The era of gnashing teeth

6 02 2017

Since Trump’s election to the Oval Office, there has been an unbelievable amount of teeth gnashing going on all over the internet….. HOW could it possibly have come to this..?

To me, the answer is as clear as a bell. People all over the world can sense that everything ‘is turning to shit’, if you pardon my fluent French. The economies of the world are faltering (in real sense, not GDP money throughput), unemployment is high, manipulated to lower figures with creative accounting, the climate is falling apart causing food shortages in Europe, and the Middle East appears as a seething hot bed of war and terrorism.

The problem lies in the fact nobody knows why this is happening, because they have been conned for years by governments everywhere telling them everything is fine, we just have to ‘return to growth’.

Trump convinces enough Americans to vote for him so he can make America great again, because neither he nor his voters have the faintest idea America is actually on the cusp of collapse.

In France, Marine Le Pen wants to make France strong again……. and just like in America, this resonates with the electorate who now look like they may make her the country’s first woman President, and the first from the extreme right.

Here in Australia, we have a similar rise from the right, with Pauline Hanson and her one nation party making scary inroads into popularity rating. A recent article in the Sydney Morning Herald states:

In the aftermath of Mr Trump’s US election victory, where he strongly advocated reviving that nation’s manufacturing industry, nearly 83 per cent of surveyed Australian said they strongly agreed (42 per cent) or agreed (40.5 per cent) with the notion we are too reliant on foreign imports. Only 6 per cent disagreed.

Support for an expansion of Australia’s manufacturing sector was robust regardless of age, gender, income or locality.

This unsurprising finding comes from the Political Persona Project, a comprehensive attempt to profile different types of Australians based on their lifestyles, social values and politics. Fairfax Media in collaboration with the Australian National University and Netherlands-based political research enterprise Kieskompas conducted the project which revealed there are seven types of Australians, representing seven dominant patterns of thinking in Australian society.

Manufacturing has been declining since the 1970’s, which coincides with the USA’s Peak Oil, in case no one noticed….. then, one in four Australian workers were employed in the sector. This downturn has gathered pace in recent years with over 200,000 manufacturing jobs lost between 2008 and 2015. But no mention of dropping net energy, or an energy cliff. The manufacturing sector now accounts for only about one in 13 Australian workers. The decline means Australia is relying more on foreign producers to supply manufactured goods……… not to mention we have to import over 90% of our liquid fuel requirements, with likely no more than 3 or 4 years before this turns to 100%.

Underpinning the nostalgia for manufacturing was a strong feeling of having been left out of the new economy, said Carol Johnson, Professor of Politics and International Studies at the University of Adelaide.

Might this have anything to do with the fact that since the Thatcher/Reagan era, the economy was converted from an energy based one to a money based version…..?

“Manufacturing still matters to the economy and Australians know it,” he said.

“The public’s gut instinct is absolutely right.”

How much more wrong could they actually be……..?





Implications of declining EROI on oil production 2013 by David J. Murphy

21 06 2015

Quite technical but a good read if you are so inclined……..

Posted on by

Murphy, David J. December 2, 2013. The implications of the declining energy return on investment of oil production. Trans. R. Soc. A 2014 372

[This is a great paper on EROI, highly recommended. Without EROI studies, we risk building energy capturing contraptions that end up being useless, consuming more oil than generated, the Easter Island Heads of our former civilization. Alice Friedemann, energyskeptic.com]

Declining production from conventional oil resources has initiated a global transition to unconventional oil, such as tar sands. Unconventional oil is generally harder to extract than conventional oil and is expected to have a (much) lower energy return on (energy) investment (EROI). Recently, there has been a surge in publications estimating the EROI of a number of different sources of oil, and others relating EROI to long-term economic growth, profitability and oil prices. The following points seem clear from a review of the literature: (i) the EROI of global oil production is roughly 17 and declining, while that for the USA is 11 and declining; (ii) the EROI of ultra-deep- water oil and oil sands is below 10; (iii) the relation between the EROI and the price of oil is inverse and exponential; (iv) as EROI declines below 10, a point is reached when the relation between EROI and price becomes highly nonlinear; and (v) the minimum oil price needed to increase the oil supply in the near term is at levels consistent with levels that have induced past economic recessions. From these points, I conclude that, as the EROI of the average barrel of oil declines, long-term economic growth will become harder to achieve and come at an increasingly higher financial, energetic and environmental cost.

Introduction

Today’s oil industry is going through a fundamental change: conventional oil fields are being rapidly depleted and new production is being derived increasingly from unconventional sources, such as tar or oil sands and shale (or tight) oil. Indeed, much of the so-called ‘peak oil debate’ rests on whether or not these sources can be produced at rates comparable to the conventional mega-oil fields of yesterday.

What is less discussed is that the production of unconventional oil most likely has a (much) lower net energy yield than the production of conventional crude oil. Net energy is commonly defined as the difference between the energy acquired from some source and the energy used to obtain and deliver that energy, measured over a full life cycle (net energy=E(out)- E(in)). A related concept is the energy return on investment (EROI), defined as the ratio of the former to the latter (EROI=E(out)/E(in)). The ‘energy used to obtain energy’, E(in), may be measured in a number of different ways. For example, it may include both the energy used directly during the operation of the relevant energy system (e.g. the energy used for water injection in oil wells) as well as the energy used indirectly in various stages of its life cycle (e.g. the energy required to manufacture the oil rig). Owing to these differences, it is necessary to ensure that the EROI estimates have been derived using similar boundaries, i.e. using the same level of specificity for Ein. Murphy et al. [1] suggested a framework for categorizing various EROI estimates, and, where applicable, I will follow this framework in this paper.

Estimates of EROI are important because they provide a measure of the relative ‘efficiency’ of different energy sources and of the energy system as a whole [2,3]. Since it is this net energy that is important for long-term economic growth [3–6], measuring and tracking the changes in EROI over time may allow us to assess the future growth potential of the global economy in ways that data on production and/or prices cannot.

Over the past few years, there has been a surge in research estimating the EROI of a number of different sources of oil, including global oil and gas [7], US oil and gas [8,9], Norwegian oil and gas [10], ultra-deep-water oil and gas [11]and oil shale[12]. In addition, there have been several publications relating EROI to long-term economic growth, firm profitability and oil prices [3, 13–15].

The main objective of this paper is to use this literature to explain the implications that declining EROI may have for long-term economic growth. Specifically, this paper: (i) provides a brief history of the development of EROI and net energy concepts in the academic literature, (ii) summarizes the most recent estimates of the EROI of oil resources, (iii) assesses the importance of EROI and net energy for economic growth and (iv) discusses the implications of these estimates for the future growth of the global economy.

(a) A brief history of energy return on investment

In the late 1960s, Charles Hall studied the energy flows within New Hope Creek, in North Carolina, USA, to understand the migration patterns of the fish within the stream. His conclusions [16] revealed that, by migrating, the fish were able to exploit new sources of food, which, after accounting for the additional energy cost of migration, conferred a large net energy gain upon the fish. In other words, owing to the abundance of food in the new locations, the fish were able to gain enough energy not only to ‘pay’ for the energy expenditure of that migration but also to grow and reproduce. Comparing the energy gained from migration to the energy expended in the migration process was ostensibly the first calculation of EROI.

In the autumn of 1973 the price of oil skyrocketed following the Arab oil embargo (the so-called ‘first oil shock’), which sent most OECD economies tumbling into recession. The apparent vulnerability of OECD nations to spikes in the price of oil led many researchers to focus on the interaction between the economy and energy. Then, in 1974, the journal Energy Policy dedicated a series of articles to the energy costs of production processes. The editor of this series, Peter Chapman, began the series with a paper titled ‘Energy costs: a review of methods’, and observed that ‘this subject is so new and undeveloped that there is no universally agreed label as yet’ [17], and followed up two years later with a second paper [18]. Today this area of research is spread among a number of different disciplines, including, but not limited to, ecological economics, industrial ecology and net energy analysis, and the EROI statistic is just one of many indicators calculated.

Also during this period researchers started using Leontief input–output tables as a way to measure the use of energy within the economy [19–22]. For example, Bullard & Herendeen [23] used a Leontief-type input–output matrix to calculate the energy intensity (in units of joules per dollar) of every major industrial sector of the US economy. Even today this paper serves as a useful model for other net energy analyses [8,24]. In addition, a workshop in Sweden in 1974 and one at Stanford, CA, in 1975 formalized the methodologies and conventions of energy analysis [25,26].

In 1974, the US Congress enacted specific legislation mandating that net energy be accounted for in energy projects. The Nuclear Energy Research and Development Act of 1974 (NERDA) included a provision stating that ‘the potential for production of net energy by the proposed technology at the stage of commercial application shall be analyzed and considered in evaluating proposals’. Further influential papers by the Colorado Energy Research Institute, Bullardet al.and Herendeen followed this requirement [27–29]. Unfortunately, the net energy provision within the NERDA was never adopted and was eventually dropped.

In 1979, the Iranian revolution led to a cessation of their oil exports (the second oil shock), which precipitated another spike in the price of oil and squeezed an already strained US economy. Responding to this, and in an attempt to control deficits and expenditure, President Reagan of the USA enacted Executive Order 12291 in 1980. This order mandated that ‘regulatory action shall not be undertaken unless the potential benefits to society from the regulation outweigh the potential costs to society’.

 

In other words, all US regulatory action had to show a net monetary benefit to US society, and the idea of measuring benefits in terms of net energy fell even further from the policy arena.

Net energy analysis remained insignificant in US energy policy debates until the dispute over corn ethanol emerged 25 years later [30,31].

Although the political emphasis had now shifted towards economic analysis, the 1980s still provided useful papers on net energy analysis (e.g. [32]). In 1981, Hall published ‘Energy return on investment for United States petroleum, coal, and uranium’, which marked the first time that the acronym EROI was published in the academic literature [33]. Later that year, Hall & Cleveland [34] published ‘Petroleum drilling and production in the United States: yield per effort and net energy analysis’. This paper analyzed the amount of energy being produced per foot drilled and found that the ratio had been declining steadily for 30 years. Further publications by Hall and colleagues then tested hypotheses relating economic growth to energy use, introduced explicitly the concept of energy return on investment and examined the EROI of most major sources of energy [35,36].

Following growing concern about environmental impacts, climate change and sustainability, documented in the Brundtland Report in 1987 [37], emphasis began to shift from energy analysis to greenhouse gas (GHG) emissions and life-cycle analysis. Life-cycle analysis (LCA) itself was born out of the process and input–output analyses codified in the aforementioned energy literature of the 1970s and 1980s, and can be used to calculate EROI and other net energy metrics. Beginning around the turn of the century, researchers began to recognize the complementarity between LCA and net energy and began publishing on the matter [38].

