A long journey
It has taken me about a year-and-a-half to get here.
The foundations for this work started in the winter of 2012 with my series, Inter-Regional Trade Movements of Petroleum. A little-discussed portion of the annual BP reviews “Statistical Review of World Energy” contained data that allowed me to analyze what kind of trends existed in petroleum exports to and from nine different regions of the world over the past decade. I even animated the results of the series in two short videos (Part 1 and Part 2), but, at total views of less than 300 after one year, I can see that this was not a very effective communication form.
After finishing my analysis of trade movement trends, in the series, Relationship between Petroleum Exports and Production I quantified the relationship between domestic production and the inter-regional exports for each of the nine regions.
With these relationships in hand, I spent the last half of 2012 to January 2013 working on the series, Predicting Global and Regional Petroleum Consumption Trends where I introduced and applied my PIE analysis. The PIE analysis concept is simple. Petroleum consumption for each region is given by Production + Imports – Exports. If one can predict the domestic production rate, import rate and export rate trends, then these data can be used in the PIE relationship to predict the petroleum consumption rate trend. As shown in that series, this approach can give quite a different prediction of what the future consumption rate might look like, as compared to a simple extrapolation of the existing consumption rate trend.
Finally, with the predicted petroleum consumption rate trends from my PIE analysis in hand, in the present series, I looked at the economic and population implications for each region out to 2065. Again, the concept behind the present series was simple. Project the population of each region out to 2065 (I used the US Census Bureau International Database as my starting point), extrapolate the predicted consumption rate for each region out 2065, and then, calculate the per capita consumption rate, expressed as barrels per person per year (b/py).
Part 1 provides the basis for my assumptions that economic growth will correlate with the size and direction of changes in per capita consumption, and, that once a region’s per capita consumption rate drops below a certain value, 1 b/py, the petroleum driven food production system fails and the population will start to decline proportionally. I assumed that the maximum population fall is to pre-petroleum era population level of circa 1900. And finally, I assessed how the predicted economic and population trends might be altered if the different regions were to mitigate their petroleum exports.
Who is vulnerable economically?
Over the longer term of the study period, all nine regions are vulnerable to economic declines because worldwide petroleum production rates are predicted to decline over the study period. Even more rapidly declining, however are export rates, which of course, make the net importing regions (NA, EU, JP, CH, rAP) more vulnerable to declines in per capita consumption with concurrent economic declines.
However, within the overall trend for declining exports there is another trend for exports being shifted anyway from NA, EU and JP and towards rAP and CH (see e.g., Figure 50 of Part 10 of Predicting Petroleum Consumption). This has a greater negative impact on JP and EU than NA, because the former two regions have virtually no (JP) or rapidly declining domestic production (EU).
Shifting exports to rAP and CH has allowed these two regions to sustain an increase in per capita conception, with concurrent economic growth over the past decade, but, total exports to these region are about to top out. Per capita petroleum conception in CH is predicted to increase for a few more years, but not for rAP. The combination of declining exports, declining domestic production and increasing population all contribute to a predicted decline in per capita consumption for rAP.
Of the four net exporting regions (ME, FS, AF and SA), the present consumption rate trends for FS and AF look rather grim. Both of these regions appear to be at or slightly past peak production and they are both on a trend of increasing exports as a proportion of their production. If this trend continued it would drive the domestic consumption rates for FS and AF into the ground by the mid- to later 2020s.
Export mitigation might help FS and AF delay an inevitable decline in consumption but this is to the detriment of the net importer regions especially EU, JP CH, and rAP. Moreover, mid-stage export mitigation (i.e., export mitigation when per capita consumption drops to 2 b/py) actually hurts AF because its small, but important inter-regional imports from EU and rAP are lost.
Who is vulnerable to a population crash?
The short-term answer is: 1) those regions that are right at the 1 b/py threshold for petroleum-dependent food production system failure (i.e., AF); 2) those regions whose population is growing at a rate that outstrips its potential to increase domestic petroleum production (i.e., AF and rAP); and 3) those regions that are highly dependent on inter-regional petroleum imports (i.e., JP, EU and rAP). An “honorable” mention goes to FS which as I mentioned above is on track to have a population crash, unless it engages in export mitigation to delay or eliminate the crash.
The long-term answer is that all nine regions are vulnerable to population declines because worldwide petroleum production rates are predicted to decline, and, I think that it is unlikely that a population of 7 billion or even 6, ...., 2 billion could be fed in the absence of petroleum to facilitate food production.
