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Institute
Arctic climate change is marked by intensified warming compared to global trends and a significant reduction in Arctic sea ice which can intricately influence mid-latitude atmospheric circulation through tropo- and stratospheric pathways. Achieving accurate simulations of current and future climate demands a realistic representation of Arctic climate processes in numerical climate models, which remains challenging.
Model deficiencies in replicating observed Arctic climate processes often arise due to inadequacies in representing turbulent boundary layer interactions that determine the interactions between the atmosphere, sea ice, and ocean. Many current climate models rely on parameterizations developed for mid-latitude conditions to handle Arctic turbulent boundary layer processes.
This thesis focuses on modified representation of the Arctic atmospheric processes and understanding their resulting impact on large-scale mid-latitude atmospheric circulation within climate models. The improved turbulence parameterizations, recently developed based on Arctic measurements, were implemented in the global atmospheric circulation model ECHAM6. This involved modifying the stability functions over sea ice and ocean for stable stratification and changing the roughness length over sea ice for all stratification conditions. Comprehensive analyses are conducted to assess the impacts of these modifications on ECHAM6's simulations of the Arctic boundary layer, overall atmospheric circulation, and the dynamical pathways between the Arctic and mid-latitudes.
Through a step-wise implementation of the mentioned parameterizations into ECHAM6, a series of sensitivity experiments revealed that the combined impacts of the reduced roughness length and the modified stability functions are non-linear. Nevertheless, it is evident that both modifications consistently lead to a general decrease in the heat transfer coefficient, being in close agreement with the observations.
Additionally, compared to the reference observations, the ECHAM6 model falls short in accurately representing unstable and strongly stable conditions.
The less frequent occurrence of strong stability restricts the influence of the modified stability functions by reducing the affected sample size. However, when focusing solely on the specific instances of a strongly stable atmosphere, the sensible heat flux approaches near-zero values, which is in line with the observations. Models employing commonly used surface turbulence parameterizations were shown to have difficulties replicating the near-zero sensible heat flux in strongly stable stratification.
I also found that these limited changes in surface layer turbulence parameterizations have a statistically significant impact on the temperature and wind patterns across multiple pressure levels, including the stratosphere, in both the Arctic and mid-latitudes. These significant signals vary in strength, extent, and direction depending on the specific month or year, indicating a strong reliance on the background state.
Furthermore, this research investigates how the modified surface turbulence parameterizations may influence the response of both stratospheric and tropospheric circulation to Arctic sea ice loss.
The most suitable parameterizations for accurately representing Arctic boundary layer turbulence were identified from the sensitivity experiments. Subsequently, the model's response to sea ice loss is evaluated through extended ECHAM6 simulations with different prescribed sea ice conditions.
The simulation with adjusted surface turbulence parameterizations better reproduced the observed Arctic tropospheric warming in vertical extent, demonstrating improved alignment with the reanalysis data. Additionally, unlike the control experiments, this simulation successfully reproduced specific circulation patterns linked to the stratospheric pathway for Arctic-mid-latitude linkages. Specifically, an increased occurrence of the Scandinavian-Ural blocking regime (negative phase of the North Atlantic Oscillation) in early (late) winter is observed. Overall, it can be inferred that improving turbulence parameterizations at the surface layer can improve the ECHAM6's response to sea ice loss.
Sustainable urban growth
(2022)
This dissertation explores the determinants for sustainable and socially optimalgrowth in a city. Two general equilibrium models establish the base for this evaluation, each adding its puzzle piece to the urban sustainability discourse and examining the role of non-market-based and market-based policies for balanced growth and welfare improvements in different theory settings. Sustainable urban growth either calls for policy actions or a green energy transition. Further, R&D market failures can pose severe challenges to the sustainability of urban growth and the social optimality of decentralized allocation decisions. Still, a careful (holistic) combination of policy instruments can achieve sustainable growth and even be first best.
Stimuli-promoted in situ formation of hydrogels with thiol/thioester containing peptide precursors
(2022)
Hydrogels are potential synthetic ECM-like substitutes since they provide functional and structural similarities compared to soft tissues. They can be prepared by crosslinking of macromolecules or by polymerizing suitable precursors. The crosslinks are not necessarily covalent bonds, but could also be formed by physical interactions such as π-π interactions, hydrophobic interactions, or H-bonding. On demand in situ forming hydrogels have garnered increased interest especially for biomedical applications over preformed gels due to the relative ease of in vivo delivery and filling of cavities. The thiol-Michael addition reaction provides a straightforward and robust strategy for in situ gel formation with its fast reaction kinetics and ability to proceed under physiological conditions. The incorporation of a trigger function into a crosslinking system becomes even more interesting since gelling can be controlled with stimulus of choice. The use of small molar mass crosslinker precursors with active groups orthogonal to thiol-Michael reaction type electrophile provides the opportunity to implement an on-demand in situ crosslinking without compromising the fast reaction kinetics.
It was postulated that short peptide sequences due to the broad range structural-function relations available with the different constituent amino acids, can be exploited for the realisation of stimuli-promoted in situ covalent crosslinking and gelation applications. The advantages of this system over conventional polymer-polymer hydrogel systems are the ability tune and predict material property at the molecular level.
The main aim of this work was to develop a simplified and biologically-friendly stimuli-promoted in situ crosslinking and hydrogelation system using peptide mimetics as latent crosslinkers. The approach aims at using a single thiodepsipeptide sequence to achieve separate pH- and enzyme-promoted gelation systems with little modification to the thiodepsipeptide sequence. The realization of this aim required the completion of three milestones.
In the first place, after deciding on the thiol-Michael reaction as an effective in situ crosslinking strategy, a thiodepsipeptide, Ac-Pro-Leu-Gly-SLeu-Leu-Gly-NEtSH (TDP) with expected propensity towards pH-dependent thiol-thioester exchange (TTE) activation, was proposed as a suitable crosslinker precursor for pH-promoted gelation system. Prior to the synthesis of the proposed peptide-mimetic, knowledge of the thiol-Michael reactivity of the would-be activated thiol moiety SH-Leu, which is internally embedded in the thiodepsipeptide was required. In line with pKa requirements for a successful TTE, the reactivity of a more acidic thiol, SH-Phe was also investigated to aid the selection of the best thiol to be incorporated in the thioester bearing peptide based crosslinker precursor. Using ‘pseudo’ 2D-NMR investigations, it was found that only reactions involving SH-Leu yielded the expected thiol-Michael product, an observation that was attributed to the steric hindrance of the bulkier nature of SH-Phe. The fast reaction rates and complete acrylate/maleimide conversion obtained with SH-Leu at pH 7.2 and higher aided the direct elimination of SH-Phe as a potential thiol for the synthesis of the peptide mimetic.
Based on the initial studies, for the pH-promoted gelation system, the proposed Ac-Pro-Leu-Gly-SLeu-Leu-Gly-NEtSH was kept unmodified. The subtle difference in pKa values between SH-Leu (thioester thiol) and the terminal cysteamine thiol from theoretical conditions should be enough to effect a ‘pseudo’ intramolecular TTE. In polar protic solvents and under basic aqueous conditions, TDP successfully undergoes a ‘pseudo’ intramolecular TTE reaction to yield an α,ω-dithiol tripeptide, HSLeu-Leu-Gly-NEtSH. The pH dependence of thiolate ion generation by the cysteamine thiol aided the incorporation of the needed stimulus (pH) for the overall success of TTE (activation step) – thiol-Michael addition (crosslinking) strategy.
