Open Access

Abstract The component-specific quality of linings and prefabricated components made from refractory castables is largely determined by the processing properties during the placement of refractory castables. These are, in particular, the rheological properties, specifically the shear rate-de-pendent dynamic viscosity. Existing measurement methods for determining the shear rate-dependent dynamic viscosity of aggregate-containing suspensions such as refractory castables are prone to errors and inaccurate. From a scientific point of view, an exact determination of the shear rate-dependent dynamic viscosity as well as influencing variables on the rheological properties of refractory castables cannot be realized due to the lack of measurement methods. This leads to contradictory and unclassifiable statements on the influence of aggregate fractions on the rheological properties of refractory castables in the state of science and technology. From a technical point of view, this complicates the rheological optimization of refractory concretes. Within this work, a measuring method was developed with which the shear rate-dependent dynamic viscosity of aggregate-containing suspensions such as refractory castables can be determined precisely. The measurement method is based on a spherical viscometer for deter-mining the dynamic viscosity and the coupling with a CFD-FEM simulation to determine the actual prevailing shear rate. The determination of the dynamic viscosity is based on the determination of the pull-out speed at a defined pull-out force (force-controlled) according to Stokes' law. It was shown that the pull-out speed and the shear rate can be correlated linearly, which made it possible to redesign the measuring method in a shear rate-controlled manner. A check showed that the shear rate-dependent dynamic viscosity of aggregate-containing suspensions such as refractory castables could be determined just as accurately. The CFD-FEM simulation downstream of the test was no longer necessary. It was demonstrated that the shear rate-dependent dynamic viscosity of aggregate-containing suspensions increases with increasing mineral aggregate content. Furthermore, it was shown that the complex composition of refractory castables defines their rheological properties. Variations in the particle size distribution of the medium grain and the coarse grain can significantly influence the shear rate-dependent dynamic viscosity, but do not necessarily have to. This also depends on the particle size distribution of the slurry. Furthermore, the dynamic viscosity can be influenced to a different extent at different shear rates. An unpredictable influence of increasing shear rates on dynamic viscosity can therefore be observed. This complexity complicates the rheological optimization of refractory concretes. Nevertheless, it has been proven that a rheological optimization of refractory concretes, for example the suppression of dilatancy, can also be achieved by optimizing the particle size distribution of the mineral aggregates.

Microplastics (MP) (1 μm to 5 mm) enter riverine environments in various ways. Point sources (e. g. industrial plants) can be differentiated from diffuse sources (e. g. erosion). Once MP has entered river systems, it underlies hydrodynamic processes and is finally transported towards the oceans. Due to fragmentation, MP particles decrease in size during transport. MP particles are highly heterogeneous considering density and shape, which makes spatially and temporally high resolved sampling difficult and thus hampers the quantification of annual loads in rivers. Within this thesis, we conducted a spatially and temporally high resolved monitoring in the River Rhine with the aim to quantify an annual MP load at our study site, Koblenz. With a literature review we exposed that most studies present their results by means of particle number instead of particle mass. Also, many studies did not consider spatial nor temporal aspects within their sampling design. For the first time, we presented a compilation of global annual load values within river systems, partly using innovative methodological approaches to convert MP items to MP mass. Hereby, a correlation between catchment area and annual MP load could be detected. Global loads showed a large range (< 1 kg/y – 1533 t/y). To estimate the annual MP load of the River Rhine at the study site Koblenz, we performed a temporally high resolved sampling using sedimentation boxes (SB, time-integrated samples over months) and a continuous flow centrifuge (CFC, discrete sampling). Via thermal degradation procedures, polymer concentration in mg/g was estimated for PP, PE, PS and PVC. Hereby, annual loads of 400 t (SB) and 60 t (CFC) were calculated. Deviation of both methods was more pronounced for polymers with lower density (PP and PE), whereas PVC loads were comparable. This led to further laboratory experiments, which showed that particle retention efficiency of the SB was varying with the particle’s properties. Thus, the SB sample might not be representative for the river’s conditions. Furthermore, the CFC had difficulties in retaining polymers with lower density (losses up to > 50 % were noticed). Nevertheless, the calculated MP loads do fit well into our compilation of global MP load values. An extensive quantification of retention efficiencies for several polymer types and particle sizes (SB) or an additional sampling step for the clearwater of the CFC for low-dense MP particles could lead to more robust MP concentration values in the future. Depth-distributed sampling campaigns with a filter cascade and filter nets revealed strong density-dependant vertical gradients within the water column. These gradients were even apparent within the smallest particle size classes and thus were larger than a theoretical determination based on the Rouse number would have suggested. Both, filter cascade and filter net showed a positive correlation between river discharge and MP concentration. This correlation allows for a first speculation on MP sources within the River Rhine: The main source of MP seems, in congruence with suspended sediments, to be a diffuse entry which rises with rising water level. In contrast, a constant entry from a point source would lead to lower concentrations during flood events due to dilution. Within this work we could point out that extensive research is needed considering the understanding of different sampling devices and their sampling efficiencies. First approaches for an improvement of these limitations have been shown. Still, a combination of sampling techniques is necessary to cover the portfolio of potential issues regarding MP research. For a more precise quantification of annual MP loads, standardisation of procedures on all working steps is urgently needed.

