The laws of thermodynamics: what role in the energy transition?

The laws of thermodynamics are often framed in such arcane terms that they are overlooked. This note outlines these three fundamental laws of physics and why they matter for energy transition. Renewables are so good that they practically break the second law of thermodynamics. Hydrogen is so poor that it halves the pace of energy transition. Industrial efficiency technologies are crucial across the board.


The First Law of Thermodynamics: Never Created or Destroyed.

The first law of thermodynamics is the law of conservation of energy. It states that energy cannot be created or destroyed. It can only transformed from one form into another.

The simple example is combusting a fuel, converting the chemical energy in the fuel into thermal energy. If we take natural gas as an example, 1mcf contains 304kWh of chemical energy. This can be transferred into 274kWh of useful heat energy in a 90% efficient boiler. The chemical energy released equals the enthalpies of new bonds formed during combustion minus the enthalpies of bonds in the fuels (chart below).

The best debating point around the first law of thermodynamics is the nuclear energy industry, which creates energy from the controlled decay of Uranium-235. To all intents and purposes, nuclear energy is “creating energy”. But the first law of thermodynamics is upheld by claiming that all matter is really just condensed energy (via the law of special relativity, E = mc2).

Another debatable example is natural gas flaring, which ran at 122bcm in 2019. To all intents and purposes the useful energy in the gas is being destroyed, as the gas is simply wasted. Again, the first law of thermodynamics would claim that flaring is not actually destroying the energy in natural gas, but converting it into heat, which then leaks into the atmosphere, and then from the atmosphere into outer space.

Where the first law of thermodynamics is most useful is to dismiss tall tales about perpetual motion machines or powering the world off of biomass. For example, you may have spent time on an exercise bike during lockdown and wondered how much power you are generating. If a person eats 2,500 calories per day, this is equivalent to around 3kWh of chemical energy. Even if your body was 100% efficient at absorbing this energy, then converting it into electricity on a stationary exercise bike, you would not be able to do more than 3kWh of useful work, by the first law of thermodynamics. To put this in perspective, 1 gallon of gasoline contains 35kWh. And for video confirmation of this disappointing thermodynamic equivalency, please see below.

The Second Law of Thermodynamics: Efficiency Losses.

The second law of thermodynamics states that entropy invariably increases in a closed system. Entropy, in turn, is defined as a state of “disorder, randomness or uncertainty”. This definition is itself somewhat disorderly, random and uncertain. But bear with me.

Mathematically, entropy is more rigorously defined in the context of a Carnot cycle heat engine, which does useful work by transferring heat from a heat source into a cooler reservoir. Entropy is the ratio of heat energy flux to absolute temperature. When the heat energy leaving the heat source divided by the absolute temperature of that heat source matches the heat energy arriving at the cooler reservoir divided by the temperature of that cooler reservoir, then entropy has been preserved. When the heat energy leaving the heat source divided by the absolute temperature of that heat source exceeds the energy arriving at the cooler reservoir divided by the temperature of that cooler reservoir, then entropy has increased.

Re-stated in human English, the second law of thermodynamics effectively says that an energy consuming process will be less than 100% efficient. And in aggregate the universe invariably progresses from a state of concentrated and useful energy towards diffuse and useless energy. Billions of years from now, the entire universe will thus devolve into an entropic soup devoid of any life.

Again the second law of thermodynamics sometimes seems debatable. Effectively a solar panel or a wind turbine is capturing diffuse and useless wind or solar energy, and converting it into concentrated, useful electrical energy. To all intents and purposes, useful energy is being created out of thin air (or sunny or windy air as the case may be).  However, strictly, the second law of thermodynamics is not being violated, from a total systems perspective, which considers the electromagnetic energy that was present in the sunshine or the kinetic energy that was present in the wind. Solar panels are only 15-25% efficient at converting incoming solar energy into electricity, with the best test-cells recently hitting 50% (chart below). No one is arguing that wind or solar efficiency will ever exceed 100% capture rate of the energy that reaches them.

As another example, a heat pump will generally yield 2-8 units of useful energy per unit of energy that is supplied in the form of electricity. The heat pump uses diffuse energy to evaporate a refrigerant (absorbing the heat) and then compresses that refrigerant onto a surface where it condenses (releasing the heat). Thus it can move diffuse heat from a low-grade and useless source to a concentrated and useful sink. However, again, from a total systems perspective, which considers the size of the heat reservoir in the air/ground, the system is not strictly violating the second laws of thermodynamics.

Where the second law of thermodynamics is useful, if properly understood, is in encouraging efficient energy use, with as few unnecessary conversion steps as possible. By the second law of thermodynamics, more conversion steps and processes will amplify efficiency losses. This is why it takes 160,000TWH of energy supplies to meet 70,000TWH of useful energy demand each year globally, per our energy market models (below).

The second law of thermodynamics means that energy efficiency is a crucial focus in our research into decarbonization, to avoid wasting energy (see below).

Green hydrogen is likely most challenged by this thermodynamic argument, out of any technology in the energy transition. Converting renewable energy into hydrogen energy in an electrolyzer will likely be 60-70% efficient, with an inevitable over-voltage at the anode. Turning that hydrogen back into useful kWh of energy in a fuel cell will likely be 60-80% efficient. There is also an energy cost of transporting and storing the hydrogen. So at best, the round-trip on green hydrogen will waste c50% of all of the renewable energy that is generated. This is one factor that hurts our hydrogen economics below, and it has nothing to do with the costs of electrolysers or fuel cells, but basic laws of physics.

Conversely the best thermodynamic way to use renewable energy to drive decarbonization is to find ways of using that renewable energy directly, including through demand shifting. If renewable energy can be integrated directly into industrial processes, each generated kWh will achieve around 2x more decarbonization than if it is converted into hydrogen, with all of the associated energy penalties. Likewise, shifting power demand to when renewables are generating is always going to be more efficient than storing renewable energy and re-releasing it later (note below). On the other hand, if your goal is simply to maximize the amount of renewable assets you can develop, then hydrogen pathways help you – you will get to develop 2x more renewables for the same amount of decarbonization. Welcome to the cobra effect.

The Third Law of Thermodynamics

The third law of thermodynamics states that a system’s entropy approaches zero as the temperature approaches absolute zero (-273°C). In turn, this means that it is not possible to lower the temperature of an object to absolute zero. And by the second law of thermodynamics, more entropy will be created outside of the cooled substance than is removed from that cooled substance (i.e., cooling cannot be 100% efficient).

The third law of thermodynamics is more removed from everyday energy use. Although the energy requirements of liquefying natural gas to -160C does emit 15-25kg of CO2 per boe of energy in the gas, equivalent to around 5-7% of the energy in the natural gas in the first place (chart below). Much worse, we estimate that cryogenically liquefying hydrogen at -253C, then transporting the hydrogen, would absorb around half of the energy content in the hydrogen in the first place. Transportation is the other key challenge for hydrogen, in our assessment.

Conclusions: thermodynamics matter

There is a strange and growing sentiment that thermodynamics, physics, or economics do not matter in the energy transition. Or at least they do not matter as much as ever-larger subsidies. Our own assessment is that policymakers set the laws within their borders, but not the laws of economics or thermodynamics. Focusing on these factors may help you find opportunities and avoid growing bubbles in the energy transition.

Farming carbon into soils: a case study?

“The key to climate change is not in the air, it’s in the ground. As a no till farmer, I’m doing my part… If [the carbon market] grows it will enact change. Farmers will change their practices”. These were the comments of an Iowa farmer that has now commercialized $330,000 of carbon credits from conservation agriculture. The case study shows how the carbon market is causing CO2-farming to expand and advance.


The opportunity farming carbon into soils?

We recently discussed the importance of agricultural carbon sequestration on the ‘Business of Agriculture’ podcast. This is one of the largest and lowest cost carbon sinks on the planet, albeit one that is mired in policy-controversies. (link here, video below).

To summarize, the organic carbon content of agricultural soils has fallen from c4% in pre-industrial times to around 1-2% today, due to mechanized agriculture, across the world’s 3bn acres of croplands. A practice called conservation agriculture restores soil carbon, through no till practices, crop rotations and cover-cropping (note below).

