Surplus cost as a life cycle impact indicator for fossil resource scarcity

  • Thomas C. Ponsioen
  • Marisa D. M. Vieira
  • Mark J. Goedkoop



In life cycle impact assessment, various proposals have been made on how to characterise fossil resource scarcity, but they lack appropriateness or completeness. In this paper, we propose a method to assess fossil resource scarcity based on surplus cost, which is the global future cost increase due to marginal fossil resource used in the life cycle of products.


The marginal cost increase (MCI in US dollars in the year 2008 per kilogram per kilogram produced) is calculated as an intermediate parameter for crude oil, natural gas and coal separately. Its calculations are based on production cost and cumulative future production per production technique or country. The surplus cost (SC in US dollars in the year 2008 per kilogram) is calculated as an indicator for fossil resource scarcity. The SC follows three different societal perspectives used to differentiate the subjective choices regarding discounting and future production scenarios.

Results and discussion

The hierarchist perspective SCs of crude oil, natural gas, and coal are 2.9, 1.5, and 0.033 US$2008/GJ, respectively. The ratios between the indicators of the different types of fossil resources (crude oil/natural gas/coal) are rather constant, except in the egalitarian perspective, where contrastingly no discounting is applied (egalitarian 100:47:21; hierarchist 100:53:1.1; individualist 100:34:0.6). The ratio of the MCIs (100:48:1.0) are similar to the individualist and hierarchist SC ratios.


In all perspectives, coal has a much lower resource scarcity impact factor per gigajoule and crude oil has the highest. In absolute terms of costs per heating value (US dollars in the year 2008 per gigajoule), there are large differences between the SCs for each perspective (egalitarian > hierarchist > individualist).


Characterisation factors Cultural theory Fossil resources Life cycle impact assessment Marginal cost increase Surplus cost 



Characterisation factor


Life cycle assessment


Life cycle impact assessment


Marginal cost increase


Surplus cost



The research was funded by the European Commission under the 7th framework programme on environment; ENV.2009. LC-IMPACT - Improved Life Cycle Impact Assessment methods (LCIA) for better sustainability assessment of technologies, grant agreement number 243827. We thank Mark Huijbregts (Radboud University Nijmegen) for his valuable feedback on draft versions of this manuscript.

Supplementary material

11367_2013_676_MOESM1_ESM.docx (249 kb)
ESM 1 (DOCX 248 kb)