There was another surge in publications in net energy analysis in the 2000s, due mainly to a growing global interest in renewable energy, and therefore an interest in metrics that compare renewable energy technologies. The debate about whether or not corn ethanol has an EROI greater than one is a good example [30,31]. There has also been a number of studies using the input–output techniques developed in the 1970s to track emissions production and/or resource consumption across regions [39].

Today, research within the field of net energy analysis is expanding rapidly. The main renewable energy options, including, but not limited to, solar photovoltaics, concentrating solar, wind power and biofuels, have each been the focus of studies estimating their net energy yield [31,40,41].

Furthermore, with the expansion of oil production into ultra-deep water, tar sands and other unconventional sources, as well as developments with shale gas, there has been a renewed interest in whether or not these sources of energy have EROI ratios similar to conventional oil and gas, and publications are expected to be forthcoming .

Recent estimates of the energy return on (energy) investment for oil and gas production

There has been a recent resurgence in EROI studies for liquid fuels, beginning with Cleveland [ 8], who estimated the EROI for oil and gas extraction in the US, Gagnon et al. [7], who estimated the same EROI for the whole world, and a number of additional studies that were contained in a 2011 special issue of the journal Sustainability. This section reviews the findings of these papers. Unless otherwise noted, all of the oil EROIs reported here are equivalent to the standard EROI (EROIstnd), as reported in Murphy et al. [1], which means that both the indirect and direct costs of energy extraction are included in the EROI calculation, but costs further downstream, such as transportation and refinement, have been omitted.

Cleveland [ 8]estimated two values for the EROI of US oil and gas that differed in the method of aggregating different types of energy carrier. The first method used thermal-equivalent aggregation, i.e. volumes of natural gas and oil are combined in terms of their heat content in joules. The second method uses a Divisia index, developed by Berndt [42], and uses both energy prices and consumption levels to adjust for the ‘quality’ of each energy carrier. Quality corrections are often used in energy analysis to adjust for the varying economic productivity of different energy carriers—for example, since electricity is more valuable, in terms of potential economic productivity, than coal, it is given more weight in the aggregate measure [43]. Quality-corrected measures better reflect the ability of energy carriers to produce marketable goods and services, so are arguably more useful.

The EROI values calculated using the energy quality-corrected data for US oil and gas production are consistently lower than those calculated from the non-quality-corrected data. This reflects the fact that many of the inputs to production are high-quality (i.e. high-priced) energy carriers such as electricity and diesel, while the outputs are unprocessed crude oil and natural gas.

Nevertheless, both estimates show the same trend over time: namely, an increase until the early 1970s, a decline until the mid-1980s, a slight recovery until the mid-1990s, followed again by decline (figure 1).

According to Cleveland, the overall downward trend from the 1970s till the mid-1990s is the result of higher extraction costs due to the depletion of oil in the USA. The up and down fluctuations within this aggregate trend are likely to be linked to changes in oil prices influencing the rate of drilling in the USA, with higher prices encouraging more drilling in less promising areas, which in turn leads to a lower yield and a lower aggregate EROI. Gagnon et al. [7] estimated the EROI for global oil and gas from 1992 to 2006 using the same energy aggregation techniques as Cleveland [8], i.e. both thermal equivalence and Divisia indices. In both cases, the EROI at the wellhead was around 26 in 1992 and increased to 35 in 1999 before declining to 18 in 2006 (figure 1).

It is not surprising that the EROI for global oil and gas is higher than that for the USA considering that oil production peaked in the USA in 1970 due mainly to the depletion of its biggest oil fields, while global production continued to flow and even increase from the mega-oil fields of the Persian Gulf.

US producers are increasingly reliant upon smaller and poorer-quality fields in difficult locations (e.g. deep water) together with the enhanced recovery of oil from existing fields—all of which are relatively energy intensive. In contrast, most OPEC members are still producing oil from high-quality supergiant fields.

The first few years of the Gagnon dataset and the last few years of the Cleveland dataset overlap in the early 1990s and both show a general increasing trend. The results from Gagnon et al. [7] then show that the increase in the early 1990s reaches a maximum in 1999, followed by a monotonic decline through the 2000s. Much like the Cleveland paper, Gagnon et al. assume that the decline is due to the depletion of easy access resources, but, as mentioned earlier, this trend also could be dependent on the trend in oil prices.

In addition to the estimates of Cleveland [ 8] and Gagnon et al. [7], Guilford et al. [9] estimated the non-quality-corrected EROI of conventional oil and gas production for the USA. They found that the EROI of oil production has declined from a peak of 24 in the 1950s to roughly 11 in 2007 (figure 1). By deriving separate estimates for exploration and production, they show how depletion reduces the rate of production from existing fields and gives incentives for increased exploration for new fields, both of which lower the aggregate EROI. They also suggest that natural gas is subsidizing oil production and that the EROI for oil alone is likely to be much lower.

Figure 1. EROI estimates from three sources, Gagnon et al. [7], Cleveland [8] and Guilford et al. [9]. The Gagnon et al. [7] data represent estimates of the EROI for global oil and gas production using aggregation by Divisia indices. The Cleveland [8] data represent the trend in EROI values for US oil and gas production calculated using the Divisia indices to aggregate energy units. The Guilford et al. [9] data represent estimates of the EROI of US oil production from 1919 to 2007

Despite differences in coverage and approach, the results from these three studies are broadly consistent, namely a general increase in EROI until 1970, then a general decline until the early 1980s, an increase through the mid-1990s and then a decline.

Grandell et al. [10] estimated the EROI of oil production from Norwegian oilfields to be roughly 20 in

  1. They also note that as the fields deplete they expect the EROI to decline further. Brandt [44] estimatedthattheEROIfromCalifornianoilfieldshasdeclinedfromover50 in the 1950s to under 10 by the mid-2000s. Similarly, Hu et al. [45] estimated that the EROI from the Daqing oil field, the biggest oil field in China, had declined from 10 in 2001 to 6.5 by 2009.

Two other recent EROI estimates of particular importance are those of Moerschbaecher & Day [11], who estimated the EROI of ultra-deep-water (depths greater than 1524 m or 5000 feet) production in the Gulf of Mexico, and Cleveland & O’Connor [12], who estimated the EROI of oil shale production.

Moerschbaecher & Day [11] estimated the EROI for deep-water oil production to be between 7 and 22. The range in EROI values is due to a sensitivity analysis performed by the authors that incorporated three different energy intensity values as proxies for the energy intensity of the ultra-deep-water oil industry. They also noted that, owing to the large infrastructure requirements of the deep-water oil industry, the real value is probably closer to the lower end of the range presented.

Cleveland & O’Connor [12] estimated that the EROI for oil shale production using either surface retorting or in situ methods was roughly 1.5, much lower than for other unconventional resources. Oil shale is the production of oil from kerogen found in sedimentary rock and is distinct from ‘shale oil’ or, preferably, ‘tight oil’, which is oil trapped in shale or other impermeable rock. Oil shale is discussed here because the western USA has vast resources of oil shale, but production costs are much higher than for other forms of unconventional oil [46].

The following summarizes the aforementioned studies:

  • EROI 11: average for US oil production today, down from roughly 20 in the early 1970s
  • EROI 17: global average, down from EROI of roughly 30 in 2000
  • EROI 10: ultra-deep-water oil production is probably less than 10
  • EROI 1.5: Oil shale (kerogen), not tight oil (aka ‘shale’ oil)

Energy return on (energy) investment, oil prices, and economic growth

The economic crash of 2008 occurred during the same month that oil prices peaked at an all-time high of $147 per barrel, leading to numerous studies that suggested a causal link between the two [47,48]. In addition, other researchers involved in net energy analysis began examining how EROI relates to both the price of oil and economic growth [3,13,15,49–51].

Murphy & Hall [3] examined the relation between EROI, oil price and economic growth over the past 40 years and found that economic growth occurred during periods that combined low oil prices with an increasing oil supply. They also found that high oil prices led to an increase in energy expenditures as a share of GDP, which has led historically to recessions. Lastly, they found that oil prices and EROI are inversely related (figure 2), which implies that increasing the oil supply by exploiting unconventional and hence lower EROI sources of oil would require high oil prices. This created what Murphy & Hall called the ‘economic growth paradox: increasing the oil supply to support economic growth will require high oil prices that will undermine that economic growth’.

Other researchers have come to similar conclusions to those of Murphy & Hall, most notably economist

James Hamilton [47]. Recently, Kopits [50], and later Nelder & Macdonald [49], reiterated the importance of the relation between oil prices and economic growth in what they describe as a ‘narrow ledge’ of oil prices. This is the idea that the range, or ledge, of oil prices that are profitable for oil producers but not so high as to hinder economic growth is narrowing as newer oil resources require high oil prices for development, and as economies begin to contract due largely to the effects of prolonged periods of high oil prices. In other words, it is becoming increasingly difficult for the oil industry to increase supply at low prices, since most of the new oil being brought online has a low EROI. Therefore, if we can only increase oil supply through low EROI resources, then oil prices must apparently rise to meet the cost, thus restraining economic growth.

Skrebowski [51]provides another interpretation of the relation between oil prices and economic growth in what he calls the ‘effective incremental oil supply cost. It should be noted there are wide divergences in estimates of oil development costs depending on what is included and the treatment of financial costs, profits and overheads. Those used here are estimates of the prices needed to justify a new, large development.’

According to data provided by Skrebowski, developing new unconventional oil production in Canada (i.e. tar sands) requires an oil price between $70 and $90 per barrel. Skrebowski also indicates that new production from ultra-deep-water areas requires prices between $70 and $80 per barrel. In other words, to increase oil production over the next few years from such resources will require oil prices above at least $70 per barrel. These oil prices may seem normal today considering that the market price for reference crude West-Texas Intermediate ranged from $78 to $110 per barrel in 2012 alone, but we should remember that the average oil price during periods of economic growth over the past 40 years was under $40 per barrel, and the average price during economic recessions was under $60 per barrel (dollar values inflation adjusted to 2010) [3]. What these data indicate is that the floor price at which we could increase oil production in the short term would require, at a minimum, prices that are correlated historically with economic recessions.

Heun & de Wit [15] found indicates that the price of oil increases exponentially as EROI declines [equation and explanation snipped, see pdf]. They suggest that the nature of the relation between EROI and the price is such that the effect on price becomes highly nonlinear as EROI declines below 10.

Figure 2. Relationship between oil prices and EROI. (Adapted from Murphy & Hall [3].)

