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

Researchers have secured $3.3 million in funding to develop an AI-powered subsurface sensing system aimed at improving the safety and efficiency of underground power line installation. Photo via Getty Images

Researchers from the University of Houston — along with a Hawaiian company — have received $3.3 million in funding to explore artificial intelligence-backed subsurface sensing system for safe and efficient underground power line installation.

Houston's power lines are above ground, but studies show underground power is more reliable. Installing underground power lines is costly and disruptive, but the U.S. Department of Energy, in an effort to find a solution, has put $34 million into its new GOPHURRS program, which stands for Grid Overhaul with Proactive, High-speed Undergrounding for Reliability, Resilience, and Security. The funding has been distributed across 12 projects in 11 states.

“Modernizing our nation’s power grid is essential to building a clean energy future that lowers energy costs for working Americans and strengthens our national security,” U.S. Secretary of Energy Jennifer M. Granholm says in a DOE press release.

UH and Hawaii-based Oceanit are behind one of the funded projects, entitled “Artificial Intelligence and Unmanned Aerial Vehicle Real-Time Advanced Look-Ahead Subsurface Sensor.”

The researchers are looking a developing a subsurface sensing system for underground power line installation, potentially using machine learning, electromagnetic resistivity well logging, and drone technology to predict and sense obstacles to installation.

Jiefu Chen, associate professor of electrical and computer engineering at UH, is a key collaborator on the project, focused on electromagnetic antennas installed on UAV and HDD drilling string. He's working with Yueqin Huang, assistant professor of information science technology, who leads the geophysical signal processing and Xuqing Wu, associate professor of computer information systems, responsible for integrating machine learning.

“Advanced subsurface sensing and characterization technologies are essential for the undergrounding of power lines,” says Chen in the release. “This initiative can enhance the grid's resilience against natural hazards such as wildfires and hurricanes.”

“If proven successful, our proposed look-ahead subsurface sensing system could significantly reduce the costs of horizontal directional drilling for installing underground utilities,” Chen continues. “Promoting HDD offers environmental advantages over traditional trenching methods and enhances the power grid’s resilience.”

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