Environmental Modeling & Assessment

, Volume 10, Issue 1, pp 63–79 | Cite as

Application of a checklist for quality assistance in environmental modelling to an energy model

  • James Risbey
  • Jeroen van der Sluijs
  • Penny Kloprogge
  • Jerry Ravetz
  • Silvio Funtowicz
  • Serafin Corral Quintana


Large, complex energy models present considerable challenges to develop and test. Uncertainty assessments of such models provide only partial guidance on the quality of the results. We have developed a model quality assistance checklist to aid in this purpose. The model checklist provides diagnostic output in the form of a set of pitfalls for the model application. The checklist is applied here to an energy model for the problem of assessing energy use and greenhouse gas emissions. Use of the checklist suggests that results on this issue are contingent on a number of assumptions that are highly value-laden. When these assumptions are held fixed, the model is deemed capable of producing moderately robust results of relevance to climate policy over the longer term. Checklist responses also indicate that a number of details critical to policy choices or outcomes on this issue are not captured in the model, and model results should therefore be supplemented with alternative analyses.


quality assistance modelling climate energy 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    W. Keepin, Review of global energy and carbon dioxide projections, Ann. Rev. Energy 3(11) (1986) 357–392. Google Scholar
  2. [2]
    S. Funtowicz and J. Ravetz, Uncertainty and Quality in Science for Policy (Kluwer, Dordrecht, 1990) 229 pp. Google Scholar
  3. [3]
    J. van der Sluijs, Anchoring amid uncertainty. On the management of uncertainties in risk assessment of anthropogenic climate change, Universiteit Utrecht, Utrecht (1997) 260 pp. Google Scholar
  4. [4]
    N. Oreskes, K. Shrader-Frechette and K. Belitz, Verification, validation, and confirmation of numerical models in the earth sciences, Science 263(3) (1994) 641–646. Google Scholar
  5. [5]
    J. Risbey, M. Kandlikar and A. Patwardhan, Assessing integrated assessments, Clim. Change 34(3–4) (1996) 369–395. CrossRefGoogle Scholar
  6. [6]
    B. Beck, Model evaluation and performance, in: Encyclopedia of Environmetrics, Vol. 3 (John Wiley & Sons, New York, 2002) pp. 1275–1279. Google Scholar
  7. [7]
    European Commission, White paper on governance. Report of the working group: Democratizing expertise and establishing scientific reference systems (Group 1b). Technical report, European Commission, Brussels (2001) 26 pp. Google Scholar
  8. [8]
    C. Mann, Why software is so bad, Tech. Review 1(4) (2002) 33–38. Google Scholar
  9. [9]
    J. van der Sluijs, J. Risbey and J. Ravetz, Uncertainty assessment of VOC emissions from paint in the Netherlands using the nusap system, Env. Mod. Ass. (2004) in press. Google Scholar
  10. [10]
    J. Ravetz, Scientific Knowledge and Its Social Problems (Clarendon Press, Oxford, 1971), Reprint: Transaction, New Brunswick NJ (1996) 449 pp. Google Scholar
  11. [11]
    J. Ravetz, Developing principles of good practice in integrated environmental assessment, Int. J. Env. Pollution 11(3) (1999) 243–265. CrossRefGoogle Scholar
  12. [12]
    N. Nakićenović, J. Alcamo, G. Davis, B. de Vries et al., Special report on emissions scenarios: A special report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press, Cambridge, UK (2000) 599 pp. Google Scholar
  13. [13]
    B. De Vries, J. Bollen, A. Bouwman, M. den Elzen, M. Janssen and E. Kreileman, Greenhouse gas emissions in an equity-, environment- and service-oriented world: an IMAGE-based scenario for the 21st century, Tech. Forecasting and Social Change 63(2–3) (2000) 137–174. CrossRefGoogle Scholar
  14. [14]
    B. De Vries, D. van Vuuren, M. den Elzen and M. Janssen, The TARGETS-IMAGE energy regional model (TIMER): Technical documentation. Technical report, National Institute for Public Health and the Environment, Bilthoven, NL (2002), Report 481508014. Google Scholar
  15. [15]
    D. van Vuuren and B. de Vries, Mitigaton scenarios in a world oriented at sustainable development: the role of technology, efficiency and timing, Clim. Policy 1(2) (2001) 189–210. CrossRefGoogle Scholar
  16. [16]
    J. Alcamo, R. Leemans and E. Kreileman, eds., Global Change Scenarios for the 21st Century. Results from the IMAGE 2.1 Model (Elsevier Science, London, 1998) 572 pp. Google Scholar
  17. [17]
    S. Funtowicz and J. Ravetz, The worth of a songbird: ecological economics as a post-normal science, Ecol. Econ. 3(10) (1994) 197–207. CrossRefGoogle Scholar
  18. [18]
    S. Schneider, Integrated assessment modeling of global climate change: transparent rational tool for policy making or opaque screen hiding value-laden assumptions, Env. Modeling and Assessment 2(6) (1997) 229–249. CrossRefGoogle Scholar
  19. [19]
    P. Kloprogge and J. van der Sluijs, Choice processes in modelling for policy support, in: Proceedings of the International Environmental Modelling and Software Society, Vol. 1, Lugano, June 2002, IEMSS, pp. 96–101. Google Scholar
  20. [20]
    J. van der Sluijs, J. Risbey, S. Corral Quintana and J. Ravetz, Uncertainty management in complex models: the NUSAP method, in: Proceedings of the International Environmental Modelling and Software Society, Vol. 2, Lugano, June 2002, IEMSS, pp. 13–18. Google Scholar
  21. [21]
    United Nations, United Nations Framework Convention on Climate Change. Text available at (1992).
  22. [22]
    A. Petersen, P. Janssen, J. van der Sluijs, J. Risbey and J. Ravetz, RIVM/MNP guidance for uncertainty assessment and communication: Mini-checklist and quickscan questionnaire, Technical report, Netherlands Environmental Assessment Agency (2003) 15 pp. Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • James Risbey
    • 1
  • Jeroen van der Sluijs
    • 2
  • Penny Kloprogge
    • 2
  • Jerry Ravetz
    • 3
  • Silvio Funtowicz
    • 4
  • Serafin Corral Quintana
    • 5
  1. 1.School of Mathematical SciencesMonash UniversityAustralia
  2. 2.Copernicus InstituteUniversiteit UtrechtUtrechtThe Netherlands
  3. 3.Research Methods ConsultancyLondonUK
  4. 4.Institute for the Protection and the Security of the Citizen, EC-JRCIspraItaly
  5. 5.Economia de las InstitucionesUniversity of La LagunaSpain

Personalised recommendations