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

• DOI: 10.1021/acs.est.0c08208
• Publication Date: 2021-05-19T00:08:53Z
• Authors: Kelly L. Pereira; Martyn W. Ward; John L. Wilkinson; Jonathan Brett Sa...; Daniel J. Bryant; William J. Dixon; Jacqueline F. Ham...; Alastair C. Lewis
• Keywords: 13. Climate action; 1600; 2304; Reproducibility of Results; Pesticides; 01 natural sciences; Chromatography, High Pressure Liquid; Mass Spectrometry; Water Pollutants, Chemical; Chromatography, Liquid; 0105 earth and related environmental sciences

Abstract The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultra-high 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 world-wide locations. The method detected >9,600 compounds in the individual environmental samples, arising from critical pollutant sources, including carcinogenic industrial chemicals, pesticides, pharmaceuticals, among others. This methodology offers considerable advances in the environmental sciences, providing a more complete assessment of sample compositions, whilst significantly increasing throughput.