Interactions between the hydrological cycle and atmospheric chemistry

The land-atmosphere exchange of atmospheric trace gases is sensitive to meteorological conditions and climate change. It contributes in turn to the atmospheric radiative forcing through its effects on tropospheric chemistry. The interactions between the hydrological cycle and atmospheric processes are intricate and often involve different levels of feedbacks. The Earth system model EMAC is used in this thesis to assess the direct role of the land surface components of the terrestrial hydrological cycle in the emissions, deposition and transport of key trace gases that control tropospheric chemistry. It is also used to examine its indirect role in changing the tropospheric chemical composition through the feedbacks between the atmospheric and the terrestrial branches of the hydrological cycle. Selected features of the hydrological cycle in EMAC are evaluated using observations from different data sources. The interactions between precipitation and the water vapor column, from the atmospheric branch of the hydrological cycle, and evapotranspiration, from its terrestrial branch, are assessed specially for tropical regions. The impacts of changes in the land surface hydrology on surface exchanges and the oxidizing chemistry of the atmosphere are assessed through two sensitivity simulations. In the first, a new parametrization for rainfall interception in the densely vegetated areas in the tropics is implemented, and its effects are assessed. The second study involves the application of a soil moisture forcing that replaces the model calculated soil moisture. Both experiments have a large impact on the local hydrological cycle, dry deposition of soluble and insoluble gases, emissions of isoprene through changes in surface temperature and the Planetary Boundary Layer height. Additionally the soil moisture forcing causes changes in local vertical transport and large-scale circulation. The changes in trace gas exchanges affect the oxidation capacity of the atmosphere through changes in OH, O$_3$, NO$_x$ concentrations.

Aspetti di sostenibilità in agricoltura a diverse scale spaziali e temporali. Valutazioni ambientali, economiche ed energetiche.

La Tesi analizza le relazioni tra i processi di sviluppo agricolo e l’uso delle risorse naturali, in particolare di quelle energetiche, a livello internazionale (paesi in via di sviluppo e sviluppati), nazionale (Italia), regionale (Emilia Romagna) e aziendale, con lo scopo di valutare l’eco-efficienza dei processi di sviluppo agricolo, la sua evoluzione nel tempo e le principali dinamiche in relazione anche ai problemi di dipendenza dalle risorse fossili, della sicurezza alimentare, della sostituzione tra superfici agricole dedicate all’alimentazione umana ed animale. Per i due casi studio a livello macroeconomico è stata adottata la metodologia denominata “SUMMA” SUstainability Multi-method, multi-scale Assessment (Ulgiati et al., 2006), che integra una serie di categorie d’impatto dell’analisi del ciclo di vita, LCA, valutazioni costi-benefici e la prospettiva di analisi globale della contabilità emergetica. L’analisi su larga scala è stata ulteriormente arricchita da un caso studio sulla scala locale, di una fattoria produttrice di latte e di energia elettrica rinnovabile (fotovoltaico e biogas). Lo studio condotto mediante LCA e valutazione contingente ha valutato gli effetti ambientali, economici e sociali di scenari di riduzione della dipendenza dalle fonti fossili. I casi studio a livello macroeconomico dimostrano che, nonostante le politiche di supporto all’aumento di efficienza e a forme di produzione “verdi”, l’agricoltura a livello globale continua ad evolvere con un aumento della sua dipendenza dalle fonti energetiche fossili. I primi effetti delle politiche agricole comunitarie verso una maggiore sostenibilità sembrano tuttavia intravedersi per i Paesi Europei. Nel complesso la energy footprint si mantiene alta poiché la meccanizzazione continua dei processi agricoli deve necessariamente attingere da fonti energetiche sostitutive al lavoro umano. Le terre agricole diminuiscono nei paesi europei analizzati e in Italia aumentando i rischi d’insicurezza alimentare giacché la popolazione nazionale sta invece aumentando.

