From the vast amount of water monitoring data, you can extract clusters of substances and identify patterns that may tell you something about the source of micropollutants, researchers write in Environments.

When monitoring water quality, you collect piles of data to check that the concentration of certain micropollutants is not rising too high. But this data is not usually analysed further. To get more out of it, researchers at the Water Research Institute (KWR) looked at clusters of substances in the datasets, rather than looking at individual substances, to see if they could find patterns and say something about where the pollutants came from.

But it is not just a matter of leaving interesting data lying around. Drinking water sources - and therefore drinking water companies - are under increasing pressure,” says Tessa Pronk, data scientist at KWR. This is due to dry summers, but also to the increasing use of chemicals that do not belong in water. Together with colleagues Elvio Amato, Stefan Kools and Thomas ter Laak, she set up a project within the industrial research of drinking water companies to see if they could discover patterns and eventually explain the dynamic concentrations of micropollutants.