Peak Oil and "The Limits to Growth": two parallel stories
Posted by Ugo Bardi on February 16, 2008 - 10:00am in The Oil Drum: Europe
Topic: Environment/Sustainability
Tags: limits to growth, sustainability [list all tags]

The figure above is taken from the 2004 edition of "The Limits to Growth". It shows the typical curves that the models of the study produce. These curves are similar to those of oil depletion studies based on the "Hubbert model". The similarity is not casual, the theory and the method behind the two approaches have a lot in common.
It is safe to say that, in the 1950s, Marion King Hubbert and Jay Wright Forrester didn't know of each other's existence. Yet, working independently, they were setting the basis for a new science. They were not the first to study the limits of the world's resources. But they were the first to do that using mathematical models that could be extrapolated into the future.
Marion King Hubbert, a geologist working at Shell Oil in Houston, was using an empirical approach for studying crude oil production. In 1956, he published his, now famous forecast that oil production in the US 48 lower states would peak around 1970 and then decline. It did. In the same paper, Hubbert applied his method to the whole world, arriving to the conclusion that oil production worldwide would peak around the year 2000. This long term forecast might turn out to have been approximately correct as the world peak ("peak oil") is still expected for the first decade of the 21st century.
Fig. 1 Hubbert's forecast for the world's oil production, from his 1956 paper
Jay Wright Forrester, professor at the Massachusetts Institute of Technology, had a background in engineering and his goals were more ambitious than those of Hubbert. In the 1950s Forrester had developed a new approach to modeling that he had called "system dynamics". The idea was to use the digital computers, newly developed at the time, to solve a set of differential equations that described the system under study.
Forrester started using his method with physical systems. Then he moved to simple economic and social systems. From there, an obvious step was to model the whole world, something that had to take into account, among other factors, the limits to Earth's resources. Forrester developed his first world models in the late 1960s and published his results in 1971 in a book titled "World Dynamics". But the real impact of Forrester's ideas arrived as a study performed by a group of young scientists at the MIT who used Forrester's approach to develop more detailed models of the world's economy.
Dennis Meadows, Donella Meadows, Jorgen Randers, and William Behrens III published their work in 1972 with the title of "The Limits to Growth." The book developed a series of scenarios according to various hypothesis on the availability of resources and on world policies that could be developed and implemented in the future. All the scenarios, except for some special cases, generated the collapse of the world's industrial and agricultural systems at some date within the 21st century. Forrester had arrived to similar results in his 1971 book.
A typical result of the 1972 LTG study is shown in the following figure for what the authors had called the "base case" model. In this model, the resources in input correspond to the best available data and it is assumed that the current policies and economic trends remain unchanged over the period considered.

Fig. 2 Base case model of the 1972 edition of "The Limits to growth". This image was published by the Time Magazine in 1972. From http://www.holmestead.ca/reserved/popexplo/popexplo.html
The work of the LTG team had a huge impact, with millions of copies of the book sold. Hubbert's work also had a considerable impact, although mostly within the world of specialists in crude oil. However, as years passed, both studies were strongly criticized. The period of apparent abundance of the 1990s seemed to cause the total obsolescence of all ideas and theories that predicted bad times ahead. "The Limits to Growth", went through a phase of active demonization that pictured it as having been "wrong" in its predictions. Even though the collapse envisioned in the scenarios was to take place only in 21st century, still today for most people the LTG study is an example of flawed predictions. Hubbert's work, ion the other hand, was simply forgotten.
But the models and the ideas that were behind these studies were not abandoned. "The Limits to Growth" study was updated and the latest version was published in 2004. It is, at present, again generating considerable interest. Hubbert's ideas and methods were revived in the late 1990s by Colin Campbell and Jean Laherrere who started what we call today the "peak oil movement."
The results of the models that we are discussing have not changed much if we compare the early work with the recent updates. Here are some results of the 2004 version of "The Limits to Growth". This is, again, the base case model. As you can see, the collapse of the world's industrial and agricultural system is still generated for this case for approximately the same date as in the 1972 version.

Fig. 3 Base case model of the 2004 edition of "The Limits to growth".