Affordable RGB-D cameras have gained broad research attention in computer vision. This imaging modality provides registered 3-D and RGB data of the perceived environment in the point cloud data format. RGB-D cameras and point clouds allow for a seamless integration of object recognition in mobile robotics applications. Not only do point clouds pose a potential for novel algorithms, the provided geometric information also facilitates estimating adequate positions for mobile manipulation – an action that often follows the recognition process in mobile robotics. Research on vision algorithms based on 3-D data is far less advanced than on 2-D images. Further, RGB-D cameras also pose some technical challenges. Due to their inner workings, they provide erroneous measurements, have a limited range and a much lower resolution than RGB cameras. In this thesis, I will focus on the object classification and detection parts of vision pipelines for mobile robotics. The main research question is whether point clouds from low-cost RGB-D cameras can be used to reliably solve these tasks. I decided to use a traditional algorithm for my investigations. Traditional algorithms usually demand less computational resources for training and require less data to build a model for inference. For these and other reasons some application scenarios might restrict or prohibit using methods based on deep neural networks (DNN). The presented point cloud processing pipeline is a non-parametric approach to object classification and detection. It is inspired by the local Naive-Bayes Nearest Neighbor (NBNN) and the Implicit Shape Model (ISM) algorithms originally introduced for 2-D images. Local feature descriptors are used to construct a spatial code-book during the training stage. In the test stage this codebook is used in a Hough voting scheme to generate object hypotheses. I will carefully adapt ideas from the above methods and extend several pipeline steps by novel contributions. At all times, I will target fast processing with limited computational resources in mind. In a first step, I will focus on isolated objects for classification to gain insights into using point clouds for vision. Subsequently, the presented pipeline will be extended to handle noisy data for object detection in cluttered environments. The contributions of this thesis include an efficient sampling method to find suitable locations for local descriptors and the creation of a descriptive codebook with ranked feature descriptors. The hypothesis generation is followed by an elaborate hypothesis verification step and an additional verification with global feature descriptors in an ensemble classifier. Further, I introduce modifications to two popular local descriptors and also extend them to the global scale. The developed approaches are evaluated on publicly available datasets with simulated and real sensor data. Further, the mobile service robot Lisa was used for evaluation during several competitions and achieved excellent results. The results of this work enable fast and reliable shape classification of isolated objects, as well as object detection in cluttered environments. The complete pipeline is open-source and is published online in a software repository under a permissive license.

