The emerging technology of quantum computing could revolutionize the fight against climate change, transforming the economics of decarbonization and becoming a major factor in limiting global warming to the target temperature of 1.5°C (see sidebar “What is quantum computing?”).
Even though the technology is in the early stages of development—experts estimate the first generation of fault-tolerant quantum computing1 will arrive in the second half of this decade—breakthroughs are accelerating, investment dollars are pouring in, and start-ups are proliferating.2 Major tech companies have already developed small, so-called noisy intermediate-scale quantum (NISQ) machines, though these aren’t capable of performing the type of calculations that fully capable quantum computers are expected to perform.
Countries and corporates set ambitious new targets for reducing emissions at the 2021 United Nations Climate Change Conference (COP26). Those goals, if fully met, would represent an extraordinary annual investment of $4 trillion by 2030, the largest reallocation of capital in human history. But the measures would only reduce warming to between 1.7°C and 1.8°C by 2050, far short of the 1.5°C level believed necessary to avoid catastrophic, runaway climate change.
Meeting the goal of net-zero emissions that countries and some industries have committed to won’t be possible without huge advances in climate technology that aren’t achievable today. Even the most powerful supercomputers available now are not able to solve some of these problems. Quantum computing could be a game changer in those areas. In all, we think quantum computing could help develop climate technologies able to abate carbon on the order of 7 gigatons a year of additional CO2 impact by 2035, with the potential to bring the world in line with the 1.5°C target.
Quantum computing could help reduce emissions in some of the most challenging or emissions-intensive areas, such as agriculture or direct-air capture, and could accelerate improvements in technologies required at great scale, such as solar panels or batteries. This article offers a look at some of the breakthroughs the technology could permit and attempts to quantify the impact of leveraging quantum-computer technology that are expected become available this decade.
Solving so far insoluble problems
Quantum computing could bring about step changes throughout the economy that would have a huge impact on carbon abatement and carbon removal, including by helping to solve persistent sustainability problems such as curbing methane produced by agriculture, making the production of cement emissions-free, improving electric batteries for vehicles, developing significantly better renewable solar technology, finding a faster way to bring down the cost of hydrogen to make it a viable alternative to fossil fuels, and using green ammonia as a fuel and a fertilizer.
Addressing the five areas designated in the Climate Math Report as key for decarbonization, we have identified quantum-computing use cases that can pave the way to a net-zero economy. We project that by 2035 the use cases listed below could make it possible to eliminate more than 7 gigatons of CO2 equivalent (CO2e) from the atmosphere a year, compared with the current trajectory, or in aggregate more than 150 gigatons over the next 30 years (Exhibit 1).
Shift 1: Electrifying our lives
Batteries are a critical element of achieving zero-carbon electrification. They are required to reduce CO2 emissions from transportation and to obtain grid-scale energy storage for intermittent energy sources such as solar cells or wind.
Improving the energy density of lithium-ion (Li-ion) batteries enables applications in electric vehicles and energy storage at an affordable cost. Over the past ten years, however, innovation has stalled—battery energy density improved 50 percent between 2011 and 2016, but only 25 percent between 2016 and 2020, and is expected to improve by just 17 percent between 2020 and 2025.
Recent research3 has shown that quantum computing will be able to simulate the chemistry of batteries in ways that can’t be achieved now. Quantum computing could allow breakthroughs by providing a better understanding of electrolyte complex formation, by helping to find a replacement material for cathode/anode with the same properties and/or by eliminating the battery separator.
As a result, we could create batteries with 50 percent higher energy density for use in heavy-goods electric vehicles, which could substantially bring forward their economic use. The carbon benefits to passenger EVs wouldn’t be huge, as these vehicles are expected to reach cost parity in many countries before the first generation of quantum computers is online, but consumers might still enjoy cost savings.
In addition, higher-density energy batteries can serve as a grid-scale storage solution. The impact on the world’s grids could be transformative. Halving the cost of grid-scale storage could enable a step change in the use of solar power, which is becoming economically competitive but is challenged by its generation profile. Our modeling suggests that halving the cost of solar panels could increase their use by 25 percent in Europe by 2050 but halving both solar and batteries might increase solar use by 60 percent (Exhibit 2). Geographies without such a high carbon price will see even greater impacts.
Through the combination of use cases described above, improved batteries could bring about an additional reduction in carbon dioxide emissions of 1.4 gigatons by 2035.
