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Artificial intelligence can provide crucial insights into how intricate mixtures of chemicals in rivers impact aquatic life, leading to enhanced environmental protection.
Researchers from the University of Birmingham have introduced a new method showcasing how cutting-edge artificial intelligence (AI) techniques can assist in detecting potentially dangerous chemicals in river waters by observing their effects on small water fleas known as Daphnia.
The research involved collaboration with experts at the Research Centre for Eco-Environmental Sciences (RCEES) in China and the Helmholtz Centre for Environmental Research (UFZ) in Germany to scrutinize water samples from the Chaobai River system near Beijing. This river system is plagued by chemical pollutants originating from various sources such as agriculture, domestic waste, and industrial activities.
Professor John Colbourne, who leads the University of Birmingham’s Centre for Environmental Research and Justice and is a senior author of the study, expressed hope that these initial discoveries could eventually lead to technologies that routinely monitor water for toxic substances that might go unnoticed otherwise.
He stated: “The environment contains an extensive array of chemicals. We cannot evaluate water safety by looking at one substance at a time. Now, we can assess the entirety of chemicals in environmental water samples to reveal how unknown substances interact to create toxicity for animals, including humans.”
The study, published in Environmental Science and Technology, indicates that certain chemical mixtures can jointly influence vital biological processes in aquatic species, which can be assessed through their genetic activity. The interactions of these chemicals can lead to environmental risks that are possibly more significant than the effects of individual chemicals alone.
The research team selected water fleas (Daphnia) as their experimental subjects due to these small crustaceans’ sensitivity to changes in water quality and their genetic similarities to other species, making them reliable indicators of potential environmental risks.
“Our novel approach utilizes Daphnia as indicator species to discover potential toxic substances in the surroundings,” explained Dr. Xiaojing Li from the University of Birmingham (UoB) and the paper’s lead author. “Employing AI methods, we can pinpoint which groups of chemicals might be especially harmful to aquatic organisms, even at low concentrations that typically wouldn’t be concerning.”
Dr. Jiarui Zhou, a co-first author and lead developer of the AI algorithms at the University of Birmingham, mentioned: “Our methodology illustrates how sophisticated computational techniques can help address urgent environmental issues. By analyzing extensive biological and chemical data concurrently, we can enhance our understanding and forecasting of environmental dangers.”
Professor Luisa Orsini, another senior author of the study, noted: “The significant innovation of this study lies in our objective, data-driven strategy for revealing how relevant concentrations of chemical mixtures can cause harm. This approach challenges traditional ecotoxicology and paves the way for legally incorporating Daphnia as indicator species, together with new methodological approaches.”
Dr. Timothy Williams of the University of Birmingham and co-author of the study added, “Usually, aquatic toxicology research either examines high concentrations of a single chemical to observe specific biological responses or only evaluates broader impacts like mortality and reproductive changes after exposure to environmental samples. This study innovates by enabling the identification of crucial chemical classes that influence organisms within actual environmental mixtures at relatively low concentrations while also characterizing the molecular changes triggered.”
The implications of these findings could enhance environmental protection by:
- Revealing previously unidentified chemical combinations that may be risky for aquatic life
- Facilitating more thorough environmental monitoring
- Promoting more informed regulations regarding chemical discharges into water bodies
This research received funding from the Royal Society International Collaboration Award, the European Union’s Horizon 2020 research and innovation program, and the Natural Environment Research Council Innovation People program.
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