Abstract: In recent decades, as crop production has increased in many areas where irrigation projects have been implemented, the global agricultural development community has promoted irrigation investments. However, due to the disappointing performance of irrigation farming in developing countries, irrigation intervention in Africa South of the Sahara including Ethiopia is an issue of debate. Moreover, several gaps exist in the Ethiopian irrigation farming literature. For instance, evidence about the direct and indirect effects of irrigation water on agriculture is not well documented. The irrigation farming literature has not disentangled the indirect effects of having access to irrigation water from the direct effect and the indirect effects have been underrepresented. Furthermore, most previous studies have applied either a quantitative or qualitative approach and have relied only on revealed data as main type of methodology, making studies that combine qualitative and quantitative research and that use both stated and revealed data underrepresented. In this study, different approaches have been applied to investigate how irrigation water impacts Ethiopia agriculture with special attention being given to disentangling the direct and indirect effects of irrigation water on Ethiopian agriculture. Using a structural equation model, a stochastic production frontier approach, and a discrete choice experiment, I drew evidence regarding the direct and indirect effects of irrigation water on crop revenue of smallholder farmers, the technical efficiency of irrigation user farmers, and the farmers’ willingness to pay to improve poor irrigation schemes from field observations, semi-structured interviews and focus group discussions with farmers, and key informant interviews with the local agricultural agents from the Koga and Fogera Districts of Amhara Region Ethiopia. The results indicate that irrigation water in general has both direct and indirect positive effects on agriculture, and the indirect effect is mediated by both improved farm inputs and the type of crops produced. The results also show that – due to poor extension services and backward agronomic practices, the mean technical efficiency of farmers in Ethiopia is very low, and that large-scale irrigation users are less technically efficient than small-scale irrigation users. Moreover, the results show that improving irrigation schemes shifts the frontier up, and smallholder farmers are strongly willing to contribute financially to the maintenance costs of irrigation schemes. The results offer relevant lessons for policymakers that providing irrigation water supply must be embedded in a comprehensive support package including access to extension services, improved input supply, and access to stable markets.

Abstract: Most farm adaptations are reactive actions that run the risk of locking farm systems into suboptimal long-term trajectories. This is especially the case with regard to water management as water scarcity will be aggravated by climate change. This paper looks into farm irrigation choices in combination with crop choices because a proper crop choice has the potential to reduce water requirements. It proposes an extended Ricardian model to capture multiple adaptation decisions explicitly. The new simultaneous irrigation-crop farm decision model uses spatially detailed farm-level data of over 18,000 European farms on irrigation and seven different crop choices. The analysis shows that larger farmers and farmers in less water-scarce regions that use irrigation are more sensitive to temperature increases than rain-fed agriculture. This might be explained by the fact that these farmers do not experience the real cost of water scarcity because of which they take less efficient decisions.

Abstract: At or below the surface of painted works of art, valuable information is present that provides insights into an object’s past, such as the artist’s technique and the creative process that was followed or its conservation history, but also on its current state of preservation. Typically, a (very) limited set of small paint samples is taken which provide direct access to the individual paint layers. The chemical build-up of these layers can then be investigated in great detail using various microscopic analytical methods. However, in recent years a new trend towards both elemental and chemical imaging techniques has been set which are capable of visualizing the (often) heterogeneous composition of painted objects on a macroscopic scale. In this dissertation, various forms of specificity attainable with X‑ray powder diffraction (XRPD) imaging are explored: at the chemical, material and spatial level. This high specificity is illustrated throughout several applications stemming from the field of cultural heritage, both at the macroscopic (MA) and microscopic (µ) scale. As a first step, XRPD imaging was transformed to a transportable instrument that can be employed for the in situ investigation of artworks, e.g., inside museums and conservation workshops. With this unique instrument large‑scale maps (cm2 – dm2) reflecting the distribution of crystalline phases on/below the surface of flat painted artefacts can be visualized in a noninvasive manner. In this way compound-specific information was attained which can be related to original pigments or materials that have been added in a later stage and even degradation/secondary products that have formed spontaneously inside the paint layers. Additionally, with MA‑XRPD imaging it was possible to link quantitative information of pigment compositions and preferred orientation effects to the 2D compound‑specific distribution images, allowing for a further distinction between very similar artists’ materials. Furthermore, promising results for the limited depth-selectivity of this technique, obtained by exploiting the small shift in the position of the diffraction signals originating from the layered sequence of the pigments, are shown. Finally, a minute paint sample from Wheat stack under a cloudy sky by Van Gogh was investigated at a synchrotron radiation facility with tomographic µ‑XRPD imaging at the microscopic scale. The high chemical and spatial specificity of this imaging method was exploited to further elucidate the degradation pathway of the red lead pigment.