The economics can be transformational, increasing crop yields by 10-30%, while also cutting input costs by 50-80% (model below). Moreover, at a $35/ton CO2 price, a mid-West farmer could make more money farming carbon than farming corn.

Two side consequences are that we expect a vast uptick in activity to measure soil carbon (screen of companies below), while the global fertilizer industry could be disrupted, as some adoptees of conservation agriculture have been able to cut their fertilizer usage by 50-100% (screen also below).

Selling carbon credits from agriculture: a case study?

Another recent episode on the Business of Agriculture illustrated a detailed case study of how Conservation Agriculture is being adopted, resulting in the commercialization of carbon credits (link here, video below). Our own summary follows.

The podcast features Kelly Garrrett, a fifth-generation farmer in Iowa, whose family farms 6,300 acres, growing corn, soybeans, winter wheat and 420 beef cows. Mr Garrett states “The key to climate change is not in the air, it’s in the ground. As a no till farmer, I’m doing my part… If [the carbon market] grows it will enact change. Farmers will change their practices”. This claim may sound exaggerated, but note that all of the words soils store around 2,500bn tons of carbon, which is 3x more than the world’s atmosphere (sources and sinks data below).

Specifically, a group of carbon brokers, Nori, and an agricultural trade body, Xtreme Ag, have certified that Mr Garrett’s farm has sequestered an average of 1.15 tons of CO2 per acre per year, from 2015-2019, across 3,800 acres of the farm (For context, we estimated a lower bound of 1T of CO2 per acre per year in our own numbers into conservation agriculture).

The certification included reviewing the farm’s FSA records, crop insurance records and the use of no till, cover cropping and crop rotations. Hence, 22,000T of carbon is deemed to have been captured over this period, through conservation agriculture. These certified carbon credits are now being sold.

e-Commerce company, Shopify, the purchased 5,000 tons of the carbon credits, to offset the CO2 from their Black Friday sales in 2020, at a price of $15/ton. Additional buyers have recently bought 2,620 credits so far in 2021, but have not agreed to be named publicly. If Mr Garrett sells all 22,000 tons of carbon credits at $15/ton, that is $330,000 of income.

Supply and demand: an increasing source of carbon offsets?

A carbon price is expanding conservation agriculture. The ability to monetize carbon has led Mr Garrett to expand his focus on carbon farming. Another c3,300 acres across his farm is thus being transitioned to this carbon-restoring practice. Hence Mr Garrett plans to re-assess additional carbon capture on the farm, again through Nori, in 2022, when the additional carbon credits from 2020-22 will be sold.

A carbon price is increasing carbon absorption in soils. The ability to monetize carbon credits has also directly led Mr Garrett to explore new technologies that can sequester additional CO2 per acre. For example, Locus Ag commercializes a microbial additive called Rhizolizer Duo, which increases soil health, and thus increases both soil carbon (24% increase in root mass for corn crops) and crop yields (8-10bu/acre for corn). Acreage that sequesters 1T CO2 per acre per year can be trebled to sequester 3T CO2 per acre per year, Locus claims. More examples are featured on the Locus website

Conclusions: agriculture and the road to net zero?

Our own roadmap to ‘net zero’ assumes that restoring the carbon content of degraded agriculture soils can sequester 4bn tons of CO2 per year, at the bottom of the CO2 cost curve (below). The case study above shows the model is beginning to work in practice, and capable of snowballing.

We consider companies that can improve agricultural productivity and carbon sequestration potential to be among the non-obvious opportunities to drive the energy transition (screen below).

Illustrating industrial energy efficiency in the context of cooking?

Industrial energy efficiency is basically impossible to define or measure. This means economy-wide CO2 prices may be the most effective way to incentivize efficiency gains, whereas specific policies may miss the mark. This note illustrates the argument, in the context of ‘home cooking’ a process technology with which most readers are likely familiar…


Improving energy efficiency is crucial to decarbonizing the global energy system and explains 20% of the bridge towards ‘net zero’ in our research (chart below).

Our recent research has also focused on the topic of energy efficiency in the context of industrial heating, arguing that granular and case-specific efficiency gains are needed, rather than over-simplified statements such as “electrify everything” (below).

But what is efficiency? Measuring the efficiency of an energy-consuming process is conceptually complex. In order to illustrate the complexity, this note will consider efficiency in home-cooking. It is a process with which we are all familiar (more so than, say, ethane cracking, below).

Ideally you will also come away from this article with some interesting insights for the next time you are in the kitchen. Cooking is responsible for 4.5% of a home’s energy use, according to the DOE, and this number excludes refrigeration or dishwashing electricity. So efficicency gains here cannot hurt either.

Standard tests for measuring cooking efficiency?

The first way to measure the energy efficiency of heating technologies is to estimate the percent of incoming energy that is converted into heat. The problem with this definition is that all combustion technologies and resistive heating technologies score close to 100% efficient. Combusting gas on a gas stove released almost all of the energy in the gas as heat (and a very very small portion of light). Passing a current through the electrically resistant nichrome coil also releases almost all of the energy as heat. But as we will see below, it would be grossly incorrect to use this definition and label cooking as 100% efficient.

Instead, one of the DOE’s standard tests for the efficiency of a cookstove technology is to place a solid aluminium test block on a stove on maximum power, until the temperature in the block has risen by 144° F (80° C). Then the the heat is reduced to 25% of maximum and held for 15-minutes. Efficiency is calculated as the ratio of thermal energy absorbed by the block divided by the energy consumed by the cooker.

On these heat-up tests, typical results might be that an electric stove would achieve 70-80% efficiency and a gas stove might achieve 30-40% efficiency. Burning gas is less efficient at heating up the aluminium block, as a large portion of energy from the flame heats the surrounding air, which then convects defiantly around the kitchen. However, as long as the pan covers the entire electric coil, electric stoves do not suffer this drawback.

But a similar problem may already have occurred in the power station that generated the electricity powering the electric stove. If that power station was only c40% efficient at converting natural gas energy into usable electricity, a reasonable number (data below), then the total efficiency of the electric stove will be 25-30% overall, and actually less efficient than the gas stove, once the electricity generation is considered.

Is the waste heat really wasted? If it is a cold day, you might regard the energy leaked into your kitchen by the gas (or electric) stove as “useful” after all, reducing the load on your home heating system. However, if it is a hot day, it may be exacerbating the load on your air conditioner, hurting efficiency further. Similarly, if the cooker is close to the fridge, waste heat may be increasing refrigeration loads.

Another problem with the aluminium heat-up test is that it cannot be used to test induction heaters, which induce eddy currents in ferromagnetic cooking vessels. Those currents generate heat in proportion to the electrical resistivity of the cookware (by the Joule effect). But aluminium blocks are non-ferromagnetic. They are not heated up by electromagnetic induction. Hence the standard test need to be modified, placing the aluminium blocks in ferromagnetic pans. Because induction heaters generate their heat directly in the pan, their efficiency is usually 80-90% on these modified tests.

The biggest problem with the heat-up test is that most people do not eat aluminium blocks for dinner. Hence, one technical paper measured the energy requirements to boil 200g of potatoes, in 200ml of water and a 700g stainless steel pan, obtaining the CO2 and cost profiles below. This further complicates our assessment of efficiency. The ultimate goal here is to produce cooked potatoes, not to produce hot pans and hot water (which will ultimately be poured down the sink). Since the potatoes comprise just 20% of the mass of the system being heated, the efficiency of this potato cooking process cannot be more than 20%. We estimate 9% efficiency in the gas cooker, 14-16% in the electric cooker, and c10% in the induction cooker (although this was not a fair test, as the induction cooker was run at a higher overall heat rate, saving time, but using more power).

This also highlights that efficiency is a function of behaviour. Cooking faster wastes more heat. Cooking half (or double) the number of potatoes in the pan would have approximately halved (or doubled) the process efficiency. As would using a 2x larger (or 50% smaller) pan. Simply covering the pot with a lid lowers the energy consumption by 12-16%. Specialized cooking equipment also helps, as boiling water in an electric kettle uses 50% less energy than in a pot on an electric stove. A pressure-cooker slashes stovetop energy by 50-75%. An egg cooker may use 60% less energy than boiling eggs in a pot. And a rice cooker can use 77% less energy versus cooking rice in a pot. Ultimately, this means that cooking behaviours are much more important to overall cooking energy and CO2 emissions that whether you are cooking on a gas or electric stove top.

