zooming in on emissions

UH team unlocks innovative approach to pinpoint pollution factors

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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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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