Measurement and modeling of cloud condensation nuclei in continental air

Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate. Knowledge of the spatial and temporal distribution of CCN in the atmosphere is essential to understand and describe the effects of aerosols in meteorological models. In this study, CCN properties were measured in polluted and pristine air of different continental regions, and the results were parameterized for efficient prediction of CCN concentrations.The continuous-flow CCN counter used for size-resolved measurements of CCN efficiency spectra (activation curves) was calibrated with ammonium sulfate and sodium chloride aerosols for a wide range of water vapor supersaturations (S=0.068% to 1.27%). A comprehensive uncertainty analysis showed that the instrument calibration depends strongly on the applied particle generation techniques, Köhler model calculations, and water activity parameterizations (relative deviations in S up to 25%). Laboratory experiments and a comparison with other CCN instruments confirmed the high accuracy and precision of the calibration and measurement procedures developed and applied in this study.The mean CCN number concentrations (NCCN,S) observed in polluted mega-city air and biomass burning smoke (Beijing and Pearl River Delta, China) ranged from 1000 cm−3 at S=0.068% to 16 000 cm−3 at S=1.27%, which is about two orders of magnitude higher than in pristine air at remote continental sites (Swiss Alps, Amazonian rainforest). Effective average hygroscopicity parameters, κ, describing the influence of chemical composition on the CCN activity of aerosol particles were derived from the measurement data. They varied in the range of 0.3±0.2, were size-dependent, and could be parameterized as a function of organic and inorganic aerosol mass fraction. At low S (≤0.27%), substantial portions of externally mixed CCN-inactive particles with much lower hygroscopicity were observed in polluted air (fresh soot particles with κ≈0.01). Thus, the aerosol particle mixing state needs to be known for highly accurate predictions of NCCN,S. Nevertheless, the observed CCN number concentrations could be efficiently approximated using measured aerosol particle number size distributions and a simple κ-Köhler model with a single proxy for the effective average particle hygroscopicity. The relative deviations between observations and model predictions were on average less than 20% when a constant average value of κ=0.3 was used in conjunction with variable size distribution data. With a constant average size distribution, however, the deviations increased up to 100% and more. The measurement and model results demonstrate that the aerosol particle number and size are the major predictors for the variability of the CCN concentration in continental boundary layer air, followed by particle composition and hygroscopicity as relatively minor modulators. Depending on the required and applicable level of detail, the measurement results and parameterizations presented in this study can be directly implemented in detailed process models as well as in large-scale atmospheric and climate models for efficient description of the CCN activity of atmospheric aerosols.

Early Warning For Large Earthquakes: Observations, Models and Real-Time Data Analysis

This thesis is a collection of works focused on the topic of Earthquake Early Warning, with a special attention to large magnitude events. The topic is addressed from different points of view and the structure of the thesis reflects the variety of the aspects which have been analyzed. The first part is dedicated to the giant, 2011 Tohoku-Oki earthquake. The main features of the rupture process are first discussed. The earthquake is then used as a case study to test the feasibility Early Warning methodologies for very large events. Limitations of the standard approaches for large events arise in this chapter. The difficulties are related to the real-time magnitude estimate from the first few seconds of recorded signal. An evolutionary strategy for the real-time magnitude estimate is proposed and applied to the single Tohoku-Oki earthquake. In the second part of the thesis a larger number of earthquakes is analyzed, including small, moderate and large events. Starting from the measurement of two Early Warning parameters, the behavior of small and large earthquakes in the initial portion of recorded signals is investigated. The aim is to understand whether small and large earthquakes can be distinguished from the initial stage of their rupture process. A physical model and a plausible interpretation to justify the observations are proposed. The third part of the thesis is focused on practical, real-time approaches for the rapid identification of the potentially damaged zone during a seismic event. Two different approaches for the rapid prediction of the damage area are proposed and tested. The first one is a threshold-based method which uses traditional seismic data. Then an innovative approach using continuous, GPS data is explored. Both strategies improve the prediction of large scale effects of strong earthquakes.

Techniques for Lagrangian modelling of dispersion in geophysical flows

Basic concepts and definitions relative to Lagrangian Particle Dispersion Models (LPDMs)for the description of turbulent dispersion are introduced. The study focusses on LPDMs that use as input, for the large scale motion, fields produced by Eulerian models, with the small scale motions described by Lagrangian Stochastic Models (LSMs). The data of two different dynamical model have been used: a Large Eddy Simulation (LES) and a General Circulation Model (GCM). After reviewing the small scale closure adopted by the Eulerian model, the development and implementation of appropriate LSMs is outlined. The basic requirement of every LPDM used in this work is its fullfillment of the Well Mixed Condition (WMC). For the dispersion description in the GCM domain, a stochastic model of Markov order 0, consistent with the eddy-viscosity closure of the dynamical model, is implemented. A LSM of Markov order 1, more suitable for shorter timescales, has been implemented for the description of the unresolved motion of the LES fields. Different assumptions on the small scale correlation time are made. Tests of the LSM on GCM fields suggest that the use of an interpolation algorithm able to maintain an analytical consistency between the diffusion coefficient and its derivative is mandatory if the model has to satisfy the WMC. Also a dynamical time step selection scheme based on the diffusion coefficient shape is introduced, and the criteria for the integration step selection are discussed. Absolute and relative dispersion experiments are made with various unresolved motion settings for the LSM on LES data, and the results are compared with laboratory data. The study shows that the unresolved turbulence parameterization has a negligible influence on the absolute dispersion, while it affects the contribution of the relative dispersion and meandering to absolute dispersion, as well as the Lagrangian correlation.

