Climatic Change

, 98:87 | Cite as

Evaluation of global warming impacts for different levels of stabilization as a step toward determination of the long-term stabilization target

  • Ayami Hayashi
  • Keigo Akimoto
  • Fuminori Sano
  • Shunsuke Mori
  • Toshimasa Tomoda


In order to estimate the benefit attributable to alleviating global warming for a kind of cost–benefit analysis of global warming mitigation, global warming impacts were quantitatively evaluated for a pathway of unmitigated CO2 emissions and three pathways to stabilize the atmospheric CO2 concentration at different levels, keeping unchanged the assumed conditions on population and GDP growths, although the GDP losses which will be caused due to the warming mitigation for the three stabilization pathways are taken into account. The evaluation results show that global warming will reduce the world total number of deaths caused by thermal stress owing to the large decrease in the cold-related deaths; it will increase the water stress in some regions, while it will decrease the stress in other regions; reductions in CO2 emissions will decrease the probability of THC collapse and terrestrial biodiversity loss; and it will enhance an increase in the wheat production potential.


  1. Akimoto K, Tomoda T, Fujii Y, Yamaji K (2004) Assessment of global warming mitigation options with integrated assessment model DNE21. Energy Econ 26:635–653CrossRefGoogle Scholar
  2. Akimoto K, Sano F, Mori S, Tomoda T (2005) Evaluation of global warming impacts on crops considering the adaptation of planting time and crop variety changes. In: Proceedings of the 24th annual meeting of Japan society of energy and resources, Toranomon pastral, Tokyo, 9–10 June 2005 [in Japanese]Google Scholar
  3. Akimoto K, Mori S, Hayashi A, Homma T, Sano F, Oda J, Tomoda T, Kaya Y (2008) How should we deal with the issue of long-term stabilization target against global warming?. Energy Resour 29(3):177. Cited 5 Sept 2008 [in Japanese]Google Scholar
  4. Annan JD, Hargreave JC (2006) Using multiple observationally-based constraints to estimate climate sensitivity. Geophys Res Lett 33:L06704. doi:10.1029/2005GL025259 CrossRefGoogle Scholar
  5. Arnell NW (2004) Climate change and global water resources: SRES emissions and socio-economic scenarios. Glob Environ Change 14:31–52CrossRefGoogle Scholar
  6. Arnell NW, Cannell MGR, Hulme M, Kovats RS, Mitchell JFB, Nicholls RJ, Parry ML, Livermore MTJ, White A (2002) The consequences of CO2 stabilization for the impacts of climate change. Clim Change 53:413–446CrossRefGoogle Scholar
  7. Bryan FO, Danabasoglu G, Nakashiki N, Yoshida Y, Kim DH, Tsutsui J, Doney SC (2006) Response of the North Atlantic thermohaline circulation and ventilation to increasing carbon dioxide in CCSM3. J Clim 19:2382–2397CrossRefGoogle Scholar
  8. CIESIN (2000) Gridded population of the world. Accessed 21 June 2007
  9. CIESIN (2002) Country-level population and downscaled projections based on the SRES B2 scenario country population. Accessed 21 June 2007
  10. CRIEPI (2004) Projection of the global warming up to 2450 using the Earth simulator. Accessed 7 June 2007 [in Japanese]
  11. Fischer G, van Velthuizen H, Shah M, Nachtergaele F (2002) Global agro-ecological assessment for agriculture in the 21st century: methodology and results. IIASA Research Report RR-02-02. Accessed 21 Sept 2007
  12. Hare B (2006) Relationship between increases in global mean temperature and impacts on ecosystems, food production, water and socio-economic systems. In: Schellnhuber HJ, Cramer W, Nakicenovic N, Wigley T, Yohe G (eds) Avoiding dangerous climate change. Cambridge University Press, Cambridge, pp 177–185Google Scholar
