K
Kathrin Fenner
Researcher at Swiss Federal Institute of Aquatic Science and Technology
Publications - 121
Citations - 11509
Kathrin Fenner is an academic researcher from Swiss Federal Institute of Aquatic Science and Technology. The author has contributed to research in topics: Biotransformation & Chemistry. The author has an hindex of 40, co-authored 109 publications receiving 9140 citations. Previous affiliations of Kathrin Fenner include ETH Zurich & École Polytechnique Fédérale de Lausanne.
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Journal ArticleDOI
The Challenge of Micropollutants in Aquatic Systems
René P. Schwarzenbach,Beate I. Escher,Kathrin Fenner,Thomas B. Hofstetter,C. Annette Johnson,Urs von Gunten,Bernhard Wehrli +6 more
TL;DR: There are three scientific challenges in addressing water-quality problems caused by micropollutants, and usage and disposal strategies should aim to minimize introduction of critical pollutants into the aquatic environment.
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Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence
Emma L. Schymanski,Junho Jeon,Rebekka Gulde,Kathrin Fenner,Matthias Ruff,Heinz Singer,Juliane Hollender +6 more
TL;DR: A level system is proposed, which arose from intense discussions within the department, to ease the communication of identification confidence and form the basis of further discussions on this topic, and specifically covers the new possibilities in HR-MS-based analysis.
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Evaluating Pesticide Degradation in the Environment: Blind Spots and Emerging Opportunities
TL;DR: The major scientific challenges in predicting the extent and pathways of pesticide degradation under specific field conditions are reviewed and emerging opportunities to identify pesticide degradation processes in the field are discussed.
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Recent Advances in Environmental Risk Assessment of Transformation Products
TL;DR: This work demonstrates how effect data for parent compounds can be used in combination with analysis of toxicophore structures and bioconcentration potential to facilitate transformation product effect assessment and integrates existing research into a coherent model-based, risk-driven framework.