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AI 根据所提供的论文材料归类:摘要主要讨论气候情景构造与政策风险评估,未明确采用所列细分领域中的识别或计量框架。

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关注这篇论文的作者
J. Isaac Miller
William A. Brock

超越 RCP8.5:利用准代表性浓度路径评估边际减排

研究问题
当减排政策的规模较小、未被既有代表性浓度路径覆盖时,如何评估其气候损害变化,并以较低计算成本刻画不确定性?
方法与思路
作者利用既有同行评审情景的浓度路径构造计算高效的准代表性浓度路径,并通过自助法评估不确定性,以英国净零目标下伦敦热应激死亡风险为例。
材料陈述的贡献
摘要称,该方法将评估范围扩展到传统情景未覆盖的较温和政策变化;伦敦案例提示,英国单独实现其政策目标对降低所考察风险作用有限。
阅读关注点
应核对准代表性路径的构造与适用范围、浓度到死亡风险的映射、自助法覆盖的不确定性来源,以及疫情类死亡事件比较的口径。
阅读边界
仅据所给出版社摘要,无法判断路径近似误差、风险区间的具体数值或英国政策结果的外推范围;摘要未说明刊本与其他版本的差异。

原文摘要

Assessments of decreases in economic damages from climate change mitigation typically rely on climate output from computationally expensive pre-computed runs of general circulation models under a handful of scenarios with discretely varying targets, such as the four representative concentration pathways for CO2 and other anthropogenically emitted gases. Although such analyses are valuable in informing scientists and policymakers about massive multilateral mitigation goals, we add to the literature by considering potential outcomes from more modest policy changes that may not be represented by any well-known concentration pathway. Specifically, we construct computationally efficient Quasi-representative Concentration Pathways (QCPs) to leverage concentration pathways of existing peer-reviewed scenarios. Computational efficiency allows for bootstrapping to assess uncertainty. We illustrate our methodology by considering the impact on the relative risk of mortality from heat stress in London from the United Kingdom’s net zero emissions goal. More than half of our interval estimate for the business-as-usual scenario covers an annual risk at least that of a COVID-19-like mortality event by 2100. Success of the UK’s policy alone would do little to mitigate the risk.

笔记与分组