Specifically designed and accurate force fields are of central importance in molecular simulations, as they are often required when investigating new or slightly modified systems. Their parameterization, referred to as force-field parameter optimization, is a complex multi-modal optimization challenge. It requires balancing the parameter’s transferability between various optimization objectives, while their interdependencies often are non-trivial and hard to unravel. This cumulative dissertation addresses this optimization challenge by systematically developing and extending an automatized multi-scale force-field parameter optimization workflow. An important feature is ist modular design that (a) allows the optimization of any amount and combination of force-field parameters towards any type and amount of target properties, and (b) facilitates the extension by additional optimization algorithms or objective functions. First, the workflow’s foundation and a proof-of-concept is provided by simultaneously optimizing the Lennard-Jones parameters towards n-octane’s liquid-phase density (i.e. a multi-molecular, thermodynamic property) and its relative conformational Energies (i.e. a single molecular structural property). By showing that the applicability of the force field was expanded, the simultaneous multi-scale optimization workflow is established. Then, the optimization workflow’s hyperparameters are fine-tuned to improveits results and it is shown that by reasonably balancing the optimization objectives using weighting factors the previously introduced errors are reduced. Next, the optimization procedure’s efficiency is increased by substituting the most time-consuming molecular dynamics simulations by machine learning surrogate models. Those simulations are required repeatedly throughout the optimization, and due to the workflow’s iterative nature, they need to be performed just-in-time. By substituting them with machine learning surrogate models the required run time is approximately reduced by 20-fold. Additionally, guidelines for the model’s training and selection are included. Subsequently, as a challenging test of the workflow, the Lennard-Jones Parameters for 1-bromobutane and 2-bromobutane are optimized. They exhibit a σ-hole allowing halogen bonding, which is subject to current research, that can be supported by accurate simulation models. It is shown that the modeling is improved by the herein presented multi-scale optimization approach, but that further refinements with respect to the workflow and the modeling are necessary. In conclusion, promising approaches to improve the optimization workflow and the modeling are suggested.

In order to support both the provision of clean drinking water and the preservation of biodiversity in aquatic ecosystems, a comprehensive scientific understanding of the identity, concentration, and behavior of anthropogenic pollutants in the aquatic environment is essential. Organic micropollutants constitute a large group of anthropogenic pollutants and originate from all areas of daily human life: pharmaceuticals are part of the daily routine for many people, pesticides are crucial for food production, and organic chemicals are used in the industrial production of paper, plastics, paints, and many other products. These micropollutants enter the water cycle, either in their parent form or as transformation products, where they can lead to potentially harmful effects. In addition to target methods, non-target approaches have been established as powerful tools for comprehensively investigating these compounds in the water cycle. Beyond the analytical challenges of instrumentally detecting these compounds, the prioritization and evaluation of the large datasets generated by non-target pose both chemical and data science challenges, forming the overarching theme of this work. The work comprises three studies demonstrating the development and application of non-target screening (NTS) methodologies. In an NTS using high-performance liquid chromatography (HPLC) coupled with high-resolution mass spectrometry (QTOF-MS/MS), 112 samples from the river Nidda and seven of its tributaries were analyzed. On average, approximately 2700 signals, or features, were detected per sample. To filter these extensive data and prioritize unknown compounds, a method was first developed to reliably assign adducts, isotopologues, source fragments and other ionization products to a common component based on retention time and peak shape. In the next step, the prioritization of unknown compounds was achieved by highlighting features that were detected specifically at individual sites under investigation, but which were not typically considered to originate from municipal wastewater. This was accomplished by comparing the data from the Nidda river system with NTS data from municipal wastewater treatment plant effluents. Only the highlighted, Nidda-specific features were considered further. As a result, an average data prioritization of 7% across all samples was achieved, leading to the identification of nine compounds. Among these were the industrial compound Nylostab S-EED™, which had not been previously observed in the environment and three algal toxins, whose occurrence resulted from the algal bloom of a nearby water body. In the second study, investigations focused on permanently cationic compounds in suspended particulate matter samples from the rivers Rhine and Saar. The data prioritization was based on the specific physicochemical properties of this substance group. Following extraction, a two-step procedure was applied, relying on interactions with strong ion exchangers and chromatography using deuterated solvents. This resulted in 5% of the detected NTS signals being labeled as potentially cationic compounds. Based on this, 22 compounds were identified, four of which were previously unknown. Trend analyses covering the period from 2005/2006 to 2018, along with an assessment of the ecotoxicological risks based on semi-quantitatively determined concentrations, suggest that identified compounds such as Basic Yellow 28 and Fluorescent Brightener 363 may have a high ecotoxicological relevance. The third study focused on the analysis of samples from disconnected, inter-regional river systems. In collaboration with the local environmental authorities, a three-year study was conducted, analyzing 524 samples from 79 sites along rivers across Saxony. For this purpose, a method was developed that allowed for the characterization of sites based on five categories, considering both known and unknown compounds to assess their chemical contamination. The results were classified by calculating the modified z-scores within each category. The method was validated based on the results of target analysis in the same samples. As a result of the study, 13 sites were classified as anomalous due to high z-scores, as elevated levels of pharmaceuticals, industrial chemicals but also unclassified unknown compounds were detected. At two potentially industrially contaminated sites, the Münzbach and Dorfbach Oberschindmaas, nine compounds were identified and their concentrations were estimated using a 1-point calibration. For the compound hexa(methoxymethyl)melamine, a concentration in the range of 300 µg/L was determined, suggesting a considerable risk for the environment (risk quotient: 5.6).

