Compliance and emission trading rules for asymmetric emission uncertainty estimates
Greenhouse gases emission inventories are computed with rather low precision. Moreover, their uncertainty distributions may be asymmetric. This should be accounted for in the compliance and trading rules. In this paper we model the uncertainty of inventories as intervals or using fuzzy numbers. The latter allows us to better shape the uncertainty distributions. The compliance and emission trading rules obtained generalize the results for the symmetric uncertainty distributions that were considered in the earlier papers by the present authors (Nahorski et al., Water Air & Soil Pollution. Focus 7(4–5):539–558, 2007; Nahorski and Horabik, 2007, J Energy Eng 134(2):47–52, 2008). However, unlike in the symmetric distribution, in the asymmetric fuzzy case it is necessary to apply approximations because of nonlinearities in the formulas. The final conclusion is that the interval uncertainty rules can be applied, but with a much higher substitutional noncompliance risk, which is a parameter of the rules.
KeywordsMembership Function Fuzzy Number Kyoto Protocol Emission Trading Interval Uncertainty
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- Bandemer H (2006) Mathematics of uncertainty. In: Studies in fuzziness and soft computing, vol 189. Springer Verlag, New YorkGoogle Scholar
- Dubois D, Prade H (2005) Fuzzy intervals versus fuzzy numbers: is there a missing concept in fuzzy set theory? In: Proc. 25th Linz seminar fuzzy set theory, Linz, AustriaGoogle Scholar
- Hurteaux MD, Hungate BA, Koch GW (2009) Accounting for risk in valuing forest carbon offset. Carbon Balance and Management 4:1. http://www.cbmjournal.com/content/4/1/1
- Mignone BK, Hurteau MD, Chen Y, Sohngen B (2009) Carbon offsets, reversal risk and US climate policy. Carbon Balance and Management 4:3. http://www.cbmjournal.com/content/4/1/3
- Nahorski Z, Horabik J (2007) Compliance and emission trading rules for uncertain estimates of inventory uncertainty. In: Proc 2nd int workshop on uncertainty in greenhouse gas inventories. IIASA, Laxenburg, pp 149–161Google Scholar
- Ramirez AR, de Keizer C, van der Sluijs JP (2006) Monte Carlo analysis of uncertainties in The Netherlands greenhouse gas emission inventory for 1990–2004. Report NWS-E-2006-58. Copernicus Institute for Sustainable Development and Innovation. Utrecht. http://www.chem.uu.nl/nws/www/publica/publicaties2006/E2006-58.pdf
- Stern N (2007) The economics of climate change. In: The stern review. Cambridge University Press, CambridgeGoogle Scholar
- Winiwarter W (2004) National greenhouse gas inventories: understanding uncertainties versus potential for improving reliability. Water, Air & Soil Pollution. Focus 7(4–5):443–450Google Scholar
- Winiwarter W, Muik B (2007) Statistical dependences in input data of national GHG emission inventories: effects on the overall GHG uncertainty and related policy issues. In: Presentation at 2nd int workshop uncertainty in greenhouse gas inventories, IIASA, Laxenburg, Austria, 27–28 September 2007. http://www.ibspan.waw.pl/ghg2007/Presentation/Winiwarter.pdf