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The potential increase in frequency and magnitude of extreme floods is currently discussed in terms of global warming and the intensification of the hydrological cycle. The profound knowledge of past natural variability of floods is of utmost importance in order to assess flood risk for the future. Since instrumental flood series cover only the last ~150 years, other approaches to reconstruct historical and pre-historical flood events are needed. Annually laminated (varved) lake sediments are meaningful natural geoarchives because they provide continuous records of environmental changes > 10000 years down to a seasonal resolution. Since lake basins additionally act as natural sediment traps, the riverine sediment supply, which is preserved as detrital event layers in the lake sediments, can be used as a proxy for extreme discharge events. Within my thesis I examined a ~ 8.50 m long sedimentary record from the pre-Alpine Lake Mondsee (Northeast European Alps), which covered the last 7000 years. This sediment record consists of calcite varves and intercalated detrital layers, which range in thickness from 0.05 to 32 mm. Detrital layer deposition was analysed by a combined method of microfacies analysis via thin sections, Scanning Electron Microscopy (SEM), μX-ray fluorescence (μXRF) scanning and magnetic susceptibility. This approach allows characterizing individual detrital event layers and assigning a corresponding input mechanism and catchment. Based on varve counting and controlled by 14C age dates, the main goals of this thesis are (i) to identify seasonal runoff processes, which lead to significant sediment supply from the catchment into the lake basin and (ii) to investigate flood frequency under changing climate boundary conditions. This thesis follows a line of different time slices, presenting an integrative approach linking instrumental and historical flood data from Lake Mondsee in order to evaluate the flood record inferred from Lake Mondsee sediments. The investigation of eleven short cores covering the last 100 years reveals the abundance of 12 detrital layers. Therein, two types of detrital layers are distinguished by grain size, geochemical composition and distribution pattern within the lake basin. Detrital layers, which are enriched in siliciclastic and dolomitic material, reveal sediment supply from the Flysch sediments and Northern Calcareous Alps into the lake basin. These layers are thicker in the northern lake basin (0.1-3.9 mm) and thinner in the southern lake basin (0.05-1.6 mm). Detrital layers, which are enriched in dolomitic components forming graded detrital layers (turbidites), indicate the provenance from the Northern Calcareous Alps. These layers are generally thicker (0.65-32 mm) and are solely recorded within the southern lake basin. In comparison with instrumental data, thicker graded layers result from local debris flow events in summer, whereas thin layers are deposited during regional flood events in spring/summer. Extreme summer floods as reported from flood layer deposition are principally caused by cyclonic activity from the Mediterranean Sea, e.g. July 1954, July 1997 and August 2002. During the last two millennia, Lake Mondsee sediments reveal two significant flood intervals with decadal-scale flood episodes, during the Dark Ages Cold Period (DACP) and the transition from the Medieval Climate Anomaly (MCA) into the Little Ice Age (LIA) suggesting a linkage of transition to climate cooling and summer flood recurrences in the Northeastern Alps. In contrast, intermediate or decreased flood episodes appeared during the MWP and the LIA. This indicates a non-straightforward relationship between temperature and flood recurrence, suggesting higher cyclonic activity during climate transition in the Northeast Alps. The 7000-year flood chronology reveals 47 debris flows and 269 floods, with increased flood activity shifting around 3500 and 1500 varve yr BP (varve yr BP = varve years before present, before present = AD 1950). This significant increase in flood activity shows a coincidence with millennial-scale climate cooling that is reported from main Alpine glacier advances and lower tree lines in the European Alps since about 3300 cal. yr BP (calibrated years before present). Despite relatively low flood occurrence prior to 1500 varve yr BP, floods at Lake Mondsee could have also influenced human life in early Neolithic lake dwellings (5750-4750 cal. yr BP). While the first lake dwellings were constructed on wetlands, the later lake dwellings were built on piles in the water suggesting an early flood risk adaptation of humans and/or a general change of the Late Neolithic Culture of lake-dwellers because of socio-economic reasons. However, a direct relationship between the final abandonment of the lake dwellings and higher flood frequencies is not evidenced.
What are the consequences of unemployment and precarious employment for individuals' health in Europe? What are the moderating factors that may offset (or increase) the health consequences of labor-market risks? How do the effects of these risks vary across different contexts, which differ in their institutional and cultural settings? Does gender, regarded as a social structure, play a role, and how? To answer these questions is the aim of my cumulative thesis. This study aims to advance our knowledge about the health consequences that unemployment and precariousness cause over the life course. In particular, I investigate how several moderating factors, such as gender, the family, and the broader cultural and institutional context, may offset or increase the impact of employment instability and insecurity on individual health.
In my first paper, 'The buffering role of the family in the relationship between job loss and self-perceived health: Longitudinal results from Europe, 2004-2011', I and my co-authors measure the causal effect of job loss on health and the role of the family and welfare states (regimes) as moderating factors. Using EU-SILC longitudinal data (2004-2011), we estimate the probability of experiencing 'bad health' following a transition to unemployment by applying linear probability models and undertake separate analyses for men and women. Firstly, we measure whether changes in the independent variable 'job loss' lead to changes in the dependent variable 'self-rated health' for men and women separately. Then, by adding into the model different interaction terms, we measure the moderating effect of the family, both in terms of emotional and economic support, and how much it varies across different welfare regimes. As an identification strategy, we first implement static fixed-effect panel models, which control for time-varying observables and indirect health selection—i.e., constant unobserved heterogeneity. Secondly, to control for reverse causality and path dependency, we implement dynamic fixed-effect panel models, adding a lagged dependent variable to the model.