  1. Anandarajah G, Pye S, Usher W, Kesicki F, McGlade C (2011) TIAM-UCL Global model documentation. Working Paper. February 2011: REF UKERC/WP/ESY/2011/001. University College LondonGoogle Scholar
  2. Bentley RW (2002) Global oil and gas depletion: an overview. Energy Policy 30(3):189–205CrossRefGoogle Scholar
  3. Berger M, Finkbeiner M (2011) Correlation analysis of life cycle impact assessment indicators measuring resource use. Int J Life Cycle Assess 16(1):74–81CrossRefGoogle Scholar
  4. Beumer C, Martens P (2010) Noah’s ark or World Wild Web? Cultural perspectives in global scenario studies and their function for biodiversity conservation in a changing world. Sustainability 2(10):3211–3238CrossRefGoogle Scholar
  5. BGR (2010) Reserves, resources and availability of energy resources. Annual report 2010. Federal Institute for Geosciences and Natural Resources (BGR)Google Scholar
  6. De Schryver AM, Van Zelm R, Humbert S, Pfister S, McKone TE, Huijbregts MAJ (2011) Value choices in life cycle impact assessment of stressors causing human health damage. J Ind Ecol 15(5):796–815CrossRefGoogle Scholar
  7. EC-JRC-IES (2011) International Reference Life Cycle Data System (ILCD) handbook—recommendations for life cycle impact assessment in the European context. First edition November 2011. European Commission-Joint Research Centre - Institute for Environment and Sustainability. Luxemburg. Scholar
  8. Finnveden G (2005) The resource debate needs to continue. Int J Life Cycle Assess 10(5):372CrossRefGoogle Scholar
  9. Frischknecht R, Braunschweig A, Hofstetter P, Suter P (2000) Human health damages due to ionising radiation in life cycle impact assessment. Environ Impact Assess 20(2):159–189CrossRefGoogle Scholar
  10. Goedkoop M, De Schryver A (2009) Fossil Resource. Chapter 13 in. Goedkoop M, Heijungs R, Huijbregts MAJ, De Schryver A, Struijs J, Van Zelm R (eds) ReCiPe 2008 A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. Report I: Characterisation factors, first editionGoogle Scholar
  11. Goedkoop M, Heijungs R, Huijbregts M, De Schryver AM, Struijs J, Van Zelm R (2008) ReCiPe 2008. A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level; First edition Report I. Characterisation. Den Haag, The Netherlands, VROMGoogle Scholar
  12. Gómez DR, Watterson JD, Americano BB, Ha C, Marland G, Matsika E, Namayanga LN, Osman-Elasha B, Saka JDK, Treanton K (2006) Stationery combustion, Chapter 2. Energy, Volume 2. In: IPCC (eds) 2006 IPCC Guidelines for National Greenhouse Gas InventoriesGoogle Scholar
  13. Guinée JB (ed), Gorrée M, Heijungs R, Huppes G, Kleijn R, de Koning A, Van Oers L, Wegener Sleeswijk A, Suh S, Udo de Haes HA, De Bruijn JA, Van Duin R, Huijbregts MAJ (2002) Handbook on life cycle assessment: operational guide to the ISO standards. Series: eco-efficiency in industry and science. Kluwer Academic Publishers. Dordrecht (Hardbound, ISBN 1-4020-0228-9; Paperback, ISBN 1-4020-0557-1)Google Scholar
  14. Harrison M (2010) Valuing the future: the social discount rate in cost-benefit analysis, Visiting Researcher Paper. Productivity Commission, CanberraGoogle Scholar
  15. Hauschild M, Potting J (2005) Spatial differentiation in life cycle impact assessment—the EDIP2003 methodology. Environmental News no. 80. The Danish Ministry of the Environment, Environmental Protection Agency, CopenhagenGoogle Scholar
  16. Hauschild MZ, Goedkoop M, Guinée J, Heijungs R, Huijbregts M, Jolliet O, Margni M, De Schryver A, Humbert S, Laurent A, Sala S, Pant R (2013) Identifying best existing practice for characterization modeling in life cycle impact assessment. Int J Life Cycle Assess 18:683–697CrossRefGoogle Scholar
  17. Hellweg S, Hofstetter TB, Hungerbiihler K (2003) Discounting and the environment: should current impacts be weighted differently than impacts harming future generations? Int J Life Cycle Assess 8(1):8–18Google Scholar
  18. Hof AF, den Elzen MGJ, van Vuuren DP (2008) Analysing the costs and benefits of climate policy: value judgements and scientific uncertainties. Glob Environ Chang 18(3):412–424CrossRefGoogle Scholar
  19. Hofstetter P (1998) Perspectives in life cycle impact assessment, a structure approach to combine models of the technosphere, ecosphere and valuesphere. Kluwer Academic Publishers, Dordrecht, The Netherlands, p 484CrossRefGoogle Scholar
  20. Hofstetter P, Baumgartner T, Scholz RW (2000) Modelling the valuesphere and the ecosphere: integrating the decision makers’ perspectives into life cycle assessment. Int J Life Cycle Assess 5:161–175CrossRefGoogle Scholar
  21. Huijbregts MAJ, Hellweg S, Frischknecht R, Hungerbühler K, Jan Hendriks A (2008) Ecological footprint accounting in the life cycle assessment of products. Ecol Econ 64(4):798–807CrossRefGoogle Scholar
  22. IEA (2009a) World energy outlook 2009. OECD/IEA, Paris, FranceGoogle Scholar
  23. IEA (2009b) Cleaner coal in China. OECD/IEA, Paris, FranceGoogle Scholar
  24. IEA (2010) Resources to Reserves 2010. Oil, gas and coal technologies for the energy markets of the future. To be released Autumn 2010Google Scholar