Secondly, with potential biomedical applications in focus, the susceptibility of TDP, like other thioesters, to intermolecular TTE reaction was probed with a group of thiols of varying thiol pKa values, since biological milieu characteristically contain peptide/protein thiols. L-cysteine, which is a biologically relevant thiol, and a small molecular weight thiol, methylthioglycolate both with relatively similar thiol pKa, values, led to an increase concentration of the dithiol crosslinker when reacted with TDP. In the presence of acidic thiols (p-NTP and 4MBA), a decrease in the dithiol concentration was observed, an observation that can be attributed to the inability of the TTE tetrahedral intermediate to dissociate into exchange products and is in line with pKa requirements for successful TTE reaction. These results additionally makes TDP more attractive and the potentially the first crosslinker precursor for applications in biologically relevant media.
Finally, the ability of TDP to promote pH-sensitive in situ gel formation was probed with maleimide functionalized 4-arm polyethylene glycol polymers in tris-buffered media of varying pHs. When a 1:1 thiol: maleimide molar ratio was used, TDP-PEG4MAL hydrogels formed within 3, 12 and 24 hours at pH values of 8.5, 8.0 and 7.5 respectively. However, gelation times of 3, 5 and 30 mins were observed for the same pH trend when the thiol: maleimide molar was increased to 2:1.
A direct correlation of thiol content with G’ of the gels at each pH could also be drawn by comparing gels with thiol: maleimide ratios of 1:1 to those with 2:1 thiol: maleimide mole ratios. This is supported by the fact that the storage modulus (G') is linearly dependent on the crosslinking density of the polymer. The values of initial G′ for all gels ranged between (200 – 5000 Pa), which falls in the range of elasticities of certain tissue microenvironments for example brain tissue 200 – 1000 Pa and adipose tissue (2500 – 3500 Pa).
Knowledge so far gained from the study on the ability to design and tune the exchange reaction of thioester containing peptide mimetic will give those working in the field further insight into the development of new sequences tailored towards specific applications.
TTE substrate design using peptide mimetic as presented in this work has revealed interesting new insights considering the state-of-the-art. Using the results obtained as reference, the strategy provides a possibility to extend the concept to the controlled delivery of active molecules needed for other robust and high yielding crosslinking reactions for biomedical applications. Application for this sequentially coupled functional system could be seen e.g. in the treatment of inflamed tissues associated with urinary tract like bladder infections for which pH levels above 7 were reported. By the inclusion of cell adhesion peptide motifs, the hydrogel network formed at this pH could act as a new support layer for the healing of damage epithelium as shown in interfacial gel formation experiments using TDP and PEG4MAL droplets.
The versatility of the thiodepsipeptide sequence, Ac-Pro-Leu-Gly-SLeu-Leu-Gly-(TDPo) was extended for the design and synthesis of a MMP-sensitive 4-arm PEG-TDPo conjugate. The purported cleavage of TDPo at the Gly-SLeu bond yields active thiol units for subsequent reaction of orthogonal Michael acceptor moieties. One of the advantages of stimuli-promoted in situ crosslinking systems using short peptides should be the ease of design of required peptide molecules due to the predictability of peptide functions their sequence structure. Consequently the functionalisation of a 4-arm PEG core with the collagenase active TDPo sequence yielded an MMP-sensitive 4-arm thiodepsipeptide-PEG conjugate (PEG4TDPo) substrate.
Cleavage studies using thiol flourometric assay in the presence of MMPs -2 and -9 confirmed the susceptibility of PEG4TDPo towards these enzymes. The resulting time-dependent increase in fluorescence intensity in the presence of thiol assay signifies the successful cleavage of TDPo at the Gly-SLeu bond as expected. It was observed that the cleavage studies with thiol flourometric assay introduces a sigmoid non-Michaelis-Menten type kinetic profile, hence making it difficult to accurately determine the enzyme cycling parameters, kcat and KM .
Gelation studies with PEG4MAL at 10 % wt. concentrations revealed faster gelation with MMP-2 than MMP-9 with 28 and 40 min gelation times respectively. Possible contributions by hydrolytic cleavage of PEG4TDPo has resulted in the gelation of PEG4MAL blank samples but only after 60 minutes of reaction. From theoretical considerations, the simultaneous gelation reaction would be expected to more negatively impact the enzymatic than hydrolytic cleavage. The exact contributions from hydrolytic cleavage of PEG4TDPo would however require additional studies.
In summary this new and simplified in situ crosslinking system using peptide-based crosslinker precursors with tuneable properties exhibited in situ crosslinking gelation kinetics on similar levels with already active dithiols reported. The advantageous on-demand functionality associated with its pH-sensitivity and physiological compatibility makes it a strong candidate worth further research as biomedical applications in general and on-demand material synthesis is concerned.
Results from MMP-promoted gelation system unveils a simple but unexplored approach for in situ synthesis of covalently crosslinked soft materials, that could lead to the development of an alternative pathway in addressing cancer metastasis by making use of MMP overexpression as a trigger. This goal has so far not being reach with MMP inhibitors despite the extensive work this regard.
Stars under influence: evidence of tidal interactions between stars and substellar companions
(2023)
Tidal interactions occur between gravitationally bound astrophysical bodies. If their spatial separation is sufficiently small, the bodies can induce tides on each other, leading to angular momentum transfer and altering of evolutionary path the bodies would have followed if they were single objects. The tidal processes are well established in the Solar planet-moon systems and close stellar binary systems. However, how do stars behave if they are orbited by a substellar companion (e.g. a planet or a brown dwarf) on a tight orbit?
Typically, a substellar companion inside the corotation radius of a star will migrate toward the star as it loses orbital angular momentum. On the other hand, the star will gain angular momentum which has the potential to increase its rotation rate. The effect should be more pronounced if the substellar companion is more massive. As the stellar rotation rate and the magnetic activity level are coupled, the star should appear more magnetically active under the tidal influence of the orbiting substellar companion. However, the difficulty in proving that a star has a higher magnetic activity level due to tidal interactions lies in the fact that (I) substellar companions around active stars are easier to detect if they are more massive, leading to a bias toward massive companions around active stars and mimicking the tidal interaction effect, and that (II) the age of a main-sequence star cannot be easily determined, leaving the possibility that a star is more active due to its young age.
In our work, we overcome these issues by employing wide stellar binary systems where one star hosts a substellar companion, and where the other star provides the magnetic activity baseline for the host star, assuming they have coevolved, and thereby provides the host's activity level if tidal interactions have no effect on it. Firstly, we find that extrasolar planets can noticeably increase the host star's X-ray luminosity and that the effect is more pronounced if the exoplanet is at least Jupiter-like in mass and close to the star. Further, we find that a brown dwarf will have an even stronger effect, as expected, and that the X-ray surface flux difference between the host star and the wide stellar companion is a significant outlier when compared to a large sample of similar wide binary systems without any known substellar companions. This result proves that substellar hosting wide binary systems can be good tools to reveal the tidal effect on host stars, and also show that the typical stellar age indicators as activity or rotation cannot be used for these stars. Finally, knowing that the activity difference is a good tracer of the substellar companion's tidal impact, we develop an analytical method to calculate the modified tidal quality factor Q' of individual host stars, which defines the tidal dissipation efficiency in the convective envelope of a given main-sequence star.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on Cross Recurrence Plots and Recurrence Quantification Analysis which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multi-dimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to Cross Recurrence Plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.