King & Hall [13] examined the relation between EROI, oil prices and the potential profitability of oil-producing firms, termed energy-producing entities (EPEs). They found that for an EPE to receive a 10% financial rate of return from an energy extraction process, which, for example, has an EROI of 11, would require an oil price of roughly $20 per barrel.3 Alternatively, a 100% financial rate of return for the same extraction project would require $60 per barrel (figure 3). King & Hall also echoed Heun & de Wit, suggesting that the relationship between EROI and profitability becomes nonlinear when the EROI declines below 10.

The pertinent results from the literature summarized in this subsection are as follows:

  • there appears to be a negative exponential relationship between the aggregate EROI of oil production and oil prices;
  • there appears to be a comparable relationship between EROI and the potential profitability of oil-producing firms;
  • the relationship between EROI and profitability appears to become nonlinear as the EROI declines below 10;
  • the minimum oil price needed to increase global oil supply in the near-term is comparable to that which has triggered economic recessions in the past.

Understanding the relationship between energy return on (energy) investment and net energy

The mathematical relation between EROI, net energy and gross energy can be used to explain why, at around an EROI of 10, the relation between EROI and most other variables, such as price, economic growth and profitability, becomes nonlinear. The following equation describes the relation between EROI, gross and net energy [3]:

Equation 3.2 net energy = gross energy (1 – 1/ EROI)

Figure 3. Oil price as a function of EROI. The lines on the figure correspond to various rates of monetary return on investment (MROI). (Adapted from King & Hall [13].)

Using this equation, we can estimate the net energy provided to society from a particular energy source or (rearranging) the amount of gross energy required to provide a certain amount of net energy [52].

We can interpret equation (3.2) as follows:

  • an EROI of 10 delivers to society 90% (1 – .2 = 90%) of the gross energy extracted as net energy
  • an EROI of 5 will deliver to society 80% (1 – .2 = 80%)
  • an EROI of 2 will deliver only 50% (1 – .5 = 50%).

This exponential relation between gross and net energy means that there is little difference in the net energy provided to society by an energy source with an EROI above 10, whether it is 11 or 100, but a very large difference in the net energy provided to society by an energy source with an EROI of 10 and one with an EROI of 5. This exponential relation between gross and net energy flows has been called the ‘net energy cliff’ [53]and it is the main reason why there is a critical point in the relation between EROI and price at an EROI of about 10 (figure 4).

Figure 4. The 'net energy cliff' graph, showing the relation between net energy and EROI. As EROI declines, the net energy as a percentage of total energy extracted declines exponentially. Note that the x-axis is in reverse order. (Adapted from Mearns [53].)

Calculating the minimum energy return on (energy) investment at the point of energy acquisition for a sustainable society

‘The true value of energy to society is the net energy, which is that after the energy costs of getting and concentrating that energy are subtracted.’ H. T. Odum [6]

According to equation (3.2), as EROI declines, the net energy provided to society declines as well, and, at some point, the amount of net energy will be insufficient to meet existing demand.

The point at which the EROI provides just enough net energy to society to sustain current activity represents the minimum EROI for a sustainable society.

But estimating empirically the actual minimum EROI for society is challenging. Hall et al. [24] estimated that the minimum EROI required to sustain the vehicle transportation system of the USA was 3. Since their calculation included only the energy costs of maintaining the transportation system, it is reasonable to expect that the minimum EROI for society as a whole could be much higher.

Exploring the minimum EROI for a sustainable society is beyond the scope of this paper. Instead, I will examine how, in theory, the minimum EROI could be calculated by using some simple models. I will first do this by examining how the idea of net energy grew from analyzing the energy budgets of organisms.

The energy that an organism acquires from its food is its gross energy intake. Let us assume, for simplicity’s sake, that an organism consumed 10 units of gross energy, but to access this food it expended 5 units of energy. Given these parameters, the EROI is 2 (=10/5) and the net energy is 5. It is important to note that the expended energy created an energy deficit (5 units) that must be repaid from the gross energy intake (10 units) before any growth, for example, in the form of building fat reserves or reproduction, can take place.

An economy also must have an influx of net energy to grow. Let us assume that Economy A produces 10,000 units of energy at an EROI of 10, which means that the energy cost of acquisition is 1,000 units and the net energy is 9,000. Like organisms, economies also have energy requirements that must be met before any investments in growth can be made. Indeed, researchers are now measuring the ‘metabolism of society’ by mapping energy consumption and flow patterns over time [54]. For example, economies must invest energy simply to maintain transportation and building infrastructure, to provide food and security, as well as to provide energy for direct consumption in transportation vehicles, households and business, etc. The energy flow to society must first pay all of these metabolic energy costs before enabling growth, such as constructing new buildings, roads, etc.

Building off this idea of societal metabolism, we can gain additional insight into the relationship between EROI and economic growth by differentiating between 3 main uses of energy by society:

  1. Metabolism, which could be described as the energy and material costs associated with the maintenance and replacement of populations and capital depreciation (examples include food consumption, bridge repair or doctor visits)
  2. Consumption: the expenditure of energy that does not increase populations or capital accumulation and is not necessary for metabolism (examples include purchasing movie tickets or plane tickets for vacation; in general, items purchased with disposable income)
  3. Growth, the investment of energy and materials in new populations and capital over and above that necessary for metabolism (examples include building new houses, purchasing new cars, increasing populations).

Figure 5. (a-d) Flow diagrams relating net energy, EROI and gross energy production for a hypothetical Economy A. Each diagram describes the energy flows according to a different EROI, where the EROI is (a) 10, (b) 5, (c) 2 and (d) 1.5

Figure 5 (a-d) illustrates how the flows of energy to the three categories change as EROI declines. Let us assume that the metabolism of Economy A requires the consumption of 5000 units of energy per year. So, of the 10,000 units of energy extracted, 1,000 must be reinvested to produce the next 10,000, and another 5,000 are invested to maintain the infrastructure of Economy A. This leaves 4,000 units of net energy that could be invested in either consumption or growth (figure 5a).

As society transitions to lower EROI energy sources, a portion of net energy that was historically used for consumption and/or growth will be transferred to the energy extraction sector. This transfer decreases the growth and consumption potential of the economy. For example, let us assume that, as energy extraction becomes more difficult in Economy A, it requires an additional 1,000 units of energy (2,000 total) to maintain its current production of gross energy, decreasing the EROI from 10 to 5 and the net energy from 9,000 to 8,000. If the metabolism of the economy remains at 5,000 units of energy, Economy A now has only 3,000 units of energy to invest in growth and/or consumption (figure 5b).

If the EROI for society were to decline to 2, the amount of energy that could previously be invested in growth and consumption would be transferred completely to the energy extraction sector. Thus, given the assumed metabolic needs of Economy A in this example, an EROI of 2 would be the minimum EROI needed to provide enough energy to pay for the current infrastructure requirements of Economy A, or, to put it another way, an EROI of 2 would be the minimum EROI for a sustainable Economy A. If the EROI were to decline below 2, for example in some biofuel systems [31], then the net energy provided to society would not be enough to maintain the infrastructure of Economy A, resulting in physical degradation and economic contraction (figure 5d).

There are a few caveats to this discussion of the minimum EROI that need to be addressed. First, it is important to remember that this is a simple example with hypothetical numbers, and, as such, the minimum EROI for our current society is probably, and maybe substantially, higher. Second, over time, efficiency improvements within the economy can mitigate the impact that lower EROI resources have on economic growth by increasing the utility of energy. That said, the exact relation between energy efficiency improvements and declining EROI is yet to be determined. Third, the model assumes that metabolic needs will be met first, then consumption and growth. This may not necessarily be the case.

It is quite possible that there could be growth at the expense of meeting metabolic needs. Likewise, we can consume at the expense of growth or metabolism. Either way, the net energy deficit that results from declining EROI will become apparent in one of the three sectors of energy use.

The gross energy requirement ratio

‘Now, here, you see, it takes all the running you can do, to keep in the same place.’ The Red Queen, in Through the looking-glass [55,p.15]

Another way to explore the impact that a decline in EROI can have on net energy flows to society is to consider the ‘gross energy requirement ratio’ (GERR). The GERR indicates the proportional increase or decrease in gross energy production that is required to maintain the net energy flow to society given a change in the EROI of the energy acquisition process. The GERR is calculated by dividing the gross energy requirement (GER) of the substitute energy source by the GER of the reference energy source.

The GER is the minimum amount of gross energy production required to produce one unit of net energy.

Both of these equations are outlined below [2]:

Equation 5.1 GER(X) = EROI(X) / EROI(X) – 1

Equation 5.2 GERR = GER(X) / GER(REF)

The GERR is most useful when examining how transitioning from high to low EROI energy sources will impact the net energy flow to society. For example, the average barrel of oil in the USA is produced at an EROI of roughly 11 [9]. Using equation (5.1), an EROI of 11 results in a GER of 1.1, i.e. 1.1 units of gross energy must be extracted to deliver 1 unit of net energy to society, with the 0.1 extra being the amount of energy required for the extraction process. For comparison, delivering one unit of net energy from an oil source with an EROI of 5 would require the extraction of 1.25 units of oil. If conventional oil at an EROI of 11 is our reference GER, and our substitute energy resource has an EROI of 5, then the GERR is 1.14. This GERR value indicates that, if society were to transition from an energy source with an EROI of 11 to one with an EROI of 5, then gross energy production would have to increase by 14% simply to maintain the same net energy flow to society. The net effect of declining EROI is to increase the GERR, requiring the extraction of larger quantities of gross energy simply to sustain the same net energy flow to society (figure 6).

Implications for the future of economic growth

The implication of these arguments is that, if we try to pursue growth by using sources of energy of lower EROI, perhaps by transitioning to unconventional fossil fuels, long-term economic growth will become harder to achieve and come at an increasingly higher financial, energetic and environmental cost.

Figure 6. The GERR as a function of declining EROI. In this example, the reference EROI was 11. As such, the GERR value associated with an EROI of 4 represents the proportional increase in gross energy required to deliver one unit of net energy if society transitioned from an energy source with an EROI of 11 to one with an EROI of 4.

Revolutionary technological advancement is really the only way in which unconventional oil can be produced with a high EROI, and thus enhance the prospects for long-term economic growth and reduce the associated financial, energetic and environmental costs. This technological advancement would have to increase the energy efficiency of unconventional oil extraction or allow for increased oil recovery from fields discovered already [56]. Alternatively, there could be massive substitution from oil to high EROI renewables such as wind or hydropower [57].