The rapid evolution of wireless communication technologies, particularly the introduction of Fifth-Generation (5G) networks and the anticipated transition to Sixth-Generation (6G) systems, ushers in a new era of connectivity, enabling transformative applications across industrial automation, the Internet of Everything (IoE), and the Industrial Internet of Things (IIoT). However, the exponential growth in the number of connected devices, stringent reliability requirements, and increasing security challenges pose significant hurdles for current network architectures. This dissertation addresses these challenges by proposing innovative frameworks and mechanisms that enhance reliability, optimize resource utilization, and strengthen security and trust management in next-generation mobile networks. The first contribution of this dissertation focuses on reliability enhancements in 5G networks. While existing mechanisms, such as Dual Connectivity (DC) and Network Function (NF) redundancy, provide partial solutions, they do not fully resolve application-layer reliability and dynamic server failover. To bridge this gap, this work introduces the Make-Before-Break- Reliability (MBBR) and enhanced Make-Before-Break-Reliability (eMBBR) mechanisms. These frameworks proactively establish redundant communication paths, ensuring seamless failovers with minimal latency and service disruption. By extending reliability to the application layer and integrating adaptive path selection and dynamic failover capabilities, these mechanisms offer robust solutions for latency-sensitive and mission-critical applications. The second major contribution addresses bandwidth optimization for industrial networks. The black channel paradigm, widely adopted for industrial safety applications, relies heavily on cyclic keep-alive messages to detect connection loss, leading to significant signaling overhead. This dissertation proposes a novel solution leveraging 5G Channel State Information (CSI) to replace cyclic messaging with real-time connection quality monitoring. By exposing CSI metrics, such as Signal-to-Noise Ratio (SNR) and Channel Quality Indicator (CQI), to the application layer, the proposed mechanism reduces bandwidth consumption while maintaining the safety and reliability requirements of industrial networks. Addressing the growing complexity of security requirements in IIoT, the third contribution introduces the AF-based Security Framework (AERO) framework. This framework empowers application providers to dynamically apply cryptographic mechanisms to the user plane, overcoming the limitations of legacy protocols and eliminating the need for redundant security layers. By ensuring backward compatibility and enabling both static and dynamic configuration of user plane encryption, AERO enhances security while minimizing computational overhead and reducing transmission delays. The fourth and final contribution redefines trust management in mobile networks through the SecUre deleGAtion of tRust (SUGAR) framework. Traditional trust models, which rely on identity chips for each connected device, are becoming increasingly impractical in the IoE era, where billions of devices require connectivity. The SUGAR framework introduces a delegation-based trust model, allowing Parent Devices (PaDs) to delegate trust to multiple Child Devices (ChDs) securely. This approach eliminates the need for individual identity chips, significantly reducing costs and enhancing scalability. Integration with System-on-a-Chip (SoC)-based identity enclaves further strengthens the security of trust credentials. The findings of this dissertation offer substantial contributions to both academia and industry. The proposed frameworks effectively address critical gaps in current 5G standards and provide valuable contributions for developing the 6G framework. By enhancing reliability, optimizing bandwidth, and redefining security and trust management, this dissertation provides a comprehensive foundation for the design and deployment of next-generation mobile networks. Furthermore, the solutions presented are adaptable to a wide range of applications, including industrial automation, autonomous systems, and smart city infrastructures. In conclusion, this dissertation represents a significant step toward realizing the full potential of next-generation mobile networks. By addressing key challenges in reliability, resource optimization, security, and trust management, the proposed frameworks pave the way for scalable, secure, and efficient mobile ecosystems that are essential for the dynamic and interconnected world of the future.

