How Quantum Computing Can Speed Up Climate Change Mitigation Efforts

In 2023, a team of researchers using quantum computers successfully modelled carbon capture molecules with unprecedented accuracy, sparking hope in the fight against climate change. This breakthrough, amongst many others out there, demonstrated how quantum computing's immense processing power could fast-track climate solutions. Unlike traditional computers, which struggle with complex environmental simulations, quantum machines can analyse vast datasets in record time. Imagine quantum algorithms optimising wind farm placement or discovering new eco-friendly materials, paving the way for a more sustainable future. This is no longer theoretical—it's happening now.

As the world faces rising sea levels, extreme weather events, and temperature increases, scientists and policymakers urgently seek innovative tools to reverse or mitigate these effects. In 2022 alone, CO₂ emissions reached a record 36.8 billion metric tons globally, underscoring the immediate need for these breakthroughs. Quantum computing, with its ability to process vast amounts of data exponentially faster than classical computers, holds the promise to accelerate solutions to climate-related problems. It is the dawn of a new era, one in which quantum technology could provide the computational power necessary to model our planet’s climate more accurately and develop new, energy-efficient materials.

But how does quantum computing work, and what is its unique capacity to contribute to the fight against climate change? Understanding these foundations is key to grasping how this emerging field could transform climate action.

Quantum computing is grounded in the principles of quantum mechanics, the branch of physics that explains how particles behave at atomic and subatomic levels. Unlike classical computers, which use binary bits (0s and 1s) to process information, quantum computers use qubits. Qubits can exist in multiple states simultaneously, thanks to phenomena like superposition and entanglement, making quantum computers exponentially more powerful for certain tasks. These principles allow quantum computers, which use qubits, to perform complex calculations far beyond the capabilities of classical computers.

The origins of quantum computing trace back to the early 1980s, when physicist Richard Feynman proposed that classical computers could not efficiently simulate quantum systems. Over the decades, quantum computing has evolved from theoretical physics to practical applications, thanks to advancements in both hardware and quantum algorithms. Today, companies like IBM, Google, and startups like Rigetti and IonQ are leading the charge toward building scalable, fault-tolerant quantum machines, some with thousands of qubits in development.

Quantum computing offers a range of promising applications in addressing climate change, from optimising renewable energy systems to enhancing climate modelling and reducing emissions. Its potential spans multiple areas, making it a powerful tool in the global fight against climate change. Quantum computing provides breakthroughs in several crucial areas, such as:

• Carbon Capture Optimization: Quantum computers excel at simulating chemical reactions, which is vital for developing better materials for capturing and storing carbon dioxide. For instance, carbon capture technologies rely on materials like metal-organic frameworks (MOFs) to trap CO₂ efficiently. However, identifying the best MOFs from millions of possible combinations is computationally expensive for classical systems. Quantum computing can simulate these interactions at the atomic level, allowing scientists to design optimal materials for carbon sequestration. The 2023 Deloitte Quantum Climate Challenge focused on using quantum simulations to enhance materials for direct air capture, yielding promising results from 120 participants across five continents. These simulations could drastically reduce the energy required for carbon capture, potentially accelerating the fight against rising atmospheric CO₂ levels.
• Energy Efficiency in Power Grids: Another application of quantum computing lies in optimising power grid operations. Power grids are complex systems involving multiple energy sources, fluctuating demand, and grid stability considerations. Quantum algorithms can optimise energy distribution in real-time, reducing wastage and integrating renewable energy sources like solar and wind more efficiently. This is particularly critical as renewable energy adoption increases but also poses challenges to grid stability. Organisations like the Oak Ridge National Laboratory (ORNL) and IonQ are actively exploring how quantum computing can modernise power grid operations. Their projects focus on optimising energy distribution, enhancing grid stability, and integrating distributed energy resources effectively.
• Enhancing Climate Models: Accurate climate modelling is essential to predict future climate scenarios and to implement mitigation strategies effectively. Current climate models are limited by the computing power available, as they must process vast amounts of data regarding the atmosphere, oceans, and land interactions. Quantum computing, with its ability to analyse multiple variables simultaneously, could create more accurate and faster climate models. Experts believe that quantum-powered simulations could improve weather forecasting and long-term climate projections, allowing policymakers to respond more swiftly to changing conditions.
• Enhancing Weather Forecasting and Climate Predictions: This function is closely tied to the previous one. Weather forecasting plays a critical role in both short-term disaster management and long-term climate mitigation strategies. Accurately predicting extreme weather events, such as hurricanes or droughts, allows governments and organisations to prepare for disasters and minimise their environmental and economic impacts. Traditional forecasting models rely on vast amounts of data, but they can only process a limited number of variables due to computational limitations. Quantum computing, with its ability to handle complex, multi-variable datasets, could revolutionise how meteorologists and climate scientists model weather and climate systems. By improving the accuracy of climate predictions, quantum computing can help forecast extreme weather events earlier and with greater precision. According to a report by Zapata Computing, a leading quantum software company, quantum computers could simulate atmospheric systems more accurately than classical models, which are prone to simplifications. Such precision could allow us to better plan for extreme weather and avoid potential disruptions to agriculture, energy grids, and infrastructure