Here is, instead, an example of recent results obtained by Jean Laherrere who uses a Hubbert-like approach for describing the production of the main categories of fossil fuels. The date for peak oil is shifted by some years forward with respect to the early predictions by Hubbert, but the bell shaped curve remains about the same.

Fig. 4 From Jean Laherrere, 2006. http://www.oilcrisis.com/laherrere/groningen.pdf
These results indicate that, in the coming decades (or even years), we may see the reversal of some of the growth trends that we came to see as the natural order of things. Peaking and decline is expected not just for fossil fuels, as shown before by Laherrere, but also for most mineral commodities (see a recent study by Bardi and Pagani ). These are just subsystems of a vaster system that may collapse in the coming years according to the LTG models.
So, "Hubbert modeling" and "world modeling" have a lot in common but, of course, they are also very different. Let's now examine more in detail how the two methods are related and what are the specific differences.
The Hubbert model is purely empirical. It postulates that the production of crude oil and of other mineral resources will follow a "bell shaped" curve, often taken as the derivative of a logistic function. Modeling production means to fit two parameters to the bell shaped curve: past production and the available reserves. Good data obtained from geological estimates are, therefore, a crucial element of the model, which is considered to be a tool for forecasting future production. The model is robust, in the sense that it depends on just a few parameters, and it has turned out to produce reasonably reliable predictions. Of course, it is rare that the model generates the amazing precision of Hubbert's 1956 forecast for the US oil production. But, on the whole, the model is able to detect an impending production peak, as it has happened for cases such as the North Sea oil production, that peaked around the turn of the century. The Hubbert model, in itself, says nothing about what could be the consequences of the global peaking of oil production, even though "peak oilers" tend to see it as an important turning point for mankind.
World modeling studies based on system dynamics start with a detailed description of the main features of the system under study. Obviously, that implies drastic simplifications in describing the world's economy. Nevertheless, world models are much more complex and detailed than the simple Hubbert one. In addition to quantitative data on the available resources, these models include such factors as market, technology, government policies, regulations and others. Because of the large number of parameters and the inherent uncertainty in the data, the results of the models may vary considerably depending on the parameters in input. For this reason, these models are not considered as predictive tools, as Hubbert-style models are, but, rather, as descriptive tools. The idea is that, if the model can describe the system under study, it can be used for understanding how one can control it. In the case of world modeling, the authors of the LTG studies always emphasized that their models were not "predictions" but rather scenarios and that their purpose was understanding what policies should be implemented for avoiding collapse.
Let's go a little more in depth on how system dynamics is used in order to simulate the whole world. In the LTG studies, it is done by aggregating the elements of the system into a relatively small number of variables: 1) natural resources, 2) agriculture, 3) population, 4) capital, 5) pollution. Here are the main elements of the model in graphical form according to Magne Myrtveit.

Fig. 5 - the main elements of the world model, according to Magne Myrtveit (https://bora.uib.no/bitstream/1956/1974/1/WPSD1.05WorldControversy.pdf)
As you see, the model takes into account mineral resources, but just as one element of a more complex system. However, it is perfectly possible to use system dynamics for modeling specific sectors of the economy, for instance for the extraction of a mineral resource. One of the first models of this kind was made in 1974 by Roger Naill who worked in close contact with the LTG team and used the same software to model natural gas production in the United States.
You can find a detailed description of Naill's model at http://www.albany.edu/cpr/sds//DL-IntroSysDyn/ch6_f.htm. The model is complex, involving such parameters as prices, technology, market responses and others. Nevertheless, the fundamental concepts of the model are simple: the resource is supposed to be finite; extraction is assumed to be driven by market factors and ultimately slowed down by the rising costs caused by depletion. The final result is a bell shaped curve similar to the typical Hubbert curve. Here is what we can call the "base case" model of this study, taken from "Towards Global Equilibrium" (1974)

Fig. 6 - Natural gas production in the 48 US lower states as modeled by Roger Naill in "Towards Global Equilibrium" 1974. "Usage rate" is what is normally called "production". The peak of the usage rate curve occurs for about 1975 in this scenario.