Another efficiency question-mark is the risk of over-cooking or burning food. Technically, in these cases, the heater has efficiently transferred heat into the food, but it was not useful heat in the sense of achieving a desired outcome. If the dish is ruined, then all prior heat transfer now needs to be “written off” in your efficiency calculation. This is where electric cooktops are more prone to problems. The heating element holds large quantities of heat and is relatively unresponsive to changing the heat rate. In one study, induction cookers can be set to very precise temperatures, gas burners tended to overshoot desired temepratures by 1C, while electric cookers tended to overshoot the desired temperature by 2-5C, and then take several minutes to cool back down again. Induction cookers also have the advantage of being less likely to cause burns to people (as long as you are not made of ferromagnetic metal).

The final question mark is whether qualitative factors matter for efficiency. Back to the potato test, noted above, cooking times ranged from 6 minutes in the microwave through to 26-minutes in a Termomix. The best flavor and texture was assessed to come from the boiled potatoes, while the worst was in the microwave. However, soluble nutrients such as vitamin C and potassium are actually lost when cooking in water, meaning the final product is debatably less nutritious. Surely no analyst can factor these subtleties into their efficiency calculations.

Why this matters: industrial efficiency is complex?

Our recent research has noted a very wide range in useful energy efficiencies of industrial heating technologies (data below). The landscape is so complex that we concluded the only way to maximize industrial efficiency was to avoid over-simplified maxims such as “electrify everything” and impose economy-wide CO2 prices, which will incentivize individual process engineers to explore ways to boost efficiencies and lower CO2 emissions.

If you are willing to grant the complexity around measuring efficiency in a process as simple as cooking potatoes, I can promise you, it is more complex in the industrial production of steel, cement, plastic, glass or paper products. All of which are explored in our note below.

Analogies can nevertheless be drawn from our cooking examples above. For example, there is a risk that efficiency mandates are as strangely detached from actual operating conditions as the aluminium block test above, or similarly that they cannot be implemented in particular sub-industries. Specific efficiency tests could be prone to being gamed at the expense of real-world efficiency. Another risk is that forcing the phase-out of one fuel in favor of another may not drive any decarbonization, if the underlying problem is inefficient processes and behaviours.

Now imagine you are trying to regulate the energy efficiency of cooking. This is a genuine question and challenge to anyone reading: what specific policies would you implement as a regulator to improve the efficiency of people cooking in their kitchens? Personally, I can think of a lot of bad answers, and only a few good ones (maybe a tax credit for taking an interactive educational course into energy efficient cooking behaviours?).

Industrial efficiency is just as complex and just as challenging to improve with specific policy measures. Again, this is the argument for a flat, fair and generalized CO2 price, incentivizing each industrial facility to seek efficiency gains where they can.


Which cooking technologies are lowest cost and lowest carbon?

Our own attempt to estimate the costs and CO2 intensities of different home cooking systems is show below. At a CO2 intensity of 0.35kg/kWh across the grid (reflecting c20% renewables penetration), we estimate a gas cooker is c15% higher carbon overall, in a household where heating and air conditioning loads balance out across the year. Gas and electric stoves have comparable costs. Induction stoves may be more powerful, sensitive, and professional, but they are likely 2x more expensive, when reflecting the $1.2-2.4k purchase prices on leading units from Frigidaire, GE and Samsung. Their payback periods on energy bills are estimated at around 44-years in one paper.

Numbers and data-points from underlying technical papers can also be stress-tested in the data-file above.

Sources

Das, T., Subramanian, R., Chakkaravarthi, A., Singh, V., Ali, S. & Bordoloi, P (2006) Journal of Food Engineering 75 pp 56–166

Korzeniowska-Ginter, R. (2019). Energy consumption by cooking appliances used in Polish households. Conf. Ser. Earth Environ. Sci. 214 012096.

Livchak, D., Hedrick, R. & Young, R. (2019). Residential Cooktop Performance and Energy Comparison Study. Frontier Energy Report # 501318071-R0

Sweeney, M., Dols, J., Fortenbery, B. & Sharp, F. (2014) Induction Cooking Technology Design and Assessment. Electric Power Research Institute, ACEEE Summer Study on Energy Efficiency in Buildings.

Global average temperatures: are the data robust and reliable?

Global average surface temperatures have risen by 1.2-1.3C since pre-industrial times and continue rising at 0.02-0.03C per year, according to data-sets from NASA, NOAA, the UK Met Office and academic institutions. This note assesses their methodologies and controversies. Uncertainty in the data is likely much higher than admitted. But the strong upward warming trend is robust.


2020 is said to be the joint-hottest year on record, tied with 2016, which experienced a particularly sharp El Nino effect. 2020 temperatures were around 1.2C warmer than 1880-1900, on data reported by NASA’s Goddard Institute for Space Studies (GISS), and 1.3C warmer on data reported by the UK Met Office’s Hadley Center and East Anglia’s Climatic Research Unit (HadCRUT).

2020’s hot temperatures were partly influenced by COVID-19, as “global shutdowns related to the ongoing coronavirus (COVID-19) pandemic reduced particulate air pollution in many areas, allowing more sunlight to reach the surface and producing a small but potentially significant warming effect”, per NASA. But the largest component of the warming is attributed to rising CO2 levels in the Earth’s atmosphere, which reached 414 ppm.

Overall, NASA’s data show temperatures have warmed by 0.02C per year over the past 50-years, 0.023C per year over the past 25-years and 0.03C per year over the past 10-years (chart above). Likewise, HadCRUT shows 0.02C per year over the past 50-years, 0.022C/year over the past 25-years and 0.024C/year over the past 10-years (below). Both data-sets suggest the rate of warming is accelerating.

How accurate are the data-sets? To answer this question, this note delves into global average surface temperature records (GASTs). It is not as simple as shoving a thermometer under the world’s armpit and waiting three minutes…

How are global average surface temperatures measures?

Surface air temperatures (SATs) are measured at weather stations. 32,000 weather stations are currently in operation and feed into various GAST indices.

Surface sea temperatures (SSTs) are measured at the surface of the sea as a proxy for immediately overlying air temperatures. Up until the 1930s, SSTs were most commonly taken by lowering a bucket overboard, and then measuring the temperature of the water in the bucket. This most likely under-estimated water temperatures in the past. From 1930-1990, SSTs were mostly measured from ships’ engine intakes. From 1990 onwards, SSTs were most commonly measured by specialized buoys and supplemented by satellite imagery.

Sea ice is particularly complicated. It takes 80% as much heat to melt 1kg of ice as it takes to boil 1kg of water, which means that the surface temperatures above sea ice can be higher than 0C. But it is difficult to access locations that are iced over with permanent weather stations. So temperatures over sea ice are often modelled not measured.

Data here: https://thundersaidenergy.com/downloads/refrigeration-and-phase-change-materials-energy-economics/

Temperatures are measured at each of these sites noted above. However GAST indices do not take raw temperature data as their inputs. First, absolute temperatures vary markedly between different weather stations that are scattered over short distances (e.g., due to shade, aspect, elevation, wind exposure), making the readings too site-specific. Moreover, the global average temperature is actually 3.6C higher in July-August than it is in December and January, because land masses experience greater seasonal temperature fluctuation than oceans, while two-thirds of the world’s land is in the Northern hemisphere, experiencing summer conditions in July-August. This would introduce too much noise into the data.

Temperature anomalies are the input to GAST indices. These are calculated by comparing average temperatures throughout each day with a baseline temperature for that site at that particular time of year. These anomalies are highly correlated, site-by-site, across hundreds of kilometers. By convention the 30-year average period from 1951-1980 is used as the baseline by NASA.

Averaging is used to aggregate the temperature anomaly data from different temperature stations across regions. Regional anomalies are then averaged into a global anomaly. Each region is weighted by its proportionate share of the Earth’s surface area. Thus a GAST index is derived.

Controversies: could there be systematic biases in the data?

