Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Dependence of economic impacts of climate change on anthropogenically directed pathways

Nature Climate Change volume 9, pages 737–741 (2019)Cite this article

Subjects

A Publisher Correction to this article was published on 07 October 2019

This article has been updated

Abstract

There are great uncertainties in the projected economic impacts of climate change1, arising from uncertainties in the climate response2, the climate change mitigation pathway3 and the socioeconomic development pathway4. Although the relative contributions of these factors are important for climate change related decision-making, they are poorly understood. Here, we show to what extent the projected economic impacts of climate change can be attributed to these three factors. Our modelling framework consisting of global, multisectoral impact models coupled with an integrated assessment model enables us to estimate the global total economic impacts of climate change while incorporating these uncertainty sources. Whereas the most pessimistic pathway without mitigation would result in a net economic impact equivalent to 6.6% (3.9–8.6%) of global gross domestic product at the end of this century, the pathways with stringent mitigation would limit the impact to around or less than 1%. Although the uncertainties are great, the climate change mitigation pathway is the dominant factor and socioeconomic developments can also contribute to alleviate the impacts of climate change. These results suggest that decisions on mitigation and development have a great influence in determining the economic impacts of climate change, regardless of the uncertainties in the climate response.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Projected economic impact.
Fig. 2: Variance of the projected impact attributed to each factor.
Fig. 3: Proportion of attributed variance for sectoral impacts.
Fig. 4: Relationships of impact, vulnerability, temperature and SED.

Data availability

Data required to reproduce the main results are available in the Supplementary Datasets and Code.

Code availability

Computer code required to reproduce the main results are available in Supplementary Datasets and Code.

Change history

  • 07 October 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. Arent, D. J. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) 659–708 (IPCC, Cambridge Univ. Press, 2014).

  2. Knutti, R. & Sedláček, J. Robustness and uncertainties in the new CMIP5 climate model projections. Nat. Clim. Change 3, 369–373 (2012).

    Article  Google Scholar 

  3. van Vuuren, D. P. et al. The representative concentration pathways: an overview. Climatic Change 109, 5 (2011).

    Article  Google Scholar 

  4. 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 (2013).

    Article  Google Scholar 

  5. Smith, L. A. & Stern, N. Uncertainty in science and its role in climate policy. Phil. Trans. R. Soc. Lond. A 369, 4818–4841 (2011).

    Article  Google Scholar 

  6. Schelling, T. C. Micromotives and Macrobehavior (WW Norton, 2006).

  7. Morgan, M. G., Henrion, M. & Small, M. Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis (Cambridge Univ. Press, 1992).

  8. Bosshard, T. et al. Quantifying uncertainty sources in an ensemble of hydrological climate‐impact projections. Water Resour. Res. 49, 1523–1536 (2013).

    Article  Google Scholar 

  9. Tol, R. S. J. Estimates of the damage costs of climate change. Part 1: Benchmark estimates. Environ. Resour. Econ. 21, 47–73 (2002).

    Article  Google Scholar 

  10. Stern, N. The Economics of Climate Change: The Stern Review (Office of Climate Change, 2006).

  11. Ciscar, J.-C. et al. Physical and economic consequences of climate change in Europe. Proc. Natl Acad. Sci. USA 108, 2678–2683 (2011).

    Article  CAS  Google Scholar 

  12. Roson, R. & Van der Mensbrugghe, D. Climate change and economic growth: impacts and interactions. Int. J. Sustain. Econ. 4, 270–285 (2012).

    Article  Google Scholar 

  13. Hsiang, S. et al. Estimating economic damage from climate change in the United States. Science 356, 1362–1369 (2017).

    Article  CAS  Google Scholar 

  14. Nordhaus, W. D. Revisiting the social cost of carbon. Proc. Natl Acad. Sci. USA 114, 1518–1523 (2017).

    Article  CAS  Google Scholar 

  15. Dellink, R., Lanzi, E. & Chateau, J. The sectoral and regional economic consequences of climate change to 2060. Environ. Resour. Econ. 72, 309–363 (2017).

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

    Article  CAS  Google Scholar 

  17. Burke, M., Davis, W. M. & Diffenbaugh, N. S. Large potential reduction in economic damages under UN mitigation targets. Nature 557, 549–553 (2018).

    Article  CAS  Google Scholar 

  18. Roson, R. & Sartori, M. Estimation of climate change damage functions for 140 regions in the GTAP 9 data base. J. Global Econ. Anal. 1, 78–115 (2016).

