Skip to main content

Framework for modelling data uncertainty in life cycle inventories

The International Journal of Life Cycle Assessment volume 6, pages 127–132 (2001)Cite this article

Abstract

Modelling data uncertainty is not common practice in life cycle inventories (LCI), although different techniques are available for estimating and expressing uncertainties, and for propagating the uncertainties to the final model results. To clarify and stimulate the use of data uncertainty assessments in common LCI practice, the SETAC working group ‘Data Availability and Quality’ presents a framework for data uncertainty assessment in LCI. Data uncertainty is divided in two categories: (1) lack of data, further specified as complete lack of data (data gaps) and a lack of representative data, and (2) data inaccuracy. Filling data gaps can be done by input-output modelling, using information for similar products or the main ingredients of a product, and applying the law of mass conservation. Lack of temporal, geographical and further technological correlation between the data used and needed may be accounted for by applying uncertainty factors to the non-representative data. Stochastic modelling, which can be performed by Monte Carlo simulation, is a promising technique to deal with data inaccuracy in LCIs.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

References

  • Beccali G, Beccali M, Cellura M (1997): Fuzzy set application in life cycle inventory of building materials. Paper. Building and the Environment: Proceedings of the Second International Conference. Volume 1: Assessment methods and natural resources. Centre Scientifique et Technique du Bâtiment, Paris

    Google Scholar 

  • Boustead I (1993): Eco-profiles of the European plastics industry. Report 3: polyethylene and polypropylene. Association of Plastics Manufacturers in Europe (APME), European Centre for Plastics and the Environment (PMWI), Brussels

    Google Scholar 

  • Boustead I (1997): Eco-profiles of the European plastics industry. Report 9: polyurethane precursors (TDI, MDI, Polyols). Second edition. Association of Plastics Manufacturers in Europe (APME), European Isocyanate Producers Association (ISOPA). Brussels

    Google Scholar 

  • Bretz R, Fankhauser P (1996): Screening LCA for large numbers of products: estimation tools to fill data gaps. Int J LCA 1 (3) 139–146

    CAS  Google Scholar 

  • Burmaster DE, Anderson PD (1994): Principles of good practice for the use of Monte Carlo techniques in human health and ecological risk assessments. Risk Analysis 14 (4) 477–481

    Article  CAS  Google Scholar 

  • Carnegie Mellon University (1999): Economic input-output life cycle assessment. http://www.eiolca.net/

  • Chevalier JL, Le Téno JF (1996). Life cycle analysis with ill-defined data and its application to building products. Int J LCA 1 (2) 90–96

    CAS  Google Scholar 

  • De Beaufort ASH, Bretz R (eds.) (2001): Code of life cycle inventory practice. SETAC WG ‘Data Availability and Data Quality’. SETAC-Europe, Brussels (forthcoming)

    Google Scholar 

  • EC (1996): Technical Guidance on in support of Commission Directive 93/67/EEC on risk assessment for new notified substances and Commission Regulation (EC) No. 1488/94 on risk assessment for existing substances 2nd part. Brussels, Commission of the European Communities, Directorate-General Environment, Nuclear Safety and Civil Protection

  • Fava J, Jensen AA, Lindfors L, Pomper S, De Smet B, Warren J, Vigon B (1994): Life-cycle assessment data quality: a conceptual framework. Society of Environmental Toxicology and Chemistry-Europe. Pensacola, Florida

    Google Scholar 

  • Finnveden G, Lindfors LG (1998): Data quality of life cycle inventory data-rules of thumb. Int J LCA 3 (2) 65–66

    Google Scholar 

  • Frischknecht R, Hofstetter P, Knoepfel I, Menard M, Dones R, Zollinger E (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

    Google Scholar 

  • Habersatter K (ed.) (1991): Ökobilanz von Packstoffen, Stand 1990, Swiss Bundesamt für Umwelt, Wald und Landschaft (BUWAL), Schriftenreihe Umwelt Nr. 132. Bern

  • Habersatter K, Fecker I (eds.) (1998): Ökoinventare für Verpackungen Vol. I + II, Swiss Bundesamt für Umwelt, Wald und Landschaft (BUWAL), Schriftenreihe Umwelt Nr. 250/I+II, Update and corrections. Bern

  • Heijungs R (1996): Identification of key issues for further investigation in improving the reliability of life cycle assessments. J Cleaner Prod 4 (3–4) 159–166

    Article  Google Scholar 

  • Hendrickson C, Horvath A, Joshi S, Lave L (1998): Economic input-output models for environmental life-cycle assessment. Environ Sci Tech 32 (7) 184A-191A

    CAS  Google Scholar 

  • Hischier R, Bretz R, Baitz M, McKeown P, Oele M, Renner I, Reusser L, Wessman H, Huybrechts D, Moessner S, De Beaufort ASH (2001): SETAC-Europe LCA Working Group, Data Availability and Data Quality, ‘Standardized Lists of Interventions’. Int J LCA (forthcoming)

  • Hoffman L, Weidema BP, Kristiansen K, Ersball AK (1995): Statistical analysis and uncertainties in relation to LCA. Special reports no. 1. Nordic Council of Ministers. Copenhagen

    Google Scholar 

  • Huijbregts MAJ (1998a): Application of uncertainty and variability in LCA. Part I: A general framework for the analysis of uncertainty and variability in life-cycle assessment. Int J LCA 3 (5) 273–280

    Google Scholar 

  • Huijbregts MAJ (1998b): Application of uncertainty and variability in LCA. Part II: Dealing with parameter uncertainty and uncertainty due to choices in life-cycle assessment. Int J LCA 3 (6) 343–351