It is difficult to assess directly how much technological progress is being or will be made by an industry, but we can get a glimpse as to how the oil industry is faring by comparing how production is responding to effort. If new technological advancements, such as hydraulic fracturing and horizontal drilling, represent the types of revolutionary technological breakthroughs that are needed, then we should at least see production increasing relative to effort. The data, however, do not indicate that this is the case. From 1987 to 2000, when the US oil industry increased the number of rigs used to produce oil, there was, as expected, a corresponding increase in the amount of oil produced (figure 7 not shown, see paper). But from 2001 to 2012 the trend shows very little correlation between drilling effort and oil production.

Biofuels are the only currently available non-fossil substitute for oil that is being produced at any sizable scale, but factors such as economic cost, land-use requirements and competition with food production restrict their potential contribution (see [58]). Most importantly, the EROI of most large-scale biofuels5 is between 1 and 3 [30,31], which means that we would be substituting towards a fuel that is even less useful, from a net energy perspective, for long-term economic growth. Others claim that substituting towards renewable electricity is the key; for example, Jacobson & Delucchi [59] argue that wind and solar energy could power global society by 2030. Even if their analysis stands up to scrutiny (and some claim that it does not [60,61]), the high price of oil in the transition period may provide a significant constraint on economic growth. Without high levels of economic growth, the investment capital needed to build, install and operate renewable energy will be hard to acquire.

The other option is to construct coal-to-liquids (CTL) or gas-to-liquids (GTL) operations, but even these solutions have their own difficulties (see [62]). For example, both CTL and GTL operations represent an energy conversion process, not an energy extraction process, which, in terms of EROI, simply adds to the cost of producing the final fuel and lowers the overall EROI. CTL and/or GTL will most probably lead to a significant increase in GHG emissions [63]. For GTL, there is a narrow window of low gas prices and high oil prices in which the GTL process can remain profitable [63]. Achieving profitability is easier in a CTL operation because of cheap coal, but the future availability, quality and cost of that resource is also becoming uncertain [64]. And, again, it will most probably be decades until any sizable portion of global demand for oil is met from a series of GTL or CTL plants, and in the mean-time economies will still be struggling to grow in a high oil price, low oil EROI environment.

Lastly, increasing oil production from low EROI resources is expected to degrade the global environment at an accelerated rate, for two main reasons. First, on average, the environmental impact per unit of energy is larger for unconventional oil than for conventional oil. GHG emissions, for example, are somewhere between 15% and 60% higher for gasoline and diesel produced from tar sands when compared to that produced from conventional petroleum [65,66]. Similarly, the water used per unit of energy produced is also much higher for most low EROI sources of energy [67]. Second, declining EROI increases the GERR. As society switches to lower EROI resources, simply maintaining the flow of net energy to society will require a proportionally larger amount of gross energy extraction, thus increasing the environmental impact associated with that extraction. This evidence indicates that the environmental impacts of energy extraction are most probably related exponentially to EROI, mimicking the relation between EROI and price (figure 8). This relationship holds as long as the flow of net energy to society remains the same or even increases despite a decrease in EROI. The relationship weakens if, when met with lower EROI resources, we simply decrease our effort in energy acquisition, i.e. embrace conservation.

The ecology of societal succession

‘Energy fixed tends to be balanced by the energy cost of maintenance in the mature or “climax” ecosystem.’ E. P. Odum [68]

Societal succession from the beginning of the Industrial Revolution to today mimics ecosystem succession in important and illuminating ways. The early stages of ecosystem development are marked by rapid growth (figure 9a), where the energy fixed through photosynthesis (gross photosynthesis) is greater than the energy consumed through respiration, resulting in a gain of net energy in the ecosystem. This gain in net energy leads to the accumulation of biomass (the energy equivalent of biomass in the context of society is embodied energy). As Odum [68] observed, as succession occurs, the gross photosynthesis of the ecosystem tends to balance with respiration as the steady-state, or ‘climax’, successional stage is reached. In other words, in the climax stage, almost all of the energy fixed by the ecosystem is used in maintenance respiration by the biomass that has accumulated over the years.

The simple diagram of forest succession (figure 9a not shown)is reflected by societal succession (figure 9b not shown)since the beginning of the Industrial Revolution until today. Figure 9 shows how gross photosynthesis is equivalent to humanity’s gross energy production-i.e. the total biomass, coal, oil, natural gas, etc. produced each year. Forest respiration is the equivalent of societal metabolism-i.e. the energy and material costs associated with the maintenance and replacement of populations and capital depreciation. The accumulation of biomass is the equivalent of societal growth-i.e. investments in populations and infrastructure that will increase overall societal metabolism. Lastly, the net energy provided to society is that left after accounting for the metabolic needs of society (i.e. net energy = gross energy production – societal metabolism). Historically, we have simply found and produced more energy as the metabolism (i.e. energy demand) of society grew. Indeed, the exponential increase in global economic output over the past 200 years is highly correlated with the same exponential increase in energy consumption (figure 10).

The question is: can global society continue to produce enough energy to outpace the increased metabolic requirements of a growing, and now very large, built infrastructure? Answering this question for each energy source is clearly beyond the scope of this paper, but the answer for oil seems clear, as the production of conventional oil seems to have peaked in 2008 [71], and both unconventional oil and other feasible substitutes have a much lower EROI. Both of these factors are likely to place contractionary pressure on the global economy by decreasing the flow of net energy to society.

The main difference between society and nature, in terms of figure 9, is in the reason for the peak and initial decline in gross energy acquisition. In forests and other natural ecosystems, the amount of gross photosynthesis declines and reaches parity with respiration as the forces of competition and natural selection create a steady-state, or ‘climax’, ecosystem. These forces exist also for society, but they are in the form of declining EROI, geological depletion, environmental degradation, climate change, water pollution, air pollution, land-cover change and such, and all the other factors that are occurring today that make it harder and harder to produce energy easily. In the end, ecosystems are able to successfully transition from a growth-oriented structure to a steady state; it is unclear whether society will be able to do the same.

Figure 10. GDP as a function of energy consumption over the past 200 years. (Adapted from Kremmer [69] and Smil [70].)

Summary

The concept of energy return on investment (EROI) was born out of ecological research in the early 1970s, and has grown over the past 30 years into an area of study that bridges the disciplines of industrial ecology, economics, ecology, geography and geology, just to name a few. The most recent estimates indicate that the EROI of conventional oil is between 10 and 20 globally, with an average of 11 in the USA.

The future of oil production resides in unconventional oil, which has, on average, higher production costs (in terms of both money and energy) than conventional oil, and should prove in time to have a (much) lower EROI than conventional oil. Similar comments apply to other substitutes such as biofuels. The lack of peer-reviewed estimates of the EROI of such resources indicates a clear need for further investigation.

Transitioning to lower EROI energy sources has a number of implications for global society.

  1. It will reallocate energy that was previously destined for society towards the energy industry alone. This will, over the long run, lower the net energy available to society, creating significant headwinds for economic growth.
  2. Transitioning to lower EROI oil means that the price of oil will remain high compared to the past, which will also place contractionary pressure on the economy.
  3. As we try to increase oil supplies from unconventional sources, we will accelerate the resource acquisition rate, and therefore the degradation of our natural environment.

It is important to realize that the problems related to declining EROI are not easily solved. Renewable energy may indeed represent the future of energy development, but renewables are a long time off from displacing oil. Lastly, it seems apparent that the supply-side solutions (more oil, renewable energy, etc.) will not be sufficient to offset the impact that declining EROI has on economic growth. All of this evidence indicates that it is time to re-examine the pursuit of economic growth at all costs, and maybe examine how we can reduce demand for oil while trying to maintain and improve quality of life. A good summary of these problems is also given in Sorrell [72].

For society, we can either dictate our own energy future by enacting smart energy policies that recognize the clear and real limits to our own growth, or we can let those limits be dictated to us by the physical constraints of declining EROI. Either way, both the natural succession of ecosystems on Earth anddeclining EROI of oil production indicate that we should expect the economic growth rates of the next 100 years to look nothing like those of the last 100 years.

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Losing our Energy Slaves

12 03 2015

Just found this brilliant video that explains the energy cliff really well.  Share widely…..  if they don’t ‘get it’ after seeing this, they’re too stupid to bother with!





Peak fossil fuel won’t stop climate change – but it could help

26 02 2015

The Conversation

Peak fossil fuel means it’s unlikely the worst climate scenario will come to pass. Gary Ellem explains.


What happens to coal in China will play a big role in deciding which climate road we’re all on. Han Jun Zeng/Flickr, CC BY-SA

Fossil fuels are ultimately a finite resource – the definition of non-renewable energy. Burning of these fuels – coal, oil and gas – is the main driver of climate change. So could the peak of fossil fuels help mitigate warming?

The short answer is maybe … but perhaps not how you might think.

In a paper published this month in the journal Fuel, my colleagues and I suggest that limits to fossil fuel availability might take climate Armageddon off the table, although we will still need to keep some fossil fuels in the ground for the best chance of keeping warming below 2C.

But more importantly, the peak of Chinese coal use is changing the face of global alternative energy industry development, and is soon likely to impact on international positioning for a low-emissions future.

Now for the long answer.

Predicting climate change

Predicting future climate change is dogged by two fundamental uncertainties: the dosage of greenhouse gas that human civilisation will add to the atmosphere, and how Earth’s climate and feedback systems will respond to it.

In the absence of a crystal ball for the future of emissions, the Intergovernmental Panel on Climate Change (IPCC) has adopted a scenario-based approach which highlights four representative concentration pathways (or RCPs). These are named after how much extra heating they add to the earth (in watts per square metre).


The relationship between emissions, and temperature projections. IPCC
Click to enlarge

From these scenarios the IPCC has developed temperature scenarios. So the RCP2.6 scenario is expected to restrict climate change to below 2C, whereas RCP8.5 represents catastrophic climate change of around 4C by the end of this century, rising to perhaps 8C in the ensuing centuries.

Fossil fuels forecast

The key thing to note here is that the emissions scenarios are demand-focused scenarios that have been developed to reflect possibilities for potential fossil fuel consumption. They explore a range of scenarios that include increasing global population and living standards, as well as the possible impact of new alternative energy technologies and global emissions-reduction agreements.

Instead of examining demand scenarios for fossil fuels, our work has focused on supply constraints to future fossil fuel production. Our work is not a forecast of future fossil fuel production and consumption, but rather seeks to determine the upper bounds of the geological resource and how it might be brought to market using normal supply and demand interactions.

We developed three projections based on different estimates of these Ultimately Recoverable Resources (URR). URR is the proportion of total fossil fuel resources that can be viably extracted now, and in the future (this accounts for some resources that are technologically inaccessible now becoming extractable in the future). The low case used the most pessimistic literature resource availability estimates, whereas the high case used the most optimistic estimates.