Shift 2: Adapting industrial operations
Many parts of the industry produce emissions that are either extremely expensive or logistically challenging to abate.
Cement is a case in point. During calcination in the kiln for the process of making clinker, a powder used to make cement, CO2 is released from raw materials. This process accounts for approximately two-thirds of cement emissions.
Alternative cement-binding materials (or “clinkers”) can eliminate these emissions, but there’s currently no mature alternative clinker that can significantly reduce emissions at an affordable cost.
There are many possible permutations for such a product, but testing by trial and error is time-consuming and costly. Quantum computing can help to simulate theoretical material combinations to find one that overcomes today’s challenges—durability, availability of raw materials and efflorescence (in the case of alkali-activated binders). This would have an estimated additional impact of 1 gigaton a year by 2035.
Shift 3: Decarbonizing power and fuel
Solar cells will be one of the key electricity-generation sources in a net-zero economy. But even though they are getting cheaper, they still are far from their theoretical maximum efficiency.
Today’s solar cells rely on crystalline silicon and have an efficiency on the order of 20 percent. Solar cells based on perovskite crystal structures, which have a theoretical efficiency of up to 40 percent, could be a better alternative. They present challenges, however, because they lack long-term stability and could, in some varieties, be more toxic. Furthermore, the technology has not been mass produced yet.
Quantum computing could help tackle these challenges by allowing for precise simulation of perovskite structures in all combinations using different base atoms and doping, thereby identifying higher efficiency, higher durability, and nontoxic solutions. If the theoretical efficiency increase can be reached, the levelized cost of electricity (LCOE) would decrease by 50 percent.
By simulating the impact of cheaper and more efficient quantum-enabled solar panels, we see a significant increase in use in areas with lower carbon prices (China, for example). This is also true of countries in Europe with high irradiance (Spain, Greece) or poor conditions for wind energy (Hungary). The impact is magnified when combined with cheap battery storage, as discussed above.
This technology could abate an additional 0.4 gigatons of CO2 emissions by 2035.
Hydrogen is widely considered to be a viable replacement for fossil fuels in many parts of the economy, especially in industry where high temperature is needed and electrification isn’t possible or sufficient, or where hydrogen is needed as a feedstock, such as steelmaking or ethylene production.
Before the 2022 gas price spikes, green hydrogen was about 60 percent more expensive than natural gas. But improving electrolysis could significantly decrease the cost of hydrogen.
Polymer electrolyte membrane (PEM) electrolyzers split water and are one way to make green hydrogen. They have improved in recent times but still face two major challenges.
- They are not as efficient as they could be. We know that “pulsing” the electrical current rather than running it constantly improves efficiency in lab environments, but we don’t understand this enough to get it to work at scale.
- Electrolyzers have delicate membranes that allow the split hydrogen to pass from the anode to the cathode (but keeps the split oxygen out). In addition, they have catalysts that speed up the overall process. Catalysts and membranes do not yet interact well. The more efficient we make the catalyst, the more it wears down the membrane. This doesn’t have to be the case, but we don’t understand the interactions well enough to design better membranes and catalysts.
Quantum computing can help model the energy state of pulse electrolysis to optimize catalyst usage, which would increase efficiency. Quantum computing could also model the chemical composition of catalysts and membranes to ensure the most efficient interactions. And it could push the efficiency of the electrolysis process up to 100 percent and reduce the cost of hydrogen by 35 percent. If combined with cheaper solar cells discovered by quantum computing (discussed above), the cost of hydrogen could be reduced by 60 percent (Exhibit 3).
Increased hydrogen use as a result of these improvements could reduce CO2 emissions by an additional 1.1 gigatons by 2035.
Ammonia is best known as a fertilizer, but could also be used as fuel, potentially making it one of the best decarbonization solutions for the world’s ships. Today, it represents 2 percent of total global final energy consumption.
For the moment, ammonia is made through the energy-intensive Haber-Bosch process using natural gas. There are several options for creating green ammonia, but they rely on similar processes. For example, green hydrogen can be used as a feedstock, or the carbon dioxide emissions that are caused by the process can be captured and stored.
