Direct Aqueous Analysis of Pesticides and PPCPs in Drinking and Bottled Water at Parts Per Ttrillion Levels

Instrumentation Focus: LCMS
Oral Presentation

Presented by K. Oetjen
Prepared by J. Stahl1, I. Moore2, R. Bosch3, B. Bajema4, B. Nieland1, P. Taylor1, J. Steed1
1 - SCIEX, Landwehrstraße 54, Landwehrstraße 54, Darmstadt, Germany, 64293, Germany
2 - SCIEX, 71 Four Valley Dr, Concord, ON, L4K 4V8, Canada
3 - Vitens, Reactorweg 47, 3542 AD Utrecht, , Netherlands
4 - Vitens, Reactorweg 47, 3542 AD Utrecht, , Netherlands


Contact Information: jianru.stahl-zeng@sciex.com; +49 6151 352000

ABSTRACT

Drinking water analysis demands extremely stringent methodologies for sensitivity and quantitative performance metrics. Water suppliers and utility companies must ensure that the final water product is safe and complies with local, national, and industrial regulations. Environmental waters can be a challenging matrix, containing dilute levels of target contaminants and potentially high levels of matrix interferences. Technologies employed for these analyses necessitate sensitivity, precision, and confidence in results, as well as the robustness to handle matrix challenges. A series of experiments was conducted in collaboration with Vitens Water Company, to test several types of water samples spiked with a mixed standard of 431 analytes, including pesticides, pharmaceuticals and personal care products. This work explores the sensitivity levels of the latest SCIEX Triple Quad™ 7500 LC-MS/MS System − QTRAP® Ready, as well as the quantitative performance of the hardware and software combined platforms.
In this work, it was demonstrated that low-level quantification (parts per trillion detection limits) across a relatively large suite of 431 contaminant residues was achievable. There is scope to expand the number of analytes tested and apply this system to other individual workflows which demand very low limits of quantification. The innovations of the SCIEX 7500 System can open the water industry up to an era of analysis where the impacts of the matrix studied is reduced while the levels of sensitivity are increased.