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Compound-Specific Chlorine Isotope Analysis of the Herbicides Atrazine, Acetochlor, and Metolachlor
Type of publication
Peer-reviewed
Publikationsform
Original article (peer-reviewed)
Author
Ponsin Violaine, Torrentó Clara, Lihl Christina, Elsner Martin, Hunkeler Daniel,
Project
Assessment of micropollutant degradation using multi-element compound-specific isotope analysis
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Original article (peer-reviewed)
Journal
Analytical Chemistry
Volume (Issue)
91(22)
Page(s)
14290 - 14298
Title of proceedings
Analytical Chemistry
DOI
10.1021/acs.analchem.9b02497
Abstract
A gas chromatography–single quadrupole mass spectrometry method was developed and validated for compound-specific chlorine isotope analysis (Cl-CSIA) of three chlorinated herbicides, atrazine, acetochlor, and metolachlor, which are widespread contaminants in the environment. For each compound, the two most abundant ions containing chlorine (202/200 for atrazine, 225/223 for acetochlor, and 240/238 for metolachlor) and a dwell time of 30 ms were determined as optimized MS parameters. A limit of precise isotope analysis for ethyl acetate solutions of 10 mg/L atrazine, 10 mg/L acetochlor, and 5 mg/L metolachlor could be reached with an associated uncertainty between 0.5 and 1‰. To this end, samples were measured 10-fold and bracketed with two calibration standards that covered a wide range of δ37Cl values and for which amplitudes matched those of the samples within 20% tolerance. The method was applied to investigate chlorine isotope fractionation during alkaline hydrolysis of metolachlor, which showed a shift in δ37Cl of +46‰ after 98% degradation, demonstrating that chlorine isotope fractionation could be a sensitive indicator of transformation processes even when limited degradation occurs. This method, combined with large-volume solid-phase extraction (SPE), allowed application of Cl-CSIA to environmentally relevant concentrations of widespread herbicides (i.e., 0.5–5 μg/L in water before extraction). Therefore, the combination of large-volume SPE and Cl-CSIA is a promising tool for assessing the transformation processes of these pollutants in the environment.
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