Enhancing pharmaceutical micropollutant identification in biosolids through derivatisation and advanced chromatographic techniques

Fell, Kate Charlotte (2022) Enhancing pharmaceutical micropollutant identification in biosolids through derivatisation and advanced chromatographic techniques. PhD thesis, University of Glasgow.

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Pharmaceutical products (PhCs) are used to remedy illness, though the environmental impact of these PhCs after excretion, is something which many do not take into consideration. Wastewater treatment plants (WWTPs) were not designed to remove complex compounds like PhCs, and so PhCs are routinely detected in WWTP effluent, including sludge and biosolids. These are often applied to agricultural land to improve soil quality - introducing a diffuse route for PhCs into the environment – which has detrimental consequences on aquatic life. Thus, monitoring the PhC levels is advisable. This thesis describes the development of a suitable analysis method for detection of PhCs in complex biosolid matrices, which adheres to principles of Green Chemistry. Qualitative characterisation of non-spiked biosolid samples was implemented through ultrasound assisted sample preparation and gas chromatographic techniques. This research combines ultrasound assisted extraction and derivatisation with two-dimensional gas chromatography time of flight mass spectrometry (GCxGC-TOFMS). Optimisation of PhC derivatisation progressed through evaluation of the primary reaction mechanism in silylation: a nucleophilic substitution of the second order (SN2) and applying the knowledge to experimental design. Silylation using 50 μL of N-trimethylsilyl-N-methyltrifluoroacetamide (MSTFA), heated to 50°C for 40 mins was successful for derivatisation of several PhC compounds including carbamazepine and warfarin. Efficacy of silylation was dependant on the molar ratio of the reaction, with an increase in molar ratio increasing the desired derivative response (Le Chatelier’s principle was observed). Competing reactions, when PhCs were derivatised in a mixture, was found to have a negative effect on derivative response. Implementation of ultrasound via a sonotrode was optimised using design of experiment and was found to significantly reduce extraction (5 mins) and derivatisation time (30s), reducing overall sample preparation time by 37%. A significant reduction (97%) in solvent consumption was observed in comparison to traditional methods though an increase in %RSD was observed, due to issues stability of TMS derivatives. The application of GCxGC for analysis of biosolid samples overcame issues with sensitivity and co-elution observed with one-dimensional GC, and matrix effects observed with LC-MS/MS. Derivatives of carbamazepine, ibuprofen, paracetamol, salicylic acid were detected in the non-spiked biosolid samples using GCxGC-TOFMS and LC-MS/MS, though triclosan was also detected when using the GC method. The optimised UAE-UAD-GCxGC-TOFMS and associated data processing was evaluated for the non-targeted characterisation of biosolid samples. The data processing method was deemed sufficient in terms of repeatability, robustness, and selectivity, though issues with sensitivity were observed. Regardless, differences between the three biosolid samples and between pellets of the same biosolid were observed. The optimised method aligns with Green Chemistry principles ‘Prevention’, ‘Atom Economy’, ‘Safer Solvents and Auxiliaries’ and ‘Design for Energy Efficiency’, making it a sustainable alternative to traditional analysis methods.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Additional Information: Supported by funding from the Engineering and Physical Sciences Research Council (EPSRC).
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Colleges/Schools: College of Science and Engineering > School of Engineering
Supervisor's Name: Gauchotte-Lindsay, Dr. Caroline
Date of Award: 2022
Depositing User: Theses Team
Unique ID: glathesis:2022-83054
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 29 Jul 2022 13:49
Last Modified: 01 Aug 2022 09:58
Thesis DOI: 10.5525/gla.thesis.83054
URI: http://theses.gla.ac.uk/id/eprint/83054

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