Climate change: will quantum computing be the deus ex machina?
According to McKinsey analysts, quantum technology can help reduce CO2 emissions by up to 7 gigatons per year by 2035, bringing the planet in line with the target of 1.5 ° C less
17 Aug 2022
Achieving net zero will not be possible without huge advances in climate technology. But quantum computing could be revolutionary in this sense, contributing to the development of climate technologies capable of reducing additional CO2 emissions by up to 7 gigatons per year by 2035 (or, overall, up to 150 gigatons in the next thirty years), compared to the current trajectory, and bringing the planet in line with the target of 1.5 ° C less.
This is stated in the report "Quantum computing might just save the planet" (DOWNLOAD THE FULL REPORT HERE), with which McKinsey & Company analyzes the potential offered by quantum computing in terms of reducing carbon dioxide emissions. The survey reveals that, in particular, quantum computing could help reduce emissions in some of the most challenging or emission-intensive sectors, such as agriculture, and could accelerate the development of necessary technologies on a large scale, such as solar panels and batteries. It could also help solve persistent sustainability issues such as improving electric batteries for the automotive sector, producing zero-emission cement, developing more advanced renewable solar technology, identifying faster ways to reduce the cost of hydrogen by making it a viable alternative to fossil fuels, and finally using green ammonia. as fuel and fertilizer.
But here is the detail of the individual application potentialities.
Index of topics
The challenge of battery energy density
Improving the energy density of lithium-ion (Li-ion) batteries enables applications in electric vehicles and energy storage at affordable costs. Over the past decade, however, innovation has stopped: battery energy density improved by 50% between 2011 and 2016, but only by 25% between 2016 and 2020, and is expected to improve by only 17% between 2020 and 2025. According to the McKinsey analysis, quantum computing could allow for breakthroughs, having a better understanding of the process of electrolyte complex formation, helping to find a replacement material for the cathode/anode with the same properties and/or eliminating the battery separator.
It would therefore be possible to create batteries with a 50% higher energy density for use in heavy electric vehicles, which could greatly anticipate their economical use. The carbon benefits for electric passenger vehicles would not be huge, as they are expected to reach cost parity in many countries before the first generation of quantum computers is online, but consumers could still enjoy cost savings. In addition, energy-intensive batteries can also serve as a grid-scale storage solution. The impact on world networks would be revolutionary. Halving the cost of grid-scale storage could allow a change of pace in the use of solar energy, which is becoming economically competitive, but is limited by critical issues related to the generation process. According to McKinsey's analysis, halving the cost of solar panels could increase their use by 25% in Europe by 2050, but halving the cost of both solar energy and batteries could increase their use by 60%.
Reducing the impact of clinkers
Cement: During calcination for the production process of clinker, a powder used to make cement, the raw materials used release CO2. This process is responsible for about two-thirds of cement emissions. Alternative binding materials (or "clinkers") for cement can eliminate these emissions, but there is currently no mature alternative clinker that can significantly reduce emissions at an affordable cost. Quantum computing can make it possible to simulate theoretical combinations of materials to find one that overcomes current challenges (durability, availability of raw materials and efflorescence), with an estimated additional impact of 1 gigaton per year by 2035.
The decarbonisation of energy
Solar panels will be one of the main sources of electricity generation in a zero-emission economy. But although they are always cheaper, they are still far from maximum theoretical efficiency. Today, solar panels are based on crystalline silicon and have an efficiency of about 20%. Panels based on perovskite crystal structures, with a theoretical efficiency of up to 40%, could be a better alternative. However, they present challenges because they lack long-term stability and, in some variants, may be more toxic. This technology, moreover, has not yet reached levels of mass production.
According to McKinsey, quantum computing could enable a precise simulation of perovskite structures in all combinations, using different base atoms and doping, thus identifying higher efficiency, greater durability and non-toxic solutions. If an increase in theoretical efficiency could be achieved, the Levelized cost of electriciy (Lcoe) would decrease by 50%. This technology could break down an additional 0.4 gigatons of CO2 by 2035.
