Report on My Activities at SUNY-ESF
As many regular readers know I have been in Syracuse, NY, at the State University of New York, Environmental Sciences and Forestry (SUNY-ESF) working with Dr. Charles Hall on biophysical economics. I've been here since Sept. 15 and it has been an absolutely dream kind of sabbatical leave. I've always thought of myself as a student-for-life and a PhD was my ticket to being able to devote my life to learning everything I could that seemed important to know (see my post: "Subjects of Interest").
I have long had an on-going interest in how energy and the economy related to one another. That is based on a very simple observation: it takes energy to do work, and the economy is nothing if not about doing work to create wealth. Therefore, energy must lie at the heart of how the world's economies function. Realizing that the vast majority of energy used by modern industrial societies, and those wanting to become industrialized, comes from fossil fuels, and fossil fuels are a fixed, finite resource, it long-ago occurred to me that industrial economies could not be sustained. The fuels are going to eventually run out. This was even before greenhouse gasses and global warming had come to the fore.
Over the last several years my interest in energy and the economy has been rekindled by the advent of peak oil. I've been spearheading several efforts to get energy systems curriculum into higher education and started exploring research questions that I might pursue. Several years ago, while reading various articles in The Oil Drum blog, I encountered the concept of energy return on energy invested (EROI or EROEI), which I found comported with my own developing ideas about the possibility that some of the proposed alternative energy methods might not actually be sustainable if it took more energy to build the systems than they would contribute to our energy needs. The concept was the brainchild of Charlie Hall who had developed it after years of studying energy flow in ecosystems. He had learned his trade from Howard T. Odum, the world famous ecologist who pretty much invented systems ecology.
Originally I had several objectives in coming here to learn about EROI analysis and how I might use it to determine the real sustainability potential for various alternative energy systems. I had built a basic model of what I called a sustainability criterion. What the model was supposed to do was determine if the total energy output from a system, say a photovoltaic (PV) system, would be enough to not only supply the user demand, but also produce enough excess power over its lifetime to feed into replicating itself. Imagine a solar PV manufacturing plant that was run entirely from a PV array. But you would also need to run the parts manufacturing plants from PV arrays, do the shipping using energy derived from PV arrays, and, in fact, run the farms that supplied the food to all the workers using PV arrays. Not so simple.
The motivation for wanting to know if many PV arrays could be generated from a few such arrays is actually essential in knowing whether or not PV is truly sustainable. Of course the above scenario would have to be modified to recognize that PV provides intermittent power, so all of those operations would have to have backup power supplied from the grid. But this would be borrowed power that would be paid back when the sun was shining so that the net effect would be as if everything was powered by PV (e.g., wind and nuclear might also contribute to the grid providing an array of sources to cover each other during down time). Right now, all of the manufacturing of wind turbines, solar collectors, etc. is actually powered by fossil fuels or existing hydroelectric. Fossil fuels are the only way to transport parts and finished products as it stands, and coal or natural gas are burned in most Midwest, southwest, and eastern states to produce electricity. Thus the whole alternative energy industry is currently subsidized by fossil fuels and it is by no means clear — no one has demonstrated with data — that these alternatives could take care of their own power needs while still building out the needed capacity to run the economy.
I came here with the idea that I would learn how to apply EROI methods to the analysis for data to fuel my model. But what I learned is that this is a daunting task. As the above example suggests, the web of interrelations between all the manufacturers, shippers, suppliers, materials extractors, even the food support system for the workers is extremely complex. The strength of the links gets more attenuated the farther from the final manufacturing plant you go. Then there is the installation and maintenance activities to consider. All in all, it is currently a nearly impossible task to collect all of the energy consumption data that would be needed to do a good job of modeling and evaluating the systems. That was the first thing I learned.
But while I was coming to this realization, I was developing another idea that had suggested itself to me in thinking about modeling energy systems in general. There is a concept called the 'boundary limits' which basically tells you something about where you should draw the line around the system of interest to prevent infinite regress. You can see this in the above problem where the tractability of analysis can only be bought by deciding to cut off the analysis effort at some reasonable distance from the center, say we decided to ignore everything beyond the first tier of parts manufacturing and shipping. We could forget about those efforts further out in the web because their total contribution might be negligible in terms of each PV system manufactured. Knowing where to draw the line is as much art as science.
The boundary problem exists for these kinds of complex systems when you are doing a 'bottom-up' kind of analysis. That got me to thinking along the lines of a 'top-down' approach. Sometimes it is easier to model a 'whole' system leaving out a lot of detail, yet capturing the essence of the system's behavior. This is, in fact, the approach I had used in modeling synapses and neurons in my days developing artificial brains for robots. Rather than trying to emulate every little detail of a system, it is sometimes possible to start from first principles and develop a model that captures the overall dynamics of the system and allows you to make predictions about system behavior under different conditions.
So for the last month+ I have been working on a macro-model of what I am calling an 'abstract economy'. It looks strictly at the energy flow dynamics of an economy based on a fixed, finite fuel source — not much different from our own real economy. What makes an economy is that energy is used to make artifacts that users need and or want (no moral judgments here). These are the assets of an economy. Some are long-lived, like buildings and railroads. Others have intermediate life spans, like washing machines and toasters. Others are consumable, like food, entertainment, and socks. But over time, when there is sufficient available energy, the economy will use that energy to convert natural resources (metals, salts, trees, etc.) into assets. With the realistic assumption that consumers are insatiable if the energy is available, then I posit a growth constant used to compute exponential growth in energy extraction and asset accumulation. In other words, it looks a lot like the classical developed world economy. I've now got a computer model running and some early, somewhat expected results. But I also have a result that would have been hidden from view had I not built the model.