We also included a “best guess” estimate by choosing country-level resource values that we considered most likely. We then compared the resulting emissions profiles for the three upper bounds to the published IPCC emissions scenarios, as shown in the figure below.


Our projections for fossil fuel supply (black) matched with emissions scenarios (colours). RCP8.5 is the worst, RCP2.6 the best. Gary Ellem
Click to enlarge

In comparison to the published emissions scenarios, we found that it was very unlikely that enough fossil fuels could be brought to market to deliver the RCP8.5 scenario and we would recommend that this be removed from the IPCC scenarios in future assessment reports.

Mining out the optimistic fossil fuel supply base could perhaps deliver the RCP6 scenario, however, our best guess limit to fossil fuel availability caps the upper limit of emissions exposure to the RCP4.5 scenario (roughly equivalent to a median estimate of 2C warming).

But even under the low resource availability scenario, it will be necessary to leave some fossil fuels untapped if we are to meet the conditions for the RCP2.6 scenario or lower (to have more than a 90% chance of avoiding 2C temperature rise).

To sum up, our supply side assessment suggests that even if the climate Armageddon of the RPC8.5 scenario were desirable, it is unlikely that enough new fossil fuel resources could be discovered in time and brought to market to deliver it. To be clear, there is still much to worry about with the RPC4.5 and RPC6 scenarios which are still possible at the limits of likely fossil fuel resources.

So a simple reflection on global fossil fuel limitation won’t save us … but nations don’t face peak fuels at the same time. A country-level analysis of peak fuels suggests the possibility of a very different future.

How China could shake the world

As part of our assessment we looked closely at the fossil fuel production projections for four countries including China, Canada, the United States and Australia. Of these, China is by far the most intriguing.

China has little in the way of oil and gas resources and so has established its remarkable industrial growth on exploiting its substantial coal resources. Our projections indicate that the rapid expansion in Chinese coal mining is rapidly depleting this resource, with Chinese peak coal imminent in the mid-2020s under even the high fossil fuel scenario, as seen in the projections below.


Various scenarios for China’s fossil fuel supply. Gary Ellem
Click to enlarge

China is well aware of this and is currently scrambling to cap coal consumption and develop alternative energy projects and industries. Its leaders understand that the alternative energy sector is really an advanced manufacturing sector, and have moved to position themselves strategically as the world leader in solar, wind, hydro, battery and nuclear technology construction and manufacturing.

As fossil fuels start to fail China as a path to economic and energy security, China will join other regions in a similar position, such as the European Union nations, which have largely depleted their fossil fuel reserves.

For these nations focused on alternative energy investment for energy and economic security, global action on climate change is strategically aligned with their industrial strength. We can therefore expect them to pressure for increasing global action as a method of improving their strategic global trading position. We may see the beginnings of this transition at this year’s international climate talks in Paris this year, but it will take a few more years for the Chinese shift to play out as they exploit the remainder of their coal resource and gain confidence in the ability of their alternative energy sector to scale.

The question then becomes “can the USA manufacturing sector afford to be out of these global alternative energy markets?”. Our guess is “no” and a global tipping point will have been reached in the alternative energy switch.

This is perhaps the most profound way that peak fuels may contribute to a low-emissions future.





Looks like Guy McPherson was seriously wrong….

12 04 2014

After debating with Dave Kimble for several months over the issue of whether we are at a tipping point, it appears he may have been right all along:  there’s no way we are even going to reach +2ºC above 1990 temperatures.  Looks like McPherson’s forecasts of Near Term Human Extinction was highly overcooked……  Why do I say this?  Read on…….

dkimble

Dave Kimble

The IPCC detailed report is out and, as Dave predicted, the temperature response for RCP2.6 is +1.5°C, range 1.1 – 1.8 by 2045.  Thereafter they show the temperature remaining constant or microscopically getting slightly lower –  in the modelling I’ve seen, it was measurably getting lower by 2100.

So no “tipping point” according to IPCC, not even for the highest scenario, RCP8.5.

Gail Tverberg

Gail Tverberg

Gail Tverberg’s latest article is a game changer in my opinion.  It completely agrees with Dave:

 

 

The Likely Effect of Oil Limits

The likely effect of oil limits–one way or the other–is to bring down the economy, and because of this bring an end to pretty much all carbon emissions (not just oil) very quickly. There are several ways this could happen:

  • High oil prices – we saw what these could do in 2008.  They nearly sank the financial system. If they return, central banks have already done most of what they can to “fix” the situation. They are likely to be short of ammunition the next time around.

  • Low oil prices – this is the current problem. Oil companies are cutting back on new expenditures because they cannot make money on a cash flow basis on shale plays and on other new oil drilling. Oil companies can’t just keep adding debt, so they are doing less investment. I talked about this in Beginning of the End? Oil Companies Cut Back on Spending. Less oil means either a rebound in prices or not enough oil produced to go around. Either way, we are likely to see massive recession and falling world GDP.

  • Huge credit problems, such as happened in 2008, only worse. Oil drilling would stop within a few years, because oil prices would drop too low, and stay too low, without lots of credit to prop up prices of commodities of all types.

  • Rapidly rising interest rates, as QE reaches its limits. (QE for the United States was put in place at the time of the 2008 crisis, and has been continued since then.) Rising interest rates lead to higher needed tax rates and high monthly payments for homes and cars. The current QE-induced bubble in stock, land, and home prices is also likely to break, sending prices down again.

  • End of globalization, as countries form new alliances, such as Russia-China-Iran. The US is making false claims that we can get along without some parts of the world, because we have so much natural gas and oil. This is nonsense. Once groups of countries start pulling in opposite directions, the countries that have been using a disproportionate share of oil (particularly Europe, the United States, and Japan) will find themselves in deep trouble.

  • Electric grid failures, because subsidies for renewables leave companies that sell fossil-fuel powered electricity with too little profit. The current payment system for renewables needs to be fixed to be fair to companies that generate electricity using fossil fuels. We cannot operate our economy on renewables alone, in part, because the quantity is far too small. Creation of new renewables and maintenance of such renewables is also fossil fuel dependent.

Given the choice between economic collapse and runaway climate change, collapse is the pick.  Collapse, however, brings surprising results according to Gail.  Have a look at this chart of hers showing Peak ALL energy happening next year:

tverberg-estimate-of-future-energy-productionSee that pale blue strip at the top?  It’s energy produced by renewables.  By 2035, it is half the height of what it is today.  And the purple nuclear strip is maybe no more than a quarter of today’s…….  ALL high tech ‘solutions’ require complex systems driven by cheap and abundant fossil fuels.  And the demise of cheap and abundant fossil fuels is exactly what will bring all this complexity to its knees…..  If you want energy security for yourself using renewables, I urge you to waste no time, do it now…  Gail further states:

The IPCC’s Message Isn’t Really Right 

We are bumping up against limits in many ways not modelled in the IPCC report. The RCP2.6 Scenario comes closest of the scenarios shown in providing an indication of our future situation. Clearly the climate is changing and will continue to change in ways that our planners never considered when they built cities and took out long-term loans. This is a problem not easily solved.

One of the big issues is that energy supplies seem to be leaving us, indirectly through economic changes that we have little control over. The IPCC report is written from the opposite viewpoint:  we humans are in charge and need to decide to leave energy supplies. The view is that the economy, despite our energy problems, will return to robust growth. With this robust growth, our big problem will be climate change because of the huge amount of carbon emissions coming from fossil fuel burning.

Unfortunately, the real situation is that the laws of physics, rather than humans, are in charge. Basically, as economies grow, it takes increasing complexity to fix problems, as Joseph Tainter explained in his book, The Collapse of Complex Societies. Dissipative structures provide this ever-increasing complexity through higher “energy rate density” (explained in the Chaisson article linked above –).

We need to understand what are really up against, if we are to think rationally about the future. It would be helpful if more people tried to understand the physics of the situation, even if it is a difficult subject. While we can’t really expect to “fix” the situation, we can perhaps better understand what “solutions” are likely to make the situation worse. Such knowledge will also provide a better context for understanding how climate change fits in with other limits we are reaching. Climate change is certainly not the whole problem, but it may still play a significant role.

For the whole picture, I can’t recommend reading the original enough……  it may well be the most important article Gail has ever written….





Mineral resources and the limits to growth

29 09 2013

I thought long and hard about reproducing this remarkable article here…….  It’s rather longer than anything I

Ugo Bardi

Ugo Bardi

usually put up, and I was concerned about copyright, but found nothing on the original website where this was published that says I can’t do it…… and I expect no one at resilience.org objects to ensuring the spread of this important message.

Five years ago, I published a very short item on roughly the same concept.  But I’m no Ugo Bardi…..  So make yourself a good cuppa your favourite poison, and enjoy….

 

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So, ladies and gentleman, let me start with this recent book of mine. It is titled “The Plundered Planet.”  You can surely notice that it is not titled “The Developed Planet” or “The Improved Planet.”  Myself and the co-authors of the book chose to emphasize the concept of “Plundering”; of the fact that we are exploiting the resources of our planet as if they were free for us for the taking; that is, without thinking of the consequences.   And the main consequence, with which we are concerned here is called “depletion,” even though we have to keep in mind the problem of pollution as well.

Now, there have been many studies on the question of depletion, but “The Plundered Planet” has a specific origin, and I can show it to you. Here it is.

It is the rather famous study that was published in 1972 with the title “The Limits to Growth”.  It was one of the first studies that attempted to quantify depletion and its effects on the world’s economic system.  It was a complex study based on the best available data at the time and that used the most sophisticated computers available to study how the interaction of various factors would affect parameters such as industrial production, agricultural production, population and the like.  Here are the main results of the 1972 study, the run that was called the “base case” (or “standard run”).  The calculations were redone in 2004, finding similar results.  

As you can see, the results were not exactly pleasant to behold.  In 1972, the study saw a slowdown of the world’s main economic parameters that would take place within the first two decades of the 21st century.  I am sure that you are comparing, in your minds, these curves with the present economic situation and you may wonder whether these old calculations may be turning out to be incredibly good.  But I would also like to say that these curves are not – and never were – meant to be taken as specific predictions.  No one can predict the future, what we can do is to study tendencies and where these tendencies are leading us.  So, the main result of the Limits to Growth study was to show that the economic system was headed towards a collapse at some moment in the future owing to the combined effect of depletion, pollution, and overpopulation.  Maybe the economic problems we are seeing nowadays are a prelude to the collapse seen by this model, maybe not – maybe the predicted collapse is still far away in the future.  We can’t say right now. 

