Quantifying the economic risks of climate change


Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost–benefit integrated assessment models, with guidance for future work.

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Figure 1: Schematic representation of the complex series of physical and socioeconomic processes and relationships encompassed by a damage function.
Figure 2: Damage estimates projected by the DICE, FUND and PAGE models at different levels of temperature change, corresponding to 2100 socioeconomics.


  1. 1

    Interagency Working Group on Social Cost of Carbon. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 1–50 (United States Government, Washington DC, 2010).

  2. 2

    Rose, S. K., Diaz, D. B. & Blanford, G. J. Understanding the social cost of carbon: a model diagnostic and inter-comparison study. Clim. Chang. Econ. 8, 1750009 (2017). An in-depth examination of the DICE, FUND and PAGE integrated assessment models used by the US Government to estimate the social cost of carbon with detailed decomposition and comparison of intermediate results.

    Google Scholar 

  3. 3

    Revesz, R. et al. Improve economic models of climate change. Nature 508, 173–175 (2014).

    Google Scholar 

  4. 4

    Burke, M. et al. Opportunities for advances in climate change economics. Science 352, 292–293 (2016).

    CAS  Google Scholar 

  5. 5

    Stern, N. The structure of economic modeling of the potential impacts of climate change: grafting gross underestimation of risk onto already narrow science models. J. Econ. Lit. 51, 838–859 (2013).

    Google Scholar 

  6. 6

    National Academies of Sciences, Engineering, and Medicine. Valuing Climate Damages: Updating Estimation of the Social Cost of Carbon Dioxide (National Academies Press, 2017). Comprehensive report examining potential approaches for updating the methodology for estimating the social cost of carbon dioxide for US regulatory analysis.

  7. 7

    Nordhaus, W. RICE-2010 and DICE-2010 Models (last accessed 20 March 2012); http://www.econ.yale.edu/nordhaus/homepage/RICEmodels.htm

    Google Scholar 

  8. 8

    Anthoff, D. & Tol, R. S. J. FUND v.3.8 Scientific Documentation (2014); http://www.fund-model.org/versions

  9. 9

    Hope, C. W. The PAGE09 Integrated Assessment Model: A Technical Description. Working Paper (Cambridge Judge Business School, 2011).

    Google Scholar 

  10. 10

    Ackerman, F. & Munitz, C. Climate damages in the FUND model: a disaggregated analysis. Ecol. Econ. 77, 219–224 (2012).

    Google Scholar 

  11. 11

    Tol, R. S. J. Estimates of the damage costs of climate change, Part II. Dynamic estimates. Environ. Resour. Econ. 21, 135–160 (2002). A methodology for modeling dynamic factors such as socioeconomic levels affecting vulnerability for eight major climate impact categories.

    Google Scholar 

  12. 12

    Anthoff, D. & Tol, R. S. J. in Climate Change and Common Sense: Essays in Honour of Tom Schelling, 260–273 (Oxford Univ. Press, 2012).

    Google Scholar 

  13. 13

    Nordhaus, W. D. Economic aspects of global warming in a post-Copenhagen environment. Proc. Natl Acad. Sci. USA 107, 11721–11726 (2010).

    CAS  Google Scholar 

  14. 14

    Weyant, J. Some contributions of integrated assessment models of global climate change. Rev. Environ. Econ. Policy 11, 115–137 (2017). Comprehensive overview of the use of IAMs in global policy analysis, discussing challenges and open issues.

    Google Scholar 

  15. 15

    Calvin, K. et al. GCAM Wiki documentation (Pacific Northwest National Laboratory, 2011); http://jgcri.github.io/gcam-doc/

    Google Scholar 

  16. 16

    Sokolov, A., Schlosser, C., Dutkiewicz, S. & Paltsev, S. MIT Integrated Global System Model (IGSM) Version 2: Model Description and Baseline Evaluation (2005); https://dspace.mit.edu/handle/1721.1/29789

    Google Scholar 

  17. 17

    Stehfest, E., Vuuren, D. van, Bouwman, L. & Kram, T. Integrated Assessment of Global Environmental Change with Image 3.0: Model Description and Policy Applications (2014); http://dspace.library.uu.nl/handle/1874/308545

    Google Scholar 

  18. 18

    Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

    CAS  Google Scholar 

  19. 19

    O'Neill, B. C. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change 122, 387–400 (2014).

