- scenarios and projections for energy demand, supply and prices (not forecasts), such as the World Energy Technology Outlook;
- analysis of CO2 emission reduction pathways in an international perspective, such as the assessment of Global Climate Policy Scenarios for 2030 and beyond;
- impacts of technological change.
The dynamics of the model are based on a recursive (year by year) simulation process of energy demand and supply with lagged adjustments to prices and a feedback loop through international energy prices.
The model is developed within the framework of a hierarchical structure of interconnected modules at the international, regional and national level. It contains technologically-detailed modules for energy-intensive sectors, including power generation, production of iron and steel, aluminium and cement, as well as modal transportation sectors.
In each sector, energy consumption is calculated both for substitutable fuels and for electricity. Each demand equation contains an income or activity variable elasticity, a price elasticity, captures technological trends and, when appropriate, saturation effects. Particular attention is paid to the treatment of price effects.
The world is subdivided into 47 regions, for which the model delivers detailed energy balances (see figure above). A single world oil market is assumed (the "one great pool" concept), while three regional markets (America, Europe and Asia) are identified for coal, in order to take into account different cost, market and technical structures. Natural gas production and trade flows are modelled on a bilateral trade basis, thus allowing for the identification of a large number of geographical specificities and the nature of different export routes.
All energy prices are determined endogenously in POLES. Oil prices in the long term depend primarily on the relative scarcity of oil reserves (i.e. the reserves-to-production ratio). In the short run, the oil price is mainly influenced by spare production capacities of large oil producing countries. It must be noted that the endogenous price forming mechanism cannot model the price volatility induced by short term market expectations.
The model is continuously being enhanced both in detail and by regional separation. Recent modifications include the addition of detailed modules for energy-intensive sectors [see, e.g. SzabÃ³ et al., 2006], and the extension to cover non-CO2 greenhouse gases [see Criqui, 2002 and Criqui et al., 2006].
 European Commission (2006): World Energy Technology Outlook -2050(WETO H2). DG Research, EUR 22038. http://ec.europa.eu/research/energy/pdf/weto-h2_en.pdf
 Russ, P., Wiesenthal, T., van Regemorter, D., Ciscar, J.C. (2007): GlobalClimate Policy Scenarios for 2030 and beyond. Analysis of Greenhouse GasEmission Reduction Pathway Scenarios with the POLES and GEM-E3 models. JRCReference Report EUR 23032 EN, 2007
 Uyterlinde, M.A., Martinus, G.H., RÃ¶sler, H.,Kouvaritakis, N., Mantzos, L., Panos, V., Zeka-Paschou, M., Keppo, I., SzabÃ³,L., Russ, P., Suwala, W., Kypreos, S., Jokisch, S., Blesl, M., Ellersdorfer,I., Zürn, M. , Fahl, U., Pratlong, F., Le Mouel, P., Sano, F., Akimoto, K.,Homma, T., Tomoda, T.( 2007): Technology options and effective policies toreduce GHG emissions and improve security of supply. Final report CASCADE MINTSPart 2
 SzabÃ³, L., Hidalgo, I., Ciscar,J.C., Soria, A. (2006): CO2 emissiontrading within the European Union and Annex B countries: the cement industrycase Energy Policy 34 (2006) 72-87.
 Criqui, P. (ed) (2002):Greenhouse gas Emission Control Strategies (GECS), Research Report for theEuropean Commission DG RTD, 2002.
 Criqui, P., Russ, P.,Deybe, D. (2006): Impacts of Multi-gas Strategies for Greenhouse Gas EmissionAbatement: Insights from a Partial Equilibrium Model, in: De la Chesnaye, F.,Weyant, J (eds).(2007), p.251.