Denatonium, torasemide and their transformation products as emerging contaminants in the aquatic environment

The work conducted for this thesis closes knowledge gaps in the context of denatonium, torasemide, and their transformation products as environmental pollutants. Denatonium is one of the bitterest compounds known today, and it is applied in numerous products to prevent an accidental or intentional consumption. Despite its wide application, this is the first study reporting denatonium itself as environmental pollutant. Generally, all water samples taken from WWTP effluents in Italy, Switzerland and from 22 plants in the federal state of Baden-Württemberg, Germany, contained denatonium with a maximum concentration of 341 ng/L. Denatonium is not significantly removed during conventional wastewater treatment and concentrations up to almost 200 ng/L were detected in wastewater-impacted surface waters. When ozonation is applied as advanced treatment technique, up to 74% of an initial denatonium load could be removed from wastewater. However, removal of denatonium was associated here by the formation of at least two polar transformation products (TPs) with unknown toxicological properties. Denatonium can undergo indirect photodegradation and seven TPs were identified for this process. They formed via amide hydrolysis, hydroxylation, N-dealkylation, and N-dearylation. Lidocaine was however the only TP of denatonium detected after conventional wastewater treatment and in surface waters, but the occurrence of this compound was associated with its application as local anesthetic rather than being a degradation product of denatonium. Generally, data presented previously in literature and the results obtained in this study point towards a persistent nature of denatonium and therefore an accumulation of this compound in the environment. Torasemide is an important loop diuretic and it was 2017 one of the ten most prescribed drugs in Germany. Maximum concentrations of this drug measured in this study for WWTPs and surface waters were about 350 ng/L and 70 ng/L, respectively. Despite an already known occurrence of torasemide throughout the urban water cycle, including very low concentrations in drinking water, no studies were performed related to its fate in the environment and an occurrence of TPs so far. Abiotic and biotic degradation experiments were therefore performed and overall sixteen products were identified. The following reaction mechanisms were involved in TP formation: aromatic and aliphatic hydroxylation, including further oxidation to carboxylic acids and quinone imines, amide cleavage, N-dealkylation, N-dearylation, and sulfonamide hydrolysis to sulfonic acids. The formation of quinone imines was in principle of great interest due to their highly reactive nature, but they were not detected in any environmental sample. While both major human metabolites hydroxytorasemide and carboxytorasemide were observed in WWTP influents, hydroxytorasemide seems to be removed during wastewater treatment and was most likely transformed into carboxytorasemide. Carboxytorasemide however was detected in all investigated WWTP effluents and surface waters, with an estimated maximum concentration of 1 µg/L

Identification of transformation products of denatonium – Occurrence in wastewater treatment plants and surface waters

Denatonium, one of the bitterest substances known to man, was recently identified as wastewater borne micropollutant in surface waters. Therefore, photodegradation experiments and electrochemical degradation were performed to identify abiotic and putative biotic transformation products (TPs). Indirect rather than direct photodegradation proved to be important for denatonium removal by solar irradiation and produced seven TPs. Amide hydrolysis, hydroxylation, N-dealkylation, and N-dearylation were revealed as the main mechanisms. Anodic oxidation of denatonium was related to the formation of overall ten products and despite considerable different yields, all TPs from indirect photodegradation were mimicked electrochemically. Among them, lidocaine was the only TP detected after conventional wastewater treatment and in surface waters. The occurrence of lidocaine was however associated with its application as local anesthetic rather than to a degradation of denatonium. The absence of additional products suggests that denatonium degradation is negligible under environmental conditions, supporting the previously described persistent nature of this compound. Advanced water treatment techniques however have the potential to degrade denatonium. About 74% of the initial denatonium load was removed from wastewater during pilot-scale ozonation. The degradation of denatonium was accompanied here with the formation of at least two polar products, which are passing unchanged through a sand filter after ozonation. Both substances have completely unknown (toxicological) properties and this study seems to be the first report about their structures in general, as none of them was found in any of the large compound libraries (e.g. PubChem). (C) 2019 Elsevier B.V. All rights reserved

Cumulative Neutral Loss Model for Fragment Deconvolution in Electrospray Ionization High-Resolution Mass Spectrometry Data