    Google Scholar 

  20. 20

    Calvin, K., Wise, M., Clarke, L., Edmonds, J. & Kyle, P. Implications of simultaneously mitigating and adapting to climate change: initial experiments using GCAM. Climatic Change 117, 545–560 (2013).

    Google Scholar 

  21. 21

    Kyle, P., Müller, C., Calvin, K. & Thomson, A. Meeting the radiative forcing targets of the representative concentration pathways in a world with agricultural climate impacts. Earth's Future 2, http://dx.doi.org/10.1002/2013EF000199 (2014).

  22. 22

    Zhou, Y., Eom, J. & Clarke, L. The effect of global climate change, population distribution, and climate mitigation on building energy use in the US and China. Climatic Change 119, 979–992 (2013).

    Google Scholar 

  23. 23

    Hejazi, M. I. et al. Integrated assessment of global water scarcity over the 21st century under multiple climate change mitigation policies. Hydrol. Earth Syst. Sci. 18, 2859–2883 (2014).

    Google Scholar 

  24. 24

    Blanc, E. et al. Modeling U. S. water resources under climate change. Earth's Future 2, 197–224 (2014).

    Google Scholar 

  25. 25

    Huber, V. et al. Climate impact research: beyond patchwork. Earth Syst. Dyn. 5, 399–408 (2014).

    Google Scholar 

  26. 26

    Waldhoff, S. T. et al. Overview of the special issue: a multi-model framework to achieve consistent evaluation of climate change impacts in the United States. Climatic Change 131, 1–20 (2015).

    CAS  Google Scholar 

  27. 27

    O'Neill, B. C. et al. The Benefits of Reduced Anthropogenic Climate changE (BRACE): a synthesis. Climatic Change https://doi.org/10.1007/s10584-017-2009-x (2017).

    Google Scholar 

  28. 28

    Rosenzweig, C. et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268–3273 (2014).

    CAS  Google Scholar 

  29. 29

    Knutti, R., Furrer, R., Tebaldi, C., Cermak, J. & Meehl, G. A. Challenges in combining projections from multiple climate models. J. Clim. 23, 2739–2758 (2010).

    Google Scholar 

  30. 30

    Warszawski, L. et al. The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework. Proc. Natl Acad. Sci. USA 111, 3228–3232 (2014). Example of recent multisector coordinated modeling initiative using standardized scenarios and input assumptions.

    CAS  Google Scholar 

  31. 31

    Roson, R. & Sartori, M. Estimation of Climate Change Damage Functions for 140 Regions in the GTAP9 Database (World Bank, 2016).

    Google Scholar 

  32. 32

    Greenstone, M., Houser, T., Hsiang, S. M. & Kopp, R. E. Climate Impact Lab; http://www.impactlab.org/

  33. 33

    Arnell, N. W. et al. The Impacts of Climate Change Avoided by Future Reductions in Emissions as Defined in the Intended Nationally-Determined Contributions (AVOID 2, UK Government, 2015).

    Google Scholar 

  34. 34

    Houser, T., Hsiang, S., Kopp, R. & Larsen, K. Economic Risks of Climate Change: An American Prospectus (Columbia Univ. Press, 2015).

    Google Scholar 

  35. 35

    Ciscar, J.-C. et al. Climate Impacts in Europe — The JRC PESETA II Project, Vol. 26586 (Publications Office of the European Union, 2014).

    Google Scholar 

  36. 36

    Bosello, F., Eboli, F. & Pierfederici, R. Assessing the economic impacts of climate change — an updated CGE point of view. SSRN Electron. J. http://dx.doi.org/10.2139/ssrn.2004966 (2012).