  19. Fujimori, S., Masui, T. & Matsuoka, Y. AIM/CGE [Basic] Manual Discussion Paper No. 2012-01 (Center for Social and Environmental Systems Research, NIES, 2012).

  20. Riahi, K. et al. The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Article  Google Scholar 

  21. Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change 109, 213–241 (2011).

    Article  CAS  Google Scholar 

  22. McSweeney, C. F. & Jones, R. G. How representative is the spread of climate projections from the 5 CMIP5 GCMs used in ISI-MIP? Clim. Serv. 1, 24–29 (2016).

    Article  Google Scholar 

  23. Howard, P. H. & Sterner, T. Few and not so far between: a meta-analysis of climate damage estimates. Environ. Resour. Econ. 68, 197–225 (2017).

    Article  Google Scholar 

  24. Rosenzweig, C. et al. Assessing inter-sectoral climate change risks: the role of ISIMIP. Environ. Res. Lett. 12, 010301 (2017).

    Article  Google Scholar 

  25. Nishina, K. et al. Decomposing uncertainties in the future terrestrial carbon budget associated with emission scenarios, climate projections, and ecosystem simulations using the ISI-MIP results. Earth Syst. Dynam. 6, 435–445 (2015).

    Article  Google Scholar 

  26. Emori, S. et al. Risk implications of long-term global climate goals: overall conclusions of the ICA-RUS project. Sustain. Sci. 13, 279–289 (2018).

    Article  Google Scholar 

  27. Lamontagne, J. R. et al. Large ensemble analytic framework for consequence-driven discovery of climate change scenarios. Earth’s Future 6, 488–504 (2018).

    Article  Google Scholar 

  28. Crespo Cuaresma, J. Income projections for climate change research: a framework based on human capital dynamics. Glob. Environ. Change 42, 226–236 (2017).

    Article  Google Scholar 

  29. Kc, S. & Lutz, W. The human core of the shared socioeconomic pathways: population scenarios by age, sex and level of education for all countries to 2100. Glob. Environ. Change 42, 181–192 (2017).

    Article  Google Scholar 

  30. Jiang, L. & O’Neill, B. C. Global urbanization projections for the Shared Socioeconomic Pathways. Glob. Environ. Change 42, 193–199 (2017).

    Article  Google Scholar 

  31. Burke, M. B., Miguel, E., Satyanath, S., Dykema, J. A. & Lobell, D. B. Warming increases the risk of civil war in Africa. Proc. Natl Acad. Sci. USA 106, 20670–20674 (2009).

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  33. Hempel, S., Frieler, K., Warszawski, L., Schewe, J. & Piontek, F. A trend-preserving bias correction—the ISI-MIP approach. Earth Syst. Dynam. 4, 219–236 (2013).

    Article  Google Scholar 

  34. Iizumi, T., Takikawa, H., Hirabayashi, Y., Hanasaki, N. & Nishimori, M. Contributions of different bias‐correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes. J. Geophys. Res. 122, 7800–7819 (2017).

    Google Scholar 

  35. Iizumi, T. et al. Responses of crop yield growth to global temperature and socioeconomic changes. Sci. Rep. 7, 7800 (2017).

    Article  Google Scholar 

  36. Iizumi, T. et al. Crop production losses associated with anthropogenic climate change for 1981–2010 compared with preindustrial levels. Int. J. Climatol. 38, 5405–5417 (2018).

    Article  Google Scholar 

  37. Rosenzweig, C. et al. Assessing agricultural risks of climate change in the twenty-first century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268 (2014).

    Article  CAS  Google Scholar 

  38. Fujimori, S. et al. Macroeconomic impacts of climate change driven by changes in crop yields. Sustainability 10, 3673 (2018).

    Article  Google Scholar 

  39. Hasegawa, T., Fujimori, S., Takahashi, K., Yokohata, T. & Masui, T. Economic implications of climate change impacts on human health through undernourishment. Climatic Change 136, 189–202 (2016).

    Article  Google Scholar 

  40. Mortality Risk Valuation in Environment, Health and Transport Policies (OECD, 2012).

  41. Honda, Y. et al. Heat-related mortality risk model for climate change impact projection. Environ. Health Prev. Med. 19, 56–63 (2014).

    Article  Google Scholar 

  42. Hasegawa, T. et al. Quantifying the economic impact of changes in energy demand for space heating and cooling systems under varying climatic scenarios. Palgrave Commun. 2, 16013 (2016).

