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Integrated Assessment Modeling

  • James A. EdmondsEmail author
  • Katherine V. Calvin
  • Leon E. Clarke
  • Anthony C. Janetos
  • Son H. Kim
  • Marshall A. Wise
  • Haewon C. McJeon
Chapter

Abstract

This entry discusses the role of integrated assessment models (IAMs) in climate change research. IAMs are an interdisciplinary research platform, which constitutes a consistent scientific framework in which the large-scale interactions between human and natural Earth systems can be examined.

Keywords

Global Warming Potential Bioenergy Crop Integrate Assessment Model Computable General Equilibrium Model Emission Mitigation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Glossary

Climate policy (greenhouse gas mitigation policy)

A climate policy refers to a policy scheme designed to deliberately limit the magnitude of climate change, often involving mitigation of greenhouse gases. Integrated assessment models (IAMs) represent climate policies in abstract forms. The most commonly modeled climate policy is attaching a universal price on emissions of carbon dioxide (or carbon dioxide equivalent of other greenhouse gases). Such policy represents a universal carbon tax or an economy-wide cap-and-trade policy. Other forms of climate policies, such as differential carbon price by sector or renewable portfolio standards, have also been used in IAMs.

Cost of greenhouse gas mitigation (economic cost)

Integrated assessment models (IAMs) employ varies metrics for estimating the economic cost of mitigation policy. One common approach estimates reduction in GDP, a proxy for slowdown in economic activity due to increased price of energy and agricultural products. Another approach estimates the (gross) loss in social welfare due to a policy by measuring the area under the marginal abatement cost curve. Other metrics include foregone consumption, compensated variation, and equivalent variation.

Integrated assessment model (IAM)

Integrated assessment model (IAM) in climate change research is a model which simulates the interactions of human decision-making about energy systems and land use with biogeochemistry and the natural Earth system. IAMs can be divided into two categories.

Higher resolution IAMs focus on explicitly representing processes and process interactions among human and natural Earth systems.

Highly aggregated IAMs use highly reduced-form representations of the link between human activities, impacts from climate change, and the cost of emissions mitigation.

Integrated earth system model (iESM)

Integrated Earth System Models (iESMs) are a class of models under development by collaboration between integrated assessment modeling community and climate modeling community. By fully integrating the human dimension from an IAM and the natural dimension from a climate model, iESM allows simultaneously estimating human system impacts on climate change and climate change impacts on human systems, as well as examining the effects of feedbacks between the components.

Land use (land-use emissions)

Land use is one of the largest anthropogenic sources of emissions of greenhouse gases, aerosols, and short-lived species. Emissions, as well as sequestration of emissions, may occur from land-use practices, changes in land cover, or changes in forested area or the density. On the other hand, land-use patterns are affected by the changes in the climate. As such, modeling land use has been an important component of the integrated assessment modeling of climate change.

Representative concentration pathways (RCPs)

The Representative Concentration Pathways (RCPs) are the most recent set of emission scenarios generated by integrated assessment models. Four scenarios explicitly considering emission mitigation efforts that were sufficiently differentiated in terms of radiative forcing at the end of the century were selected from published literature. RCPs are designed to facilitate the interactions with climate models by including geospatially resolved emissions and land-use data.

