Practical Policy Applications of Uncertainty Analysis for National Greenhouse Gas Inventories



International policy makers and climate researchers use greenhouse gas emissions inventory estimates in a variety of ways. Because of the varied uses of the inventory data, as well as the high uncertainty surrounding some of the source category estimates, considerable effort has been devoted to understanding the causes and magnitude of uncertainty in national emissions inventories. In this paper, we focus on two aspects of the rationale for quantifying uncertainty: (1) the possible uses of the quantified uncertainty estimates for policy (e.g., as a means of adjusting inventories used to determine compliance with international commitments); and (2) the direct benefits of the process of investigating uncertainties in terms of improving inventory quality. We find that there are particular characteristics that an inventory uncertainty estimate should have if it is to be used for policy purposes: (1) it should be comparable across countries; (2) it should be relatively objective, or at least subject to review and verification; (3) it should not be subject to gaming by countries acting in their own self-interest; (4) it should be administratively feasible to estimate and use; (5) the quality of the uncertainty estimate should be high enough to warrant the additional compliance costs that its use in an adjustment factor may impose on countries; and (6) it should attempt to address all types of inventory uncertainty. Currently, inventory uncertainty estimates for national greenhouse gas inventories do not have these characteristics. For example, the information used to develop quantitative uncertainty estimates for national inventories is often based on expert judgments, which are, by definition, subjective rather than objective, and therefore difficult to review and compare. Further, the practical design of a potential factor to adjust inventory estimates using uncertainty estimates would require policy makers to (1) identify clear environmental goals; (2) define these goals precisely in terms of relationships among important variables (such as emissions estimate, commitment level, or statistical confidence); and (3) develop a quantifiable adjustment mechanism that reflects these environmental goals. We recommend that countries implement an investigation-focused (i.e., qualitative) uncertainty analysis that will (1) provide the type of information necessary to develop more substantive, and potentially useful, quantitative uncertainty estimates-regardless of whether those quantitative estimates are used for policy purposes; and (2) provide information needed to understand the likely causes of uncertainty in inventory data and thereby point to ways to improve inventory quality (i.e., accuracy, transparency, completeness, and consistency).


adjustment data quality emissions greenhouse gas inventory Kyoto Protocol trading ratio uncertainty uncertainty analysis UNFCCC 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bartoszczuk, P., & Horabik, J. (2007). Tradable permit system: Considering uncertainty in emission estimates. Water, Air, & Soil Pollution: Focus (in press) doi:10.1007/s11267-006-9110-xGoogle Scholar
  2. Cohen, J., Sussman, F., & Jayaraman, K. (1998). Improving Greenhouse Gas Emission Verification, Final report prepared by ICF Consulting and submitted to Environment Canada, 2 January. Subsequently released as an Environment Canada Report, February.Google Scholar
  3. ISO (1993). International vocabulary of basic and general terms in metrology, Second edition. Geneva, Switzerland: ISO (International Organization for Standardization).Google Scholar
  4. Jonas, M., & Nilsson, S. (2007). Prior to economic treatment of emissions and their uncertainties under the Kyoto Protocol: Scientific uncertainties that must be kept in mind. Water, Air, & Soil Pollution: Focus (in press) doi:10.1007/s11267-006-9113-7Google Scholar
  5. Kasa, K. (2000). Knightian uncertainty and home bias. Federal Reserve Bank of San Francisco Economic Letter. (October 6)Google Scholar
  6. King, D. M., & Kuch, P. J. (2003). Will nutrient trading ever work? An assessment of supply and demand problems and institutional obstacles. 33 ELR 10352, Environmental Law Institute, Washington, DC, USA.Google Scholar
  7. Knight, F. H. (1921). A treatise on probability. London, UK: Macmillan.Google Scholar
  8. Monni, S., Syri, S., Pipatti, R., & Savolainen, I. (2007). Extension of EU emissions trading scheme to other sectors and gases: Consequences for uncertainty of total tradable amount. Water, Air, & Soil Pollution: Focus (in press) doi:10.1007/s11267-006-9111-9Google Scholar
  9. Morgan, M. G., & Henrion, M. (1990). Uncertainty: A guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge, UK: Cambridge University Press.Google Scholar
  10. Nahorski, Z., Horabik, J., & Jonas, M. (2007). Compliance and emissions trading under the Kyoto Protocol: Rules for uncertain inventories. Water, Air, & Soil Pollution: Focus (in press) doi:10.1007/s11267-006-9112-8Google Scholar
  11. Nilsson, S., Shvidenko, A., Jonas, M., & McCallum, I. (2007). Uncertainties of a regional terrestrial biota full carbon account: A systems analysis. Water, Air, & Soil Pollution: Focus (in press) doi:10.1007/s11267-006-9119-1Google Scholar
  12. Nishimura, K. G., & Ozaki, H. (2001). Search and Knightian uncertainty. Working paper, University of Tokyo, Japan.Google Scholar
  13. Rousse, O., & Sévi, B. (2007). The impact of uncertainty on banking behavior: Evidence from the US sulfur dioxide emissions allowance trading program. Water, Air, & Soil Pollution: Focus (in press) doi:10.1007/s11267-006-9109-3Google Scholar
  14. Rypdal, K., & Winiwarter, W. (2000). Uncertainties in greenhouse gas emission inventories — evaluation, comparability and implications. Environmental Science and Policy, 107–116.Google Scholar
  15. Sussman, F. (1998). Compliance and uncertainty in emissions inventories. Presentation to UNCTAD meeting on verification and accountability, London, UK, 6 April.Google Scholar
  16. Sussman, F., Cohen, J., & Jayaraman, K. R. (1998). Uncertain emissions inventories, compliance, and trading. Presentation at Global Climate Change: Science, Policy, and Mitigation/Adaptation Strategies, Annual meeting of the Air & Waste Management Association, Washington, D.C., USA 13–15 October.Google Scholar
  17. Taylor, J. R. (1997). An introduction to error analysis: The study of uncertainties in physical measurement, Second edition. Sausalito, CA, USA: University Science Books.Google Scholar
  18. UNFCCC (2000). Views from parties on national systems, adjustments and guidelines under Articles 5, 7 and 8 of the Kyoto Protocol. FCCC/SBSTA/2000/MISC.1, 24 February.Google Scholar
  19. Webster, M., Forest, C., Reilly, J., Babiker, M., Kicklighter, D., Mayer, M., et al. (2003). Uncertainty analysis of climate change and policy response. Climate Change, 61, 295–320.CrossRefGoogle Scholar
  20. Winiwarter, W. (2007). National greenhouse gas inventories: Understanding uncertainties versus potential for improving reliability. Water, Air, & Soil Pollution: Focus (in press) doi:10.1007/s11267-006-9117-3Google Scholar
  21. Winiwarter, W., & Rypdal, K. (2001). Assessing the uncertainty associated with national greenhouse gas emission inventories: A case study for Austria. Atmospheric Environment, 5425–5440.Google Scholar

Copyright information

© Springer Science + Business Media B.V. 2007

Authors and Affiliations

  1. 1.Environmental Resources TrustWashington, DCUSA
  2. 2.ICF InternationalWashington, DCUSA

Personalised recommendations