Even if all the regions were to equally share the remaining predicted world-wide petroleum production (causing huge economic crashes in NA, EU and JP), I still expect that the global population will break away from the
census bureau’s continuing projected population increase. The break would occur in the mid-2050s, when the per capita consumption petroleum consumption drops below 1 b/py. US
The regional per capita consumption profiles from the PIE analysis suggest that AF is in jeopardy of mass starvation and a population decline about now, and, FS absence export mitigation would follow soon afterwards in the 2020s, with rAP, JP and EU having population crashes in the mid-2030s.
Mid- or late-stage export mitigation delays the population crashes in AF to the early 2020s, and into the 2040s for FS, but then the population decline in rAP, JP and EU occurs sooner in the 2030s and the population declines are steeper for these regions.
Early-stage global export mitigation would cause an immediate population crash in JP. In one version of early-stage mitigation, rAP’s population also crashes immediately while in another version, the population crash is delayed to the mid 2020s. In one version of early-stage mitigation, AF’s and EU’s populations crash in the late 2020s while in another version the crash is in the early 2020s.
I would be amazed if the per capita petroleum consumption curves and population declines for each region were to all exactly follow the curves predicted in this study according just a single one of the several scenarios discussed in Part 8 or Part 9.
Rather, some regions will probably follow one type of scenario while other regions follows a different scenario. There could be several such hybrid scenarios that are all plausible, and it is hard to imagine what the individual regional decline curves would look like.
Still, I would be even more amazed if per capita petroleum consumption just stayed at present levels or increased going forwards, and, the world population would continued to grow to 9.7 billion by 2065, based on the US census bureau numbers discussed in Part 8.
My best estimate is that, absent a major war (which may be represented by the early-stage mitigation scenario) or some form of world government (which may be represented by total sharing scenario) we will see a hybrid scenario ranging from the primary PIE analysis scenario to mid-stage export mitigation, with late-stage mitigation being my favored scenario.
Considering some questions about this analysis
I find it interesting when I get comments along the lines of:
Why doesn’t your scenario consider the interactions between peak oil, and financial crisis, climate change, soil erosion, fresh water depletions, the effects of the Fukushima Daiichi nuclear disaster etc....
You haven’t considered how much more petroleum can be produced from coal, algae, the tar sands, shale, the arctic ocean etc....
After having spent over a year on this analysis, my reaction is typically, oh sure, let me get back you in a few minutes or so, and, by the way, please provide all the data I need for such an analysis. And, if you could also provide a staff of dozen or so people, that would be just great.
But, I realize that people hear about all sorts of other problems that could be a limit to economic and population growth, and, at the same time, hear about how there will be plenty of petroleum to feed future growth, including population growth 10 billion.
Here’s a general response to such comments, in particular, a comment on what this analysis does, and, what it doesn’t do.
The first thing to understand is that this a top-down type of trend analysis. That is, for each region, I looked at recent petroleum production rate trends, by fitting the logistic (Hubbert) equation to the recent data, and by analyzing the recent interregional import and export trend using a linear regression fit. Then I extrapolate these trends into the future.
This is in contrast to, and much easier than, trying to do a bottom-up type of analysis, where one might try and guess what all present and potential sources of petroleum may generate in the future and then add these all up. While this might give you an alternative estimate of production rates, it seems that you would still then have to look at the export and imports trends anyways to estimate regional consumption rates.
One nice thing about a trend analysis is that if any of the financial crisis, climate change, soil erosion, fresh water depletion etc... or new petroleum sources, are factors that have been having had an effect on the recent production, or the import and export trends, then their effects should show up as part of the trend.
One bad thing about a trend analysis is that if some very recent factor(s) have an affect on any of these trends, then a trend analysis will tend to dampen or average out this effect. For instance, if the real cost (i.e., something more than the nominal non-inflation adjusted price) that society was willing or able to pay for oil were to go up, then I imagine that one or both of the logistic equation parameters, a, and Qmax, corresponding to the yearly extraction rate constant and ultimately recoverable reserves, respectively, would also go up. But it might take some several years of a consistent trend before one might see a significant change in these parameters. Likewise, if energy return on energy invested into petroleum production is in decline then ultimately recoverable reserves and net-extraction rates might both go down. But again, it might take several years of a consistent trend before one might see a significant change in these parameters.
