气候变化
国内生产总值
环境科学
气候学
作业成本法
地理
航程(航空)
概率逻辑
气象学
自然资源经济学
经济
统计
经济增长
数学
生态学
复合材料
地质学
会计
材料科学
生物
作者
Solomon Hsiang,Robert E. Kopp,Amir Jina,James Rising,Michael Delgado,Shashank Mohan,D. J. Rasmussen,Robert Muir‐Wood,Paul Wilson,Michael Oppenheimer,Kate Larsen,Trevor Houser
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2017-06-30
卷期号:356 (6345): 1362-1369
被引量:1176
标识
DOI:10.1126/science.aal4369
摘要
Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors-agriculture, crime, coastal storms, energy, human mortality, and labor-increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).
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