Partial melting within the lower crust – Constraints from bulk rock geochemical data and trace element mineral analyses of granulites and migmatites from Central Finland

This PhD thesis concerns geochemical constraints on recycling and partial melting of Archean continental crust. A natural example of such processes was found in the Iisalmi area of Central Finland. The rocks from this area are Middle to Late Archean in age and experienced metamorphism and partial melting between 2.7-2.63 Ga. The work is based on extensive field work. It is furthermore founded on bulk rock geochemical data as well as in-situ analyses of minerals. All geochemical data were obtained at the Institute of Geosciences, University of Mainz using X-ray fluorescence, solution ICP-MS and laser ablation-ICP-MS for bulk rock geochemical analyses. Mineral analyses were accomplished by electron microprobe and laser ablation ICP-MS. Fluid inclusions were studied by microscope on a heating-freezing-stage at the Geoscience Center, University Göttingen. Part I focuses on the development of a new analytical method for bulk rock trace element determination by laser ablation-ICP-MS using homogeneous glasses fused from rock powder on an Iridium strip heater. This method is applicable for mafic rock samples whose melts have low viscosities and homogenize quickly at temperatures of ~1200°C. Highly viscous melts of felsic samples prevent melting and homogenization at comparable temperatures. Fusion of felsic samples can be enabled by addition of MgO to the rock powder and adjustment of melting temperature and melting duration to the rock composition. Advantages of the fusion method are low detection limits compared to XRF analyses and avoidance of wet-chemical processing and use of strong acids as in solution ICP-MS as well as smaller sample volumes compared to the other methods. Part II of the thesis uses bulk rock geochemical data and results from fluid inclusion studies for discrimination of melting processes observed in different rock types. Fluid inclusion studies demonstrate a major change in fluid composition from CO2-dominated fluids in granulites to aqueous fluids in TTG gneisses and amphibolites. Partial melts were generated in the dry, CO2-rich environment by dehydration melting reactions of amphibole which in addition to tonalitic melts produced the anhydrous mineral assemblages of granulites (grt + cpx + pl ± amph or opx + cpx + pl + amph). Trace element modeling showed that mafic granulites are residues of 10-30 % melt extraction from amphibolitic precursor rocks. The maximum degree of melting in intermediate granulites was ~10 % as inferred from modal abundances of amphibole, clinopyroxene and orthopyroxene. Carbonic inclusions are absent in upper-amphibolite facies migmatites whereas aqueous inclusion with up to 20 wt% NaCl are abundant. This suggests that melting within TTG gneisses and amphibolites took place in the presence of an aqueous fluid phase that enabled melting at the wet solidus at temperatures of 700-750°C. The strong disruption of pre-metamorphic structures in some outcrops suggests that the maximum amount of melt in TTG gneisses was ~25 vol%. The presence of leucosomes in all rock types is taken as the principle evidence for melt formation. However, mineralogical appearance as well as major and trace element composition of many leucosomes imply that leucosomes seldom represent frozen in-situ melts. They are better considered as remnants of the melt channel network, e.g. ways on which melts escaped from the system. Part III of the thesis describes how analyses of minerals from a specific rock type (granulite) can be used to determine partition coefficients between different minerals and between minerals and melt suitable for lower crustal conditions. The trace element analyses by laser ablation-ICP-MS show coherent distribution among the principal mineral phases independent of rock composition. REE contents in amphibole are about 3 times higher than REE contents in clinopyroxene from the same sample. This consistency has to be taken into consideration in models of lower crustal melting where amphibole is replaced by clinopyroxene in the course of melting. A lack of equilibrium is observed between matrix clinopyroxene / amphibole and garnet porphyroblasts which suggests a late stage growth of garnet and slow diffusion and equilibration of the REE during metamorphism. The data provide a first set of distribution coefficients of the transition metals (Sc, V, Cr, Ni) in the lower crust. In addition, analyses of ilmenite and apatite demonstrate the strong influence of accessory phases on trace element distribution. Apatite contains high amounts of REE and Sr while ilmenite incorporates about 20-30 times higher amounts of Nb and Ta than amphibole. Furthermore, trace element mineral analyses provide evidence for magmatic processes such as melt depletion, melt segregation, accumulation and fractionation as well as metasomatism having operated in this high-grade anatectic area.

