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        Non-targeted Screening for Environmental Water Quality Monitoring

        In this on-demand webinar, Dr. Andrea Brunner of KWR discusses emerging contaminants and associated challenges and solutions of non-targeted screening for environmental water quality monitoring.

        The ever-increasing production and use of chemicals augment their occurrence in drinking water and its sources to an extent that monitoring, using targeted chemical analyses alone, is no longer sufficient. Complementary methods that can detect a multitude of chemicals simultaneously, referred to as suspect and non-target screening, are required, and must also be able to detect including mobile and polar compounds in low concentrations.

        These methods rely on liquid chromatography coupled to high resolution mass spectrometry in combination with novel data analysis workflows. The range of challenges in their application and strategies to overcome these will be presented, such as the identification of “known unknowns” and “unknown unknowns” in different water matrices and the confidence thereof, the automation of non-target screening data analysis, and the use of cheminformatics and data mining for the prioritization of suspect chemicals.

        Key learning objectives

        • Understand the challenges of ensuring water quality
        • How to confidently identify "known unknown" and "unknown unknown" emerging contaminants
        • Automation and streamlining of complex data analysis

        About the presenter

        Dr. Andrea Mizzi Brunner, Scientific Researcher, KWR

        Dr. Andrea Mizzi Brunner, Scientific Researcher, KWR

        Andrea Mizzi Brunner, Ph.D., is a mass spectrometry (MS) expert working as a scientific researcher in the Chemical Water Quality and Health team at KWR. Andrea’s work focuses on non-target screening approaches with high resolution accurate mass spectrometry to identify unknown compounds in water, such as chemical transformation products and metabolites, as well as the handling of big data sets.

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