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System Energy Assessment (SEA), Defining a Standard Measure of EROI for Energy Businesses as Whole Systems

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Author Info

  • Philip F. Henshaw

    ()
    (HDS Systems Design Science, Synapse9.com, New York, NY 10040, USA)

  • Carey King

    ()
    (Center for International Energy and Environmental Policy, University of Texas, Austin, TX 78713, USA)

  • Jay Zarnikau

    ()
    (LBJ School of Public Affairs & College of Natural Sciences, University of Texas, Austin, TX 78713, USA)

Abstract

A more objective method for measuring the energy needs of businesses, System Energy Assessment (SEA), measures the combined impacts of material supply chains and service supply chains, to assess businesses as whole self-managing net-energy systems. The method is demonstrated using a model Wind Farm, and defines a physical measure of their energy productivity for society (EROI-S), a ratio of total energy delivered to total energy expended. Energy use records for technology and proxy measures for clearly understood but not individually recorded energy uses for services are combined for a whole system estimate of consumption required for production. Current methods count only energy needs for technology. Business services outsource their own energy needs to operate, leaving no traceable record. That uncounted business energy demand is often 80% of the total, an amount of “dark energy” hidden from view, discovered by finding the average energy estimated needs for businesses far below the world average energy consumed per dollar of GDP. Presently for lack of information the energy needs of business services are counted to be “0”. Our default assumption is to treat them as “average”. The result is a hard measure of total business demand for energy services, a “Scope 4” energy use or GHG impact assessment. Counting recorded energy uses and discounting unrecorded ones misrepresents labor intensive work as highly energy efficient. The result confirms a similar finding by Hall et al . in 1981 [1]. We use exhaustive search for what a business needs to operate as a whole, tracing internal business relationships rather than energy data, to locate its natural physical boundary as a working unit, and so define a business as a physical rather than statistical subject of scientific study. See also online resource materials and notes [2].

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Bibliographic Info

Article provided by MDPI, Open Access Journal in its journal Sustainability.

Volume (Year): 3 (2011)
Issue (Month): 10 (October)
Pages: 1908-1943

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Handle: RePEc:gam:jsusta:v:3:y:2011:i:10:p:1908-1943:d:14373

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Web page: http://www.mdpi.com/

Related research

Keywords: physical measurement; EROI; natural systems; net energy; energy economics; outsourcing; system boundaries; life cycle assessment;

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References

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  1. Cleveland, Cutler J., 2005. "Net energy from the extraction of oil and gas in the United States," Energy, Elsevier, vol. 30(5), pages 769-782.
  2. C. A. Hidalgo & B. Klinger & A. -L. Barabasi & R. Hausmann, 2007. "The Product Space Conditions the Development of Nations," Papers 0708.2090, arXiv.org.
  3. Cleveland, Cutler J. & Kaufmann, Robert K. & Stern, David I., 2000. "Aggregation and the role of energy in the economy," Ecological Economics, Elsevier, vol. 32(2), pages 301-317, February.
  4. Bullard, Clark W. & Penner, Peter S. & Pilati, David A., 1978. "Net energy analysis : Handbook for combining process and input-output analysis," Resources and Energy, Elsevier, vol. 1(3), pages 267-313, November.
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Citations

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Cited by:
  1. Adam R. Brandt & Michael Dale, 2011. "A General Mathematical Framework for Calculating Systems-Scale Efficiency of Energy Extraction and Conversion: Energy Return on Investment (EROI) and Other Energy Return Ratios," Energies, MDPI, Open Access Journal, vol. 4(8), pages 1211-1245, August.
  2. Arturo Macías & Mariano Matilla-García, 2012. "Net energy analysis in a Ramsey-Hotelling growth model," Banco de Espa�a Working Papers 1217, Banco de Espa�a.
  3. Charles A.S. Hall & Bruce E. Dale & David Pimentel, 2011. "Seeking to Understand the Reasons for Different Energy Return on Investment (EROI) Estimates for Biofuels," Sustainability, MDPI, Open Access Journal, vol. 3(12), pages 2413-2432, December.
  4. Leena Grandell & Charles A.S. Hall & Mikael Höök, 2011. "Energy Return on Investment for Norwegian Oil and Gas from 1991 to 2008," Sustainability, MDPI, Open Access Journal, vol. 3(11), pages 2050-2070, October.
  5. Colin M. Beal & Robert E. Hebner & Michael E. Webber & Rodney S. Ruoff & A. Frank Seibert & Carey W. King, 2012. "Comprehensive Evaluation of Algal Biofuel Production: Experimental and Target Results," Energies, MDPI, Open Access Journal, vol. 5(6), pages 1943-1981, June.

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