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

A View From UH

A University of Houston team looked into what areas in Houston had the highest impact on emissions and how certain meteorological factors play into ozone formation. Photo via UH.edu

A team of researchers at the University of Houston are using machine learning to help guide pollution fighting strategies.

As reported in the journal Environmental Pollution last month, the team used the SHAP algorithm of machine learning (a game theory approach) and the Positive Matrix Factorization to pinpoint what areas in Houston had the highest impact on emissions and how certain meteorological factors play into ozone formation.

The paper was authored by Delaney Nelson, a doctoral student at the Department of Earth and Atmospheric Sciences of UH, and Yunsoo Choi, corresponding author and professor of atmospheric chemistry, AI deep learning, air quality modeling and satellite remote sensing.

The team's research closely tracked nitrogen-based compound and volatile organic compound measurements from Texas Commission on Environmental Quality's monitoring stations in the Houston area. After importing measurements from The Lynchburg Ferry station in Houston's ship channel and the urban Milby Park station, the machine learning and SHAP analysis showed a chemically definitive difference between the two areas.

For example, at the industrial station, the most impactful sources of pollution were from oil and gas flaring/production. At the urban site n_decane and industrial emissions/evaporation had the most impact on ozone.

According to Nelson and Choi, this shows that the machine learning and SHAP analysis approach can be used to tailor more precise air quality management strategies in different areas based on the site's unique characteristics.

“Once we know the specific emission sources and factors, we can develop targeted strategies to reduce emissions, which will in turn reduce ozone in the air and make it healthier for everyone," Choi said in a statement.

“Pollution is a critical issue in Houston, where you have extreme high heat and high concentration of ozone in the summers. The types of insights we got are very useful information for the local community to develop effective policies. That’s why we put our time, effort and technological expertise into this project," he continued.

Next the team envisions applying their approach in different cities and across the country.

“Austin, San Antonio and Dallas all have different characteristics, so I expect (volatile organic compound) sources will also be different,” Choi said. “Identifying VOC sources in different cities is very important because each city should have its own unique pollution fighting strategy.”

This summer, the City of Houston released an updated report on its major strategies to combat climate change and build a more resilient future for its residents.

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