We can now compare Naill's results with those that Hubbert had proposed in 1956 for natural gas production in the United States

Fig. 7 - Natural gas production in the US as modeled by Marion King Hubbert in 1956
One difference that is immediately apparent in these models is that Hubbert's curve is normally symmetric or slightly skewed backwards, as in this case. Naill's curve, instead, is skewed forward; as it seems to be the case for most system dynamics studies of this kind. The reason for the forward slanting curve lies in the built-in tendency of the market of compensating for depletion by increasing the effort of extraction. This strategy succeeds in retarding the production peak. However, since the extractable amount is finite anyway, postponing the peak must be paid with a more rapid decline. Apart from this point, the two models produce similar curves and, in this case, indicate approximately the same date for peaking.
Several decades after that these models were proposed, we can say that neither one provided an exact description of reality. Natural gas production in the US did peak in the early 1970s, as Hubbert had predicted and as Naill's models tended to indicate. But, after about 10 years of decline, production stopped following a bell shaped curve. It picked up again and peaked a second time approximately in 2000, without having reached again the level the first peak. This behavior may be explained in various ways (see a recent reassessment by Luis de Souza), but that is not the point here; models are always approximate anyway. The point is that when modeling the production of a single mineral resource, the Hubbert approach and system dynamics generate very similar curves.
That doesn't mean, of course, that world modeling is the same thing as Hubbert modeling. World models take into account many more elements than resource depletion models. In particular, as early as in the first LTG study, one of the elements of the model was called "pollution;" something that, today, we see as mainly related to global warming. Depending on the input parameters chosen, the collapse that the LTG world models generate may be caused mainly by resource depletion or by a runaway climate change.
If global warming hits us first, our worries about resource depletion are of little importance and the reverse is also true. At present, we can't say which problem is the more immediate one. What we can say is that fossil fuels (and crude oil in particular) are the crucial resource of the world's economy. In the hypothesis that resource depletion is a more pressing concern than global warming, the vision of impending "peak oil" and "peak fossils" is equivalent to that of the "base case" model of the LTG studies. In both cases, we see the collapse of the industrial society due to resource depletion.
So, it may be that peak oil and "peak civilization" will coincide as an event taking place in the first decades of 21st century. Of course, we are not there yet, but the world's economic system is letting out ominous creaking noises. Are these signs of impending collapse? We won't have to wait for many years to know.
There would be much more to say on the subject of peak oil and world modeling. One is how the results of the first LTG study have been so effectively demonized and marginalized; a fate that peak oil studies have avoided - although they received a fair share of political criticism as well. That will be the subject of another post.
I wish to thank Dennis Meadows, Jorgen Randers, Magne Myrtveit and several others who introduced me to the fascinating world of system dynamics
References
Matthew Simmons was one of the first of those involved in peak oil studies to re-examine the story of the Limits to Growth. His 2000 essay on this subject can be found at http://www.simmonsco-intl.com/files/172.pdf
A detailed reappraisal of the world model controversy can be found in Magne Myrtveit's 2005 paper at https://bora.uib.no/bitstream/1956/1974/1/WPSD1.05WorldControversy.pdf
Jean Laherrere has also re-examined the LTG study in this paper, pubshed in the ASPO-Ireland site
http://www.aspo-ireland.org/index.cfm?page=speakerArticles&rbId=9
Another recent positive reassessment of the LTG study by "Big Gav" can be found at http://anz.theoildrum.com/node/3572
A description of how Roger Naill generated the Hubbert model from system dynamics assumptions can be found at http://www.albany.edu/cpr/sds//DL-IntroSysDyn/energy.htm. His model was published for the first time in "Toward Global Equilibrium, Collected Papers". D.L. Meadows and D.H. Meadows (eds), Cambridge, MA, 1974, pp 213-256.
The original 1956 article by Marion King Hubbert can be found at
http://www.energybulletin.net/13630.html



Good comparison. We have used the Limits of Growth report as well in our stories about the ecological bottlenecks that await us. The best overview & comparison of the two methods I've seen so far.
Applause from the hall.
Thanks!