We explore the role of the family by focusing on close ties within households: we consider the presence of a stable partner and his/her working status as a source of social and economic support. According to previous literature, having a partner should reduce the stress from adverse events, thanks to the symbolic and emotional dimensions that such a relationship entails, regardless of any economic benefits. Our results, however, suggest that benefits linked to the presence of a (female) partner also come from the financial stability that (s)he can provide in terms of a second income. Furthermore, we find partners' employment to be at least as important as the mere presence of the partner in reducing the negative effect of job loss on the individual's health by maintaining the household's standard of living and decreasing economic strain on the family. Our results are in line with previous research, which has highlighted that some people cope better than others with adverse life circumstances, and the support provided by the family is a crucial resource in that regard.
We also reported an important interaction between the family and the welfare state in moderating the health consequences of unemployment, showing how the compensation effect of the family varies across welfare regimes. The family plays a decisive role in cushioning the adverse consequences of labor market risks in Southern and Eastern welfare states, characterized by less developed social protection systems and –especially the Southern – high level of familialism.
The first paper also found important gender differences concerning job loss, family and welfare effects. Of particular interest is the evidence suggesting that health selection works differently for men and women, playing a more prominent role for women than for men in explaining the relationship between job loss and self-perceived health. The second paper, 'Gender roles and selection mechanisms across contexts: A comparative analysis of the relationship between unemployment, self-perceived health, and gender.' investigates more in-depth the gender differential in health driven by unemployment.
Being a highly contested issue in literature, we aim to study whether men are more penalized than women or the other way around and the mechanisms that may explain the gender difference. To do that, we rely on two theoretical arguments: the availability of alternative roles and social selection. The first argument builds on the idea that men and women may compensate for the detrimental health consequences of unemployment through the commitment to 'alternative roles,' which can provide for the resources needed to fulfill people's socially constructed needs. Notably, the availability of alternative options depends on the different positions that men and women have in society.
Further, we merge the availability of the 'alternative roles' argument with the health selection argument. We assume that health selection could be contingent on people's social position as defined by gender and, thus, explain the gender differential in the relationship between unemployment and health. Ill people might be less reluctant to fall or remain (i.e., self-select) in unemployment if they have alternative roles. In Western societies, women generally have more alternative roles than men and thus more discretion in their labor market attachment. Therefore, health selection should be stronger for them, explaining why unemployment is less menace for women than for their male counterparts.
Finally, relying on the idea of different gender regimes, we extended these arguments to comparison across contexts. For example, in contexts where being a caregiver is assumed to be women's traditional and primary roles and the primary breadwinner role is reserved to men, unemployment is less stigmatized, and taking up alternative roles is more socially accepted for women than for men (Hp.1). Accordingly, social (self)selection should be stronger for women than for men in traditional contexts, where, in the case of ill-health, the separation from work is eased by the availability of alternative roles (Hp.2).
By focusing on contexts that are representative of different gender regimes, we implement a multiple-step comparative approach. Firstly, by using EU-SILC longitudinal data (2004-2015), our analysis tests gender roles and selection mechanisms for Sweden and Italy, representing radically different gender regimes, thus providing institutional and cultural variation. Then, we limit institutional heterogeneity by focusing on Germany and comparing East- and West-Germany and older and younger cohorts—for West-Germany (SOEP data 1995-2017). Next, to assess the differential impact of unemployment for men and women, we compared (unemployed and employed) men with (unemployed and employed) women. To do so, we calculate predicted probabilities and average marginal effect from two distinct random-effects probit models. Our first step is estimating random-effects models that assess the association between unemployment and self-perceived health, controlling for observable characteristics. In the second step, our fully adjusted model controls for both direct and indirect selection. We do this using dynamic correlated random-effects (CRE) models. Further, based on the fully adjusted model, we test our hypotheses on alternative roles (Hp.1) by comparing several contexts – models are estimated separately for each context. For this hypothesis, we pool men and women and include an interaction term between unemployment and gender, which has the advantage to allow for directly testing whether gender differences in the effect of unemployment exist and are statistically significant. Finally, we test the role of selection mechanisms (Hp.2), using the KHB method to compare coefficients across nested nonlinear models. Specifically, we test the role of selection for the relationship between unemployment and health by comparing the partially-adjusted and fully-adjusted models. To allow selection mechanisms to operate differently between genders, we estimate separate models for men and women.
We found support to our first hypotheses—the context where people are embedded structures the relationship between unemployment, health, and gender. We found no gendered effect of unemployment on health in the egalitarian context of Sweden. Conversely, in the traditional context of Italy, we observed substantive and statistically significant gender differences in the effect of unemployment on bad health, with women suffering less than men. We found the same pattern for comparing East and West Germany and younger and older cohorts in West Germany.