Today, more than half of the world’s population lives in urban areas. With a high density of population and assets, urban areas are not only the economic, cultural and social hubs of every society, they are also highly susceptible to natural disasters. As a consequence of rising sea levels and an expected increase in extreme weather events caused by a changing climate in combination with growing cities, flooding is an increasing threat to many urban agglomerations around the globe.
To mitigate the destructive consequences of flooding, appropriate risk management and adaptation strategies are required. So far, flood risk management in urban areas is almost exclusively focused on managing river and coastal flooding. Often overlooked is the risk from small-scale rainfall-triggered flooding, where the rainfall intensity of rainstorms exceeds the capacity of urban drainage systems, leading to immediate flooding. Referred to as pluvial flooding, this flood type exclusive to urban areas has caused severe losses in cities around the world. Without further intervention, losses from pluvial flooding are expected to increase in many urban areas due to an increase of impervious surfaces compounded with an aging drainage infrastructure and a projected increase in heavy precipitation events. While this requires the integration of pluvial flood risk into risk management plans, so far little is known about the adverse consequences of pluvial flooding due to a lack of both detailed data sets and studies on pluvial flood impacts. As a consequence, methods for reliably estimating pluvial flood losses, needed for pluvial flood risk assessment, are still missing.
Therefore, this thesis investigates how pluvial flood losses to private households can be reliably estimated, based on an improved understanding of the drivers of pluvial flood loss. For this purpose, detailed data from pluvial flood-affected households was collected through structured telephone- and web-surveys following pluvial flood events in Germany and the Netherlands.
Pluvial flood losses to households are the result of complex interactions between impact characteristics such as the water depth and a household’s resistance as determined by its risk awareness, preparedness, emergency response, building properties and other influencing factors. Both exploratory analysis and machine-learning approaches were used to analyze differences in resistance and impacts between households and their effects on the resulting losses. The comparison of case studies showed that the awareness around pluvial flooding among private households is quite low. Low awareness not only challenges the effective dissemination of early warnings, but was also found to influence the implementation of private precautionary measures. The latter were predominately implemented by households with previous experience of pluvial flooding. Even cases where previous flood events affected a different part of the same city did not lead to an increase in preparedness of the surveyed households, highlighting the need to account for small-scale variability in both impact and resistance parameters when assessing pluvial flood risk.
While it was concluded that the combination of low awareness, ineffective early warning and the fact that only a minority of buildings were adapted to pluvial flooding impaired the coping capacities of private households, the often low water levels still enabled households to mitigate or even prevent losses through a timely and effective emergency response.
These findings were confirmed by the detection of loss-influencing variables, showing that cases in which households were able to prevent any loss to the building structure are predominately explained by resistance variables such as the household’s risk awareness, while the degree of loss is mainly explained by impact variables.
Based on the important loss-influencing variables detected, different flood loss models were developed. Similar to flood loss models for river floods, the empirical data from the preceding data collection was used to train flood loss models describing the relationship between impact and resistance parameters and the resulting loss to building structures. Different approaches were adapted from river flood loss models using both models with the water depth as only predictor for building structure loss and models incorporating additional variables from the preceding variable detection routine.
The high predictive errors of all compared models showed that point predictions are not suitable for estimating losses on the building level, as they severely impair the reliability of the estimates. For that reason, a new probabilistic framework based on Bayesian inference was introduced that is able to provide predictive distributions instead of single loss estimates. These distributions not only give a range of probable losses, they also provide information on how likely a specific loss value is, representing the uncertainty in the loss estimate.
Using probabilistic loss models, it was found that the certainty and reliability of a loss estimate on the building level is not only determined by the use of additional predictors as shown in previous studies, but also by the choice of response distribution defining the shape of the predictive distribution. Here, a mix between a beta and a Bernoulli distribution to account for households that are able to prevent losses to their building’s structure was found to provide significantly more certain and reliable estimates than previous approaches using Gaussian or non-parametric response distributions.
The successful model transfer and post-event application to estimate building structure loss in Houston, TX, caused by pluvial flooding during Hurricane Harvey confirmed previous findings, and demonstrated the potential of the newly developed multi-variable beta model for future risk assessments. The highly detailed input data set constructed from openly available data sources containing over 304,000 affected buildings in Harris County further showed the potential of data-driven, building-level loss models for pluvial flood risk assessment.
In conclusion, pluvial flood losses to private households are the result of complex interactions between impact and resistance variables, which should be represented in loss models. The local occurrence of pluvial floods requires loss estimates on high spatial resolutions, i.e. on the building level, where losses are variable and uncertainties are high.
Therefore, probabilistic loss estimates describing the uncertainty of the estimate should be used instead of point predictions. While the performance of probabilistic models on the building level are mainly driven by the choice of response distribution, multi-variable models are recommended for two reasons:
First, additional resistance variables improve the detection of cases in which households were able to prevent structural losses.
Second, the added variability of additional predictors provides a better representation of the uncertainties when loss estimates from multiple buildings are aggregated.
This leads to the conclusion that data-driven probabilistic loss models on the building level allow for a reliable loss estimation at an unprecedented level of detail, with a consistent quantification of uncertainties on all aggregation levels. This makes the presented approach suitable for a wide range of applications, from decision support in spatial planning to impact- based early warning systems.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.
Moss-microbe associations are often characterised by syntrophic interactions between the microorganisms and their hosts, but the structure of the microbial consortia and their role in peatland development remain unknown.
In order to study microbial communities of dominant peatland mosses, Sphagnum and brown mosses, and the respective environmental drivers, four study sites representing different successional stages of natural northern peatlands were chosen on a large geographical scale: two brown moss-dominated, circumneutral peatlands from the Arctic and two Sphagnum-dominated, acidic peat bogs from subarctic and temperate zones.
The family Acetobacteraceae represented the dominant bacterial taxon of Sphagnum mosses from various geographical origins and displayed an integral part of the moss core community. This core community was shared among all investigated bryophytes and consisted of few but highly abundant prokaryotes, of which many appear as endophytes of Sphagnum mosses. Moreover, brown mosses and Sphagnum mosses represent habitats for archaea which were not studied in association with peatland mosses so far. Euryarchaeota that are capable of methane production (methanogens) displayed the majority of the moss-associated archaeal communities. Moss-associated methanogenesis was detected for the first time, but it was mostly negligible under laboratory conditions. Contrarily, substantial moss-associated methane oxidation was measured on both, brown mosses and Sphagnum mosses, supporting that methanotrophic bacteria as part of the moss microbiome may contribute to the reduction of methane emissions from pristine and rewetted peatlands of the northern hemisphere.
Among the investigated abiotic and biotic environmental parameters, the peatland type and the host moss taxon were identified to have a major impact on the structure of moss-associated bacterial communities, contrarily to archaeal communities whose structures were similar among the investigated bryophytes. For the first time it was shown that different bog development stages harbour distinct bacterial communities, while at the same time a small core community is shared among all investigated bryophytes independent of geography and peatland type.
The present thesis displays the first large-scale, systematic assessment of bacterial and archaeal communities associated both with brown mosses and Sphagnum mosses. It suggests that some host-specific moss taxa have the potential to play a key role in host moss establishment and peatland development.
