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The IIASA IAM framework consists of a combination of five different models or modules - the energy model MESSAGE, the land use model GLOBIOM, the air pollution and GHG model GAINS, the aggregated macro-economic model MACRO and the simple climate model MAGICC - which complement each other and are specialized in different areas. All models and modules together build the IIASA IAM framework, also referred to as MESSAGE-GLOBIOM owing to the fact that the energy model MESSAGE and the land use model GLOBIOM are its most important components. The five models provide input to and iterate between each other during a typical SSP scenario development cycle. Below is a brief overview of how the models interact and describe which further steps are taken within the IIASA IAM framework to develop an SSP scenario.
MESSAGEix<ref>Daniel Huppmann, Matthew Gidden, Oliver Fricko, Peter Kolp, Clara Orthofer, Michael Pimmer, Nikolay Kushin, Adriano Vinca, Alessio Mastrucci, Keywan Riahi, and Volker Krey. The messageix 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. ''Environmental Modelling & Software'', 112:143–156, 2019. doi:10.1016/j.envsoft.2018.11.012.</ref> represents the core of the IIASA IAM framework and its main task is to optimize the energy system so that it can satisfy specified energy demand at the lowest cost. MESSAGEix carries out this optimization in an iterative setup with MACRO, which provides estimates of the macro-economic demand response that results from energy system and services costs computed by MESSAGEix. For the six commercial end-use demand categories depicted in MESSAGEix (see [[Energy_demand_-_MESSAGE-GLOBIOM|Demand section of MESSAGEix-GLOBIOM]]), MACRO adjusts useful energy demand based on demand prices until the two models have reached equilibrium (see [[Macro-economy_-_MESSAGE-GLOBIOM|Macro-economy section of MESSAGEix-GLOBIOM]]). It thus reflects price-induced energy efficiency improvements that can occur when energy prices change. MESSAGEix can represent different energy- and climate-related policies (see [https://www.iamcdocumentation.eu/index.php/Policy_-_MESSAGE-GLOBIOM Policy section of MESSAGEix-GLOBIOM)].  


MESSAGE represents the core of the IIASA IAM framework <xr id="fig:MESSAGE-GLOBIOM_iiasaiam"/> and its main task is to optimize the energy system so that it can satisfy specified energy demands at the lowest costs. MESSAGE carries out this optimization in an iterative setup with MACRO, which provides estimates of the macro-economic demand response that results of energy system and services costs computed by MESSAGE. For the six commercial end-use demand categories depicted in MESSAGE (see [[Energy_demand_-_MESSAGE-GLOBIOM|Demand of MESSAGE-GLOBIOM]]), MACRO will adjust useful energy demands, until the two models have reached equilibrium (see [[Macro-economy_-_MESSAGE-GLOBIOM|Macro-economy section of MESSAGE-GLOBIOM]]). This iteration reflects price-induced energy efficiency improvements that can occur when energy prices increase.
GLOBIOM provides MESSAGEix with information on land use and its implications, like the availability and cost of bio-energy, and the availability and cost of emission mitigation in the AFOLU (Agriculture, Forestry and Land Use) sector (see [[Land-use_-_MESSAGE-GLOBIOM|Land-use of MESSAGEix-GLOBIOM]]). To reduce computational costs, MESSAGEix iteratively queries a GLOBIOM emulator which provides an approximation of land-use outcomes during the optimization process instead of requiring the GLOBIOM model to be rerun iteratively. Once the iteration between MESSAGEix and MACRO has converged, the resulting bioenergy demands along with corresponding carbon prices are used for a concluding analysis with the full-fledged GLOBIOM model. This ensures full consistency in the results from MESSAGEix and GLOBIOM, and also allows a more extensive set of land-use related indicators, including spatially explicit information on land use, to be reported.