  13. Hasumi H, Emori S (2004) K-1 coupled GCM (MIROC) description. Accessed 4 June 2007
  14. Hegerl GC, Crowley TJ, Hyde WT, Frame DJ (2006) Climate sensitivity constrained by temperature reconstructions of the past seven centuries. Nature 440:1029–1032CrossRefGoogle Scholar
  15. Hirst AC (1999) The Southern Ocean response to global warming in the CSIRO coupled ocean-atmosphere model. Environ Model Softw 14:227–241CrossRefGoogle Scholar
  16. IPCC (1994) Climate change 1994. Cambridge University Press, CambridgeGoogle Scholar
  17. IPCC (1996a) Climate change 1995: the science of climate change. Cambridge University Press, CambridgeGoogle Scholar
  18. IPCC (1996b) Climate change 1995: impacts, adaptations and mitigation of climate change: scientific-technical analyses. Cambridge University Press, CambridgeGoogle Scholar
  19. IPCC (2000) Special report on emissions scenarios. Cambridge University Press, CambridgeGoogle Scholar
  20. IPCC (2001a) Climate change 2001: the scientific basis. Cambridge University Press, CambridgeGoogle Scholar
  21. IPCC (2001b) Climate change 2001: impacts, adaptation and vulnerability. Cambridge University Press, CambridgeGoogle Scholar
  22. IPCC (2007a) Climate change 2007: the physical science basis. Cambridge University Press, CambridgeGoogle Scholar
  23. IPCC (2007b) Climate change 2007: impacts, adaptation and vulnerability. Cambridge University Press, CambridgeGoogle Scholar
  24. Kanae S (2002) Population data from CIESIN. Accessed 22 June 2007
  25. Kaplan JO, Bigelow NH, Prentice IC, Harrison SP, Bartlein PJ, Christensen TR, Cramer W, Matveyeva NV, McGuire AD, Murray DF, Razzhivin VY, Smith B, Walker DA, Anderson PM, Andreev AA, Brubaker LB, Edwards ME, Lozhkin AV (2003) Climate change and arctic ecosystems: 2. modeling, paleodata-model comparisons, and future projections. J Geophys Res 108(D19):8171. doi:10.1029/2002JD002559 CrossRefGoogle Scholar
  26. Manabe S, Stouffer RJ (1994) Multiple-century response of a coupled ocean-atmosphere model to an increase of the atmospheric carbon dioxide. J Clim 7:5–23CrossRefGoogle Scholar
  27. Martens WJM (1998) Climate Change, thermal stress and mortality changes. Soc Sci Med 46(3):331–344CrossRefGoogle Scholar
  28. Martens WJM, Jetten TH, Focks DA (1997) Sensitivity of malaria, schistosomiasis and dengue to global warming. Clim Change 35:145–156CrossRefGoogle Scholar
  29. Martens P, Kovats RS, Nijhof S, de Vries P, Livermore MTJ, Bradley DJ, Cox J, McMichael AJ (1999) Climate change and future populations at risk of malaria. Glob Environ Change 9:S89–S107CrossRefGoogle Scholar
  30. Martin PH, Lefebvre MG (1995) Malaria and climate: sensitivity of malaria potential transmission to climate. Ambio 24(4):200–207Google Scholar
  31. Millennium Ecosystem Assessment (2005a) Ecosystem and human well-being: biodiversity synthesis. World Resources Institute, WashingtonGoogle Scholar
  32. Millennium Ecosystem Assessment (2005b) Ecosystem and human well-being: volume 2, scenarios. Island, WashingtonGoogle Scholar
  33. Mori S, Akimoto K, Homma T, Sano F, Oda J, Hayashi A, Dowaki K, Tomoda T (2006) Integrated assessments of global warming issues and an overview of project PHOENIX –a comprehensive approach. IEEJ Trans Electr Electron Eng 1(4):383–396CrossRefGoogle Scholar
  34. Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantification of modeling uncertainties in a large ensemble of climate change simulations. Nature 430:768–772CrossRefGoogle Scholar
