The changing climate and depleting resources keep causing businesses major headaches. The economic harm from climate change is projected to hit a staggering $2.3 trillion by 2100 if we continue business as usual, according to Statista. When it comes to sustainable energy, it’s all about measuring costs, probabilities, and convenience.
As we scramble to hit net-zero targets without breaking the bank, AI might just be the answer. Let’s take a dive into how the market can use AI to transform carbon capture, utilization and storage (CCUS).
Better capture precision. Can AI make it happen?
Cutting carbon emissions isn’t easy – it’s resource-heavy and a real challenge for companies aiming for net-zero. Now, enter AI, which promises to make the carbon capture process smarter, faster, and more efficient. One latest example is Cambridge and Amsterdam-based company CuspAI that offers AI-designed materials for CCUS. The growing need for this technology has already secured the company $30 million from European and US venture funds.
But AI is only as good as the data it processes. That’s why ensuring accuracy of information is key to a hassle-free process. Currently, only a handful of countries like the United States, China, and Iran are pioneering AI in carbon capture. To achieve a global shift, we need a precise implementation model, as suggested by the Journal of CO2 Utilization since the available data might be too vague for companies to get accurate results.
From carbon to value
Capturing CO2 is just the start. Turning it into valuable products is where the real potential lies. And AI is at the forefront of optimising these transformation processes.
Switzerland-based company Climeworks converts captured CO2 into carbon-neutral synthetic fuels, targeting 1 million metric tons of CO2 captured annually by 2025, thanks to AI-driven efficiency improvements. Another example is US-based LanzaTech that leverages AI to transform captured CO2 into ethanol and other chemicals, recycling millions of tons of CO2 into products, like jet fuel, plastics, and chemicals.
Transportation of CO2: enhancing efficiency and safety
Transporting CO2 efficiently isn’t just about moving gas from point A to B, it’s a complex operation requiring top-notch safety and efficiency. According to the U.S. Department of Energy, AI is making a significant impact here by optimizing sensor networks and enhancing decision support.
It has the power to optimise sensor placements to find potential leaks, forecast threats in real-time, identify new signals to find failure, and explore new ways to transport carbon. For example, Drax Group in the UK uses AI to revolutionise pipeline monitoring, improving safety by predicting and preventing potential failures. Meanwhile, Schlumberger in France leverages AI for smarter route planning and real-time leak detection. One of the main challenges with carbon transportation is ensuring data accuracy, as any imperfections could undermine the benefits AI offers.
Storage safety
When it comes to carbon storage, international think-tanks like Global CCS Institute are spearheading efforts with predictive models that enhance site selection and evaluate storage viability. AI algorithms can sift through geological data, identifying optimal locations for carbon storage while predicting potential risks with high accuracy.
Aker Carbon Capture in Norway uses AI to streamline the monitoring of storage sites. Their technology integrates real-time data from sensors placed underground to detect any anomalies or potential leaks, ensuring long-term stability and safety.
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Future potential of AI
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