Untargeted Chemometric Characterisation of High Resolution Orbitrap Mass Spectra of Riverine and Point Source Dissolved Organic Matter

  • Jonathan Pemberton

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)

Abstract

Dissolved organic matter (DOM) is found in all natural aquatic systems and consists of a complex mixture of compounds that play a vital role in the ecosystem. However, anthropogenic compounds discharged into the water cycle threaten future water security and the aquatic ecosystem. These micropollutants are often low in concentration but their chronic exposure to organisms has been shown to have a wide range of adverse effects. This has led to a number of high profile media articles which demonstrate the growing public concern and awareness of the impact that micropollutants are having on the environment. Therefore, the comprehensive identification of known and unknown micropollutants and the characterisation of their sources is crucial to understanding the impact that these compounds may have on the environment. The chemical complexity of the DOM has until recently precluded detailed investigation of its chemistry at the molecular level. Chemical investigations of organic compounds have largely revolved around targeted analyses of priority pollutants for regulatory purposes. Comprehensive or untargeted analyses of DOM chemistry has until recently been an unattainable goal. However, recent advances in mass spectrometry, particularly routine liquid introduction using electrospray ionisation combined with high resolution mass spectrometry, have introduced the possibility of investigating DOM chemistry in hitherto unattainable detail.

This thesis aimed to develop and apply such techniques, specifically DI-Orbitrap HRMS and HPLC-Orbitrap HRMS, in an untargeted approach to investigate the DOM composition of point sources in comparison to the background river DOM at three UK sewage treatment works. A critical aspect of the method development was the implementation of a novel combination of statistical tools required to interpret the complex distribution of ions revealed in both the background river and sewage works effluent DOM.

DIMS revealed differences and similarities in the point source and background river DOM at all three sites. The complexity of the DI-HRMS spectra made a direct manual comparison between spectra, containing many thousands of individual ions, impractical. However, by using multivariate statistics including PCA and hierarchical cluster analysis, compositional differences between different DOM extracts were clearly revealed. Heatmaps were shown to provide an effective visualisation method to compare individual ions across different complex DI-HRMS spectra. Kruskal-Wallis analysis provided an essential data reduction step to determine the discriminating ions between different DOM spectra. The identification of compounds giving rise to these ions was achieved in some cases using HPLC-MS and HPLC-MS/MS. This approach highlighted compounds, which had been previously identified in sewage effluent demonstrating that this new approach prioritises a relevant list of compounds. Significantly, the method revealed a number of pollutants, not previously identified, as originating from a sewage treatment works. In particular, the combined use of DI-HRMS prior to HPLC-MS allowed the identification of oligomeric molecular species, which were not apparent using HPLC-MS alone.

Overall, the research presented in this thesis demonstrates a novel methodology of potentially wide utility for comprehensively assessing the chemistry of DOM from point sources in order to identify both known and previously unknown micropollutant contributions to aquatic environments.
Date of Award6 Dec 2019
Original languageEnglish
Awarding Institution
  • The University of Bristol
SupervisorRichard P Evershed (Supervisor) & Penny J Johnes (Supervisor)

Cite this

Untargeted Chemometric Characterisation of High Resolution Orbitrap Mass Spectra of Riverine and Point Source Dissolved Organic Matter
Pemberton, J. (Author). 6 Dec 2019

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)