  37. 37

    Moore, F. C., Baldos, U., Hertel, T. W. & Diaz, D. B. New science of climate change impacts on agriculture implies higher social cost of carbon. Nat. Commun. (in the press); https://doi.org/10.1038/s41467-017-01792-x

  38. 38

    Carleton, T. & Hsiang, S. Social and economic impacts of climate change. Science 353, aad9837 (2016).

    Google Scholar 

  39. 39

    Dell, M., Jones, B. F. & Olken, B. A. What do we learn from the weather? The new climate-economy literature. J. Econ. Lit. 53, 740–798 (2014). Comprehensive review of the growing empirical literature on weather effects using panel data, with implications for economic research.

    Google Scholar 

  40. 40

    Hsiang, S. M., Burke, M. & Miguel, E. Quantifying the influence of climate on human conflict. Science 341, 1235367 (2013).

    Google Scholar 

  41. 41

    Fishman, R., Russ, J. & Carrillo, P. Long-Term Impacts of High Temperatures on Economic Productivity (2015); https://ideas.repec.org/p/gwi/wpaper/2015-18.html

    Google Scholar 

  42. 42

    Seppanen, O., Fisk, W. J. & Lei, Q. Effect of Temperature on Task Performance in Office Environments (LBNL, 2006).

    Google Scholar 

  43. 43

    Obradovich, N. Climate change may speed democratic turnover. Climatic Change 140, 135–147 (2017).

    Google Scholar 

  44. 44

    Mendelsohn, R., Nordhaus, W. D. & Shaw, D. The impact of global warming on agriculture: a Ricardian analysis. Am. Econ. Rev. 84, 753–771 (1994).

    Google Scholar 

  45. 45

    Schlenker, W. & Roberts, D. L. Nonlinear temperature effects indicate severe damages to US corn yields under climate change. Proc. Natl Acad. Sci. USA 106, 15594–15598 (2009).

    CAS  Google Scholar 

  46. 46

    Tack, J., Barkley, A. & Nalley, L. L. Effect of warming temperatures on US wheat yields. Proc. Natl Acad. Sci. USA 112, 6931–6936 (2015).

    CAS  Google Scholar 

  47. 47

    Lobell, D. B., Banziger, M., Magorokosho, C. & Vivek, B. Nonlinear heat effects on African maize as evidenced by historical yield trials. Nat. Clim. Change 1, 42–45 (2011).

    Google Scholar 

  48. 48

    Auffhammer, Maximilian and Anin Aroonruengsawat. Hotspots of Climate-Driven Increases in Residential Electricity Demand: A Simulation Exercise Based on Household Level Billing Data for California. Publication number: CEC-500-2012-021 (California Climate Change Center, California Energy Commission, 2012).

  49. 49

    Davis, L. W. & Gertler, P. J. Contribution of air conditioning adoption to future energy use under global warming. Proc. Natl Acad. Sci. USA 112, 5962–5927 (2015).

    CAS  Google Scholar 

  50. 50

    Deschênes, O. & Greenstone, M. Climate change, mortality, and adaptation: evidence from annual fluctuations in weather in the US. Am. Econ. J. Appl. Econ. 3, 152–185 (2011).

    Google Scholar 

  51. 51

    Barreca, A., Clay, K., Deschenes, O., Greenstone, M. & Shapiro, J. S. Adapting to climate change: the remarkable decline in the US temperature–mortality relationship over the 20th century. J. Polit. Econ. 124, 105–159 (2013).

    Google Scholar 

  52. 52

    Barreca, A. Climate change, humidity, and mortality in the United States. J. Environ. Econ. Manage. 63, 19–34 (2012).

    Google Scholar 

  53. 53

    Deschênes, O., Greenstone, M. & Guryan, J. Climate change and birth weight. Am. Econ. Rev. Pap. Proc. 99, 211–217 (2009).

    Google Scholar 

  54. 54

    Heal, G. & Park, J. Feeling the Heat: Temperature, Physiology & the Wealth of Nations (2013); http://www.nber.org/papers/w19725

    Google Scholar 

  55. 55

    Graff Zivin, J. & Neidell, M. Temperature and the allocation of time: implications for climate change. J. Labor Econ. 32, 1–26 (2014).

