气候变化领域集成服务门户(CCPortal): Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile

CCPortal

DOI	10.1080/14693062.2018.1503153
	Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile
	O’ Ryan R.; Benavides C.; Díaz M.; San Martín J.P.; Mallea J.
发表日期	2019
ISSN	14693062
起始页码	299
结束页码	314
卷号	19 期号:3
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.
英文关键词	climate change policy; emission baselines; Energy systems modelling; nationally determined contributions; probabilistic analysis; uncertainty
语种	英语
scopus关键词	carbon emission; climate change; developing world; environmental policy; forecasting method; greenhouse gas; probability; uncertainty analysis; Chile
来源期刊	Climate Policy
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/153424
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
推荐引用方式 GB/T 7714	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],2019,19(3).
APA	O’ Ryan R.,Benavides C.,Díaz M.,San Martín J.P.,&Mallea J..(2019).Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile.Climate Policy,19(3).
MLA	O’ Ryan R.,et al."Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile".Climate Policy 19.3(2019).