One of the most significant obstacles is the limitation of quantum hardware. While tech giants like IBM, Google, and Rigetti have made impressive advancements in building quantum computers, current systems remain error-prone and limited in scale. The machines we have today, such as Google’s 53-qubit Sycamore processor, are groundbreaking but still far from the level of stability and scalability required to solve climate-related challenges. Quantum computers need to be fault-tolerant to handle complex calculations consistently, but this requires machines with millions of qubits, whereas current systems operate with only tens or hundreds of qubits. In 2023, IBM made strides by introducing its Osprey processor with 433 qubits, but even that is far from the millions needed for real-world climate applications.

Quantum computers are also highly susceptible to quantum noise, a phenomenon that can cause qubits to lose coherence due to their sensitivity to environmental disturbances. This results in computation errors, which are particularly challenging when trying to run long or complex calculations. Although error correction techniques are under development, they remain computationally expensive. Researchers at MIT have made strides in improving qubit architectures to enhance error correction capabilities, demonstrating higher accuracy rates in operations between qubits. Despite these advancements, the overall robustness required for widespread commercial use is still under development.

Economic barriers also play a critical role. Quantum computing is an incredibly expensive technology to develop and maintain. The specialised equipment required to operate quantum systems, such as cooling mechanisms that bring the environment close to absolute zero, adds to the high operational costs. Building quantum computers and continuously advancing their hardware and algorithms involves massive financial investments. While the market for quantum computing is expected to grow to $125 billion by 2030, much of this funding will have to come from governments and large corporations. This raises the question of whether the returns on investment will justify the costs in the short term. Currently, only a few sectors can afford to invest heavily in quantum technology.

Nonetheless, there are significant investments being made in quantum computing. The European Union’s Quantum Flagship program, with its €1 billion budget over ten years, is focused on accelerating research in quantum technology. The U.S. has also committed to quantum R&D through the National Quantum Initiative Act, which funnels federal resources into quantum research. On the private sector front, companies like Amazon and Microsoft are creating cloud-based quantum services to make the technology more accessible. Despite this, high costs will remain a limiting factor until quantum systems become more scalable and affordable.

A less discussed but equally critical challenge is the shortage of skilled professionals in the quantum field. Quantum computing requires a specialised skill set that combines knowledge of quantum mechanics, computer science, and engineering. Unfortunately, the current supply of qualified experts is not keeping pace with the growing demand. According to McKinsey, the demand for quantum talents could be up to 1 million jobs by 2030, but universities and training programs are only beginning to develop the necessary educational pathways. This skills gap will likely slow down the development and implementation of quantum solutions for climate change in the short term. Countries like the United Kingdom are taking steps to address this gap, with the government launching a National Quantum Strategy aimed at training 1,000 postgraduate research students in quantum-relevant disciplines by 2033. However, training the next generation of quantum experts will take time, and the current workforce is insufficient to meet the demand.

The road ahead for quantum computing in climate change mitigation is filled with both promise and obstacles. Although hardware limitations, quantum noise, and high operational costs are significant barriers, continuous investment in research and development is helping to make steady progress. Advances in error correction, new quantum algorithms, and emerging talent in the field are paving the way for future applications. Experts believe that quantum computing could start making meaningful contributions to climate mitigation by 2030, aligning with the global efforts to meet the Sustainable Development Goals.v

Given the current rate of technological advancements, quantum computing could play a critical role in the next decade, helping to reverse the devastating effects of climate change before it is too late. The question remains: will we be able to develop quantum solutions in time to make a real difference? The answer lies in continued investment, research, and global cooperation.