I started with the idea of a reservoir of fixed, finite size (arbitrary in the model). The reservoir contains unrefined fuels of average energy density. Extracting the fuels from the reservoir takes work. You are working to find places to drill, working to do the drilling, working to do the extraction, and working to alter the fuel for consumption at the end uses (e.g. refining oil to gasoline and kerosene, etc.). All of that work requires energy from the stream of energy flow, and it takes more work to accomplish the same energy production as the resource depletes. This is the EROI aspect. So the model computes for each time step the gross energy extracted, the energy cost of extraction, the net energy available to asset production (gross minus costs — a concept any accountant or financial person can appreciate), and the accumulation of assets. Here is a graph from a typical run of the model.
The model correctly behaves with respect to the peaking of gross energy production (e.g. peak oil; top, blue line) and increasing costs (bottom, red line). Net energy available for asset production can also be seen peaking. But curiously, it peaks before gross energy. The time units are about 5 years, so net peaks about 20 - 25 years before gross peaks. This is significant in that it is the net energy that runs the rest of the economy.
If it is true that we are currently at or past (or about to get to) the peak of oil production, and all of the data are consistent with this hypothesis, and since oil is the 'kingpin' energy source, needed to extract and transport every other fuel, then it is conceivable that we are also very near the peak of gross energy as depicted. If that is the case then this supports evidence that we have already passed the peak of net energy and hence we are in the phase of decelerating asset production.
I have written for some time about this possibility, but I have only had anecdotal evidence in the economic crises we have been faced with for the last ten years or so (seeing globalization and offshoring of manufacturing and jobs as a crisis for the US workers, as well as our general neglect of critical infrastructure). Now this model reinforces what I suspected. It isn't peak oil that will get us, so much as peak net has already done some damage.
Note how even after net energy flow peaks asset accumulation continues. This is because there still is some net energy available to build new assets. But after a while the decline in net energy becomes so intense that asset accumulation itself peaks and its all downhill from there.
It is easy to understand why energy from a fixed, finite resource peaks and then declines after a time. What isn't completely obvious is why assets would decline the way they do. The reason is that the 2nd Law of Thermodynamics is always at work on our assets. Plus, we are constantly consuming some of those assets. Entropic decay eats at our bridges and buildings. Physical things age and fall apart unless there is a constant supply of energy to fix them up, repair damage (from use), or replace a worn out object. The rate of asset decay is probably less than shown in the graph because for this first pass I have lumped all types of asset into one class and set a somewhat arbitrary decay rate for them all. As I improve the model's resolution and details I will subclass at least three types of assets (long-term, well-built; intermediate-term; and consumable over the time steps used) and have them decay or be consumed at more realistic rates. But that will not change the general trend over the very long term. The decline in net energy is not unrealistic given the assumption that it comes from a finite resource.
A next step in model refinement will be to add back in the less-than 20% gross energy supplied by supposed renewable sources, esp. hydroelectric and nuclear, with provisions for a growth rate in alternatives like wind and solar. Then we can test how various rates of build-out of the alternatives may shape the future of gross and net energies. We fully expect that a large growth rate for alternatives will extend the gross line at a higher level (but below peak for the non-renewables) for a longer time. But what we don't yet know is what the effect will be on the net energy. Everything depends on the wide-sense EROI of these sources. If they are high (meaning above 20:1) and the growth rate of build-out is sufficiently high (which is a research question to ask the model) then we may be able to see net energy maintaining a higher level and at least keep our asset base from shrinking. My own speculations lead me to believe that it will take an EROI of more than 50:1 and a build-out growth rate greater than 15% per annum for the first 20 years followed by steadily declining rates over the next decades as we approach 100% replacement. That is what the model might be able to tell us. And it is important to know.
If we determine that our assets can be stabilized at something like the above numbers, then it is crucial to know which alternatives will provide us with adequate sustainability (high, sustained EROI) and direct our remaining net energy investments into building those top performers at a rate that will achieve that stability. Right now we are guessing and hoping, hardly a predicament to be in for a supposedly scientific age and mind set.
But therein lies the real problem. We have scientists like Hall and many others who are earnestly trying to ascertain the numbers so we can make informed decisions. The problem is we are in the minority and often just ignored because we bring potentially bad economic and political news to the only people who can do something about all of this. And our less than sapient leaders, indeed the majority of the citizens, just don't want to hear bad news. Achieving what I have in mind will take extreme sacrifice on the part of everyone to allow diversion of our remaining ability to do useful work toward the build-out of these alternative energy sources (and, BTW, this also includes increased efficiency and conservation efforts). No politician is ready to spread the message of sacrifice. I'm sorely disappointed in Obama in not following through on his inaugural address when he said that we would need to sacrifice. In retrospect I guess this was code for 'all you working class folks are going to have to sacrifice (lose your income) while the bankers prosper'. Too bad.
There is one more thing I need to point out that will seem a little untoward, but is essential to grasp. The assets I mentioned include all human biomass! That may sound perverse, but the fact is that our population is supported by the energy flow through the economy. A lot of that energy flow is actually directed to managing the agricultural and food distribution system. More net energy means more and bigger (obese) people are able to exist. Consider, if you will, what the meaning of a crash, as depicted in the graph, means for human life. I'll leave you with that thought. And with a question: What do you think we should do about it?