Very large data-sets over very long timeframes are complicated beasts. They are prone to being revised and adjusted. Some commentators have worried that there could be systematic biases in the revisions and adjustments.

More data. As an example, NOAA digitized and added more observations from the early 20th century into its methodology in 2016. This caused prior data to be re-stated. But this reason seems fair and relatively uncontroversial.

New weather stations are slightly more controversial. How do you know what the baseline temperature would have been at a site in 1950-1980, if the first weather station was only added there in 2000? Some of the baselines must therefore be derived from models, rather than hard data. Some commentators have criticized that the models used to set these baselines themselves pre-suppose anthropogenic climate change, assuming past temperatures were cooler, thereby placing the cart before the horse. This fear may be counter-balanced by looking at weather stations with longer records. For example, of the 12,000 weather stations surveyed by NASA’s 2020 data, as many as 5,000 may have records going back beyond 1930.

Urban heat islands are somewhat more controversial again. Imagine a weather station situated in the countryside outside of a city. Over the past century, the city has grown. Now the weather station has been engulfed by the city. Cities will tend to be 1-3C warmer than rural lands, due to the urban heat island effect. So for the data to remain comparable, past data must be adjusted upwards. GISS notes that the largest change in its calculation methodology over time has been to adjust for urban heat islands. Although some commentators have questioned whether the adjustment process is at risk of not being extensive enough. This fear may be counter-balanced by the relatively small portion of weather stations experiencing this engulfing effect.

The adjustment of anomalous-looking data is most controversial. Algorithms are used to sift through millions of historical data-points and filter away outliers that run counter to expectations. The algorithms are opaque. One set of algorithms ‘homogenizes’ the data of stations showing divergent patterns to its neighbours, by replacing that station’s data with that of its neighbours. As the general trend has been for a warming climate, this means that some stations showing cooling could be at risk of getting homogenized out of the data-set, causing the overall data to overstate the degree of warming.

The data also do not correlate perfectly with rising CO2 levels: especially in 1880-1920, which appears to get cooler; and around the Second World War, which appears to produce a spike in temperatures then a normalization. On the other hand, no one is arguing that CO2 is the sole modulator of global temperature. El Nino, solar cycles and ‘weather’ also play a role. And despite the annual volatility, the recent and most accurate data from 1970+ rise in lockstep with CO2.

The most vehement critics of GAST indices have therefore argued that past temperature adjustments could be seen to contribute over half of the warming shown in the data. There is most distrust over the revisions to NASA’s early temperature records. One paper states “Each new version of GAST has nearly always exhibited a steeper warming linear trend over its entire history. And, it was nearly always accomplished by systematically removing the previously existing cyclical temperature pattern. This was true for all three entities providing GAST data measurement, NOAA, NASA and Hadley CRU”.

Uncertainties should not detract from the big picture

Our own impression from reviewing the evidence is that the controversies above should not be blown out of proportion. The Earth is most likely experiencing a 0.02-0.03C/year warming trend over the past 10-50-years.

Multiple independent bodies are constructing GAST indices in parallel, and all seem to show a similar warming trend. Pages could be written on the subtle differences in methodologies. For example, NOAA and the Berkeley Earth project use different, more complex methodologies than GISS, but produce similar end results. NOAA, for example, does not infer temperatures in polar regions that lack observations, and thus reports somewhat lower warming, of just 1.0C. This is because Arctic warming exceeds the global average, as minimum sea ice has declined by 13% each decade, allowing more sunlight to be absorbed and in turn, and causing more warming.

No doubt the construction of a global average temperature index, covering the whole planet back to 1880 is fraught with enormous data-challenges that could in principle be subject to uncertainties and biases. But it is nothing short of a conspiracy theory to suggest that multiple independent agencies are wilfully introducing those biases. And then lying about it. The Q&A section of NASA’s website states “Q: Does NASA/GISS skew the global temperature trends to better match climate models? A: No”.

You can also review all of the adjusted and unadjusted data for individual weather stations side-by-side, here. If we take the example below, in New York’s Central Park, the adjusted/homogenized and unadjusted data are not materially different, especially in recent years. Although the uncertainty is visibly higher for the 1880-1940 data.

Source: https://data.giss.nasa.gov/cgi-bin/gistemp/stdata_show_v4.cgi?id=USW00094728&dt=1&ds=14

Criticisms of the NASA data adjustments, cited in the skeptical technical paper above, do not appear particularly well founded either. It is true that NASA’s 1980s estimates of temperatures in 1920-1980 have been progressively lowered by 0.1-0.3C from 1981 to 2017, which could be seen to over-exaggerate the warming that has occurred since that time-period. However this is mostly because of bad data back in the pre-digital world of the 1980s. In fact, NASA’s 1981 data-set did not include any sea surface temperature data and only included data from 1,219 land stations, all in the Northern hemisphere.

Revisions in more recent data-sets are minimal. For example, HadCRUT’s data are shown below.

Another review of the data concludes that the net effect of revisions has been to under-state global temperature increases, by adjusting the temperatures in 1880-1930 upwards, which would under-state warming relative to this baseline (here). This is actually a blend of effects. Temperatures on land have generally been adjusted downwards by 0.1-0.2C in the 1880-1950 timeframe. Temperatures at sea have been adjusted upwards by 0.2-0.3C over 1880-1935. The original article also contains some helpful and transparent charts.

Finally, recent data are increasingly reliable. In total, 32,000 land stations and 1.2M sea surface observations are now taken every year, across multiple data-sets. Hence GISS estimates the uncertainty range in its global annual temperature data is +/- 0.05C, rising to 0.1-0.2C prior to 1960, at a 95% confidence level. From our review above, we think the uncertainty is likely higher than this. But the strong upwards trend is nevertheless robust.

Conclusions: 30-years to get to net zero?

Global temperatures are most likely rising at 0.023-0.03C per year, and 1.2-1.3C of warming has most likely occurred since pre-industrial times. This would suggest 30-years is an appropriate time-frame to get to Net Zero while limiting total warming to 2C, per our recent research note below.

A paradox in our research is that the $3trn per year economic cost of reaching net zero by 2050 seems to outweigh the $1.5trn per year economic cost of unmitigated climate change. One of the most popular solutions to this paradox, per the recent survey on our website below, was to consider re-optimizing and potentially softening climate targets. There may be economic justifications for this position. But the temperature data above show the result could be materially more warming.

Our own view is that the world should also decarbonize for moral reasons and as an insurance policy against tail-risks (arguments 3 and 6, above). And it should favor decarbonization pathways that are most economical and also restore nature (note below).

Our climate model, including all of the temperature data cited in this report are tabulated in the data-file below.

Britain’s industrial revolution: what happened to energy demand?

Britain’s remarkable industrialization in the 18th and 19th centuries was part of the world’s first great energy transition. In this short note, we have aggregated data, estimated the end uses of different energy sources in the Industrial Revolution, and drawn five key conclusions for the current Energy Transition.


In this short note, we have sourced and interpolated long run data into energy supplies in England and Wales, by decade, from 1560-1860. The graph is a hockey stick, with Britain’s total energy supplies ramping up 30x from 18TWH to 515TWH per year. Part of this can be attributed to England’s population rising 6x, from around 3M people to 18M people over the same timeframe. The remainder of the chart is dominated by a vast increase in coal from the 1750s onwards.

A more comparable way to present the data is shown below (and tabulated here). We have divided through by population to present the data on a per-capita basis. But we have also adjusted each decade’s data by estimated efficiency factors, to yield a measure of the total useful energy consumed per person. For example, coal supplies rose 40x from 1660 to 1860, but per-capita end use of coal energy only rose c6.5x, because the prime movers of the early industrial revolution were inefficient. This note presents our top five conclusions from evaluating the data.

Five Conclusions into Energy Demand from the Industrial Revolution

(1) Context. Useful energy demand per capita trebled from 1MWH pp pa in the 1600s to over 3MWH pp pa in the mid-19th century, an unprecedented increase.

For comparison, today’s useful energy consumption per capita in the developed world is 6x higher again, as compared with the 1850s. A key challenge for energy transition in the developed world is that people want to keep consuming 20MWH pp pa of energy, rather than reverting to pre-industrial or early-industrial energy levels. As a rough indicator, 20MWH is the annual energy output of c$120-150k of solar panels spread across 600 m2 (model here).

