and environmental benefits arising from retrofit actions of buildings. Energ Build 62:97–106CrossRefGoogle Scholar
  9. Cellura M, Guarino F, Longo S, Mistretta M, Orioli A (2013b) The role of the building sector for reducing energy consumption and greenhouse gases: an Italian case study. Renew Energ 60:586–597CrossRefGoogle Scholar
  10. Dandres T, Gaudreault C, Tirado-Seco P, Samson R (2011) Assessing non-marginal variations with consequential LCA: application to European energy sector. Renew Sustain Energy Rev 15(6):3121–3132CrossRefGoogle Scholar
  11. De Haan P (2008) Identification, quantification, and containment of energy-efficiency induced rebound effects: a research agenda. Rebound Research Report Nr. 1. ETH Zurich, IED-NSSI, report EMDM1521, 26 pages. doi:10.3929/ethz-a-006224281
  12. De Haan P, Mueller MG, Peters A (2005) Does the hybrid Toyota Prius lead to rebound effects? Analysis of size and number of cars previously owned by Swiss Prius buyers. Ecol Econ 58(3):592–605CrossRefGoogle Scholar
  13. Dimitropoulos J, Sorrell S (2008) The rebound effect: microeconomic definitions, extensions and limitations. Ecol Econ 65(3):636–649CrossRefGoogle Scholar
  14. Durrenberger G, Patzel N, Hartmann C (2001) Household energy consumption in Switzerland. Int J Environ Pollut 15(2):159–170Google Scholar
  15. Ekvall T (2000) A market-based approach to allocation at open-loop recycling. Resour Conserv Recycl 29(1–2):91–109CrossRefGoogle Scholar
  16. Ekvall T (2002) Cleaner production tools: LCA and beyond. J Clean Prod 10(5):403–406CrossRefGoogle Scholar
  17. Erdmann L, Hilty L, Goodman J, Arnfalk P (2004) The future impact of ICTs on environmental sustainability. Institute for Prospective Technological StudiesGoogle Scholar
  18. Fishbone LG, Abilock H (1981) Markal, a linear-programming model for energy systems analysis: technical description of the bnl version. Int J Energy Res 5(4):353–375CrossRefGoogle Scholar
  19. Font Vivanco D, Kemp R, Van der Voet E, Heijungs R (2014) Using LCA-based decomposition analysis to study the multi-dimensional contribution of technological innovation to environmental pressures. J Ind Ecol 18(3):380–392CrossRefGoogle Scholar
  20. Freeman C (1998) The economics of technical change. Trade, Growth and Technical Change, Cambridge, pp 16–54Google Scholar
  21. Girod BV (2008) Environmental impact of Swiss household consumption, and estimated income rebound effects, Eidgen-Âssische Technische Hochschule Zurich, IED-Institute for Environmental Decisions, NSSI-Natural and Social Science InterfaceGoogle Scholar
  22. Girod B, De Haan P (2009) GHG reduction potential of changes in consumption patterns and higher quality levels: Evidence from Swiss household consumption survey. Energ Policy 37(12):5650–5661CrossRefGoogle Scholar
  23. Girod B, De Haan P (2010) More or Better? A model for changes in household greenhouse gas emissions due to higher income. J Ind Ecol 14(1):31–49CrossRefGoogle Scholar
  24. Girod B, De Haan P, Scholz R (2011) Consumption-as-usual instead of ceteris paribus assumption for demand. Int J Life Cycle Assess 16(1):3–11CrossRefGoogle Scholar
  25. Goedkoop MJ (1999) Product service systems, ecological and economic basics, Ministry of Housing, Spatial Planning and the Environment, Communications DirectorateGoogle Scholar
  26. Goedkoop MJ, Te Riele H, Van Halen C, Rommens P (1998) Product service combinations. Proceedings of the 3rd International Conference on Ecobalance, Tsukuba, pp 25–27Google Scholar
  27. Greening A, Greene DL, Difiglio C (2000) Energy efficiency and consumption-the rebound effect: a survey. Energ Policy 28(6–7):389–401CrossRefGoogle Scholar
  28. Heijungs R, Huppes G, Guinée J (2009) A scientific framework for LCA. Deliverable (D15) of work package 2 (WP2) CALCAS projectGoogle Scholar
  29. Hertel T (1999) Global trade analysis: modeling and applications. Cambridge, University PressGoogle Scholar
  30. Hertwich EG (2005) Consumption and the rebound effect: an industrial ecology perspective. J Ind Ecol 9(1–2):85–98Google Scholar
  31. Hofstetter P, Madjar M (2003) Linking change in happiness, time-use, sustainable consumption, and environmental impacts; an attempt to understand time-rebound effects. Final report to the Society for Non-Traditional Technology. Japan/BAO & Consultrix, ZurichGoogle Scholar
  32. Hofstetter P, Bare JC, Hammitt JK, Murphy PA, Rice GE (2002) Tools for comparative analysis of alternatives: competing or complementary perspectives? Risk Anal 22(5):833–851CrossRefGoogle Scholar
  33. Hofstetter P, Madjar M, Ozawa T (2006) Happiness and sustainable consumption: psychological and physical rebound effects at work in a tool for sustainable design. Int J Life Cycle Assess 11(1):105–115Google Scholar
  34. Huppes G, De Koning A, Suh S, Heijungs R, Van Oers L, Nielsen P, Guinée JB (2006) Environmental impacts of consumption in the European Union: high-resolution input–output tables with detailed environmental extensions. J Ind Ecol 10(3):129–146CrossRefGoogle Scholar
  35. Jalas M (2002) A time use perspective on the materials intensity of consumption. Ecol Econ 41(1):109–123CrossRefGoogle Scholar
  36. Khazzoom JD (1980) Economic implications of mandated efficiency in standards for household appliances. Energ J 1(4):21–40Google Scholar
  37. Kondo Y, Takase K (2007) An integrated model for evaluating environmental impact of consumer’s behavior: consumption technologies and the waste input–output model. Advances in Life Cycle Engineering for Sustainable Manufacturing Businesses, pp 413–416Google Scholar
  38. Manne AS, Wene CO (1992) MARKAL-MACRO: a linked model for energy-economy analysis. Brookhaven National Lab, UptonGoogle Scholar
  39. Murray CK (2013) What if consumers decided to all ‘go green’? Environmental rebound effects from consumption decisions. Energ Policy 54:240–256CrossRefGoogle Scholar
  40. Ornetzeder M, Hertwich EG, Hubacek K, Korytarova K, Haas W (2008) The environmental effect of car-free housing: a case in Vienna. Ecol Econ 65(3):516–530CrossRefGoogle Scholar
  41. Parke T (1987) The social constructions of technological systems: new directions in the sociology and history of technology the MIT PressGoogle Scholar
  42. Polimeni JM, Mayumi K, Giampietro M, Alcott B (eds) (2008) The Jevons Paradox and the Myth of Resource Efficiency Improvements. EarthscanGoogle Scholar
  43. Pothen F (2010) Industrial ecology in policy making: what is achievable and what is not?, Centre for European Economic Research (ZEW) - Environmental and Resource Economics, Environmental Management ResearchGoogle Scholar
  44. Rajagopal D, Hochman G, Zilberman D (2011) Indirect fuel use change (IFUC) and the lifecycle environmental impact of biofuel policies. Energ Policy 39(1):228–233CrossRefGoogle Scholar
  45. Ramos-Martin J (2003) Empiricism in ecological economics: a perspective from complex systems theory. Ecol Econ 46(3):387–398CrossRefGoogle Scholar
  46. Roth IF, Ambs LL (2004) Incorporating externalities into a full cost approach to electric power generation life-cycle costing. Energy 29(12–15):2125–2144CrossRefGoogle Scholar
  47. Sandén B, Karlstrom M (2007) Positive and negative feedback in consequential life-cycle assessment. J Clean Prod 15(15):1469–1481CrossRefGoogle Scholar
  48. Saunders HD (2000) A view from the macro side: rebound, backfire, and Khazzoom-Brookes. Energ Policy 28(6–7):439–449CrossRefGoogle Scholar
  49. Seebregts AJ, Goldstein GA, Smekens K (2002) Energy/environmental modeling with the MARKAL family of models, Springer, pp 75–82Google Scholar
  50. Sorrell S (2007) The rebound effect: an assessment of the evidence for economy-wide energy savings from improved energy efficiency. Project Report, UK Energy Research CentreGoogle Scholar
