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Energy Resources

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Energy Resources in the FTT family of models

Technology diffusion in the FTT family of models of substitution in order to remain within feasible limits of the natural system. This is done by using a global database of energy resources. Its conceptual framework is given here using the image above. This was constructed by the ESM group at 4CMR [1] based on an extensive literature review and some original calculations. 

Energy resources are always ranked in order of quality by developers before proceeding to their exploitation. This is done through an evaluation of the cost of exploitation, an attempt to determine whether particular resources are profitable to use in comparison to others. The best resources are chosen first, if at all by developers. Examples of this include bore cost evaluations for oil wells, the productivity of particular windy sites for wind turbines, or heat resources in volcanic areas for geothermal systems. 
 
The FTT family of models cannot possibly include the details of all resources in their individual occurrences, but the choice of lowest cost resources by investors simplifies the problem significantly. If one ranks all know occurrences of a particular resources (windy sites, river basins, sunny areas etc), one may define a distribution of the amount of energy resource available within cost ranges (a). Small numbers of high productivity sites are generally available (at the low cost end), while large amounts of low quality resources exist (at the high cost end), generating low amounts of energy. The productive range lies somewhere in the middle. 
 
In order to determine the amount of resources available at or below a certain cost value, one must sum all resources up to that cost (b). This corresponds to the economic potential. The total amount of resources can be obtained if one is willing to pay a very high cost, and this corresponds to the technical potential
 
In the FTT modelling framework, it is simpler to use the inverse function to the economic potential, called a cost-supply curve (c). This expresses the cost of an additional amount of resource given that a certain quantity has already been consumed. The cost becomes very high for high consumption rates. 
 
Resource assessments are however very uncertain. It is not possible to really know the total amounts of resources available, only estimates can be obtained. Existing estimates vary significantly in the literature. Therefore, it is more appropriate to express cost-supply curves in terms of ranges, or probability distributions of how much resources are thought to be available to the best of current knowledge (d). We present this as a range delimited by three curves, two red curves for the upper and lower limits, and a blue curve for the statistical mode, such that there is a 96% chance that the real cost-supply curve (if it was possible to know it) lies within that range.

 

[1] J.-F. Mercure and P. Salas, An assessment of global energy resource economic potentials, Energy, 46, 322-336 (2012), Free text available on ArXiV arXiv:1205.4693v2

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A key area of research at 4CMR over the past 5 years has been the development of the Future Technology Transformation model, used in exploring how policies influence global technology and carbon. This includes an on-line visualisation tool so you can view our results.

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4CMR works closely with the Cambridge Centre for Environment, Energy and Natural Resource Governance, with overlapping interests, skills and projects. C-EENRG is also located in the Department of Land Economy, with a core mission to "conduct integrative research on the governance of environmental transitions, understood as social and technological processes driven by environmental constraints that lead to fundamental changes in social organisation."

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