Furthermore, today’s useful energy consumption in the emerging world is only c2x higher than Britain in the 1860s. I.e., large parts of the emerging world are in very early stages of industrialization, comparable to where Britain was 150-years ago. Models of global decarbonization must therefore allow energy access to continue rising in the emerging world (charts below), and woe-betide any attempt to stop this train.

(2) Shortages as a driver of transition? One of the great cliches among energy analysts is that we “didn’t emerge from the stone age because we ran out of stone”. In Britain’s case, in fact, the data suggest we did shift from wood to coal combustion as we began to run out of wood.

Wood use and total energy use both declined in the 16th Century, and coal first began ramping up as an alternative heating fuel (charts above). In 1560, Britain’s heating fuel was 70% wood and 30% coal. By 1660, it was 70% coal and 30% wood. This was long before the first coal-fired pumps, machines or locomotives.

This is another reminder that energy transitions tend to occur when incumbent energy sources are under-supplied and highly priced, per our research below. Peak supply tends to preceed peak demand, not the other way around.

(3) Energy transition and abolitionism? Amazingly, human labor was the joint-largest source of useful energy around 1600, at c25% of total final energy consumption. But reliance upon human muscle power as a prime mover was bound up in one of the greatest atrocities of human history: the coercion of millions of Africans, slaves and serfs; to row in galleys, transport bulk materials and work land.

By the time Britain banned the slave trade in 1807, human muscle power was supplying just 10% of usable energy. By the time of the Abolition Act in 1833, it was closer to 5%.

Some people today feel that unmitigated CO2 emissions is an equally great modern-day evil. On this model, it could be the vast ramp-up of renewable energy that eventually helps to phase out conventional energy. But our current models below do not suggest that renewables can reach sufficient size or scale for this feat until around 2100.

What is also different today is that policy-makers seem intent on banning incumbent energy sources before we have transitioned to alternatives. We have never found a good precedent for bans working in past energy systems. Although US Prohibition, from 1920-1933, makes an interesting case study.

(4) Jevons Paradox states that more efficient energy technologies cause demand to rise (not fall) as better ways of consuming energy simply lead to more consumption.

Hence no major energy source in history has ‘peaked’ in absolute terms. Even biomass and animal traction remain higher in absolute terms than before the industrial revolution, both globally and in our UK data from 1560-1860.

Jevons Paradox is epitomized by the continued emergence of new coal-consuming technologies in the chart below, which in turn stoked the ascent of coal-powered demand, while wood demand was not totally displaced.

The fascinating modern-day equivalent would suggest that the increasing supply of renewable electricity technologies will create new demand for electric vehicles, drones, flying cars, smart energy and digitization; rather than simply substituting out fossil fuels.

(5) Long timeframes. Any analysis of long-term energy markets inevitably concludes that transitions take decades, even centuries. This is visible in the 300-year evolution plotted above, and in the full data-set linked below. Attempts to speed up the transition create the paradox of very high costs or potential bubbles. We have also compiled a helpful guide into transition timings by mapping twenty prior technology transitions. Our recent research, summarized below, covers all of these topics, for further information.


Source: Wrigley, E. A. (2011). Energy and the English Industrial Revolution, Cambridge, TSE Estimates. With thanks to the Renewable Energy Foundation for sharing the data-set.

Costs of climate change: solving the paradox?

Our lowest cost route to an energy transition was spelled out in December-2020 (note below), looking across 90 prior research reports and 270 data-files. It is fully possible to reach ‘net zero’ by 2050. The economic costs ratchet up to $3trn per annum.

However, based on the latest disclosures from the IPCC, we estimate that the unmitigated costs of climate change are only $1.5trn per year. So paradoxically, the energy transition appears to cost 2x more than climate change itself (note below).

What implications? The note above spells out our own solutions to the paradox. However, we also undertook a survey, to understand broader perspectives among decision makers. The results are tabulated below…

(1) Does energy transition matter? 68% of those who participated in our survey agreed or strongly agreed that the energy transition matters. Conversely, 23% disagreed or strongly disagreed. It is interesting to note that support for targeting an energy transition is strong but not universal.

(2) Do economics matter in the energy transition? 90% agreed that economics should be a material consideration in targeting an energy transition. 77% strongly agreed, the most strongly held view in the entire survey. This would suggest there is great importance in understanding which transition technologies will ultimately be economic. We expected a more polarized view here, although there could be some sampling bias at play.

(3) The paradox identified in our recent research is that the $3trn per year costs of achieving net zero appear to exceed the $1.5trn per year costs of unmitigated climate change. 65% agreed that this paradox might seem to challenge the rationale for targeting an energy transition. 23% disagreed. This is a similar split as on question (1).

(4) Could energy transition therefore be becoming a bubble? 74% agreed with this statement. 48% strongly agreed. Only 9% disagreed or strongly disagreed. This is interesting, albeit frightning support for our own thesis below.

(5) A higher cost of climate change was one solution that we proposed to resolve our paradox above. It is possible, the argument goes, that the costs of climate change are much higher than the $1.5trn per year that we estimated. 42% agreed or strongly agreed that the costs of climate change would likely be higher than we had estimated. 32% disagreed. There is no clear consensus on the unmitigated costs of climate change.

(6) A lower cost of achieving a transition was another solution that we proposed to the paradox. 35% agreed or strongly agreed that the costs of climate change would likely be lower than we had estimated. Again, there is no clear consensus on the cost of delivering the energy transition. Questions (5) and (6) had the highest portion of ‘neutral’ responses of any categories in our survey.

(7) The insurance argument is that it may still be rational to target an energy transition, even if the most likely costs of the transition exceed the most likely costs of unmitigated climate change, because climate change creates tail-risks of very large, catastrophic problems. 48% agreed or strongly agreed with this argument, making it the second most popular resolution to the paradox.

(8) The affordability argument is that it may still be rational to target an energy transition, even if the costs exceed the costs of climate change, because the costs of the former will be borne by wealthier populations in the developed world, while the costs of the latter would be incurred by poorer populations in the emerging world. Only 29% agreed with this argument, making it the least popular argument in the survey.

(9) The optimization argument is that targeting 2C of warming may not be the optimal balance, as the costs appear to outweigh the benefits. But there could be alternative timings, or alternative ceilings on global warming (e.g., 2.5C, 3C, 3.5C ?) where the costs do outweigh the benefits. 58% agreed or strongly agreed with this argument, making it the most popular argument in the survey. It may be interesting to consider how markets would react if a re-optimization of global climate targets ever came onto the political agenda.

(10) The moral argument is that it is morally ‘wrong’ to change the world’s climate, so it does not matter whether the energy transition is economically rational. 35% agreed or strongly agreed with this statement, making it the second least popular argument in the survey.


Notable perspectives and feedback

Notable perspectives were also shared by those taking part in the survey. In order to help understand others’ perspectives, some of the most cogent examples are noted below.

“The climate has always changed and humans have adapted in the past. Low cost adaption plus nature based solutions could go a long way to address the issue. Additionally, we really do not know if the 1.5-2.0 degrees is the tipping point. It was just a number conveniently picked. Reduce carbon and emissions yes, but not to the extent it wrecks the global economy.” — investor

“Difficult to see where rationality will come from, as what began as a worthy goal has become an uber-ideology that will cut any politician who stands in the way to shreds. I don’t think humanity has seen such a pervasive injection of zeal since the Christianization of the Roman Empires.” — investor

“I think the missing piece is the much higher likelihood of war(s) in an adverse climate change scenario. Judging purely by the costs incurred in a (relatively) small conflict like Iraq ($1tn per year), such costs would likely quickly exceed the $1.5tn total estimate. There are further risks to democracies and government stability if climate change results in mass migrations, epidemics, additional wealth inequality, etc. Such risks would also easily “cost” meaningfully more than the $1.5tn estimate implies.” — investor

“Ideally, the energy transition would be guided by the optimal low cost solution. this is unlikely to occur because the politicians will not support it. Furthermore, current politicians who set goals for decades in the future will not be around to enforce the painful restrictions required to achieve the targets”. — energy company strategist