In any case, the results of the study can be seen at least worrisome.  And a reasonable reaction when the book came out in 1972 would have been to study the problem in greater depth – nobody wants the economy to collapse, of course.  But, as you surely know, the Limits to Growth study was not well received.  It was strongly criticized, accused of having made “mistakes” of all kinds and at times to be part of a worldwide conspiracy to take control of the world and to exterminate most of humankind.  Of course, most of this criticism had political origins.  It was mostly a gut reaction: people didn’t like these results and sought to find ways to demonstrate that the model was wrong (or the data, or the approach, or something else).  If they couldn’t do that, they resorted to demonizing the authors – that’s nothing now; I described it in a book of mine “Revisiting the limits to growth“.

Nevertheless, there was a basic criticism of the “Limits” study that made sense.  Why should one believe in this model?  What are exactly the factors that generate the expected collapse?  Here, I must say, the answer often given in the early times by the authors and by their supporters wasn’t so good.  What the creators of the models said was that the model made sense according to their views and they could show a scheme that was this (from the 1972 Italian edition of the book):

Now, I don’t know what do you think of it; to me it looks more or less like the map of the subway of Tokyo, complete with signs in kanji characters.  Not easy to navigate, to say the least.  So, why did the authors create this spaghetti model?  What was the logic in it?  It turns out that the Limits to Growth model has an internal logic and that it can be explained in thermodynamic terms.  However, it takes some work to describe the whole story.  So, let me start with the ultimate origin of these models:

If you have studied engineering, you surely recognize this object.  It is called a “governor” and it is a device developed in 19th century to regulate the speed of steam engines.  It turns with the engine, and the arms open or close depending on speed.  In so doing, the governor closes or opens the valve that sends steam into the engine.  It is interesting because it is the first self-regulating device of this kind and, at its time, it generated a lot of interest.  James Clerk Maxwell himself studied the behaviour of the governor and, in 1868, he came up with a set of equations describing it. Here is a page from his original article

I am showing you these equations just to let you note how these systems can be described by a set of correlated differential equations.  It is an approach that is still used and today we can solve this kind of equations in real time and control much more complex systems than steam engines.  For instance, drones.

You see here that a drone can be controlled so perfectly that it can hold a glass without spilling the content. And you can have drones playing table tennis with each other and much more.  Of course they are also machines designed for killing people, but let’s not go into that.  The point is that if you can solve a set of differential equations, you can describe – and also control – the behaviour of quite complex systems.

The work of Maxwell so impressed Norbert Wiener, that it led him to develop the concept of “cybernetics”

We don’t use so much the term cybernetics today.  But the ideas that started from the governor study by Maxwell were extremely fecund and gave rise to a whole new field of science.  When you use these equations for controlling mechanical system, you use the term “control theory.”  But when you use the equations for study the behaviour of socio-economic systems, you use the term “system dynamics”

System dynamics is something that was developed mainly by Jay Wright Forrester in the 1950s and 1960s, when there started to exist computers powerful enough to solve sets of coupled differential equations in reasonable times.  That generated a lot of studies, including “The Limits to Growth” of 1972 and today the field is alive and well in many areas.

A point I think is important to make is that these equations describe real world systems and real world systems must obey the laws of thermodynamics.  So, system dynamics must be consistent with thermodynamics. It does.  Let me show you a common example of a system described by system dynamics: practitioners in this field are fond of using a bathub as an example:

On the right you have a representation of the real system, a bathtub partly filled with water.  On the left, its representation using system dynamics.  These models are called “stock and flow”, because you use boxes to represent stocks (the quantity of water in the tub) and you use double edged arrows to indicate flows.  The little butterfly like things indicate valves and single edged arrows indicate relationship.

Note that I used a graphic convention that I like to use for my “mind sized” models.  That is, I have stocks flowing “down”, following the dissipation of thermodynamic potential.  In this case what moves the model is the gravitational potential; it is what makes water flow down, of course.  Ultimately, the process is driven by an increase in entropy and I usually ask to my students where is that entropy increases in this system.  They usually can’t give the right answer.  It is not that easy, indeed – I leave that to you as a little exercise

The model on the left is not simply a drawing of box and arrows, it is made with a software called “Vensim” which actually turns the model “alive” by building the equations and solving them in real time.  And, as you may imagine, it is not so difficult to make a model that describes a bathtub being filled from one side and emptied from the other. But, of course, you can do much more with these models.  So, let me show a model made with Vensim that describes the operation of a governor and of the steam engine.

Before we go on, let me introduce a disclaimer.  This is just a model that I put together for this presentation. It seems to work, in the sense that it describes a behaviour that I think is correct for a governor (you can see the results plotted inside the boxes).  But it doesn’t claim to be a complete model and surely not the only possible way to make a system dynamics model of a governor.  This said, you can give a look to it and notice a few things.  The main one is that we have two “stocks” of energy: one for the large wheel of the steam energy, the other for the small wheel which is the governor.  In order to provide some visual sense of this difference in size, I made the two boxes of different size, but that doesn’t change the equations underlying the model.  Note the “feedback”, the arrows that connect flows and stock sizes.  The concept of feedback is fundamental in these models.

Of course, this is also a model that is compatible with thermodynamics.  Only, in this case we don’t have a gravitational potential that moves the system, but a potential based on temperature differences.  The steam engine works because you have this temperature difference and you know the work of Carnot and the others who described it.  So, I used the same convention here as before; thermodynamic potential are dissipated going “down” in the model’s graphical representation

Now, let me show you another simple model, the simplest version I can think of a model that describes the exploitation of non renewable resources:

It is, again, a model based on thermodynamics and, this time, driven by chemical potentials.  The idea is that the “resources” stock as a high chemical potential in the sense that it may be thought as, for instance, crude oil, which spontaneously combines with oxygen to create energy.  This energy is used by human beings to create what I can call “capital” – the sum of everything you can do with oil; from industries to bureaucracies.

On the right, you can see the results that the model provides in terms of the behaviour as a function of time of the stock of the resources, their production, and the capital stock.  You may easily notice how similar these curves are to those provided by the more complex model of “The Limits to Growth.”  So, we are probably doing something right, even with this simple model.

But the point is that the model works!  When you apply it to real world cases, you see that its results can fit the historical data.  Let me show you an example:

This is the case of whaling in 19th century, when whale oil was used as fuel for lamps, before it became common to use kerosene.  I am showing you this image because it is the first attempt I made to use the model and I was surprised to see that it worked – and it worked remarkably well.  You see, here you have two stocks: one is whales, the other is the capital of the whaling industry that can be measured by means of a proxy that is the total tonnage of the whaling fleet.  And, as I said, the model describes very well how the industry grew on the profit of killing whales, but they killed way too many of them.  Whales are, of course, a renewable resource; in principle.  But, of course, if too many whales are killed, then they don’t have enough time to reproduce and they behave as a non-renewable resource.  Biologists have determined that at the end of this fishing cycle, there were only about 50 females of the species being hunted at that time.  Non renewable, indeed!

So, that is, of course, one of the several cases where we found that the model can work.  Together with my co-workers, we found that it can work also for petroleum extraction, as we describe in a paper published in 2009 (Bardi and Lavacchi).  But let me skip that – the important thing is that the model works in some cases but, as you would expect, not in all. And that is good – because what you don’t want is a “fit-all” model that doesn’t tell you anything about the system you are studying.  Let’s say that the model reproduces what’s called the “Hubbert model” of resource exploitation, which is a purely empirical model that was proposed more than 50 years ago and that remains a basic one in this kind of studies: it is the model that proposes that extraction goes through a “bell-shaped” curve and that the peak of the curve, the “Hubbert peak” is the origin of the concept of “peak oil” which you’ve surely heard about.  Here is the original Hubbert model and you see that it has described reasonably well the production of crude oil in the 48 US lower states.

Now, let’s move on a little.  What I have presented to you is a very simple model that reproduces some of the key elements of the model used for “The Limits to Growth” study but it is of course a very simplified version.  You may have noted that the curves for industrial production of the Limits to Growth tend to be skewed forward and this simple model can’t reproduce that.  So, we must move one step forward and let me show you how it can be done while maintaining the basic idea of a “thermodynamic cascade” that goes from higher potentials to lower potentials.  Here is what I’ve called the “Seneca model”


You see that I added a third stock to the system.   In this case I called it “pollution”; but you might also call it, for instance, “bureaucracy” or may be even “war”.  It is any stock that draws resource from the “Capital” (aka, “the economy”) stock.  And the result is that the capital stock and production collapse rather rapidly; this is what I called “the Seneca effect”; from the roman philosopher Lucius Anneaus Seneca who noted that “Fortune is slow, but ruin is rapid”.

For this model, I can’t show you specific historical cases – we are still working on this idea, but it is not easy to make quantitative fittings because the model is complicated.  But there are cases of simple systems where you see this specific behaviour, highly forward skewed curves – caviar fishing is an example.  But let’s not go there right now.

What I would like to say is that you can move onward with this idea of cascading thermodynamic potentials and build up something that may be considered as a simplified version of the five main stocks taken into account in the “Limits to Growth” calculations.  Here it is

Now, another disclaimer: I am not saying that this model is equivalent to that of the Limits to Growth, nor that it is the only way to arrange stocks and flows in order to produce similar results to the one obtained by the Limits to Growth model.  It is here just to show to you the logic of the model.  And I think you can agree, now, that there is one.  The “Limits” model is not just randomly arranged spaghetti, it is something that has a deep logic based on thermodynamics.  It describes the dissipation of a cascade of thermodynamic potentials.

In the end, all these model, no matter how you arrange their elements, tend to generate similar basic results: the bell shaped curve; the one that Hubbert had already proposed in 1956

The curve may be skewed forward or not, but that changes little on the fact that the downside slope is not so pleasant for those who live it.

Don’t expect this curve to be a physical law; after all it depend on human choices and human choices may be changed.  But, in normal conditions, human beings tend to follow rather predictable patterns, for instance exploiting the “easy” resources (those which are at the highest thermodynamic potential) and then move down to the more difficult ones.  That generates the curve.

Now, I could show you many examples of the tendency of real world systems to follow the bell shape curve.  Let me show you just one; a recent graph recently made by Jean Laherrere.

These are data for the world’s oil production.  As you can see, there are irregularities and oscillations.  But note how, from 2004 to 2013, we have been following the curve: we move on a predictable path.  Already in 2004 we could have predicted what would have been today’s oil production.  But, of course, there are other elements in this system.  In the figure on the right, you can see also the appearance of the so-called “non-conventional” oil resources, which are following their own curve and which are keeping the production of combustible liquids (a concept slightly different from that of “crude oil) rather stable or slightly increasing.  But, you see, the picture is clear and the predictive ability of these models is rather good even though, of course, approximate.