On the contrary, our results did not support our theoretical argument on social selection. We found that in Sweden, women are more selected out of employment than men. In contrast, in Italy, health selection does not seem to be the primary mechanism behind the gender differential—Italian men and women seem to be selected out of employment to the same extent. Namely, we do not find any evidence that health selection is stronger for women in more traditional countries (Hp2), despite the fact that the institutional and the cultural context would offer them a more comprehensive range of 'alternative roles' relative to men. Moreover, our second hypothesis is also rejected in the second and third comparisons, where the cross-country heterogeneity is reduced to maximize cultural differences within the same institutional context. Further research that addresses selection into inactivity is needed to evaluate the interplay between selection and social roles across gender regimes.
While the health consequences of unemployment have been on the research agenda for a pretty long time, the interest in precarious employment—defined as the linking of the vulnerable worker to work that is characterized by uncertainty and insecurity concerning pay, the stability of the work arrangement, limited access to social benefits, and statutory protections—has emerged only later. Since the 80s, scholars from different disciplines have raised concerns about the social consequences of de-standardization of employment relationships. However, while work has become undoubtedly more precarious, very little is known about its causal effect on individual health and the role of gender as a moderator. These questions are at the core of my third paper : 'Bad job, bad health? A longitudinal analysis of the interaction between precariousness, gender and self-perceived health in Germany'. Herein, I investigate the multidimensional nature of precarious employment and its causal effect on health, particularly focusing on gender differences.
With this paper, I aim at overcoming three major shortcomings of earlier studies: The first one regards the cross-sectional nature of data that prevents the authors from ruling out unobserved heterogeneity as a mechanism for the association between precarious employment and health. Indeed, several unmeasured individual characteristics—such as cognitive abilities—may confound the relationship between precarious work and health, leading to biased results. Secondly, only a few studies have directly addressed the role of gender in shaping the relationship. Moreover, available results on the gender differential are mixed and inconsistent: some found precarious employment being more detrimental for women's health, while others found no gender differences or stronger negative association for men. Finally, previous attempts to an empirical translation of the employment precariousness (EP) concept have not always been coherent with their theoretical framework. EP is usually assumed to be a multidimensional and continuous phenomenon; it is characterized by different dimensions of insecurity that may overlap in the same job and lead to different "degrees of precariousness." However, researchers have predominantly focused on one-dimensional indicators—e.g., temporary employment, subjective job insecurity—to measure EP and study the association with health. Besides the fact that this approach partially grasps the phenomenon's complexity, the major problem is the inconsistency of evidence that it has produced. Indeed, this line of inquiry generally reveals an ambiguous picture, with some studies finding substantial adverse effects of temporary over permanent employment, while others report only minor differences.
To measure the (causal) effect of precarious work on self-rated health and its variation by gender, I focus on Germany and use four waves from SOEP data (2003, 2007, 2011, and 2015). Germany is a suitable context for my study. Indeed, since the 1980s, the labor market and welfare system have been restructured in many ways to increase the German economy's competitiveness in the global market. As a result, the (standard) employment relationship has been de-standardized: non-standard and atypical employment arrangements—i.e., part-time work, fixed-term contracts, mini-jobs, and work agencies—have increased over time while wages have lowered, even among workers with standard work. In addition, the power of unions has also fallen over the last three decades, leaving a large share of workers without collective protection. Because of this process of de-standardization, the link between wage employment and strong social rights has eroded, making workers more powerless and more vulnerable to labor market risks than in the past. EP refers to this uneven distribution of power in the employment relationship, which can be detrimental to workers' health. Indeed, by affecting individuals' access to power and other resources, EP puts precarious workers at risk of experiencing health shocks and influences their ability to gain and accumulate health advantages (Hp.1).
Further, the focus on Germany allows me to investigate my second research question on the gender differential. Germany is usually regarded as a traditionalist gender regime: a context characterized by a configuration of roles. Here, being a caregiver is assumed to be women's primary role, whereas the primary breadwinner role is reserved for men. Although many signs of progress have been made over the last decades towards a greater equalization of opportunities and more egalitarianism, the breadwinner model has barely changed towards a modified version. Thus, women usually take on the double role of workers (the so-called secondary earner) and caregivers, and men still devote most of their time to paid work activities. Moreover, the overall upward trend towards more egalitarian gender ideologies has leveled off over the last decades, moving notably towards more traditional gender ideologies.
In this setting, two alternative hypotheses are possible. Firstly, I assume that the negative relationship between EP and health is stronger for women than for men. This is because women are systematically more disadvantaged than men in the public and private spheres of life, having less access to formal and informal sources of power. These gender-related power asymmetries may interact with EP-related power asymmetries resulting in a stronger effect of EP on women's health than on men's health (Hp.2).
An alternative way of looking at the gender differential is to consider the interaction that precariousness might have with men's and women's gender identities. According to this view, the negative relationship between EP and health is weaker for women than for men (Hp.2a). In a society with a gendered division of labor and a strong link between masculine identities and stable and well-rewarded job—i.e., a job that confers the role of primary family provider—a male worker with precarious employment might violate the traditional male gender role. Men in precarious jobs may perceive themselves (and by others) as possessing a socially undesirable characteristic, which conflicts with the stereotypical idea of themselves as the male breadwinner. Engaging in behaviors that contradict stereotypical gender identity may decrease self-esteem and foster feelings of inferiority, helplessness, and jealousy, leading to poor health.