“Paradoxically, we must be as economically rational as possible in execution of something that may be economically irrational! Thus, I find your comparisons of various costs of ton of captured to be extremely powerful” — investor

“Climate change will cost lives while energy transition will save it. Covid has shown that cost should not be the only factor driving policy decisions. So even if the transition is expensive (though I don’t agree with the thesis), it is worth pursuing.” — individual

“There should be a Pareto optimal solution analysis of the costs of mitigation and adaption (the latter of which tends to be ignored) relative to the costs of climate change itself.” — strategy consultant


Energy Transition Paradox Survey

The survey is still open, below, and we welcome additional perspectives…


Transitioning the world to 'net zero' is a crucial objective that should be pursued by decision-makers.
Economics matter to the energy transition. Lower-cost transition pathways are preferable to higher-cost transition pathways.
The costs of transitioning the energy system to 'net zero' by 2050 will likely reach $3trn per year. However, the ultimate costs of unmitigated climate change are likely only $1.5trn per year. If these numbers are correct, then they would challenge the rationale for targeting 'net zero' by 2050?
If achieving 'net zero' by 2050 is economically irrational, then this is another reason to fear many new energy technologies may be becoming bubbles?
Targeting an energy transition is still economically rational, because the costs of climate change will most likely be materially higher than the $1.5trn per annum that Thunder Said Energy has estimated.
Targeting an energy transition is still economically rational, because new technologies are likely to deflate the costs of achieving 'net zero' far below the $3trn per annum that Thunder Said Energy has estimated.
Targeting an energy transition is still economically rational, if this lowers the chances of catastrophic tail risks. Even though these tail risks are unlikely, they could have materially larger impacts than Thunder Said Energy's base case cost estimate of $1.5trn per annum.
Targeting an energy transition is still economically rational, because the $3trn per year costs of energy transition will mostly be borne in wealthier countries (which can more readily afford them), while the $1.5trn per year costs of climate change would mostly be borne in less wealthy countries (which can less readily afford them).
If the costs of achieving the Paris Climate goals, limiting warming to 2C, and reaching 'net zero' by 2050 outweigh the benefits, then this suggests the need to re-optimize climate targets. There could be alternative timings, or alternative ceilings on global warming (e.g., 2.5C, 3C, 3.5C ?) where the costs do outweigh the benefits. Better-optimized climate targets should therefore be explored.
It is morally 'wrong' to change the world's climate. So it does not matter whether the energy transition is economically rational.
We will share the results of the survey with you, when we have gathered enough responses. We will not disclose your email address to anyone else.

Our Top Ten Research Notes of 2020

We published 250 new research notes and data-files on our website in 2020. The purpose of this review is to highlight the ‘top ten’ reports. This includes our economic roadmap to reaching ‘Net Zero’, the greatest risks and opportunities that we have found in the transition, and the analysis that has most shaped our views.


(1) The single most powerful decarbonization option in all of our work is reforestation. Costs are as low as $3-10/ton. There is 15GTpa of carbon-offsetting potential (note here). But this is not an investment. It is an act of charity. It matters because increasing numbers of decision-makers are choosing to restore nature and offset their CO2 at low cost, rather than purchasing higher-cost new energies, which could make them uncompetitive.

(2) Restoring soil carbon is equally powerful, and surprisingly fascinating. Agricultural soil has lost three-quarters of its carbon since pre-industrial times. Restoring it could offset another 3-15GTpa of CO2. With a $30/ton CO2 price, mid-Western farmers could make more money farming carbon than corn. The theme would also disrupt the global fertilizer industry.

(3) Is energy transition becoming a bubble? If you read a single piece of research on energy transition this year, I would recommend this one. We fear an “investment bubble” is forming in the energy transition space. Half of all transition technologies we have evaluated are on the “wrong” side of the cost curve and may be displaced by the nature based solutions we described above.. Deflation and profitability are often antagonistic. And some spaces have seen incredible run-ups despite challenging economics and overlooked technical challenges. The purpose of this note is to suggest pragmatic responses.

(4) The green hydrogen economy may be the largest bubble. Our work this year has assessed the theme in detail, both in power markets and as a transportation fuel. Costs are immutably high. This is due to the laws of physics and thermodynamics. Transporting green hydrogen will also be more challenge than any other commodity in history (note here). The note below is the best overview of our work. Many expect c80% deflation in the total costs of electrolysers. Our data suggest this is impossible. We welcome challenges to these numbers, but so far, have not received any from our contacts in the hydrogen industry.

(5) The green hydrogen bubble will give way to blue. Blue hydrogen is not just a low-carbon fuel. More importantly, it is the most economic and practical route to establishing large-scale carbon capture and storage. Economics are 80-90% superior to green hydrogen. Risks are materially lower. Our research note ends by identifying projects that should reach FID in 2021, and a public company with a clear ‘moat’ in the space.

(6) Non-obvious opportunities. Other novel technologies have a vast role in the route to Net Zero. The non-obvious opportunities are best, and are not at risk of becoming bubbles. Our research has covered many examples in 2020: deep geothermal, supercapacitors eclipsing batteries, industrial efficiency initiatives such as fully subsea offshore or next-generation refining; and backing up renewables with CHPs, PCMs and smart energy systems. If you read one research note into a non-obvious opportunity, we recommend this deep-dive below into additive manufacturing, which will re-shape every industry globally.

(7) Patent analysis can give you an edge identifying opportunities in the energy transition and, and avoiding hidden risks, particularly as bubbles build. Our note below lays out six themes, including worked examples, based on reviewing over 1M patents.

(8) Our most economic roadmap to Net Zero ties together all of our work. We find it is possible to decarbonize global energy by 2050, even as global energy demand rises by 65%. The total cost of decarbonization is $50trn, which is almost halved versus last year’s estimate in December-2019. The fully decarbonized energy system still contains 85Mbpd of oil and 375TCF per year of natural gas.

(9) Oil and gas are heading for devastating under-supply if our analysis is correct. This is historically precedented during technology transitions. Below we have evaluated supply-demand and pricing in the whale oil industry from 1805-1905, as it was disrupted by rock oil and later by electric lighting. Whale oil prices outperformed over this timeframe, as supply peaked before demand. Our latest our oil market outlook is here, and our gas market outlook is here.

(10) The optimal strategy for incumbent energy companies is thus suggested in our research note below. We argue that Energy Majors embracing these principles can uplift their valuations by c50% (assuming flat commodity prices).

Wet sand: what impacts on shale breakevens and CO2?

A fully decarbonized energy system may still require 85Mbpd of oil and 375TCF of gas. Hence a focus of our research is to find improved technologies that can improve the efficieny and lower the CO2 intensity of oil and gas production. This note profiles the exciting new prospect of ‘wet sand’ for hydraulic fracturing in shale plays. It can reduce breakeven costs up to $1/bbl and CO2 intensity up to 0.6kg/bbl.


Wet sand is defined as having a moisture content between 1% and 10% by weight. This is opposed to the 43MTpa of dry sand supplied in the Permian in 2018, where all the moisture has been burned away in a kiln, shortly after the washing process.

Wet sand has reached technical maturity. In a December-2020 technical paper, PropX described a patent pending process to “screen, transport, deliver and meter wet sand from local mines to the frac blender, bypassing the drying process altogether”.

A full trial of wet sand has also been undertaken at a 10-well pad in Oklahoma, implied to have been operated by Ovintiv. Over 4Mlbs of sand per day was delivered and pumped downhole. The system was reliable and consistently flowed wet sand with 4-8% moisture content.

The advantages: cost and CO2 savings?

Cost savings from pumping wet sand are estimated at $2-10/ton. The largest capital component is in potential capex savings, as the kiln at a sand mine usually comprises $20-50M (including associated drying, storage and conveyance) out of a $180M total budget at a 2.5MTpa mine. A second saving is in opex, as labor costs average $5/ton across 15 surveyed sand mines (chart below), and the drying unit requires one-third of the labor force. Finally, there are fuel savings, likely around $1/ton.

After modelling the economics below, our base case estimate is that a greenfield sand mine can lower its total production costs by $5/ton, with a shift from dry to wet sand.

