POLES
Source: Commission modelling inventory and knowledge management system (MIDAS)
Date of Report Generation: Thu Mar 06 2025
Dissemination: Public
© European Union, 2025
The Commission's reuse policy is implemented by the Commission Decision of 12 December 2011 on the reuse of Commission documents. Unless otherwise indicated (e.g. in individual copyright notices), content owned by the EU on this website is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. This means that reuse is allowed, provided appropriate credit is given and changes are indicated. You may be required to clear additional rights if a specific content depicts identifiable private individuals or includes third-party works. To use or reproduce content that is not owned by the EU, you may need to seek permission directly from the rightholders. Software or documents covered by industrial property rights, such as patents, trade marks, registered designs, logos and names, are excluded from the Commission's reuse policy and are not licensed to you.
Disclaimer: The Commission accepts no responsibility or liability whatsoever with regard to any and all information made available on or accessible through MIDAS website. The information, including but not limited to models, impact assessments, models’ input and output data, and metadata, modelling exercises and policy contributions, is of a general nature only and is not intended to address the specific circumstances of any particular individual or entity, and may not be regarded as comprehensive, complete, accurate or upto-date. The Commission furthermore does not assume any responsibility for content of any external websites to which links maybe provided on this website. Any and all information provided may not be regarded as professional or legal advice. Information available through the website may not be referenced as officially adopted text of European Union regulatory or policy documents or sources. Their authentic versions can only be accessed through the Official Journal of the European Union (the printed edition or, since 1 July 2013, the electronic edition on the EUR-Lex website).
Overview
Acronym
POLES
Full title
Prospective Outlook for the Long term Energy System
Main purpose
POLES is a world energy demand and supply and greenhouse gas emissions model used for international energy and climate policy assessment.
Summary
The POLES model is a global sectoral simulation model for the development of energy and greenhouse gases scenarios until 2050 (2100 for research projects). It has been developed by the JRC since 1996, and JRC runs the POLES-JRC version, which also includes a module on emissions of air pollutants.
The dynamics of the energy system 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, non-metallic minerals and chemistry, as well as detail of energy uses in buildings and modal transportation sectors. The model also provides a complete coverage of greenhouse gas emissions: the detailed energy system gives the evolution of CO2 from fossil fuels combustion; emissions from industry are derived from the description of the economy structure while agriculture and land use emissions come from a reduced form of the specialist GLOBIOM model. All GHG emissions can be affected by climate mitigation policy.
The model supports policy anticipation and formulation by developing consistent global energy scenarios that feed in to policy developments in the field of energy and climate change. The scenarios provide the input for climate negotiations under the UNFCCC and a consistent global energy outlook as boundary conditions for more detailed analyses of the EU energy markets and related policy areas.
Model categories
ClimateEnergy
Model keywords
Climate policyEnergy modelenergy policyscenario analysis
Model homepage
Ownership and Licence
Ownership
Co-ownership (EU & third parties)
Ownership details
Licence type
Non-Free Software licence
The license has one or more of the following restrictions: it prohibits creation of derivative works; it prohibits commercial use; it obliges to share the licensed or derivative works on the same conditions.
Details
Structure and approach
POLES is a global recursive dynamic simulation model of the energy system allowing simulating a wide range of energy and climate policies, being they on the demand side or in the supply sector. It displays a high regional resolution and sectoral representation, and provides endogenous simulation of all steps of the energy system by energy vector and sector: final energy demand, transformation (including power generation), trade, primary supply, international and final user prices, as well as the development of energy-consuming equipment. GHG emissions from fossil fuel combustion, industry, waste, agriculture and land use are also covered. Anthropogenic air pollution can also be covered.
Input and parametrization
Main inputs are:
- Projection / framing conditions: population, GDP growth, economic structure, energy resources
- Historical: socio-economic activity variables (mobility per transport mode, freight volumes, vehicles stock, buildings stock), energy balance (production, demand, transformation, power capacities, prices), technology costs, sectoral GHG emissions.
- Parameters: demand function elasticities, energy efficiency technological trends, technology learning rate
Key input assumptions include socio-economics (population and growth of GDP) and energy resources. Population is an exogenous driver, standard source used is the UN World Population. GDP is also exogenous and is derived from various international sources. Latest work used GDP assumptions from: latest IMF forecasts (for the short run), OECD, or CEPII forecasts (for the longer run). Consistency with population is checked. Energy resources come from various international sources, including BGR and USGS.
The model also uses historical databases on energy production, energy demand, energy prices, energy trade, power generation capacities, GHG emissions and other key activity data (sectoral value added, mobility per mode, freight volumes, vehicles stock, buildings stock). Assumptions on technology costs are also included, either as full prospective data series or as to inform endogenously recreated learning curves. Additional parameters consist in econometric elasticities and policy-dependent energy efficiency improvement trends.
Finally, key inputs are bioenergy cost curves and land-related GHG emissions cost curves from the GLOBIOM model.