I develop a new indicator of EP that empirically translates a definition of EP as a multidimensional and continuous phenomenon. I assume that EP is a latent construct composed of seven dimensions of insecurity chosen according to the theory and previous empirical research: Income insecurity, social insecurity, legal insecurity, employment insecurity, working-time insecurity, representation insecurity, worker's vulnerability. The seven dimensions are proxied by eight indicators available in the four waves of the SOEP dataset. The EP composite indicator is obtained by performing a multiple correspondence analysis (MCA) on the eight indicators. This approach aims to construct a summary scale in which all dimensions contribute jointly to the measured experience of precariousness and its health impact.
Further, the relationship between EP and 'general self-perceived health' is estimated by applying ordered probit random-effects estimators and calculating average marginal effect (further AME). Then, to control for unobserved heterogeneity, I implement correlated random-effects models that add to the model the within-individual means of the time-varying independent variables. To test the significance of the gender differential, I add an interaction term between EP and gender in the fully adjusted model in the pooled sample.
My correlated random-effects models showed EP's negative and substantial 'effect' on self-perceived health for both men and women. Although nonsignificant, the evidence seems in line with previous cross-sectional literature. It supports the hypothesis that employment precariousness could be detrimental to workers' health. Further, my results showed the crucial role of unobserved heterogeneity in shaping the health consequences of precarious employment. This is particularly important as evidence accumulates, yet it is still mostly descriptive.
Moreover, my results revealed a substantial difference among men and women in the relationship between EP and health: when EP increases, the risk of experiencing poor health increases much more for men than for women. This evidence falsifies previous theory according to whom the gender differential is contingent on the structurally disadvantaged position of women in western societies. In contrast, they seem to confirm the idea that men in precarious work could experience role conflict to a larger extent than women, as their self-standard is supposed to be the stereotypical breadwinner worker with a good and well-rewarded job. Finally, results from the multiple correspondence analysis contribute to the methodological debate on precariousness, showing that a multidimensional and continuous indicator can express a latent variable of EP.
All in all, complementarities are revealed in the results of unemployment and employment precariousness, which have two implications: Policy-makers need to be aware that the total costs of unemployment and precariousness go far beyond the economic and material realm penetrating other fundamental life domains such as individual health. Moreover, they need to balance the trade-off between protecting adequately unemployed people and fostering high-quality employment in reaction to the highlighted market pressures. In this sense, the further development of a (universalistic) welfare state certainly helps mitigate the adverse health effects of unemployment and, therefore, the future costs of both individuals' health and welfare spending. In addition, the presence of a working partner is crucial for reducing the health consequences of employment instability. Therefore, policies aiming to increase female labor market participation should be promoted, especially in those contexts where the welfare state is less developed.
Moreover, my results support the significance of taking account of a gender perspective in health research. The findings of the three articles show that job loss, unemployment, and precarious employment, in general, have adverse effects on men's health but less or absent consequences for women's health. Indeed, this suggests the importance of labor and health policies that consider and further distinguish the specific needs of the male and female labor force in Europe. Nevertheless, a further implication emerges: the health consequences of employment instability and de-standardization need to be investigated in light of the gender arrangements and the transforming gender relationships in specific cultural and institutional contexts. My results indeed seem to suggest that women's health advantage may be a transitory phenomenon, contingent on the predominant gendered institutional and cultural context. As the structural difference between men's and women's position in society is eroded, egalitarianism becomes the dominant normative status, so will probably be the gender difference in the health consequences of job loss and precariousness. Therefore, while gender equality in opportunities and roles is a desirable aspect for contemporary societies and a political goal that cannot be postponed further, this thesis raises a further and maybe more crucial question: What kind of equality should be pursued to provide men and women with both good life quality and equal chances in the public and private spheres? In this sense, I believe that social and labor policies aiming to reduce gender inequality in society should focus on improving women's integration into the labor market, implementing policies targeting men, and facilitating their involvement in the private sphere of life. Equal redistribution of social roles could activate a crucial transformation of gender roles and the cultural models that sustain and still legitimate gender inequality in Western societies.
In the present thesis, AC electrokinetic forces, like dielectrophoresis and AC electroosmosis, were demonstrated as a simple and fast method to functionalize the surface of nanoelectrodes with submicrometer sized biological objects. These nanoelectrodes have a cylindrical shape with a diameter of 500 nm arranged in an array of 6256 electrodes. Due to its medical relevance influenza virus as well as anti-influenza antibodies were chosen as a model organism. Common methods to bring antibodies or proteins to biosensor surfaces are complex and time-consuming. In the present work, it was demonstrated that by applying AC electric fields influenza viruses and antibodies can be immobilized onto the nanoelectrodes within seconds without any prior chemical modification of neither the surface nor the immobilized biological object. The distribution of these immobilized objects is not uniform over the entire array, it exhibits a decreasing gradient from the outer row to the inner ones. Different causes for this gradient have been discussed, such as the vortex-shaped fluid motion above the nanoelectrodes generated by, among others, electrothermal fluid flow. It was demonstrated that parts of the accumulated material are permanently immobilized to the electrodes. This is a unique characteristic of the presented system since in the literature the AC electrokinetic immobilization is almost entirely presented as a method just for temporary immobilization. The spatial distribution of the immobilized viral material or the anti-influenza antibodies at the electrodes was observed by either the combination of fluorescence microscopy and deconvolution or by super-resolution microscopy (STED). On-chip immunoassays were performed to examine the suitability of the functionalized electrodes as a potential affinity-based biosensor. Two approaches were pursued: A) the influenza virus as the bio-receptor or B) the influenza virus as the analyte. Different sources of error were eliminated by ELISA and passivation experiments. Hence, the activity of the immobilized object was inspected by incubation with the analyte. This resulted in the successful detection of anti-influenza antibodies by the immobilized viral material. On the other hand, a detection of influenza virus particles by the immobilized anti-influenza antibodies was not possible. The latter might be due to lost activity or wrong orientation of the antibodies. Thus, further examinations on the activity of by AC electric fields immobilized antibodies should follow. When combined with microfluidics and an electrical read-out system, the functionalized chips possess the potential to serve as a rapid, portable, and cost-effective point-of-care (POC) device. This device can be utilized as a basis for diverse applications in diagnosing and treating influenza, as well as various other pathogens.
