Bioenergy - POLES

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Model Documentation - POLES

Corresponding documentation
Model information
Model link
Institution JRC - Joint Research Centre - European Commission (EC-JRC), Belgium, http://ec.europa.eu/jrc/en/poles.
Solution concept Partial equilibrium (price elastic demand)
Solution method SimulationRecursive simulation
Anticipation Myopic

Primary biomass resources for energy uses are classified in 3 categories for all countries/regions:

  • energy crops (in agricultural area, grassland)
  • short rotation crops (cellulosic)
  • forest residues (cellulosic)

Energy crops are dedicated to 1st generation biofuels, the 2 other categories are used in all other energy uses (a further split of biomass feedstocks has been implemented for Europe using information from the model GREEN-X). POLES uses by default a simplified modeling of land use to estimate the potential of these resources: land available, yields (evolve over time, based on historical evolution), share of harvest/land that can be allocated to energy uses.

Figure 1: Biomass resource use in POLES

POLES also uses in a standard way exogenous estimates of potentials: for instance a soft linkage with the model GLOBIOM/G4M has been implemented that goves potential estimates and cost curves for all World regions (with the model GREEN-X at EU level). Biomass supply cost curves are attached to the various biomass types and come from GREEN-X, GLOBIOM and other sources.

The conversion into liquid biofuels distinguishes first generation (agricultural energy crops) and second generation (cellulosic).

The model has been used in several studies to examine the future use of biomass as an energy source1, bio-energy trade23 and the role of biomass in emissions mitigation45.

Information sources include: FAO6.

References

  1. ^  |  Sarah Mubareka, Ragnar Jonsson, Francesca Rinaldi, Giulia Fiorese, Jesús San-Miguel-Ayanz, Ola Sallnäs, Claudia Baranzelli, Roberto Pilli, Carlo Lavalle, Alban Kitous (2014). An Integrated Modelling Framework for the Forest-based Bioeconomy.Cold Spring Harbor Laboratory Press. http://dx.doi.org/10.1101/011932
  2. ^  |  Julian Matzenberger, Lukas Kranzl, Eric Tromborg, Martin Junginger, Vassilis Daioglou, Chun Sheng Goh, Kimon Keramidas (2015). Future perspectives of international bioenergy trade. Renewable and Sustainable Energy Reviews, 43 (), 926-941. http://dx.doi.org/10.1016/j.rser.2014.10.106
  3. ^  |  Lukas Kranzl, Vassilis Daioglou, Andre Faaij, Martin Junginger, Kimon Keramidas, Julian Matzenberger, Erik Tromborg (2013). Medium and Long-Term Perspectives of International Bioenergy Trade. In Lecture Notes in Energy Vol.17: International Bioenergy Trade(pp. 173-189). Springer Nature. http://dx.doi.org/10.1007/978-94-007-6982-3_8
  4. ^  |  Gunnar Luderer, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, Kenichi Wada (2013). The role of renewable energy in climate stabilization: results from the EMF27 scenarios. Climatic Change, 123 (), 427-441. http://dx.doi.org/10.1007/s10584-013-0924-z
  5. ^  |  Detlef P. van Vuuren, Elie Bellevrat, Alban Kitous, Morna Isaac (2010). Bio-Energy Use and Low Stabilization Scenarios. The Energy Journal, 31 ()http://dx.doi.org/10.5547/issn0195-6574-ej-vol31-nosi-8
  6. ^  |  Emissions Land Use database FAOSTAT. Food and Agriculture Organisation of the United Nations. 2015. [1]