    Google Scholar 

  56. 56

    Ranson, M. Crime, weather, and climate change. J. Environ. Econ. Manage. 67, 274–302 (2014).

    Google Scholar 

  57. 57

    Hsiang, S. et al. Estimating economic damage from climate change in the United States. Science 356, 1362–1369 (2017). Recent multisector assessment of US climate damages at high spatial resolution of both physical and economic impacts, with a focus on empirical support for sectoral damage functions.

    CAS  Google Scholar 

  58. 58

    Hsiang, S. Climate econometrics. Ann. Rev. Res. Econ. 8, 43–75 (2016).

    Google Scholar 

  59. 59

    Deschênes, O. & Greenstone, M. The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. Am. Econ. Rev. 97, 354–385 (2007).

    Google Scholar 

  60. 60

    Lemoine, D. & Kapnick, S. A top-down approach to projecting market impacts of climate change. Nat. Clim. Change 6, 51–55 (2016).

    Google Scholar 

  61. 61

    Dell, M., Jones, B. F. & Olken, B. A. Temperature shocks and economic growth: evidence from the last half century. Am. Econ. J. Macroecon. 4, 66–95 (2012).

    Google Scholar 

  62. 62

    Burke, M., Hsiang, S. M. & Miguel, E. Global non-linear effect of temperature on economic production. Nature 527, 235–239 (2015).

    CAS  Google Scholar 

  63. 63

    Moore, F. C. & Diaz, D. B. Temperature impacts on economic growth warrant stringent mitigation policy. Nat. Clim. Change 5, 127–131 (2015).

    Google Scholar 

  64. 64

    IPCC: Summary for Policymakers. In Climate Change 2007: Impacts, Adaptation and Vulnerability (eds Parry, M. L. et al.) (Cambridge Univ. Press, 2007).

  65. 65

    Tol, R. S. J. The economic effects of climate change. J. Econ. Perspect. 23, 29–51 (2009).

    Google Scholar 

  66. 66

    Anthoff, D., Nicholls, R. J., Tol, R. S. J. & Vafeidis, A. T. Global and Regional Exposure to Large Rises in Sea-Level: A Sensitivity Analysis (2006); http://www.tyndall.ac.uk/sites/default/files/wp96_0.pdf

    Google Scholar 

  67. 67

    Warren, R. et al. Spotlighting Impacts Functions in Integrated Assessment (Tyndall Centre for Climate Change Research, 2006).

    Google Scholar 

  68. 68

    Nordhaus, W. D. Expert opinion on climatic change. Am. Sci. 82, 45–51 (1994).

    Google Scholar 

  69. 69

    Ackerman, F., Stanton, E. A., Hope, C. W. & Alberth, S. Did the Stern Review underestimate US and global climate damages? Energy Policy 37, 2717–2721 (2009).

    Google Scholar 

  70. 70

    Weitzman, M. L. GHG targets as insurance against catastrophic climate damages. J. Public Econ. Theory 14, 221–244 (2012). Describes how fat-tailed climate risks affect the cost–benefit analysis of climate change, highlighting limitations in the treatment of: uncertainty, risk, discounting and welfare (in the face of catastrophic outcomes).

    Google Scholar 

  71. 71

    Dietz, S. & Stern, N. Endogenous growth, convexity of damage and climate risk: how Nordhaus' framework supports deep cuts in carbon emissions. Econ. J. 125, 574–620 (2015).

    Google Scholar 

  72. 72

    Ackerman, F. & Stanton, E. A. Climate risks and carbon prices: revising the social cost of carbon. Economics 6, 1–25 (2012).

    Google Scholar 

  73. 73

    van den Bergh, J. C. J. M. & Botzen, W. J. W. A lower bound to the social cost of CO2 emissions. Nat. Clim. Change 4, 253–258 (2014).