Constraints on neutrino mass fraction using Redshift Space Distortions

Redshift Space Distortions (RSD) are an apparent anisotropy in the distribution of galaxies due to their peculiar motion. These features are imprinted in the correlation function of galaxies, which describes how these structures distribute around each other. RSD can be represented by a distortions parameter $\beta$, which is strictly related to the growth of cosmic structures. For this reason, measurements of RSD can be exploited to give constraints on the cosmological parameters, such us for example the neutrino mass. Neutrinos are neutral subatomic particles that come with three flavours, the electron, the muon and the tau neutrino. Their mass differences can be measured in the oscillation experiments. Information on the absolute scale of neutrino mass can come from cosmology, since neutrinos leave a characteristic imprint on the large scale structure of the universe. The aim of this thesis is to provide constraints on the accuracy with which neutrino mass can be estimated when expoiting measurements of RSD. In particular we want to describe how the error on the neutrino mass estimate depends on three fundamental parameters of a galaxy redshift survey: the density of the catalogue, the bias of the sample considered and the volume observed. In doing this we make use of the BASICC Simulation from which we extract a series of dark matter halo catalogues, characterized by different value of bias, density and volume. This mock data are analysed via a Markov Chain Monte Carlo procedure, in order to estimate the neutrino mass fraction, using the software package CosmoMC, which has been conveniently modified. In this way we are able to extract a fitting formula describing our measurements, which can be used to forecast the precision reachable in future surveys like Euclid, using this kind of observations.