To test the economic impacts of a $5/ton reduction in sand costs, we turn to our economic model below. At a large, sand-intensive well, we estimate $0.1M of potential savings. This flows through to a $0.5/bbl reduction in the well’s NPV10 breakeven. However, the savings will be lower at industry average wells, which only consume 10-20M lbs of proppand.

CO2 savings are realized by cutting out fuel demand in the drying kilns at sand mines, typically at 0.3-0.4mmbtu per ton of dried sand, requiring 0.4mcf of gas, whose combustion would release 20kg of CO2. Again, we can run the savings through our models (below) and estimate CO2 could be reduced by up to 0.6kg/boe, which is not bad against a baseline of 26kg/boe of total upstream Scope 1 and Scope 2.

HSE advantages are also noted in the technical paper. Fugitive silica dust is materially reduced, as wet sand particles adhere to one-another. This helps meet OSHA’s 2016 silica exposure limits, below 50mg/m3 of air, averaged over an 8-hour shift.

The challenges: is wet sand more difficult to pump?

The challenge of wet sand is that wet san grains cohere to one-another, which impedes their smooth flow and can cause sand to “clump together”. In cold climates (but probably not Texas!) the water molecules can also freeze. Hence, PropX notes three areas where it has needed to innovate the sand supply chain.

Last-mile. It is recommended to use containers (rather than trailers) to transport sand to well-sites. These can be lifted from trucks onto the wellsite with “the fewest touch points and the least modification”.  A typical container system carries 23,000-27,000lbs of sand, with a capacity of 28,500 lbs. These volumes have been emulated by PropX, by enlarging the container opening (from 20” diameter to 6’x6’, and covering it with a tarp, as is widely used in transportation of agricultural products.

Emptying containers is easy with dry sand as it flows naturally, emptying in c60-seconds. Wet sand containers need to be emptied into a blender hopper. This likely takes 120-seconds, via a 100bpm slurry rate carrying 2.7ppg of sand. PropX has undertaken successful trials placing the sand containers on a vibration table, with a sloped discharge cone, silicon-inserts to lower friction and a larger discharge exit gate.

Sand delivery to the well must occur at a rate of 16,800 lbs of sand per minute, for example, comprising 80-100bpm of slurry carrying 0.5-4.0ppg of sand. A unique belt has been designed which can carry up to 7.9ppg at up to 100bpm. It includes a metering system and screwless surge hopper, also on vibrating tables, to enable accurate, reliable and continuous pumping of wet sand without the risk of bridging.

Sand has undergone huge changes in the past, which suggests this supply chain is not ossified. For example, back in 2017, 90% of sand was shipped by rail to the Permian from Minnesota, Illinois and Wisconsin. Today there are 50 “local” sand mines in the Permian basin, with 107MTpa of capacity. This has reduced transload cost, and allowed sand pricing to run as low as $20/ton recently. Further deflation may lie ahead.

Why it matters: deflation and CO2 reduction?

A fully decarbonized energy system may still require 85Mbpd of oil and 375TCF of gas, as per the conclusion of our research to date. Hence a focus of our research is to find improved technologies that can improve the efficieny and lower the CO2 intensity of oil and gas production.

We still see great productivity enhancements ahead for the shale industry, after reviewing over 1,000 technical papers. A 5% CAGR is possible from 2019’s baseline.

There is also great potential for shale to lower its CO2 intensity, potentially towards zero (Scope 1 and 2 basis), as argued in our recent research (below). The potential is further enhanced by using waste water to cultivate nature based solutions (also below).

Shale thus sets the marginal cost in oil markets, as our numbers require of 2.5Mbpd of shale growth each year from 2022-2025 (models below).

But nearer-term we see risks, that sentiment will sour around shale capex, while productivity could temporarily disappoint during the COVID recovery.

Bio-engineer plants to absorb more CO2?

Our roadmap towards ‘net zero’ requires 20-30GTpa of carbon offsets using nature based solutions, including reforestation and soil carbon. This short note considers whether the task could be facilitated by bio-engineering plants to sequester more CO2. We find exciting ambitions, and promising pilots, but the space is not yet investable.


What is bio-engineering? In 2016, scientists at DuPont gene-edited maize to grow more effectively in dry conditions. In 2017, researchers at the University of Oxford introduced a maize gene into rice plants, to increase the number of photosynthetic chloroplasts surrounding leaf veins. In 2019, scientists at Huazhong Agricultural University gene-edited rice to tolerate higher soil salinity. These are examples of bio-engineering: modifying the genetic code of plants for practical purposes.

How could it help? The world’s land plants absorb 123GTpa of carbon each year through photosynthesis. 120GTpa is re-released through respiration and decomposition. The result is a net sink of 3GTpa. For contrast, total anthropogenic carbon emissions are 12GTpa. It follows that small changes in the natural carbon cycle could materially shift carbon balances, per our climate model below.

The limitations of photosynthesis. Photosynthesis uses sunlight to convert CO2 into plant-sugars. It is only 1-5% inefficient, suggesting great potential for improvement. It is also vastly complex, comprising over 170 separate sub-stages. Amidst the complexity, RuBisCO is the most crucial limitation.

The limitations of RuBisCO. RuBisCO is an enzyme that catalyzes the reaction between CO2 and RuBP during photosynthesis. However, the RuBisCO enzyme is imprecise. It evolved at a time when the world’s atmosphere contained much lower oxygen concentrations. Unfortunately, under present atmospheric conditions, 20-35% of RuBisCO’s catalytic activity reacts O2 with RuBP, instead of CO2. The resultant products cannot continue their biochemical journey into becoming sugars. Instead, they are broken down in the process of photorespiration. Photorespiration uses up c30% of the total energy fixed by photosynthesis, and re-releases CO2 into the atmosphere. Photorespiration lowers agricultural yields by 20-40%.

What if RuBisCO could be helped to fix more CO2 and less oxygen? One way to do this is to increase the atmospheric concentration of CO2 in greenhouses, which can increase crop yields by c30%, per our note below. Another way is through bio-engineering.

Realizing Increased Photosynthetic Efficiency (RIPE) is a research institute funded by the Bill and Melinda Gates Foundation, UK foreign aid, the USDA and academic institutions. It aims to generate higher crop yields per unit of land, using bioscience. After ten years of research, RIPE has recently modified tobacco plants with genes from green algae and pumpkin plants to reduce the energy penalties from photorespiration. The result is that these modified tobacco plants grew 40% larger. A follow-up study may achieve plants that are 60% larger. Similar modifications are also being tested on soybeans and cowpea plants.

Researchers at the University of Wurzburg have also modelled metabolic pathways that may increase the photosynthetic efficiency of plants, potentially by as much as 5x, with results published in 2020. The work uses synthetic CO2-fixating carboxylases, RuBisCO from cyanobacteria, and additional methods of preventing fixed CO2 from being re-released. Experiments are planned to test the work in tobacco plants and thale cress.

Increasing photosynthetic efficiency and crop yields could be a crucial help, lowering the land intensity of crop production, which covers 1.7bn hectares of the globe today (data below). For comparison, our target of 15GTpa of reforestation will require 1.2bn hectares of land, hence any material reductions in cropland requirements will be helpful.

Sequestering more of the CO2. 50-95% of the carbon that is stored in natural eco-systems is not stored in biomass above ground, but in the soil. An emerging set of agricultural practices that restore soil carbon are explored in our research note below. But another option is to ‘program’ plants to grow deeper, larger roots, which push more carbon into soils.

The Land Institute in Salina, Kansas has developed a grain called Kernza. It is derived from an ancestor of wheat. It is perennial, rather than requiring yearly replanting. Its roots reach 3-6x further into the soil than conventional wheat, which connotes 3-6x more carbon storage, and also promotes drought resistance. It is being grown across 2,000 acres today.

The US Department of Energy also has a Laboratory of Environmental Molecular Sciences, aiming to increase carbon transfer into the soil. One team has developed a strain of rice that emits less methane, as it contains a gene from barley, reducing the carbon that the plant moves underground, which in turn reduces the carbon that can be metabolized by anaerobic bacteria. Studies are underway to reverse the process and increase the carbon that crops move underground.