Modeling, characterization and microalgal cultivation in an airlift panel photobioreactors.

Microalgae cultures are attracting great attentions in many industrial applications. However, one of the technical challenges is to cut down the capital and operational costs of microalgae production systems, with special difficulty in reactor design and scale-up. The thesis work open with an overview on the microalgae cultures as a possible answer to solve some of the upcoming planet issues and their applications in several fields. After the work offers a general outline on the state of the art of microalgae culture systems, taking a special look to the enclosed photobioreactors (PBRs). The overall objective of this study is to advance the knowledge of PBRs design and lead to innovative large scale processes of microalgae cultivation. An airlift flat panel photobioreactor was designed, modeled and experimentally characterized. The gas holdup, liquid flow velocity and oxygen mass transfer of the reactor were experimentally determined and mathematically modeled, and the performance of the reactor was tested by cultivation of microalgae. The model predicted data correlated well with experimental data, and the high concentration of suspension cell culture could be achieved with controlled conditions. The reactor was inoculated with the algal strain Scenedesmus obliquus sp. first and with Chlorella sp. later and sparged with air. The reactor was operated in batch mode and daily monitored for pH, temperature, and biomass concentration and activity. The productivity of the novel device was determined, suggesting the proposed design can be effectively and economically used in carbon dioxide mitigation technologies and in the production of algal biomass for biofuel and other bioproducts. Those research results favored the possibility of scaling the reactor up into industrial scales based on the models employed, and the potential advantages and disadvantages were discussed for this novel industrial design.

Kinetic modeling and experiments on gas uptake and chemical transformation of organic aerosol in the atmosphere

