Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Analysis
  • Published:

Estimation of global final-stage energy-return-on-investment for fossil fuels with comparison to renewable energy sources

Abstract

Under many scenarios, fossil fuels are projected to remain the dominant energy source until at least 2050. However, harder-to-reach fossil fuels require more energy to extract and, hence, are coming at an increasing ‘energy cost’. Associated declines in fossil fuel energy-return-on-investment ratios at first appear of little concern, given that published estimates for oil, coal and gas are typically above 25:1. However, such ratios are measured at the primary energy stage and should instead be estimated at the final stage where energy enters the economy (for example, electricity and petrol). Here, we calculate global time series (1995–2011) energy-return-on-investment ratios for fossil fuels at both primary and final energy stages. We concur with common primary-stage estimates (~30:1), but find very low ratios at the final stage: around 6:1 and declining. This implies that fossil fuel energy-return-on-investment ratios may be much closer to those of renewables than previously expected and that they could decline precipitously in the near future.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Conceptual framework for global fossil fuels EROI estimation.
Fig. 2: Basic MRIO structure with energy extensions vector.
Fig. 3: Global primary-stage fossil fuel EROI ratios from 1995–2011.
Fig. 4: Global final-stage fossil fuel EROI ratios from 1995–2011.
Fig. 5: Components of the EROI calculations.
Fig. 6: Analysis results superimposed on the ‘net energy cliff’.

Similar content being viewed by others

Data availability

The extended energy input datasets were obtained under licence from the IEA. The IEA World Energy Statistics and Balances can be downloaded with institutional or other user licence from https://doi.org/10.1787/enestats-data-en. The EXIOBASE 3.4 database is available at http://exiobase.eu/index.php/data-download/exiobase3mon. The concordance matrices used in the EXIOBASE-based calculations are available in the associated University of Leeds data repository47. The aggregate EROI datasets generated are available from the corresponding author upon reasonable request.

Code availability

The MATLAB code written for generating EiE in the EROI calculations is available at GitHub at the following link: https://github.com/earao/EROI.

References

  1. Gilliland, M. W. Energy analysis and public policy. Science 189, 1051–1056 (1975).

    Article  Google Scholar 

  2. Odum, H. T. Energy, ecology, and economics. Ambio 2, 220–227 (1973).

    Google Scholar 

  3. Federal Nonnuclear Energy Research and Development Act of 1974 (United States Congress, 1974).

  4. Bullard, C. W., Penner, P. S. & Pilati, D. A. Net energy analysis: handbook for combining process and input–output analysis. Resour. Energy 1, 267–313 (1978).

    Article  Google Scholar 

  5. Mulder, K. & Hagens, N. J. Energy return on investment: toward a consistent framework. Ambio 37, 74–79 (2008).

    Article  Google Scholar 

  6. Kunz, H., Hagens, N. J. & Balogh, S. B. The influence of output variability from renewable electricity generation on net energy calculations. Energies 7, 150–172 (2014).

    Article  Google Scholar 

  7. Gagnon, N., Hall, C. A. S. & Brinker, L. A preliminary investigation of energy return on energy investment for global oil and gas production. Energies 2, 490–503 (2009).

    Article  Google Scholar 

  8. Lambert, J. G. et al. EROI of Global Energy Resources: Status, Trends and Social Implications (GOV.UK, 2013).

  9. IPCC Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) (Cambridge Univ. Press, 2014).

  10. King, L. C. & Van Den Bergh, J. C. J. M. Implications of net energy-return-on-investment for a low-carbon energy transition. Nat. Energy 3, 334–340 (2018).

    Article  Google Scholar 

  11. World Energy Outlook 2017 (IEA, 2017); https://www.iea.org/weo2017.

  12. Sers, M. R. & Victor, P. A. The energy-missions trap. Ecol. Econ. 151, 10–21 (2018).

    Article  Google Scholar 

  13. Hall, C. A. S., Balogh, S. & Murphy, D. J. R. What is the minimum EROI that a sustainable society must have? Energies 2, 25–47 (2009).

    Article  Google Scholar 

  14. Fizaine, F. & Court, V. Energy expenditure, economic growth, and the minimum EROI of society. Energy Policy 95, 172–186 (2016).

    Article  Google Scholar 

  15. Hall, C. A. S., Lambert, J. G. & Balogh, S. B. EROI of different fuels and the implications for society. Energy Policy 64, 141–152 (2014).

    Article  Google Scholar 

  16. Brand-Correa, L. I. et al. Developing an input–output based method to estimate a national-level energy return on investment (EROI). Energies 10, 534 (2017).

    Article  Google Scholar 

  17. Cleveland, C. J., Costanza, R., Hall, C. A. S. & Kaufmann, R. Energy use and the US economy: a biophysical perspective. Science 225, 890–897 (1983).

