Category: Report

A new wave of direct air capture (DAC) companies has been emerging rapidly since 2019, targeting 50-90% lower costs and energy penalties than incumbent S-DAC and L-DAC, potentially reaching $100/ton and 500kWh/ton in the 2030s. Five opportunities excite us and warrant partial de-risking in this 19-page report. Could DAC even beat batteries and hydrogen in smoothing renewable-heavy grids?

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Direct air capture (DAC) aims to pull CO2 out of atmospheric air in order to mitigate climate change caused by the greenhouse effect.

Historically, we have found DAC challenging to de-risk, due to high costs and high energy penalties, which are quantified on pages 2-4.

But the physics of DAC suggest that next-generation sorbents could deliver $100/ton costs and 500kWh/ton energy use (page 5).

Liquid DAC (L-DAC) uses alkali solvents to react with ambient CO2, and has gained prominence through Carbon Engineering and Occidental. Advantages and challenges of L-DAC are reviewed on page 6.

Solid DAC (S-DAC) uses sorbents to react with ambient CO2. Advantages and challenges of S-DAC are reviewed on page 7.

Next-generation sorbents are where we see the greatest potential for DAC to improve in the future. Exciting numbers on page 8.

Passive DAC and mineralization are two further options to lower the costs of blowing air and compressing CO2 for disposal (pages 9-12).

Can DAC demand shift to backstop renewables? Interestingly, we think the costs and energy penalties of decarbonizing hydrocarbons with DAC could be materially less than via green hydrogen (page 13).

Can DAC costs get to $100/ton? Our DAC economic model captures the capex costs, utilization rates, energy use, energy cost and opex that would be needed (pages 14-15).

Leading DAC companies have trebled in number over the past five years, concentrating around the next-generation opportunities above. Highlights from our DAC company screen are on pages 16-19.

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Over the past decade, costs have deflated by 85% for lithium ion batteries, 75% for solar and 25% for onshore wind. Now new energies costs are entering a new era. Future costs are mainly determined by materials. Bottlenecks matter. Deflation is slower. Even higher-grade materials are needed to raise efficiency. This 14-page note explores the new age of materials, how much new energies deflation is left, and who benefits?

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Over the past decade, new energies have seen remarkable deflation. Installed costs of a utility-scale solar project have fallen 75% from $4,000/kW to $1,000/kW. Lithium ion batteries have fallen by 85% from over $800/kWh to $150/kWh. Onshore wind has deflated by 20% from $1,900/kW in 2012 to $1,500/kW in 2022, although offshore wind, as an exception, has reinflated. How has this happened? And what happens from here?

The scale-up to mass manufacturing has been the largest driver of new energies deflation, reducing the manufacturing costs by up to 90% over the past decade. This is quantified on pages 2-4 for each new energies technology. However, manufacturing costs are now just c25% of total new energies costs and so future deflation must come from elsewhere.

The age of materials has arrived. For the first time, in 2022, materials were over 50% of the total installed cost of new energies, in aggregate, up from just 17% of total costs a decade ago, and mainly because manufacturing costs fell away. Our outlook for these materials and their bottlenecks are presented on pages 5-6.

Efficiency gains offer the best opportunity for further deflation. Rising efficiency lowers all cost lines. Including materials costs. This is illustrated in detail for solar. But we think the outlook for efficiency gains is very different among different new energies, per pages 7-10.

High-grading versus thrifting. A change of view in this report is that we see high-grading of materials to be more likely than thrifting. This helps improve efficiency. For example, there are routes to using 20-30% less silver in solar modules, but new HJT cells are actually using 80-100% more silver, because this helps to deliver efficiency gains that deflate all of the other cost lines. The same is true in batteries. And does this make advanced materials less commoditized and higher margin? Further examples and discussion on pages 11-12.

Which emerging new energies technologies could see more versus less deflation? Some ideas are on page 13.

Advanced materials companies for the energy transition have stood out in our research, especially as new energies enter the new age of materials. Our top ten ideas are summarized, with links to further research, on page 14.

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Using a commodity more efficiently can cause its demand to rise not fall, as greater efficiency opens up unforeseen possibilities. This is Jevons’ Paradox. Our 16-page report finds it is more prevalent than we expected. Efficiency gains underpin 25% of our roadmap to net zero. To be effective, commodity prices must rise, otherwise rebound effects raise demand.

