In my most recent post, Why the Standard Model of Future Energy Supply Doesn’t Work, I made some comments about the calculation of Energy Returned on Energy Invested. Professor Charles Hall sent me the following response to what I said, which he wanted to have published. I have a few follow-up comments, but I will save them for the comments section.
Section of Why the Standard Model of Future Energy Supply Doesn’t Work Upon Which Comments Are Being Made
The Energy Return on Energy Invested (EROEI) Model of Prof. Charles Hall depended on the thinking of the day: it was the energy consumption that was easy to count that mattered. If a person could discover which energy products had the smallest amount of easily counted energy products as inputs, this would provide an estimate of the efficiency of an energy type, in some sense. Perhaps a transition could be made to more efficient types of energy, so that fossil fuels, which seemed to be in short supply, could be conserved.
The catch is that it is total energy consumption, that matters, not easily counted energy consumption. In a networked economy, there is a huge amount of energy consumption that cannot easily be counted: the energy consumption to build and operate schools, roads, health care systems, and governments; the energy consumption required to maintain a system that repays debt with interest; the energy consumption that allows governments to collect significant taxes on exported oil and other goods. The standard EROEI method assumes the energy cost of each of these is zero. Typically, wages of workers are not considered either.
There is also a problem in counting different types of energy inputs and outputs. Our economic system assigns different dollar values to different qualities of energy; the EROEI method basically assigns only ones and zeros. In the EROEI method, certain categories that are hard to count are zeroed out completely. The ones that can be counted are counted as equal, regardless of quality. For example, intermittent electricity is treated as equivalent to high quality, dispatchable electricity.
The EROEI model looked like it would be helpful at the time it was created. Clearly, if one oil well uses considerably more energy inputs than a nearby oil well, it would be a higher-cost well. So, the model seemed to distinguish energy types that were higher cost, because of resource usage, especially for very similar energy types.
Another benefit of the EROEI method was that if the problem were running out of fossil fuels, the model would allow the system to optimize the use of the limited fossil fuels that seemed to be available, based on the energy types with highest EROEIs. This would seem to make best use of the fossil fuel supply available.
Charlie Hall responds:
I have always been, remain and will probably always continue to be a huge fan of Gail Tverberg, her analyses and her blogs. I am also committed to try and make sure science, such as I understand it, remains committed to truth, such as that is possible, which includes an accurate representation of the scientific work of others. In that spirit I wish to correct a short piece (referenced above) that is attempting to represent my own work on Energy Return on Investment (EROI or EROEI) but does not do so in a way that is fully consistent with the published work of myself and my colleagues.
I define EROI as a simple ratio, not a model, but have no particular concern about Gail’s use of the word model other than that it may imply something more complicated than it is. EROI is an observational tool for analysis, not a model with an objective in mind. My perspective is summarized in my 2017 book “Energy Return on Investment: A unifying principle for Biology, Economics, and Sustainability” although my approach is consistent throughout my published work with occasional small additions as our understanding expands, changes in available data occur or new questions arise. For example my methods going as far back as Cleveland et al. 1984 and Hall, Cleveland and Kaufmann (1986) are available for anyone to see and virtually the same as those in Murphy et al. 2011 and Hall 2017. The field is rich and very active today, with an entire well-funded and attended four day meeting at the French Institute of Physics at Les Houches dedicated to EROI last year, a two day session on petroleum (including many papers on EROI) at the American Chemical Society in New Orleans a month ago, and many very interesting publications by, for example, Carey King, Marco Raugui, Adam Brandt, Mohammed Masnadi, Victor Court and Florian Fizaine among many others.
As others increasingly used EROI there became increasingly different approaches used, so, in order to generate a consistent nomenclature and basis for comparison (EROIstandard) while allowing flexibility and creativity in use we published a protocol for performing EROI analysis (Murphy et al. 2011; Carey King has also addressed making the nomenclature and methods more explicit). Sometimes EROI studies are not easily comparable due to limitations in data or philosophy (see point 3). This is not something that escapes EROI researchers and is widely discussed in the literature. Sometimes we have examined the reasons for different EROI’s in the literature (e.g. Hall, Dale and Pimentel). Another issue is that it is common for blogs and reporters to read more into the results of scientific publications on EROI than the authors sought to assess, and such false conclusions can move very quickly on the Internet.