    Article  Google Scholar 

  43. Park, C. et al. Avoided economic impacts of energy demand changes by 1.5 and 2 °C climate stabilization. Environ. Res. Lett. 13, 045010 (2018).

    Article  Google Scholar 

  44. Isaac, M. & Van Vuuren, D. P. Modeling global residential sector energy demand for heating and air conditioning in the context of climate change. Energy Policy 37, 507–521 (2009).

    Article  Google Scholar 

  45. Fujimori, S., Masui, T. & Matsuoka, Y. Development of a global computable general equilibrium model coupled with detailed energy end-use technology. Appl. Energy 128, 296–306 (2014).

    Article  Google Scholar 

  46. Takakura, J. et al. Cost of preventing workplace heat-related illness through worker breaks and the benefit of climate-change mitigation. Environ. Res. Lett. 12, 064010 (2017).

    Article  Google Scholar 

  47. Budd, G. M. Wet-bulb globe temperature (WBGT)—its history and its limitations. J. Sci. Med. Sport 11, 20–32 (2008).

    Article  Google Scholar 

  48. Jacklitsch, B. et al. Criteria for a Recommended Standard: Occupational Exposure to Heat and Hot Environments: Revised Criteria 2016–2106 (NIOSH, 2016).

  49. Zhou, Q., Hanasaki, N., Fujimori, S., Masaki, Y. & Hijioka, Y. Economic consequences of global climate change and mitigation on future hydropower generation. Climatic Change 147, 77–90 (2018).

    Article  Google Scholar 

  50. Hanasaki, N. et al. An integrated model for the assessment of global water resources—Part 1: Model description and input meteorological forcing. Hydrol. Earth Syst. Sci. 12, 1007–1025 (2008).

    Article  Google Scholar 

  51. Hanasaki, N. et al. An integrated model for the assessment of global water resources—Part 2: Applications and assessments. Hydrol. Earth Syst. Sci. 12, 1027–1037 (2008).

    Article  Google Scholar 

  52. Zhou, Q. et al. Cooling water sufficiency in a warming world: projection using an integrated assessment model and a global hydrological model. Water 10, 872 (2018).

    Article  Google Scholar 

  53. Zhou, Q., Hanasaki, N. & Fujimori, S. Economic consequences of cooling water insufficiency in the thermal power sector under climate change scenarios. Energies 11, 1–11 (2018).

    Google Scholar 

  54. Kinoshita, Y., Tanoue, M., Watanabe, S. & Hirabayashi, Y. Quantifying the effect of autonomous adaptation to global river flood projections: application to future flood risk assessments. Environ. Res. Lett. 13, 014006 (2018).

    Article  Google Scholar 

  55. Tanoue, M., Hirabayashi, Y. & Ikeuchi, H. Global-scale river flood vulnerability in the last 50 years. Sci. Rep. 6, 36021 (2016).

    Article  CAS  Google Scholar 

  56. Yamazaki, D., Kanae, S., Kim, H. & Oki, T. A physically based description of floodplain inundation dynamics in a global river routing model. Water Resour. Res. 47, W04501 (2011).

    Article  Google Scholar 

  57. Takata, K., Emori, S. & Watanabe, T. Development of the minimal advanced treatments of surface interaction and runoff. Glob. Planet. Change 38, 209–222 (2003).

    Article  Google Scholar 

  58. Ikeuchi, H. et al. Modeling complex flow dynamics of fluvial floods exacerbated by sea level rise in the Ganges–Brahmaputra–Meghna Delta. Environ. Res. Lett. 10, 124011 (2015).

    Article  Google Scholar 

  59. Klein Goldewijk, K., Beusen, A., van Drecht, G. & de Vos, M. The HYDE 3.1 spatially explicit database of human-induced global land-use change over the past 12,000 years. Glob. Ecol. Biogeogr. 20, 73–86 (2011).

    Article  Google Scholar 

  60. Tsuchida, K., Tamura, M., Kumano, N., Masunaga, E. & Yokoki, H. Global impact and uncertainty assessment of sea level rise based on multiple climate models. J. Jpn Soc. Civ. Eng. G 74, 1167–1174 (2018).

    Google Scholar 

  61. Yotsukuri, M., Tamura, M., Kumano, N., Masunaga, E. & Yokoki, H. Global impact assessment of sea level rise based on RCP/SSP scenarios. J. Jpn. Soc. Civ. Eng. G 73, I369–I376 (2017).

    Google Scholar 

  62. Tamura, M., Kumano, N., Yotsukuri, M. & Yokoki, H. Global assessment of the effectiveness of adaptation in coastal areas based on RCP/SSP scenarios. Climatic Change 152, 363–377 (2019).