Now, there is another important point I’d like to make.  You see, these models are ultimately based on thermodynamics and there is an embedded thermodynamic parameter in the models that is called EROI (or ERoEI) which is the energy return for the energy invested. It is basically the decline in this parameter that makes, for instance, the extraction of oil gradually producing less energy and, ultimately, becoming pointless when the value of the ERoEI goes below one.  Let me show you an illustration of this concept:

You see?  The data you usually read for petroleum production are just that: how much petroleum is being produced in terms of volume.  There is already a problem with the fact that not all petroleums are the same in the sense of energy per unit volume, but the real question is the NET energy you get by subtracting the energy invested from the energy produced.  And that, as you see, goes down rapidly as you move to more expensive and difficult resources.  For EROEIs under about 20, the problem is significant and below about 10 it becomes serious.  And, as you see, there are many energy resources that have this kind of low EROEI.  So, don’t get impressed by the fact that oil production continues, slowly, to grow.  Net energy is the problem and many things that are happening today in the world seem to be related to the fact that we are producing less and less net energy.  In other words, we are paying more to produce the same.  This appears in terms of high prices in the world market.

Here is an illustration of how prices and production have varied during the past decades from the blog “Early Warning” kept by Stuart Staniford.

And you see that, although we are able to manage a slightly growing production, we can do so only at increasingly high prices.  This is an effect of increasing energy investments in extracting difficult resources – energy costs money, after all.

So, let me show you some data for resources that are not petroleum.  Of course, in this case you can’t speak in terms of ERoEI; because you are not producing energy.  But the problem is the same, since you are using fossil fuels to produce most of the commodities that enter the industrial system, and that is valid also for agriculture. Here are some data.

Food production worldwide is still increasing, but the high costs of fossil fuels are causing this increase in prices.  And that’s a big problem because we all know that the food demand is highly inelastic – in plain words you need to eat or you die.  Several recent events in the world, such as wars and revolutions in North Africa and Middle East have been related to these increases in food prices.

Now, let me go to the general question of mineral production.  Here, we have the same behaviour: most mineral commodities are still growing in terms of extracted quantities, as you can see here (from a paper by Krausmann et al, 2009 http://dx.doi.org/10.1016/j.ecolecon.2009.05.007)

These data go up to 2005 – more recent data show signs of plateauing production, but we don’t see clear evidence of a peak, yet. This is bad, because we are creating a climate disaster. As you see from the most recent data, CO2 are still increasing in a nearly exponential manner

 

But the system is clearly under strain. Here are some data relative to the average price index for aluminium, copper, gold, iron ore, lead, nickel, silver, tin and zinc (adapted from a graphic reported by Bertram et al., Resource Policy, 36(2011)315)

So, you see, there has been this remarkable “bump” in the prices of everything and that correlates well with what I was arguing before: energy costs more and, at the same time, energy requirements are increasing because of ore depletion.  At present, we are still able to keep production stable or even slowly increasing, but this is costing society tremendous sacrifices in terms of reducing social services, health care, pensions and all the rest.  And, in addition, we risk destroying the planetary ecosystem because of climate change.

Now I can summarize what I’ve been saying and get to the take-home point which, I think can be expressed in a single sentence “Mining takes energy

Of course, many people say that we are so smart that we can invent new ways of mining that don’t require so much energy.  Fine, but look at that giant wheel, above, used to extract coal in the mine of Garzweiler in Germany.  Think of how much energy you need to make that wheel; do you think you could use an i-pad, instead?

In the end, energy is the key of everything and if we want to keep mining, and we need to keep mining, we need to be able to keep producing energy.  And we need to obtain that energy without fossil fuels. That’s the concept of the “Energy Transition”

Here, I use the German term “Energiewende” which stands for “Energy Transition”. And I have also slightly modified the words by Stanley Jevons, he was talking about coal, but the general concept of energy is the same.  We need to go through the transition, otherwise, as Jevons said long ago, we’ll be forced to return to the “laborious poverty” of older times.

That doesn’t mean that the times of low cost mineral commodities will ever return but we should be able to maintain a reasonable flux of mineral commodities into the industrial system and keep it going.  But we’ll have to adapt to less opulent and wasteful life as the society of “developed” countries has been accustomed to so far.  I think it is not impossible, if we don’t ask too much:

h/t ms. Ruza Jankovich – the car shown here is an old Fiat “500” that was produced in the 1960s and it would move people around without the need of SUVs

____________________________________________

Acknowledgement:

The Club of Rome team

Daphne Davies
Ian Johnson
Linda Schenk
Alexander Stefes
Joséphine von Mitschke-Collande
Karl Wagner

And the coauthors of the book “Plundering the Planet”

Philippe Bihouix
Colin Campbell
Stefano Caporali
Partick Dery
Luis De Souza
Michael Dittmar
Ian Dunlop
Toufic El Asmar
Rolf Jakobi
Jutta Gutberlet
Rui Rosa
Iorg Schindler
Emilia Suomalainen
Marco Pagani
Karl Wagner
Werner Zittel

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More on the Energy Cliff

5 05 2013

Remember my post about Pedro Prieto‘s email to me regarding the energy cliff?  Well here’s a new article I found about his latest views on Photo Voltaics……

Solar Dreams, Spanish Realities

Facing limits to sun-powered renewable energy. Latest in a series.

By Andrew Nikiforuk, 1 May 2013,

Reproduced from http://thetyee.ca/News/2013/05/01/Solar-Dreams/

WHAT’S BLOCKING SUN POWER?

The sun showers the earth with more energy every hour than what civilization currently burns with fossil fuels every year. Given this tantalizing bounty many greens view the resource as cheap, clean, noiseless and limitless.

Yet despite 50 years of solar innovation the industrial world currently runs on 17 terawatts of primary energy mostly provided by coal, gas and oil.

Solar, a determined energy underdog, provides but one-tenth of one per cent of energy demand. (Only 80 terawatt hours of the world’s 22,000 terawatt hours generated by the global electric grid every year come from solar modules.)

Nevertheless many experts estimate that solar PV and thermal systems if planted on the world’s deserts occupying an area the size of Venezuela — could eventually create about 15 terawatts of energy within 50 years. In fact solar is the only renewable with the potential to challenge the dominance of hydrocarbons.

But many analysts suspect these figures, based on theoretical exercises, are way too optimistic. A group of Spanish engineers, for example, calculates in an unpublished paper that no more than two to four terawatts of solar energy can ever be successfully harvested for human use due in part to many of following realities:

Geography: The sun does not shine brightly or intensely everywhere. As a consequence it costs less to generate more power in places like sunny California than it does cloudy Germany or Ontario. Yet for political reasons much infrastructure has been built in cloudy developed nations with highs of energy spending combined with mediocre levels of radiation. Cheap oil has discouraged use of solar power in the Middle East.

Ownership: Solar is mostly a bipolar operation. It is either used by individuals to provide 20 to 60 per cent of their electrical needs or by large corporations and big utilities to generate hundreds of megawatts with massive installations. Supplying solar power owned and used by local communities for their own needs remains a largely novel idea. Community ownership would use less space, decentralize power distribution and possibly lower energy spending. Yet as one 2010 study noted few such experiments exist and “they often don’t meet their objectives of providing clean, environmentally-friendly energy that is affordable for the community stakeholders.”

Materials: The making of solar photovoltaic cells requires rare elements such as gallium, tellurium, indium and selenium. Called “hitchhiker” metals, most are the byproduct of industrial copper, zinc or lead production. New thin-film solar sheets, for example, depend on indium. Moreover indium reserves are largely located in China and the U.S. Geological Survey predicts global supplies could be depleted within 10 years. Concentrated solar power which use mirrors to direct solar rays to heat water, also employs silver at rates of one gram per square meter. A global boom in such solar units would create silver shortages. Copper shortages are also a concern.

Storage: Solar power offers intermittent bursts of energy, posing storage challenges. The average percentage of time a solar operation pours electricity onto the grid at full rated capacity ranges from 12 to 19 per cent. In contrast a coal-fired plant runs 70 to 90 per cent of the time. Storing sun-derived power in batteries, molten salts or compressed air schemes remains problematic if not costly due to significant energy losses in storage and release.

Energy Density: Just as a slice of cheese offers more calories than a potato, different energy sources pack difference punches. The amount of energy contained in a solar ray versus a lump of coal is reflected in their respective geographical footprint. A 1,000 megawatt coal-fired plant requires 1 to 4 square km to mine and transport the coal. In contrast it takes 20 to 50 square km or the area of a small city to generate the same amount of energy from a photovoltaic farm. A large solar industry will compete with other land uses.

Economic Volatility: Solar power is expensive to install and is only beginning to reach the same price levels as other electrical providers. The U.S. Department of Energy’s SunShot Initiative, for example, seeks to reduce the cost of solar energy systems by 75 per cent by 2020. But investments in alternative energy sources also tend to be highly cyclical. When oil prices are high, communities, industry and government tend to divert dollars to renewables. But as soon as fossil fuel prices fall, that interest wanes and the renewable booms dissolves. Tom Murphy, U.S. physicist, solar advocate and energy blogger (Do the Math), argues that governments should “artificially” keep energy prices high enough “to maintain the impetus for developing alternatives, pumping the revenue into a national alternative energy infrastructure. But governments are bound by voters who simply don’t want sustained high energy prices.”

— Andrew Nikiforuk

“We had a lot of hopes and now we’re more skeptical.”

That’s how Pedro Prieto, a 62-year-old global telecom engineer and solar entrepreneur, sums up Spain’s famous solar revolution.

Spain’s renewable dream, of course, began as sunny-multi-billion-dollar boom. Quasi-religious images of fields of photovoltaics and radiant concentrated solar towers wowed North American greens. (Concentrated solar uses 624 mirrors to focus radiation to a receiver that heats steam to drive a turbine.)

But the revolution rapidly collapsed into a messy economic bust that has left more questions than answers. Moreover, Prieto and his Spanish compatriots are still counting the unpredictable casualties of the nation’s stalled energy transition.

Now the engineer is no stranger to solar power. As a telecom engineer he has worked with photovoltaic panels in remote locations since the 1970s. Nor is he a cheerleader for fossil fuels. As the co-founder of the Spanish Association for the Study of Energy Resources, Prieto has long advocated abandoning oil before its volatile pricing and pollution leave the globe in financial and atmospheric chaos.