    Article  Google Scholar 

  18. Raugei, M. & Leccisi, E. A comprehensive assessment of the energy performance of the full range of electricity generation technologies deployed in the United Kingdom. Energy Policy 90, 46–59 (2016).

    Article  Google Scholar 

  19. Raugei, M. Net energy analysis must not compare apples and oranges. Nat. Energy 4, 86–88 (2019).

    Article  Google Scholar 

  20. IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  21. Capellán-Pérez, I. et al. Global Model: MEDEAS-World Model and IOA Implementation at Global Geographical Level (MEDEAS, 2017); https://www.medeas.eu/system/files/documentation/files/Deliverable%204.1%20%28D13%29_Global%20Model.pdf

  22. Dale, M., Krumdieck, S. & Bodger, P. Global energy modelling—a biophysical approach (GEMBA) part 1: an overview of biophysical economics. Ecol. Econ. 73, 152–157 (2012).

    Article  Google Scholar 

  23. Fagnart, J. F. & Germain, M. Net energy ratio, EROEI and the macroeconomy. Struct. Change Econ. Dyn. 37, 121–126 (2016).

    Article  Google Scholar 

  24. King, C. W. & Hall, C. A. S. Relating financial and energy return on investment. Sustainability 3, 1810–1832 (2011).

    Article  Google Scholar 

  25. Court, V. & Fizaine, F. Long-term estimates of the energy-return-on-investment (EROI) of coal, oil, and gas global productions. Ecol. Econ. 138, 145–159 (2017).

    Article  Google Scholar 

  26. Guilford, M. C., Hall, C. A. S., Connor, P. O. & Cleveland, C. J. A new long term assessment of energy return on investment (EROI) for U.S. oil and gas discovery and production. Sustainability 3, 1866–1887 (2011).

    Article  Google Scholar 

  27. King, C. W., Maxwell, J. P. & Donovan, A. Comparing world economic and net energy metrics, part 2: total economy expenditure perspective. Energies 8, 12975–12996 (2015).

    Article  Google Scholar 

  28. IEA World Energy Statistics and Balances (IEA, 2017); https://doi.org/10.1787/data-00513-en

  29. Stadler, K. et al. EXIOBASE 3: Developing a time series of detailed environmentally extended multi-regional input–output tables. J. Ind. Ecol. 22, 502–515 (2018).

    Article  Google Scholar 

  30. Brandt, A. R., Dale, M. & Barnhart, C. J. Calculating systems-scale energy efficiency and net energy returns: a bottom-up matrix-based approach. Energy 62, 235–247 (2013).

    Article  Google Scholar 

  31. World Energy Balances: Database Documentation (2018 Edition) (IEA, 2018); http://wds.iea.org/wds/pdf/WORLDBAL_Documentation.pdf

  32. Murphy, D. J., Carbajales-Dale, M. & Moeller, D. Comparing apples to apples: why the net energy analysis community needs to adopt the life-cycle analysis framework. Energies 9, 1–15 (2016).

    Article  Google Scholar 

  33. Palmer, G. An input–output based net-energy assessment of an electricity supply industry. Energy 141, 1504–1516 (2017).

    Article  Google Scholar 

  34. Palmer, G. & Floyd, J. An exploration of divergence in EPBT and EROI for solar photovoltaics. Biophys. Econ. Resour. Qual. 2, 15 (2017).

    Article  Google Scholar 

  35. Barrett, J. et al. Consumption-based GHG emission accounting: a UK case study. Clim. Policy 13, 451–470 (2013).

    Article  Google Scholar 

  36. Owen, A. et al. Energy consumption-based accounts: a comparison of results using different energy extension vectors. Appl. Energy 190, 464–473 (2017).

    Article  Google Scholar 

  37. Bashmakov, I. Three laws of energy transitions. Energy Policy 35, 3583–3594 (2007).

    Article  Google Scholar 

  38. Kilian, L. The economic effects of energy price shocks. J. Econ. Lit. 46, 871–909 (2008).

    Article  Google Scholar 

  39. Aucott, M. & Hall, C. Does a change in price of fuel affect GDP growth? An examination of the U.S. data from 1950–2013. Energies 7, 6558–6570 (2014).

    Article  Google Scholar 

  40. Bauer, N., Baumstark, L. & Leimbach, M. The REMIND-R model: the role of renewables in the low-carbon transformation-first-best vs. second-best worlds. Clim. Change 114, 145–168 (2012).

    Article  Google Scholar 

  41. Bernard, A. & Vielle, M. GEMINI-E3, a general equilibrium model of international–national interactions between economy, energy and the environment. Comput. Manag. Sci. 5, 173–206 (2008).

    Article  MathSciNet  MATH  Google Scholar 

  42. Clarke, L. et al. in Climate Change 2014: Mitigation of Climate Change (eds. Edenhofer, O. et al.) 413–510 (Cambridge Univ. Press, 2014).

