scenario_simulation
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| scenario_simulation [2023/09/08 11:53] – [Land use, land use change and forestry (LULUCF)] massfeller | scenario_simulation [2023/09/08 12:07] (current) – [Land use, land use change and forestry (LULUCF)] massfeller | ||
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| ====Land use, land use change and forestry (LULUCF) ==== | ====Land use, land use change and forestry (LULUCF) ==== | ||
| - | ===1. LULUCF in the basic model === | + | ===LULUCF in the basic model === |
| Before SUPREMA LULUCF and area-based carbon accounting were not depicted in the global market model. Land demand was conceptually derived from maximising farmers profit. Land supply was represented with a function that links supply to agricultural land rents with an elasticity. Non-agricultural land use that complements farm land to give the total region area was disaggregated into forestry, built up areas (urban or “artificial” land) and a remaining “other land” category. There was neither a mapping of land use categories in the market model to the UNFCCC categories, nor a modelling of the transition matrix accompanied by a very limited product-based carbon accounting which was not in line with IPCC. | Before SUPREMA LULUCF and area-based carbon accounting were not depicted in the global market model. Land demand was conceptually derived from maximising farmers profit. Land supply was represented with a function that links supply to agricultural land rents with an elasticity. Non-agricultural land use that complements farm land to give the total region area was disaggregated into forestry, built up areas (urban or “artificial” land) and a remaining “other land” category. There was neither a mapping of land use categories in the market model to the UNFCCC categories, nor a modelling of the transition matrix accompanied by a very limited product-based carbon accounting which was not in line with IPCC. | ||
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| In spite of full consistency, | In spite of full consistency, | ||
| - | == 1.1.Land transitions via Gamma density and Marcov chain == | + | == Land transitions via Gamma density and Marcov chain == |
| The area-based carbon modelling and accounting requires the land transition matrix describing how an initial allocation of land uses (either from the base year or from an intermediate simulation year) is transformed into the currently simulated one. The transition matrix may be expressed in terms of absolute areas L< | The area-based carbon modelling and accounting requires the land transition matrix describing how an initial allocation of land uses (either from the base year or from an intermediate simulation year) is transformed into the currently simulated one. The transition matrix may be expressed in terms of absolute areas L< | ||
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| * by considering for the remaining class without land use change (on the diagonal of the land transition matrix) only the annual carbon effects per ha, relevant for the case of gains via forest management. | * by considering for the remaining class without land use change (on the diagonal of the land transition matrix) only the annual carbon effects per ha, relevant for the case of gains via forest management. | ||
| - | === 2. LULUCF and carbon accounting if SUPREMA is active === | + | === LULUCF and carbon accounting if SUPREMA is active === |
| Within the SUPREMA project two major changes were made: | Within the SUPREMA project two major changes were made: | ||
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| Second, the methodological approach was changed including a) statistical estimation of land use changes assuming a gamma density as in the supply model, b) re-specification of the total land transitions as average transitions per year times the projection horizon as in the supply model (replacement of the Markov chain approach) and c) representation of the disaggregated land supply in the market model through multinomial logit form to. These changes in the SUPREMA project allow for a more symmetric land use representation and carbon accounting between the supply models for European NUTS2 regions and in the global market model of CAPRI. | Second, the methodological approach was changed including a) statistical estimation of land use changes assuming a gamma density as in the supply model, b) re-specification of the total land transitions as average transitions per year times the projection horizon as in the supply model (replacement of the Markov chain approach) and c) representation of the disaggregated land supply in the market model through multinomial logit form to. These changes in the SUPREMA project allow for a more symmetric land use representation and carbon accounting between the supply models for European NUTS2 regions and in the global market model of CAPRI. | ||
| - | == 2.1. Multinomial logit function == | + | == Multinomial logit function == |
| Under SUPREMA we have introduced a multinomial logit form for land supply of all major endogenous land types f = g = h = m = {ag, fr, ur, ot}. This approach is conceptually fully in line with land supply in the regional supply models. In this way we have integrated and replaced the above separate treatment of land supply for agricultural and non-agricultural land: | Under SUPREMA we have introduced a multinomial logit form for land supply of all major endogenous land types f = g = h = m = {ag, fr, ur, ot}. This approach is conceptually fully in line with land supply in the regional supply models. In this way we have integrated and replaced the above separate treatment of land supply for agricultural and non-agricultural land: | ||
