Gaseous fuels - MESSAGE-GLOBIOM
|Model Documentation - MESSAGE-GLOBIOM|
|Institution|| International Institute for Applied Systems Analysis (IIASA), Austria, http://data.ene.iiasa.ac.at/message-globiom/.|
main users: IIASA, the MESSAGE model is distributed via the International Atomic Energy Agency (IAEA) to member countries
|Solution concept||Hybrid model (energy engineering and land use partial equilibrium models soft-linked to macro-economic general equilibrium model)|
|Solution method||Hybrid model (linear program optimization for the energy systems and land-use modules, non-linear program optimization for the macro-economic module)|
|Anticipation||Myopic/Perfect Foresight (MESSAGE can be run both with perfect foresight and myopically, while GLOBIOM runs myopically)|
See Table 1 for a list of gaseous fuel production technologies in MESSAGE.
|biomass gasification with CCS|
|coal gasification with CCS|
See Table 2 for a list of hydrogen production technologies in MESSAGE.
|Energy source||Technology||Electricity cogeneration|
|Gas||steam methane reforming||yes|
|steam methane reforming with CCS||no|
|coal gasification with CCS||yes|
|biomass gasification with CCS||yes|
As already mentioned in the section for :ref:`electricity`, technological change in MESSAGE is generally treated exogenously, although pioneering work on the endogenization of technological change in energy-engineering type models has been done with MESSAGE (Messner, 1997 1). The current cost and performance parameters, including conversion efficiencies and emission coefficients is generally derived from the relevant engineering literature. For the future alternative cost and performance projections are usually developed to cover a relatively wide range of uncertainties that influences model results to a good extent. As an example, Figure 1 below provides an overview of costs ranges for a set of key energy conversion technologies (Fricko et al., 2016 2).
In Figure 1, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively. Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. CCS – Carbon capture and storage; CTL – Coal to liquids; GTL – Gas to liquids; BTL – Biomass to liquids (Fricko et al., 2016 2).
- Sabine Messner (1997). Endogenized technological learning in an energy systems model. Journal of Evolutionary Economics, 7 (3), 291--313. |
- Oliver Fricko, Petr Havlik, Joeri Rogelj, Zbigniew Klimont, Mykola Gusti, Nils Johnson, Peter Kolp, Manfred Strubegger, Hugo Valin, Markus Amann, Tatiana Ermolieva, Nicklas Forsell, Mario Herrero, Chris Heyes, Georg Kindermann, Volker Krey, David L McCollum, Michael Obersteiner, Shonali Pachauri, Shilpa Rao, Erwin Schmid, Wolfgang Schoepp, Keywan Riahi (2016). The marker quantification of the shared socioeconomic pathway 2: a middle-of-the-road scenario for the 21st century. Global Environmental Change, In press (). |