    Article  Google Scholar 

  63. EM-DAT: The International Disaster Database (CRED, accessed 1 November 2015); http://www.emdat.be/

  64. Matsumoto, K. I. Climate change impacts on socioeconomic activities through labor productivity changes considering interactions between socioeconomic and climate systems. J. Clean. Prod. 216, 528–541 (2019).

    Article  Google Scholar 

  65. Fujimori, S. et al. SSP3: AIM implementation of Shared Socioeconomic Pathways. Glob. Environ. Change 42, 268–283 (2017).

    Article  Google Scholar 

  66. Honaker, J., King, G. & Blackwell, M. Amelia II: a program for missing data. J. Stat. Softw. 45, 47 (2011).

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the Environment Research and Technology Development Fund (no. S-14) of the Environmental Restoration and Conservation Agency.

Author information

Authors and Affiliations

  1. Center for Social and Environmental Systems Research, National Institute for Environmental Studies, Tsukuba, Japan

    Jun’ya Takakura & Kiyoshi Takahashi

  2. Department of Environmental Engineering, Kyoto University, Kyoto, Japan

    Shinichiro Fujimori

  3. Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan

    Naota Hanasaki & Yasuaki Hijioka

  4. College of Science and Engineering, Ritsumeikan University, Kusatsu, Japan

    Tomoko Hasegawa

  5. Department of Civil Engineering, Shibaura Institute of Technology, Tokyo, Japan

    Yukiko Hirabayashi & Masahiro Tanoue

  6. Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan

    Yasushi Honda

  7. Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, Tsukuba, Japan

    Toshichika Iizumi & Zhihong Shen

  8. Graduate School of Agriculture, Ehime University, Matsuyama, Japan

    Naoko Kumano

  9. Department of Landscape Architecture, College of Urban Science, University of Seoul, Seoul, Korea

    Chan Park

  10. Institute for Global Change Adaptation Science, Ibaraki University, Mito, Japan

    Makoto Tamura

  11. Nippon Koei, Tokyo, Japan

    Koujiro Tsuchida

  12. Department of Civil, Architectural, and Environmental Engineering, Graduate School of Science and Engineering, Ibaraki University, Hitachi, Japan

    Hiromune Yokoki

  13. School of Economics and Management, North China Electric Power University, Beijing, China

    Qian Zhou

  14. Institute for Future Initiatives, The University of Tokyo, Tokyo, Japan

    Taikan Oki

  15. United Nations University, Tokyo, Japan

    Taikan Oki

Authors
  1. Jun’ya Takakura
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shinichiro Fujimori
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Naota Hanasaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tomoko Hasegawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yukiko Hirabayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yasushi Honda
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Toshichika Iizumi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Naoko Kumano
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Chan Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Zhihong Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Kiyoshi Takahashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Makoto Tamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Masahiro Tanoue
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Koujiro Tsuchida
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Hiromune Yokoki
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Qian Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Taikan Oki
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Yasuaki Hijioka
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.F., N.H., T.H., Y.Hirabayashi, Y.Honda, T.I., N.K., C.P., Z.S., K.Takahashi., J.T., M.Tamura., M.Tanoue, K.Tsuchida, H.Y. and Q.Z. conducted analyses on the sectoral impacts and provided the data. J.T. conducted the analysis of the aggregated impacts. J.T. and S.F. wrote the manuscript. T.O. and Y.Hijioka directed the study. All authors participated in the interpretation of the results, discussion and revising the draft of the manuscript.

Corresponding author

Correspondence to Jun’ya Takakura.

Ethics declarations

Competing interests

J.T. was employed by Toshiba Corporation, which is associated with the manufacture, sale, distribution and marketing of hydro/thermal power plants, until February 2016. K.Tsuchida has been employed by Nippon Koei, which is associated with consultation on natural disaster prevention (including fluvial flooding and coastal inundation) and on hydro/thermal power plants, since April 2019. The other authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Roberto Roson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–23, Discussions 1–4, Tables 1–5, Methods 1–4 and references.

Reporting Summary

Supplementary Datasets and Code

Supplementary datasets and code to reproduce main results.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Takakura, J., Fujimori, S., Hanasaki, N. et al. Dependence of economic impacts of climate change on anthropogenically directed pathways. Nat. Clim. Chang. 9, 737–741 (2019). https://doi.org/10.1038/s41558-019-0578-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41558-019-0578-6

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing