ripple effect

UH team develops method to use electricity to remove harmful carbon from ocean waters

UH assistant professor Mim Rahimi published a paper on the development of his lab's emerging negative emissions technology known as electrochemical direct ocean capture. Photo via UH.edu

Researchers at the University of Houston are developing a new, cost-effective way to help rid oceans of harmful carbon dioxide and fight the effects of climate change.

UH assistant professor Mim Rahimi published a paper on the development of his lab's emerging negative emissions technology known as electrochemical direct ocean capture (eDOC) in the journal Energy & Environmental Science this month.

The paper details how Rahimi's team is working to create electrochemical tubes to remove dissolved inorganic carbon from synthetic seawater, according to a release from UH. The process aims to amplify the ocean’s ability to absorb carbon and can easily be integrated into existing on-shore and off-shore infrastructure, including desalination plants and oil rigs.

Unlike other methods that involve complex processes, expensive materials and specialized membranes, the eDOC method focuses on adjusting the ocean water's acidity using affordable electrodes.

“While eDOC won’t single-handedly turn the tide on climate change, it enriches our mitigation toolkit,” Rahimi said in a statement. “In this global challenge, every innovative approach becomes invaluable.”

Rahimi's research is funded by a $250,000 grant from the U.S. Department of Energy and preliminary research was sponsored by UH Energy’s Center for Carbon Management in Energy.

“The promise of eDOC is undeniable, but scaling it, optimizing costs and achieving peak efficiency remain challenges we’re actively addressing,” he added in a statement.

Late last month, UH shared details on another carbon removal project it is involved with–this time focused on direct air capture (DAC). Known as the Pelican Gulf Coast Carbon Removal study–led by Louisiana State University and including UH and Shell—the project looks at the feasibility of a DAC hub that would pull carbon dioxide from the air and either store it in deep geological formations or use it to manufacture various products, such as concrete.

In August, UH announced that the project received nearly $4.9 million in grants, including almost $3 million from the U.S. Department of Energy. Click here to read more.

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A View From HETI

Meta will use electricity generated by one of ENGIE's Texas solar farms to power its U.S. data centers. Photo via engie.com.

Meta, the parent company of social media platform Facebook, has agreed to buy all of the power from a $900 million solar farm being developed near Abilene by Houston-based energy company ENGIE North America.

The 600-megawatt Swenson Ranch solar farm, located in Stonewall County, will be the largest one ever built in the U.S. by ENGIE. The solar farm is expected to go online in 2027.

Meta will use electricity generated by the solar farm to power its U.S. data centers. All told, Meta has agreed to purchase more than 1.3 gigawatts of renewable energy from four ENGIE projects in Texas.

“This project marks an important step forward in the partnership between our two companies and their shared desire to promote a sustainable and competitive energy model,” Paulo Almirante, ENGIE’s senior executive vice president of renewable and flexible power, said in a news release.

In September, ENGIE North America said it would collaborate with Prometheus Hyperscale, a developer of sustainable liquid-cooled data centers, to build data centers at ENGIE-owned renewable energy and battery storage facilities along the I-35 corridor in Texas. The corridor includes Austin, Dallas-Fort Worth, San Antonio and Waco.

The first projects under the ENGIE-Prometheus umbrella are expected to go online in 2026.

ENGIE and Prometheus said their partnership “brings together ENGIE's deep expertise in renewables, batteries, and energy management and Prometheus' highly efficient liquid-cooled data center design to meet the growing demand for reliable, sustainable compute capacity — particularly for AI and other high-performance workloads.”

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