GLOBIOM provides MESSAGE with information on land use and its implications, like the availability and cost of bio-energy, and availability and cost of emission mitigation in the AFOLU (Agriculture, Forestry and Land Use) sector (see [[Land-use_-_MESSAGE-GLOBIOM|Land-use of MESSAGE-GLOBIOM]]). To reduce computational costs, MESSAGE iteratively queries a GLOBIOM emulator which can provide possible land-use outcomes during the optimization process instead of requiring the GLOBIOM model to be rerun continuously. Only once the iteration between MESSAGE and MACRO has converged, the resulting bioenergy demands along with corresponding carbon prices are used for a concluding online analysis with the full-fledged GLOBIOM model. This ensures full consistency in the modelled results from MESSAGE and GLOBIOM, and also allows the production of a more extensive set of reporting variables.
Air pollution implications of the energy system are computed in MESSAGEix by applying technology-specific pollution coefficients from GAINS (see [[Pollutants_and_non-GHG_forcing_agents_-_MESSAGE-GLOBIOM|Pollutants and non-GHG forcing agents for MESSAGEix-GLOBIOM]] and [[Air_pollution_and_health_-_MESSAGE-GLOBIOM|Air pollution and health of MESSAGEix-GLOBIOM]]). This approach had been applied to the SSP process (Rao et al. 2017)<ref>S. Rao, Z. Klimont, S.J. Smith, R. Van Dingenen, F. Dentener, L. Bouwman, K. Riahi, M. Amann, B.L. Bodirsky, D.P. van Vuuren, L. Aleluia Reis, K. Calvin, L. Drouet, O. Fricko, S. Fujimori, D. Gernaat, P. Havlik, M. Harmsen, T. Hasegawa, C. Heyes, J. Hilaire, G. Luderer, T. Masui, E. Stehfest, J. Strefler, S. van der Sluis, and M. Tavoni. Future air pollution in the shared socio-economic pathways. ''Global Environmental Change'', 42:346–358, 2017. doi:10.1016/j.gloenvcha.2016.05.012.</ref>. Alternatively, GAINS can be run ex-post based on MESSAGEix-GLOBIOM scenarios to estimate air pollution emissions, concentrations and the related health impacts. This approach allows for the analysis of different air polllution policy packages (e.g., current legislation, maximum feasible reduction), including the estimation of costs for air pollution control measures. Examples for applying this way of linking MESSAGEix-GLOBIOM and GAINS can be found in McCollum et al (2018)<ref>D.L. McCollum, W. Zhou, C. Bertram, H.-S. De Boer, V. Bosetti, S. Busch, J. Després, L. Drouet, J. Emmerling, M. Fay, O. Fricko, S. Fujimori, M. Gidden, M. Harmsen, D. Huppmann, G. Iyer, V. Krey, E. Kriegler, C. Nicolas, S. Pachauri, S. Parkinson, M. Poblete-Cazenave, P. Rafaj, N. Rao, J. Rozenberg, A. Schmitz, W. Schoepp, D. Van Vuuren, and K. Riahi. Energy investment needs for fulfilling the paris agreement and achieving the sustainable development goals. ''Nature Energy'', 3(7):589–599, 2018. doi:10.1038/s41560-018-0179-z.</ref> and Grubler et al. (2018)<ref>A. Grubler, C. Wilson, N. Bento, B. Boza-Kiss, V. Krey, D.L. McCollum, N.D. Rao, K. Riahi, J. Rogelj, S. De Stercke, J. Cullen, S. Frank, O. Fricko, F. Guo, M. Gidden, P. Havlík, D. Huppmann, G. Kiesewetter, P. Rafaj, W. Schoepp, and H. Valin. A low energy demand scenario for meeting the 1.5 °c target and sustainable development goals without negative emission technologies. ''Nature Energy'', 3(6):515–527, 2018. doi:10.1038/s41560-018-0172-6.</ref>.