This Thesis puts its focus on the physics of neutron stars and its description with methods of numerical relativity. In the first step, a new numerical framework the Whisky2D code will be developed, which solves the relativistic equations of hydrodynamics in axisymmetry. Therefore we consider an improved formulation of the conserved form of these equations. The second part will use the new code to investigate the critical behaviour of two colliding neutron stars. Considering the analogy to phase transitions in statistical physics, we will investigate the evolution of the entropy of the neutron stars during the whole process. A better understanding of the evolution of thermodynamical quantities, like the entropy in critical process, should provide deeper understanding of thermodynamics in relativity. More specifically, we have written the Whisky2D code, which solves the general-relativistic hydrodynamics equations in a flux-conservative form and in cylindrical coordinates. This of course brings in 1/r singular terms, where r is the radial cylindrical coordinate, which must be dealt with appropriately. In the above-referenced works, the flux operator is expanded and the 1/r terms, not containing derivatives, are moved to the right-hand-side of the equation (the source term), so that the left hand side assumes a form identical to the one of the three-dimensional (3D) Cartesian formulation. We call this the standard formulation. Another possibility is not to split the flux operator and to redefine the conserved variables, via a multiplication by r. We call this the new formulation. The new equations are solved with the same methods as in the Cartesian case. From a mathematical point of view, one would not expect differences between the two ways of writing the differential operator, but, of course, a difference is present at the numerical level. Our tests show that the new formulation yields results with a global truncation error which is one or more orders of magnitude smaller than those of alternative and commonly used formulations. The second part of the Thesis uses the new code for investigations of critical phenomena in general relativity. In particular, we consider the head-on-collision of two neutron stars in a region of the parameter space where two final states a new stable neutron star or a black hole, lay close to each other. In 1993, Choptuik considered one-parameter families of solutions, S[P], of the Einstein-Klein-Gordon equations for a massless scalar field in spherical symmetry, such that for every P > P⋆, S[P] contains a black hole and for every P < P⋆, S[P] is a solution not containing singularities. He studied numerically the behavior of S[P] as P → P⋆ and found that the critical solution, S[P⋆], is universal, in the sense that it is approached by all nearly-critical solutions regardless of the particular family of initial data considered. All these phenomena have the common property that, as P approaches P⋆, S[P] approaches a universal solution S[P⋆] and that all the physical quantities of S[P] depend only on |P − P⋆|. The first study of critical phenomena concerning the head-on collision of NSs was carried out by Jin and Suen in 2007. In particular, they considered a series of families of equal-mass NSs, modeled with an ideal-gas EOS, boosted towards each other and varied the mass of the stars, their separation, velocity and the polytropic index in the EOS. In this way they could observe a critical phenomenon of type I near the threshold of black-hole formation, with the putative solution being a nonlinearly oscillating star. In a successive work, they performed similar simulations but considering the head-on collision of Gaussian distributions of matter. Also in this case they found the appearance of type-I critical behaviour, but also performed a perturbative analysis of the initial distributions of matter and of the merged object. Because of the considerable difference found in the eigenfrequencies in the two cases, they concluded that the critical solution does not represent a system near equilibrium and in particular not a perturbed Tolmann-Oppenheimer-Volkoff (TOV) solution. In this Thesis we study the dynamics of the head-on collision of two equal-mass NSs using a setup which is as similar as possible to the one considered above. While we confirm that the merged object exhibits a type-I critical behaviour, we also argue against the conclusion that the critical solution cannot be described in terms of equilibrium solution. Indeed, we show that, in analogy with what is found in, the critical solution is effectively a perturbed unstable solution of the TOV equations. Our analysis also considers fine-structure of the scaling relation of type-I critical phenomena and we show that it exhibits oscillations in a similar way to the one studied in the context of scalar-field critical collapse.
