big moves

Fast-growing startup with carbon-free solution sets up pilot plant in Houston

The opening of the pilot plant marks the debut of Cemvita’s eCO2 business as a wholly owned subsidiary. Photo courtesy of Cemvita

Cleantech startup Cemvita has set up a pilot plant in its hometown of Houston to develop technology for converting carbon emissions as feedstock to make products like fertilizer, plastics, methane, and fuel.

The opening of the pilot plant marks the debut of Cemvita’s eCO2 business as a wholly owned subsidiary. The term eCO2 refers to equivalent carbon dioxide, or a way to measure a combination of greenhouse gases such as carbon dioxide and methane.

With a capacity of more than 14,000 gallons, the plant is producing eCO2 oil, an alternative to soybean oil. The company already is shipping samples of eCO2 products to customers, including renewable-fuel companies and plastics manufacturers.

Cemvita says the biofuel industry is facing feedstock shortages and price fluctuations. Biofuel feedstocks produce starches or sugars that can be converted to produce ethanol, while others produce oil that can be used in biodiesel production, according to the Sustainable Agriculture Research & Education (SARE) program.

“Traditional biofuels, including renewable diesel and sustainable aviation fuel, have relied on oils derived from crops, such as soybean and corn, as well as recycled vegetable oils,” Cemvita says. “As demand grows for petroleum-free alternatives, feedstock is in short supply and must compete with food markets. Crops of soybeans, sugar, and corn use huge swaths of land, and the raw materials require extensive refining — two factors that impede the processes from being sustainable.”

By contrast, eCO2 plants like Cemvita’s can supply feedstock production with minimal land and electricity requirements, and without relying on hydrogen or sunlight, the company says. Furthermore, the output of eCO2 plants is designed to carbon-negative, not just carbon-neutral.

Cemvita’s eCO2 biomanufacturing platform uses engineered microbes that absorb and convert carbon dioxide into feedstocks and finished products.

“The energy transition requires completely new, cost-effective approaches for heavy industry,” Charlie Nelson, chief operating officer of Cemvita, says in a news release. “We built this next-generation pilot plant in response to strong demand from … partners who are actively seeking sustainable solutions to the … feedstock shortage.”

Brother-and-sister team Moji and Tara Karimi founded Cemvita in 2017.

Investors in Cemvita include Oxy Low Carbon Ventures, an investment arm of Houston-based Occidental Petroleum, as well as BHP Group, Mitsubishi, and United Airlines Ventures.

Oxy Low Carbon Ventures and United Airlines Ventures are financing Cemvita’s work on sustainable jet fuel. United Airlines operates a hub at George Bush Intercontinental Airport Houston.

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This article originally ran on InnovationMap.

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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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