Black Friday
March 7 2008 11:30 am ( NY time )
BOOM
A very interesting exercise is to plot the 1st derivative(slope)versus time, of the non-renewable resources curve from the "business-as-usual" or baseline scenario of "Limits of Growth" for any of the three books. If you then invert the resulting curve it forms a nice Hubbert type "peaking" trend. Of course, this is to be expected as the resources curve has a nice inflection point. Shown this way non-renewable resources, for this baseline scenario, reaches a peak in about 2015. It is not surprising then that the world is experiencing the current questions about resource sustainability exactly midpoint between Hubbert's 2000 peak oil and "limits to Growth" 2015 peak non-renewable resources.
Any chance of seeing a chart? If you can't post charts then email it to me - png is best but jpg or tiff will do - and I'll post it.
Euan
Thanks to jmac for his plot. And a comment attached:
Very nice. Thanks Jmac!
The basic building blocks of system dynamic models are reservoirs (stocks) and flows, and mechanisms that regulate the flows into and out of the reservoirs. That means that you have to close off the world that you model, otherwise things that enter or leave your system can give unpredictable consequences. And so the real "art" of system dynamics is to divide real –open– systems into closed systems of stocks and flows. Yet in open systems – open, for instance, to flows of information, and/or open to flows of solar energy – new forms of self-organisation can be created, that cannot be captured in a system dynamics model. However, the valuable point of the stock/flow models is of course that it helped to unmask the inconvenient truth of resource depletion. The System Dynamics Society now celebrates its 50th anniversary, without getting much honour for that. Work continues though. Members recently received the first announcement of The First European Energy Workshop, organised by EIfER and LISTO and kindly hosted by EIfER. "This Workshop aims at gathering all SD-practitioners in the energy domain together in a pleasant atmosphere. The workshop shall take place on Thursday and Friday April 17-18 at EIfER in Karlsruhe (Germany)." Contact: Tobias Jaeger (www.eifer.uni-karlsruhe.de), and Luc Van Den Durpel (www.listo.be).
Filed under "Peak Oil", "Peak Everything Else".
-Andre'
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System dynamics sounds great. Working upwards and outwards or staying in a small system, being modular, all depending on what you intend to model, the world or a limited system. If we at TOD want to get away from just resource modeling with Hubbert Linearization and talk about the big picture wtih various planning scenarios this is the set of tools we will have to use. For a layman or anyone with a good science or engineering background and an inteest it seems this would be what we need to learn in our spare tim to figur out how to see what is possible and what not. I would presume however that such a model, depending on what one has inmind needs a computer programme, custom made and lots of data gathered over many months so that it would be impractical for our off th cuff threads made over a weekend. Is this right or can one just work up something quick and dirty with standard tools on the web or elsewhere?
I've found that learning system dynamics is a little like learning to play chess. You first learn how to move pieces, then you can play the game. But becoming a master takes years of practice. I am still a novice in system dynamics; I am learning. I can make models using Vensim and found that it is a good way for focusing one's mind on the way the system you are studying works. On the other hand, coming from Hubbert style modeling, I found surprising that Vensim (and not even Stella, as far as I know) has no routines for data fitting. It is a different world, a different philosophy. S.D. models, it seems, are not supposed to be predictive tools. Nevertheless, I am trying to do exactly that; use S.D. models to fit oil production curves. For that, I had to enlist the help of a coworker who is a better programmer than I am and who built specific routines using Simulink. We are getting interesting results that we plan to publish, but we are doing that in our spare time, as usual. It is a law of academia that the most interesting research project is the one that doesn't get financial support. So, it moves on, but sloooowly......
Systems dynamics has its uses (IIRC that's what the World Energy Modeling Project are using). However it tends to break down in two main areas:
So when you are talking about resources or areas where humans just react blindly it can deliver some insight. However when things start going wrong it can badly fail to represent strategic or tactical action from C&C type economies.
As a simple for instance. It would be perfectly possible to imagine someone letting off a nuke in the heart of the Saudi oil region. The instantaneous effect on oil supply would be obvious, as would the environmental impacts. However it would also bring other worldview models to the front. The world after such an event wouldn't run on the same rules as the world before. There is no way system dynamics can model such changes since the very makeup of the model depends on your understanding of how the world works now.
If you want to play, there are SD tools around. However I'd tend to focus on complex adaptive systems approaches if I were you.