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| which permits to make use of the same empirical information (on elasticities of agricultural land supply) and assumptions (on the ranking of responsiveness of non-agricultural areas) that have been used so far in the pre-SUPREMA version. For this purpose, a calibration problem has been set up that minimises weighted squared differences to the starting values by modifying parameters δ< | which permits to make use of the same empirical information (on elasticities of agricultural land supply) and assumptions (on the ranking of responsiveness of non-agricultural areas) that have been used so far in the pre-SUPREMA version. For this purpose, a calibration problem has been set up that minimises weighted squared differences to the starting values by modifying parameters δ< | ||
| - | == 2.2. Spatial extension == | + | == Spatial extension == |
| Under SUPREMA the land use categories of the market model are mapped to the UNFCCC categories. The mapping of market model land types LT< | Under SUPREMA the land use categories of the market model are mapped to the UNFCCC categories. The mapping of market model land types LT< | ||
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| These shares are trivially zero or one in case that certain land types like “temporary non-fodder crops” (tc) and permanent crops (pc) are exclusively mapped to one UNFCCC category (cropland). The remainder to total cropland derives from temporary fodder and fallow land which is a fraction of total fodder area with the remainder being (productive) permanent grassland. The allocation of “other land” (ot) to grassland (ϕ< | These shares are trivially zero or one in case that certain land types like “temporary non-fodder crops” (tc) and permanent crops (pc) are exclusively mapped to one UNFCCC category (cropland). The remainder to total cropland derives from temporary fodder and fallow land which is a fraction of total fodder area with the remainder being (productive) permanent grassland. The allocation of “other land” (ot) to grassland (ϕ< | ||
| - | == 2.3. Land transitions as average transitions per year times the projection horizon | + | == Land transitions as average transitions per year times the projection horizon |
| The new accounting in the CAPRI global market model may be explained as follows, starting from a calculation of the total GHG effects G over horizon h = t-s from total land transitions L< | The new accounting in the CAPRI global market model may be explained as follows, starting from a calculation of the total GHG effects G over horizon h = t-s from total land transitions L< | ||
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| While adding up of shares (or probabilities) of LUC from class I to k over all receiving classes k continues to hold as stated above. It should be highlighted that the land use accounting implemented under SUPREMA avoids the need to explicitly trace the annual transitions in the form of a Markov chain and thereby economised on equations and variables. In this form LUC by CAPRI region and the associated accounting of carbon effects turned out computationally feasible even though the number of equations in the global market model increased from about 78000 to about 83000. Apart from feasibility the format above also permitted to retain the typical CAPRI accounting identity that some total “quantity” (“GROF”) should be computable as the effects “per activity” times activity levels. It was therefore also adopted in the CAPRI supply models. | While adding up of shares (or probabilities) of LUC from class I to k over all receiving classes k continues to hold as stated above. It should be highlighted that the land use accounting implemented under SUPREMA avoids the need to explicitly trace the annual transitions in the form of a Markov chain and thereby economised on equations and variables. In this form LUC by CAPRI region and the associated accounting of carbon effects turned out computationally feasible even though the number of equations in the global market model increased from about 78000 to about 83000. Apart from feasibility the format above also permitted to retain the typical CAPRI accounting identity that some total “quantity” (“GROF”) should be computable as the effects “per activity” times activity levels. It was therefore also adopted in the CAPRI supply models. | ||
| - | === 3.Technical aspects === | + | === Technical aspects === |
| - | Concerning the improvements made under SUPREMA from a technical perspective, | + | Concerning the improvements made under SUPREMA from a technical perspective, |
| - | === 4.Carbon accounting === | + | === Carbon accounting === |
| - | A last recent change concerns the transfer of the existing carbon accounting equations from the supply model to the global market model. These equations run if the global variable %supremaMrk% == on. More information on the equations can be found in the description of the supply model. The equations concerned are, indicated with their present “CAPRI names” in the supply models and plus “Mrk” in the market model: | + | A last recent change concerns the transfer of the existing carbon accounting equations from the supply model to the global market model. These equations run if the global variable %supremaMrk% == on. More information on the equations can be found in the [[module_for_agricultural_supply_at_regional_level|description of the supply model]]. The equations concerned are, indicated with their present “CAPRI names” in the supply models and plus “Mrk” in the market model: |
| Table 3. Equations concerning mitigation modelling in CAPRI | Table 3. Equations concerning mitigation modelling in CAPRI | ||
scenario_simulation.1694174002.txt.gz · Last modified: 2023/09/08 11:53 by massfeller