Dynamic development of hydrofractures

Natürliche hydraulische Bruchbildung ist in allen Bereichen der Erdkruste ein wichtiger und stark verbreiteter Prozess. Sie beeinflusst die effektive Permeabilität und Fluidtransport auf mehreren Größenordnungen, indem sie hydraulische Konnektivität bewirkt. Der Prozess der Bruchbildung ist sowohl sehr dynamisch als auch hoch komplex. Die Dynamik stammt von der starken Wechselwirkung tektonischer und hydraulischer Prozesse, während sich die Komplexität aus der potentiellen Abhängigkeit der poroelastischen Eigenschaften von Fluiddruck und Bruchbildung ergibt. Die Bildung hydraulischer Brüche besteht aus drei Phasen: 1) Nukleation, 2) zeitabhängiges quasi-statisches Wachstum so lange der Fluiddruck die Zugfestigkeit des Gesteins übersteigt, und 3) in heterogenen Gesteinen der Einfluss von Lagen unterschiedlicher mechanischer oder sedimentärer Eigenschaften auf die Bruchausbreitung. Auch die mechanische Heterogenität, die durch präexistierende Brüche und Gesteinsdeformation erzeugt wird, hat großen Einfluß auf den Wachstumsverlauf. Die Richtung der Bruchausbreitung wird entweder durch die Verbindung von Diskontinuitäten mit geringer Zugfestigkeit im Bereich vor der Bruchfront bestimmt, oder die Bruchausbreitung kann enden, wenn der Bruch auf Diskontinuitäten mit hoher Festigkeit trifft. Durch diese Wechselwirkungen entsteht ein Kluftnetzwerk mit komplexer Geometrie, das die lokale Deformationsgeschichte und die Dynamik der unterliegenden physikalischen Prozesse reflektiert. rnrnNatürliche hydraulische Bruchbildung hat wesentliche Implikationen für akademische und kommerzielle Fragestellungen in verschiedenen Feldern der Geowissenschaften. Seit den 50er Jahren wird hydraulisches Fracturing eingesetzt, um die Permeabilität von Gas und Öllagerstätten zu erhöhen. Geländebeobachtungen, Isotopenstudien, Laborexperimente und numerische Analysen bestätigen die entscheidende Rolle des Fluiddruckgefälles in Verbindung mit poroelastischen Effekten für den lokalen Spannungszustand und für die Bedingungen, unter denen sich hydraulische Brüche bilden und ausbreiten. Die meisten numerischen hydromechanischen Modelle nehmen für die Kopplung zwischen Fluid und propagierenden Brüchen vordefinierte Bruchgeometrien mit konstantem Fluiddruck an, um das Problem rechnerisch eingrenzen zu können. Da natürliche Gesteine kaum so einfach strukturiert sind, sind diese Modelle generell nicht sonderlich effektiv in der Analyse dieses komplexen Prozesses. Insbesondere unterschätzen sie die Rückkopplung von poroelastischen Effekten und gekoppelte Fluid-Festgestein Prozesse, d.h. die Entwicklung des Porendrucks in Abhängigkeit vom Gesteinsversagen und umgekehrt.rnrnIn dieser Arbeit wird ein zweidimensionales gekoppeltes poro-elasto-plastisches Computer-Model für die qualitative und zum Teil auch quantitativ Analyse der Rolle lokalisierter oder homogen verteilter Fluiddrücke auf die dynamische Ausbreitung von hydraulischen Brüchen und die zeitgleiche Evolution der effektiven Permeabilität entwickelt. Das Programm ist rechnerisch effizient, indem es die Fluiddynamik mittels einer Druckdiffusions-Gleichung nach Darcy ohne redundante Komponenten beschreibt. Es berücksichtigt auch die Biot-Kompressibilität poröser Gesteine, die implementiert wurde um die Kontrollparameter in der Mechanik hydraulischer Bruchbildung in verschiedenen geologischen Szenarien mit homogenen und heterogenen Sedimentären Abfolgen zu bestimmen. Als Resultat ergibt sich, dass der Fluiddruck-Gradient in geschlossenen Systemen lokal zu Störungen des homogenen Spannungsfeldes führen. Abhängig von den Randbedingungen können sich diese Störungen eine Neuausrichtung der Bruchausbreitung zur Folge haben kann. Durch den Effekt auf den lokalen Spannungszustand können hohe Druckgradienten auch schichtparallele Bruchbildung oder Schlupf in nicht-entwässerten heterogenen Medien erzeugen. Ein Beispiel von besonderer Bedeutung ist die Evolution von Akkretionskeilen, wo die große Dynamik der tektonischen Aktivität zusammen mit extremen Porendrücken lokal starke Störungen des Spannungsfeldes erzeugt, die eine hoch-komplexe strukturelle Entwicklung inklusive vertikaler und horizontaler hydraulischer Bruch-Netzwerke bewirkt. Die Transport-Eigenschaften der Gesteine werden stark durch die Dynamik in der Entwicklung lokaler Permeabilitäten durch Dehnungsbrüche und Störungen bestimmt. Möglicherweise besteht ein enger Zusammenhang zwischen der Bildung von Grabenstrukturen und großmaßstäblicher Fluid-Migration. rnrnDie Konsistenz zwischen den Resultaten der Simulationen und vorhergehender experimenteller Untersuchungen deutet darauf hin, dass das beschriebene numerische Verfahren zur qualitativen Analyse hydraulischer Brüche gut geeignet ist. Das Schema hat auch Nachteile wenn es um die quantitative Analyse des Fluidflusses durch induzierte Bruchflächen in deformierten Gesteinen geht. Es empfiehlt sich zudem, das vorgestellte numerische Schema um die Kopplung mit thermo-chemischen Prozessen zu erweitern, um dynamische Probleme im Zusammenhang mit dem Wachstum von Kluftfüllungen in hydraulischen Brüchen zu untersuchen.

Imaging and modeling of pore scale processes in porous media using X-ray computed tomography and lattice Boltzmann solver

In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.

Comparative study of the different models for the calculation of BLEVEs overpressure effects