I googled complex adaptive systems and got a university link with some Mac software:
http://cognitrn.psych.indiana.edu/rgoldsto/complex/
and a quote:
http://www.innovation.cc/volumes-issues/rogers-adaptivesystem7final.pdf
and from WIKI of course:
http://en.wikipedia.org/wiki/Complex_adaptive_system
Sorry, I did tend to throw away the end comment.
The benefit from my perspective is that you can create individual agents which behave as actors in your simulation, complete with known behaviours, possible behaviours, and memory. You then combine these and look at what comes out of the complex whole, together with a degree of Monte Carlo simulation of parameters, random events. From the population of results you gain understanding of how the simulation will tend to react across a likely range of circumstances (eg where are the attractors) and if your simulation is anything like reality, a deeper understanding of how real systems will react. Agents don't need to be people/nations, they can be identified groupings, resources, anything.
I think you can see from the links you pulled out why I think they are a better match for modelling the characteristics we are interested in.
intuitive appreciation !
Studied all this stuff (and much more) through those, you know, "Quantum Chromodynamics & The Charmed Quark for Dummies" style books.(populist commentries may be the precise term ?)
These matters you good folks speak of are definitely valid as methodologies and I basically make all my decisions in life based upon an intuitive mathematical engine that compiles many varieties of maths, science and pseudo-science into a functional world view. I'm doing very well thanks. A little bird tells me, WE are not doing so well at all.
Prediction - things are going to "blow up in our face" within weeks.
(The Finance system is an odds on favourite, so it probably won't be that LOL)
Smile, it's a good feeling.
Not quite... What he actually said *in the same paper* was:
"On the basis of the present estimates of the ultimate reserves of petroleum and natural gas, it appears that the culmination of world production of these products should occur within about half a century..."
That would make his estimate for peak the year 2006. In my opinion a far more astounding feat of prediction than the oft misquoted "around the year 2000".
Well, Hubbert was no fool, of course. The figure shown in the 1956 paper has the peak in 2000, but of course he knew that a prediction for 50 years in the future could only be approximate and he said so. It was an astoundingly good prediction, indeed!
The problem with the limits to growth is it's using an old and crappy simulation.
I knocked one up myself on an excel spreadsheet and depending on the inputs you can run it at a steady state. The problem is, the numbers don't always make sense if you fiddle around with the constants.
Due to the nature of feedback you can end up with chaotic systems and I suspect this is the problem with the limits to growth theory.
I made one with the following assumptions:
Pollution increases along with gdp growth (no assumption that pollution would be mitigated at a certain level of GDO).
Increased pollution causes increased death rates.
Increased population above a limit causes depletion of agriculture.
Below a certain limit per person of agriculture, the death rate increased.
What it predicted was this:
GDP continues to climb till 2030 or thereabouts, the population drops about a billion, bumps up slightly then shoots down in a pendulum like manner to BELOW zero and bounces up again with a widenining variance between low and high.
So the moral of the story is this: you can do anything with an excel spreadsheet and the limits of growth was done way before excel.
PS anyone who wants a copy of my spreadsheet to tinker with is welcome.
I got a telling off here as it is some 30 years since I read 'Limits' and I was dependent on my memory for the statements I made, amongst the replies being that it did not predict anything but painted scenarios.
I still remember though the feeling of horror with which I looked at their 'scenarios', as it was immediately obvious that the outcome was totally dependent on the initial assumptions.
I also remember that in spite of their backing off from the word 'prediction', as it could not possibly be substantiated, in the ensuing political debate the document was indeed treated as a prediction, with many claiming that it showed this or that.
A similar process can be observed at work today, where the 'scenarios' painted by the IPCC take on a life of their own and somehow become probabalistic estimates.
As soon as it became possible modelling was inevitable, but the results need handling with some care.
It is interesting however to tinker with it.
I also understand the feelings of dread the original modelers must have felt when they tried various assumptions and they all produced a crash.
I got exactly the same results until I started to put in limits such as population limits before depletion of agriculture sets in and also increased breeding in low density (things that actually happen in the real world).
What I found was that in the unmodified original scenario there is a hubber like boom then a bust. With a slight modification (population stabilizes but pollution does not) I get a population boom then a leveling off then a crash.
The crazy thing, however was when I started putting in all sorts of limits the system became chaotic (in the scientific sense of the word) and that the population crashed then started to bounce around wildly with massive swings.