Bibliography

  1. 1.
    Wigley TML, Richels R, Edmonds JA (1996) Economic and environmental choices in the stabilization of atmospheric CO2 concentrations. Nature 379:240–243ADSCrossRefGoogle Scholar
  2. 2.
    Nordhaus WD, Yohe GW (1983) Future carbon dioxide emissions from fossil fuels. Changing climate: report of the carbon dioxide assessment committee. National Academy Press, Washington DC, pp 87–153Google Scholar
  3. 3.
    Nordhaus WD (1993) Optimal greenhouse-gas reductions and tax policy in the “DICE” model. Am Econ Rev 83:313–317Google Scholar
  4. 4.
    Nordhaus WD, Yang Z (1996) A regional dynamic general-equilibrium model of alternative climate-change strategies. Am Econ Rev 86:741–765Google Scholar
  5. 5.
    Dowlatabadi H, Morgan MG (1993) A model framework for integrated studies of the climate problem. Energy Policy 21:209–221CrossRefGoogle Scholar
  6. 6.
    Hope C, Anderson J, Wenman P (1993) Policy analysis of the greenhouse effect: an application of the PAGE model. Energy Policy 21:327–338CrossRefGoogle Scholar
  7. 7.
    Tol RSJ (1997) On the optimal control of carbon dioxide emissions: an application of FUND. Environ Model Assess 2:151–163CrossRefGoogle Scholar
  8. 8.
    Weyant J, Davidson O, Dowlatabadi H, Edmonds J, Grubb M, Parson EA, Richels R, Rotmans J, Shukla PR, Tol RSJ (1996)Integrated assessment of climate change: an overview and comparison of approaches and results. In: Bruce JP, H-sŏng Yi, Haites EF (eds) Climate change 1995: economic and social dimensions of climate change. The contribution of working group III to the second assessment report of the intergovernmental panel on climate change. Cambridge University Press, UK/New York, pp 367–396Google Scholar
  9. 9.
    Parson EA, Fisher-Vanden K (1997) Integrated assessment models of global climate change. Annu Rev Energy Env 22:589–628CrossRefGoogle Scholar
  10. 10.
    Nordhaus W (2007) Critical assumptions in the Stern Review on climate change. Science 317:201–202CrossRefGoogle Scholar
  11. 11.
    Stern NH (2007) The economics of climate change: the Stern Review. Cambridge University Press, Cambridge, UK/New YorkGoogle Scholar
  12. 12.
    Portney PR, Weyant JP (eds) (1999) Discounting and intergenerational equity. Resources for the Future, Washington, DCGoogle Scholar
  13. 13.
    Dasgupta P, Mäler KG, Barrett S (1999) Intergenerational equity, social discount rates and global warming. In: Portney PR, Weyant JP (eds) Discounting and intergenerational equity. Resources for the Future, Washington, DCGoogle Scholar
  14. 14.
    Clarke L, Edmonds J, Jacoby H, Pitcher H, Reilly J, Richels R (2007) Scenarios of greenhouse gas emissions and atmospheric concentrations. Synthesis and assessment product 2.1a, report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. U.S. Government Printing Office, Washington, DCGoogle Scholar
  15. 15.
    Edmonds J, Reilly J (1983) A long-term global energy- economic model of carbon dioxide release from fossil fuel use. Energy Econ 5:74–88CrossRefGoogle Scholar
  16. 16.
    Edmonds J, Reilly J (1983) Global energy and CO2 to the year 2050. Energy J 4:21–48Google Scholar
  17. 17.
    Edmonds J, Reilly J (1983) Global energy production and use to the year 2050. Energy 8:419–432CrossRefGoogle Scholar
  18. 18.
    Edmonds J, Reilly JM (1985) Global energy: assessing the future. Oxford University Press, New YorkGoogle Scholar
  19. 19.
    Brenkert A, Smith S, Kim S, Pitcher H (2003) Model documentation for the MiniCAM. Pacific Northwest National Laboratory. Technical report PNNL-14337Google Scholar
  20. 20.
    Kim SH, Edmonds JA, Smith SJ, Wise M, Lurz J (2006) The object-oriented energy climate technology systems (ObjECTS) framework and hybrid modeling of transportation in the MiniCAM long-term, global integrated assessment model. Energy J 27:63–91Google Scholar
  21. 21.
    Clarke L, Wise M, Kim S, Smith S, Lurz J, Edmonds J, Pitcher H (2007) Model documentation for the minicam climate change science program stabilization scenarios: CCSP product 2.1 a. Pacific Northwest National Laboratory, PNNL-16735Google Scholar
  22. 22.
