Agriculture - REMIND-MAgPIE: Difference between revisions
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REMIND derives non-CO2 emissions in the absence of climate policies from various agricultural activities for given assumptions on socio-economic pathways from corresponding MAgPIE scenarios. An important nexus between the energy system and agriculture is bioenergy demand. In standalone mode, REMIND uses bioenergy supply costs derived from MAgPIE, see section “Bioenergy”. To account for the sensitivity of resource potentials to carbon pricing, REMIND uses different supply curve parameterizations in baseline and climate policy scenarios. Bioenergy-induced emissions of N2O (fertilizer use) and CO2 (land-use change) are accounted for using specific per-unit emission coefficients. | REMIND derives non-CO2 emissions in the absence of climate policies from various agricultural activities for given assumptions on socio-economic pathways from corresponding MAgPIE scenarios. An important nexus between the energy system and agriculture is bioenergy demand. In standalone mode, REMIND uses bioenergy supply costs derived from MAgPIE, see section “Bioenergy”. To account for the sensitivity of resource potentials to carbon pricing, REMIND uses different supply curve parameterizations in baseline and climate policy scenarios. Bioenergy-induced emissions of N2O (fertilizer use) and CO2 (land-use change) are accounted for using specific per-unit emission coefficients. | ||
In standalone mode, REMIND derives the economic mitigation potential of agricultural CH4 and N2O emissions is calculated using marginal abatement cost curves (MACCs) from Lucas | In standalone mode, REMIND derives the economic mitigation potential of agricultural CH4 and N2O emissions is calculated using marginal abatement cost curves (MACCs) from Lucas <ref>Lucas PL, van Vuuren DP, Olivier JGJ, den Elzen MGJ (2007) Long-term reduction potential of non-CO2 greenhouse gases. Environmental Science & Policy 10:85–103. doi: 10.1016/j.envsci.2006.10.007</ref>. For land-use related CO2, similar MACCs derived from MAgPIE are employed. | ||
As described in [http://themasites.pbl.nl/models/advance/index.php/Land-use_-_REMIND Figure 1], if run in coupled mode REMIND adopts consistent GHG emission projections and bioenergy supply curves from MAgPIE. | As described in [http://themasites.pbl.nl/models/advance/index.php/Land-use_-_REMIND Figure 1], if run in coupled mode REMIND adopts consistent GHG emission projections and bioenergy supply curves from MAgPIE. |
Revision as of 14:51, 3 February 2017
Corresponding documentation | |
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Previous versions | |
Model information | |
Model link | |
Institution | Potsdam Institut für Klimafolgenforschung (PIK), Germany, https://www.pik-potsdam.de. |
Solution concept | General equilibrium (closed economy)MAgPIE: partial equilibrium model of the agricultural sector; |
Solution method | OptimizationMAgPIE: cost minimization; |
Anticipation |
REMIND derives non-CO2 emissions in the absence of climate policies from various agricultural activities for given assumptions on socio-economic pathways from corresponding MAgPIE scenarios. An important nexus between the energy system and agriculture is bioenergy demand. In standalone mode, REMIND uses bioenergy supply costs derived from MAgPIE, see section “Bioenergy”. To account for the sensitivity of resource potentials to carbon pricing, REMIND uses different supply curve parameterizations in baseline and climate policy scenarios. Bioenergy-induced emissions of N2O (fertilizer use) and CO2 (land-use change) are accounted for using specific per-unit emission coefficients.
In standalone mode, REMIND derives the economic mitigation potential of agricultural CH4 and N2O emissions is calculated using marginal abatement cost curves (MACCs) from Lucas [1]. For land-use related CO2, similar MACCs derived from MAgPIE are employed.
As described in Figure 1, if run in coupled mode REMIND adopts consistent GHG emission projections and bioenergy supply curves from MAgPIE.
- ↑ Lucas PL, van Vuuren DP, Olivier JGJ, den Elzen MGJ (2007) Long-term reduction potential of non-CO2 greenhouse gases. Environmental Science & Policy 10:85–103. doi: 10.1016/j.envsci.2006.10.007