Eisenbahnunternehmen setzen Condition Monitoring Systeme (CMS) zur Überwachung ihrer Anlagen und Komponenten ein. CMS sind im Risikomanagement der Branche relevant, aber ihr Einsatz leidet unter einem Präventionsparadoxon: Sie werden oft erst nach Schäden oder Richtlinien eingeführt. CMS können auch den Instandhaltungsaufwand reduzieren. Bei den streckenseitigen WTMS tragen Infrastrukturbetreiber die Kosten, während Verkehrs-unternehmen den Nutzen durch effizientere Instandhaltung sehen. Um fundierte Geschäftsmodelle zu entwickeln, muss deshalb der Nutzen von CMS quantifiziert werden. Die Informationsqualität, einschließlich der Sensoren und der Symptomaussagekraft, beeinflusst diesen Nutzen. Diese Verbindung von Anwendungswert und Nutzen ist bisher unzureichend erforscht. Aufgrund dessen ist das Forschungsziel folgendermaßen gesetzt worden: Entwicklung eines systemdynamischen Modells und eines Verfahrens zur Erfassung des Informationswertes von Condition Monitoring Systems, anhand des Fallbeispiels der Radsatzlagerüberwachung im Eisenbahnverkehr.“ Das Forschungsziel dieser Arbeit umfasst als Erkenntnisziel das Verständnis der Zusammenhänge und Wechselwirkungen im CMS und dabei den Nutzen des Einsatzes der Systeme zu bewerten. Das Gestaltungsziel beinhaltet die Untersuchung der Eignung des systemdynamischen Verfahrens. Zur Erreichung dieser Ziele sollen folgende Forschungsfragen beantwortet werden: 1. Welche Ziele verfolgen die Eisenbahnorganisationen in Bezug auf den Betrieb ihrer Radsatzlager und inwiefern können die Informationen aus den Messdaten der heutzutage eingesetzten Radsatzlagerüberwachungssysteme zur Zielerreichung beitragen? 2. Lassen sich mit der systemdynamischen Vorgehensweise, die für die Bewertung von CMS relevanten Wechselwirkungen im Eisenbahnsystem abbilden? 3. Lässt sich anhand der systemdynamischen Vorgehensweise untersuchen, welche Informationen für die Erhöhung des Nutzens der Radsatzlagerüberwachungssysteme relevant sind? Die Ergebnisse der Arbeit erwirken die Erkenntnis, dass die Methodik dazu geeignet ist, die relevanten Zusammenhänge und Wechselwirkungen darzustellen und mithilfe der Simulationsergebnisse relevante Instandhaltungsstrategien und der Nutzen von RDMT zu bewerten. Damit sind die Ergebnisse sowohl für die Forschung als auch für Entscheidungsträger in der Eisenbahnbranche relevant.

The presence of synthetic chemicals in the environment can affect both ecosystems and human health. In particular, the increasing contamination of the aquatic environment by complex mixtures of anthropogenic trace substances has become a major global concern. Once released into the environment, these compounds can undergo diverse transformation processes to form a wide range of transformation products (TPs), which are commonly unknown. Transformation inevitably alters the pattern of contamination and exposure, as new substances are formed with frequently different physicochemical properties, environmental behavior and toxicity in comparison to their precursor compounds. For instance, TPs can exhibit significantly greater persistence and mobility in the aquatic environment, posing a threat to both aquatic ecosystems and drinking water resources. Therefore, TPs need to be considered in the risk assessment and authorization process of chemicals. However, due to a combination of predictive, analytical, and regulatory challenges, TPs currently remain largely unrecognized and unregulated. By addressing these challenges, this thesis comprehensively characterizes the entry paths, occurrence, fate, and (eco)toxicological relevance of selected TPs in the aquatic system in Germany. These TPs have been largely overlooked in environmental studies and aquatic monitoring programs for decades, despite their precursors being produced and used in large quantities on a global scale. The highly persistent and mobile substance trifluoroacetate (TFA) has garnered significant attention in recent years due to its diverse sources, widespread occurrence in the aquatic environment, and the lack of economically viable options to remove TFA from contaminated waters. One of the most frequently discussed diffuse sources is the formation of TFA in the atmosphere through the oxidation of volatile precursors and its subsequent scavenging from the atmosphere by wet deposition. Despite the previously reported occurrence of TFA in precipitation, the lack of recent and comprehensive data has severely limited the understanding of the significance of wet deposition as a source of TFA to the (aquatic) environment. Thus, in the present work, a nationwide field monitoring campaign covering all precipitation events over a one-year sampling period was conducted at eight sites across