The separation of aqueous and organic mixtures with thermal separation processes is an important and challenging task in the chemical industry. Rising prices for energy, stricter environmental regulations and the increasing demand for high purity chemicals are the main driving forces to find alternative solutions to common separation technologies such as distillation and absorption. These are mostly too energy consumptive and can show limited separation performance, especially when applied to close boiling or azeotropic mixtures. Pervaporation can overcome these thermodynamic limitations and requires less energy because only the separated components need to be evaporated. This separation technology is already well established for the production of anhydrous solvents, but not yet widely distributed in the chemical and petrochemical industry due to some crucial challenges, which are still to overcome. Besides the need of high selective membranes, the development of membrane modules adapted to the specific requirements of organoselective pervaporation needs more research effort. Furthermore, only few modelling and simulation tools are available, which hinders the distribution of this process in industrial scale. In this work, these issues are addressed in a combined approach. In close collaboration with our cooperation partners, a novel membrane module for organophilic pervaporation is developed. A novel technology to manufacture high selective polymeric pervaporation membranes is applied to produce a membrane for an industrially relevant organic-organic separation task. A three step modelling approach ranging from a shortcut and a discrete to a rigorous model is developed and implemented in a user interface. A hydrophilic and an organophilic membrane are characterised for the separation of a 2-butanol/water mixture in a wide range of feed temperature and feed concentration in order to establish a generally valid description of the membrane performances. This approach is implemented in the three developed models to simulate the novel membrane module in industrial scale. The simulations are compared to the results of pilot scale experiments conducted with the novel membrane module. Good agreement between simulated and experimental values is reached.

Skin sensitization resulting for allergic contact dermatitis (ACD) is an occupational and environmental health issue. The allergic hazard for workers and consumers is a serious problem for individuals, employers and marketing certain products. Consequently, it is necessary to accurately identify chemicals skin sensitization potential. According to the new EU chemical regulation REACH (Registration, Evaluation, Authorization and Restriction of Chemicals), information of skin sensitization of chemicals manufactured or imported at or above 1 ton/year should be available. Currently, valid approaches assessing skin sensitization rely on animal testing, such as local lymph node assay (LLNA). However, it now ultimately eliminates using animals for this purpose. Based on the fact that a key step in the skin sensitization process is formatting a covalent adduct between allergic sensitizers and proteins and/or peptides in skin, a lot of additional approaches are proposed and developed for replacing or reducing animal used. In this research, three bioassays, 24 h growth inhibition toward Tetrahymena pyriformis, long term (24 h) and short term (30 min) bacterial toxicity (to Vibrio fischeri), and a kinetic glutathione chemoassay are applied for predicting the organic chemicals’ skin sensitization potential. The major results and conclusions obtained are listed as follows: 1. Toxicity enhancement (Te) of 55 chemicals comprising different sensitization potencies were determined and compared with their narcotic toxicity to predict their skin sensitization. Three linear regressions yielded for all allergic sensitizer without nonsensitizers for each bioassay. The linear regressions are improved after classifying sensitizers into five different reaction mechanistic domains. Correspondingly, five different slopes from various reaction mechanisms indicate a decreased sensitivity of toxicity enhancement to skin sensitization potential with order SNAr > SN2 > acylation ≈ Schiff base > aromatic Michael addition. Based on the fact that a key step in the skin sensitization process is forming a covalent adduct between allergic sensitizers and proteins and/or peptides, Te > 10 as a threshold is applied to discriminate these allergic sensitizers, with 100% accuracy for strong (with extreme) and weaker sensitizers, up to 72% accuracy for moderate sensitizers and less than 69% accuracy for nonsensitizers. Compared with these bioassays, a decreasing order of sensitivities is 24 h growth inhibition (Tetrahymena pyriformis) > 24 h growth inhibition (Vibrio fischeri) > 30 min bioluminescence inhibition (Vibrio fischeri). These three bioassays are useful tools for screening sensitization potency of allergic chemicals, and the toxicity enhancement (Te) can be used to discriminate sensitizers from weak or nonsensitizers. However, in this context we should separate aromatic from aliphatic Mas (Michael acceptors). Moreover, metabolic biotransformation should be considered during predicting nonsensitizers’ skin sensitization. 2. Chemical reactivity of selected 55 compounds measuring through kinetic glutathione chemoassay applies to predict their skin sensitization. This chemoassay confirms the fact that the key step of sensitizers eliciting skin sensitization is formatting a covalent adduct between sensitizers and skin proteins or peptides. The chemical reactivity of tested sensitizers strongly relates with their sensitization potential, with strong (extreme) sensitizers presenting the highest reactivity as followed with moderate sensitizers, weak sensitizers as well as nonsensitizers. Moreover, an integrated platform of this chemoassay data and three bioassays data is performed, and this performance shows good sensitivity for monitoring skin sensitization potency, with more rational accuracy for each sensitizing classifications. 3. Thiol reactivity (kGSH) as well as toxicity enhancement (Te) of additional 21 aliphatic α,β-unsaturated compounds are determined for predicting their skin sensitization potential. The linear regressions of skin sensitization versus thiol reactivity and skin sensitization versus toxicity enhancement are significantly improved after classifying these 21 compounds to four chemical subgroups (acrylates, other esters, ketones and aldehydes). Thiol reactivity of these subgroups presented different sensitivity to skin sensitization, with a decreasing order as acrylates (－2.05) > other esters (－1.26) > ketones (－0.43) > aldehydes (－0.21). Moreover, thiol reactivity is confirmed to be a more sensitive tool for predicting skin sensitization, compared with toxicity enhancement. Although the datasets are probably too small to give a definite decision, hydrophobicity reveals contribution to skin sensitization for aliphatic MAs, which is different with literature report. This study suggests that aliphatic MAs should be treated separately into different chemical subgroups for analysis, and their skin sensitization potency can be predicted using kinetic glutathione chemoassay as well as toxicity enhancement bioassay.

