USGS Science⌕ Search

USGS · 70019504

Identification of ionic chloroacetanilide-herbicide metabolites in surface water and groundwater by HPLC/MS using negative ion spray

Abstract

Solid-phase extraction (SPE) was combined with high-performance liquid chromatography/high-flow pneumatically assisted electrospray mass spectrometry (HPLC/ESP/MS) for the trace analysis of oxanilic and sulfonic acids of acetochlor, alachlor, and metolachlor. The isolation procedure separated the chloroacetanilide metabolites from the parent herbicides during the elution from C 18 cartridges using ethyl acetate for parent compounds, followed by methanol for the anionic metabolites. The metabolites were separated chromatographically using reversed-phase HPLC and analyzed by negative-ion MS using electrospray ionization in selected ion mode. Quantitation limits were 0.01 μg/L for both the oxanilic and sulfonic acids based on a 100-mL water sample. This combination of methods represents an important advance in environmental analysis of chloroacetanilide−herbicide metabolites in surface water and groundwater for two reasons. First, anionic chloroacetanilide metabolites are a major class of degradation products that are readily leached to groundwater in agricultural areas. Second, anionic metabolites, which are not able to be analyzed by conventional methods such as liquid extraction and gas chromatography/mass spectrometry, are effectively analyzed by SPE and high-flow pneumatically assisted electrospray mass spectrometry. This paper reports the first HPLC/MS identification of these metabolites in surface water and groundwater.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Imma Ferrer, E.M. Thurman, Damia Barcelo. 1997-11-15. Identification of ionic chloroacetanilide-herbicide metabolites in surface water and groundwater by HPLC/MS using negative ion spray. https://doi.org/10.1021/ac9704671

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Exploring the potential of electrospray-Orbitrap for stable isotope analysis using nitrate as a model

Widely used isotope ratio mass spectrometers have limited capabilities to measure metabolites, drugs, or small polyatomic ions without the loss of structural isotopic information. A new approach has recently been introduced that uses electrospray ionization Orbitrap to measure multidimensional isotope signatures of intact polar compounds. Using nitrate as a model compound, this study aims to establish performance metrics for comparisons with conventional IRMS at the natural abundance level. We present a framework on how to convert isotopolog intensities to δ values that are commonly used in the isotope geochemistry community. The quantification of seven nitrate isotopologs provides multiple pathways for obtaining the primary N and O δ values including non-mass-dependent O isotope variations, as well as opportunities to explore nonrandom isotopic distributions (i.e., clumping effects) within molecular nitrate. Using automation and the adaptation of measurement principles that are specific to isotope ratio analysis, nitrate δ15NAIR, δ18OVSMOW, and δ17OVSMOW were measured with a long-term precision of 0.4‰ or better for isotopic reference materials and purified nitrate from environmental samples. In addition, we demonstrate promising results for unpurified environmental samples in liquid form. With these new developments, this study connects the two largely disparate mass spectrometry fields of bioanalytical MS and isotope ratio MS, thus providing a route to measure new isotopic signatures in diverse organic and inorganic solutes.

Analytical Chemistry↗

New organic reference materials for hydrogen, carbon, and nitrogen stable isotope-ratio measurements: caffeines, n-alkanes, fatty acid methyl esters, glycines, L-valines, polyethylenes, and oils

An international project developed, quality-tested, and determined isotope−δ values of 19 new organic reference materials (RMs) for hydrogen, carbon, and nitrogen stable isotope-ratio measurements, in addition to analyzing pre-existing RMs NBS 22 (oil), IAEA-CH-7 (polyethylene foil), and IAEA-600 (caffeine). These new RMs enable users to normalize measurements of samples to isotope−δ scales. The RMs span a range of δ 2 H VSMOW-SLAP values from −210.8 to +397.0 mUr or ‰, for δ 13 C VPDB-LSVEC from −40.81 to +0.49 mUr and for δ 15 N Air from −5.21 to +61.53 mUr. Many of the new RMs are amenable to gas and liquid chromatography. The RMs include triads of isotopically contrasting caffeines, C 16 n -alkanes, n -C 20 -fatty acid methyl esters (FAMEs), glycines, and l -valines, together with polyethylene powder and string, one n -C 17 -FAME, a vacuum oil (NBS 22a) to replace NBS 22 oil, and a 2 H-enriched vacuum oil. A total of 11 laboratories from 7 countries used multiple analytical approaches and instrumentation for 2-point isotopic normalization against international primary measurement standards. The use of reference waters in silver tubes allowed direct normalization of δ 2 H values of organic materials against isotopic reference waters following the principle of identical treatment. Bayesian statistical analysis yielded the mean values reported here. New RMs are numbered from USGS61 through USGS78, in addition to NBS 22a. Because of exchangeable hydrogen, amino acid RMs currently are recommended only for carbon- and nitrogen-isotope measurements. Some amino acids contain 13 C and carbon-bound organic 2 H-enrichments at different molecular sites to provide RMs for potential site-specific isotopic analysis in future studies.

Analytical Chemistry↗

Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log–log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model’s parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

Analytical Chemistry↗