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Jevons’ Paradox was articulated by William Stanley Jevons, in 1865, after observing a +8x improvement in steam engine efficiency from 1710 to 1860, causing British coal use not to fall, but to rise +18x to 80MTpa, and +6x in per capita terms.

The Jevons Effect is a particular type of rebound effect. All rebound effects involve new demand counteracting the impacts of efficiency improvements (i.e., 3% efficiency gain – 1% rebound effect = 2% net energy reduction). But in the Jevons Effect, specifically, the new demand is of a larger magnitude than the efficiency gain itself (i.e., 3% efficiency gain – 5% rebound effect = 2% overall increase in energy demand).

The Jevons Effect matters as our roadmap to net zero wants to see 25% of all decarbonization coming from efficiency gains, while other forecasters have even proposed that a large step-up in efficiency gains will see net global energy demand decline by as much as 20% by 2050 (although this assumption looks dangerously wrong to us, note here).

This report aims to quantify the Jevons Effect, objectively, using as much data as possible from our library of 1,000 data-files and models, built up over the past five-years. Overall, we found the Jevons Effect to be much more prevalent than we expected.

Where the Jevons Effect occurs, across seven large areas reviewed in the report, each 1% improvement in energy efficiency has coincided with a 0.7% net increase in energy demand. In other areas, we also find rebound effects, where each 1% improvement in energy efficiency is muted by a c0.5% rebound. These may be useful rules of thumb.

Examples considered in the report include the rise of the internet (pages 5-6), commercial lighting (pages 7-8), material possessions (page 9), US automotive fuel economy standards (pages 10-11), developed world aviation (page 12), US air conditioning (page 13-14) and US residential electricity use (page 15).

Our conclusions from the analysis suggest it will be harder to use energy efficiency initiatives as a route to decarbonization, unless underlying commodity prices also trend higher over time.

Otherwise energy demand will surprise to the upside. Vast new markets will also be unlocked by efficiency initiatives. Some of these new and evolving markets are also linked to human progress and it would be quite sad if they were stifled by decarbonization aspirations.

This 17-page note makes the largest changes to our shale forecasts in five years, amidst evidence that productivity growth is slowing. Productivity now peaks after 2025, precisely as energy markets hit steep undersupply. Our shale outlook still sees +1Mbpd/year of liquids potential through 2030, but it is back loaded, and requires persistently higher oil prices?

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We spent summer of 2017, reading several hundred technical papers from the US shale industry, and published a 200-page book arguing shale was a “new technology paradigm, a digital revolution, offering 50-70% further productivity gains” as ever-improving productivity unlocked the potential to add 2Mbpd of supply each year, and ultimately ramp past 25Mbpd by 2030 in a completely unconstrained scenario. This was 2017. Most people believed shale was ‘dead’ at $60/bbl. Indeed, forecasters such as the EIA/IEA were projecting 5-7Mbpd of shale oil in 2025-30.

This 17-page note contains the largest revisions to our shale outlook since 2017. It is hard to ‘fit a depletion curve’ onto US shale productivity. But in 2017, we would have picked the dark green line (chart above), with 200bn bbls of liquid resources remaining, which simplistically, at a 20-year RP ratio, would land in the 25-30Mbpd production range. Our latest forecasts are shown by the dark blue line and maybe 100bn bbls remain.

Quantitative evidence for slowing productivity is discussed on pages 4-7. Productivity data has moved sideways for 3-years now in the Permian, but there are also important trends and data interpretation issues.

Qualitative evidence for slowing productivity is discussed on pages 8-10. We reviewed the technical papers from URTEC in 2023 (one E&P really stood out). Productivity improves more slowly from here?

Changes to our forecasts for productivity, shale production growth, ultimate production potential, year-by-year supply, activity, oil prices and shale E&P free cash flow are all discussed on pages 10-16.

How wrong were we? In 2017, we heavily caveated our shale forecasts, noting that “world-changing trends are rarely realized in smooth trajectories” and the most likely reason we would be wrong would be because shale’s smooth production growth would be disrupted by “periodic oil price volatility”. At the time we envisaged the volatility to stem from OPEC policies. Ironically, it was COVID, war, rate rises and the ESG movement, while OPEC itself has recently been acting as a stabilizing force! The de-railing impacts of volatility may be important to consider for other energy transition technologies that are widely hoped to ramp up in a perfect, uninterrupted straight line (pages 17-18).

