Bioenergy - REMIND-MAgPIE: Difference between revisions
m (1 revision imported) |
Laura Delsa (talk | contribs) No edit summary |
||
| Line 3: | Line 3: | ||
|DocumentationCategory=Bioenergy | |DocumentationCategory=Bioenergy | ||
}} | }} | ||
== Bioenergy == | |||
REMIND models three types of bioenergy feedstocks: | |||
# First-generation biomass produced from sugar, starch, and oilseeds (typically small in quantity, based on an exogenous scenario); | |||
# Ligno-cellulosic residues from agriculture and forest; and | |||
# Second-generation purpose-grown biomass from specialized ligno-cellulosic grassy and woody bioenergy crops, such as miscanthus, poplar, and eucalyptus. | |||
To represent supply of purpose-grown bioenergy from the land-use sector, REMIND draws on an emulation of the land-use model MAgPIE (Model of Agricultural Production and its Impact on the Environment) (Lotze-Campen et al. 2008; Popp et al. 2010; Lotze-Campen et al. 2010). The emulator describes supply costs and total agricultural emissions as a function of bioenergy demand, as described in detail in Klein et al. (2014). The supply curves capture the time, scale and region dependent change of bioenergy production costs, as well as path dependencies resulting from past land conversions and induced technological changes in the land-use sector, as represented in MAgPIE. Ligno-cellulosic agricultural and forest residues bases on low-cost bioenergy supply options. Their potential is assumed to increase from 20 EJ/yr in 2005 to 70 EJ/yr in 2100 (Chum et al. 2011), based on Haberl et al. (2010). | |||
In REMIND, we assume that the use of traditional biomass (supplied by residues) is phased out, as modern and less harmful fuels are increasingly used with rising incomes rise (Sims et al. 2010). We also assume that first generation modern biofuels are phased-out, reflecting their high costs and to account for concerns about land-use impacts, co-emissions, and competition with food production from first-generation biofuels (Fargione et al. 2008; Searchinger et al. 2008). As a concequence, the main sources of bioenergy in REMIND sceanrios are second-generation purpose-grown biomass and from ligno-cellulosic agricultural and forestry residues. | |||
REMIND represents a number of energy conversion technologies using bioenergy as feedstock. If REMIND is run stand-alone, bioenergy resource potentials are represented as time-dependent and region-specific supply cost-curves derived from MAgPIE (Klein et al. 2014). To account for the sensitivity of resource potentials to carbon pricing, REMIND uses different supply curve parameterizations in baseline and climate policy scenarios. Direct and indirect GHG emissions (CO<sub>2</sub> and N<sub>2</sub>O) induced by bioenergy production are accounted for using specific emission factors. | REMIND represents a number of energy conversion technologies using bioenergy as feedstock. If REMIND is run stand-alone, bioenergy resource potentials are represented as time-dependent and region-specific supply cost-curves derived from MAgPIE (Klein et al. 2014). To account for the sensitivity of resource potentials to carbon pricing, REMIND uses different supply curve parameterizations in baseline and climate policy scenarios. Direct and indirect GHG emissions (CO<sub>2</sub> and N<sub>2</sub>O) induced by bioenergy production are accounted for using specific emission factors. | ||
Alternatively, the coupled REMIND-MAgPIE system allows for a detailed analysis of the impacts of bioenergy use for climate change mitigation and land use. | Alternatively, the coupled REMIND-MAgPIE system allows for a detailed analysis of the impacts of bioenergy use for climate change mitigation and land use. | ||
Revision as of 19:04, 19 October 2016
| Corresponding documentation | |
|---|---|
| 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 | |
Bioenergy
REMIND models three types of bioenergy feedstocks:
- First-generation biomass produced from sugar, starch, and oilseeds (typically small in quantity, based on an exogenous scenario);
- Ligno-cellulosic residues from agriculture and forest; and
- Second-generation purpose-grown biomass from specialized ligno-cellulosic grassy and woody bioenergy crops, such as miscanthus, poplar, and eucalyptus.
To represent supply of purpose-grown bioenergy from the land-use sector, REMIND draws on an emulation of the land-use model MAgPIE (Model of Agricultural Production and its Impact on the Environment) (Lotze-Campen et al. 2008; Popp et al. 2010; Lotze-Campen et al. 2010). The emulator describes supply costs and total agricultural emissions as a function of bioenergy demand, as described in detail in Klein et al. (2014). The supply curves capture the time, scale and region dependent change of bioenergy production costs, as well as path dependencies resulting from past land conversions and induced technological changes in the land-use sector, as represented in MAgPIE. Ligno-cellulosic agricultural and forest residues bases on low-cost bioenergy supply options. Their potential is assumed to increase from 20 EJ/yr in 2005 to 70 EJ/yr in 2100 (Chum et al. 2011), based on Haberl et al. (2010).
In REMIND, we assume that the use of traditional biomass (supplied by residues) is phased out, as modern and less harmful fuels are increasingly used with rising incomes rise (Sims et al. 2010). We also assume that first generation modern biofuels are phased-out, reflecting their high costs and to account for concerns about land-use impacts, co-emissions, and competition with food production from first-generation biofuels (Fargione et al. 2008; Searchinger et al. 2008). As a concequence, the main sources of bioenergy in REMIND sceanrios are second-generation purpose-grown biomass and from ligno-cellulosic agricultural and forestry residues.
REMIND represents a number of energy conversion technologies using bioenergy as feedstock. If REMIND is run stand-alone, bioenergy resource potentials are represented as time-dependent and region-specific supply cost-curves derived from MAgPIE (Klein et al. 2014). To account for the sensitivity of resource potentials to carbon pricing, REMIND uses different supply curve parameterizations in baseline and climate policy scenarios. Direct and indirect GHG emissions (CO2 and N2O) induced by bioenergy production are accounted for using specific emission factors.
Alternatively, the coupled REMIND-MAgPIE system allows for a detailed analysis of the impacts of bioenergy use for climate change mitigation and land use.