The Salk Institute for Biological Studies is based in La Jolla, California. It is undertaking the most elaborate program to bioengineer crops and other plants, to sequester up to 20x more CO2 than conventional crops. Deploying these plants across 6% of the world’s agricultural lands are said to potentially offset 50% of global CO2 emissions.

Salk’s Harnessing Plants Initiative started in 2017 and aims to grow “ideal plants” with greater efficiency at pulling CO2 from the air, deeper roots that store more carbon underground, and other superior agricultural properties. One pathway is to promote production of suberin, the carbon-rich polymer in cork (but also found in melon rinds, avocado skins and plant roots). This is a waxy, water-resistant compound that degrades very slowly, thus remaining in the soil for centuries.

In 2019, Salk’s team discovered a gene, which determines whether roots will grow shallow or deep. It is called EXOCYST70A3, and affects the distribution of the PIN4 protein. PIN4 modulates the transport of auxin, a hormone that regulates root architecture. Different alleles of EXOCYST70A3 can increase root depth and plant resistance.

Technical readiness is the challenge for all of the bio-engineering methods discussed above. We generally begin integrating technologies into our models (first with high risking, later with lower risking) once they have surpassed TRL7. No bio-engineering method is there yet. Salk received a $35M grant in 2019, to accelerate its work, but prototype crop variants (corn, soybean, rice) are still not foreseen for five years. More pessimistically, scientists at RIPE have said it could take 15-years to deploy enhanced crops in the field. So while we will track this technology, it is not yet moving our models.

The Amazon tipping point theory?

The Amazon tipping point theory postulates that another 2-10% deforestation could make the world’s largest tropical rainforest too dry to sustain itself. Thus the Amazon would turn into a savanna, releasing 80GT of carbon into the atmosphere, single-handedly inflating atmospheric CO2 by 40ppm (to well above the 450ppm limit for 2C warming). This matters as Amazon deforestation rates have already doubled under Jair Bolsonaro’s presidency. This note explores implications, including international tensions, divestments, prioritization in a Biden presidency, and consequences for other transition technologies.


Global deforestation remains the single largest contributor to CO2e-emissions induced by man’s activities, more than the emissions from all passenger cars; and destruction of nature remains the largest overall contributor, more than all of China (chart below). This note is about a particularly worrying feedback loop in the Amazon rainforest, which could single-handedly wipe out the world’s remaining CO2 budget, effectively negating the impact of all other climate policies globally.

What is the Amazon tipping point theory?

The Amazon rainforest currently covers 5.5M square kilometers, comprising the largest, contiguous tropical forest in the world. 50% is in Brazil, and the remainder is spread around Peru, Colombia and half-a-dozen other South American countries. It contains 20% of all the planet’s plant and animal species, including 40,000 plant species alone.

Deforestation of the Amazon has reached 15-17% of its original area overall, and around 19% in Brazil. 800,000 square kilometers has been lost to-date (a land area equivalent to 2x California; or all of France plus Germany). Brazil’s annual deforestation rates have averaged 20,000 square kilometers per year from 1990-2004 (the land area of New Jersey or Slovenia). But the rate slowed to a trough of 5,000 square kilometers in 2014 due to improving environmental policies.

Unfortunately, more recently, Brazil’s deforestation rate has re-doubled (chart below). Jair Bolsonaro’s Presidency began in January-2019, following campaign pledges to ease environmental and land use regulations (which require 80% of legal Amazon land holdings to remain uncleared). Violations of these regulations are now said to be going unpunished. Bans on planting sugarcane in the Amazon have been lifted. Bolsonaro has even repudiated data published by Brazil’s own government agencies showing deforestation rates rising and accused actor and environmentalist, Leonardo DiCaprio of starting wildfires!

This matters because of the hydrology of the Amazon. Water in the basin tends to move from East to West. Each molecule typically falls as rainfall six times. It is repeatedly taken up by trees, transpired back into the atmosphere, and precipitated back down to Earth. Over half of the rain falling in the Amazon has originated from trees in the Amazon. It is a self-sustaining feedback loop.

The Amazon Tipping Point theory predicts that below some critical level of forest cover, this self-sustaining feedback loop will break. Less rainforest means less transpiration. Less transpiration means less rainfall. Less rainfall means less rainforest. Specifically, converting each hectare of forest to cropland reduces regional precipitation by 0.5M liters/year.

After the tipping point it is feared that the basin will transition into a savanna or scrubland. 50-100% of the forest cover would die back.

Unfortunately, this is not a ‘fringe’ theory. Many different technical papers acknowledge and model the risk, although specific climate models are imprecise, and do not always agree on timings and magnitudes. For example, the Western Amazon, closer to the Andes, might retain more forests than the East and Central parts of the basin. Another uncertainty is the moderating impacts of fire, as dryer forests will be more flammable, and thus more susceptible to slash-and-burn clearances, while raging fires will also reach further.

When is the tipping point? Various technical papers have estimated that the Amazon tipping point occurs when 20-25% of the forest has been cleared. This is an additional 2-10% from today’s levels, equivalent to deforesting another 100-600k acres, which could happen within 2-30 years.

What carbon stock is at risk of being released?

A typical forest contains around 300T of carbon per hectare (chart below). Thus 5.5M square kilometers of the Amazon is expected to contain 165GT of carbon. About 40% of the carbon is usually stored in trees (estimated at 60-80GT in the Amazon) and 60% is stored in roots and soils, which degrades more slowly. Hence, if just half of the remaining Amazon disappears, this would slowly release c80GT of carbon into the atmosphere.

Each billion tons (GT) of carbon released into the atmosphere is equivalent to raising atmospheric CO2 by around 0.5ppm. Hence a 80GT carbon release from the Amazon would by itself raise atmospheric CO2 from 415ppm today to around 455ppm. This single change (notwithstanding the continued and unmitigated burning of fossil fuels) would tip the world above the 450ppm threshold needed to keep global warming to an estimated 2-degrees (climate model below).

Can the tipping point be averted?

The solution to Amazon tipping points is technically simple: stop burning down forests and start re-planting them. This does not require electrolysing water molecules into hydrogen, smoothing volatility in renewable-heavy grids, or developing next-generation batteries. It requires something much harder: international diplomacy.

Inflammatory statements? In September-2019, Bolsonaro defended his environmental policies in a speech at the UN General Assembly. International critics were accused of assaulting Brazil’s sovereignty. Brazil considers itself free to prioritize economic development over environment.

Forest for ransom? In the past, Western countries have actually paid Brazil to safeguard its rainforests, although this arrangement has now fallen apart. Specifically, the ‘Amazon Fund’ was created in 2008. It is managed by Brazil’s state-owned development bank, BNDES. $1.3bn has been donated to the fund, from Norway (94%), Germany (5%) and Petrobras (1%). But after taking office, Bolsonaro has packed the fund’s steering committee with members of his inner circle, and in May-2019, he started using the Fund to compensate land developers whose lands were confiscated for environmental violations. Hence Norway and Germany suspended fund payments.

Divestment and trade tensions? As Brazil’s stance on the Amazon has grown more confrontational, it is possible that decision-makers may distance themselves from the country. Global investment funds have threatened to divest. (Could Brazil even surpass the coal industry as the divestment movement’s whipping boy?). Multi-national corporations may also be more cautious around investing in the country (but probably at the margin). Finally, Amazon deforestation is said to endanger future trade deals.

The Biden Factor? President-elect Biden may also seek to influence the Amazon issue. Biden stated the world should collectively offer Brazil $20bn to stop Amazon deforestation and threaten economic consequences for refusing. An executive order re-entering the Paris Climate Agreement would also help the situation (Brazil had actually committed to restoring 12M hectares of native vegetation under the accord). It will be interesting to see how Biden balances climate-focused priorities in the US with this arguably more urgent issue abroad.

Crucial Conclusions? If the Amazon surpasses its tipping point, there would be no chance of limiting atmospheric CO2 to 450ppm or preventing a catastrophic loss of biodiversity. Diplomacy is difficult. But fortunately, decision-makers can take measures into their own hands. Our note below profiles tree-planting charities. This is the lowest-cost decarbonization option we have found in all of our research. It restores nature, including the Amazon. Ultimately, we have argued that restoring nature may the most practical route to achieving climate objectives, while ‘bursting the bubble’ of other transition technologies.