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A Dynamic Function for Energy Return on Investment

Author

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  • Michael Dale

    (Advanced Energy and Material Systems (AEMS) Lab, Department of Mechanical Engineering, University of Canterbury, Christchurch 8041, New Zealand)

  • Susan Krumdieck

    (Advanced Energy and Material Systems (AEMS) Lab, Department of Mechanical Engineering, University of Canterbury, Christchurch 8041, New Zealand)

  • Pat Bodger

    (Electrical and Computer Engineering, University of Canterbury, Christchurch 8041, New Zealand)

Abstract

Most estimates of energy-return-on-investment (EROI) are “static”. They determine the amount of energy produced by a particular energy technology at a particular location at a particular time. Some “dynamic” estimates are also made that track the changes in EROI of a particular resource over time. Such approaches are “bottom-up”. This paper presents a conceptual framework for a “top-down” dynamic function for the EROI of an energy resource. This function is constructed from fundamental theoretical considerations of energy technology development and resource depletion. Some empirical evidence is given as corroboration of the shape of the function components.

Suggested Citation

  • Michael Dale & Susan Krumdieck & Pat Bodger, 2011. "A Dynamic Function for Energy Return on Investment," Sustainability, MDPI, vol. 3(10), pages 1-14, October.
  • Handle: RePEc:gam:jsusta:v:3:y:2011:i:10:p:1972-1985:d:14376
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    References listed on IDEAS

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    Cited by:

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    17. Dale, M. & Krumdieck, S. & Bodger, P., 2012. "Global energy modelling — A biophysical approach (GEMBA) Part 2: Methodology," Ecological Economics, Elsevier, vol. 73(C), pages 158-167.
    18. Bo Xu & Lianyong Feng & William X. Wei & Yan Hu & Jianliang Wang, 2014. "A Preliminary Forecast of the Production Status of China’s Daqing Oil field from the Perspective of EROI," Sustainability, MDPI, vol. 6(11), pages 1-21, November.
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