The Greenland Ice Sheet is the second-largest mass of ice on Earth. Being almost 2000 km long, more than 700 km wide, and more than 3 km thick at the summit, it holds enough ice to raise global sea levels by 7m if melted completely. Despite its massive size, it is particularly vulnerable to anthropogenic climate change: temperatures over the Greenland Ice Sheet have increased by more than 2.7◦C in the past 30 years, twice as much as the global mean temperature. Consequently, the ice sheet has been significantly losing mass since the 1980s and the rate of loss has increased sixfold since then. Moreover, it is one of the potential tipping elements of the Earth System, which might undergo irreversible change once a warming threshold is exceeded. This thesis aims at extending the understanding of the resilience of the Greenland Ice Sheet against global warming by analyzing processes and feedbacks relevant to its centennial to multi-millennial stability using ice sheet modeling.
One of these feedbacks, the melt-elevation-feedback is driven by the temperature rise with decreasing altitudes: As the ice sheet melts, its thickness and surface elevation decrease, exposing the ice surface to warmer air and thus increasing the melt rates even further. The glacial isostatic adjustment (GIA) can partly mitigate this melt-elevation feedback as the bedrock lifts in response to an ice load decrease, forming the negative GIA feedback. In my thesis, I show that the interaction between these two competing feedbacks can lead to qualitatively different dynamical responses of the Greenland Ice Sheet to warming – from permanent loss to incomplete recovery, depending on the feedback parameters. My research shows that the interaction of those feedbacks can initiate self-sustained oscillations of the ice volume while the climate forcing remains constant.
Furthermore, the increased surface melt changes the optical properties of the snow or ice surface, e.g. by lowering their albedo, which in turn enhances melt rates – a process known as the melt-albedo feedback. Process-based ice sheet models often neglect this melt-albedo feedback. To close this gap, I implemented a simplified version of the diurnal Energy Balance Model, a computationally efficient approach that can capture the first-order effects of the melt-albedo feedback, into the Parallel Ice Sheet Model (PISM). Using the coupled model, I show in warming experiments that the melt-albedo feedback almost doubles the ice loss until the year 2300 under the low greenhouse gas emission scenario RCP2.6, compared to simulations where the melt-albedo feedback is neglected,
and adds up to 58% additional ice loss under the high emission scenario RCP8.5. Moreover, I find that the melt-albedo feedback dominates the ice loss until 2300, compared to the melt-elevation feedback.
Another process that could influence the resilience of the Greenland Ice Sheet is the warming induced softening of the ice and the resulting increase in flow. In my thesis, I show with PISM how the uncertainty in Glen’s flow law impacts the simulated response to warming. In a flow line setup at fixed climatic mass balance, the uncertainty in flow parameters leads to a range of ice loss comparable to the range caused by different warming levels.
While I focus on fundamental processes, feedbacks, and their interactions in the first three projects of my thesis, I also explore the impact of specific climate scenarios on the sea level rise contribution of the Greenland Ice Sheet. To increase the carbon budget flexibility, some warming scenarios – while still staying within the limits of the Paris Agreement – include a temporal overshoot of global warming. I show that an overshoot by 0.4◦C increases the short-term and long-term ice loss from Greenland by several centimeters. The long-term increase is driven by the warming at high latitudes, which persists even when global warming is reversed. This leads to a substantial long-term commitment of the sea level rise contribution from the Greenland Ice Sheet.
Overall, in my thesis I show that the melt-albedo feedback is most relevant for the ice loss of the Greenland Ice Sheet on centennial timescales. In contrast, the melt-elevation feedback and its interplay with the GIA feedback become increasingly relevant on millennial timescales. All of these influence the resilience of the Greenland Ice Sheet against global warming, in the near future and on the long term.
Extreme flooding displaces an average of 12 million people every year. Marginalized populations in low-income countries are in particular at high risk, but also industrialized countries are susceptible to displacement and its inherent societal impacts. The risk of being displaced results from a complex interaction of flood hazard, population exposed in the floodplains, and socio-economic vulnerability. Ongoing global warming changes the intensity, frequency, and duration of flood hazards, undermining existing protection measures. Meanwhile, settlements in attractive yet hazardous flood-prone areas have led to a higher degree of population exposure. Finally, the vulnerability to displacement is altered by demographic and social change, shifting economic power, urbanization, and technological development. These risk components have been investigated intensively in the context of loss of life and economic damage, however, only little is known about the risk of displacement under global change.
This thesis aims to improve our understanding of flood-induced displacement risk under global climate change and socio-economic change. This objective is tackled by addressing the following three research questions. First, by focusing on the choice of input data, how well can a global flood modeling chain reproduce flood hazards of historic events that lead to displacement? Second, what are the socio-economic characteristics that shape the vulnerability to displacement? Finally, to what degree has climate change potentially contributed to recent flood-induced displacement events?
To answer the first question, a global flood modeling chain is evaluated by comparing simulated flood extent with satellite-derived inundation information for eight major flood events. A focus is set on the sensitivity to different combinations of the underlying climate reanalysis datasets and global hydrological models which serve as an input for the global hydraulic model. An evaluation scheme of performance scores shows that simulated flood extent is mostly overestimated without the consideration of flood protection and only for a few events dependent on the choice of global hydrological models. Results are more sensitive to the underlying climate forcing, with two datasets differing substantially from a third one. In contrast, the incorporation of flood protection standards results in an underestimation of flood extent, pointing to potential deficiencies in the protection level estimates or the flood frequency distribution within the modeling chain.
Following the analysis of a physical flood hazard model, the socio-economic drivers of vulnerability to displacement are investigated in the next step. For this purpose, a satellite- based, global collection of flood footprints is linked with two disaster inventories to match societal impacts with the corresponding flood hazard. For each event the number of affected population, assets, and critical infrastructure, as well as socio-economic indicators are computed. The resulting datasets are made publicly available and contain 335 displacement events and 695 mortality/damage events. Based on this new data product, event-specific displacement vulnerabilities are determined and multiple (national) dependencies with the socio-economic predictors are derived. The results suggest that economic prosperity only partially shapes vulnerability to displacement; urbanization, infant mortality rate, the share of elderly, population density and critical infrastructure exhibit a stronger functional relationship, suggesting that higher levels of development are generally associated with lower vulnerability.
Besides examining the contextual drivers of vulnerability, the role of climate change in the context of human displacement is also being explored. An impact attribution approach is applied on the example of Cyclone Idai and associated extreme coastal flooding in Mozambique. A combination of coastal flood modeling and satellite imagery is used to construct factual and counterfactual flood events. This storyline-type attribution method allows investigating the isolated or combined effects of sea level rise and the intensification of cyclone wind speeds on coastal flooding. The results suggest that displacement risk has increased by 3.1 to 3.5% due to the total effects of climate change on coastal flooding, with the effects of increasing wind speed being the dominant factor.
In conclusion, this thesis highlights the potentials and challenges of modeling flood- induced displacement risk. While this work explores the sensitivity of global flood modeling to the choice of input data, new questions arise on how to effectively improve the reproduction of flood return periods and the representation of protection levels. It is also demonstrated that disentangling displacement vulnerabilities is feasible, with the results providing useful information for risk assessments, effective humanitarian aid, and disaster relief. The impact attribution study is a first step in assessing the effects of global warming on displacement risk, leading to new research challenges, e.g., coupling fluvial and coastal flood models or the attribution of other hazard types and displacement events. This thesis is one of the first to address flood-induced displacement risk from a global perspective. The findings motivate for further development of the global flood modeling chain to improve our understanding of displacement vulnerability and the effects of global warming.
