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Name and version

IMAGE framework 3.0

Institution and users

Utrecht University (UU), Netherlands,
PBL Netherlands Environmental Assessment Agency (PBL), Netherlands,


IMAGE documentation consists of a referencecard and detailed model documentation

Model scope and methods

Model documentation: Model scope and methods - IMAGE


IMAGE is an ecological-environmental model framework that simulates the environmental consequences of human activities worldwide. The objective of the IMAGE model is to explore the long- term dynamics and impacts of global changes that result. More specifically, the model aims

  1. to analyse interactions between human development and the natural environment to gain better insight into the processes of global environmental change;
  2. to identify response strategies to global environmental change based on assessment of options and
  3. to indicate key inter-linkages and associated levels of uncertainty in processes of global environmental change.


The IMAGE framework can best be described as a geographically explicit assessment, integrated assessment simulation model, focusing a detailed representation of relevant processes with respect to human use of energy, land and water in relation to relevant environmental processes.

Solution method

Recursive dynamic solution method


Simulation modelling framework, without foresight. However, a simplified version of the energy/climate part of the model (called FAIR) can be run prior to running the framework to obtain data for climate policy simulations.

Temporal dimension

Base year:1970, time steps:1-5 year time step, horizon: 2100

Spatial dimension

Number of regions:26

  1. Canada
  2. USA
  3. Mexico
  4. Rest of Central America
  5. Brazil
  6. Rest of South America
  7. Northern Africa
  8. Western Africa
  9. Eastern Africa
  10. South Africa
  11. Western Europe
  12. Central Europe
  13. Turkey
  14. Ukraine +
  15. Asian-Stan
  16. Russia +
  17. Middle East
  18. India +
  19. Korea
  20. China +
  21. Southeastern Asia
  22. Indonesia +
  23. Japan
  24. Oceania
  25. Rest of South Asia
  26. Rest of Southern Africa

Policy implementation

Key areas where policy responses can be introduced in the model are:

  • Climate policy
  • Energy policies (air pollution, access and energy security)
  • Land use policies (food)
  • Specific policies to project biodiversity
  • Measures to reduce the imbalance of the nitrogen cycle

Socio economic drivers

Model documentation: Socio-economic drivers - IMAGE

Exogenous drivers

  • Exogenous GDP
  • Total Factor Productivity
  • Labour Productivity
  • Capital Technical progress
  • Energy Technical progress
  • Materials Technical progress
  • GDP per capita

Endogenous drivers

  • Energy demand
  • Renewable price
  • Fossil fuel prices
  • Carbon prices
  • Technology progress
  • Energy intensity
  • Preferences
  • Learning by doing
  • Agricultural demand
  • Population
  • Value added


  • GDP per capita
  • Income distribution in a region
  • Urbanisation rate
  • Education level
  • Labour participation rate

Note: GDP per capita and income distrubition are exogenous

Macro economy

Model documentation: Macro-economy - IMAGE

Economic sectors

  • Agriculture
  • Industry
  • Energy
  • Transport
  • Services

Note: No explicit economy representation in monetary units. Explicit economy representation in terms of energy is modelled (for the agriculture, industry, energy, transport and built environment sectors)

Cost measures

  • GDP loss
  • Welfare loss
  • Consumption loss
  • Area under MAC
  • Energy system costs


  • Coal
  • Oil
  • Gas
  • Uranium
  • Electricity
  • Bioenergy crops
  • Food crops
  • Capital
  • Emissions permits
  • Non-energy goods
  • Bioenergy products
  • Livestock products


Model documentation: Energy - IMAGE


In the energy model, substitution among technologies is described in the model using the multinomial logit formulation. The multinomial logit model implies that the market share of a certain technology or fuel type depends on costs relative to competing technologies. The option with the lowest costs gets the largest market share, but in most cases not the full market. We interpret the latter as a representation of heterogeneity in the form of specific market niches for every technology or fuel.

Resource use

  • Coal
  • Oil
  • Gas
  • Uranium
  • Biomass

Note: Distinction between traditional and modern biomass

Electricity technologies

  • Coal
  • Gas
  • Oil
  • Nuclear
  • Biomass
  • Wind
  • Solar PV
  • CCS
  • CSP

Note: wind: offshore;
coal: conventional, IGCC, IGCC + CCS, IGCC + CHP, IGCC + CHP + CCS;
oil: conventional, OGCC, OGCC + CCS, OGCC + CHP, OGCC + CHP + CCS);
natural gas: conventional, CC, CC + CCS, CC + CHP, CC + CHP + CCS;
biomass: conventional, CC, CC + CCS, CC + CHP, CC + CHP + CCS

Conversion technologies

  • CHP
  • Heat pumps
  • Hydrogen
  • Fuel to gas
  • Fuel to liquid

Grid and infrastructure

  • Electricity
  • Gas
  • Heat
  • CO2
  • H2

Energy technology substitution

  • Discrete technology choices
  • Expansion and decline constraints
  • System integration constraints

Energy service sectors

  • Transportation
  • Industry
  • Residential and commercial


Model documentation: Land-use - IMAGE; Non-climate sustainability dimension - IMAGE


  • Forest
  • Cropland
  • Grassland
  • Abandoned land
  • Protected land

Other resources

Model documentation: Non-climate sustainability dimension - IMAGE

Other resources

  • Water
  • Metals
  • Cement

Emissions and climate

Model documentation: Emissions - IMAGE; Climate - IMAGE

Green house gasses

  • CO2
  • CH4
  • N2O
  • HFCs
  • CFCs
  • SF6


  • NOx
  • SOx
  • BC
  • OC
  • Ozone
  • VOC
  • NH3
  • CO

Climate indicators

  • CO2e concentration (ppm)
  • Climate damages $ or equivalent
  • Radiative Forcing (W/m2 )
  • Temperature change (°C)