Policy - MESSAGE-GLOBIOM: Difference between revisions
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A number of different energy- and climate-related policies are, depending on the scenario setup and the research question | A number of different energy- and climate-related policies are, depending on the scenario setup and the research question, explicitly represented in MESSAGEix. This includes the following list of policies: | ||
*GHG emission pricing | *GHG emission pricing | ||
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*Air pollution legislation packages (fixed legislation, current and planned legislation, stringent legislation, maximum feasible reduction) | *Air pollution legislation packages (fixed legislation, current and planned legislation, stringent legislation, maximum feasible reduction) | ||
In general, these policies are implemented via constraints or cost coefficients (negative and positive) in the optimization problem. | In general, these policies are implemented via constraints or cost coefficients (negative and positive) in the optimization problem. For air pollution policies, the different legislation packages are implemented via a set of emission coefficients and associated costs derived from the [[Pollutants_and_non-GHG_forcing_agents_-_MESSAGE-GLOBIOM|GAINS model]]. The cost coefficients are, however, not part of the optimization procedure, but instead allow an ex-post quantification of air pollution policy costs for a specific energy scenario. | ||
Latest revision as of 11:14, 16 November 2020
| Corresponding documentation | |
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| 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 | |
A number of different energy- and climate-related policies are, depending on the scenario setup and the research question, explicitly represented in MESSAGEix. This includes the following list of policies:
- GHG emission pricing
- GHG emission caps and trading permits
- Renewable energy portfolio standards (e.g., share of renewable energy in electricity generation)
- Renewable energy and other technology capacity targets
- Energy import taxes
- Fuel subsidies and micro-financing for achieving universal access to modern energy services in developing countries
- Air pollution legislation packages (fixed legislation, current and planned legislation, stringent legislation, maximum feasible reduction)
In general, these policies are implemented via constraints or cost coefficients (negative and positive) in the optimization problem. For air pollution policies, the different legislation packages are implemented via a set of emission coefficients and associated costs derived from the GAINS model. The cost coefficients are, however, not part of the optimization procedure, but instead allow an ex-post quantification of air pollution policy costs for a specific energy scenario.