However, there are other potential approaches, such as nitrogenase bioelectrocatalysis, which is how nitrogen fixation works naturally when plants take nitrogen gas directly from the air and nitrogenase enzymes catalyze its conversion into ammonia. This method is attractive because it can be done at room temperature and at 1 bar pressure, compared with 500°C at high pressure using Haber-Bosch, which consumes large amounts of energy (in the form of natural gas) (Exhibit 4).
Innovation has reached a stage where it might be possible to replicate nitrogen fixation artificially, but only if we can overcome challenges such as enzyme stability, oxygen sensitivity, and low rates of ammonia production by nitrogenase. The concept works in the lab but not at scale.
Quantum computing can help simulate the process of enhancing the stability of the enzyme, protecting it from oxygen and improving the rate of ammonia production by nitrogenase. That would result in a 67 percent cost reduction over today’s green ammonia produced through electrolysis, which would make green ammonia even cheaper than traditionally produced ammonia. Such a cost reduction could not only lessen the CO2 impacts of the production of ammonia for agricultural use but could also bring forward the breakeven for ammonia in shipping—where it is expected to be a major decarbonization option—forward by ten years.
Using quantum computing to facilitate cheaper green ammonia as a shipping fuel could abate an additional CO2 by 0.4 gigatons by 2035.
Shift 4: Ramping up carbon capture and carbon sequestration activity
Carbon capture is required to achieve net zero. Both types of carbon capture—point source and direct—could be aided by quantum computing.
Point-source carbon capture allows CO2 to be captured directly from industrial sources such as a cement or steel blast furnace. But the vast majority of CO2 capture is too expensive to be viable for now, mainly because it is energy intense.
One possible solution: novel solvents, such as water-lean and multiphase solvents, which could offer lower-energy requirements, but it is difficult to predict the properties of the potential material at a molecular level.
Quantum computing promises to enable more accurate modeling of molecular structure to design new, effective solvents for a range of CO2 sources, which could reduce the cost of the process by 30 to 50 percent.
We believe this has significant potential to decarbonize industrial processes, which could lead to additional decarbonization of up to 1.5 gigatons a year, including cement. If the cement clinker approach described above is successful, this would still have an effect of 0.5 gigatons a year, due to fuel emissions. In addition, alternative clinkers may not be available in some regions.
Direct-air capture, which involves sucking CO2 from the air, is a way to address carbon removals. While the Intergovernmental Panel on Climate Change says this approach is required to achieve net zero, it is very expensive (ranging from $250 to $600 per ton a day today) and even more energy intensive than point-source capture.
Adsorbents are best suited for effective direct-air capture and novel approaches, such as metal organic frameworks, or MOFs, have the potential to greatly reduce the energy requirements and the capital cost of the infrastructure. MOFs act like a giant sponge—as little as a gram can have a surface area larger than a football field—and can absorb and release CO2 at far lower temperature changes than conventional technology.
Quantum computing can help advance research on novel adsorbents such as MOFs and resolve challenges4 arising from sensitivity to oxidation, water, and degradation caused by CO2.
Novel adsorbents that have a higher adsorption rate could reduce the cost of technology to $100 per ton of CO2e captured. This could be a critical threshold for uptake, given that corporate climate leaders such as Microsoft5 have publicly announced an expectation to pay $100 a ton long term for the highest-quality carbon removals. This would lead to an additional CO2 reduction of 0.7 gigatons a year by 2035.
Shift 5: Reforming food and forestry
Twenty percent of annual greenhouse-gas emissions come from agriculture—and methane emitted by cattle and dairy is the primary contributor (7.9 gigatons of CO2e, based on 20-year global-warming potential).
Research has established that low-methane feed additives could effectively stop up to 90 percent of methane emissions. Yet applying those additives for free-range livestock is particularly difficult.
An alternative solution is an antimethane vaccine that produces methanogen-targeting antibodies. This method has had some success in lab conditions, but in a cow’s gut—churning with gastric juices and food—the antibodies struggle to latch on to the right microbes. Quantum computing could accelerate the research to find the right antibodies by precise molecule simulation instead of a costly and long trial-and-error method. With estimated uptake determined according to data from the US Environmental Protection Agency, we arrive at carbon reduction of up to an additional 1 gigaton a year by 2035.
Another prominent use case in agriculture is green ammonia discussed as a fuel above, where today’s Haber-Bosch process uses large amounts of natural gas. Using such an alternative process could have an additional impact of up to 0.25 gigatons a year by 2035, replacing current conventionally produced fertilizers.