  25. IEA (2011a) Coal. Medium-term market report 2011. Market trends and projections to 2016. IEA, Paris, FranceGoogle Scholar
  26. IEA (2011b) Key world energy statisticsGoogle Scholar
  27. IEA (2012) World energy outlook 2012. OECD/IEA, Paris, FranceCrossRefGoogle Scholar
  28. IHS (2011) Petrochemical Industry Overview. Accessed April 2011
  29. IPCC (2000) Emission scenarios. A special report of the IPCC working group IIIGoogle Scholar
  30. Jackson T, Papathanasopoulou E (2008) Luxury or ‘lock-in’? An exploration of unsustainable consumption in the UK: 1968 to 2000. Ecol Econ 68(1–2):80–95CrossRefGoogle Scholar
  31. Jolliet O, Müller-Wenk R, Bare J, Brent A, Goedkoop M, Heijungs R, Itsubo N, Peña C, Pennington D, Potting J, Rebitzer G, Stewart M, De Haes HU, Weidema B (2004) The LCIA midpoint-damage framework of the UNEP/SETAC life cycle initiative. Int J Life Cycle Assess 9(6):394–404CrossRefGoogle Scholar
  32. Kapur A (2005) The future of red metal—scenario analysis. Futures 37(10):1067–1094CrossRefGoogle Scholar
  33. Lenzen M, Dey C, Foran B (2004) Energy requirements of Sydney households. Ecol Econ 49(3):375–399CrossRefGoogle Scholar
  34. Li H, Jenkins-Smith HC, Silva CL, Berrens RP, Herron KG (2009) Public support for reducing US reliance on fossil fuels: Investigating household willingness-to-pay for energy research and development. Ecol Econ 68(3):731–742CrossRefGoogle Scholar
  35. Lindeijer E, Müller-Wenk R, Steen B (2002) Impact assessment of resources and land use. In: Udo de Haes HA, Finnveden G, Goedkoop M, Hauschild M, Hertwich EG, Hofstetter P, Jolliet O, Klöpffer W, Krewitt W, Lindeijer EW, Müller-Wenk R, Olsen SI, Pennington DW, Potting J, Steen B (eds) Life-Cycle Impact Assessment: Striving towards best practice. SETAC-Press, PensacolaGoogle Scholar
  36. McGlade C (2011) Uncertainties in the long term availability of crude oil. 34th IAEE International Conference Proceedings. Accessed 10 April 2012
  37. Müller-Wenk R (1998) Depletion of abiotic resources weighted on base of “virtual” impacts of lower grade deposits used in future. IWO- Diskussionsbeitrag nr. 57. ISBN-Nr. 3-906502-57-0Google Scholar
  38. R Development Core Team (2012) R: a language and environment for statistical computing, version 2.11.1 (2010-05-31). R Foundation for Statistical Computing: Vienna, Austria, 2012;
  39. Remme U, Blesl M, Fahl U (2007) Global resources and energy trade: an overview for coal, natural gas, oil and uranium. Universität Stuttgart. Institut für Energiewirtschaft und Rationelle EnergieanwendungGoogle Scholar
  40. Schneider L, Berger M, Finkbeiner M (2011) The anthropogenic stock extended abiotic depletion potential (AADP) as a new parameterisation to model the depletion of abiotic resources. Int J Life Cycle Assess 16(9):929–936CrossRefGoogle Scholar
  41. Steen B (1999) A systematic approach to environmental priority strategies in product development (EPS). Version 2000 – Models and data of the default method. CPM report 1999:5. Chalmers University of Technology, Environmental Systems AnalysisGoogle Scholar
  42. Steen BA (2006) Abiotic resource depletion: different perceptions of the problem with mineral deposits. Int J Life Cycle Assess 11(1):49–54CrossRefGoogle Scholar
  43. Stewart M, Weidema BA (2005) Consistent framework for assessing the impacts from resource use: a focus on resource functionality. Int J Life Cycle Assess 10(4):240–247CrossRefGoogle Scholar
  44. Tilton JE (2003) On borrowed time? Assessing the threat of mineral depletion. Resources for the Future, WashingtonGoogle Scholar
  45. Udo de Haes H, Jolliet O, Finnveden G, Hauschild M, Krewitt W, Müller-Wenk R (1999) Best available practice regarding impact categories and category indicators in life cycle impact assessment. Int J Life Cycle Assess 4(2):66–74CrossRefGoogle Scholar
  46. Van der Voet E (2013) Criticality and abiotic resource depletion in life cycle assessment. Chapter 5. In: Mancini L, De Camillis C, Pennington D (eds) Security of supply and scarcity of raw materials: towards a methodological framework for sustainability assessment. European Commission, LuxemburgGoogle Scholar
  47. Vieira M, Storm P, Goedkoop M (2011) Stakeholder consultation: what do decision makers in public policy and industry want to know regarding abiotic resource use? In: Finkbeiner M (ed) Towards life cycle sustainability management. Springer, Dordrecht Heidelberg London New YorkGoogle Scholar
  48. Weidema BP (2009) Using the budget constraint to monetarise impact assessment results. Ecol Econ 68(6):1591–1598CrossRefGoogle Scholar
  49. Weidema B, Finnveden G, Stewart M (2005) Impacts from resource use: a common position paper. Int J Life Cycle Assess 10(6):382CrossRefGoogle Scholar
  50. Yohe GW, Lasco RD, Ahmad QK, Arnell NW, Cohen SJ, Hope C, Janetos AC, Perez RT (2007) Perspectives on climate change and sustainability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, pp 811–841Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thomas C. Ponsioen
    • 1
  • Marisa D. M. Vieira
    • 1
  • Mark J. Goedkoop
    • 1
  1. 1.PRé Consultants BVAmersfoortThe Netherlands

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