Germany. Samples were analyzed for TFA using ion exchange chromatography (IC) coupled to negative-ion electrospray tandem mass spectrometry (ESI-MS/MS). Of the analyzed samples, 16% exhibited TFA concentrations ≥ 1 μg/L. The precipitation-weighted average TFA concentration of 0.34 μg/L highlighted that wet deposition alone is responsible for approximately 0.3 to 0.4 μg/L of TFA in surface waters in Germany. The annual wet deposition fluxes ranged from 91 to 400 μg/m², with the highest fluxes observed in densely populated regions. The annual wet deposition of TFA for Germany during the observation period was estimated to be 68 t. The sampling revealed a pronounced seasonality, with the highest concentrations and wet deposition fluxes of TFA observed in summer. Pearson correlation analyses indicated that the transformation of TFA precursors in the troposphere is enhanced in summer due to elevated concentrations of photochemically generated oxidants, primarily •OH, which ultimately results in increased atmospheric TFA deposition. Overall, the study provided the first published data on TFA in precipitation in Germany since 1995/96. The derived data serves as a benchmark for future studies. In addition, it allows for the establishment of mass balances and can be used to develop models to predict the loads of TFA entering the aquatic environment from multiple sources. The lack of robust historical data on the wet deposition fluxes of TFA also impeded long- term trend analyses. Specifically, a postulated increase in atmospheric formation and deposition of TFA due to substantial emission increases of numerous volatile TFA precursors in recent decades remained unquantified. To address this knowledge gap, archived plant samples were analyzed to evaluate the long-term temporal trends in the atmospheric deposition of TFA in Germany. A robust and highly sensitive analytical method for TFA in plant matrices was developed and validated. The method encompassed a three-step sequential extraction procedure followed by the analysis of the diluted sample extracts using IC-ESI-MS/MS. Subsequently, archived leaf samples of various tree species and sampling sites from the German Environmental Specimen Bank (observation period: 1989−2020) were analyzed for TFA. Statistical analysis revealed significant (p < 0.05) positive trends in TFA concentrations in plant leaves, which is likely the result of both phytoaccumulation and increasing emissions of gaseous TFA precursors over the observation period. The concentrations increased by factors of up to 12 from 1989 to 2020. The highest concentrations (up to ∼1,000 μg/kg dry weight) were found in Lombardy poplar leaves. Overall, the study presents the first trend analysis of TFA in biota and raises awareness of the escalating atmospheric deposition of TFA over the past three decades. Sulfamate has previously been identified as a TP of the artificial sweeteners cyclamate and acesulfame in wastewater and drinking water treatment. The preliminary results indicated that sulfamate concentrations in wastewater treatment plant (WWTP) effluent are substantially higher than those of other wastewater-borne contaminants. However, despite its high global production and usage, no information was available on the sources, occurrence, and environmental significance of sulfamate in the aquatic system in Germany. To close this knowledge gap, a quantitative monitoring approach of different urban water cycle compartments was conducted. Target analysis based on IC-ESI-MS/MS revealed exceptionally high concentrations of sulfamate in wastewater (up to 1,900 μg/L), surface water (up to 580 μg/L), and finished drinking water (up to 140 μg/L) in Germany. Considering the limited data on short-term ecotoxicity, approximately 30% of the sulfamate concentrations detected in groundwater and surface water samples exceeded the derived predicted no-effect concentration (PNEC) of sulfamate. Therefore, the potential impact of sulfamate on the aquatic ecosystem in Germany cannot be excluded. Municipal WWTP effluent was identified as the primary source of sulfamate for the aquatic system, as its concentrations correlated positively (r > 0.77) with the municipal wastewater tracer carbamazepine in samples from different waterbodies. Ozonation and activated sludge experiments demonstrated that sulfamate can be formed through chemical and biological degradation of various precursors containing a sulfonamide group. Nevertheless, the transformation of precursors to sulfamate in WWTPs and receiving waters was found to be quantitatively insignificant, due to the substantial direct use of sulfamic acid as a descaling agent in domestic and industrial applications. Laboratory batch experiments, in