Insider Brief
- Quantum computing could support cleaner energy and industrial processes with a relatively small emissions footprint, according to a BCG study.
- BCG estimates that fully deployed quantum-enabled technologies could prevent 3 billion to 7 billion metric tons of emissions annually through advances in batteries, carbon capture and industrial chemistry.
- Only 10% to 15% of those potential savings may be realized by 2040 because commercialization and replacement of long-lived industrial equipment could take decades.
- Image: Photo by Yamu_Jay on Pixabay
The rise of artificial intelligence has raised a new question about whether the next major computing technology will add another large load to power grids. Some experts are worried that quantum systems might do the same as they scale.
A Boston Consulting Group study suggests that is unlikely.
BCG estimates that quantum-enabled technologies could eventually prevent 3 billion to 7 billion metric tons of emissions annually if fully deployed. At 5 billion metric tons — the midpoint, or middle of that range — the savings would equal nearly a tenth of current global emissions.
Although that sounds impressive, the report cautions that those gains would take decades to realize. Under normal equipment replacement cycles, BCG estimates that only 10% to 15% of the potential savings could arrive by 2040, even if commercially viable quantum solutions emerge around 2035.
BCG describes quantum as a specialized computing technology that could help solve chemistry and materials problems without the extensive infrastructure built to support AI. Better battery materials could help electricity grids store more renewable power and reduce their dependence on fossil-fuel backup, BCG experts write.
The study suggests that quantum’s climate value would depend primarily on what researchers discover with it and how quickly companies can put those discoveries into use.
A Smaller Computing Footprint
BCG models quantum computing’s emissions at approximately 90 million metric tons of carbon dioxide equivalent in 2040. The measure combines the warming effects of different greenhouse gases into a common unit.
That would represent less than 0.2% of the 50 billion metric tons of global emissions the study expects that year, and about 7% of projected 2040 data center emissions at the midpoint of its estimates. The relatively small footprint does not necessarily mean individual quantum computers consume little electricity. A full-scale machine could draw roughly 1 megawatt of power, comparable to a small data center, according to BCG.
The difference lies in the number of machines required. The firm estimates that roughly 230 to 1,400 quantum computers could serve global demand by 2040, including spare capacity and systems operated by governments, universities and laboratories.
By comparison, the study says it takes more than 11,000 data centers to support current AI and other computing workloads.
BCG expects quantum computers to handle a limited set of problems for which they offer an advantage. The forecast does not assume they replace conventional processors across the economy and additional applications could increase demand beyond the modeled range, the analysts acknowledge.
Manufacturing the machines accounts for most of the projected quantum emissions footprint, alongside the electricity needed to operate them.
BCG compares that footprint with the midpoint of its eventual annual emissions-savings estimate to suggest a climate benefit of approximately 60 to 1. That comparison pairs a 2040 footprint with the benefits of full deployment, however; it should not be read as the expected balance of emissions and savings in 2040.
Better Batteries, Cleaner Power
The study assessed roughly 50 known quantum computing applications and identified 16 that could plausibly reduce emissions. It excluded seven because existing technologies could deliver the same savings or because more computing power would do little to resolve the underlying obstacle.
The remaining nine depend on understanding how molecules and materials behave.
This may sound like a leap in logic toward sustainable energy, but the analysts report that designing better batteries or chemical catalysts will first require predicting interactions among electrons. Conventional computers use approximations to make many such calculations manageable, but accurately modeling increasingly complex materials becomes difficult.
Sufficiently capable quantum computers could expand the range of materials researchers can evaluate and improve the accuracy of those calculations, according to BCG. Researchers could then direct laboratory experiments toward the most promising candidates.
For batteries, the opportunity involves finding better combinations of electrodes and electrolytes, the components that help determine storage capacity, charging speed and useful life.
BCG says quantum-enabled discoveries could produce batteries that store more energy, last longer or cost less. Those improvements could support long-haul electric trucks and help power grids use more renewable electricity.
Wind and solar plants sometimes generate more power than grids can use, forcing operators to reduce output. At other times, insufficient renewable generation requires fossil-fuel backup.
Better storage could capture otherwise unused electricity and deliver it when needed. That offers a possible connection to cleaner, more reliable electricity supplies that could help meet growing computing demand, even without reducing the power consumed by AI systems themselves.
The study also sees broader benefits in regions where electricity remains expensive or unreliable. Improved battery cost and performance could make renewable power practical in more locations.
Carbon Capture and Industrial Chemistry
BCG identifies carbon capture as one of the significant emissions-savings opportunities among the uses it assessed.
Direct air capture, which removes carbon dioxide from the atmosphere, costs approximately $600 to $1,000 per metric ton, according to the study. That remains well above the roughly $100 level often cited as necessary for widespread adoption.
Part of the challenge is finding better capture materials, known as sorbents. They must hold carbon dioxide firmly enough to collect it, but release it without consuming excessive energy so the material can be reused.
Quantum computing could help researchers evaluate a larger range of possible sorbents and predict their behavior more accurately. Materials that require less energy to capture and release carbon could lower operating costs.
The study describes an ambitious longer-term possibility in which affordable carbon removal helps governments close the gap between remaining emissions and climate goals. But storage capacity and the speed of deployment would still constrain its use.
Another major opportunity involves ammonia, the foundation of synthetic fertilizers that support food production for roughly half the world’s population. BCG attributes approximately 1% to 2% of global emissions to ammonia production.
Conventional production relies heavily on hydrogen made from natural gas and requires high temperatures and pressure. Better catalysts — materials that help chemical reactions proceed — could reduce energy requirements and improve the economics of lower-emission production.
Quantum computers could help identify those catalysts before researchers make and test them. Related advances could improve green hydrogen production, supporting steelmaking that relies less on fossil fuels.
BCG says the largest benefits from green hydrogen and ammonia would come through the industries they help decarbonize, including steel and shipping.
Deployment Will Set the Pace
One of the main constraints may not appear on quantum roadmaps or data center construction schedules, but, ultimately, rests in industrial construction schedules.
Steel mills, cement kilns and chemical plants can operate for 20 to 40 years before major replacement or refurbishment. A better process discovered soon after a plant overhaul might wait decades for widespread adoption.
BCG estimates that industries including steel, cement, chemicals, aviation, shipping, trucking, aluminum and oil and gas will account for roughly 30% of global emissions in 2040. Quantum-enabled technologies could eventually reduce 20% to 40% of their emissions, according to its analysis, but most of the benefit would arrive after that year.
Faster deployment is possible, according to the report. Strong economics, government requirements, common standards and subsidies for industrial upgrades could bring adoption forward.
Therefore, the analysts write that preparation should begin before quantum computing reaches commercial maturity. Capital spending plans, technology partnerships and equipment replacement strategies could determine whether a useful discovery moves quickly into production or waits for the next investment cycle.
Established industrial companies would play a central role because they own the plants, engineering capabilities and infrastructure needed to deploy new processes. BCG sees an investment opportunity in both technology developers and the companies positioned to use their discoveries.
The projections remain conditional because quantum computers must become capable enough to solve the relevant problems, and the resulting materials must prove economical outside the laboratory.