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2020
DOI: 10.1039/c9ee02627d
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MEDEAS: a new modeling framework integrating global biophysical and socioeconomic constraints

Abstract: Description of the open-source MEDEAS integrated assessment modeling framework, which focuses on the biophysical and economic dimensions, restrictions and interactions arising during energy transitions.

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Cited by 104 publications
(113 citation statements)
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References 175 publications
(269 reference statements)
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“…Today, several IAMs coexist to deal with the complex interactions, high uncertainties and knowledge gaps between interconnections within the environment and human societies. For these reasons, it is usually quite challenging to compare IAMs with very different characteristics [10]. Moreover, these simulation tools do not consider the possibility to jointly analyse the resource limitations, the impact of climate and the feedbacks with the environment; besides they are mainly world models with no geographical disaggregation of the economic evolution at lower geographical levels.…”
Section: Discussionmentioning
confidence: 99%
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“…Today, several IAMs coexist to deal with the complex interactions, high uncertainties and knowledge gaps between interconnections within the environment and human societies. For these reasons, it is usually quite challenging to compare IAMs with very different characteristics [10]. Moreover, these simulation tools do not consider the possibility to jointly analyse the resource limitations, the impact of climate and the feedbacks with the environment; besides they are mainly world models with no geographical disaggregation of the economic evolution at lower geographical levels.…”
Section: Discussionmentioning
confidence: 99%
“…This theme becomes even more difficult when the phenomena under study concern the dynamics of complex systems like socio-economic systems, energy systems and environmental systems that are all interconnected by a dense network of feedbacks. In this case, it is necessary to resort to the use of While the World and EU MEDEAS models have already been presented and discussed in the literature [10], [17], [18], [23], [24], [25], until the current work, the MEDEAS country models for Austria and Bulgaria had not been the subject of any publication. Hence, the current work aims to present the adaptation of the MEDEAS models to a smaller regional scale as well as to test their validity by benchmarking their results against the well-known TIMES and LEAP models.…”
Section: Introductionmentioning
confidence: 99%
“…The MEDEAS suite of models [5] is a set of mathematical models that aims to improve the state-of-the-art of IAMs: System dynamics modeling approach makes MEDEAS able to overcome the traditional IAMs sequential structure that allows only for a restricted number of feedbacks among the represented subsystems. Indeed, the highly aggregated nature of the dynamics simulated with IAMs usually translates in an oversimplification of the dynamics related to the economic dimension, e.g., by using aggregated production functions and using prices as indicators of scarcity [6].…”
Section: Introductionmentioning
confidence: 99%
“…Considering new limits for RES and the impacts of climate change, MEDEAS configures as a more advanced IAM, providing new perspectives on the actions required for the transition, identifying new topics that need attention and further study, for instance, scarcity of the rare earth metals needed to develop energy storage [15,16]. MEDEAS also configures as powerful tools to give insight on 'decoupling' strategies [17]: In MEDEAS, economic demand is estimated from exogenous pathways of expected per capita gross domestic product and population evolution [5,13].…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, renewable energy sources (RES) are assumed with no limitations and, most relevant, IAMs often omit climate change assessment and impacts (Dietz et al, 2015;Diaz et al, 2017;Ringkjøb et al, 2017). MEDEAS novel approach proposes a new modelling framework, integrating global biophysical and socioeconomic constraints, providing advanced overtures in interpreting experimental data and in developing more performant IAMs (Capellan-Perez et al, 2019a, 2019bSolé et al, 2019).…”
Section: Introductionmentioning
confidence: 99%