    Wise MA, Calvin KV, Thomson AM, Clarke LE, Bond-Lamberty B, Sands RD, Smith SJ, Janetos AC, Edmonds JA (2009) The implications of limiting CO2 concentrations for agriculture, land use, land-use change emissions and bioenergy. Pacific Northwest National LaboratoryGoogle Scholar
  23. 23.
    Sokolov AP, Schlosser CA, Dutkiewicz S, Paltsev S, Kicklighter DW, Jacoby HD, Prinn RG, Forest CE, Reilly JM, Wang C, et al (2005) MIT integrated global system model (IGSM) version 2: model description and baseline evaluation, MIT Joint Program for the Science and Policy of Global Change. Report 124, Cambridge, MAGoogle Scholar
  24. 24.
    Manne A, Mendelsohn R, Richels R (1995) MERGE: a model for evaluating regional and global effects of GHG reduction policies. Energy Policy 23:17–34CrossRefGoogle Scholar
  25. 25.
    Blanford GJ, Richels RG, Rutherford TF (2009) Feasible climate targets: the roles of economic growth, coalition development and expectations. Energy Econ 31:S82–S93CrossRefGoogle Scholar
  26. 26.
    Kainuma M, Matsuoka Y, Morita T (eds) (2003) Climate policy assessment: Asia-Pacific integrated modeling. Springer-Verlag, TokyoGoogle Scholar
  27. 27.
    Wigley TML, Raper SCB (1992) Implications for climate and sea level of revised IPCC emissions scenarios. Nature 357:293–300ADSCrossRefGoogle Scholar
  28. 28.
    Wigley TML, Raper SCB (2002) Reasons for larger warming projections in the IPCC third assessment report. J Climate 15:2945–2952ADSCrossRefGoogle Scholar
  29. 29.
    Raper SCB, Wigley TML, Warrick RA (1996) Global sea-level rise: past and future. In: Milliman JD Haq BU (eds) Sea-level rise and coastal subsidence: causes, consequences, and strategies. Kluwer Academic Publishers, Dordrecht, NetherlandsGoogle Scholar
  30. 30.
    Clarke JF, Edmonds JA (1993) Modeling energy technologies in a competitive market. Energy Econ 15:123–129CrossRefGoogle Scholar
  31. 31.
    McFadden D (1974) Conditional logit analysis of qualitative choice behavior. In: Zarambka P (ed) Frontiers of econometrics. Academic, New York, pp 105–142Google Scholar
  32. 32.
    McFadden D (1981) Econometric models for probabilistic choice among products. In: Manski C, McFadden D (eds) Structural analysis of discrete data with econometric applications. MIT Press, Cambridge, MA, pp 198–272Google Scholar
  33. 33.
    Wise M, Calvin K, Thomson A, Clarke L, Bond-Lamberty B, Sands R, Smith SJ, Janetos A, Edmonds J (2009) Implications of limiting CO2 concentrations for land use and energy. Science 324:1183–1186ADSCrossRefGoogle Scholar
  34. 34.
    Bouwman AF, Kram T, Goldewijk KK (2006) Integrated modeling of global environmental change: an overview of Image 2.4. Netherlands Environmental Assessment AgencyGoogle Scholar
  35. 35.
    Searchinger T, Heimlich R, Houghton RA, Dong F, Elobeid A, Fabiosa J, Tokgoz S, Hayes D, Yu T-H (2008) Use of U.S. Croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 319:1238–1240ADSCrossRefGoogle Scholar
  36. 36.
    Lal R (2004) Soil carbon sequestration impacts on global climate change and food security. Science 304:1623–1627ADSCrossRefGoogle Scholar
  37. 37.
    Fargione J, Hill J, Tilman D, Polasky S, Hawthorne P (2008) Land clearing and the biofuel carbon debt. Science 319:1235–1238ADSCrossRefGoogle Scholar
  38. 38.
    Luckow P, Wise MA, Dooley JJ, Kim SH (2010) Large-scale utilization of biomass energy and carbon dioxide capture and storage in the transport and electricity sectors under stringent CO2 concentration limit scenarios. Int J Greenh Gas Control 4:865–877CrossRefGoogle Scholar
  39. 39.
    Edmonds JA, Scott MJ, Roop JM, MacCracken CN (1999) International emission trading and the cost of greenhouse gas emissions mitigation. The Pew Center on Global Climate Change, ArlingtonGoogle Scholar
  40. 40.
    Kyoto Protocol: the kyoto protocol to the united nations framework convention on climate change. UNEP/WMO, KyotoGoogle Scholar
  41. 41.
    Peck SC, Wan YS (1996) Analytic solutions of simple optimal greenhouse gas emission models. In: van Ierland E, Górka K (eds) Economics of atmospheric pollution. Springer, Berlin, pp 113–121CrossRefGoogle Scholar
  42. 42.
