Scopus记录号: 2-s2.0-85052076897
论文题名: Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile
作者: O’ Ryan R. ; Benavides C. ; Díaz M. ; San Martín J.P. ; Mallea J.
刊名: Climate Policy
ISSN: 14693062
出版年: 2019
卷: 19, 期: 3 起始页码: 299
结束页码: 314
语种: 英语
英文关键词: climate change policy
; emission baselines
; Energy systems modelling
; nationally determined contributions
; probabilistic analysis
; uncertainty
Scopus关键词: carbon emission
; climate change
; developing world
; environmental policy
; forecasting method
; greenhouse gas
; probability
; uncertainty analysis
; Chile
英文摘要: In this paper, initial steps are presented toward characterizing, quantifying, incorporating and communicating uncertainty applying a probabilistic analysis to countrywide emission baseline forecasts, using Chile as a case study. Most GHG emission forecasts used by regulators are based on bottom-up deterministic approaches. Uncertainty is usually incorporated through sensitivity analysis and/or use of different scenarios. However, much of the available information on uncertainty is not systematically included. The deterministic approach also gives a wide range of variation in values without a clear sense of probability of the expected emissions, making it difficult to establish both the mitigation contributions and the subsequent policy prescriptions for the future. To improve on this practice, we have systematically included uncertainty into a bottom-up approach, incorporating it in key variables that affect expected GHG emissions, using readily available information, and establishing expected baseline emissions trajectories rather than scenarios. The resulting emission trajectories make explicit the probability percentiles, reflecting uncertainties as well as possible using readily available information in a manner that is relevant to the decision making process. Additionally, for the case of Chile, contradictory deterministic results are eliminated, and it is shown that, whereas under a deterministic approach Chile’s mitigation ambition does not seem high, the probabilistic approach suggests this is not necessarily the case. It is concluded that using a probabilistic approach allows a better characterization of uncertainty using existing data and modelling capacities that are usually weak in developing country contexts. Key policy insights Probabilistic analysis allows incorporating uncertainty systematically into key variables for baseline greenhouse gas emission scenario projections. By using probabilistic analysis, the policymaker can be better informed as to future emission trajectories. Probabilistic analysis can be done with readily available data and expertise, using the usual models preferred by policymakers, even in developing country contexts. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. 资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/122581
Appears in Collections: 气候变化事实与影响
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作者单位: EARTH Center, Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, and Center for Climate and Resilience Research (CR2), Santiago, Chile; Energy Center, Department of Electrical Engineering, Universidad de Chile, Santiago, Chile; Department of Industrial Engineering, Universidad de Chile, Santiago, Chile
Recommended Citation:
O’ Ryan R.,Benavides C.,Díaz M.,et al. Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile[J]. Climate Policy,2019-01-01,19(3)