A new approach developed by researchers at the University of Birmingham is using advanced artificial intelligence (AI) techniques to identify potentially harmful chemicals in rivers by monitoring their effects on tiny Daphnia spp. shows how it can help.
The research team collaborated with scientists from China’s Research Center for Ecological and Environmental Sciences (RCEES) and Germany’s Hemholtz Center for Environmental Research (UFZ) to analyze water samples taken from the Chaobai River system near Beijing. This river system receives chemical pollutants from a variety of sources, including agricultural, domestic, and industrial sources.
Professor John Colborne is director of the Center for Environmental Research and Justice at the University of Birmingham and one of the paper’s senior authors. He hopes that by building on these early discoveries, such technology could one day be deployed to regularly monitor water for toxic substances that would otherwise go undetected. He said he was optimistic.
“There are a huge variety of chemicals in the environment. We cannot assess the safety of water one substance at a time,” he said. “We now have a way to monitor the whole thing and find out what unknown substances work together.” This is because it is toxic to animals, including humans. ”
The results, published in the journal Environment Science and Technology, show that certain mixtures of chemicals can work together to influence important biological processes measured by genes in aquatic organisms. revealed. The combination of these chemicals poses a potentially greater environmental hazard than the chemicals present individually.
innovative approach
The research team used Daphnia daphnia (Daphnia daphnia) as a test organism in the study. Because these small crustaceans are highly sensitive to changes in water quality and share many genes with other species, they are good indicators of potential environmental hazards.
“Our innovative approach utilizes Daphnia as a surveillance species to detect potentially toxic substances in the environment,” said Dr. Xiaojing Li from the University of Birmingham (UoB) and lead author of the study. Let me explain.
“By using AI methods, we can identify a subset of chemicals that may be particularly harmful to aquatic life, even at low concentrations that would not normally cause concern.”
Dr Jiarui Zhou, co-first author of the paper and who led the development of the AI algorithm, also from the University of Birmingham, said: “Our approach provides insight into how advanced computational techniques can help solve pressing environmental challenges. By capturing biological and chemical data simultaneously, we can better understand and predict environmental risks.”
A data-driven approach
Professor Luisa Orsini, another senior author of the study, said: “An important innovation of this study is that it sheds light on how chemical mixtures at environmentally relevant concentrations can cause harm. “This is a data-driven and unbiased approach that challenges traditional ecotoxicology and paves the way for regulation.” Employing the sentinel species Daphnia along with a new approach methodology.
Co-author Dr Timothy Williams from the University of Birmingham added: ‘Aquatic toxicity studies typically use high concentrations of individual chemicals to determine detailed biological responses or Either they determine only apical effects, such as later reproductive changes.” Exposure to environmental samples.
“However, this study breaks new ground by identifying an important class of chemicals that affect organisms at relatively low concentrations in true environmental mixtures, while also allowing us to characterize the biomolecular changes induced. Exploring.”
This discovery identifies previously unknown combinations of chemicals that pose a risk to aquatic life, enabling more comprehensive environmental monitoring and better-informed emissions of chemicals into waterways. Supporting regulations could help improve environmental protection.