Though that sort of thing can happen with turbulence in, say a saucepan of water being heated on a stove, it just doesn't happen with species populations.
Species populations do the following:
They can do the algae bloom thing where they grow mindlessly and then crash down to starvation levels.
They can go up and then stabilize (the famous "S curve")
OR
They can fluctuate between two or more levels (the famous "prey-predator" curve).
My guess is that only some of our populations will do the algae bloom thing (e.g. massive cities of several million who are powered purely by hydrocarbons).
Others will do the S-Curve and stabilize (the fewest I would guess).
The most I expect will fluctuate downwards in a prey-predator collapse and then go up again as the world economy reconfigures around renewable energy and renewable agriculture. (In some cases the predator will be war or disease).
If we as a species crash completely then we are as stupid as algae and we deserve to die.
I doubt that is the case.
Or, with some glichiness due to peak oil, the population could rise to about 9.5bn, then start a gentle downward path ending up at perhaps 4 billion in 2200.
There is, after all, as our friends who are fans of solar power will tell us, plenty of energy, and as all peak oilers will tell us, that is a critical resource.
The arguments for peaks in other supplies, with the exception of some rare minerals, seem to me much weaker - if you have enough energy.
That is really the dangerous thing about modelling, it is entirely dependent on assumptions, and just as is the case for models of global warming, we are then told, 'our models show that' when other outcomes have been ruled out by the assumptions chosen.
For instance, the GW projections assume the fossil fuels are there and accessible to cause the warming, which like all long term trends is a lot bigger at the end of the projected period, ie from the end of the 21st century on.
That is why these models are a dangerous thing - they are deeply deceptive in their usual application.
It's a little odd to me to hear that it is "dangerous" that models are dependent on assumptions. To me that's like saying it's really "dangerous" that the distance I throw a baseball is based on the initial force I give it. It's the assumptions (i.e. variables, both initial and ongoing) that make a model an extraordinarily powerful tool.
The way I see it, one really valuable thing a model does is point out that if we don't change a specific variable over time (say, pollution production per person), there is a predictable, almost certain outcome.
In the case of the Real Earth Model(tm) that we're all participating in, there are so many variables now that need to be changed that perhaps the endgame is now a foregone conclusion. Off the top of my head, some of the variables that need dramatic change seem to be:
And of course the one variable to rule them all, the reproductive rate per person.
I happen to be one of those people who thinks if it isn't fossil fuel depletion that gets us (leading to a crash of industrial civilization), the next variable waiting in line is...well, take your pick from the list above.
When I first heard James Lovelock say that there is a good chance, in his view, that humanity will be reduced to a few breeding pairs at the poles because that will be where we'll find arable land in the future, my reaction was immediate denial: "That's silly."
After some digging into the topic, now I've completely reversed my view on this matter. In fact, whether it's a few of us at the poles or pockets of humans scattered around a significantly denuded planet, I think either of those outcome are more likely than 9.6 billion people living happily on a planet built for one billion or so.
-Andre'
It is the way the models are usually used that is dangerous, not the models themselves.
They are inevitable, but need handling with care.
Hi, DaveMart.
Understood. I was going off of the sentence "That is really the dangerous thing about modelling, it is entirely dependent on assumptions, and just as is the case for models of global warming, we are then told, 'our models show that' when other outcomes have been ruled out by the assumptions chosen."
Perhaps a more accurate way of saying the above would be: "The really dangerous thing about communicating the results of modeling is that other outcomes are ruled out by the assumptions chosen and that's not always made clear by the modelers."
Something like that. I apologize for belaboring this; I think your point is a very good one so that's why I'm spending time on getting the wording right. Can you tell I'm an educator?
DaveMatt - your scathing criticism of modelling by the IPCC [Inter-Governmental Panel on Climate Change] for using in their models the resource assumptions provided by the founding Governments, seems pretty facile.
Quote - "For instance, the GW projections assume the fossil fuels are there and accessible to cause the warming, which like all long term trends is a lot bigger at the end of the projected period, ie from the end of the 21st century on.
That is why these models are a dangerous thing - they are deeply deceptive in their usual application."