The BLEVE, acronym for Boiling Liquid Expanding Vapour Explosion, is one of the most dangerous accidents that can occur in pressure vessels. It can be defined as an explosion resulting from the failure of a vessel containing a pressure liquefied gas stored at a temperature significantly above its boiling point at atmospheric pressure. This phenomenon frequently appears when a vessel is engulfed by a fire: the heat causes the internal pressure to raise and the mechanical proprieties of the wall to decrease, with the consequent rupture of the tank and the instantaneous release of its whole content. After the breakage, the vapour outflows and expands and the liquid phase starts boiling due to the pressure drop. The formation and propagation of a distructive schock wave may occur, together with the ejection of fragments, the generation of a fireball if the stored fluid is flammable and immediately ignited or the atmospheric dispersion of a toxic cloud if the fluid contained inside the vessel is toxic. Despite the presence of many studies on the BLEVE mechanism, the exact causes and conditions of its occurrence are still elusive. In order to better understand this phenomenon, in the present study first of all the concept and definition of BLEVE are investigated. A historical analysis of the major events that have occurred over the past 60 years is described. A research of the principal causes of this event, including the analysis of the substances most frequently involved, is presented too. Afterwards a description of the main effects of BLEVEs is reported, focusing especially on the overpressure. Though the major aim of the present thesis is to contribute, with a comparative analysis, to the validation of the main models present in the literature for the calculation and prediction of the overpressure caused by BLEVEs. In line with this purpose, after a short overview of the available approaches, their ability to reproduce the trend of the overpressure is investigated. The overpressure calculated with the different models is compared with values deriving from events happened in the past and ad-hoc experiments, focusing the attention especially on medium and large scale phenomena. The ability of the models to consider different filling levels of the reservoir and different substances is analyzed too. The results of these calculations are extensively discussed. Finally some conclusive remarks are reported.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Sensitivity of pelagic calcification to ocean acidification

Ocean acidification might reduce the ability of calcifying plankton to produce and maintain their shells of calcite, or of aragonite, the more soluble form of CaCO3. In addition to possibly large biological impacts, reduced CaCO3 production corresponds to a negative feedback on atmospheric CO2. In order to explore the sensitivity of the ocean carbon cycle to increasing concentrations of atmospheric CO2, we use the new biogeochemical Bern3D/PISCES model. The model reproduces the large scale distributions of biogeochemical tracers. With a range of sensitivity studies, we explore the effect of (i) using different parameterizations of CaCO3 production fitted to available laboratory and field experiments, of (ii) letting calcite and aragonite be produced by auto- and heterotrophic plankton groups, and of (iii) using carbon emissions from the range of the most recent IPCC Representative Concentration Pathways (RCP). Under a high-emission scenario, the CaCO3 production of all the model versions decreases from ~1 Pg C yr−1 to between 0.36 and 0.82 Pg C yr−1 by the year 2100. The changes in CaCO3 production and dissolution resulting from ocean acidification provide only a small feedback on atmospheric CO2 of −1 to −11 ppm by the year 2100, despite the wide range of parameterizations, model versions and scenarios included in our study. A potential upper limit of the CO2-calcification/dissolution feedback of −30 ppm by the year 2100 is computed by setting calcification to zero after 2000 in a high 21st century emission scenario. The similarity of feedback estimates yielded by the model version with calcite produced by nanophytoplankton and the one with calcite, respectively aragonite produced by mesozooplankton suggests that expending biogeochemical models to calcifying zooplankton might not be needed to simulate biogeochemical impacts on the marine carbonate cycle. The changes in saturation state confirm previous studies indicating that future anthropogenic CO2 emissions may lead to irreversible changes in ΩA for several centuries. Furthermore, due to the long-term changes in the deep ocean, the ratio of open water CaCO3 dissolution to production stabilizes by the year 2500 at a value that is 30–50% higher than at pre-industrial times when carbon emissions are set to zero after 2100.

Sensitivity of Nd isotopic composition in seawater to changes in Nd sources and paleoceanographic implications

It has been argued that past changes in the sources of Nd could hamper the use of the Nd isotopic composition (ϵNd) as a proxy for past changes in the overturning of deep water masses. Here we reconsider uncertainties associated with ϵNd in seawater due to potential regional to global scale changes in the sources of Nd by applying a modeling approach. For illustrative purposes we describe rather extreme changes in the magnitude of source fluxes, their isotopic composition or both. We find that the largest effects on ϵNd result from changes in the boundary source. Considerable changes also result from variations in the magnitude or ϵNd of dust and rivers but are largely constrained to depths shallower than 1 km, except if they occur in or upstream of regions where deep water masses are formed. From these results we conclude that changes in Nd sources have the potential to affect ϵNd. However, substantial changes are required to generate large-scale changes inϵNd in deep water that are similar in magnitude to those that have been reconstructed from sediment cores or result from changes in meridional overturning circulation in model experiments. Hence, it appears that a shift in ϵNdcomparable to glacial-interglacial variations is difficult to obtain by changes in Nd sources alone, but that more subtle variations can be caused by such changes and must be interpreted with caution.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Chemotherapeutic strategies against Trypanosoma brucei: drug targets vs. drug targeting