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Lighting is 2% of global energy, 6% of electricity, 25% of buildings’ energy. LEDs are 2-20x more efficient than alternatives. Hence this 16-page report presents our outlook for LEDs in the energy transition. We think LED market share doubles to c100% in the 2030s, to save energy, especially in solar-heavy grids. But demand is also rising due to ‘rebound effects’ and use in digital devices. We have screened 20 mature and (mostly) profitable pure plays.

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LEDs generate light as a direct current passes across a PN junction, and electrons recombine with holes. Loosely, this makes them ‘solar panels in reverse’. A concise overview of the physics and different LED components — dyes, phosphors, packages, lamps and luminaires — is on pages 2-3.

What outlook for LEDs? We think LEDs will ascent from <50% adoption today to almost 100% in the early 2030s. Market sizing context, reasoned explanations and comparison with the pace of other technology transitions, are on pages 4-5.

Regulations support this unusually strong outlook. New regulations came into force in summer of 2023, banning non-LEDs in the US (July-23) and Europe (September-23).

Rebound effects are also growing the market, as more efficient lighting creates new demand for lighting. The Sphere at the Venetian contains 54,000m2 of Jevons paradox. More broadly, LEDs are used in the rise of electric vehicles and the rise of the internet (pages 6-7).

But the main reason for writing this market outlook for LEDs is that all roads lead to Rome. Several TSE research reports in 2023 augur well for LEDs, and an accelerating pace of adoption. The top three drivers are explored on pages 8-10.

LED costs and payback periods? As a rule of thumb, the higher the night-time electricity price, the larger the budget for efficient LED lighting. Costs, payback periods and IRRs are stress tested on pages 11-12.

Light infantry: leading companies? 20 leading LED and lighting companies derive $40bn of cumulative revenues from across the value chain, with typical operating margins around 8%. Many are midcaps. But in our view, it is unusual to find growing, profitable companies with pure-play exposure to an obvious energy transition theme (solar in reverse!) on undemanding multiples (pages 13-15).

Light conclusions. New technologies, comments about China exposure, and our overall outlook for LEDs are spelled out on page 16.

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This 14-page report re-visits our wind industry outlook. Our long-term forecasts are reluctantly being revised downwards by 25%, especially for offshore wind, where levelized costs have reinflated by 30% to 13c/kWh. Material costs are widely blamed. But rising rates are the greater evil. Upscaling is also stalling. What options to right this ship?

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For some mysterious reason, energy commentators often like to lump wind and solar together, under the rubric ‘renewables’. Why though? In our view, solar and wind are really about as similar as pasta and turnips, whose main commonality is that in the world of carbohydrates they are “both not bread”. Vast differences between wind and solar, their costs, their technology gains, and their outlooks are discussed on page 3.

Upscaling wind turbines is hitting its limits. Two years ago, in a note entitled Offshore wind: can costs follow Moore’s Law?, we noted that “The IEA expects levelized costs for offshore wind in Europe to deflate from 7.5c/kWh to 2.5c/kWh by 2050. This assumption looks dangerously wrong to us… Physics punishes larger turbines. They incur greater physical stresses. We illustrate this point by reviewing 50 recent patents from Siemens Gamesa”. We gently recommend re-visiting this long-forgotten research note. Key points are re-capped on page 4.

What are the realistic costs of offshore wind in 2023? Why have costs re-inflated by over 30% since 2019? How much is one-off material cost reinflation, versus higher interest rates? What are the economic sensitivities? We have expanded our commodity price databases and offshore wind models to answer these questions on pages 6-9.

What forecasts for global offshore wind capacity and offshore wind installations? What targets have been published in different regions globally? How much can we de-risk delivery of those targets, amidst the current industry outlook? And what would we need to see, for the tide to turn, to start getting more excited about the offshore wind industry outlook again? Our answers are on pages 10-12.

How is our roadmap to net zero changing? The overarching goal in our research is to model what we consider to be the ‘most likely’ route to Net Zero by 2050. Our long-term wind forecasts are being revised downwards by around 25%. Accordingly, we see a larger share of electricity sector decarbonization coming from solar (large 10% upgrades by 2050, in our models here), and to a lesser extent, gas and CCS.

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This 14-page report explores whether global industrial activity is set to become ever more concentrated in a few advantaged locations, especially the US Gulf Coast, China and the Middle East. Industries form ecosystems. Different species cluster together. Elsewhere, in our view, you can no more re-shore a few select industries than introduce dung beetles onto the moon. These mega-trends matter for economic forecasts and valuations.

