seeing green

Houston researchers launch 2 nature-based carbon credit projects

Both projects will seek to develop “tracking and evaluation systems for the emerging nature-based carbon credit market.” Photo via Getty Images

A team at Rice University has announced plans for two research projects that will focus on nature-based carbon credits.

The George R. Brown School of Engineering and the Severe Storm Prediction, Education and Evacuation from Disasters (SSPEED) Center reported that the projects will be funded through a gift from Emissions Reduction Corp. with the goal of advancing global decarbonization through a series of carbon sequestration, avoidance and reduction projects.

Both projects will seek to develop “tracking and evaluation systems for the emerging nature-based carbon credit market” according to a news release.

“The Rice School of Engineering is very interested in research into nature-based engineering solutions,” Luay Nakhleh, the William and Stephanie Sick Dean of Engineering and a professor of computer science and biosciences at Rice, says in the release. “For too long, we have used nature as a platform but not as a partner. This research will hopefully open the door on a new era of nature-based engineering. Moreover, this is a very timely initiative as bringing science to bear on the emergent carbon credit economy is of critical importance to meeting the challenges of a changing climate.”

For the first project, which is expected to take six months, the SSPEED Center will be commissioning the design of a digital monitoring, reporting and verification (dMRV) system for tracking nature-based carbon credits using satellite and drone imagery to monitor coastal blue carbon projects, soil, and forest projects.

The direct input of this data into blockchain and other record-keeping technologies will be the main part of the system. .A Houston-based local nonprofit carbon registry BC Carbon, and blockchain provider Change Code will also take part in the research.

The second project will see the SSPEED Center undertake hydrologic computer modeling, and take 12 to 18 months to complete. This will help determine the effectiveness of restoring native prairie grasslands as a flood control technique where a portion of the Brazos River will be modeled relative to predict increases in the frequency of “100-year floods” via climate change. Overall, it will evaluate whether prairie restoration funded via soil carbon credits could mitigate flooding risk, which could eliminate the need to raise the 30 miles of levees in Fort Bend County downstream of the carbon project. The George Foundation,BCarbon, and Fort Bend County Flood Control District will work together on this project.

“Using nature to solve flooding problems has been discussed but seldom executed at the level of a major river system,” Herman Brown Professor of Engineering and SSPEED Center director at Rice Phillip Bedient adds. “We are excited that carbon credits and prairie restoration might break open this nature-based flood engineering area.”

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A View From HETI

Hadi Ghasemi, a University of Houston professor, has uncovered a method to release heat from data centers and electronics at record performance. Photo courtesy UH.

A University of Houston professor has developed a new cooling method that can remove heat at least three times more effectively from AI data centers than current technologies.

Hadi Ghasemi, a distinguished professor of Mechanical & Aerospace Engineering at UH, published his findings in two articles in the International Journal of Heat and Mass Transfer. The findings solve a critical issue in the growing AI sector, according to UH.

High-powered AI data centers generate huge amounts of heat due to the GPU and operating systems they use with extreme power densities, which introduce complex thermal challenges. Traditionally, cooling methods, like microchannels, which use flow and spray cooling, have had limitations when exposed to extreme heat flux, according to UH.

Ghasemi’s research, however, found a more effective way to design thin-film evaporation structures to release heat from data centers and electronics at record performance.

Ghasem’s solution coupled topology optimization and AI modeling to determine the best shapes for thin film efficiency, ultimately landing on a branch-like structure—resembling a tree.

The model found that the “branches” needed to be about 50 percent solid and 50 percent empty space for optimum efficiency, and that they could sustain high heat fluxes with minimal thermal resistance.

“These structures could achieve high critical heat flux at much lower superheat compared to traditionally studied structures,” Ghasemi said in a news release. “The new structures can remove heat without having to get as hot as previous removal systems.

Ghasemi’s doctoral candidates, Amirmohammad Jahanbakhsh and Saber Badkoobeh Hezave, also worked on the project. The team believes their results show the impact of a physics-aware, AI design and can help ensure reliability, longevity and stability of AI data centers.

“Beyond achieving record performance, these new findings provide fundamental insight into the governing heat-transfer physics and establishes a rational pathway toward even higher thermal dissipation capacities,” Ghasemi added in the release

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