A type of scientific modelling that tries to link main features of society and economy with the biosphere and atmosphere into one modelling framework.

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Integrated assessment modelling (IAM) or integrated modelling (IM) is a term used for a type of scientific modelling that tries to link main features of society and economy with the biosphere and atmosphere into one modelling framework. The goal of integrated assessment modelling is to accommodate informed policy-making, usually in the context of climate change 1 though also in other areas of human and social development. While the detail and extent of integrated disciplines varies strongly per model, all climatic integrated assessment modelling includes economic processes as well as processes producing greenhouse gases.2 Other integrated assessment models also integrate other aspects of human development such as education, health, infrastructure, and governance.

These models are integrated because they span multiple academic disciplines, including economics and climate science and for more comprehensive models also energy systems, land-use change, agriculture, infrastructure, conflict, governance, technology, education, and health. The word assessment comes from the use of these models to provide information for answering policy questions.3 To quantify these integrated assessment studies, numerical models are used. Integrated assessment modelling does not provide predictions for the future but rather estimates what possible scenarios look like.3

There are different types of integrated assessment models. One classification distinguishes between firstly models that quantify future developmental pathways or scenarios and provide detailed, sectoral information on the complex processes modelled. Here they are called process-based models. Secondly, there are models that aggregate the costs of climate change and climate change mitigation to find estimates of the total costs of climate change.2 A second classification makes a distinction between models that extrapolate verified patterns (via econometrics equations), or models that determine (globally) optimal economic solutions from the perspective of a social planner, assuming (partial) equilibrium of the economy.45

Process-based models

Intergovernmental Panel on Climate Change (IPCC) have relied on process-based integrated assessment models to quantify mitigation scenarios.67 They have been used to explore different pathways for staying within climate policy targets such as the 1.5 °C target agreed upon in the Paris Agreement. Moreover, these models have underpinned research including energy policy assessment and simulate the Shared socioeconomic pathways.89 Notable modelling frameworks include IMAGE,10 MESSAGEix,11 AIM/GCE,12 GCAM,13 REMIND-MAgPIE,14 and WITCH-GLOBIOM.1516 While these scenarios are highly policy-relevant, interpretation of the scenarios should be done with care.17

A Review of Criticisms of Integrated Assessment Models and Proposed Approaches to Address These, through the Lens of BECCS
— Energies, MDPI

Non-equilibrium models include[26] those based on econometric equations and evolutionary economics (such as E3ME),[^27] and agent-based models (such as the agent-based DSK-model).5 These models typically do not assume rational and representative agents, nor market equilibrium in the long term.18

Aggregate cost-benefit models

Cost-benefit integrated assessment models are the main tools for calculating the social cost of carbon, or the marginal social cost of emitting one more tonne of carbon (as carbon dioxide) into the atmosphere at any point in time.[28] For instance, the DICE,[29] PAGE,[30] and FUND[31] models have been used by the US Interagency Working Group to calculate the social cost of carbon and its results have been used for regulatory impact analysis.[32]

This type of modelling is carried out to find the total cost of climate impacts, which are generally considered a negative externality not captured by conventional markets. In order to correct such a market failure, for instance by using a carbon tax, the cost of emissions is required.[28] However, the estimates of the social cost of carbon are highly uncertain[33] and will remain so for the foreseeable future.[34] It has been argued that “IAM-based analyses of climate policy create a perception of knowledge and precision that is illusory, and can fool policy-makers into thinking that the forecasts the models generate have some kind of scientific legitimacy”.[35] Still, it has been argued that attempting to calculate the social cost of carbon is useful to gain insight into the effect of certain processes on climate impacts, as well as to better understand one of the determinants international cooperation in the governance of climate agreements.[33]

Integrated assessment models have not been used solely to assess environmental or climate change-related fields. They have also been used to analyze patterns of conflict,[36] the Sustainable Development Goals,[37] trends across issue area in Africa,[38] and food security.[39]

Shortcomings
All numerical models have shortcomings. In 2021, the integrated assessment modeling community examined gaps in what was termed the “possibility space” and how these might best be consolidated and addressed.[40]

REMIND by PIK

REMIND (REgional Model of Investment and Development) is a numerical model that represents the future evolution of the world economies with a special focus on the development of the energy sector and the implications for our world climate. The goal of REMIND is to find the optimal mix of investments in the economy and the energy sectors of each model region given a set of population, technology, policy and climate constraints. It also accounts for regional trade characteristics on goods, energy fuels, and emissions allowances. All greenhouse gas emissions due to human activities are represented in the model.