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Over the past five years, we have mapped 150 industrial value chains for our energy transition models. As a general observation, value chains form ecosystems, clustering together, as outputs from one industrial process are inputs for the next. This is under-appreciated and has profound consequences for the world.

Direct links. A single commodity chemical facility often supports 20 downstream processes. While a naphtha cracker produces seven main petrochemical feedstocks, and offtakers must be found for all seven. To illustrate the inherent clustering tendencies of industrial ecosystems, some of our favorite examples and rules of thumb are spelled out on pages 2-10.

Surprising links. Some semiconductor materials are produced at larger metals refineries (for example, indium is a by-product of refining zinc for galvanized steel), and in turn, metals refineries often tend to cluster around oil refineries (for petcoke, industrial gases, heat).

Global transportation is always possible, but typically adds 3-5% in transportation costs of individual materials, eating into c20% typical EBIT margins, cascading along industrial value chains that can include up to 20 intermediates, and introducing risks (page 8).

Network effects allow larger industrial ecosystems to share ever better infrastructure. For example, the US Gulf Coast already has 900 miles of hydrogen pipelines. Yet here in the Baltics, we do not have a complete 2-lane highway to Western Europe (video below, more on page 9).

The US Gulf Coast stands out. It has a unique combination of geopolitical security and stability, low energy costs, a coastal location, world-class infrastructure, world class companies, and a credible long-term route to decarbonization. Our growing view is that the energy transition will see activity boom in the US Gulf Coast and its surrounding industrial ecosystem, with consequences for economic growth and valuations (pages 11-12).

Elsewhere in the developed world, we remain concerned that reshoring efforts will fall flat, due to high energy costs and unclear policies. You cannot re-shore “just one or two select industries like solar” any more than you can introduce dung beetles onto the moon. Viable conditions are needed for an entire industrial ecosystem (page 13).

Ecosystem approach? If industrial activity does become ever more concentrated in the energy transition, then investors may wish to consider geographic alignments of companies (some of our favorite examples are on page 14); companies may wish to grow their exposure to thriving industrial ecosystems (and exit waning regions); while policymakers should prioritize competitiveness.

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HJT solar modules are accelerating, as they are efficient and easy to manufacture. But HJT could also be a kingmaker for Indium, used in transparent and conductive thin films (ITO). Our forecasts see primary Indium demand rising 4x by 2050. Indium is 100x rarer than Rare Earth metals. It could be a bottleneck. This 16-page note explores the costs and benefits of using Indium in HJT solar, and who benefits as solar evolves?

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Solar energy is a semiconductor technology and thus it evolves quickly. Last year, we saw interest accelerate in TOPCon cells. This year, interest is accelerating in heterojunctions (HJT), due to even higher efficiency and simpler manufacturing (as explained on page 2).

What is an HJT solar cell? The purpose of pages 3-4 in the PDF is to explain how HJTs work, concisely, using numbers, so that a reasonably science-literate decision maker can understand key advantages versus incumbent solar cells that comprised 80-90% of modules sold in 2019-21.

The very short answer is that HJTs benefit from conjoining different semiconductors, with different bandgaps, to capture more energy across the spectrum of incoming light. The higher bandgap semiconductor is amorphous Si:H. But it has low conductivity. And thus, for current to reach the electrical contacts, a transparent conducive oxide (TCO) thin film is needed. The most common TCO is ITO. ITO is 74% Indium (page 5).

What demand for Indium in HJT solar, and what will HJT solar do to total global Indium demand? There are scenarios where HJT solar cells could absorb 1-4x total global primary indium production. Modelling the energy transition is an exercise in minimizing overall ridiculousness. Hence our own models and assumptions are on pages 6-7.

How is Indium produced for ITO thin films and HJT solar cells? We describe the supply chain, including the association with zinc refining, and discuss Indium costs ($/kg), Indium energy use (MWH/kg) and Indium CO2 intensity (kg/kg) on pages 8-10.

Do Indium costs detract from solar? Some commentators argue that high cost materials, energy-intensive materials or CO2-intensive materials count against ramping up solar. Indium is a very high cost, energy intensive and CO2 intensive material. But the numbers on pages 11-12 show that HJT solar designs repay these costs about 10-100x over.

Will Indium be a bottleneck for HJT solar? The rise of HJT solar cells is compared with other bottlenecks in our solar bill of materials, quadrupling global demand for Indium, while using double the silver of incumbent solar cells. Bottlenecks are contrasted on page 13.