  35. Murray JL, Lopez AL (1996) The global burden of disease. Harvard University Press, CambridgeGoogle Scholar
  36. Nohara D, Kitoh A, Hosaka M, Oki T (2006) Impact of climate change on river discharge predicted by multi-model ensemble. J Hydrometeorol 7(5):1076–1089CrossRefGoogle Scholar
  37. Oki T (2001) Total runoff integrating pathways (TRIP). Accessed 4 June 2007
  38. PCMDI (2006) WCRP CMIP3 multi-model database. Accessed 4 June 2007
  39. Schmittner A (2005) Decline of the marine ecosystem caused by a reduction in the Atlantic overturning circulation. Nature 434:628–633CrossRefGoogle Scholar
  40. Stocker TF, Schmittner A (1997) Influence of CO2 emission rates on the stability of the thermohaline circulation. Nature 388:862–865CrossRefGoogle Scholar
  41. Stouffer RJ, Manabe S (1999) Response of a coupled ocean-atmosphere model to increasing atmospheric carbon dioxide: sensitivity to the rate of increase. J Clim 12:2224–2237CrossRefGoogle Scholar
  42. Thorpe RB (2005) The impact of changes in atmospheric and land surface physics on the thermohaline circulation response to anthropogenic forcing in HadCM2 and HadCM3. Clim Dyn 24:449–456CrossRefGoogle Scholar
  43. Tol RSJ (2002a) Estimate of the damage costs of climate change, part i: benchmark estimates. Environ Resour Econ 21:47–73CrossRefGoogle Scholar
  44. Tol RSJ (2002b) Estimate of the damage costs of climate change, part ii: dynamic estimates. Environ Resour Econ 21:135–160CrossRefGoogle Scholar
  45. UN (1998) World population projections to 2150. United Nations, New YorkGoogle Scholar
  46. UN (2004) World urbanization prospects, the 2003 revision. publications/wup2003/2003Highlights.pdf. Accessed 1 Oct 2008
  47. UNEP (1999) Global environment outlook 2000. Accessed 28 June 2007
  48. van Lieshout M, Kovats RS, Livermore MTJ, Martens P (2004) Climate change and malaria: analysis of the SRES climate and socio-economic scenarios. Glob Environ Change Part A, 14(1):87–99CrossRefGoogle Scholar
  49. Vellinga M, Wood RA (2002) Global climatic impacts of a collapse of the atlantic thermohaline circulation. Clim Change 54:251–267CrossRefGoogle Scholar
  50. Voss R, Mikolajewicz U (2001) Long-term climate changes due to increased CO2 concentration in the coupled atmosphere-ocean general circulation model ECHAM3/LSG. Clim Dyn 17:45–60CrossRefGoogle Scholar
  51. Warren R (2006) Impacts of climate change at different annual mean global temperature increases. In: Schellnhuber HJ, Cramer W, Nakicenovic N, Wigley T, Yohe G (eds) Avoiding dangerous climate change. Cambridge University Press, Cambridge, pp 93–131Google Scholar
  52. Wigley TML (1993) Balancing the carbon budget. Implications for projections of future carbon dioxide concentration changes. Tellus 45B:409–425Google Scholar
  53. Wigley TML (2005) The climate change commitment. Science 307:1766–1769CrossRefGoogle Scholar
  54. Wigley TML, Raper SCB (1992) Implications for climate and sea level of revised IPCC emissions scenarios. Nature 357(28):293–300CrossRefGoogle Scholar
  55. Wigley TML, Raper SCB, Hulme M, Smith SJ (2000) The MAGICC/SCENGEN climate scenario generator: version 2.4: technical manual Accessed 1 Oct 2008

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Ayami Hayashi
    • 1
  • Keigo Akimoto
    • 1
  • Fuminori Sano
    • 1
  • Shunsuke Mori
    • 2
  • Toshimasa Tomoda
    • 1
  1. 1.Research Institute of Innovative Technology for the Earth (RITE)KyotoJapan
  2. 2.Faculty of Science and TechnologyTokyo University of ScienceChibaJapan

Personalised recommendations