conjunction with the findings from the sampling conducted at full- scale waterworks, demonstrated that the commonly applied drinking water treatment techniques, including ozonation and activated carbon filtration, are largely ineffective in removing sulfamate. Bank filtration was identified as the only option to efficiently eliminate sulfamate from contaminated raw water resources (removal: 62% to 99%). Overall, the study presents the first comprehensive analysis of sulfamate in the urban water cycle and suggests that there may be other high production volume inorganic chemicals that are currently overlooked in environmental studies and monitoring programs. Despite pantoprazole (PPZ) being one of the most widely prescribed human pharmaceuticals globally, consistently low concentrations of this proton-pump inhibitor in environmental water samples have been documented. This can be attributed to the extensive metabolism of PPZ within the human body, with only minor amounts of the parent compound being excreted. Since environmental monitoring and risk assessment for regulatory purposes focus on the parent substances of pharmaceuticals, it was assumed that the current environmental exposure associated with the use of PPZ is considerably underestimated. In the presented thesis, 4′-O-demethyl-PPZ sulfide (M1) was identified as the most relevant PPZ metabolite for environmental analysis. This was achieved by applying reversed-phase high-performance liquid chromatography (RP- HPLC) coupled to high-resolution mass spectrometry (HRMS) to urine samples of a PPZ user, as well as to municipal wastewater. M1, which had not been investigated in previous monitoring studies, was found to be ubiquitous in WWTP influent and effluent (max.: 3 μg/L, detention frequency: 100%) as well as in surface water (max.: 1.2 μg/L; detection frequency: 97%) in Germany. Its average surface water concentration was approximately 30 times higher than that of the parent compound PPZ. Moreover, quantitative structure- toxicity relationship (QSTR) modeling indicated a lower preliminary freshwater PNEC for M1 (4.8 μg/L) compared to PPZ (28 μg/L). The analysis of archived suspended particulate matter (SPM) samples from the Rhine at Koblenz revealed that the concentrations of M1 increased significantly from 2005 to 2015 and were positively correlated with the prescription volume of PPZ. Conventional biological wastewater treatment was found to be insufficient to remove M1 (average removal: 22%). Laboratory-scale experiments and the analysis of samples taken after different treatment steps of an advanced full-scale WWTP demonstrated that post-treatment with activated carbon as well as ozonation can significantly improve the removal of M1 and PPZ during wastewater treatment, thereby reducing their release to the aquatic environment. During ozonation, a rapid oxidation of M1 was observed, accompanied by the formation of several ozonation products, which were proposed for the first time. The identity of the main ozonation TPs of M1 was confirmed through the synthesis of reference compounds. Their detection in samples collected after the ozonation step of a full-scale WWTP demonstrated the transferability of the laboratory-scale ozonation experiments. M1 was found to be sufficiently removed from contaminated source waters (max. raw water concentration: 0.25 μg/L) by bank filtration under different redox conditions (removal ≥ 80 %) and by other commonly applied purification processes in drinking water production. In summary, this study revealed that the environmental exposure and risk associated with the use of PPZ have been previously underestimated, which likely extends to other human pharmaceuticals. Therefore, these findings call for more sophisticated approaches to environmental monitoring and risk assessment of pharmaceuticals that take TPs into account. This thesis provides an in-depth understanding of the entry paths, occurrence, fate, and environmental significance of selected TPs in the aquatic system in Germany. It significantly advances our understanding of the introduction of TFA into the water cycle, by characterizing the source of wet deposition and elucidating long-term temporal trends of atmospherically deposited TFA. Additionally, the thesis gives comprehensive insights into the formation, behavior, removability, and potential (eco)toxicological risks of sulfamate, PPZ and its TPs. The thesis addresses key challenges in assessing and integrating TPs into chemical management and presents solutions to overcome these challenges. Finally, it highlights the urgent need for increased focus on TPs in research, aquatic monitoring, and regulation to safeguard the environment and human health.

