US scientists develop mechanical trees for air purification

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Researchers at Arizona State University have developed ‘mechanical trees’ that capture CO2 passively and sequester it for industrial and agricultural use.

The technology involves discs of sorbent stacked in columns. When a column is fully extended, the discs are exposed to air and capture atmospheric CO2. Once full, the discs are them lowered back into the column where the CO2 is extracted and either sequestered or sold for commercial use.

A cluster of 12 trees will be capable of removing one metric ton of CO2 per day, at a cost of less than $100 per ton. According to the researchers, this will be the lowest cost across the carbon removal industry, making it a viable solution to mitigate climate change at scale.

“The situation has gotten to the point where we need to stop talking about it and start doing something about it,” said engineering Professor Klaus Lackner, director of Arizona State University’s Centre for Negative Carbon Emissions (CNCE), and developer of the technology.

“Carbon dioxide is a waste product we produce every time we drive our cars or turn on the lights in our homes. Our device can recycle it, bringing it out of the atmosphere and either bury it or use it as an industrial gas.”

The technology will be brought to market by Dublin-based Silicon Kingdom Holdings (SKH), for whom Lackner will act as chief scientific advisor. SKH will deploy the technology in a pilot CO2 farm targeting 100 metric tons of CO2 capture per day. Full-scale CO2 farms using the mechanical trees will be capable of removing up to 3.8 million metric tons of CO₂ annually, according to the researchers.

“Our goal is to accelerate the global climate effort set out in the Paris Agreement to contribute to reversing global carbon emissions in the next 10 to 15 years,” said Pól Ó Móráin, CEO of SKH. “Our passive process is the evolution of carbon capture technology which has the ability to be both economically and technologically viable at scale in a reasonably short time frame.”

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