LONDON: Artificial intelligence could provide important insights into how the complex mix of chemicals in rivers affects aquatic life, paving the way for more efficient ones. Environmental protection.
A new method developed by academics at the University of Birmingham shows how advanced artificial intelligence (AI) approaches can detect potentially dangerous chemicals in rivers by monitoring their effects on tiny water fleas (Daphnia). Can help discover substances.
The team, along with scientists from the Research Center for Eco-Environmental Sciences (RCEES) in China and the Helmholtz Center for Environmental Research (UFZ) in Germany, analyzed water samples from the Chaobai River system near Beijing. This river system receives chemical pollution from a number of different sources, including agricultural, domestic and industrial.
Professor John Colborne is director of the Center for Environmental Research and Justice at the University of Birmingham and one of the senior authors of the paper. He hopes that building on these preliminary findings, such technology could one day be used to routinely monitor water for toxins that would otherwise go undetected.
He said: “There is a wide array of chemicals in the environment. Water safety cannot be assessed one substance at a time. We now have the means to monitor the total concentration of chemicals in water samples from the environment. to determine which unknown substances act together to produce toxicity to animals, including humans.”
The findings, published in Environmental Science and Technology, show that certain combinations of chemicals can work together to affect important biological processes in aquatic organisms, as measured by their genes. Combinations of these chemicals create environmental hazards that are potentially greater than when the chemicals are present individually.
The research team used water fleas (Daphnia) as test organisms in the study because these tiny crustaceans are highly sensitive to changes in water quality and share many genes with other species, allowing They make excellent indicators of potential environmental hazards.
“Our innovative approach uses Daphnia as a sentinel species to detect potential toxins in the environment,” explains Dr Zhaojing Li from the University of Birmingham (UoB) and lead author of the study. “Using AI methods, we can identify which substrates of chemicals may be particularly harmful to aquatic life, even at low concentrations that would not normally raise concerns. ”
Dr Jiaroi Chow, also at the University of Birmingham and co-first author of the paper, who led the development of the AI algorithm, said: “Our approach shows how advanced computational methods can be used to solve environmental challenges. can help. Biological and chemical data simultaneously, we can better understand and predict environmental hazards.”
Professor Luisa Orsini, another senior author of the study, added: “The key innovation of the study is our data-driven, unbiased approach to uncovering how ecologically relevant concentrations of chemical compounds cause harm. can lead to. It challenges traditional ecology and paves the way for the adoption of sentinel species Daphnia, as well as new approaches.”
Dr. Timothy Williams of the University of Birmingham and co-author of the paper also noted that, “Typically, aquatic toxicity studies either use high concentrations of individual chemicals to determine detailed biological responses or only mortality rates. and determine altered reproductive effects. However, this study allows us to identify key classes of chemicals that affect life in relatively low concentrations within an actual environmental mixture characterize the biomolecular changes that occur simultaneously.”