Valueloading And Uncertainty In A Sector-based Differentiation Scheme For Emission Allowances

Climatic Change(2005)

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摘要
The Triptych approach is a sectoral approach for differentiation of quantitative greenhouse gas emission reduction objectives. In this study we investigate the ranges in emission reduction targets that result from differences in valueladen assumptions and uncertainties in input data and parameters. In order to assess the effect of highly valueladen assumptions on resulting objectives we used two approaches. First we performed a sensitivity analysis. Then we elaborated the approach from four ideal-typical value-orientations: the administrator, the businessman, the campaigner and the survivor. For each of these value-orientations we specified corresponding sets of assumptions of highly valueladen parameters. Within each set, we also assessed uncertainties for the remaining parameters and input data. We assessed the strength and we quantified their inexactnesses with probability distribution functions. Next, we carried out Monte Carlo simulations in each of the four value-orientations to quantify error propagation from the inexactnesses in input data and parameters. We found targets for the year 2015 for Annex I countries differed up to around 20%-points over the four value-orientations. For developing countries differences in allowances were found up to the order of four. In addition, results are affected to a large extent by uncertainties in the other input data and parameters. Ranges in the outcome resulting from uncertainties are between 10 and 35%-points for Annex I countries, depending on the value-orientation chosen and between 20 and 120%-points for non-Annex I countries. However, the ranking of countries within the calculated differentiation remains roughly the same, an exception being the ranking that resulted from the businessman’s perspective. Other consistent combinations of valueladen assumptions may result in objectives that are outside the range that we based on the four value-orientations. We concluded that care should be taken when assessing valueloading in calculations schemes for emissions objectives based on a limited number of value-orientations only. Our analysis clearly underlines the relevance of making explicit policy variables in schemes for the differentiation of commitments. It is necessary to reach consensus on these variables if such schemes are to support negotiations on greenhouse gas emissions allowances.
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关键词
Input Data,Monte Carlo Simulation,Emission Reduction,Probability Distribution Function,Policy Variable
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