    Google Scholar 

  74. 74

    Nordhaus, W. D. To slow or not to slow: the economics of the greenhouse effect. Econ. J. 101, 920–937 (1991).

    Google Scholar 

  75. 75

    Warren, R. The role of interactions in a world implementing adaptation and mitigation solutions to climate change. Phil. Trans. R. Soc. A 369, 217–41 (2011).

    CAS  Google Scholar 

  76. 76

    Marten, A. L. et al. Improving the assessment and valuation of climate change impacts for policy and regulatory analysis. Climatic Change 117, 433–438 (2013).

    Google Scholar 

  77. 77

    Watkiss, P. Aggregate economic measures of climate change damages: explaining the differences and implications. Wiley Interdiscip. Rev. Clim. Change 2, 356–372 (2011).

    Google Scholar 

  78. 78

    Howard, P. Omitted Damages: What's Missing from the Social Cost of Carbon. (2014); http://go.nature.com/2wKYTcF

    Google Scholar 

  79. 79

    Watkiss, P. & Downing, T. E. The social cost of carbon: valuation estimates and their use in UK policy. Integr. Assess. J. Bridg. Sci. Policy 8, 85–105 (2008).

    Google Scholar 

  80. 80

    Neumann, J. E. & Strzepek, K. State of the literature on the economic impacts of climate change in the United States. J. Benefit Cost Anal. 5, 411–443 (2014).

    Google Scholar 

  81. 81

    Kopp, R. E. & Mignone, B. B. K. The US government's social cost of carbon estimates after their first two years: pathways for improvement. Economics E-Journal 6, 1–41 (2012).

    Google Scholar 

  82. 82

    Bell, A., Zhu, T., Xie, H. & Ringler, C. Climate–water interactions: challenges for improved representation in integrated assessment models. Energy Econ. 46, 510–521 (2014).

    Google Scholar 

  83. 83

    Li, J., Mullan, M. & Helgeson, J. Improving the practice of economic analysis of climate change adaptation. J. Benefit Cost Anal. 5, 445–467 (2014).

    Google Scholar 

  84. 84

    de Bruin, K. C., Dellink, R. B. & Tol, R. S. J. AD-DICE: an implementation of adaptation in the DICE model. Climatic Change 95, 63–81 (2009).

    Google Scholar 

  85. 85

    Farmer, J. D., Hepburn, C., Mealy, P. & Teytelboym, A. A third wave in the economics of climate change. Environ. Resour. Econ. 62, 329–357 (2015).

    Google Scholar 

  86. 86

    Kelly, D., Kolstad, C. & Mitchell, G. Adjustment costs from environmental change. J. Environ. Econ. Manage. 50, 468–495 (2005). Conceptual framework for understanding adjustment costs and equilibrium response, with an empirical application for US agriculture.

    Google Scholar 

  87. 87

    Schneider, S. H., Easterling, W. E. & Mearns, L. O. Adaptation: sensitivity to natural variability, agent assumptions and dynamic climate changes. Climatic Change 45, 203–221 (2000).

    Google Scholar 

  88. 88

    Hornbeck, R. The enduring impact of the American Dust Bowl: short and long-run adjustments to environmental catastrophe. Am. Econ. Rev. 102, 1477–1507 (2012).

    Google Scholar 

  89. 89

    Heal, G. & Millner, A. Reflections: uncertainty and decision making in climate change economics. Rev. Environ. Econ. Policy 8, 120–137 (2014).

    Google Scholar 

  90. 90

    Cai, Y., Judd, K. L., Lenton, T. M., Lontzek, T. S. & Narita, D. Environmental tipping points significantly affect the cost-benefit assessment of climate policies. Proc. Natl Acad. Sci. USA 112, 4606–4611 (2015). Example of recent advances using stochastic dynamic programming to model uncertain climate thresholds with an endogenous hazard rate and incorporate catastrophic uncertainty into IAMs.

    CAS  Google Scholar 

  91. 91

    Lemoine, D. & Traeger, C. Watch your step: optimal policy in a tipping climate. Am. Econ. J. Econ. Policy 6, 137–166 (2014).

