G2TT
来源类型Monograph (IIASA Interim Report)
规范类型报告
Reporting GHG Emissions: Change in Uncertainty and Its Relevance for Detection of Emission Changes.
Hamal K
发表日期2010
出版者IIASA, Laxenburg, Austria: IR-10-003
出版年2010
语种英语
摘要Uncertainty in the inventories of greenhouse gas emissions that countries report under the Kyoto Protocol to demonstrate that they are in compliance can obstruct, and in some cases paralyze, implementation of the Protocol. If uncertainty in emissions is equal to, or greater than, a country's committed change in emissions, it is not possible to determine the direction of these changes at the end of the commitment period - even if the country reports emission inventories that comply with its commitments. As a consequence, uncertainty also poses difficulties for trading of emissions quotas. This study analyzes the relative uncertainty in emissions of greenhouse gases over time that countries report in their annual national inventories under the Kyoto Protocol to the United Nations Framework Convention on Climate Change. The analysis shows how to take advantage of emissions estimates that are recalculated annually and how this knowledge can be used to estimate biases (systematic errors) that are included in the reporting (first-order approximation or one-sided view). This study focuses on the EU- 15 as a whole, with examples drawn from individual countries. The study advances the use of preparatory signal detection techniques (developed by Jonas et al. in IR-04-024). These techniques assume that our knowledge of uncertainty in the commitment year/period in relative terms will be as good as the knowledge we have today. The study provides first-ever estimates of changes in uncertainty due to learning and structural change.
主题Forestry (FOR) ; Young Scientists Summer Program (YSSP)
URLhttp://pure.iiasa.ac.at/id/eprint/9476/
来源智库International Institute for Applied Systems Analysis (Austria)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/125805
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Hamal K. Reporting GHG Emissions: Change in Uncertainty and Its Relevance for Detection of Emission Changes.. 2010.
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