Advancing charge selective contacts for efficient monolithic perovskite-silicon tandem solar cells
(2019)
Hybrid organic-inorganic perovskites are one of the most promising material classes for photovoltaic energy conversion. In solar cells, the perovskite absorber is sandwiched between n- and p-type contact layers which selectively transport electrons and holes to the cell’s cathode and anode, respectively. This thesis aims to advance contact layers in perovskite solar cells and unravel the impact of interface and contact properties on the device performance. Further, the contact materials are applied in monolithic perovskite-silicon heterojunction (SHJ) tandem solar cells, which can overcome the single junction efficiency limits and attract increasing attention. Therefore, all contact layers must be highly transparent to foster light harvesting in the tandem solar cell design. Besides, the SHJ device restricts processing temperatures for the selective contacts to below 200°C.
A comparative study of various electron selective contact materials, all processed below 180°C, in n-i-p type perovskite solar cells highlights that selective contacts and their interfaces to the absorber govern the overall device performance. Combining fullerenes and metal-oxides in a TiO2/PC60BM (phenyl-C60-butyric acid methyl ester) double-layer contact allows to merge good charge extraction with minimized interface recombination. The layer sequence thereby achieved high stabilized solar cell performances up to 18.0% and negligible current-voltage hysteresis, an otherwise pronounced phenomenon in this device design. Double-layer structures are therefore emphasized as a general concept to establish efficient and highly selective contacts.
Based on this success, the concept to combine desired properties of different materials is transferred to the p-type contact. Here, a mixture of the small molecule Spiro-OMeTAD [2,2’,7,7’-tetrakis(N,N-di-p-methoxyphenylamine)-9,9’-spirobifluoren] and the doped polymer PEDOT [poly(3,4-ethylenedioxythiophene)] is presented as a novel hole selective contact. PEDOT thereby remarkably suppresses charge recombination at the perovskite surface, allowing an increase of quasi-Fermi level splitting in the absorber. Further, the addition of Spiro-OMeTAD into the PEDOT layer is shown to enhance charge extraction at the interface and allow high efficiencies up to 16.8%.
Finally, the knowledge on contact properties is applied to monolithic perovskite-SHJ tandem solar cells. The main goal is to optimize the top contact stack of doped Spiro-OMeTAD/molybdenum oxide(MoOx)/ITO towards higher transparency by two different routes. First, fine-tuning of the ITO deposition to mitigate chemical reduction of MoOx and increase the transmittance of MoOx/ITO stacks by 25%. Second, replacing Spiro-OMeTAD with the alternative hole transport materials PEDOT/Spiro-OMeTAD mixtures, CuSCN or PTAA [poly(triaryl amine)]. Experimental results determine layer thickness constrains and validate optical simulations, which subsequently allow to realistically estimate the respective tandem device performances. As a result, PTAA represents the most promising replacement for Spiro-OMeTAD, with a projected increase of the optimum tandem device efficiency for the herein used architecture by 2.9% relative to 26.5% absolute. The results also reveal general guidelines for further performance gains of the technology.
Floods continue to be the leading cause of economic damages and fatalities among natural disasters worldwide. As future climate and exposure changes are projected to intensify these damages, the need for more accurate and scalable flood risk models is rising. Over the past decade, macro-scale flood risk models have evolved from initial proof-of-concepts to indispensable tools for decision-making at global-, nationaland, increasingly, the local-level. This progress has been propelled by the advent of high-performance computing and the availability of global, space-based datasets. However, despite such advancements, these models are rarely validated and consistently fall short of the accuracy achieved by high-resolution local models. While capabilities have improved, significant gaps persist in understanding the behaviours of such macro-scale models, particularly their tendency to overestimate risk. This dissertation aims to address such gaps by examining the scale transfers inherent in the construction and application of coarse macroscale models. To achieve this, four studies are presented that, collectively, address exposure, hazard, and vulnerability components of risk affected by upscaling or downscaling.
The first study focuses on a type of downscaling where coarse flood hazard inundation grids are enhanced to a finer resolution. While such inundation downscaling has been employed in numerous global model chains, ours is the first study to focus specifically on this component, providing an evaluation of the state of the art and a novel algorithm. Findings demonstrate that our novel algorithm is eight times faster than existing methods, offers a slight improvement in accuracy, and generates more physically coherent flood maps in hydraulically challenging regions. When applied to a case study, the algorithm generated a 4m resolution inundation map from 30m hydrodynamic model outputs in 33 s, a 60-fold improvement in runtime with a 25% increase in RMSE compared with direct hydrodynamic modelling. All evaluated downscaling algorithms yielded better accuracy than the coarse hydrodynamic model when compared to observations, demonstrating similar limits of coarse hydrodynamic models reported by others. The substitution of downscaling into flood risk model chains, in place of high-resolution modelling, can drastically improve the lead time of impactbased forecasts and the efficiency of hazard map production. With downscaling, local regions could obtain high resolution local inundation maps by post-processing a global model without the need for expensive modelling or expertise.
The second study focuses on hazard aggregation and its implications for exposure, investigating implicit aggregations commonly used to intersect hazard grids with coarse exposure models. This research introduces a novel spatial classification framework to understand the effects of rescaling flood hazard grids to a coarser resolution. The study derives closed-form analytical solutions for the location and direction of bias from flood grid aggregation, showing that bias will always be present in regions near the edge of inundation. For example, inundation area will be positively biased when water depth grids are aggregated, while volume will be negatively biased when water elevation grids are aggregated. Extending the analysis to effects of hazard aggregation on building exposure, this study shows that exposure in regions at the edge of inundation are an order of magnitude more sensitive to aggregation errors than hazard alone. Among the two aggregation routines considered, averaging water surface elevation grids better preserved flood depths at buildings than averaging of water depth grids. The study provides the first mathematical proof and generalizeable treatment of flood hazard grid aggregation, demonstrating important mechanisms to help flood risk modellers understand and control model behaviour.