I now address some of Gail Tverberg’s specific points (in bold):
1) “The catch is that it is total energy consumption that matters, not easily counted energy consumption”. To understand this one must begin with the definition of EROI, for example on page 66 of the above book:
As we define again and again we have used the direct (e.g. natural gas to pressurize an oil field) plus indirect (energy to make the capital equipment: see Fig. 6 legend of Cleveland et al.) energies that are used to exploit fuels from Nature. We have consistently defined EROI to mean energy at the wellhead, mine mouth, bussbar or farm gate unless explicitly stated otherwise. We consider the energy used subsequently to deliver or use that energy as efficiency (as in food chain efficiency) of the use system. These data are not easy to gain, requiring many months of research in many libraries and government archives (See Appendix 1 of Guilford et al.) and are becoming more difficult as much of our National data gathering erodes. Such difficulties and their consequences are usually referred to in peer-reviewed EROI research papers by the authors themselves.
2) “The standard EROEI method assumes the energy cost of each of these is zero.” This is most explicitly not true. As appropriate (and as we have become better at the analysis) we have included energy costs of taxes (e.g. Prieto and Hall), Roads (Hall, Balogh and Murphy; Prieto and Hall), labor (e.g. Hall et al 1986; Prieto and Hall) and so on. We have tended to avoid the contentious issue of whether or not to include labor as “input” or “consumption” but occasionally undertook it as sensitivity analysis.
Gail is correct in saying that there are many more costs associated with energy, and that these costs are extremely important to society. But we normally consider these as costs associated with use of energy, but not its extraction from Nature which is the point and definition of EROI analysis. We have considered these before as EROIpou, that is at the point of use, or more recently (and better in my opinion now) as the EROI (at the mine mouth) required to support various levels of societal well-being (e.g. education, health care, arts etc.; Lambert et al.). At the logical extreme we may wish to include all of civilization’s activities as supportive of the energy extractive process so that EROI would be (by definition) 1:1, but that does not seem useful to me. We need to know how much energy it takes to get each actual or potential energy resource. For example, with an EROI of close to 1:1 corn-based ethanol is not a net energy source to a modern complex society. The lower EROI of renewables after accounting for intermittency (see below) will make the transition to renewables, if that is possible, very difficult.
3) “The ones that can be counted are counted as equal, regardless of quality”. This is absolutely not true. We have considered quality exhaustively, and have even presented our results with and without quality corrections from our earliest publications (Cleveland et al., Hall et al.) through our most recent publications (Hall 2017 p. 133 etc.). Murphy et al. includes a sophisticated procedure called the Divisia index to correct qualities of input and output energy which we sometimes use in our results. The question of intermittency with wind and photovoltaic energy is a difficult issue repeatedly considered in EROI analysis although not fully resolved by the greater scientific community, but also clarified with the recent publications of Palmer (and Tverberg) for certain systems. Depending upon the penetration of renewables, including intermittency in the analysis greatly reduces the EROI of these technologies. Whether one corrects for the quality of energy output for these sources is best handled with sensitivity analysis.
EROI is not some flawed tool of the past, but a consistent yet evolving and improving tool becoming more and more important everyday as the depletion of our primary fuels continues and as replacement with renewables is increasingly considered. While EROI analysis is hardly precision science, mostly due to data limitations, nevertheless as I reviewed my older publications for this response I was impressed by the general consistency of our results (corrected for e.g. depletion over time) from 1979 and especially 1984 to present. A large problem is the erosion of the Federal support for, and hence quality of, the data of e.g. the U.S. Bureau of Census and the increasing use of EROI (and scientific analysis more generally) for advocacy rather than objective analysis and hypothesis testing. Essentially all credible analyses show a declining EROI of our principle fuels and a much lower EROI for those fuels we might have to replace them. The economic consequences are likely to be enormous. It continues to astonish me that there is essentially no Federal or other support for good, objective analysis of EROI and its implications. EROI is not only as important as when it was created it is critical now as we choose, or more likely will be forced into, making an energy transition. With appropriate support we have the conceptual and procedural tools to undertake needed analyses which can be an important tool in understanding and (with other tools) guiding our transition to renewable energy resources, if indeed that is possible.