Die vorliegende kumulative Promotionsarbeit beschäftigt sich mit leistungsstarken Schülerinnen und Schülern, die seit 2015 in der deutschen Bildungspolitik, zum Beispiel im Rahmen von Förderprogrammen wieder mehr Raum einnehmen, nachdem in Folge des „PISA-Schocks“ im Jahr 2000 zunächst der Fokus stärker auf den Risikogruppen lag. Während leistungsstärkere Schülerinnen und Schüler in der öffentlichen Wahrnehmung häufig mit „(Hoch-)Begabten“ identifiziert werden, geht die Arbeit über die traditionelle Begabungsforschung, die eine generelle Intelligenz als Grundlage für Leistungsfähigkeit von Schülerinnen und Schülern begreift und beforscht, hinaus. Stattdessen lässt sich eher in den Bereich der Talentforschung einordnen, die den Fokus weg von allgemeinen Begabungen auf spezifische Prädiktoren und Outcomes im individuellen Entwicklungsverlauf legt. Der Fokus der Arbeit liegt daher nicht auf Intelligenz als Potenzial, sondern auf der aktuellen schulischen Leistung, die als Ergebnis und Ausgangspunkt von Entwicklungsprozessen in einer Leistungsdomäne doppelte Bedeutung erhält.
Die Arbeit erkennt die Vielgestaltigkeit des Leistungsbegriffs an und ist bestrebt, neue Anlässe zu schaffen, über den Leistungsbegriff und seine Operationalisierung in der Forschung zu diskutieren. Hierfür wird im ersten Teil ein systematisches Review zur Operationalisierung von Leistungsstärke durchgeführt (Artikel I). Es werden Faktoren herausgearbeitet, auf welchen sich die Operationalisierungen unterscheiden können. Weiterhin wird ein Überblick gegeben, wie Studien zu Leistungsstarken sich seit dem Jahr 2000 auf diesen Dimensionen verorten lassen. Es zeigt sich, dass eindeutige Konventionen zur Definition schulischer Leistungsstärke noch nicht existieren, woraus folgt, dass Ergebnisse aus Studien, die sich mit leistungsstarken Schülerinnen und Schülern beschäftigen, nur bedingt miteinander vergleichbar sind. Im zweiten Teil der Arbeit wird im Rahmen zwei weiterer Artikel, welche sich mit der Leistungsentwicklung (Artikel II) und der sozialen Einbindung (Artikel III) von leistungsstarken Schülerinnen und Schülern befassen, darauf aufbauend der Ansatz verfolgt, die Variabilität von Ergebnissen über verschiedene Operationalisierungen von Leistungsstärke deutlich zu machen. Damit wird unter anderem auch die künftige Vergleichbarkeit mit anderen Studien erleichtert. Genutzt wird dabei das Konzept der Multiversumsanalyse (Steegen et al., 2016), bei welcher viele parallele Spezifikationen, die zugleich sinnvolle Alternativen für die Operationalisierung darstellen, nebeneinandergestellt und in ihrem Effekt verglichen werden (Jansen et al., 2021). Die Multiversumsanalyse knüpft konzeptuell an das bereits vor längerem entwickelte Forschungsprogramm des kritischen Multiplismus an (Patry, 2013; Shadish, 1986, 1993), erhält aber als spezifische Methode aktuell im Rahmen der Replizierbarkeitskrise in der Psychologie eine besondere Bedeutung. Dabei stützt sich die vorliegende Arbeit auf die Sekundäranalyse großangelegter Schulleistungsstudien, welche den Vorteil besitzen, dass eine große Zahl an Datenpunkten (Variablen und Personen) zur Verfügung steht, um Effekte unterschiedlicher Operationalisierungen zu vergleichen.
Inhaltlich greifen Artikel II und III Themen auf, die in der wissenschaftlichen und gesellschaftlichen Diskussion zu Leistungsstarken und ihrer Wahrnehmung in der Öffentlichkeit immer wieder aufscheinen: In Artikel II wird zunächst die Frage gestellt, ob Leistungsstarke bereits im aktuellen Regelunterricht einen kumulativen Vorteil gegenüber ihren weniger leistungsstarken Mitschülerinnen und Mitschülern haben (Matthäus-Effekt). Die Ergebnisse zeigen, dass an Gymnasien keineswegs von sich vergrößernden Unterschieden gesprochen werden kann. Im Gegenteil, es verringerte sich im Laufe der Sekundarstufe der Abstand zwischen den Gruppen, indem die Lernraten bei leistungsschwächeren Schülerinnen und Schülern höher waren. Artikel III hingegen betrifft die soziale Wahrnehmung von leistungsstarken Schülerinnen und Schülern. Auch hier hält sich in der öffentlichen Diskussion die Annahme, dass höhere Leistungen mit Nachteilen in der sozialen Integration einhergehen könnten, was sich auch in Studien widerspiegelt, die sich mit Geschlechterstereotypen Jugendlicher in Bezug auf Schulleistung beschäftigen. In Artikel III wird unter anderem erneut das Potenzial der Multiversumsanalyse genutzt, um die Variation des Zusammenhangs über Operationalisierungen von Leistungsstärke zu beschreiben. Es zeigt sich unter unterschiedlichen Operationalisierungen von Leistungsstärke und über verschiedene Facetten sozialer Integration hinweg, dass die Zusammenhänge zwischen Leistung und sozialer Integration insgesamt leicht positiv ausfallen. Annahmen, die auf differenzielle Effekte für Jungen und Mädchen oder für unterschiedliche Fächer abzielen, finden in diesen Analysen keine Bestätigung.
Die Dissertation zeigt, dass der Vergleich unterschiedlicher Ansätze zur Operationalisierung von Leistungsstärke — eingesetzt im Rahmen eines kritischen Multiplismus — das Verständnis von Phänomenen vertiefen kann und auch das Potenzial hat, Theorieentwicklung voranzubringen.
The NAC transcription factor (TF) JUNGBRUNNEN1 (JUB1) is an important negative regulator of plant senescence, as well as of gibberellic acid (GA) and brassinosteroid (BR) biosynthesis in Arabidopsis thaliana. Overexpression of JUB1 promotes longevity and enhances tolerance to drought and other abiotic stresses. A similar role of JUB1 has been observed in other plant species, including tomato and banana. Our data show that JUB1 overexpressors (JUB1-OXs) accumulate higher levels of proline than WT plants under control conditions, during the onset of drought stress, and thereafter. We identified that overexpression of JUB1 induces key proline biosynthesis and suppresses key proline degradation genes. Furthermore, bZIP63, the transcription factor involved in proline metabolism, was identified as a novel downstream target of JUB1 by Yeast One-Hybrid (Y1H) analysis and Chromatin immunoprecipitation (ChIP). However, based on Electrophoretic Mobility Shift Assay (EMSA), direct binding of JUB1 to bZIP63 could not be confirmed. Our data indicate that JUB1-OX plants exhibit reduced stomatal conductance under control conditions. However, selective overexpression of JUB1 in guard cells did not improve drought stress tolerance in Arabidopsis. Moreover, the drought-tolerant phenotype of JUB1 overexpressors does not solely depend on the transcriptional control of the DREB2A gene. Thus, our data suggest that JUB1 confers tolerance to drought stress by regulating multiple components. Until today, none of the previous studies on JUB1´s regulatory network focused on identifying protein-protein interactions. We, therefore, performed a yeast two-hybrid screen (Y2H) which identified several protein interactors of JUB1, two of which are the calcium-binding proteins CaM1 and CaM4. Both proteins interact with JUB1 in the nucleus of Arabidopsis protoplasts. Moreover, JUB1 is expressed with CaM1 and CaM4 under the same conditions. Since CaM1.1 and CaM4.1 encode proteins with identical amino acid sequences, all further experiments were performed with constructs involving the CaM4 coding sequence. Our data show that JUB1 harbors multiple CaM-binding sites, which are localized in both the N-terminal and C-terminal regions of the protein. One of the CaM-binding sites, localized in the DNA-binding domain of JUB1, was identified as a functional CaM-binding site since its mutation strongly reduced the binding of CaM4 to JUB1. Furthermore, JUB1 transactivates expression of the stress-related gene DREB2A in mesophyll cells; this effect is significantly reduced when the calcium-binding protein CaM4 is expressed as well. Overexpression of both genes in Arabidopsis results in early senescence observed through lower chlorophyll content and an enhanced expression of senescence-associated genes (SAGs) when compared with single JUB1 overexpressors. Our data also show that JUB1 and CaM4 proteins interact in senescent leaves, which have increased Ca2+ levels when compared to young leaves. Collectively, our data indicate that JUB1 activity towards its downstream targets is fine-tuned by calcium-binding proteins during leaf senescence.
Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments
(2024)
The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics.
The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources.
The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for permafrost extent and ALT but reveals a significant global cold temperature bias, notably over Siberia. These results echo a persistent challenge identified in numerous studies: the existence of a systematic 'cold bias' in soil temperature over permafrost regions. To address this challenge, the following research questions propose dual sensitivity experiments.
The third research question represents the first study to apply a Plant Functional Type (PFT)-based approach to derive soil texture and soil organic matter (SOM), departing from the conventional use of coarse-resolution global data in LSMs. This novel method results in a more uniform distribution of soil organic matter density (OMD) across the domain, characterized by reduced OMD values in most regions. However, changes in soil texture exhibit a more intricate spatial pattern. Comparing the results to observations reveals a significant reduction in the cold bias observed in the control run. This method shows noticeable improvements in permafrost extent, but at the cost of an overestimation in ALT. These findings emphasize the model's high sensitivity to variations in soil texture and SOM content, highlighting the crucial role of soil composition in governing heat transfer processes and shaping the seasonal variation of soil temperatures in permafrost regions.
Expanding upon a site experiment conducted in Trail Valley Creek by \citet{dutch_impact_2022}, the fourth research question extends the application of the snow scheme proposed by \citet{sturm_thermal_1997} to cover the entire Arctic domain. By employing a snow scheme better suited to the snow density profile observed over permafrost regions, this thesis seeks to assess its influence on simulated soil temperatures. Comparing this method to observational datasets reveals a significant reduction in the cold bias that was present in the control run. In most regions, the Sturm run exhibits a substantial decrease in the cold bias. However, there is a distinctive overshoot with a warm bias observed in mountainous areas. The Sturm experiment effectively addressed the overestimation of permafrost extent in the control run, albeit resulting in a substantial reduction in permafrost extent over mountainous areas. ALT results remain relatively consistent compared to the control run. These outcomes align with our initial hypothesis, which anticipated that the reduced snow insulation in the Sturm run would lead to higher winter soil temperatures and a more accurate representation of permafrost physics.
In summary, this thesis demonstrates significant advancements in understanding permafrost dynamics and its integration into LSMs. It has meticulously unraveled the intricacies involved in the interplay between heat transfer, soil properties, and snow dynamics in permafrost regions. These insights offer novel perspectives on model representation and performance.
The trace gases CO2 and CH4 pertain to the most relevant greenhouse gases and are important exchange fluxes of the global carbon (C) cycle. Their atmospheric quantity increased significantly as a result of the intensification of anthropogenic activities, such as especially land-use and land-use change, since the mid of the 18th century. To mitigate global climate change and ensure food security, land-use systems need to be developed, which favor reduced trace gas emissions and a sustainable soil carbon management. This requires the accurate and precise quantification of the influence of land-use and land-use change on CO2 and CH4 emissions. A common method to determine the trace gas dynamics and C sink or source function of a particular ecosystem is the closed chamber method. This method is often used assuming that accuracy and precision are high enough to determine differences in C gas emissions for e.g., treatment comparisons or different ecosystem components.
However, the broad range of different chamber designs, related operational procedures and data-processing strategies which are described in the scientific literature contribute to the overall uncertainty of closed chamber-based emission estimates. Hence, the outcomes of meta-analyses are limited, since these methodical differences hamper the comparability between studies. Thus, a standardization of closed chamber data acquisition and processing is much-needed.
Within this thesis, a set of case studies were performed to: (I) develop standardized routines for an unbiased data acquisition and processing, with the aim of providing traceable, reproducible and comparable closed chamber based C emission estimates; (II) validate those routines by comparing C emissions derived using closed chambers with independent C emission estimates; and (III) reveal processes driving the spatio-temporal dynamics of C emissions by developing (data processing based) flux separation approaches.
The case studies showed: (I) the importance to test chamber designs under field conditions for an appropriate sealing integrity and to ensure an unbiased flux measurement. Compared to the sealing integrity, the use of a pressure vent and fan was of minor importance, affecting mainly measurement precision; (II) that the developed standardized data processing routines proved to be a powerful and flexible tool to estimate C gas emissions and that this tool can be successfully applied on a broad range of flux data sets from very different ecosystem; (III) that automatic chamber measurements display temporal dynamics of CO2 and CH4 fluxes very well and most importantly, that they accurately detect small-scale spatial differences in the development of soil C when validated against repeated soil inventories; and (IV) that a simple algorithm to separate CH4 fluxes into ebullition and diffusion improves the identification of environmental drivers, which allows for an accurate gap-filling of measured CH4 fluxes.
Overall, the proposed standardized data acquisition and processing routines strongly improved the detection accuracy and precision of source/sink patterns of gaseous C emissions. Hence, future studies, which consider the recommended improvements, will deliver valuable new data and insights to broaden our understanding of spatio-temporal C gas dynamics, their particular environmental drivers and underlying processes.
Enhanced geothermal systems (EGS) are considered a cornerstone of future sustainable energy production. In such systems, high-pressure fluid injections break the rock to provide pathways for water to circulate in and heat up. This approach inherently induces small seismic events that, in rare cases, are felt or can even cause damage. Controlling and reducing the seismic impact of EGS is crucial for a broader public acceptance. To evaluate the applicability of hydraulic fracturing (HF) in EGS and to improve the understanding of fracturing processes and the hydromechanical relation to induced seismicity, six in-situ, meter-scale HF experiments with different injection schemes were performed under controlled conditions in crystalline rock in a depth of 410 m at the Äspö Hard Rock Laboratory (Sweden).
I developed a semi-automated, full-waveform-based detection, classification, and location workflow to extract and characterize the acoustic emission (AE) activity from the continuous recordings of 11 piezoelectric AE sensors. Based on the resulting catalog of 20,000 AEs, with rupture sizes of cm to dm, I mapped and characterized the fracture growth in great detail. The injection using a novel cyclic injection scheme (HF3) had a lower seismic impact than the conventional injections. HF3 induced fewer AEs with a reduced maximum magnitude and significantly larger b-values, implying a decreased number of large events relative to the number of small ones. Furthermore, HF3 showed an increased fracture complexity with multiple fractures or a fracture network. In contrast, the conventional injections developed single, planar fracture zones (Publication 1).