Air pollution implications of the energy system are computed in MESSAGE by applying technology-specific pollution coefficients from GAINS (see [[Pollutants_and_non-GHG_forcing_agents_-_MESSAGE-GLOBIOM|Pollutants and non-GHG forcing agents for MESSAGE-GLOBIOM]] and [[Air_pollution_and_health_-_MESSAGE-GLOBIOM|Air pollution and health of MESSAGE-GLOBIOM]]).
In general, cumulative global GHG emissions from all sectors are constrained at different levels, with equivalent pricing applied to other GHGs, to reach the desired radiative forcing levels (cf. right-hand side). <xr id="fig:MESSAGE-GLOBIOM_iiasaiam"></xr>The climate constraints are thus taken up in the coupled MESSAGEix-GLOBIOM optimization, and the resulting carbon price is fed back to the full-fledged GLOBIOM model for full consistency. Finally, the combined results for land use, energy, and industrial emissions from MESSAGEix and GLOBIOM are merged and fed into MAGICC (see [[Climate_-_MESSAGE-GLOBIOM|Climate of MESSAGEix-GLOBIOM]]), a global carbon-cycle and climate model, which then provides estimates of the climate implications in terms of atmospheric concentrations, radiative forcing, and global-mean temperature increase. Importantly, climate impacts and impacts of the carbon cycle are - depending on the specific application - only partly accounted for in the IIASA IAM framework. The entire framework is linked to an online database infrastructure which allows straightforward visualisation, analysis, comparison and dissemination of results (Riahi et al., 2017)<ref>Keywan Riahi, Detlef P. van Vuuren, Elmar Kriegler, Jae Edmonds, Brian O’Neill, Shinichiro Fujimori, Nico Bauer, Katherine Calvin, Rob Dellink, Oliver Fricko, Wolfgang Lutz, Alexander Popp, Jesus Crespo Cuaresma, Samir KC, Marian Leimbach, Leiwen Jiang, Tom Kram, Shilpa Rao, Johannes Emmerling, Kristie Ebi, Tomoko Hasegawa, Petr Havlik, Florian Humpenoder, Lara Aleluia Da Silva, Steve Smith, Elke Stehfest, Valentina Bosetti, Jiyong Eom, David Gernaat, Toshihiko Masui, Joeri Rogelj, Jessica Strefler, Laurent Drouet, Volker Krey, Gunnar Luderer, Mathijs Harmsen, Kiyoshi Takahashi, Lavinia Baumstark, Jonathan Doelman, Mikiko Kainuma, Zbigniew Klimont, Giacomo Marangoni, Hermann Lotze-Campen, Michael Obersteiner, Andrzej Tabeau, and Massimo Tavoni. The Shared Socioeconomic Pathways and their Energy, Land Use, and Greenhouse Gas Emissions Implications. ''Global Environmental Change'', 42:153–168, 2017. URL: <nowiki>http://pure.iiasa.ac.at/13280/</nowiki>, doi:10.1016/j.gloenvcha.2016.05.009.</ref>.


In general, cumulative global GHG emissions from all sectors are constrained at different levels to reach the forcing levels (cf. right-hand side <xr id="fig:MESSAGE-GLOBIOM_iiasaiam"/>). The climate constraints are thus taken up in the coupled MESSAGE-GLOBIOM optimization, and the resulting carbon price is fed back to the full-fledged GLOBIOM model for full consistency. Finally, the combined results for land use, energy, and industrial emissions from MESSAGE and GLOBIOM are merged and fed into MAGICC (see [[Climate_-_MESSAGE-GLOBIOM|Climate of MESSAGE-GLOBIOM]]), a global carbon-cycle and climate model, which then provides estimates of the climate implications in terms of atmospheric concentrations, radiative forcing, and global-mean temperature increase. Importantly, climate impacts and impacts of the carbon cycle are currently not accounted for in the IIASA IAM framework. The entire framework is linked to an online database infrastructure which allows straightforward visualisation, analysis, comparison and dissemination of results (Fricko et al., 2016 [[CiteRef::MSG-GLB_fricko_marker_2016]]).
The scientific software underlying the global MESSAGEix-GLOBIOM model is called the MESSAGEix framework, an open-source, versatile implementation of a linear optimization problem, with the option of coupling to the computable general equilibrium (CGE) model MACRO to incorporate the effect of price changes on economic activity and demand for commodities and resources. MESSAGEix is integrated with the ''ix modelling platform (ixmp)'', a "data warehouse" for version control of reference timeseries, input data and model results. ixmp provides interfaces to the scientific programming languages Python and R for efficient, scripted workflows for data processing and visualisation of results (Huppmann et al., 2019)<ref>Daniel Huppmann, Matthew Gidden, Oliver Fricko, Peter Kolp, Clara Orthofer, Michael Pimmer, Nikolay Kushin, Adriano Vinca, Alessio Mastrucci, Keywan Riahi, and Volker Krey. The messageix 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. ''Environmental Modelling & Software'', 112:143–156, 2019. doi:10.1016/j.envsoft.2018.11.012.</ref>.


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<figure id="fig:MESSAGE-GLOBIOM_iiasaiam">
<figure id="fig:MESSAGE-GLOBIOM_iiasaiam">
 
[[File:iiasaiam.png|left|900px|thumb|<caption>Overview of the IIASA IAM framework. Coloured boxes represent respective specialized disciplinary models which are integrated for generating internally consistent scenarios. Figure from Riahi et al. (2016).</caption>]] [[CiteRef::MSG-GLB_riahi_shared_2016]]
[[File:iiasaiam.png|900px|thumb|<caption>Overview of the IIASA IAM framework. Coloured boxes represent respective specialized disciplinary models which are integrated for generating internally consistent scenarios (Riahi et al., 2016 [[CiteRef::MSG-GLB_riahi_shared_2016]])</caption>]]
 
</figure>
</figure>
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Latest revision as of 14:01, 16 November 2020

Model Documentation - MESSAGE-GLOBIOM

Corresponding documentation
Previous versions
Model information
Model link
Institution International Institute for Applied Systems Analysis (IIASA), Austria, http://data.ene.iiasa.ac.at.
Solution concept General equilibrium (closed economy)
Solution method Optimization
Anticipation

MESSAGEix[1] represents the core of the IIASA IAM framework and its main task is to optimize the energy system so that it can satisfy specified energy demand at the lowest cost. MESSAGEix carries out this optimization in an iterative setup with MACRO, which provides estimates of the macro-economic demand response that results from energy system and services costs computed by MESSAGEix. For the six commercial end-use demand categories depicted in MESSAGEix (see Demand section of MESSAGEix-GLOBIOM), MACRO adjusts useful energy demand based on demand prices until the two models have reached equilibrium (see Macro-economy section of MESSAGEix-GLOBIOM). It thus reflects price-induced energy efficiency improvements that can occur when energy prices change. MESSAGEix can represent different energy- and climate-related policies (see Policy section of MESSAGEix-GLOBIOM).

GLOBIOM provides MESSAGEix with information on land use and its implications, like the availability and cost of bio-energy, and the availability and cost of emission mitigation in the AFOLU (Agriculture, Forestry and Land Use) sector (see Land-use of MESSAGEix-GLOBIOM). To reduce computational costs, MESSAGEix iteratively queries a GLOBIOM emulator which provides an approximation of land-use outcomes during the optimization process instead of requiring the GLOBIOM model to be rerun iteratively. Once the iteration between MESSAGEix and MACRO has converged, the resulting bioenergy demands along with corresponding carbon prices are used for a concluding analysis with the full-fledged GLOBIOM model. This ensures full consistency in the results from MESSAGEix and GLOBIOM, and also allows a more extensive set of land-use related indicators, including spatially explicit information on land use, to be reported.

Air pollution implications of the energy system are computed in MESSAGEix by applying technology-specific pollution coefficients from GAINS (see Pollutants and non-GHG forcing agents for MESSAGEix-GLOBIOM and Air pollution and health of MESSAGEix-GLOBIOM). This approach had been applied to the SSP process (Rao et al. 2017)[2]. Alternatively, GAINS can be run ex-post based on MESSAGEix-GLOBIOM scenarios to estimate air pollution emissions, concentrations and the related health impacts. This approach allows for the analysis of different air polllution policy packages (e.g., current legislation, maximum feasible reduction), including the estimation of costs for air pollution control measures. Examples for applying this way of linking MESSAGEix-GLOBIOM and GAINS can be found in McCollum et al (2018)[3] and Grubler et al. (2018)[4].

In general, cumulative global GHG emissions from all sectors are constrained at different levels, with equivalent pricing applied to other GHGs, to reach the desired radiative forcing levels (cf. right-hand side). <xr id="fig:MESSAGE-GLOBIOM_iiasaiam"></xr>The climate constraints are thus taken up in the coupled MESSAGEix-GLOBIOM optimization, and the resulting carbon price is fed back to the full-fledged GLOBIOM model for full consistency. Finally, the combined results for land use, energy, and industrial emissions from MESSAGEix and GLOBIOM are merged and fed into MAGICC (see Climate of MESSAGEix-GLOBIOM), a global carbon-cycle and climate model, which then provides estimates of the climate implications in terms of atmospheric concentrations, radiative forcing, and global-mean temperature increase. Importantly, climate impacts and impacts of the carbon cycle are - depending on the specific application - only partly accounted for in the IIASA IAM framework. The entire framework is linked to an online database infrastructure which allows straightforward visualisation, analysis, comparison and dissemination of results (Riahi et al., 2017)[5].

The scientific software underlying the global MESSAGEix-GLOBIOM model is called the MESSAGEix framework, an open-source, versatile implementation of a linear optimization problem, with the option of coupling to the computable general equilibrium (CGE) model MACRO to incorporate the effect of price changes on economic activity and demand for commodities and resources. MESSAGEix is integrated with the ix modelling platform (ixmp), a "data warehouse" for version control of reference timeseries, input data and model results. ixmp provides interfaces to the scientific programming languages Python and R for efficient, scripted workflows for data processing and visualisation of results (Huppmann et al., 2019)[6].

