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An Automated Methodology for Non-targeted Compositional Analysis of Small Molecules in High Complexity Environmental Matrices Using Coupled Ultra Performance Liquid Chromatography Orbitrap Mass Spectrometry
Author(s) -
Kelly L. Pereira,
Martyn W. Ward,
John L. Wilkinson,
J. Brett Sallach,
Daniel J. Bryant,
William G Dixon,
Jacqueline F. Hamilton,
Alastair C. Lewis
Publication year - 2021
Publication title -
environmental science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.851
H-Index - 397
eISSN - 1520-5851
pISSN - 0013-936X
DOI - 10.1021/acs.est.0c08208
Subject(s) - orbitrap , mass spectrometry , environmental analysis , sample preparation , environmental chemistry , chemistry , chromatography , process engineering , environmental science , biochemical engineering , engineering
The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultrahigh-resolution mass spectrometers, such as the Orbitrap, provide unprecedented analytical capabilities to probe the molecular composition of such matrices, but the extraction of non-targeted chemical information is impractical to perform via manual data processing. Automated non-targeted tools rapidly extract the chemical information of all detected compounds within a sample dataset. However, these methods have not been exploited in the environmental sciences. Here, we provide an automated and (for the first time) rigorously tested methodology for the non-targeted compositional analysis of environmental matrices using coupled liquid chromatography-mass spectrometric data. First, the robustness and reproducibility was tested using authentic standards, evaluating performance as a function of concentration, ionization potential, and sample complexity. The method was then used for the compositional analysis of particulate matter and surface waters collected from worldwide locations. The method detected >9600 compounds in the individual environmental samples, arising from critical pollutant sources, including carcinogenic industrial chemicals, pesticides, and pharmaceuticals among others. This methodology offers considerable advances in the environmental sciences, providing a more complete assessment of sample compositions while significantly increasing throughput.

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