Additional use cases
There are many more ways that quantum computing could be applied to the fight against climate change. Future possibilities include identification of new thermal-storage materials, high-temperature superconductors as a future base for lower losses in grids, or simulations to support nuclear fusion. Use cases aren’t limited to climate mitigation, but can also apply to adaptation, for example, improvements in weather prediction to give greater warning of major climatic events. But progress on those innovations will have to wait because first-generation machines will not be powerful enough for such breakthroughs (see sidebar “Methodology”).
Opportunity for corporates
The leap in CO2 abatement could be a major opportunity for corporates. With $3 to $5 trillion in value at stake in sustainability, according to McKinsey research, climate investment is an imperative for big companies. The use cases presented above represent major shifts and potential disruptions in these areas, and they are associated with huge value for players who take the lead. This opportunity is recognized by industry leaders who are already developing capabilities and talent.
Nevertheless, quantum technology is in the early stage and comes with the risks linked to leading-edge technology development, as well as tremendous cost. We have highlighted the stage of the industry in the Quantum Technology Monitor.6 The risk to investors can be mitigated somewhat through steps such as onboarding technical experts to run in-depth diligence, forming joint investments with public entities or consortia, and investing in companies that bundle various ventures under one roof and provide the necessary experience to set up and scale these ventures.
In addition, governments have an important role to play by creating programs at universities to develop quantum talent and by providing incentives for quantum innovation for climate, particularly for use cases that today do not have natural corporate partners, such as disaster prediction, or that aren’t economical, such as direct-air capture. Governments could start more research programs like the partnership between IBM and the United Kingdom,7 the collaboration between IBM and Fraunhofer-Gesellschaft,8 the public–private partnership Quantum Delta9 in the Netherlands, and the collaboration between the United States and the United Kingdom.10 By tapping into quantum computing for sustainability, countries will accelerate the green transition, achieve national commitments, and get a head start in export markets. But even with those measures, the risk and expense remain high (Exhibit 5).
Here are some questions corporates and investors need to ask before taking a leap into quantum computing.
Is quantum computing relevant for you?
Determine whether there are use cases that can potentially disrupt your industry or your investments and address the decarbonization challenges of your organization. This article has highlighted anecdotal use cases across several categories to showcase the potential impact of quantum computing, but we’ve identified more than 100 sustainability-relevant use cases where quantum computing could play a major role. Quickly identifying use cases that are applicable to you and deciding how to address them can be highly valuable, as talent and capacity will be scarce in this decade.
How do I approach quantum computing now, if it is relevant?
Once you have engaged on quantum computing, building the right kind of approach, mitigating risk and securing access to talent and capacity are key.
Because of the high cost of this research, corporates can maximize their impact by forming partnerships with other players from their value chains and pooling expense and talent. For example, major consumers of hydrogen might join up with electrolyzer manufacturers to bring down the cost and share the value. These arrangements will require companies to figure out how to share innovation without losing competitive advantage. Collaborations such as joint ventures or precompetitive R&D could be an answer. We also foresee investors willing to support such endeavors to potentially remove some of the risk for corporates. And there are large amounts of dedicated climate finance available, judging by pledges11 made at COP26 that aim to reach the target of $100 billion a year in spending.
Do I have to start now?
While the first fault-tolerant quantum computer is several years away, it is important to start development work now. There is significant prework to be done to get to a maximal return on the significant investment that application of quantum computing will require.
Determining the exact parameters of a given problem and finding the best possible application will mean collaboration between application experts and quantum-computing technicians well versed in algorithm development. We estimate algorithm development would take up to 18 months, depending on the complexity.
It will also take time to set up the value chain, production, and go-to-market to ensure they are ready when quantum computing can be deployed and to fully benefit from the value created.
Quantum computing is a revolutionary technology that could allow for precise molecular-level simulation and a deeper understanding of nature’s basic laws. As this article shows, its development over the next few years could help solve scientific problems that until recently were believed to be insoluble. Clearing away these roadblocks could make the difference between a sustainable future and climate catastrophe.
Making quantum computing a reality will require an exceptional mobilization of resources, expertise, and funds. Only close cooperation between governments, scientists, academics, and investors in developing this technology can make it possible to reach the target for limiting emissions that will keep global warming at 1.5°C and save the planet.