Abstract: In this study a numerical groundwater reactive transport model of a shallow groundwater aquifer contaminated with volatile organic compounds is developed. In addition to advective-dispersive transport, the model includes contaminant release from source areas, natural attenuation, abiotic degradation by a permeable reactive barrier at the site, and dilution by infiltrating rain. Aquifer heterogeneity is parameterized using pilot points for hydraulic conductivity, specific yield and groundwater recharge. A methodology is developed and applied to estimate the large number of parameters from the limited data at the field site (groundwater levels, groundwater concentrations of multiple chemical species, point-scale measurements of soil hydraulic conductivity, and lab-scale derived information on chemical and biochemical reactions). The proposed methodology relies on pilot point parameterization of hydraulic parameters and groundwater recharge, a regularization procedure to reconcile the large number of spatially distributed model parameters with the limited field data, a step-wise approach for integrating the different data sets into the model, and high performance computing. The methodology was proven to be effective in reproducing multiple contaminant plumes and in reducing the prior parameter uncertainty of hydraulic conductivity and groundwater recharge. Our results further indicate that contaminant transport predictions are strongly affected by the choice of the groundwater recharge model and flow parameters should be identified using both head and concentration measurements. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: The implementation of high-resolution mass spectrometry systems offers new possibilities for the analysis of complex art samples such as historical oil paintings. However, these multicomponent systems generate large and complex data sets that require advanced visualization tools to aid interpretation, especially when no chromatographic separation is performed. In the context of this research, it was crucial to propose a data analysis tool to identify the products generated during the synthesis, drying, and aging of historical pigments. This study reports for the first time a nontraditional mass defect analysis of oil paint samples containing a fugitive brominated-organic pigment, eosin or geranium lake, by using direct infusion electrospray ionization in combination with a high-resolution Orbitrap mass spectrometer. The use of nontraditional Kendrick mass defect plots is presented in this study as a processing and visualization tool to recognize brominated species based on their specific mass defect and isotope pattern. The results demonstrate that this approach could provide valuable molecular compositional information on the degradation pathways of this pigment. We anticipate that mass defect analysis will become highly relevant in future degradation studies of many more historical organic pigments.

Abstract: High-rate activated sludge (HRAS) systems typically generate diluted sludge which requires further thickening prior to anaerobic digestion (AD), besides the need to add considerable coagulant and flocculant for the solids separation. As an alternative to conventional gravitational settling, a dissolved air flotation (DAF) unit was coupled to a HRAS system or a high-rate contact stabilization (HiCS) system. The HRAS-DAF system allowed up to 78% removal of the influent solids, and the HiCS-DAF 67%. Both were within the range of values typically obtained for HRAS-settler systems, albeit at a lower chemical requirement. The separated sludge had a high concentration of up to 47 g COD L−1, suppressing the need of further thickening before AD. Methanation tests showed a biogas yield of up to 68% on a COD basis. The use of a DAF separation system can thus enable direct organics removal at high sludge concentration and with low chemical needs.

