Data - POLES: Difference between revisions
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Synthetic view of POLES data sources: | |||
== Macro-economic drivers == | |||
Population | |||
* UN (2015, medium fertility) | |||
GDP | |||
* World Bank (2015), EC (2015), IMF (2016), OECD (2013, see also Dellink et al. 2014) | |||
Value added | |||
* World Bank (2015); projection endogenous | |||
Mobility, vehicles, households, tons of steel | |||
* Sectoral databases; projections endogenous | |||
== Energy resources == | |||
Oil, gas, coal | |||
* BGR (2014), USGS (2013), WEC (2013), sectoral databases | |||
Uranium | |||
* OECD (2014) | |||
Biomass | |||
* EU: Green-X model1 | |||
* Non-EU: GLOBIOM model | |||
Hydro | |||
* Enerdata (2015) | |||
Wind, solar | |||
* NREL (2013), Pietzcker (2014) | |||
== Energy balances == | |||
Reserves, production | |||
* BP (2015), Enerdata (2015), IEA (2015); projections endogenous | |||
Demand by sector and fuel, transformation (including. power), losses | |||
* Enerdata (2015), IEA (2015); projections endogenous | |||
== Energy prices == | |||
International energy prices, prices to consumer | |||
* EIA (2016), Enerdata (2015), IEA (2015); projections endogenous | |||
== GHG emissions == | |||
Energy CO2 | |||
* Derived from energy balances; endogenous | |||
Other GHG Annex 1 | |||
* UNFCCC (2015); projections endogenous, and derived from data from GLOBIOM | |||
Other GHG Non-Annex 1 (excl. LULUCF) | |||
* EDGAR (EC JRC 2015); projections endogenous, and derived from data from GLOBIOM | |||
LULUCF Non-Annex 1 | |||
* FAO (2015); projections endogenous, and derived from data from GLOBIOM | |||
== Technology costs == | |||
JRC-POLES learning curves based on literature, including but not only: EC JRC (2014), IEA Technology Roadmaps, WEC (2013), TECHPOL database (developed in several European research projects: SAPIENT, SAPIENTIA, CASCADE MINTS - see for instance: [http://cordis.europa.eu/result/rcn/47819_en.html]) | |||
Revision as of 18:13, 20 October 2016
| Corresponding documentation | |
|---|---|
| Previous versions | |
| Model information | |
| Model link | |
| Institution | JRC - Joint Research Centre - European Commission (EC-JRC), Belgium, http://ec.europa.eu/jrc/en/. |
| Solution concept | Partial equilibrium (price elastic demand) |
| Solution method | SimulationRecursive simulation |
| Anticipation | Myopic |
Synthetic view of POLES data sources:
Macro-economic drivers
Population
- UN (2015, medium fertility)
GDP
- World Bank (2015), EC (2015), IMF (2016), OECD (2013, see also Dellink et al. 2014)
Value added
- World Bank (2015); projection endogenous
Mobility, vehicles, households, tons of steel
- Sectoral databases; projections endogenous
Energy resources
Oil, gas, coal
- BGR (2014), USGS (2013), WEC (2013), sectoral databases
Uranium
- OECD (2014)
Biomass
- EU: Green-X model1
- Non-EU: GLOBIOM model
Hydro
- Enerdata (2015)
Wind, solar
- NREL (2013), Pietzcker (2014)
Energy balances
Reserves, production
- BP (2015), Enerdata (2015), IEA (2015); projections endogenous
Demand by sector and fuel, transformation (including. power), losses
- Enerdata (2015), IEA (2015); projections endogenous
Energy prices
International energy prices, prices to consumer
- EIA (2016), Enerdata (2015), IEA (2015); projections endogenous
GHG emissions
Energy CO2
- Derived from energy balances; endogenous
Other GHG Annex 1
- UNFCCC (2015); projections endogenous, and derived from data from GLOBIOM
Other GHG Non-Annex 1 (excl. LULUCF)
- EDGAR (EC JRC 2015); projections endogenous, and derived from data from GLOBIOM
LULUCF Non-Annex 1
- FAO (2015); projections endogenous, and derived from data from GLOBIOM
Technology costs
JRC-POLES learning curves based on literature, including but not only: EC JRC (2014), IEA Technology Roadmaps, WEC (2013), TECHPOL database (developed in several European research projects: SAPIENT, SAPIENTIA, CASCADE MINTS - see for instance: [1])