This thesis explores the application of passive sampling as a novel monitoring technique capable of quantifying aquatic pollutants at low environmental concentrations, and in a form that is directly applicable to risk assessment. Two passive samplers, namely polyethersulfone (PES) and silicone rubber (SR), were used to monitor some endocrine disruptors (EDCs) and hydrophobic organic chemicals (HOCs) in freshwater and sediments of a tropical river in Kenya. PES was applied for the first time for time-integrative sampling of these compound classes and was able to quantify the target compounds at low concentrations that were not significantly different to those obtained using the well-established SR, despite differences in uptake mechanisms with both sampler materials. This study demonstrated that passive samplers are versatile tools that can be applied in remote locations, and with proper storage, they can be transported and analyzed far afield.

Ein nicht-invasiver Atemtest zur Lungenkrebsdetektion setzt Kenntnis über lungenkrebsspezifische Substanzen voraus. Die Identifizierung von Lungenkrebsbiomarkern in der Atemluft war das Ziel dieser Arbeit. Leichtflüchtige organische Substanzen (VOC) wurden als Zielkomponenten ausgewählt. Für die VOC-Analytik wurde eine SPME-GC-MS-Methode entwickelt und sowohl auf Modellsysteme als auch auf Realproben angewendet. Drei Lungenadenokarzinomzelllinien wurden in-vitro untersucht. Die VOC-Analyse wurde mit drei verschiedenen Probenahmestrategien durchgeführt und es war ein deutlicher Hintergrundeinfluss der eingesetzten Einwegzellkulturflaschen auf das analysierte VOC-Profil feststellbar. Trotzdem konnten signifikante Unterschiede zwischen Tumorzellen und zellfreien Nährmedien beobachtet werden: 1-Propanol wurde von den Zellen produziert, während der Gehalt einiger Aldehyde sank. Die eingeschränkte Ähnlichkeit des gewählten Zellkulturmodells mit realen Atemluftproben bedingt eine geringe Eignung dieser Ergebnisse für die Biomarkerableitung. Ein Gasmodell auf Basis angefeuchteter, synthetischer Luft wurde als Grundlage für die qualitätsgesicherte, quantitative VOC-Analyse der realen Atemluftproben konzipiert. Diese Modellluft wurde mit 24 Zielsubstanzen (Alkane, Aromaten, sauerstoffhaltige Spezies) sowie 3 Matrix-VOC mit starker Dominanz in den Atemluftproben (Isopren, Aceton, 2-Propanol) angereichert. In Kooperation mit zwei Berliner Kliniken wurden 37 Atemluftproben von Lungenkrebspatienten und 23 Proben von Gesunden gesammelt. Die Anwendung von 1-Butanol als univariater Marker erlaubt eine Erkennung von Lungenkrebs mit einer Sensitivität von 92% und Spezifität von 78%. Durch lineare Diskriminanzanalyse konnte ein Set aus 4 VOC (1-Butanol, 2-Butanon, 2-Pentanon, n-Hexanal) ermittelt werden, welches ebenfalls eine Sensitivität von 92% und mit 87% eine höhere Spezifität aufwies. Gegebenenfalls handelt es sich bei diesen Substanzen jedoch nur um allgemeine Krankheitsmarker. / A non-invasive breath test for lung cancer detection would be favorable but knowledge on lung cancer specific substances is required. This work aims at the identification of potential lung cancer biomarkers in breath. Volatile organic compounds (VOC) were chosen as targets and a SPME-GC-MS method was developed to analyze the VOC profiles of model systems and real samples. Three lung adenocarcinoma cell lines were investigated in-vitro. The VOC analysis, carried out with 3 different sampling strategies, was influenced by the VOC background of the used disposable culture vessels. Changes in the VOC profiles of cell lines compared to cell-free culture media were obvious: 1-propanol was released by the tumor cells whereas the content of some aldehydes was diminished. The similarity of this model system with real breath samples of lung cancer patients was seen to be insignificant. Consequently, these cell cultures were not suitable for biomarker identification. A gaseous model consisting of humidified synthetic air was developed. It was fortified with 24 target VOC (alkanes, aromatics and oxygenated species) as well as 3 matrix compounds (isoprene, acetone and 2-propanol) dominating patients’ VOC profiles in breath. This model was used for the quality assured quantitative VOC analysis in real breath samples. In cooperation with two hospitals 37 single mixed expiratory breath samples from lung cancer patients and 23 from healthy controls were collected. Applying 1-butanol as an univariate biomarker patients and controls were discriminated with a sensitivity of 92% and a specificity of 78%. Linear discriminant analysis displayed a set of 4 VOC (1-butanol, 2-butanone, 2-pentanone, n-hexanal) with similar sensitivity but higher specificity of 87%. However, these potential biomarkers might rather be a consequence of illness in general.

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