An independent, complementary approach based on a comparison of modeled and observed tilt exploits transient long-period signals recorded at the horizontal components of two broad-band seismometers a few tens of meters apart from the injections. It validated the efficient creation of hydraulic fractures and verified the AE-based fracture geometries. The innovative joint analysis of AEs and tilt signals revealed different phases of the fracturing process, including the (re-)opening, growth, and aftergrowth of fractures, and provided evidence for the reactivation of a preexisting fault in one of the experiments (Publication 2). A newly developed network-based waveform-similarity analysis applied to the massive AE activity supports the latter finding.
To validate whether the reduction of the seismic impact as observed for the cyclic injection schemes during the Äspö mine-scale experiments is transferable to other scales, I additionally calculated energy budgets for injection experiments from previously conducted laboratory tests and from a field application. Across all three scales, the cyclic injections reduce the seismic impact, as depicted by smaller maximum magnitudes, larger b-values, and decreased injection efficiencies (Publication 3).
Hydraulic-driven fractures play a key role in subsurface energy technologies across several scales. By injecting fluid at high hydraulic pressure into rock with intrinsic low permeability, in-situ stress field and fracture development pattern can be characterised as well as rock permeability can be enhanced. Hydraulic fracturing is a commercial standard procedure for enhanced oil and gas production of rock reservoirs with low permeability in petroleum industry. However, in EGS utilization, a major geological concern is the unsolicited generation of earthquakes due to fault reactivation, referred to as induced seismicity, with a magnitude large enough to be felt on the surface or to damage facilities and buildings. Furthermore, reliable interpretation of hydraulic fracturing tests for stress measurement is a great challenge for the energy technologies. Therefore, in this cumulative doctoral thesis the following research questions are investigated. (1): How do hydraulic fractures grow in hard rock at various scales?; (2): Which parameters control hydraulic fracturing and hydro-mechanical coupling?; and (3): How can hydraulic fracturing in hard rock be modelled?
In the laboratory scale study, several laboratory hydraulic fracturing experiments are investigated numerically using Irazu2D that were performed on intact cubic Pocheon granite samples from South Korea applying different injection protocols. The goal of the laboratory experiments is to test the concept of cyclic soft stimulation which may enable sustainable permeability enhancement (Publication 1).
In the borehole scale study, hydraulic fracturing tests are reported that were performed in boreholes located in central Hungary to determine the in-situ stress for a geological site investigation. At depth of about 540 m, the recorded pressure versus time curves in mica schist with low dip angle foliation show atypical evolution. In order to provide explanation for this observation, a series of discrete element computations using Particle Flow Code 2D are performed (Publication 2).
In the reservoir scale study, the hydro-mechanical behaviour of fractured crystalline rock due to one of the five hydraulic stimulations at the Pohang Enhanced Geothermal site in South Korea is studied. Fluid pressure perturbation at faults of several hundred-meter lengths during hydraulic stimulation is simulated using FracMan (Publication 3).
The doctoral research shows that the resulting hydraulic fracturing geometry will depend “locally”, i.e. at the length scale of representative elementary volume (REV) and below that (sub-REV), on the geometry and strength of natural fractures, and “globally”, i.e. at super-REV domain volume, on far-field stresses. Regarding hydro-mechanical coupling, it is suggested to define separate coupling relationship for intact rock mass and natural fractures. Furthermore, the relative importance of parameters affecting the magnitude of formation breakdown pressure, a parameter characterising hydro-mechanical coupling, is defined. It can be also concluded that there is a clear gap between the capacity of the simulation software and the complexity of the studied problems. Therefore, the computational time of the simulation of complex hydraulic fracture geometries must be reduced while maintaining high fidelity simulation results. This can be achieved either by extending the computational resources via parallelization techniques or using time scaling techniques. The ongoing development of used numerical models focuses on tackling these methodological challenges.
The concept of hydrologic connectivity summarizes all flow processes that link separate regions of a landscape. As such, it is a central theme in the field of catchment hydrology, with influence on neighboring disciplines such as ecology and geomorphology. It is widely acknowledged to be an important key in understanding the response behavior of a catchment and has at the same time inspired research on internal processes over a broad range of scales. From this process-hydrological point of view, hydrological connectivity is the conceptual framework to link local observations across space and scales.
This is the context in which the four studies this thesis comprises of were conducted. The focus was on structures and their spatial organization as important control on preferential subsurface flow. Each experiment covered a part of the conceptualized flow path from hillslopes to the stream: soil profile, hillslope, riparian zone, and stream.
For each study site, the most characteristic structures of the investigated domain and scale, such as slope deposits and peat layers were identified based on preliminary or previous investigations or literature reviews. Additionally, further structural data was collected and topographical analyses were carried out. Flow processes were observed either based on response observations (soil moisture changes or discharge patterns) or direct measurement (advective heat transport). Based on these data, the flow-relevance of the characteristic structures was evaluated, especially with regard to hillslope to stream connectivity.
Results of the four studies revealed a clear relationship between characteristic spatial structures and the hydrological behavior of the catchment. Especially the spatial distribution of structures throughout the study domain and their interconnectedness were crucial for the establishment of preferential flow paths and their relevance for large-scale processes. Plot and hillslope-scale irrigation experiments showed that the macropores of a heterogeneous, skeletal soil enabled preferential flow paths at the scale of centimeters through the otherwise unsaturated soil. These flow paths connected throughout the soil column and across the hillslope and facilitated substantial amounts of vertical and lateral flow through periglacial slope deposits.
In the riparian zone of the same headwater catchment, the connectivity between hillslopes and stream was controlled by topography and the dualism between characteristic subsurface structures and the geomorphological heterogeneity of the stream channel. At the small scale (1 m to 10 m) highest gains always occurred at steps along the longitudinal streambed profile, which also controlled discharge patterns at the large scale (100 m) during base flow conditions (number of steps per section). During medium and high flow conditions, however, the impact of topography and parafluvial flow through riparian zone structures prevailed and dominated the large-scale response patterns.
In the streambed of a lowland river, low permeability peat layers affected the connectivity between surface water and groundwater, but also between surface water and the hyporheic zone. The crucial factor was not the permeability of the streambed itself, but rather the spatial arrangement of flow-impeding peat layers, causing increased vertical flow through narrow “windows” in contrast to predominantly lateral flow in extended areas of high hydraulic conductivity sediments.
These results show that the spatial organization of structures was an important control for hydrological processes at all scales and study areas. In a final step, the observations from different scales and catchment elements were put in relation and compared. The main focus was on the theoretical analysis of the scale hierarchies of structures and processes and the direction of causal dependencies in this context. Based on the resulting hierarchical structure, a conceptual framework was developed which is capable of representing the system’s complexity while allowing for adequate simplifications.
The resulting concept of the parabolic scale series is based on the insight that flow processes in the terrestrial part of the catchment (soil and hillslopes) converge. This means that small-scale processes assemble and form large-scale processes and responses. Processes in the riparian zone and the streambed, however, are not well represented by the idea of convergence. Here, the large-scale catchment signal arrives and is modified by structures in the riparian zone, stream morphology, and the small-scale interactions between surface water and groundwater. Flow paths diverge and processes can better be represented by proceeding from large scales to smaller ones. The catchment-scale representation of processes and structures is thus the conceptual link between terrestrial hillslope processes and processes in the riparian corridor.
