Jointly meeting global challenges Annual report 2012

 

Doing more with mass spectrometer data through smarter data processing

17 April 2012BTO

Measurements made with high-resolution mass spectrometers provide more information about substances in different types of water thanks to new analysis methods and better data-processing software.

For some time now, KWR has used high-resolution mass spectrometers to measure substances found in different types of water. These mass spectrometers can determine the molecular mass of a substance to five decimal places. They are frequently used in the identification of different substances found in very low concentrations in a single sample. The technique enables the conduct of broad screening research, that is, the measurement of as many simultaneously present substances as possible. Before this technique became available, analyses were targeted primarily at specific, previously selected, substances (target analysis).

Testing software and jointly building database

The measurements produce an enormous amount of data over several years. Water companies like to know what substances are, or could be, present in their raw water. This allows them to take timely measures to remove undesirable substances during drinking water production and, if necessary, push for emission restrictions. But the harvesting of usable data from the big data files is still being actively worked on.
In order to process data more rapidly, researchers are testing two software packages and employing them in ongoing research in collaboration, among others, with RIVM. This work shows that the new software makes it possible to study whether particular substances, or substance types, occur more frequently in groundwater and surface water, and whether their concentrations are increasing or decreasing.
KWR is also, together with fellow institutes, building a joint accurate mass database, so that knowledge in Europe can be bundled thus speeding up the identification process for many substances occurring in water.

© 2017 KWR Watercycle Research Institute

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