Part II: Dealing with parameter uncertainty and uncertainty due to choices in life cycle assessment

Application of uncertainty and variability in LCA

Abstract

Results of product assessments are often criticised as to their handling of uncertainty. Therefore, it is necessary to develop a comprehensive methodology reflecting parameter uncertainty in combination with uncertainty due to choices in the outcome of LCAs. This paper operationalises the effect of combined parameter uncertainties in the inventory and in the characterisation factors for global warming and acidification for the comparison of two exemplary types of roof gutters. For this purpose, Latin Hypercube sampling is used in the matrix (inventory) method. To illustrate the influence of choices, the effect on LCA outcomes is shown of two different allocation procedures in open-loop recycling and three time horizons for global warming potentials. Furthermore, an uncertainty importance analysis is performed to show which parameter uncertainties mainly contribute to uncertainties in the comparison and the separate environmental profiles of the product systems. These results can be used to prioritise further data research.

Keywords

Allocation rules parameter uncertainty LCA Latin hypercube simulation parameter uncertainty LCA LCA parameter uncertainty Life Cycle Assessment parameter uncertainty open-loop recycling parameter uncertainty LCA parameter uncertainty LCA probabalistic simulation parameter uncertainty LCA scenario analysis parameter uncertainty LCA simulation Latin hypercube simulation parameter uncertainty LCA simulation probabalistic simulation parameter uncertainty LCA uncertainty LCA variability parameter 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albritton, D., R.G. Derwent, I.S.A. Isaksen, M. Lal &D.J. Wuebbles (1995): Trace gas radiative forcing indices. In:Houghton, J.T., L.G. Meira Filho, J. Bruce, Hoesung Lee, B.A. Callander, E. Haites, N. Harris &K. Maskell. Climate change 1994: radiative forcing of climate change and an evaluation of the IPCC IS92 emission scenarios. Cambridge University Press, London, UKGoogle Scholar
  2. Albritton, D., R. Derwent, I. Isaksen, M. Lal &D. Wuebbles (1996): Trace gas radiative forcing indices. In:Houghton, J.T., L.G. Mfira Filho, B.A. Callander, N. Harris, A. Kattenberg &K. Maskell. Climate change 1995: the science of climate change. Cambridge University Press, Londen, UKGoogle Scholar
  3. Caldeira, K. &J.F. Kasting (1993): Insensitivity of global warming potentials to carbon dioxide emissions scenarios. Nature 366: 251–253CrossRefGoogle Scholar
  4. Decisioneering (1996): Crystal Ball version 4.0. Forecasting and risk analysis for spreadsheet users. Denver, Colorado, USAGoogle Scholar
  5. Finnveden G., Y. Andersson-Sköld, M.O. Samuelsson, L. Zetterberg &L.-G. Lindfors (1992): Classification (impact analysis) in connection with life cycle assessments — a preliminary study. In: Product life cycle assessment — principles and methodology. Nord 1992:9Google Scholar
  6. Frischknecht, R., P. Hoestetter, I. Knoepfel, M. Ménard, R. Dones &E. Zollinger (eds.) (1996): Ökoinventare für Energiesystemen. Grundlagen für den ökologischen Vergleich von Energiesystemen und den Einbezug von Energiesystemen in Ökobilanzen für die Schweiz. Eidgenössische Technische Hochschule, Zürich, SwitzerlandGoogle Scholar
  7. Heijungs, R., J.B. Guinée, G. Huppes, R.M. Lankreijer, H.A. Udo de Haes, A. Wegener Sleeswijk, A.M.M. Ansems, A.M.M. Eggels, R. van Duin &H.P. de Goede (1992): Environmental life cycle assessment of products. Guidelines and backgrounds. Centre of Environmental Sciences, Leiden, The NetherlandsGoogle Scholar
  8. Heijungs, R. (1994): A generic method for the identification of options for cleaner products. Ecol. Econ. 10: 69–81CrossRefGoogle Scholar
  9. Heijungs, R. (1996): Identification of key issues for further investigation in improving the reliability of life cycle assessments. J. Cleaner Prod. 4 (3-4): 159–166CrossRefGoogle Scholar
  10. Hauschild, M. &H. Wenzel (1998): Environmental assessment of products. Volume 2: Scientific background. Chapter 4: Acidification as a criterion in the environmental assessment of products. Chapman & Hall, London, UKGoogle Scholar
  11. Huijbregts, M.A.J. (1998): Application of Uncertainty and Variability in LCA. A General Framework for the Application of Uncertainty and Variability in Life-Cycle Assessment. Int. J. LCA 3 (5): 273–280CrossRefGoogle Scholar
  12. Kennedy, D.J., D.C. Montgomery &B.H. Quay (1996): Data quality. Stochastic environmental life cycle assessment modeling. A probabilistic approach to incorporate variable input data quality. Int. J. LCA 1 (4): 199–207CrossRefGoogle Scholar
  13. Kortman, J.G.M.,P.G. Eggels,G. Huppes,L. van Oers,E.W. Lindeijer,B.L. van der Ven &J.B. Guinée (1996): Inschatting milieu-effecten van de afdankfase van langcyclische produkten. SPA Programma rapportnr. 96.005. Rijksinstituut voor Integraal Zoetwaterbeheer en Afvalwaterbehandeling Werkdocument nr. 96.155x. Lelystad, The NetherlandsGoogle Scholar
  14. Microsoft ( 1995): Microsoft Excel version 7.0. Microsoft CorporationGoogle Scholar
  15. Morgan, M.G. &M. Henrion (1990): A guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge University Press, New york, NY, USAGoogle Scholar
  16. Weidema, B.P. &M.S. Wesnæs, 1996. Data quality management for life cycle inventories: an example of using data quality indicators. J. Cleaner Prod. 4 (3-4): 167–174CrossRefGoogle Scholar

Copyright information

© Ecomed Publishers 1998

Authors and Affiliations

  1. 1.Inter/faculty Department of Environmental Science, Faculty of Environmental ScienceUniversity of AmsterdamAmsterdamThe Netherlands

Personalised recommendations