Leading producers of Indium? Indium could be a large bottleneck. Excitement over HJTs is also accelerating at a time when Indium prices are relatively low and many industrial metals are unloved in 2023’s macro environment. We have screened 35 indium producers. Eight listed companies are discussed on pages 14-16.

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Polyurethanes are elastic polymers, used for insulation, electric vehicles, electronics and apparel. This $75bn pa market expands 3x by 2050. But could energy transition double historically challenging margins, by freeing up feedstock supplies? This 13-page note builds a full mass balance for the 20+ stage polyurethane value chain and screens 20 listed companies.

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Polyurethanes are elastic and foam-able polymers, formed when diisocyanates combine with polyols. Specifically, a diisocyanate has the symmetrical chemical structure O=C=N-R1-N=C=O. (That N=C=O ‘cyanate’ group is also referred to as a ‘urethane’). Similarly, a di-ol (the simplest polyol) has the structure H-O-R2-O-H. Key chemistry on page 2.

Global demand for polyurethanes will be around 25MTpa in 2023 and treble by 2050, including for insulation, electric vehicles, power electronics, data-centers underpinning the rise of AI and in consumer applications, from Indian mattresses to European Mamils. Our outlook on these different uses of polyurethane is on pages 3-5.

How is polyurethane made? Producing polyurethanes is a 20+ stage process, starting with oil and gas. The real work behind this note is to build up a full mass balance across this production process, so that we can map the amount of different input materials per kg of finished polyurethane products (pages 6-7).

What are the costs of polyurethane? The production costs of polyurethane will tend to average $2.5-3.0/kg at $65/bbl oil and $6/mcf input gas. Sensitivities to input oil and gas prices, and costs of decarbonization via using low-carbon hydrogen are broken down in our model here and discussed on pages 7-8.

Will the energy transition deflate feedstock costs for polyurethane? Our answer is emphatically yes, although the extent varies by geography, timing matters, and the answer also depends on the integration of producers (i.e., what input materials do they consume). Some polyurethanes can benefit from low-carbon hydrogen or directly absorb CO2. This is all mapped on pages 9-10.

Who are the leading companies in polyurethanes? 20 large and listed companies control c80% of the total global polyurethane market, and the five largest companies control half of the market. We have screened polyurethane producers, and mapped their exposure to growing markets and deflating feedstocks on pages 11-13.

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There is an economic paradox where shifting towards lower cost supply sources can cause inflation in the total costs of supply. Renewable-heavy grids are subject to this levelized cost paradox, as they have high fixed costs and falling utilization. As power prices rise, there are growing incentives for self-generation. Energy transition requires a balanced approach.

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If you rent an apartment for $100 per night, and then you also start renting a second apartment for $50 per night, then your total rental costs go up by 50%, not down by 50%. The simple levelized cost of the second apartment is 50% lower than the first. But overall costs rise as the costs of the first apartment are fixed, and renting the second apartment erodes the utilization rate of the first one. Similar examples of ‘inverse deflation’ are contrasted on page 2 of this 12 page report.

Renewable heavy grids may also be prone to this levelized cost paradox. Power grids have fixed costs (e.g., per GW of capacity, including due to statutory rate of return regulation). Renewables reduce grid utilization rates because their load factors are low and their output is volatile. Unit costs rise when fixed costs are spread across lower utilization. Some countries that ramped renewables fastest now have some of the highest power prices (data here). Facts and figures on pages 3-6.

A deep dive into grid utilization rates? The average developed world power grid had a utilization factor of 55% at peak in 1998, which has since decreased to 38% in 2022 (chart above, data here). Reasons for the decline in grid utilization are on pages 7-8.

What consequences from this levelized cost paradox? We expect rising power prices and inflation (page 9), growing incentives for power consumers to disconnect from the grid and self-generate where they can (page 10), tightening demand for several capital goods categories (also on page 10) and resultant feedback loops that further elevate electricity prices for remaining power grid customers (page 11).

Achieving an energy transition requires a balanced and pragmatic approach. Our top five suggestions are spelled out on pages 12-13.

To be 100% clear, this note is not ‘anti-renewables’. Far from it. Wind and solar generation must rise 8.5x in our roadmap to net zero, to reach 30,000 TWH of supply in 2050, or 25% of all useful energy supplies. This note is simply anti-oversimplified levelized cost analysis. Rather, we think that a balanced, pragmatic ‘all of the above’ approach is more likely to accelerate real decarbonization progress.