Abstract: Superconductivity is one of the most important discoveries of the last century. With many applications in physics, engineering, and technology, superconductors are crucial to our way of living. Several material and engineering issues however prevent their widespread usage in everyday life. Comprehensive studies are being directed at these materials and their properties to come up with new technologies that will address these challenges and enhance their superconductive capabilities. In this context, numerical modeling plays an important role in the search of new solutions to existing material and engineering issues. The time-dependent Ginzburg-Landau (TDGL) theory is a powerful predictive tool for modeling the macroscopic behavior of superconductors. However most of the numerical algorithms developed so far are incapable of describing many basic properties of real superconducting devices, and are too slow on current hardware for large-scale numerical simulations necessary for their accurate description. Therefore, the purpose of this thesis is to develop high-performing numerical solutions that can correctly describe material features to be used as modeling tools of laboratory experiments. Some important innovations introduced in this work include the numerical modeling of nonrectangular geometrical shapes with complex electrical and insulating components, the inclusion of dynamic heating of the material, and the description of different types of material inhomogeneities. These encompass the principal features necessary for a complete description of the superconductive physics in real material samples. In this thesis a numerical solution is developed for modeling superconducting thin films and used to study the superconductive properties of three experimental configurations: the dynamics of vortex matter in a Corbino disk, the motion of ultrafast vortices in an hourglass-shaped microbridge, and the photon detection process in a meander-patterned nanowire. Moreover, a numerical solution is developed for modeling three-dimensional superconductors which are studied here for the first time in the type-I superconducting regime. These numerical algorithms are optimized to exploit the computational horsepower of graphics processing units (GPUs) and multicore central-processing unit (CPU) clusters such that they can achieve high-performance and be used to model large-scale problems previously impossible on conventional machines. Several computational tools are also designed to assist with the modeling of superconducting devices. These include a numerical library of the TDGL equations, a novel mechanism for the generation of complex geometries, a closed-form solver to conduct numerical simulations, and a graphics user interface (GUI) to visualize the dynamic behavior of superconductors. The contributions in this thesis ultimately push the boundaries on what is possible in state-of-the-art numerical modeling of superconductivity.

Abstract: Microalgal biomass production is a resource-efficient answer to the exponentially increasing demand for protein, yet variability in biomass quality is largely unexplored. Nutritional value and safety were determined for Chlorella and Spirulina biomass from different producers, production batches and the same production batch. Chlorella presented a similar protein content (47 ± 8%) compared to Spirulina (48 ± 4%). However, protein quality, expressed as essential amino acid index, and digestibility were lower for Chlorella (1.1 ± 0.1 and 51 ± 9%, respectively) compared to Spirulina (1.3 ± 0.1 and 61 ± 4%, respectively). Generally, variability was lower between batches and within a batch. Heavy metals, pesticides, mycotoxins, antibiotics and nitrate did not violate regulatory limits, while polycyclic aromatic hydrocarbon levels exceeded the norm for some samples, indicating the need for continuous monitoring. This first systematic screening of commercial microalgal biomass revealed a high nutritional variability, necessitating further optimization of cultivation and post-processing conditions. Based on price and quality, Spirulina was preferred above Chlorella.

Abstract: Uncovering an efficient and stable photocatalytic system for seawater splitting is a highly desirable but challenging goal. Herein, Cd0.2Zn0.8S@Silicalite-1 (CZS@S-1) composites, in which CZS is embedded in the hierarchical zeolite S-1, were prepared and show remarkably high activity, stability and salt resistance in seawater.

Abstract: Hierarchically porous metals possess intriguing high accessibility of matter molecules and unique continuous metallic frameworks, as well as a high level of exposed active atoms. High rates of diffusion and fast energy transfer have been important and challenging goals of hierarchical design and porosity control with nanostructured metals. This review aims to summarize recent important progress toward the development of hierarchically porous metals, with special emphasis on synthetic strategies, hierarchical design in structure-function and corresponding applications. The current challenges and future prospects in this field are also discussed.