Trypanosoma brucei rhodesiense and T. b. gambiense are the causative agents of sleeping sickness, a fatal disease that affects 36 countries in sub-Saharan Africa. Nevertheless, only a handful of clinically useful drugs are available. These drugs suffer from severe side-effects. The situation is further aggravated by the alarming incidence of treatment failures in several sleeping sickness foci, apparently indicating the occurrence of drug-resistant trypanosomes. Because of these reasons, and since vaccination does not appear to be feasible due to the trypanosomes' ever changing coat of variable surface glycoproteins (VSGs), new drugs are needed urgently. The entry of Trypanosoma brucei into the post-genomic age raises hopes for the identification of novel kinds of drug targets and in turn new treatments for sleeping sickness. The pragmatic definition of a drug target is, a protein that is essential for the parasite and does not have homologues in the host. Such proteins are identified by comparing the predicted proteomes of T. brucei and Homo sapiens, then validated by large-scale gene disruption or gene silencing experiments in trypanosomes. Once all proteins that are essential and unique to the parasite are identified, inhibitors may be found by high-throughput screening. However powerful, this functional genomics approach is going to miss a number of attractive targets. Several current, successful parasiticides attack proteins that have close homologues in the human proteome. Drugs like DFMO or pyrimethamine inhibit parasite and host enzymes alike--a therapeutic window is opened only by subtle differences in the regulation of the targets, which cannot be recognized in silico. Working against the post-genomic approach is also the fact that essential proteins tend to be more highly conserved between species than non-essential ones. Here we advocate drug targeting, i.e. uptake or activation of a drug via parasite-specific pathways, as a chemotherapeutic strategy to selectively inhibit enzymes that have equally sensitive counterparts in the host. The T. brucei purine salvage machinery offers opportunities for both metabolic and transport-based targeting: unusual nucleoside and nucleobase permeases may be exploited for selective import, salvage enzymes for selective activation of purine antimetabolites.

Graphite exfoliation by supercritical carbon dioxide extraction

Supercritical carbon dioxide is used to exfoliate graphite, producing a small, several-layer graphitic flake. The supercritical conditions of 2000, 2500, and 3000 psi and temperatures of 40°, 50°, and 60°C, have been used to study the effect of critical density on the sizes and zeta potentials of the treated flakes. Photon Correlation Spectroscopy (PCS), Brunauer-Emmett-Teller (BET) surface area measurement, field emission scanning electron microscopy (FE-SEM), and atomic force microscopy (AFM) are used to observe the features of the flakes. N-methyl-2-pyrrolidinone (NMP), dimethylformamide (DMF), and isopropanol are used as co-solvents to enhance the supercritical carbon dioxide treatment. As a result, the PCS results show that the flakes obtained from high critical density treatment (low temperature and high pressure) are more stable due to more negative charges of zeta potential, but have smaller sizes than those from low critical density (high temperature and low pressure). However, when an additional 1-hour sonication is applied, the size of the flakes from low critical density treatment becomes smaller than those from high critical density treatment. This is probably due to more CO2 molecules stacked between the layers of the graphitic flakes. The zeta potentials of the sonicated samples were slightly more negative than nonsonicated samples. NMP and DMF co-solvents maintain stability and prevented reaggregation of the flakes better than isopropanol. The flakes tend to be larger and more stable as the treatment time increases since larger flat area of graphite is exfoliated. In these experiments, the temperature has more impact on the flakes than pressure. The BET surface area resultsshow that CO2 penetrates the graphite layers more than N2. Moreover, the negative surface area of the treated graphite indicates that the CO2 molecules may be adsorbed between the graphite layers during supercritical treatment. The FE-SEM and AFM images show that the flakes have various shapes and sizes. The effects of surfactants can be observed on the FE-SEM images of the samples in one percent by weight solution of SDBS in water since the sodium dodecylbenzene sulfonate (SDBS) residue covers all of the remaining flakes. The AFM images show that the vertical thickness of the graphitic flakes can ranges from several nanometers (less than ten layers thick), to more than a hundred nanometers. In conclusion, supercritical carbon dioxide treatment is a promising step compared to mechanical and chemical exfoliation techniques in the large scale production of thin graphitic flake, breaking down the graphite flakes into flakes only a fewer graphene layers thick.