Main output
- Projected socio-economic activity variables: sectoral value added, tons of steel consumed and produced, mobility per transport mode, freight volumes, vehicles stock, buildings stock
- Projected energy balance per country / region: energy production, energy demand, energy trade (in energy terms), energy transformation, power capacities, energy prices
- Investment needs, technology costs, energy trade (in economic value)
- Projected sectoral GHG emissions for energy, industry, agriculture and LULUCF
Spatial & Temporal extent
The output has the following spatial-temporal resolution and extent:
| Parameter | Description |
|---|---|
| Spatial extent / country coverage | EU Member states 27ALADI countriesAndean Community countriesArab Common Market countriesCACM countriesASEAN countriesEFTA countriesOECD countriesCAIS countriesOPEC countriesLAES countriesCAEMC countriesWAEMU countriesWestern BalkansBenelux countriesACP countriesComecon countriesCaricom countriesEcowas countriesGCC countriesMercosur countriesMediterranean third countriesCentral and Eastern European CountriesAAMS countriesAPEC countriesCEFTA countriesEAC countriescountries of the Pacific CommunitySAARC countriesCAEU countriesBRICS countriesALL countries of the WORLD |
| 66 geographical units: 54 countries and 12 regions made of country aggregates covering the World. Countries include all OECD countries and large non-OECD countries. All G20 countries and EU27 Member States are explicitly represented. For the energy supply side, a more detailed geographical split is followed, with 88 oil and gas producers, and 81 coal producers. | |
| Spatial resolution | World-regions (supranational)National |
| Temporal extent | Long-term (more than 15 years) |
| Time horizon 2050 (optional 2100) | |
| Temporal resolution | Years |
| Yearly for projections; hourly detail for representative days in the modelling of power demand/supply |
Quality & Transparency
Quality
Model uncertainties
Models are by definition affected by uncertainties (in input data, input parameters, scenario definitions, etc.). Have the model uncertainties been quantified? Are uncertainties accounted for in your simulations?
- response
- no
- details
- Different model runs can be done with different settings to represent uncertainty in model parameters.
- url
Sensitivity analysis
Sensitivity analysis helps identifying the uncertain inputs mostly responsible for the uncertainty in the model responses. Has the model undergone sensitivity analysis?
- response
- yes
- details
- In multiple occasions, batch runs have been done to test the model's reactiveness to different values of a single input parameter (carbon price, technology costs…).
- url
Have model results been published in peer-reviewed articles?
- response
- yes
- details
- The model has participated in inter-model comparison exercises for many years, in which peers compare models' results and methodologies, and has participated in many peer-reviewed papers.
- url
Has the model formally undergone scientific review by a panel of international experts?
Please note that this does not refer to the cases when model results were validated by stakeholders.
- response
- no
- details
- url
Model validation
Has model validation been done? Have model predictions been confronted with observed data (ex-post)?
- response
- not applicable
- details
- Historic period (from 1990 to current year -1 or -2) is used to calibrate parameters that allow the model to endogenously reproduce observed patterns.
- url
Transparency
To what extent do input data come from publicly available sources?
This may include sources accessible upon subscription and/or payment
- response
- Based on both publicly available and restricted-access sources
Is the full model database as such available to external users?
Whether or not it implies a specific procedure or a fee
- response
- no
- details
- A large part of input data is not public. The full list of data sources is available in the POLES-JRC manual. Additional data can be provided on demand.
- url
Have model results been presented in publicly available reports?
Note this excludes IA reports.
- response
- yes
- details
- documents
For details please refer to the 'peer review for model validation' documents in the bibliographic references
Have output datasets been made publicly available?
Note this could also imply a specific procedure or a fee.
- response
- yes
- details
- Examples of output data made available are energy and GHG emissions balances provided with the GECO report(s), as well as a web interface to navigate results and access data on the GECO web site
- url
Is there any user friendly interface presenting model results that is accessible to the public?
For instance: Dashboard, interactive interfaces...
- response
- no
- details
- url
Has the model been documented in a publicly available dedicated report or a manual?
Note this excludes IA reports.
- response
- yes
- details
Is there a dedicated public website where information about the model is provided?
- response
- yes
Is the model code open-source?
- response
- no
- details
Can the code be accessed upon request?
- response
- no
- details
The model’s policy relevance and intended role in the policy cycle
The model is designed to contribute to the following policy areas
- Agriculture and rural development
- Climate action
- Energy
- Environment
- Transport
The model is designed to contribute to the following phases of the policy cycle
- Anticipation – such as foresight and horizon scanning
- Formulation – such as ex-ante Impact Assessments
- Other
The model’s potential
POLES is designed to contribute primarily to the following policy areas: Climate Action, Energy. It could also be used in the following policy areas: Agricultural, Environment, Trade, Transport.
POLES can be used to support policy anticipation and formulation by developing consistent global energy scenarios that feed in to policy developments in the field of energy and climate change. The model has been and is still very much used to assess the impact of European and international energy and climate policies on energy markets and GHG emissions, by DG CLIMA in the context of international climate policy negotiations and by DG ENER in the context of the EU Energy Union.
POLES has also been applied for the analyses of various Impact Assessments in the field of climate change and energy, among them: the Proposal for a revised energy efficiency Directive (COM(2016)0761 final) and The Paris Protocol – A blueprint for tackling global climate change beyond 2020 (COM(2015) 81 final/2).
The model is being extended towards co-benefits of energy and climate policy in terms of land use and water use.
Previous use of the model in ex-ante impact assessments of the European Commission
Use of the model in ex-ante impact assessments since July 2017.
2024SWD/2024/63 final
Impact Assessment Report Part 1 Accompanying the document Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions Securing our future Europe's 2040 climate target and path to climate neutrality by 2050 building a sustainable, just and prosperous society
- Lead by
- CLIMA
- Run by
- EnerFuture: Global Energy Forecasts
- Contribution role
- baseline and assessment of policy options
- Contribution details
The POLES model is used to provide the global climate and energy policy context. The POLES model is the main tool used for the JRC “Global Energy and Climate Outlook” GECO report series, which provides a detailed analysis of the evolution of global GHG emissions under national climate and energy pledges and of global pathways compatible with the Paris Agreement temperature objectives. POLES has also been used to indicate high-level cost-effective decarbonisation pathways for the energy and industry CO2 sectors.