<figure id="fig:MESSAGE-GLOBIOM_iiasaiam">

Overview of the IIASA IAM framework. Coloured boxes represent respective specialized disciplinary models which are integrated for generating internally consistent scenarios. Figure from Riahi et al. (2016).
MSG-GLB_riahi_shared_2016

</figure>

  1. ↑ Daniel Huppmann, Matthew Gidden, Oliver Fricko, Peter Kolp, Clara Orthofer, Michael Pimmer, Nikolay Kushin, Adriano Vinca, Alessio Mastrucci, Keywan Riahi, and Volker Krey. The messageix 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. Environmental Modelling & Software, 112:143–156, 2019. doi:10.1016/j.envsoft.2018.11.012.
  2. ↑ S. Rao, Z. Klimont, S.J. Smith, R. Van Dingenen, F. Dentener, L. Bouwman, K. Riahi, M. Amann, B.L. Bodirsky, D.P. van Vuuren, L. Aleluia Reis, K. Calvin, L. Drouet, O. Fricko, S. Fujimori, D. Gernaat, P. Havlik, M. Harmsen, T. Hasegawa, C. Heyes, J. Hilaire, G. Luderer, T. Masui, E. Stehfest, J. Strefler, S. van der Sluis, and M. Tavoni. Future air pollution in the shared socio-economic pathways. Global Environmental Change, 42:346–358, 2017. doi:10.1016/j.gloenvcha.2016.05.012.
  3. ↑ D.L. McCollum, W. Zhou, C. Bertram, H.-S. De Boer, V. Bosetti, S. Busch, J. Després, L. Drouet, J. Emmerling, M. Fay, O. Fricko, S. Fujimori, M. Gidden, M. Harmsen, D. Huppmann, G. Iyer, V. Krey, E. Kriegler, C. Nicolas, S. Pachauri, S. Parkinson, M. Poblete-Cazenave, P. Rafaj, N. Rao, J. Rozenberg, A. Schmitz, W. Schoepp, D. Van Vuuren, and K. Riahi. Energy investment needs for fulfilling the paris agreement and achieving the sustainable development goals. Nature Energy, 3(7):589–599, 2018. doi:10.1038/s41560-018-0179-z.
  4. ↑ A. Grubler, C. Wilson, N. Bento, B. Boza-Kiss, V. Krey, D.L. McCollum, N.D. Rao, K. Riahi, J. Rogelj, S. De Stercke, J. Cullen, S. Frank, O. Fricko, F. Guo, M. Gidden, P. Havlík, D. Huppmann, G. Kiesewetter, P. Rafaj, W. Schoepp, and H. Valin. A low energy demand scenario for meeting the 1.5 °c target and sustainable development goals without negative emission technologies. Nature Energy, 3(6):515–527, 2018. doi:10.1038/s41560-018-0172-6.
  5. ↑ Keywan Riahi, Detlef P. van Vuuren, Elmar Kriegler, Jae Edmonds, Brian O’Neill, Shinichiro Fujimori, Nico Bauer, Katherine Calvin, Rob Dellink, Oliver Fricko, Wolfgang Lutz, Alexander Popp, Jesus Crespo Cuaresma, Samir KC, Marian Leimbach, Leiwen Jiang, Tom Kram, Shilpa Rao, Johannes Emmerling, Kristie Ebi, Tomoko Hasegawa, Petr Havlik, Florian Humpenoder, Lara Aleluia Da Silva, Steve Smith, Elke Stehfest, Valentina Bosetti, Jiyong Eom, David Gernaat, Toshihiko Masui, Joeri Rogelj, Jessica Strefler, Laurent Drouet, Volker Krey, Gunnar Luderer, Mathijs Harmsen, Kiyoshi Takahashi, Lavinia Baumstark, Jonathan Doelman, Mikiko Kainuma, Zbigniew Klimont, Giacomo Marangoni, Hermann Lotze-Campen, Michael Obersteiner, Andrzej Tabeau, and Massimo Tavoni. The Shared Socioeconomic Pathways and their Energy, Land Use, and Greenhouse Gas Emissions Implications. Global Environmental Change, 42:153–168, 2017. URL: http://pure.iiasa.ac.at/13280/, doi:10.1016/j.gloenvcha.2016.05.009.
  6. ↑ Daniel Huppmann, Matthew Gidden, Oliver Fricko, Peter Kolp, Clara Orthofer, Michael Pimmer, Nikolay Kushin, Adriano Vinca, Alessio Mastrucci, Keywan Riahi, and Volker Krey. The messageix 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. Environmental Modelling & Software, 112:143–156, 2019. doi:10.1016/j.envsoft.2018.11.012.
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