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Analysis of Pharmaceuticals in Water by Isotope Dilution Liquid Chromatography/Tandem Mass Spectrometry

Open access
Vanderford, Brett J., Snyder, Shane A.·2006·Environmental Science & Technology

Abstract

A method has been developed for the trace analysis of 15 pharmaceuticals, four metabolites of pharmaceuticals, three potential endocrine disruptors, and one personal care product in various waters. The method employs solid-phase extraction (SPE) and liquid chromatography/tandem mass spectrometry (LC-MS/MS), using electrospray ionization (ESI) in both positive and negative modes. Unlike many previous LC-MS/MS methods, which suffer from matrix suppression, this method uses isotope dilution for each compound to correct for matrix suppression, as well as SPE losses and instrument variability. The method was tested in five matrices, and results indicate that the method is very robust. Matrix spike recoveries for all compounds were between 88 and 106% for wastewater influent, 85 and 108% for wastewater effluent, 72 and 105% for surface water impacted by wastewater, 96 and 113% for surface water, and 91 and 116% for drinking water. The method reporting limits for all compounds were between 0.25 and 1.0 ng/L, based on 500 mL of sample extracted and a final extract volume of 500 microL. Occurrence of the compounds in all five matrices is also reported.

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Metadata

Authors
Vanderford, B. J., & Snyder, S. A.
Venue
Environmental Science & Technology
Published
2006-09-22
Volume
40
Issue
23
Pages
7312-7320
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2017004306
Cited by
457
References
0
FWCI
19.69
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Analysis of Pharmaceuticals in Water by Isotope Dilution Liquid Chromatography/Tandem Mass Spectrometry. https://app.cochat.ai/papers/10.1021/es0613198
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Vanderford, B. J., & Snyder, S. A. (2006). Analysis of Pharmaceuticals in Water by Isotope Dilution Liquid Chromatography/Tandem Mass Spectrometry. Environmental Science & Technology. https://doi.org/10.1021/es0613198

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.