Aerosolpartikel beeinflussen das Klima durch Streuung und Absorption von Strahlung sowie als Nukleations-Kerne für Wolkentröpfchen und Eiskristalle. Darüber hinaus haben Aerosole einen starken Einfluss auf die Luftverschmutzung und die öffentliche Gesundheit. Gas-Partikel-Wechselwirkunge sind wichtige Prozesse, weil sie die physikalischen und chemischen Eigenschaften von Aerosolen wie Toxizität, Reaktivität, Hygroskopizität und optische Eigenschaften beeinflussen. Durch einen Mangel an experimentellen Daten und universellen Modellformalismen sind jedoch die Mechanismen und die Kinetik der Gasaufnahme und der chemischen Transformation organischer Aerosolpartikel unzureichend erfasst. Sowohl die chemische Transformation als auch die negativen gesundheitlichen Auswirkungen von toxischen und allergenen Aerosolpartikeln, wie Ruß, polyzyklische aromatische Kohlenwasserstoffe (PAK) und Proteine, sind bislang nicht gut verstanden.rn Kinetische Fluss-Modelle für Aerosoloberflächen- und Partikelbulk-Chemie wurden auf Basis des Pöschl-Rudich-Ammann-Formalismus für Gas-Partikel-Wechselwirkungen entwickelt. Zunächst wurde das kinetische Doppelschicht-Oberflächenmodell K2-SURF entwickelt, welches den Abbau von PAK auf Aerosolpartikeln in Gegenwart von Ozon, Stickstoffdioxid, Wasserdampf, Hydroxyl- und Nitrat-Radikalen beschreibt. Kompetitive Adsorption und chemische Transformation der Oberfläche führen zu einer stark nicht-linearen Abhängigkeit der Ozon-Aufnahme bezüglich Gaszusammensetzung. Unter atmosphärischen Bedingungen reicht die chemische Lebensdauer von PAK von wenigen Minuten auf Ruß, über mehrere Stunden auf organischen und anorganischen Feststoffen bis hin zu Tagen auf flüssigen Partikeln. rn Anschließend wurde das kinetische Mehrschichtenmodell KM-SUB entwickelt um die chemische Transformation organischer Aerosolpartikel zu beschreiben. KM-SUB ist in der Lage, Transportprozesse und chemische Reaktionen an der Oberfläche und im Bulk von Aerosol-partikeln explizit aufzulösen. Es erforder im Gegensatz zu früheren Modellen keine vereinfachenden Annahmen über stationäre Zustände und radiale Durchmischung. In Kombination mit Literaturdaten und neuen experimentellen Ergebnissen wurde KM-SUB eingesetzt, um die Effekte von Grenzflächen- und Bulk-Transportprozessen auf die Ozonolyse und Nitrierung von Protein-Makromolekülen, Ölsäure, und verwandten organischen Ver¬bin-dungen aufzuklären. Die in dieser Studie entwickelten kinetischen Modelle sollen als Basis für die Entwicklung eines detaillierten Mechanismus für Aerosolchemie dienen sowie für das Herleiten von vereinfachten, jedoch realistischen Parametrisierungen für großskalige globale Atmosphären- und Klima-Modelle. rn Die in dieser Studie durchgeführten Experimente und Modellrechnungen liefern Beweise für die Bildung langlebiger reaktiver Sauerstoff-Intermediate (ROI) in der heterogenen Reaktion von Ozon mit Aerosolpartikeln. Die chemische Lebensdauer dieser Zwischenformen beträgt mehr als 100 s, deutlich länger als die Oberflächen-Verweilzeit von molekularem O3 (~10-9 s). Die ROIs erklären scheinbare Diskrepanzen zwischen früheren quantenmechanischen Berechnungen und kinetischen Experimenten. Sie spielen eine Schlüsselrolle in der chemischen Transformation sowie in den negativen Gesundheitseffekten von toxischen und allergenen Feinstaubkomponenten, wie Ruß, PAK und Proteine. ROIs sind vermutlich auch an der Zersetzung von Ozon auf mineralischem Staub und an der Bildung sowie am Wachstum von sekundären organischen Aerosolen beteiligt. Darüber hinaus bilden ROIs eine Verbindung zwischen atmosphärischen und biosphärischen Mehrphasenprozessen (chemische und biologische Alterung).rn Organische Verbindungen können als amorpher Feststoff oder in einem halbfesten Zustand vorliegen, der die Geschwindigkeit von heterogenen Reaktionenen und Mehrphasenprozessen in Aerosolen beeinflusst. Strömungsrohr-Experimente zeigen, dass die Ozonaufnahme und die oxidative Alterung von amorphen Proteinen durch Bulk-Diffusion kinetisch limitiert sind. Die reaktive Gasaufnahme zeigt eine deutliche Zunahme mit zunehmender Luftfeuchte, was durch eine Verringerung der Viskosität zu erklären ist, bedingt durch einen Phasenübergang der amorphen organischen Matrix von einem glasartigen zu einem halbfesten Zustand (feuchtigkeitsinduzierter Phasenübergang). Die chemische Lebensdauer reaktiver Verbindungen in organischen Partikeln kann von Sekunden bis zu Tagen ansteigen, da die Diffusionsrate in der halbfesten Phase bei niedriger Temperatur oder geringer Luftfeuchte um Größenordnungen absinken kann. Die Ergebnisse dieser Studie zeigen wie halbfeste Phasen die Auswirkung organischeer Aerosole auf Luftqualität, Gesundheit und Klima beeinflussen können. rn

Monitoring the extracellular matrix mineralization processes in biological scaffolds using bioreactors, x-ray μct technology and 3-d modeling methods (monitoraggio dei processi di mineralizzazione della matrice extracellulare in scaffolds biologici, utilizzando bioreattore, tecnologia μct a raggi x e metodi di modellizzazione 3d)