The final two studies focus on the aggregation of vulnerability models or flood damage functions, investigating the practice of applying per-asset functions to aggregate exposure models. Both studies extend Jensen’s inequality, a well-known 1906 mathematical proof, to demonstrate how the aggregation of flood damage functions leads to bias. Applying Jensen’s proof in this new context, results show that typically concave flood damage functions will introduce a positive bias (overestimation) when aggregated. This behaviour was further investigated with a simulation experiment including 2 million buildings in Germany, four global flood hazard simulations and three aggregation scenarios. The results show that positive aggregation bias is not distributed evenly in space, meaning some regions identified as “hot spots of risk” in assessments may in fact just be hot spots of aggregation bias. This study provides the first application of Jensen’s inequality to explain the overestimates reported elsewhere and advice for modellers to minimize such artifacts.
In total, this dissertation investigates the complex ways aggregation and disaggregation influence the behaviour of risk models, focusing on the scale-transfers underpinning macro-scale flood risk assessments. Extending a key finding of the flood hazard literature to the broader context of flood risk, this dissertation concludes that all else equal, coarse models overestimate risk. This dissertation goes beyond previous studies by providing mathematical proofs for how and where such bias emerges in aggregation routines, offering a mechanistic explanation for coarse model overestimates. It shows that this bias is spatially heterogeneous, necessitating a deep understanding of how rescaling may bias models to effectively reduce or communicate uncertainties. Further, the dissertation offers specific recommendations to help modellers minimize scale transfers in problematic regions. In conclusion, I argue that such aggregation errors are epistemic, stemming from choices in model structure, and therefore hold greater potential and impetus for study and mitigation. This deeper understanding of uncertainties is essential for improving macro-scale flood risk models and their effectiveness in equitable, holistic, and sustainable flood management.
The present thesis introduces an iterative expert-based Bayesian approach for assessing greenhouse gas (GHG) emissions from the 2030 German new vehicle fleet and quantifying the impacts of their main drivers. A first set of expert interviews has been carried out in order to identify technologies which may help to lower car GHG emissions and to quantify their emission reduction potentials. Moreover, experts were asked for their probability assessments that the different technologies will be widely adopted, as well as for important prerequisites that could foster or hamper their adoption. Drawing on the results of these expert interviews, a Bayesian Belief Network has been built which explicitly models three vehicle types: Internal Combustion Engine Vehicles (which include mild and full Hybrid Electric Vehicles), Plug-In Hybrid Electric Vehicles, and Battery Electric Vehicles. The conditional dependencies of twelve central variables within the BBN - battery energy, fuel and electricity consumption, relative costs, and sales shares of the vehicle types - have been quantified by experts from German car manufacturers in a second series of interviews. For each of the seven second-round interviews, an expert's individually specified BBN results. The BBN have been run for different hypothetical 2030 scenarios which differ, e.g., in regard to battery development, regulation, and fuel and electricity GHG intensities. The present thesis delivers results both in regard to the subject of the investigation and in regard to its method. On the subject level, it has been found that the different experts expect 2030 German new car fleet emission to be at 50 to 65% of 2008 new fleet emissions under the baseline scenario. They can be further reduced to 40 to 50% of the emissions of the 2008 fleet though a combination of a higher share of renewables in the electricity mix, a larger share of biofuels in the fuel mix, and a stricter regulation of car CO$_2$ emissions in the European Union. Technically, 2030 German new car fleet GHG emissions can be reduced to a minimum of 18 to 44% of 2008 emissions, a development which can not be triggered by any combination of measures modeled in the BBN alone but needs further commitment. Out of a wealth of existing BBN, few have been specified by individual experts through elicitation, and to my knowledge, none of them has been employed for analyzing perspectives for the future. On the level of methods, this work shows that expert-based BBN are a valuable tool for making experts' expectations for the future explicit and amenable to the analysis of different hypothetical scenarios. BBN can also be employed for quantifying the impacts of main drivers. They have been demonstrated to be a valuable tool for iterative stakeholder-based science approaches.
Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail.
A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask.
Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious.
In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.
The light reactions of photosynthesis are carried out by a series of multiprotein complexes embedded in thylakoid membranes. Among them, photosystem I (PSI), acting as plastocyanin-ferderoxin oxidoreductase, catalyzes the final reaction. Together with light-harvesting antenna I, PSI forms a high-molecular-weight supercomplex of ~600 kDa, consisting of eighteen subunits and nearly two hundred co-factors. Assembly of the various components into a functional thylakoid membrane complex requires precise coordination, which is provided by the assembly machinery. Although this includes a small number of proteins (PSI assembly factors) that have been shown to play a role in the formation of PSI, the process as a whole, as well as the intricacy of its members, remains largely unexplored.
In the present work, two approaches were used to find candidate PSI assembly factors. First, EnsembleNet was used to select proteins thought to be functionally related to known PSI assembly factors in Arabidopsis thaliana (approach I), and second, co-immunoprecipitation (Co-IP) of tagged PSI assembly factors in Nicotiana tabacum was performed (approach II).