Digitalisation in industry – also called “Industry 4.0” – is seen by numerous actors as an opportunity to reduce the environmental impact of the industrial sector. The scientific assessments of the effects of digitalisation in industry on environmental sustainability, however, are ambivalent. This cumulative dissertation uses three empirical studies to examine the expected and observed effects of digitalisation in industry on environmental sustainability. The aim of this dissertation is to identify opportunities and risks of digitalisation at different system levels and to derive options for action in politics and industry for a more sustainable design of digitalisation in industry. I use an interdisciplinary, socio-technical approach and look at selected countries of the Global South (Study 1) and the example of China (all studies). In the first study (section 2, joint work with Marcel Matthess), I use qualitative content analysis to examine digital and industrial policies from seven different countries in Africa and Asia for expectations regarding the impact of digitalisation on sustainability and compare these with the potentials of digitalisation for sustainability in the respective country contexts. The analysis reveals that the documents express a wide range of vague expectations that relate more to positive indirect impacts of information and communication technology (ICT) use, such as improved energy efficiency and resource management, and less to negative direct impacts of ICT, such as electricity consumption through ICT. In the second study (section 3, joint work with Marcel Matthess, Grischa Beier and Bing Xue), I conduct and analyse interviews with 18 industry representatives of the electronics industry from Europe, Japan and China on digitalisation measures in supply chains using qualitative content analysis. I find that while there are positive expectations regarding the effects of digital technologies on supply chain sustainability, their actual use and observable effects are still limited. Interview partners can only provide few examples from their own companies which show that sustainability goals have already been pursued through digitalisation of the supply chain or where sustainability effects, such as resource savings, have been demonstrably achieved. In the third study (section 4, joint work with Peter Neuhäusler, Melissa Dachrodt and Marcel Matthess), I conduct an econometric panel data analysis. I examine the relationship between the degree of Industry 4.0, energy consumption and energy intensity in ten manufacturing sectors in China between 2006 and 2019. The results suggest that overall, there is no significant relationship between the degree of Industry 4.0 and energy consumption or energy intensity in manufacturing sectors in China. However, differences can be found in subgroups of sectors. I find a negative correlation of Industry 4.0 and energy intensity in highly digitalised sectors, indicating an efficiency-enhancing effect of Industry 4.0 in these sectors. On the other hand, there is a positive correlation of Industry 4.0 and energy consumption for sectors with low energy consumption, which could be explained by the fact that digitalisation, such as the automation of previously mainly labour-intensive sectors, requires energy and also induces growth effects. In the discussion section (section 6) of this dissertation, I use the classification scheme of the three levels macro, meso and micro, as well as of direct and indirect environmental effects to classify the empirical observations into opportunities and risks, for example, with regard to the probability of rebound effects of digitalisation at the three levels. I link the investigated actor perspectives (policy makers, industry representatives), statistical data and additional literature across the system levels and consider political economy aspects to suggest fields of action for more sustainable (digitalised) industries. The dissertation thus makes two overarching contributions to the academic and societal discourse. First, my three empirical studies expand the limited state of research at the interface between digitalisation in industry and sustainability, especially by considering selected countries in the Global South and the example of China. Secondly, exploring the topic through data and methods from different disciplinary contexts and taking a socio-technical point of view, enables an analysis of (path) dependencies, uncertainties, and interactions in the socio-technical system across different system levels, which have often not been sufficiently considered in previous studies. The dissertation thus aims to create a scientifically and practically relevant knowledge basis for a value-guided, sustainability-oriented design of digitalisation in industry.
Functional nanoporous carbon-based materials derived from oxocarbon-metal coordination complexes
(2017)
Nanoporous carbon based materials are of particular interest for both science and industry due to their exceptional properties such as a large surface area, high pore volume, high electroconductivity as well as high chemical and thermal stability. Benefiting from these advantageous properties, nanoporous carbons proved to be useful in various energy and environment related applications including energy storage and conversion, catalysis, gas sorption and separation technologies. The synthesis of nanoporous carbons classically involves thermal carbonization of the carbon precursors (e.g. phenolic resins, polyacrylonitrile, poly(vinyl alcohol) etc.) followed by an activation step and/or it makes use of classical hard or soft templates to obtain well-defined porous structures. However, these synthesis strategies are complicated and costly; and make use of hazardous chemicals, hindering their application for large-scale production. Furthermore, control over the carbon materials properties is challenging owing to the relatively unpredictable processes at the high carbonization temperatures.
In the present thesis, nanoporous carbon based materials are prepared by the direct heat treatment of crystalline precursor materials with pre-defined properties. This synthesis strategy does not require any additional carbon sources or classical hard- or soft templates. The highly stable and porous crystalline precursors are based on coordination compounds of the squarate and croconate ions with various divalent metal ions including Zn2+, Cu2+, Ni2+, and Co2+, respectively. Here, the structural properties of the crystals can be controlled by the choice of appropriate synthesis conditions such as the crystal aging temperature, the ligand/metal molar ratio, the metal ion, and the organic ligand system. In this context, the coordination of the squarate ions to Zn2+ yields porous 3D cube crystalline particles. The morphology of the cubes can be tuned from densely packed cubes with a smooth surface to cubes with intriguing micrometer-sized openings and voids which evolve on the centers of the low index faces as the crystal aging temperature is raised. By varying the molar ratio, the particle shape can be changed from truncated cubes to perfect cubes with right-angled edges.
These crystalline precursors can be easily transformed into the respective carbon based materials by heat treatment at elevated temperatures in a nitrogen atmosphere followed by a facile washing step. The resulting carbons are obtained in good yields and possess a hierarchical pore structure with well-organized and interconnected micro-, meso- and macropores. Moreover, high surface areas and large pore volumes of up to 1957 m2 g-1 and 2.31 cm3 g-1 are achieved, respectively, whereby the macroscopic structure of the precursors is preserved throughout the whole synthesis procedure.
Owing to these advantageous properties, the resulting carbon based materials represent promising supercapacitor electrode materials for energy storage applications. This is exemplarily demonstrated by employing the 3D hierarchical porous carbon cubes derived from squarate-zinc coordination compounds as electrode material showing a specific capacitance of 133 F g-1 in H2SO4 at a scan rate of 5 mV s-1 and retaining 67% of this specific capacitance when the scan rate is increased to 200 mV s-1.
In a further application, the porous carbon cubes derived from squarate-zinc coordination compounds are used as high surface area support material and decorated with nickel nanoparticles via an incipient wetness impregnation. The resulting composite material combines a high surface area, a hierarchical pore structure with high functionality and well-accessible pores. Moreover, owing to their regular micro-cube shape, they allow for a good packing of a fixed-bed flow reactor along with high column efficiency and a minimized pressure drop throughout the packed reactor. Therefore, the composite is employed as heterogeneous catalyst in the selective hydrogenation of 5-hydroxymethylfurfural to 2,5-dimethylfuran showing good catalytic performance and overcoming the conventional problem of column blocking.
Thinking about the rational design of 3D carbon geometries, the functions and properties of the resulting carbon-based materials can be further expanded by the rational introduction of heteroatoms (e.g. N, B, S, P, etc.) into the carbon structures in order to alter properties such as wettability, surface polarity as well as the electrochemical landscape. In this context, the use of crystalline materials based on oxocarbon-metal ion complexes can open a platform of highly functional materials for all processes that involve surface processes.