Economic impacts of tipping points in the climate system

被引:107
作者
Dietz, Simon [1 ,2 ]
Rising, James [3 ]
Stoerk, Thomas [2 ]
Wagner, Gernot [4 ,5 ]
机构
[1] London Sch Econ & Polit Sci, Dept Geog & Environm, London WC2A 2AE, England
[2] London Sch Econ & Polit Sci, Grantham Res Inst Climate Change & Environm, London WC2A 2AE, England
[3] Univ Delaware, Coll Earth Ocean & Environm, Newark, DE 19716 USA
[4] NYU, Dept Environm Studies, New York, NY 10003 USA
[5] NYU, Robert F Wagner Grad Sch Publ Serv, New York, NY 10003 USA
基金
欧盟地平线“2020”;
关键词
climate tipping points; social cost of carbon; integrated assessment model; climate risk; CARBON-DIOXIDE; SOCIAL COST; TEMPERATURE; POLICY; RISK; ELEMENTS; MODELS; PANEL;
D O I
10.1073/pnas.2103081118
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Climate scientists have long emphasized the importance of climate tipping points like thawing permafrost, ice sheet disintegration, and changes in atmospheric circulation. Yet, save for a few fragmented studies, climate economics has either ignored them or represented them in highly stylized ways. We provide unified estimates of the economic impacts of all eight climate tipping points covered in the economic literature so far using a meta-analytic integrated assessment model (IAM) with a modular structure. The model includes national-level climate damages from rising temperatures and sea levels for 180 countries, calibrated on detailed econometric evidence and simulation modeling. Collectively, climate tipping points increase the social cost of carbon (SCC) by similar to 25% in our main specification. The distribution is positively skewed, however. We estimate an similar to 10% chance of climate tipping points more than doubling the SCC. Accordingly, climate tipping points increase global economic risk. A spatial analysis shows that they increase economic losses almost everywhere. The tipping points with the largest effects are dissociation of ocean methane hydrates and thawing permafrost. Most of our numbers are probable underestimates, given that some tipping points, tipping point interactions, and impact channels have not been covered in the literature so far; however, our method of structural meta-analysis means that future modeling of climate tipping points can be integrated with relative ease, and we present a reduced-form tipping points damage function that could be incorporated in other IAMs.
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页数:9
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