Published October 10, 2025
| Version v1
Journal article
Open
Model linking for low-carbon transitions: Technical and conceptual challenges and best practices
Authors/Creators
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Keppo, Ilkka Johannes1
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Al Khourdajie, Alaa2, 3
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Gardumi, Francesco4
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Holtz, Georg5
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Nikas, Alexandros6
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Xexakis, Georgios7
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Ferreras-Alonso, Noelia8
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Fragkos, Panagiotis9
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Frilingou, Natasha10
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Ghadaksaz, Hesam1
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Hawkes, Adam2
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Mateo, Adrián11
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Mittal, Shivika12
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Parrado-Hernando, Gonzalo13
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Peters, Glen P.12
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Rinaldi, Lorenzo14
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Rocco, Matteo Vincenzo15
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Sognnaes, Ida Andrea Braathen16
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van de Ven, Dirk-Jan17
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Zamanipour, Behzad1
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1.
Aalto University
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2.
Imperial College London
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3.
International Institute for Applied Systems Analysis
- 4. KTH Royal Institute of Technology
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5.
Wuppertal Institute for Climate, Environment and Energy
- 6. National Technical University of Athens, Greece
- 7. HOLISTIC, Greece
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8.
CARTIF
- 9. E3 Modelling SA
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10.
National Technical University of Athens
- 11. CARTIF Foundation, Spain
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12.
CICERO Center for International Climate Research
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13.
Universidad de Valladolid
- 14. Politecnico di Milano Dipartimento di Energia
- 15. Department of Energy, Politecnico di Milano, Italy
- 16. CICERO Center for International Climate Research, Norway
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17.
Basque Centre for Climate Change
Description
Linking existing models to extend energy system and integrated assessment analysis is an increasingly common practice. Despite this, and unlike in the field of environmental and earth sciences, little attention has so far been paid to the details of it, to the trade-offs involved and the way in which the model linking affects the interpretation of the outcomes of the interlinked model system. Our aim in this paper is to first focus on a set of key technical and methodological problems that are common in model linking and suggest how these could be approached in different model linking contexts. We then further explore how model linking may affect the nature of the knowledge produced, and how this should be considered in the model linking process. Reflecting our literature driven assessment of the issues and possible solutions, we compile “a check list” to assist in the process of decision making for model linking.
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