    Google Scholar 

  92. 92

    Diaz, D. B. & Keller, K. A potential disintegration of the West Antarctic Ice Sheet: implications for economic analyses of climate policy. Am. Econ. Rev. Pap. Proc. 106, 1–5 (2016).

    Google Scholar 

  93. 93

    Kopp, R. E., Shwom, R. L., Wagner, G. & Yuan, J. Tipping elements and climate–economic shocks: Pathways toward integrated assessment. Earth's Future 4, 346–372 (2016).

    Google Scholar 

  94. 94

    Moyer, E., Woolley, M., Glotter, M. & Weisbach, D. Climate impacts on economic growth as drivers of uncertainty in the social cost of carbon. J. Legal Stud. 43, 401–425 (2014).

    Google Scholar 

  95. 95

    Pindyck, R. S. Climate change policy: what do the models tell us? J. Econ. Lit. 51, 860–872 (2013).

    Google Scholar 

  96. 96

    Sterner, T. & Persson, U. M. An even sterner review: introducing relative prices into the discounting debate. Rev. Environ. Econ. Policy 2, 61–76 (2008).

    Google Scholar 

  97. 97

    Weitzman, M. L. On modelling and interpreting the economics of catastrophic climate change. Rev. Econ. Stat. 91, 1–19 (2009).

    Google Scholar 

  98. 98

    Weitzman, M. L. What is the 'damages function' for global warming — and what difference might it make? Clim. Chang. Econ. 1, 57–69 (2012).

    Google Scholar 

  99. 99

    Anthoff, D., Tol, R. S. J. & Yohe, G. W. Risk aversion, time preference, and the social cost of carbon. Environ. Res. Lett. 4, 24002 (2009).

    Google Scholar 

  100. 100

    Anthoff, D., Hepburn, C. & Tol, R. S. J. Equity weighting and the marginal damage costs of climate change. Ecol. Econ. 68, 836–849 (2009).

    Google Scholar 

  101. 101

    Dennig, F., Budolfson, M. B., Fleurbaey, M., Siebert, A. & Socolow, R. H. Inequality, climate impacts on the future poor, and carbon prices. Proc. Natl Acad. Sci. USA 112, 1513967112 (2015).

    Google Scholar 

  102. 102

    Newbold, S. C. & Daigneault, A. Climate response uncertainty and the benefits of greenhouse gas emissions reductions. Environ. Resour. Econ. 44, 351–377 (2009).

    Google Scholar 

  103. 103

    Crost, B. & Traeger, C. P. Optimal CO2 mitigation under damage risk valuation. Nat. Clim. Change 4, 631–636 (2014).

    CAS  Google Scholar 

  104. 104

    Jensen, S. & Traeger, C. P. Optimal climate change mitigation under long-term growth uncertainty: stochastic integrated assessment and analytic findings. Eur. Econ. Rev. 69, 104–125 (2014).

    Google Scholar 

  105. 105

    Daniel, K. D., Litterman, R. B. & Wagner, G. Applying Asset Pricing Theory to Calibrate the Price of Climate Risk (2015); http://go.nature.com/2xw8SSL

    Google Scholar 

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A portion of this research was supported by the National Academies of Sciences, Engineering, and Medicine and the Electric Power Research Institute (EPRI) as part of an ancillary literature review of climate impacts and damages conducted as background to Chapter 5 of ref. 6. That work benefited from discussions with committee members M. Auffhammer and S. Rose. F.C.M. acknowledges support from US Department of Agriculture NIFA grant 2016-098. The views expressed in this paper are those of the individual authors and do not necessarily reflect those of a government agency, EPRI or its members.

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D.B.D. and F.C.M. designed and wrote the manuscript. F.C.M. produced Fig. 1. D.B.D. performed the analysis and produced Fig. 2.

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Correspondence to Delavane Diaz.

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Diaz, D., Moore, F. Quantifying the economic risks of climate change. Nature Clim Change 7, 774–782 (2017). https://doi.org/10.1038/nclimate3411

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