New methods for removing harmful nitrates from drinking water identified
Nitrate contamination of drinking water poses a major health concern, particularly in agricultural communities where fertilizers, livestock manure and septic systems can leach nitrates into groundwater. ...
Nitrate contamination of drinking water poses a major health concern, particularly in agricultural communities where fertilizers, livestock manure and septic systems can leach nitrates into groundwater. Many rural households rely on private water wells, which may not be routinely tested, leading some to consume contaminated water without realizing it.
In a promising step toward mitigating this threat, researchers at Stevens Institute of Technology have identified catalysts that offer a novel approach to removing nitrates from drinking water.
The study, "Multitask Learning Reveals Shared Descriptors Governing Activity and Selectivity in Catalytic Nitrate Reduction," is published in the journal Environmental Science & Technology.
Health risks and environmental fallout
Removing nitrates from water is a complex challenge because current treatment methods result in the production of additional contaminants, like ammonium, while others generate concentrated, nitrate-rich wastewater that is difficult and costly to dispose of.
"Nitrate is one of the most common contaminants found in drinking water, so if a farming family uses a private well, they may be exposed to high levels of nitrates," explains Assistant Professor Tao Ye at Stevens School of Engineering and Science's Department of Civil, Environmental and Ocean Engineering, who led the study.
High levels of nitrates in drinking water can be a health hazard. Although rare, nitrates can cause a potentially life-threatening "blue baby syndrome" in infants because nitrates may reduce the blood's ability to carry oxygen. Some studies have linked long-term nitrate exposure to an increased risk of certain cancers, thyroid disorders and pregnancy complications.
There is also an environmental cost, Ye points out. "Nitrate is a nutrient, which is why it's used as a fertilizer," he explains. "Too much nitrate in rivers and lakes fuels algae growth, triggering massive algal blooms that suck out oxygen from the water and create dead zones where fish and other aquatic creatures can't survive."
The limits of current treatment
Until now, identifying treatment methods required labor-intensive laboratory experiments and a lot of trial and error. The team behind the new findings used AI to pioneer a new approach, making the search for better nitrate-removal solutions faster and more precise.
Currently, the most common way of removing nitrates from water is an ion-exchange method, in which water passes through a special material such as a resin, which traps nitrate ions and releases harmless ions, such as chloride. (Chloride is part of the body's natural processes, including the stomach's hydrochloric acid, which is vital for digesting food and killing ingested bacteria.)
However, the ion-exchange method is not ideal because it produces a concentrated, nitrate-rich waste brine, explains Ph.D. student and study co-author Mahjib Hossain. "The catch is that the ion exchange method doesn't destroy nitrates," Hossain says. "Instead, it transfers the nitrate into a concentrated waste stream. The resin must then be regenerated with a salt solution, producing brine that requires careful treatment or disposal."
Prior research identified a metal called palladium as a promising alternative. Rather than filtering nitrates out, palladium serves as a catalyst that fosters a chemical reaction that converts harmful nitrates into water and harmless nitrogen gas, which constitutes about 78 percent of the air we breathe. However, that reaction can also produce ammonium, an undesirable byproduct that researchers seek to minimize, Hossain says.
Palladium alone cannot efficiently break apart nitrate molecules, so it needs to be paired with a second metal, such as indium, tin or copper, to serve as bimetallic catalysts. Identifying the optimal combinations is challenging because it requires manual work, time and sophisticated laboratory equipment. "Traditionally, researchers develop the catalyst by trial and error," explains Hossain. "That can take years."
AI points to better catalysts
To speed up the process, Ye and Hossain developed an artificial intelligence framework that learned from 106 studies published over three decades on palladium- and platinum-based catalysts and predicted which materials are most likely to remove nitrate efficiently while minimizing unwanted byproducts such as ammonium. The model analyzed multiple aspects of catalyst performance and produced more accurate predictions than conventional approaches.
It also identified the key chemical properties that drive successful nitrate removal, including catalyst composition, acidity (pH) and other factors.
The team's work signifies a shift in the effort to discover new water purification methods. "Rather than focusing on developing a specific catalyst, we did something fundamentally different," explains Ye. "We built a roadmap, a framework for creating better catalysts faster. Our work will reduce that trial-and-error process and speed up the development of catalysts for nitrate removal."
The nitrogen pollution problem will continue to pose a challenge because of the important role nitrogen plays in agriculture, Ye notes.
"Nitrogen is a big issue right now, particularly in agricultural regions such as the Midwest and in many other parts of the world. Improving technologies that remove nitrate from drinking water is essential for protecting human health as well as the environment, so it's crucial that we develop remediation technologies quickly. AI can help us do it faster and more efficiently."
Publication details
Md. Mahjib Hossain et al, Multitask Learning Reveals Shared Descriptors Governing Activity and Selectivity in Catalytic Nitrate Reduction, Environmental Science & Technology (2026). DOI: 10.1021/acs.est.6c02715
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Citation: New methods for removing harmful nitrates from drinking water identified (2026, July 24) retrieved 24 July 2026 from https://phys.org/news/2026-07-methods-nitrates.html
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