Optimize efficiency to reduce the cost of hydrogen
Before the 2022 gas price surges, green hydrogen was about 60% more expensive than natural gas. However, improving electrolysis could reduce its cost significantly. Polymer electrolytic membrane (PEM) electrolytic converters break down water and are a way to produce green hydrogen. They have improved in recent times, but they still face two major challenges, related to efficiency and the still suboptimal interaction between membranes and catalysts.
According to McKinsey, quantum computing can help calculate the energy state of pulse electrolysis and thus optimize the use of the catalyst, optimizing its efficiency. It could also analyze the composition of catalysts and membranes to ensure more efficient interactions. Finally, it could increase the efficiency of electrolysis by up to 100% and reduce the cost of hydrogen by 35%. When combined with cheaper solar panels, the cost of hydrogen could be reduced by 60%. Increased use of hydrogen as a result of these improvements could reduce CO2 emissions by an additional 1.1 gigatons by 2035.
Improving the production rate of ammonia
Ammonia is currently produced through the energy-intensive Haber-Bosch process using natural gas. However, there are other possible approaches, such as the bioelectrocatalysis of nitrogenase, which can be achieved at room temperature and at 1 bar of pressure – compared to the high-pressure 500°C of the Haber-Bosch process, which consumes large amounts of energy, in the form of natural gas. Thanks to current innovations, it may be possible to artificially replicate nitrogen fixation, but only by overcoming challenges such as enzyme stability, oxygen stability and low ammonia production rates by nitrogenase.
According to McKinsey, quantum computing can make it possible to simulate the process of increasing the stability of the enzyme, protecting it from oxygen and improving the rate of ammonia production. This would result in a cost reduction of 67% compared to the current green ammonia produced by electrolysis, making green ammonia even cheaper than that traditionally produced. Such a cost reduction could not only reduce the CO2 impact of ammonia production for agricultural use, but also anticipate by ten years the breakeven of ammonia in the marine sector, where it is expected to be one of the main decarbonisation options. Using quantum computing to facilitate the use of green ammonia at lower costs as a fuel for shipping could reduce CO2 by 0.4 gigatons by 2035.
Enhancing carbon capture and sequestration activities
Point source capture technology makes it possible to capture CO2 directly from industrial sources, such as a blast furnace for concrete or steel. But, in most cases, carbon capture is still too expensive to be viable, especially because of its energy intensity. One possible solution is new solvents, such as water-based or multiphase- solvents, which may offer lower energy requirements, but it is difficult to predict the properties of potential materials at the molecular level.
According to McKinsey, quantum computing enables a more accurate analysis of the molecular structure, so as to design new effective solvents for different sources of CO2, potentially reducing the cost of the process by 30-50%.. It would therefore have significant potential for the decarbonization of industrial processes, with an additional abatement of up to 1.5 gigatons per year.
Direct-air capture technology is also very expensive ($250 to $600 per ton per day). And as if that were not enough, it requires even more energy than Point source capture. In this case, quantum computing can support the advancement of research on new adsorption materials such as organometallic structures (MOFs) and the challenges arising from sensitivity to oxidation, water and degradation caused by CO2. New materials with a higher adsorption rate could reduce the cost of this technology to $100 per ton of CO2 captured, reaching a possible critical threshold for its adoption. This application of quantum computing could result in a further REDUCTION in CO2 of 0.7 gigatons per year by 2035.
Food and forestry processing
20% of annual greenhouse gas emissions come from agriculture, and methane emitted from cattle and the dairy sector is primarily responsible (7.9 gigatons of CO2 equivalent, based on the 20-year global warming potential). One possible solution is the development of antimethane vaccines, which produce antibodies directed against methanogenic microbes.
According to McKinsey, quantum computing couldaccelerate research to find the right antibodies through a precise simulation of molecules. According to an estimate based on data from the US Environmental Protection Agency, carbon dioxide emissions would be reduced by up to 1 additional gigaton by 2035.