Microplastics (MP), i.e., plastic particles < 5 mm, are perceived as a threatening envi- ronmental and human health issue. Growing public interest in this class of contaminants requires standardized and harmonized methods for their quantification. While an abun- dance of analytical methods (both particle-based and mass-based) for the detection of microplastics is available, existing studies on the quantity of MP in the environment lack comparability. Therefore, the aim of this work was to establish a fast, reliable screen- ing method for the quantification of the most common synthetic polymers in complex environmental samples. This was accomplished by a two-step pressurized liquid extraction (PLE) followed by analysis via pyrolysis coupled to gas chromatography and mass spectrometry (Py–GC– MS). In the first extraction step, a large part of the organic matrix was removed with methanol at 100 ∘C and 100 bar, followed by a second step with tetrahydrofuran at 185 ∘C and 100 bar to extract the polymers that were subsequently adsorbed to silica gel and measured with Py–GC–MS. With the developed method, limits of quantification in an environmentally relevant concentration range of 7–8 μg g−1 for the most common thermoplastic polymers polyethylene (PE), polypropylene (PP), and polystyrene (PS) were achieved. In order to improve the robustness of the method, poly(styrene-d5) (PSd5) was initially applied as internal standard. However, further analyses revealed a deuterium–hydrogen exchange during Py–GC–MS measurement, which was catalyzed by the inorganic ma- trix. This effect was thereupon systematically investigated and poly(4-fluorostyrene) was established as a new, stable internal standard. While the developed method enabled the quantification of PE, PP, and PS, several other polymers had to be excluded. In particular, the quantification of poly(ethylene tereph- thalate) (PET) proved challenging via Py–GC–MS. A variety of catalytic effects by the inorganic matrix was revealed and systematically investigated, e.g., changes in pyrolysis product distribution. Several different sample preparation approaches failed to resolve these issues. PLE led to a depolymerization of PET which was also catalyzed by the inorganic sample matrix. After further optimization and reduction of false positives, the developed method has the potential to be included in future standardized procedures for MP quantification. It provides a fast, robust analysis of MP in complex samples, while also considering widely overlooked matrix effects. Potential quantification approaches for other polymers that are not included in the developed method (e.g., tire wear particles, paint particles) are also discussed in this thesis.

In sowohl den Kulturwissenschaften als auch den Kognitionswissenschaften haben sich neuere Theorien etabliert, welche verstärkt die Verkörperung und Materialität unseres Denkens, Fühlens und Handelns betonen. Diese Dissertation untersucht aus der Perspektive der philosophischen Anthropologie, wie die ‚material culture studies‘ sowie die ‚embodied cognition‘-Forschungen zusammengedacht werden können. Im Fokus liegt hier der Phänomenbereich der Musik: Denn nicht nur spielen bei dieser eine Vielzahl von Gegenständen der materiellen Kultur eine zentrale Rolle (Instrumente, Tonträger, etc.), sondern auch der Körper des hörenden oder musizierenden Subjekts. Die philosophische Reflexion erfolgte vor allem aus der Perspektive des Enaktivismus, einer spezifischen Strömung der ‚embodied cognition‘, ergänzt durch Konzepte und Ansätze aus den Traditionen der Phänomenologie und des Pragmatismus. Diese wurden nicht nur herangezogen, um zusammen mit dem enaktivistischen Denken auf der Sachebene die verkörperte Natur der Musik darzustellen, sondern auch um die methodische Problemstellung zu behandeln: Der phänomenologische Gedanke des Doppelaspekts von Leib und Körper (Fuchs) und die pragmatistische Anthropologie der Artikulation (Jung) dienten eben dazu, das Zusammendenken von Kognitions- und Kulturwissenschaften in Bezug auf Musik zu ermöglichen. So ließen sich verschiedene Detailfragen zu den beiden größeren Themenkomplexen der Wahrnehmung von und des Umgangs mit Musik(-kultur) beantworten, inklusive solche bezüglich der Rolle des Affektiven und des Sozialen sowie nach der möglichen Ausdehnung von Kognition und Leib. Zusätzlich ergab sich so auch eine exemplarische Demonstration der methodologischen Gedanken, da diese Fragestellungen anhand der genannten Konzepte untersucht wurden und so deren Fruchtbarkeit für das Verbinden von natur- und kulturwissenschaftlichen Forschungen dargelegt werden konnte.