Al fine di migliorare le tecniche di coltura cellulare in vitro, sistemi a bioreattore sono sempre maggiormente utilizzati, e.g. ingegnerizzazione del tessuto osseo. Spinner Flasks, bioreattori rotanti e sistemi a perfusione di flusso sono oggi utilizzati e ogni sistema ha vantaggi e svantaggi. Questo lavoro descrive lo sviluppo di un semplice bioreattore a perfusione ed i risultati della metodologia di valutazione impiegata, basata su analisi μCT a raggi-X e tecniche di modellizzazione 3D. Un semplice bioreattore con generatore di flusso ad elica è stato progettato e costruito con l'obiettivo di migliorare la differenziazione di cellule staminali mesenchimali, provenienti da embrioni umani (HES-MP); le cellule sono state seminate su scaffold porosi di titanio che garantiscono una migliore adesione della matrice mineralizzata. Attraverso un microcontrollore e un'interfaccia grafica, il bioreattore genera tre tipi di flusso: in avanti (senso orario), indietro (senso antiorario) e una modalità a impulsi (avanti e indietro). Un semplice modello è stato realizzato per stimare la pressione generata dal flusso negli scaffolds (3•10-2 Pa). Sono stati comparati tre scaffolds in coltura statica e tre all’interno del bioreattore. Questi sono stati incubati per 21 giorni, fissati in paraformaldehyde (4% w/v) e sono stati soggetti ad acquisizione attraverso μCT a raggi-X. Le immagini ottenute sono state poi elaborate mediante un software di imaging 3D; è stato effettuato un sezionamento “virtuale” degli scaffolds, al fine di ottenere la distribuzione del gradiente dei valori di grigio di campioni estratti dalla superficie e dall’interno di essi. Tale distribuzione serve per distinguere le varie componenti presenti nelle immagini; in questo caso gli scaffolds dall’ipotetica matrice cellulare. I risultati mostrano che sia sulla superficie che internamente agli scaffolds, mantenuti nel bioreattore, è presente una maggiore densità dei gradienti dei valori di grigio ciò suggerisce un migliore deposito della matrice mineralizzata. Gli insegnamenti provenienti dalla realizzazione di questo bioreattore saranno utilizzati per progettare una nuova versione che renderà possibile l’analisi di più di 20 scaffolds contemporaneamente, permettendo un’ulteriore analisi della qualità della differenziazione usando metodologie molecolari ed istochimiche.

Tracing of 15N in a mountain spruce forest: comparison of experimental data with th TRACE model

Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

Monitoring and Modeling of the Hydraulic and Sediment Processes at In-Stream Restoration Structures in the Vicinity of a Bridge Crossing

The long-term performance of infrastructure depends on reliable and sustainable designs. Many of Pennsylvania’s streams experience sediment transport problems that increase maintenance costs and lower structural integrity of bridge crossings. A stream restoration project is one common mitigation measure used to correct such problems at bridge crossings. Specifically, in an attempt to alleviate aggradation problems with the Old Route 15 Bridge crossing on White Deer Creek, in White Deer, PA, two in-stream structures (rock cross vanes) and several bank stabilization features were installed along with a complete channel redevelopment. The objectives of this research were to characterize the hydraulic and sediment transport processes occurring at the White Deer Creek site, and to investigate, through physical and mathematical modeling, the use of instream restoration structures. The goal is to be able to use the results of this study to prevent aggradation or other sediment related problems in the vicinity of bridges through improved design considerations. Monitoring and modeling indicate that the study site on White Deer Creek is currently unstable, experiencing general channel down-cutting, bank erosion, and several local areas of increased aggradation and degradation of the channel bed. An in-stream structure installed upstream of the Old Route 15 Bridge failed by sediment burial caused by the high sediment load that White Deer Creek is transporting as well as the backwater effects caused by the bridge crossing. The in-stream structure installed downstream of the Old Route 15 Bridge is beginning to fail because of the alignment of the structure with the approach direction of flow from upstream of the restoration structure.

Bayesian Hidden Markov Modeling of Array CGH Data

Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Since the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme and breast cancer are analyzed, and comparisons are made with some widely-used algorithms to illustrate the reliability and success of the technique.

MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.