Here’s the gist of another line of comments:
Your assumption of a fall back to year-1900 population level may be incorrect. It is too low because the regional you are discussion still have significant non-petroleum dependent food production into the 1950s, 60s... Or, it is too high because the financial crisis, climate change, soil erosion, fresh water depletions, the effects of the Fukushima Daiichi nuclear disaster etc.... will cause a greater population die off.
Your assumption of starvation due to a lack of food production when per capita consumption drops below 1 b/py may be incorrect, because in the past, region XX with a per capita consumption of less than 1 b/py still had population growth.
I’m not sure why, but some people love to get caught up in the minutiae of exact numbers and dates. Maybe it is a defense mechanism—if this thing doesn’t happen on this exact date, as predicted, then the entire premise of the analysis if wrong, and therefore, I can ignore everything.
To me, it doesn’t really matter if a region’s population (e.g., rAP) falls back from a population of 3 billion, with petroleum, to a population of 0.5 billion versus 0.9 billion, without petroleum. Of greater interest for me, is the time range when each of the nine regions becomes vulnerable to starvation due to declining petroleum per capita.
However, to do this analysis, I needed fall back numbers for each region. I choose the year 1900 as my population fall back year because I was pretty sure that none of the regions substantially relied on petroleum for food production back in 1900, and, I could make estimates of the populations of each of my nine regions for the year 1900.
I could imagine different, maybe better, ways to estimate a post-petroleum population fall back value. Maybe it should be the year when the population working on farms dropped below some percentage. Or maybe, it should be the year when a certain number of farms transitioned to a mono-crop production system. The problem is, I would have to know what these numbers are for each one of the regions, and, finding these numbers would amount to a study unto itself.
Let's consider assumption of the per capita consumption of 1 b/py as being the limit for starvation and a population decline. Of course, every one of these regions likely had growing populations in the days before they started using petroleum to facilitate food production and distribution. However, it is petroleum that allowed a green revolution in food production, and with this, a sharp increase in the population growth rate. The mechanization of food production made possible by petroleum also shifted millions (billions?) of farm workers off of farms and into urban areas to find work. The remaining mechanized farms become larger and highly specialized, often growing only one type of crop which gets shipped 100s or 1000s of miles for processing and redistribution. The children or grand-children (or great-grand children in the west) of those farmers do not have the know-how to go back to the farm and start growing food the old-fashion non-petroleum dependent way. Usually there is no farm to go back to—it has been swallowed by ever-expanding urban sprawl or absorbed into a large factory farm. A rapid return to non-petroleum dependent traditional non-mechanized food production be fast enough to avoid mass starvation looks improbable to me.
Although I did spend quite bit time analyzing this in past series (see Part 9, and, The relationship between hunger and petroleum consumption-Part 1) it is likely that the 1 b/py limit varies from region to region. It wouldn’t surprise me if the limit for regions like NA, EU and JP are higher than 1 b/py or that the limit for regions like AF, rAP and CH are lower. If the limit is higher, then any population crash would occur sooner than predicted here, whereas if the limit is lower then any population crash would occur later. If the shift from 1 b/py is large enough, that could shift the year for reaching the critical limit by several years, in either direction.
Here’s one final line of comments:
This analysis is too long and is too hard read, and, I just want to know what is going to happen and what I should do.
Maybe this series gives you a view into the future, but you don’t like that I have clouded up that view by presenting several different plausible scenarios, and now you have to think about which one look most plausible. Maybe this, in turn, causes you to have some doubts about what you should do?
As I have remarked a few times on this blog, I have come to see this blog as much of an open log note book of my studies as a commentary. It is important to put down all of my assumptions and methods of analysis, as much for my future benefit, as the interested reader.
Perhaps, as a result, the writing style “sucks,” but then, I am not really trying to produce a piece of entertainment. I am well aware that this will make these posts unappealing to some readers.
Well, warts and all, this series is over!
If BP is still around, and still publishes its statistical review, and, if I am still around, then I will revisit this analysis in a few years time.
Possible lines of improvement in the future could include splitting rAP up into yet more separate regions. The most obvious splits would be
India and Australasia.
I hope that you were able to get some insights into how your particular region of the world might fare over the coming decades. Perhaps you will have a better understanding of why the decline happening around, and to, you seems never-ending.
I need to make some long overdue housekeeping clean ups to this blog site, and, after that, I’ll be back in the coming weeks and months with some "softer" posts, discussing de-growth, the post-doomerism era, and re-visit a few topics that I have wrote about in the past.