Having said this I would like to point out where Gail does have a very good point. The amount of energy necessary to maintain the infrastructure within which our energy extraction industries can function (e.g. roads, schools, health care, perhaps civilization itself) is enormous and is not counted in my most of my studies as part of the investments to get the energy. OK good point. How to do this i.e. how to prorate this relative to e.g. all of the health care investments for all of the population? One might add up all of the labor in the appropriate energy industries, compare this to the total population and multiply the ratio by the total energy used in health care. Or one might assume that all of the energy required to support labor, including the energy associated with the depreciation of the worker (i.e. the energy used to support the family of the worker) is well represented by the worker’s salary. So if a worker makes $70,000 in a year one could multiply that by the mean energy intensity of the U.S. economy (about 6 MJ per dollar) to generate the energy used to support labor for year (420 GigaJoules, equal to about 70 barrels of oil). Again doing this for all energy workers would be a huge sum. When as part of sensitivity analysis we added in an estimate of the energy to support workers’ salaries for building solar facilities in Spain it doubled the energy cost of building and maintaining the PV structures and halved its EROI. The main point that I think Gail is making is that as our high quality fossil fuels are depleted and we contemplate shifting to renewable energies we will have a lower and lower net energy delivered to run the non-energy portion of society with very large consequences. I completely agree with this.
References (in chronological order – there are many more that could be added)
Hall, C.A.S., M. Lavine and J. Sloane. 1979. Efficiency of energy delivery systems: Part I. An economic and energy analysis. Environ. Mgment. 3 (6): 493-504.
Hall, C.A.S., C. Cleveland and M. Berger. 1981. Energy return on investment for United States Petroleum, Coal and Uranium, p. 715-724. in W. Mitsch (ed.), Energy and Ecological Modeling. Symp. Proc., Elsevier Publishing Co.
Cleveland, C.J., R. Costanza, C.A.S. Hall and R. Kaufmann. 1984. Energy and the United States economy: a biophysical perspective. Science 225: 890-897.
Murphy, David J., Hall, Charles A. S. 2010. Year in review—EROI or energy return on (energy) invested. Annals of the New York Academy of Sciences. Special Issue Ecological Economics Reviews: 1185, 102-118.
Murphy, D.J, Hall, C.A.S. 2011. Energy return on investment, peak oil, and the end of economic growth. Annals of the New York Academy of Sciences. Special Issue on Ecological economics. 1219: 52–72.
Hall, C.A.S., and Hanson, D. (Eds.) 2011. Sustainability: Special Issue on EROI
Murphy, D., Hall, C.A.S., Cleveland, C., P. O’Conner. 2011. Order from chaos: A Preliminary Protocol for Determining EROI for Fuels. Sustainability: Special Issue on EROI. 2011. Pages 1888-1907.
Guilford, M., C.A.S., Hall, P. O’Conner, and C.J., Cleveland. 2011. A new long term assessment of EROI for U.S. oil and gas: Sustainability: Special Issue on EROI. Pages 1866-1887.
Hall, C. A. S., Dale, B. and D. Pimentel. 2011. Seeking to understand the reasons for the different EROIs of biofuels. Sustainability 2011: 2433-2442.
Prieto, P., C.A.S. Hall. 2012 Spain’s Photovoltaic Revolution: The energy return on investment. Springer, N.Y.
Hall, Charles A.S., Jessica G. Lambert, Stephen B. Balogh. 2014. EROI of different fuels and the implications for society Energy Policy Energy Policy. 64,: 141–152.
Lambert, Jessica, Charles A.S. Hall, Stephen Balogh, Ajay Gupta, and Michelle Arnold. 2014. Energy, EROI and quality of life. Energy Policy Volume 64: 153-167
Hall, C.A.S. 2017. Energy Return on Investment: A unifying principle for Biology, Economics and sustainability. SpringerNature N.Y.
Palmer, G. 2017, A Framework for Incorporating EROI into Electrical Storage, BioPhysical Economics and Resource Quality, vol. 2, no. 2