    CAS  Google Scholar 

  • Janssen PHM, Slob W, Rotmans J (1990): Gevoeligheidsanalyse en onzekerheidsanalyse, een inventarisatie van ideeën, methoden en technieken (in Dutch). Report no. 958805001. National Institute of Public Health and the Environment, Bilthoven

    Google Scholar 

  • Kennedy DJ, Montgomery DC, Quay BH (1996): Data quality. Stochastic environmental life cycle assessment modelling. A probabilistic approach to incorporating variable input data quality. Int J LCA 1 (4) 199–207

    CAS  Article  Google Scholar 

  • Maurice B, Frischknecht R, Coehlo-Schwirtz V, Hungerbühler K (2000): Uncertainty analysis in life cycle inventory. Application to the production of electricity with French coal power plants. J Cleaner Prod 8 (2) 95–108

    Article  Google Scholar 

  • Morgan MG, Henrion M, Morris SC Amaral DAL (1985): Uncertainty in risk assessment. A case study involving sulfur transport and health effects. Environ Sci Tech 19 (8) 662–667

    Article  CAS  Google Scholar 

  • Morgan MG, Henrion M (1990): A guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge University Press, New York, NY

    Google Scholar 

  • Norris GA (1997): An Integrated Economic/Environmental Accounting Analysis System for the USA. In: Regional and National Material Flow Accounting: From Paradigm to Practice of Sustainability. Wuppertal Institute for Climate, Environment, and Energy, Germany

    Google Scholar 

  • Petersen EH (1997): Life-cycle assessment of building components. Handling uncertainties in LCAs. Paper. Building and the Environment: Proceedings of the Second International Conference. Volume 1: Assessment methods and natural resources. Centre Scientifique et Technique du Batiment, Paris

    Google Scholar 

  • Ragas AMJ, Etienne RS, Willemsen FH, Van de Meent D (1999): Assessing model uncertainty for environmental decision making: a case study of the coherence of independently derived environmental quality objectives for air and water. Environ Toxicol Chem 18, 1856–1867

    Google Scholar 

  • Singhofen A, Hemming CR, Weidema BP, Grisel L, Bretz R, De Smet B, Russell D (1996): Life cycle inventory data: development of a common format. Int J LCA 1 (3) 171–178

    Google Scholar 

  • Suh S (2000): Missing inventory estimation tool (MIET 1.2). http:// www.leidenuniv.nl/cml/ssp/software/

  • Taylor AC (1993): Using objective and subjective information to develop distributions for probabilistic exposure assessment. J Expos Anal Environ Epidem 3 (3) 285–298

    CAS  Google Scholar 

  • Vose D (1996): Quantitative risk analysis. A guide to Monte Carlo simulation modelling. John Wiley & Sons, West Sussex

    Google Scholar 

  • Weidema BP (1998): Multi-user test of the data quality matrix for product life cycle inventory data. Int J LCA 3 (5) 259–265

    Google Scholar 

  • Weidema B P. (1999). The SPOLD file format ‘99. http://www.spold.org/publ/

  • Weidema BP, Wesnæs MS (1996): Data quality management for life cycle inventories: an example of using data quality indicators. J Cleaner Prod 4 (3–4) 167–174

    Article  Google Scholar 

Download references

Author information

Author notes

  1. Mark A. J. Huijbregts

    Present address: Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Nieuwe Achtergracht 166, NL-1018, WV Amsterdam, The Netherlands

  2. Gregory Norris

    Present address: , 147 Bauneg Hill Rd., Suite 200, ME 03906, Sylvatica, North Berwick, USA

  3. Rolf Bretz

    Present address: Ciba Specialty Chemicals Inc, K-1370.A.522, POB, CH-4002, Basel, Switzerland

  4. Andreas Ciroth

    Present address: Institut fuer Technischen Umweltschutz, Abfallvermeidung und Sekundaerrohstoff-wirtschaft, Technical University Berlin, Strasse des 17. Juni 135, D-10623, Berlin, Germany

  5. Benoit Maurice

    Present address: Electricité De France, Research and Development Division, Energy Systems Branch, Site des Renardières, Ecuelles F-77 818, Moret sur Loing, France

  6. Bo von Bahr

    Present address: CPM - Centre for Environmental Assessment of Product and Material Systems Chalmers University of Technology, S-412 96, Göteborg, Sweden

  7. Bo Weidema

    Present address: 2.-0 LCA consultants, Borgergade 6, Copenhagen, Denmark

  8. Angeline S. H. de Beaufort

    Present address: FEFCO-G0-KI, Graeterweg 13, NL-6071 ND, Swalmen, The Netherlands

Authors and Affiliations

  1. Department of Environmental Sciences, Nijmegen University, Toernooiveld 1, NL-6500, GL Nijmegen, The Netherlands

    Mark A. J. Huijbregts

Authors
  1. Mark A. J. Huijbregts
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gregory Norris
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rolf Bretz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andreas Ciroth
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Benoit Maurice
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bo von Bahr
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Bo Weidema
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Angeline S. H. de Beaufort
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Huijbregts, M.A.J., Norris, G., Bretz, R. et al. Framework for modelling data uncertainty in life cycle inventories. Int J LCA 6, 127–132 (2001). https://doi.org/10.1007/BF02978728

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02978728

Key words

  • Data gaps
  • data inaccuracy
  • data uncertainty
  • unrepresentative data
  • general framework
  • life cycle inventory (LCI)
  • Monte Carlo simulation
  • sensitivity analysis
  • SETAC LCA-WG
  • Data Availability
  • Data Quality
  • uncertainty assessment
  • uncertainty importance