Fragment deconvolution is a crucial step during componentization of non-targeted analysis (NTA) high-resolution mass spectrometry (HRMS) data, aiming to filter out false positive (FP) signals that do not belong to the component. Moreover, inclusion of FP fragments could lead to, for example, wrong identification further down the workflow. Commonly used methods for deconvolution of fragment signals rely on the presence of a time domain (e.g., peak apex retention time difference and correlation analysis). However, when there is no or insufficient MS2 information in the time domain, these methods are unusable and only the mass domain remains. A probability based cumulative neutral loss (CNL) model for fragment deconvolution using the mass domain information was thus developed to allow deconvolution for such cases. The optimized model, with a mass tolerance of 0.005 Da and a CNL score threshold of -0.95, was able to achieve true positive rate (TPr) of 95.0%, a false discovery rate (FDr) of 25.6%, and a reduction rate of 39.9%. Additionally, the CNL model was extensively tested on real samples containing predominantly pesticides at different concentration levels and with matrix effects. Overall, the model was able to obtain a TPr above 95% with FD rates between 45% and 77% and reduction rates between 10% and 24%. Finally, the CNL model was compared with the retention time difference method and peak shape correlation analysis, showing that a combination of correlation analysis and the CNL model was the most effective for fragment deconvolution, obtaining a TPr of 93.1%, a FDr of 57.2%, and a reduction rate of 42.6%

Assessment of <i>N</i>‑Oxide Formation during Wastewater Ozonation

Worldwide, ozonation of secondary wastewater effluents is increasingly considered in order to decrease the load of organic contaminants before environmental discharge. However, despite the constantly growing knowledge of ozonation over the past few years, the characterization of transformation products (TPs) is still a major concern, particularly because such TPs might remain biologically active. It has been shown for selected tertiary amine pharmaceuticals that they react with ozone and form the corresponding <i>N</i>-oxides. This study therefore applies liquid chromatography-high resolution mass spectrometry (LC-HRMS) to assess the overall <i>N</i>-oxide formation during the pilot-scale ozonation of a secondary wastewater effluent from a major city in Germany. Sample analysis by LC-HRMS revealed the occurrence of 1,229 compounds, among which 853 were precursors attenuated by ozone and 165 were TPs. Further examination of precursors and TPs using Kendrick mass and Kendrick mass defect analysis revealed 34 pairs of precursors and products corresponding to a mono-oxygenation. Among these, 27 pairs (16% of all TPs) were consistent with <i>N</i>-oxides since the TP had a higher retention time than the precursor, a characteristic of these compounds. Using high resolution tandem mass spectrometry, 10 of these <i>N</i>-oxides could be identified and were shown to be stable during a subsequent filtration step

Reducing the influence of geometry-induced gradient deformation in liquid chromatographic retention modelling

Rapid optimization of gradient liquid chromatographic (LC) separations often utilizes analyte retention modelling to predict retention times as function of eluent composition. However, due to the dwell volume and technical imperfections, the actual gradient may deviate from the set gradient in a fashion unique to the employed instrument. This makes accurate retention modelling for gradient LC challenging, in particular when very fast separations are pursued. Although gradient deformation has been addressed in method-transfer situations, it is rarely taken into account when reporting analyte retention parameters obtained from gradient LC data, hampering the comparison of data from various sources. In this study, a response-function-based algorithm was developed to determine analyte retention parameters corrected for geometry-induced deformations by specific LC instruments. Out of a number of mathematical distributions investigated as response-functions, the so-called “stable function” was found to describe the formed gradient most accurately. The four parameters describing the model resemble the statistical moments of the distribution and are related to chromatographic parameters, such as dwell volume and flow rate. The instrument-specific response function can then be used to predict the actual shape of any other gradient programmed on that instrument. To incorporate the predicted gradient in the retention modelling of the analytes, the model was extended to facilitate an unlimited number of linear gradient steps to solve the equations numerically. The significance and impact of distinct gradient deformation for fast gradients was demonstrated using three different LC instruments. As a proof of principle, the algorithm and retention parameters obtained on a specific instrument were used to predict the retention times on different instruments. The relative error in the predicted retention times went down from an average of 9.8% and 12.2% on the two other instruments when using only a dwell-volume correction to 2.1% and 6.5%, respectively, when using the proposed algorithm. The corrected retention parameters are less dependent on geometry-induced instrument effects