Here, the novel PSI assembly factors designated CO-EXPRESSED WITH PSI ASSEMBLY 1 (CEPA1) and Ycf4-INTERACTING PROTEIN 1 (Y4IP1) were identified. A. thaliana null mutants for CEPA1 and Y4IP1 showed a growth phenotype and pale leaves compared with the wild type. Biophysical experiments using pulse amplitude modulation (PAM) revealed insufficient electron transport on the PSII acceptor side. Biochemical analyses revealed that both CEPA1 and Y4IP1 are specifically involved in PSI accumulation in A. thaliana at the post-translational level but are not essential. Consistent with their roles as factors in the assembly of a thylakoid membrane protein complex, the two proteins localize to thylakoid membranes. Remarkably, cepa1 y4ip1 double mutants exhibited lethal phenotypes in early developmental stages under photoautotrophic growth. Finally, co-IP and native gel experiments supported a possible role for CEPA1 and Y4IP1 in mediating PSI assembly in conjunction with other PSI assembly factors (e.g., PPD1- and PSA3-CEPA1 and Ycf4-Y4IP1). The fact that CEPA1 and Y4IP1 are found exclusively in green algae and higher plants suggests eukaryote-specific functions. Although the specific mechanisms need further investigation, CEPA1 and Y4IP1 are two novel assembly factors that contribute to PSI formation.
Antarctic glacier forfields are extreme environments and pioneer sites for ecological succession. The Antarctic continent shows microbial community development as a natural laboratory because of its special environment, geographic isolation and little anthropogenic influence. Increasing temperatures due to global warming lead to enhanced deglaciation processes in cold-affected habitats and new terrain is becoming exposed to soil formation and accessible for microbial colonisation. This study aims to understand the structure and development of glacier forefield bacterial communities, especially how soil parameters impact the microorganisms and how those are adapted to the extreme conditions of the habitat. To this effect, a combination of cultivation experiments, molecular, geophysical and geochemical analysis was applied to examine two glacier forfields of the Larsemann Hills, East Antarctica. Culture-independent molecular tools such as terminal restriction length polymorphism (T-RFLP), clone libraries and quantitative real-time PCR (qPCR) were used to determine bacterial diversity and distribution. Cultivation of yet unknown species was carried out to get insights in the physiology and adaptation of the microorganisms. Adaptation strategies of the microorganisms were studied by determining changes of the cell membrane phospholipid fatty acid (PLFA) inventory of an isolated bacterium in response to temperature and pH fluctuations and by measuring enzyme activity at low temperature in environmental soil samples. The two studied glacier forefields are extreme habitats characterised by low temperatures, low water availability and small oligotrophic nutrient pools and represent sites of different bacterial succession in relation to soil parameters. The investigated sites showed microbial succession at an early step of soil formation near the ice tongue in comparison to closely located but rather older and more developed soil from the forefield. At the early step the succession is influenced by a deglaciation-dependent areal shift of soil parameters followed by a variable and prevalently depth-related distribution of the soil parameters that is driven by the extreme Antarctic conditions. The dominant taxa in the glacier forefields are Actinobacteria, Acidobacteria, Proteobacteria, Bacteroidetes, Cyanobacteria and Chloroflexi. The connection of soil characteristics with bacterial community structure showed that soil parameter and soil formation along the glacier forefield influence the distribution of certain phyla. In the early step of succession the relative undifferentiated bacterial diversity reflects the undifferentiated soil development and has a high potential to shift according to past and present environmental conditions. With progressing development environmental constraints such as water or carbon limitation have a greater influence. Adapting the culturing conditions to the cold and oligotrophic environment, the number of culturable heterotrophic bacteria reached up to 108 colony forming units per gram soil and 148 isolates were obtained. Two new psychrotolerant bacteria, Herbaspirillum psychrotolerans PB1T and Chryseobacterium frigidisoli PB4T, were characterised in detail and described as novel species in the family of Oxalobacteraceae and Flavobacteriaceae, respectively. The isolates are able to grow at low temperatures tolerating temperature fluctuations and they are not specialised to a certain substrate, therefore they are well-adapted to the cold and oligotrophic environment. The adaptation strategies of the microorganisms were analysed in environmental samples and cultures focussing on extracellular enzyme activity at low temperature and PLFA analyses. Extracellular phosphatases (pH 11 and pH 6.5), β-glucosidase, invertase and urease activity were detected in the glacier forefield soils at low temperature (14°C) catalysing the conversion of various compounds providing necessary substrates and may further play a role in the soil formation and total carbon turnover of the habitat. The PLFA analysis of the newly isolated species C. frigidisoli showed that the cold-adapted strain develops different strategies to maintain the cell membrane function under changing environmental conditions by altering the PLFA inventory at different temperatures and pH values. A newly discovered fatty acid, which was not found in any other microorganism so far, significantly increased at decreasing temperature and low pH and thus plays an important role in the adaption of C. frigidisoli. This work gives insights into the diversity, distribution and adaptation mechanisms of microbial communities in oligotrophic cold-affected soils and shows that Antarctic glacier forefields are suitable model systems to study bacterial colonisation in connection to soil formation.