  51. Sorrell S (2009) Jevons Paradox revisited: the evidence for backfire from improved energy efficiency. Energ Policy 37(4):1456–1469CrossRefGoogle Scholar
  52. Spielmann M, De Haan P, Scholz RW (2008) Environmental rebound effects of high-speed transport technologies: a case study of climate change rebound effects of a future underground maglev train system. J Clean Prod 16(13):1388–1398CrossRefGoogle Scholar
  53. Suh S, Huppes G (2002) Missing inventory estimation tool using extended input–output analysis. Int J Life Cycle Assess 7(3):134–140CrossRefGoogle Scholar
  54. Takahashi KI, Tatemichi H, Tanaka T, Nishi S, Kunioka T (2004) Environmental impact of information and communication technologies including rebound effects. In: Electronics and the environment, 2004. Conference Record. 2004 I.E. International Symposium, pp 13–16Google Scholar
  55. Takase K, Kondo Y, Washizu A (2005) An analysis of sustainable consumption by the waste input–output model. J Ind Ecol 9(1–2):201–219Google Scholar
  56. Takase K, Kondo Y, Washizu A (2006) An analysis of consumers behavior by the waste input–output model: environmental impact of income and time use. Int J Life Cycle Assess Jpn 2(1):48–55CrossRefGoogle Scholar
  57. Thiesen J, Christensen T, Kristensen T, Andersen T, Andersen R, Brunoe B, Gregersen T, Thrane M, Weidema B (2006) Rebound effects of price differences. Int J Life Cycle Assess 13(2):104–114CrossRefGoogle Scholar
  58. Thomas BA, Azevedo ISL (2013a) Estimating direct and indirect rebound effects for U.S. households with input–output analysis Part 1: Theoretical framework. Ecol Econ 86:199–210CrossRefGoogle Scholar
  59. Thomas BA, Azevedo ISL (2013b) Estimating direct and indirect rebound effects for U.S. households with input–output analysis. Part 2: Simulation. Ecol Econ 86:188–198CrossRefGoogle Scholar
  60. Tukker A, Goldbohm RA, De Koning A, Verheijden M, Kleijn R, Wolf O, Pérez-Domínguez I, Rueda-Cantuche JM (2011) Environmental impacts of changes to healthier diets in Europe. Ecol Econ 70(10):1776–1788CrossRefGoogle Scholar
  61. Van den Bergh JCJM (2011) Energy conservation more effective with rebound policy. Environ Resour Econ 48(1):43–58CrossRefGoogle Scholar
  62. Weidema B (1993) Market aspects in product life cycle inventory methodology. J Clean Prod 1(3–4):161–166CrossRefGoogle Scholar
  63. Weidema B, Thrane M (2007) Comments on the development of harmonized method for Sustainability Assessment of Technologies (SAT). Sustainability Assessment of TechnologiesGoogle Scholar
  64. Weidema BP, Wesnaes J, Hermansen J, Kristensen J, Halberg N (2008) Environmental improvement potentials of meat and dairy products. Office for Official Publications of the European Communities, LuxembourgGoogle Scholar
  65. Whitefoot KS, Grimes-Casey HG, Girata CE, Morrow WR, Winebrake JJ, Keoleian GA, Skerlos SJ (2011) Consequential life cycle assessment with market-driven design. J Ind Ecol 15(5):726–742CrossRefGoogle Scholar
  66. Wood R, Hertwich E (2013) Economic modelling and indicators in life cycle sustainability assessment. Int J Life Cycle Assess 18:1710–1721CrossRefGoogle Scholar
  67. Ybema JR, Kram T (1997) MARKAL modelling and scenarios relating to availability of new energy technologies. Energy Research Foundation ECN, NetherlandsGoogle Scholar
  68. Zamagni P, Buttol PL, Porta R, Buonamici R, Masoni P, Guinée J, Heijungs R, Ekvall T, Bersani R, Bienkowska A, Pretato U (2008) Critical review of the current research needs and limitations related to ISO-LCA practice. Deliverable D7 of work package 5 of the CALCAS projectGoogle Scholar
  69. Zamagni A, Guinée J, Heijungs R, Masoni P, Raggi A (2012) Lights and shadows in consequential LCA. Int J Life Cycle Assess 17(7):904–918CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Institute of Environmental Sciences (CML)Leiden UniversityLeidenNetherlands

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