    Edmonds JA, Wise MA, Dooley JJ, Kim SH, Smith SJ, Runci PJ, Clarke LE, Malone EL, Stokes GM (2007) Global energy technology strategy: addressing climate change phase 2 findings from an international public-private sponsored research program. Pacific Northwest National Laboratory (PNNL), RichlandGoogle Scholar
  43. 43.
    Metz B, Davidson O, Bosch P, Dave R, Meyer L (eds) (2007)Climate change 2007: mitigation of climate change; contribution of working group III to the 4th assessment report of the intergovenmental panel on climate change. Cambridge University Press, Cambridge, UK/New YorkGoogle Scholar
  44. 44.
    Weyant JP, Francisco C, Blanford GJ (2006) Overview of EMF-21: multigas mitigation and climate policy. Energy J 27:1–32Google Scholar
  45. 45.
    National Research Council (U.S.) (2005) Climate research committee: radiative forcing of climate change: expanding the concept and addressing uncertainties. Academic, Washington, DCGoogle Scholar
  46. 46.
    Wuebbles DJ, Edmonds J (1991) Primer on greenhouse gases. Lewis Publishers, Chelsea, MichiganGoogle Scholar
  47. 47.
    Solomon S, Qin D, Manning M, Marquis M, Averyt K, Tignor M, LeRoy Miller H, Chen Z (eds) (2007) Climate change 2007. The physical science basis: contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK/New YorkGoogle Scholar
  48. 48.
    Houghton JT, Meiro Filho LG, Callander BA, Harris N, Kattenburg A, Maskell K (eds) (1996) Climate change 1995: the science of climate change. Cambridge University Press, Cambridge, UKGoogle Scholar
  49. 49.
    Joos F, Prentice IC, Sitch S, Meyer R, Hooss G, Plattner G-K, Gerber S, Hasselmann K (2001) Global warming feedbacks on terrestrial carbon uptake under the Intergovernmental Panel on Climate Change (IPCC) emission scenarios. Global Biogeochem Cy 15:891–908ADSCrossRefGoogle Scholar
  50. 50.
    Houghton JT, Jenkins GJ, Ephraums JJ (eds) (1990) Climate change: the IPCC scientific assessment. Cambridge University Press, Cambridge, UKGoogle Scholar
  51. 51.
    Houghton JT, Jenkins GJ, Ephraums JJ (eds) (1990) Climate change: the IPCC response strategies. Cambridge University Press, Cambridge, UKGoogle Scholar
  52. 52.
    Manne AS, Richels RG (2001) An alternative approach to establishing trade-offs among greenhouse gases. Nature 410:675–677ADSCrossRefGoogle Scholar
  53. 53.
    Arrow KJ (1950) A difficulty in the concept of social welfare. J Polit Econ 58:328–346CrossRefGoogle Scholar
  54. 54.
    Milliman SR, Prince R (1989) Firm incentives to promote technological change in pollution control. J Environ Econ Manag 17:247–265CrossRefGoogle Scholar
  55. 55.
    McJeon HC, Clarke L, Kyle P, Wise M, Hackbarth A, Bryant BP, Lempert RJ (2011) Technology interactions among low-carbon energy technologies: what can we learn from a large number of scenarios? Energy Econ 33:619–631CrossRefGoogle Scholar
  56. 56.
    Böhringer C, Rutherford TF, Tol RSJ (2009) THE EU 20/20/2020 targets: an overview of the EMF22 assessment. Energy Econ 31:S268–S273CrossRefGoogle Scholar
  57. 57.
    Edmonds J, Clarke L, Lurz J, Wise M (2008) Stabilizing CO2 concentrations with incomplete international cooperation. Clim Policy 8:355–376CrossRefGoogle Scholar
  58. 58.
    Clarke L, Edmonds J, Krey V, Richels R, Rose S, Tavoni M (2009) International climate policy architectures: overview of the EMF 22 international scenarios. Energy Econ 31:S64–S81CrossRefGoogle Scholar
  59. 59.
    Edmonds JA, Reilly J, Trabalka JR, Reichle DE (1984) An analysis of possible future atmospheric retention of fossil fuel CO2, TR013, US Department of Energy Carbon Dioxide Research Division, Washington DCGoogle Scholar
  60. 60.
    Trabalka JR, Reichle DE (eds) (1986) The changing carbon cycle: a global analysis. Springer, New YorkGoogle Scholar
  61. 61.
    Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756ADSCrossRefGoogle Scholar
  62. 62.
    Leggett J, Pepper WJ, Swart RJ, Edmonds J, Meira Filho LG, Mintzer I, Wang MX, Wasson J (1992) Emissions scenarios for the IPCC: an update. Climate change 1992: The supplementary report to the IPCC scientific assessment. Cambridge University Press, Cambridge, UK/New YorkGoogle Scholar
  63. 63.
    Nakicenovic N, Alcamo J, Davis G, de Vries B, Fenhann J, Gaffin S, Gregory K, Grubler A, Jung TY, Kram T (2000) Special report on emissions scenarios: a special report of working group III of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK/New YorkGoogle Scholar