The assumptions underlying your critique have no such formal justification as does the IPCC -
You assume apparently that GHG output will fall with declining conventional fossil fuel supplies, when in fact, here in the UK (and predictably elsewhere) elevated gas prices have already increased coal burning for power, thus raising TCO2eq/MWH.
Furthermore, recent reports from Asia should have informed your assumptions that both Japan and India have embarked on the exploitation of seabed Methyl Hydrates (formerly known as Clathrates). Their scale as a fuel resource utterly dwarfs that of the vast Permafrost Peat fuel-stocks, which in turn dwarfs the very large Boreal, Temperate & Tropical Forest Wood fuel-stocks.
It seems that you fail to comprehend the core of the GW problem, namely that our emissions are nearing the point at which a diverse range of positive feedbacks will, quite predictably, cause sufficient warming to offset the entire intake of the planet's rather fragile GHG Sinks (varying around 30% of Anthro-output). At that point we'd no longer have any serious prospect of managing events, as the planetary heating would be independent of our GHG outputs.
Thus it matters not a damn whether "coal supplies won't last till 2100" - what matters is sufficiently cutting the rate of global GHG output, and increasing the recovery of excess airborne carbon, In The Coming Decade.
And every tonne of dirtier replacement fuels burned as a result of depletion effects makes it more likely that we will face an American-lead global genocide by droughts and famine, advanced and exacerbated by subsidized food-crop combustion.
The problem is that urgent, and I suggest that the unwarranted turf-wars between campaigners on PO & GW are an indulgence that neither campaign can afford. In fact I'm of the view that it's high time the two issues were fully integrated to a single focus of concern.
So before trying to undermine the modelling by the IPCC, maybe you'd do well to reconsider whether they are actually doing their best under severe administrative constraints ?
Regards,
Backstop
Bryn Davidson of Dynamic Cities does a really nice job of explaining why these issues should be tackled together.
http://dynamiccities.squarespace.com/home/
Your point about positive feedbacks is well stated. We have lit a fuse. We have a very short time to smother the spark.
gTrout – thanks for your response and the link – I’d heard of the Dynamic Cities Project [DCP] but not opened it before.
Sadly I can’t find the article you recommend – any directions welcome.
The DCP organization is rather intriguing – they have the site well structured but often hollow, being titles in front of “ under construction” notes, with a notable exception being the marketing of city gardening document-guides.
They also post some amusing graphs of a rather arbitrary set of shares of global emissions budget for the next 42 years – with nations set in four categories being :
Dirtier Developed, Cleaner Developed, Wealthier Developing, Poorer Developing.
This they juxtapose with a 2050 scenario of Contraction & Convergence-to-per-Capita-Parity of emissions entitlements, but it’s hard to be sure just why, or how the massive injustices of so arbitrary a set of entitlement classes is addressed (if at all), without an explanatory text being shown.
What seems quite plain is that the proposed program of global emissions cuts on which their USA + Canada cuts are premised are not remotely commensurate with the dynamics of the energy-pollution problem.
For example, they refer to an “evolving consensus” around limiting warming to less than 2 degrees Centigrade;
and further propose that this can be done merely by cutting global GHG output by 50% by 2050.
This ignores diverse well publicized contra-indicators :
eg.: Hansen, the renowned US climate scientist, points out that to avoid accelerating the feedbacks out of control, we need to reduce airborne carbon to between 300 and 350 ppmv from its present 384 ppmv, as opposed to allowing it to rise to 450 ppmv as would reportedly give “an even chance of staying under the 2 degrees ceiling”.
eg.: In the early ‘90s the IPCC advised the UN.FCCC that to halt any further increase of airborne GHGs’ concentration, we’ll need to cut global emissions by over 60%. This advice has since been refined to: 60% to 80% .
Which means that the DCP’s “50% cut by 2050” is merely a proposal to reduce the global rate at which we are adding to the problem of excess airborne GHGs, and to take 42 years doing so. It would radically exceed the 2 degrees ceiling requirement.
By contrast, Blair & FOE’s 60% and the Pres. candidates’ 80% would get as far as halting additions to the problem in 42 years time, but only if the feedbacks magically switch off tonight.