REMIND is used in connection with other models to provide a detailed answer. One such model is MAgPIE (Model of Agricultural Production and its Impacts on the Environment).

https://unfccc.int/topics/mitigation/workstreams/response-measures/integrated-assessment-models-iams-and-energy-environment-economy-e3-models

https://www.zhihu.com/question/59956643

http://scholar.pku.edu.cn/hanchengdai

  1. Wang, Zheng; Wu, Jing; Liu, Changxin; Gu, Gaoxiang (2017). Integrated Assessment Models of Climate Change Economics. Singapore: Springer Singapore. https://www.springer.com/gp/book/9789811039430. ↩︎

  2. Weyant, John (2017). “Some Contributions of Integrated Assessment Models of Global Climate Change”. Review of Environmental Economics and Policy. 11 (1): 115–137. doi:10.1093/reep/rew018 ↩︎ ↩︎

  3. “Inaugural lecture Detlef van Vuuren: Integrated Assessment: Back to the Future - PBL Netherlands Environmental Assessment Agency”. www.pbl.nl. Retrieved 2019-06-01. ↩︎ ↩︎

  4. Pauliuk, Stefan; Arvesen, Anders; Stadler, Konstantin; Hertwich, Edgar G. (2017). “Industrial ecology in integrated assessment models”. Nature Climate Change. 7 (1): 13–20. ↩︎

  5. Lamperti, F.; Dosi, G.; Napoletano, M.; Roventini, A.; Sapio, A. (2018). “Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model”. Ecological Economics. 150: 315–339. doi:10.1016/j.ecolecon.2018.03.023. ↩︎ ↩︎

  6. Intergovernmental Panel on Climate Change Staff. (2015-01-26). Climate Change 2014: Mitigation of Climate Change : Working Group III Contribution to the IPCC Fifth Assessment Report. ISBN 978-1107654815. OCLC 994399607. ↩︎

  7. Intergovernmental Panel on Climate Change, issuing body. Global warming of 1.5°C. OCLC 1056192590. ↩︎

  8. “Explainer: How ‘Shared Socioeconomic Pathways’ explore future climate change”. Carbon Brief. 2018-04-19. Retrieved 2019-06-02. ↩︎

  9. Riahi, Keywan et al. (2017-01-01). “The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview”. Global Environmental Change. 42: 153–168. doi:10.1016/j.gloenvcha.2016.05.009. ISSN 0959-3780 ↩︎

  10. Stehfest, E. (Elke) (2014). Integrated assessment of global environmental change with IMAGE 3.0 : model description and policy applications. ↩︎

  11. Huppmann, Daniel et al. (February 2019). “The MESSAGE Integrated Assessment Model and the ix modeling platform (ixmp): An open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development” (PDF). Environmental Modelling & Software. 112: 143–156. doi:10.1016/j.envsoft.2018.11.012. ↩︎

  12. Fujimori, Shinichiro; Masui, Toshihiko; Matsuoka, Yuzuru (2017), “AIM/CGE V2.0 Model Formula”, Post-2020 Climate Action, Springer Singapore, pp. 201–303, doi:10.1007/978-981-10-3869-3_12, ↩︎

  13. Calvin, Katherine et al. “GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems”. Geoscientific Model Development. 12 (2): 677–698. doi:10.5194/gmd-12-677-2019. ISSN 1991-9603. ↩︎

  14. Luderer, Gunnar et al. “Description of the REMIND Model (Version 1.6)”. SSRN Working Paper Series. doi:10.2139/ssrn.2697070. ISSN 1556-5068. ↩︎

  15. Bosetti, Valentina et al. (2006) “WITCH - A World Induced Technical Change Hybrid Model” (PDF). SSRN Working Paper Series. doi:10.2139/ssrn.948382. ISSN 1556-5068. ↩︎

  16. Gambhir, Ajay; Butnar, Isabela; Li, Pei-Hao; Smith, Pete; Strachan, Neil (2019-05-08). “A Review of Criticisms of Integrated Assessment Models and Proposed Approaches to Address These, through the Lens of BECCS”. Energies. 12 (9): 1747. doi:10.3390/en12091747. ISSN 1996-1073. ↩︎

  17. Huppmann, Daniel et al. (2018-10-15) “A new scenario resource for integrated 1.5 °C research” (PDF). Nature Climate Change. 8 (12): 1027–1030. doi:10.1038/s41558-018-0317-4. ISSN 1758-678X. S2CID 92398486. ↩︎

  18. Hafner, Sarah et al. (2020-11-01). “Emergence of New Economics Energy Transition Models: A Review”. Ecological Economics. 177: 106779. ↩︎