  64. 64.
    Riahi K, Grübler A, Nakicenovic N (2007) Scenarios of long-term socio-economic and environmental development under climate stabilization. Technol Forecast Soc 74:887–935CrossRefGoogle Scholar
  65. 65.
    Fujino J, Nair R, Kainuma M, Masui T, Matsuoka Y (2006) Multi-gas mitigation analysis on stabilization scenarios using AIM global model. Energy J SI3:343–354Google Scholar
  66. 66.
    Hijioka Y, Matsuoka Y, Nishimoto H, Masui M, Kainuma M (2008) Global GHG emissions scenarios under GHG concentration stabilization targets. J Global Environ Eng 13:97–108Google Scholar
  67. 67.
    Smith SJ, Wigley TML (2006) Multi-gas forcing stabilization with MiniCAM. Energy J SI3:373–392Google Scholar
  68. 68.
    van Vuuren DP, Eickhout B, Lucas PL, den Elzen MGJ (2006) Long-term multi-gas scenarios to stabilize radiative forcing-exploring costs and benefits within an integrated assessment framework. Energy J SI3:201–234Google Scholar
  69. 69.
    van Vuuren DP, Elzen MGJ, Lucas PL, Eickhout B, Strengers BJ, Ruijven B, Wonink S, Houdt R (2007) Stabilizing greenhouse gas concentrations at low levels: an assessment of reduction strategies and costs. Clim Change 81:119–159CrossRefGoogle Scholar
  70. 70.
    van Vuuren DP, Riahi K, Moss R, Edmonds J, Thomson A, Nakicenovic N, Kram T, Berkhout F, Swart R, Janetos A, Rose SK, Arnell N (2011) A proposal for a new scenario framework to support research and assessment in different climate research communities. Global Environ Chang (In Press)Google Scholar
  71. 71.
    Kriegler E, O’Neill BC, Hallegatte S, Kram T, Lempert R, Moss RH, Wilbanks TJ (2010) Socio-economic scenario development for climate change analysis. CIRED working paper. Centre International de Recherche sur l’Environnement et le Développement, Paris, FranceGoogle Scholar
  72. 72.
    Janetos AC, Clarke L, Collins W, Ebi K, Edmonds J, Foster I, Jacoby HJ, Judd K, Leung L, Newell R, Ojima D, Pugh G, Sanstad A, Schultz P, Stevens R, Weyant J, Wilbanks T (2008) Science challenges and future directions: climate change integrated assessment research. U.S. Department of Energy, Office of Science. http://science.energy.gov/~/media/ber/pdf/Ia_workshop_low_res_06_25_09.pdf. Accessed 5 Dec 2011
  73. 73.
    Leemans R, Eickhout B (2004) Another reason for concern: regional and global impacts on ecosystems for different levels of climate change. Global Environ Change Part A 14:219–228CrossRefGoogle Scholar
  74. 74.
    Reilly J, Paltsev S, Felzer B, Wang X, Kicklighter D, Melillo J, Prinn R, Sarofim M, Sokolov A, Wang C (2007) Global economic effects of changes in crops, pasture, and forests due to changing climate, carbon dioxide, and ozone. Energy Policy 35:5370–5383CrossRefGoogle Scholar
  75. 75.
    Edmonds JA, Rosenberg NJ (2005) Climate change impacts for the conterminous USA: an integrated assessment summary. Clim Change 69:151–162CrossRefGoogle Scholar
  76. 76.
    Parry M, Canzaiani O, Palutikof J, Van der Linden P, Hanson C (eds) (2007) Climate change 2007: impacts, adaptation and vulnerability; Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK/New YorkGoogle Scholar
  77. 77.
    Melillo JM, Reilly JM, Kicklighter DW, Gurgel AC, Cronin TW, Paltsev S, Felzer BS, Wang X, Sokolov AP, Schlosser CA (2009) Indirect emissions from biofuels: how important? Science 326:1397–1399ADSCrossRefGoogle Scholar
  78. 78.
    Weyant JP, Hill J (1999) The costs of the Kyoto protocol: a multi-model evaluation; introduction and overview. Energy J 20(Special Issue):vii–xlivGoogle Scholar
  79. 79.
    Kyle P, Clarke L, Rong F, Smith SJ (2010) Climate policy and the long-term evolution of the US buildings sector. Energy J 31:145–172Google Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • James A. Edmonds
    • 1
    Email author
  • Katherine V. Calvin
    • 1
  • Leon E. Clarke
    • 1
  • Anthony C. Janetos
    • 1
  • Son H. Kim
    • 1
  • Marshall A. Wise
    • 1
  • Haewon C. McJeon
    • 1
  1. 1.Joint Global Change Research Institute (JGCRI)Pacific Northwest National Laboratory (PNNL)College ParkUSA

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