In the real world, India, which recently joined Africa and the EU Parliament in declaring for Contraction and Convergence, has now set a blunt public challenge for the West – that it will keep its own per capita GHG emissions below the average of industrialized nations. Given that its people emit around one tenth of western peoples’ per-capita volumes, and its energy usage is rising fast, this makes the West’s dalliance with the far-too-little far-too-late 2050 targets both scientifically and diplomatically bankrupt.
The real prospect is that the West, to win Developing nations’ co-operation in getting a reliable treaty, is going to commit to buying GHG emissions entitlements from those nations with surpluses due to their large populations with low per capita emissions.
The revenues so earned need to be ring-fenced to accredited mitigation-projects if the system-outcomes are to be optimized
(the provision of assistance with adaption-projects is evidently a justice issue in its own right)
and while the provision of traded entitlement will usefully allow industrialized nations to progress out of fossil fuel dependence far faster than would otherwise be the case, that ring-fencing of vendor-nations’ revenues will, critically, help them to avoid any further increase in FF dependence.
However, those purchased entitlements will need to be paid for, and the sole logical and reliable source of sufficient funds is from the value of the GHG pollution permits traded within nations under (what should be called) “Cap, Allocate & Trade” schemes. This unavoidable dynamic has yet to be discussed on any US media that I’ve seen, and is surely of central future relevance for North American cities.
Hoping that there may be more to the DCP setup than I’ve found so far
(not least as regards the member-cities’ interaction with the countryside on which they depend fundamentally),
regards,
Backstop
Hi Backstop,
There is a global warming vs peak oil slide show and talk on this page:
http://dynamiccities.squarespace.com/dcp-slideshows-publications/
I agree, the targets have fallen behind current science, but those targets have been shrinking quite a bit. (we are in deeper trouble that we imagined just a few years back). But I think his main points are that the two camps need to work together. Solving peak oil by coal to liquids is a disaster. And trying to solve global warming by switching from coal generated power to NG (soon to run out in North America) is a dead end and we don't have time for more dead ends. Bio fuels have a similar problem.
I have to admit I don't know much about GHG mitigation plans that currently exist. Do you know of a technically feasible plan to reach 80% reduction by 2050?
Thanks for the commentary regarding the evolving nature of climate targets. The intent of the analysis isn't to argue for any one global target, but rather to lay out a methodology for arriving at (and communicating) appropriate local targets relative to whatever the consensus is for global reductions.
In this case the general algorithm is:
1. Assume a global target for emissions reductions
(a political consensus target in contrast, perhaps, to what the evolving science might actually be calling for - as noted by Backstop)
2. Assume a relative share for the wealthier+higher emitting nations vs. poorer and lower emitting
(again the 4 tiers are arbitrary, and are used as an analytical tool vs. being a proposal for policy)
3. Assume a relative share for leading cities vs. other parts of a nation that are likely to lag
(again arbitrary, but with an assumption that cities have the infrastructure, capital, knowledge etc. to be leaders when compared to rural and suburban areas)
The result? If you want to get to a global-average target of 50% by 2050, then leading cities like Vancouver should probably be targeting 80-90% reductions for the same time period. Independent of where the science is, we believe that these targets are close to what will be politically enacted over the next decade - and will manifest as fiscal policy (just as the the BC Carbon Tax was announced today).
Again, if the global target is more aggressive, then the local target should update as well.
The point? To create an emissions reduction path that can be compared/contrasted with oil depletion scenarios to see which might end up being the greater driver for change.
As a general strategy, Dynamic Cities aims to use scenarios, which bundle multiple sets of assumptions together, vs. arguing at length about any one assumption (TOD is much better at that!). We've found this approach to be very helpful when engaging a broader range of stakeholders as it allows for a dialogue that can bypass some of the technical and ideological barriers which often get in the way of discussing the most important aspects of 'energy transition'.
Thanks
Bryn Davidson
www.dynamiccities.org
ps
We're currently an all volunteer group of architects, planners etc. whose day jobs sometimes interfere with our peak oil / climate hobbies (!) We're working towards getting the funding to flesh out the framework and content, but the effort has been challenging over the last several years due to a general lack of depletion literacy on the part of funding bodies. To those ends, anyone interested in contributing, or providing leads to funding sources please contact us. bd