Since 2004 he has designed, consulted and helped to build more than 30 megawatts (MW) of solar photovoltaic (PV) plants. He even manages, operates and partially owns a PV plant that spills one megawatt of juice (enough to power up to 1,000 homes) onto the national electrical grid in the province of Extremadura.

Given his vast technical experience Prieto also consults with governments around the world on solar renewable prospects. And he has also teamed up with ecologist Charles Hall to produce a provocative book: Spain’s Photovoltaic Revolution: The Energy Return on Investment.

These days Prieto ends his presentations, more often than not, by asking to his audience to “pray for alternatives to nuclear.”

Prieto is also the sort of guy that practically beams out inconvenient statistics. In 2007 installed solar power amounted to .0006 of the world’s electrical consumption and did not keep pace with the growth of electric consumption.

Or as Prieto put it in 2008: “The Energy Consumption Chariot goes over 200 times faster than the Solar Power horses.”

Spain, of course, has gained some fame and notoriety as a global solar pioneer. One-tenth in 2009 and one-fifteenth of the world’s installed solar power modules now dot the Spanish countryside. But these expansive operations provide but 4.3 per cent of Spain’s electricity.

The sun’s sheer abundance has always made it the world’s most popular renewable form of energy. Of all green alternatives solar energy is the only one whose potential harvest far outstrips the demand for fossil fuels. Enough radiation hits the earth every hour to meet all of the world’s electrical needs for a year. By some very optimistic estimates the rapidly growing solar industry could account for 10 per cent of the world’s electrical production by 2020.

Sunny climes

Spain, of course, gets more irradiation than any other European country. The nation’s sunny plains and deserts absorb about 1,500 terawatt hours of solar energy every year. That represents at least three times more power than what Spain’s 46 million citizens actually consume. (A terawatt hour by the way represents enough energy to operate one billion washing machines.)

But achieving that goal might come with some staggering financial costs, significant land disturbance as well as disappointing energy returns. Prieto has even come to view solar power in its current big industrial mindset as just “another extension of fossil fuels.”

And he’s not short of examples. The sun is renewable but photovoltaics are not. Just to make the silicon used to trap the sun’s rays on manufactured wafers requires the melting of silica rock at 3,000 Fahrenheit (1,649 Celsius). And the electricity of coal-fired plants or ultrapurified hydrogen obtained from fossil sources provide the heat to do that. It also takes a fantastic amount of oil to make concrete, glass and steel for solar modules.

But Spain’s interest in renewables is no mystery. Not only does the world’s 14th economic power rely on fossil fuels more than any other European nation (consumption has doubled in the last decade), but it suffers from a 90 per cent dependency on foreign imports.

This energy servitude combined with the nation’s concerns about climate change spurred an unusual revolution in 2004. That’s when the government offered generous subsidies or premium tariffs for solar and wind-made electricity added to the national grid. The initiative guaranteed 25-year-long profitable returns of at about 20 per cent for solar entrepreneurs. The government also came up with an inviting mantra, “The Sun Moves Us.”

Solar boom

Within short order farmers signed over orchards and plots of land for solar PV farms. Next came concentrated solar tower installations. Unlike Germany’s solar revolution, which planted thousands of modules on rooftops, Spain focused its solar growth on installed ground facilities. They are, says Prieto, much more efficient and easy to maintain.

In response to the subsidies factories making silicon wafers and/or assembling modules popped up like orange trees across the nation. Sensing a financial killing, global banks and pension funds poured money into Spain’s solar boom the same way they funded financial derivatives or the shale gas revolution in North America.

By 2008 Spain’s solar explosion eagerly swallowed half of the globe’s photovoltaic module production. Facing module shortages the country even started to import products from Germany, the U.S. and China.

This unexpected development undermined the goal of growing a renewable Spanish industry, says Prieto. (At one point China-based Suntech, the world’s largest solar panel manufacturer, sold 40 per cent of its product to Spain. Last month Suntech declared bankruptcy.)

Meanwhile, the boom surpassed every government electrical target says Prieto. The government set an initial goal of creating 400 MW of power from solar power by 2010. But industry surpassed that goal in 2006-7. “Banks and investment funds treated solar like a financial product. These were the days of wine and roses.”

But by 2008 the excesses of the boom became readily apparent. For starters, the government realized that it could no longer subsidize renewables for 25 years to the tune of 2.5 billion Euros a year.

And so it issued new royal decrees cutting promised returns from 46 cents a KW hour to 32 cents for investors. Later decrees forced more reductions putting brakes on the entire solar module industry.

“There have been 15 royal decrees on renewables since 2004,” explains Prieto. “Each one tries to fix the unanticipated problems of the last one. Each one is worst than the last. But each decree makes renewables less credible.” A raft of lawsuits has predictably clogged the courts.

The crash

An industry poised for a massive build-up based on guaranteed returns, explains Prieto, then laid off workers as a debt-heavy government cancelled or lowered promised financial returns from the sun. The solar PV sector now estimates that 44,000 of the nation’s 57,900 installations are on the verge of bankruptcy.

During the solar “craziness” as Prieto calls it, other problems emerged too. Investors often planted installations of poor quality and design across the landscape. Many facilities weren’t even located in the sunniest parts of Spain.

Spain’s renewable boom (wind installations now make up 17 per cent of Spain’s electricity supply with peaks covering up to 56 per cent) also created havoc with the nation’s energy balance. Government investment in natural gas fired plants (a backup for intermittent wind) combined with renewables resulted in overcapacity in the system. Even the nation’s nuclear power plants had to power down from 7.7 to 6.7 gigawatts for a while.

“The energy industry is much more complicated and integrated than anyone thought. The left side of Spain’s energy planning brain didn’t know what the right side was doing.”

But what troubled Prieto most were the paltry energy returns of some 57,900 solar plants, both big and small. He reviewed Spain’s excellent data on the energy outputs of the nation’s solar network and than compared those findings to actual energy inputs. To his dismay Prieto found that solar offered only slightly better returns than biofuels. Or 2.4 to one.

“That is not enough to maintain society as it is today.”

His finding surprised many researchers and for good reason. Previous studies put solar returns as high as eight or even up to 30 to one in some cases, or almost on par with conventional oil.

But most of this research used the same sort of best-case scenario modelling typically employed by car industry mileage studies. As long as the roads are flat, the fuel is good, the tires full and the driver competent, then great mileage can be achieved.

But real life experience can be different for car mileage as well as the energy output for solar installations.

Solar power, fossil fuel inputs

Spain discovered, for example, that the earth is rarely flat (a big issue for tracking and directing solar rays in the right direction). Moreover the modules (only 15 per cent efficient on average) rarely perform as expected. Not only do the panels require regular maintenance but constant cleaning to remove films of dust. And they only last 25 years.

But Prieto added together another 24 factors illustrating the industry’s profound dependence on fossil fuels. They included road maintenance, rights of ways, module theft, intermittent loads, as well as the cost of natural gas fired back-up stations. In the end he concluded that the solar industry “eats and spends considerable energy.”

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Pedro Prieto

Solar energy author Pedro Prieto: ‘We had a lot of hopes.’

Moreover countries such as Germany which receive but two-thirds of Spain’s sunlight in the best case and on average deploy much less inefficient rooftop arrays will probably have returns one-fifth to one-third lower than Spain.

“Solar installations are dependent on a fossil fuel world and there are difficulties scaling up the power of the sun,” says Prieto.

And what does Prieto think of big plans to industrialize the deserts of the U.S. southwest to provide power for the east? Or plans to colonize the Sahara desert of North Africa for European delights?

Not much, he replies sadly. The engineer calculates that just one plan proposed by former French President Nicolas Sarkozy was so big that it was obsolete before it harvested one solar ray. The plan would have covered 400 sq. km of land and burned three to six million tons of coal to erect 1.8 to 3.6 million tons of steel and two to four million tons of glass. Vast amounts of clean water and lakes of desalinated water would have been needed to maintain the plants. Yet the plan would have generated only three per cent of the electricity that nations of the Mediterranean basin now consume. Such a scheme would exchange the political insecurity of oil and gas pipelines with high voltage cable lines.

“It would be far more rational to strive for a world with far lower levels of more localized demand and widely distributed, small and local generation and distribution networks where possible,” the engineer concluded in a recent editorial.

Nations as solar plantations

Big Solar would also turn poor countries like Morocco into virtual solar plantations or colonies that feed electrical power to wealthy at a project cost of $60-billion. (Another unrealistic forecast suggests that industrial solar plants in the Sahara could produce enough energy for 100 million homes for half a trillion dollars by 2050. Prieto says this plan, dubbed Desertec would be lucky to achieve 30 per cent of Europe’s electrical needs.)

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But the big issue for solar is simply scaling up the enterprise to capture enough of the sun’s rays to retire just a fraction of fossil fuels. Prieto calculates, for example, that to replace all electricity made by nuclear and fossil fuels in Spain would take a solar module complex covering 6,000 sq. km of the country at the cost the entire Spanish budget (1.2 billion Euros in 2007). It would also require the equivalent of 300 billion car batteries to store the energy for night-time use.

Prieto is not alone in reaching such sobering conclusions. A 2013 Stanford University report, for example, calculated that global photovoltaic industry now requires more electricity to make silicon wafers and solar troughs than it actually produces in return. Since 2000 the industry consumed 75 per cent more energy than it put onto the grid and all during its manufacturing and installation process.

Moreover it won’t pay off this energy debt or energy consumed in its construction until 2016. As a consequence, ramping up of industrial solar production produces more greenhouse gases than it saves for nearly a decade. The study also recommended that reducing the fossil fuel inputs for a next generation of photovoltaic systems be a key priority.

“We have to leave oil before it leaves us,” says Prieto paraphrasing the famous Fatih Birol quote, “and it is not good for nature or the planet.”

Back to the village

“In my opinion we can use solar PV energy, as far as it is available and we can afford it for specific applications,” says Prieto. But he now views solar PV systems as “non-renewable energy systems that can only capture a portion of the renewable energies temporarily.”

Moreover there is no way solar power can sustain “our present wasteful way of living.”

In Spain where nearly a quarter of the workforce sits idle and political unrest smolders in the cities, there is much talk about “La vida buena” or what the French call “decroissance” or degrowth.

The grassroots movement is all about living better by consuming less and sharing more. Prieto suspects the future may be determined more by behavior change than by investments in renewables.

“In general terms, I would suggest we make every possible effort to move towards a lower consumption and lower mobility society,” sums up the 62-year-old.

“We need to deurbanize and localize as much as it is possible, and to return to the countryside, as much as it is possible, and to use more animal draft force.”

When asked for advice on what other nations should do, Prieto thoughtfully pauses.

“It is difficult to give advice.”