  43. Capellán-Pérez, I., Mediavilla, M., de Castro, C., Carpintero, Ó. & Miguel, L. J. Fossil fuel depletion and socio-economic scenarios: an integrated approach. Energy 77, 641–666 (2014).

    Article  Google Scholar 

  44. Bhandari, K. P., Collier, J. M., Ellingson, R. J. & Apul, D. S. Energy payback time (EPBT) and energy return on energy invested (EROI) of perovskite tandem photovoltaic solar cells. Renew. Sustain. Energy Rev. 47, 133–141 (2015).

    Article  Google Scholar 

  45. Dale, M. & Benson, S. M. Energy balance of the global photovoltaic (PV) industry-is the PV industry a net electricity producer? Environ. Sci. Technol. 47, 3482–3489 (2013).

    Article  Google Scholar 

  46. Cullen, J. M. & Allwood, J. M. Theoretical efficiency limits for energy conversion devices. Energy 35, 2059–2069 (2010).

    Article  Google Scholar 

  47. Brockway, P. E., Owen, A., Brand-Correa, L. I. & Hardt, L. University of Leeds Data Repository Data from: Estimation of global final-stage energy-return-on-investment for fossil fuels with comparison to renewable energy sources. (University of Leeds Data Repository, 2019); https://doi.org/10.5518/598

  48. Miller, R. E. & Blair, P. D. Input–Output Analysis: Foundations and Extensions (Cambridge Univ. Press, 2009).

  49. Brandt, A. R. & Dale, M. 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 4, 1211–1245 (2011).

    Article  Google Scholar 

  50. Moeller, D. & Murphy, D. Net energy analysis of gas production from the Marcellus Shale. Biophys. Econ. Resour. Qual. 1, 5 (2016).

    Article  Google Scholar 

  51. Lenzen, M. & Treloar, G. J. Endogenising capital: a comparison of two methods. J. Appl. Input-Output Anal. 10, 1–11 (2004).

    Google Scholar 

  52. Södersten, C. J. H., Wood, R. & Hertwich, E. G. Endogenizing capital in MRIO models: the implications for consumption-based accounting. Environ. Sci. Technol. 52, 13250–13259 (2018).

    Article  Google Scholar 

  53. Chen, G. Q. & Wu, X. F. Energy overview for globalized world economy: source, supply chain and sink. Renew. Sustain. Energy Rev. 69, 735–749 (2017).

    Article  Google Scholar 

  54. Brandt, A. R. Oil depletion and the energy efficiency of oil production: the case of California. Sustainability 3, 1833–1854 (2011).

    Article  Google Scholar 

  55. Raugei, M., Fullana-i-Palmer, P. & Fthenakis, V. The energy return on energy investment (EROI) of photovoltaics: methodology and comparisons with fossil fuel life cycles. Energy Policy 45, 576–582 (2012).

    Article  Google Scholar 

  56. Leccisi, E., Raugei, M. & Fthenakis, V. The energy and environmental performance of ground-mounted photovoltaic systems—a timely update. Energies 9, 622 (2016).

    Article  Google Scholar 

  57. Kubiszewski, I., Cleveland, C. J. & Endres, P. K. Meta-analysis of net energy return for wind power systems. Renew. Energy 35, 218–225 (2010).

    Article  Google Scholar 

  58. Mearns, E. The global energy crisis and its role in the pending collapse of the global economy. The Oil Drum Europe http://theoildrum.com/node/4712 (2008).

Download references

Acknowledgements

This research was primarily funded by the UK Energy Research Centre, supported by the UK Research Councils under EPSRC award EP/L024756/1. We also acknowledge support for P.E.B. under EPSRC Fellowship award EP/R024251/1. The contributions of A.O. were also supported by the Centre for Industrial Energy, Materials and Products (EPSRC award EP/N022645/1), and under EPSRC Fellowship award EP/R005052/1. L.I.B.-C. was supported by the Living Well Within Limits project funded by the Leverhulme Trust.

Author information

Authors and Affiliations

Authors

Contributions

P.E.B., L.I.B.-C., A.O. and L.H. jointly designed the study and wrote the paper. P.E.B. and L.H. sourced IEA data and undertook calculations to calculate the total energy produced and direct energy consumed. L.I.B.-C. and A.O. performed the MRIO calculations to obtain indirect energy estimates.

Corresponding author

Correspondence to Paul E. Brockway.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Brockway, P.E., Owen, A., Brand-Correa, L.I. et al. Estimation of global final-stage energy-return-on-investment for fossil fuels with comparison to renewable energy sources. Nat Energy 4, 612–621 (2019). https://doi.org/10.1038/s41560-019-0425-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41560-019-0425-z

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing