| 1. |
- Gama, Fabio, 1980-
(författare)
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Managing the Collaborative Front End of Innovation in Manufacturing Firms : Requirements, Capabilities, and Conditions
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The front end of innovation is critical to innovative efforts in firms yet it remains to be poorly understood. This especially important since innovation efforts in the front end are becoming increasingly open in line with the era of open innovation. Although the literature on the front end of innovation is well developed, prior studies have largely focused on bilateral agreements and have overlooked conditions for collaborations with science-based partners (universities and research institutes). This is especially true for manufacturing firms, for which a continuous stream of new product ideas are a key source of competitiveness. To make things worse, the front end of innovation in this setting is often characterized by incongruent practices by partners, different magnitudes of fuzziness, and high risks in revealing new ideas. Developing new product definitions with different partners is thus a risky endeavor that may seriously compromise competitive advantages if mishandled. Therefore, there is a need for greater knowledge to facilitate the collaborative front end with different types of partners. Accordingly, the purpose of this dissertation is to understand how to manage the collaborative front end in manufacturing firms, with a particular focus on requirements, capabilities, and conditions.To fulfill this research purpose, data on manufacturing firms were collected through four case studies and one survey. In total, this dissertation is based on empirical data from 81 interviews with R&D members across 10 medium-sized and large manufacturing firms, as well as a survey of 146 small and medium-sized manufacturing firms. Respondents were based in Brazil or Sweden. The key theories and literatures covered in this dissertation include coordination modes, control mechanisms, organizational routines, the resource-based view, and appropriability mechanisms.This dissertation makes numerous theoretical contributions to the front-end literature. First, it extends the front-end literature by presenting the concepts of systematic idea generation and fuzziness assessment as a prerequisite for improving front-end performance. Second, this dissertation extends the front-end literature by listing the collaboration conditions that help firms cooperate with science-based partners. By collaborating with science-based partners, firms can access (unpublished) codified and tacit scientific knowledge, enabling them to rapidly build on the latest research findings. The findings suggest particular practices that can be applied to reduce cultural differences and diminish goal divergence among project members. Third, the findings in this dissertation enrich the front-end literature by describing a set of detailed practices to streamline the involvement of different types of partners using diverse protective practices. Fourth, it suggests a theoretical framework that describes how to manage the collaborative front end of innovation. The theoretical framework explains how manufacturing firms can use their organizational capabilities to develop new product ideas efficiently and safely. In particular, the framework discerns the capabilities that are necessary to explore mechanisms, practices, and routines in terms of divergent thinking, external expertise, and multiple opinions. Altogether, these contributions assist firms to better manage collaborative front end.
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| 2. |
- Akhmetkaliyeva, Raya
(författare)
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Maximal regularity of the solutions for some degenerate differential equations and their applications
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This PhD thesis deals with the study of existence and uniqueness together with coercive estimates for solutions of certain differential equations.The thesis consists of six papers (papers A, B, C, D, E and F), two appendices and an introduction, which put these papers and appendices into a more general frame and which also serves as an overview of this interesting field of mathematics.In the text below the functionsr = r(x), q = q(x), m = m(x) etc. are functions on (−∞,+∞), which are different but well defined in each paper. Paper A deals with the study of separation and approximation properties for the differential operator in the Hilbert space (here is the complex conjugate of ). A coercive estimate for the solution of the second order differential equation is obtained and its applications to spectral problems for the corresponding differential operator is demonstrated. Some sufficient conditions for the existence of the solutions of a class of nonlinear second order differential equations on the real axis are obtained.In paper B necessary and sufficient conditions for the compactness of the resolvent of the second order degenerate differential operator in is obtained. We also discuss the two-sided estimates for the radius of fredholmness of this operator.In paper C we consider the minimal closed differential operator in , where are continuously differentiable functions, and is a continuous function. In this paper we show that the operator is continuously invertible when these coefficients satisfy some suitable conditions and obtain the following estimate for : ,where is the domain of .In papers D, E, and F various differential equations of the third order of the form are studied in the space .In paper D we investigate the case when and .Moreover, in paper E the equation (0.1) is studied when . Finally, in paper F the equation (0.1) is investigated under certain additional conditions on .For these equations we establish sufficient conditions for the existence and uniqueness of the solution, and also prove an estimate of the form for the solution of equation (0.1).
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| 3. |
- Alhashimi, Anas, 1978-
(författare)
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Statistical Sensor Calibration Algorithms
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The use of sensors is ubiquitous in our IT-based society; smartphones, consumer electronics, wearable devices, healthcare systems, industries, and autonomous cars, to name but a few, rely on quantitative measurements for their operations. Measurements require sensors, but sensor readings are corrupted not only by noise but also, in almost all cases, by deviations resulting from the fact that the characteristics of the sensors typically deviate from their ideal characteristics.This thesis presents a set of methodologies to solve the problem of calibrating sensors with statistical estimation algorithms. The methods generally start with an initial statistical sensor modeling phase in which the main objective is to propose meaningful models that are capable of simultaneously explaining recorded evidence and the physical principle for the operation of the sensor. The proposed calibration methods then typically use training datasets to find point estimates of the parameters of these models and to select their structure (particularlyin terms of the model order) using suitable criteria borrowed from the system identification literature. Subsequently, the proposed methods suggest how to process the newly arriving measurements through opportune filtering algorithms that leverage the previously learned models to improve the accuracy and/or precision of the sensor readings.This thesis thus presents a set of statistical sensor models and their corresponding model learning strategies, and it specifically discusses two cases: the first case is when we have a complete training dataset (where “complete” refers to having some ground-truth informationin the training set); the second case is where the training set should be considered incomplete (i.e., not containing information that should be considered ground truth, which implies requiring other sources of information to be used for the calibration process). In doing so, we consider a set of statistical models consisting of both the case where the variance of the measurement error is fixed (i.e., homoskedastic models) and the case where the variance changes with the measured quantity (i.e., heteroskedastic models). We further analyzethe possibility of learning the models using closed-form expressions (for example, when statistically meaningful, Maximum Likelihood (ML) and Weighted Least Squares (WLS) estimation schemes) and the possibility of using numerical techniques such as Expectation Maximization (EM) or Markov chain Monte Carlo (MCMC) methods (when closed-form solutions are not available or problematic from an implementation perspective). We finally discuss the problem formulation using classical (frequentist) and Bayesian frameworks, and we present several field examples where the proposed calibration techniques are applied on sensors typically used in robotics applications (specifically, triangulation Light Detection and Rangings (Lidars) and Time of Flight (ToF) Lidars).
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| 4. |
- AlHayali, Amani
(författare)
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In vitro-solubility and supersaturation behavior of supersaturating drug delivery systems
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The development of new pharmaceutical products has been challenged by the growing number of poorly water-soluble drugs, which often lead to suboptimal bioavailability. Various approaches, such as the use of amor-phous solid dispersions and cocrystals, have been used to improve the solu-bility, and subsequent bioavailability, of these drug molecules. Supersaturat-ing drug delivery systems (SDDSs) have potential for achieving adequate oral drug bioavailability by increasing the drug solubility and creating a su-persaturated state in the gastrointestinal tract. However, there is a need for better understanding of the supersaturation behavior in SDDSs and of the factors affecting supersaturation. The main objective of this thesis was to improve understanding of the supersaturation solubility behavior in SDDSs with a particular focus on rapidly dissolving solid forms (amorphous forms/cocrystals).In the course of the work, a new formulation for ezetimibe using an amorphous solid dispersion was prepared, cocrystals of tadalafil were pre-pared, and oral films of silodosin were formulated for the first time. These new formulations were thoroughly characterized using a number of solid-state and pharmaceutical characterization techniques.The dissolution and supersaturation behavior of the prepared SDDSs were studied. The effects of various factors on the supersaturation and precipita-tion characteristics were investigated. These factors included the preparation method, the temperature of the dissolution medium, the type of dissolution biorelevant medium (gastric/intestinal) used, the permeability of the relevant gastrointestinal membranes, the addition of polymers, and the addition of surfactants. The amorphous solid dispersions, cocrystals and oral films that were prepared represent new drug formulations that provide significantly higher dissolution rates and supersaturated solubility than crystalline drug forms. Solid dispersions prepared by the melting method had better super-saturation properties than those prepared by spray drying. The precipitation kinetics of the solid dispersion were faster at 37 ̊C than at 25 ̊C in bio-relevant media. Implementation of an absorption tool during in vitro evalua-tion of supersaturation levels could improve the prediction accuracy of su-persaturation and precipitation. A better understanding of the effects of ex-cipients on the supersaturation and precipitation behavior of these types of formulation was obtained in this thesis. The improvement in supersaturation solubility obtained by adding polymers and surfactants was not proportional to the amounts of excipient used.This thesis has made notable contributions to the field of pharmaceutical science by advancing our understanding of the supersaturation solubility behavior of the newly prepared SDDSs.
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| 5. |
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| 6. |
- Antonopoulou, Io, 1989-
(författare)
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Development of biocatalytic processes for selective antioxidant production
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Feruloyl esterases (FAEs, EC 3.1.1.73) represent a subclass of carboxylic acid esterases that under normal conditions catalyze the hydrolysis of the ester bond between hydroxycinnamic acids (ferulic acid, sinapic acid, caffeic acid, p-coumaric acid) and sugar residues in plant cell walls. Based on their specificity towards monoferulates and diferulates, substitutions on the phenolic ring and on their amino acid sequence identity, they have been classified into four types (A-D) while phylogenetic analysis has resulted in classification into thirteen subfamilies (SF1-13). Under low water content, these enzymes are able to catalyze the esterification of hydroxycinnamic acids or the transesterification of their esters (donor) with alcohols or sugars (acceptor) resulting in compounds with modified lipophilicity, having a great potential for use in the tailor-made modification of natural antioxidants for cosmetic, cosmeceutical and pharmaceutical industries. The work described in this thesis focused on the selection,characterization and application of FAEs for the synthesis of bioactive esters with antioxidant activity in non-conventional media. The basis of the current classification systems was investigated in relation with the enzymes’ synthetic and hydrolytic abilities while the developed processes were evaluated for their efficiency and sustainability.Paper I was dedicated to the screening and evaluation of the synthetic abilities of 28 fungal FAEs using acceptors of different lipophilicity at fixed conditions in detergentless microemulsions. It was revealed that FAEs classified in phylogenetic subfamilies related to acetyl xylan esterases (SF5 and 6) showed increased transesterification rates and selectivity. In general, FAEs showed preference on more hydrophilic alcohol acceptors and in descending order to glycerol > 1-butanol > prenol. Homology modeling and small molecule docking simulations were employed as tools for the identification of a potential relationship between the predicted surface and active site properties of selected FAEs and the transesterification selectivity.Papers II- IV focused on the characterization of eight promising FAEs and the optimization of reaction conditions for the synthesis of two bioactive esters (prenyl ferulate and L-arabinose ferulate) in detergentless microemulsions. The effect of the medium composition, the donor and acceptor concentration, the enzyme load, the pH, the temperature and the agitation on the transesterification yield and selectivity were investigated. It was observed that the acceptor concentration and enzyme load were crucial parameters for selectivity. Fae125 (Type A, SF5) iiexhibited highest prenyl ferulate yield (81.1%) and selectivity (4.685) converting 98.5% of VFA to products after optimization at 60 mM VFA, 1.5 M prenol, 0.04 mg FAE mL-1, 40oC, 24 h, 53.4:43.4:3.2 v/v/v n-hexane: t-butanol: 100 mM MOPS-NaOH pH 8.0. On the other hand, FaeA1 (Type A, SF5) showed highest L-arabinose ferulate yield (52.2 %) and selectivity (1.120) at 80 mM VFA, 55 mM L-arabinose, 0.02 mg FAE mL-1, 50oC, 8 h, 19.8: 74.7: 5.5 v/v/v n-hexane: t-butanol: 100 mM MOPS-NaOH pH 8.0.In paper V, the effect of reaction media on the enzyme stability and transesterification yield and selectivity was studied in different solvents for the synthesis of two bioactive esters: prenyl ferulate and L-arabinose ferulate. The best performing enzyme (Fae125) was used in the optimization of reaction conditions in the best solvent (n-hexane) via response surface methodology. Both bioconversions were best described by a two-factor interaction model while optimal conditions were determined as the ones resulting in highest yield and selectivity.Highest prenyl ferulate yield (87.5%) and selectivity (7.616) were observed at 18.56 mM prenol mM-1VFA, 0.04 mg FAE mL-1, 24.5 oC, 24.5 h, 91.8: 8.2 v/v n-hexane: 100 mM sodium acetate pH 4.7. Highest L-arabinose ferulate yield (56.2%) and selectivity (1.284) were observed at 2.96 mM L-arabinose mM-1VFA, 0.02 mg FAE mL-1, 38.9 oC, 12 h, 90.5: 5.0: 4.5 v/v/v n-hexane: dimethyl sulfoxide: 100 mM sodium acetate pH 4.7. The enzyme could be reused for six consecutive reaction cycles maintaining 66.6% of its initial synthetic activity. The developed bioconversions showed exceptional biocatalyst productivities (> 300 g product g-1FAE) and the waste production was within the range of pharmaceutical processes.Paper VI focused on the investigation of the basis of the type A classification of a well-studied FAE from Aspergillus niger(AnFaeA) by comparing its activity towards methyl and arabinose hydroxycinnamic acid esters. For this purpose, L-arabinose ferulateand caffeate were synthesized enzymatically. kcat/Kmratios revealed that AnFaeA hydrolyzed arabinose ferulate 1600 times and arabinose caffeate 6.5 times more efficiently than methyl esters. This study demonstrated that short alkyl chain hydroxycinnamate esters which are used nowadays for FAE classification can lead to activity misclassification, while L-arabinose esters could potentially substitute synthetic esters in classification describing more adequately the enzyme specificitiesin the natural environment.
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| 7. |
- Babu, Bijish, Tec. Lic. 1979-
(författare)
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Mechanism-based flow stress model for Ti-6Al-4V : applicable for simulation of additive manufacturing and machining
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Ti-6Al-4V has remarkable properties such as high specific mechanical properties (viz. stiffness, strength, toughness, fatigue resistance), corrosion resistance, biocompatibility etc. These properties make it attractive for applications in aerospace, chemical industry, energy production, surgical implants, etc. Many of these applications have to satisfy high requirements on mechanical properties, which are directly affected by the microstructure. Therefore, it is essential to understand as well as to model the microstructure evolution during manufacturing as well as in-service. Furthermore, this alloy has a narrow temperature and strain rate window of workability.This work was initiated as part of a project aimed at performing finite element simulations of a manufacturing process chain involving hot forming, welding, machining, additive manufacturing and heat treatment of Ti-6Al-4V components within the aerospace industry. Manufacturing process chain simulations can compute the cumulative effect of the various processes by following the material state through the whole chain and give a realistic prediction of the final component. Capacity to describe material behavior in a wide range of temperatures and strain rates is crucial for this task.A material model based on the dominant deformation mechanisms of the alloy is assumed to have a more extensive range of validity compared to an empirical relationship. Explicit dislocation dynamics based models are not practically feasible for manufacturing process simulation, and therefore the concept of dislocation density, (length of dislocations per unit volume) developed by (Kocks1966; Bergström, 1970) is followed here. This mean field approach provides a representation of the average behavior of a large number of dislocations, grains, etc. Conrad (1981) studied the influence of various factors like solutes, interstitials, strain, strain rate, temperature, etc., on the strength and ductility of titanium systems and proposed a binary additive relationship for its yield strength. The first component relates to long-range interactions and second short-range relates to lattice resistance for dislocation motion. For high strain rate deformation, this short-range term is extended to include the effects of a viscous drag given by phonon and electron drag (Lesuer et al. 2001). Immobilisation of dislocation by pile-ups gives hardening and remobilization/annihilation by dislocation glide and climb gives restoration. Globularization is also considered to restore the material. The material model is calibrated using isothermal compression tests at a wide range of temperatures and strain rates. Compression tests performed using Gleeble thermo-mechanical simulator is used at low-strain rates and split-Hopkins pressure bar is used at high strain rates for calibration.During additive manufacturing depending on the temperature, heating/cooling rates, Ti-6Al-4V undergoes allotropic phase transformation. This transformation results in a variety of textures that can give different mechanical properties. Based on the texture (Semiatin et al., 1999b; Seetharaman and Semiatin, 2002; Thomas et al., 2005) identified few microstructural features that are relevant to the mechanical properties. The three separate alpha phase fractions; Widmanstatten, grain boundary, Martensite, and the beta-phase fraction are included in the current model. However, since the strengthening contributions of these individual alpha phases are not known, a linear rule of mixtures for the total alpha-beta composition is developed. This model is calibrated using continuous cooling tests performed by Malinov et al. 2001 with differential scanning calorimeter at varying cooling rates. This mechanism-based model is formulated in such a way that it can be implemented in any standard finite element software. In the current work, this is implemented as subroutines within MSC Marc and used for simulation of hot-forming and additive manufacturing.
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| 8. |
- Bach-Oller, Albert, 1989-
(författare)
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Alkali-enhanced gasification of biomass : laboratory-scale experimental studies
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Gasification seeks to break carbonaceous materials into synthetic gas (CO+H2) which can be subsequently upgraded into valuable products. Thus gasification can be utilized to convert low grade biomass stocks into carbon-neutral chemicals heat and power. Nonetheless, gasification produces tar and soot as a by-product, impurities which deposit on cold surfaces thereby risking operation downstream of the gasifier. Cleaning the syngas after the gasifier is a conventional way to attenuate the problem, yet a complex and expensive one. Thus, tar and soot should preferably be addressed already in the gasifier. Given that these impurities are non-equilibrium species they could be targeted by using some sort of catalytic material. Alkali elements have precisely shown to possess catalytic activity on char gasification, besides they have also been associated with a decrease in tar and soot. Yet, to design a functional alkali-catalysed gasification process we need to investigate in more detail on what exact products does alkali show an activity on, on what stage, under what circumstances and, on the measure that it is possible, the mechanism. This was investigated on the basis of experimental work that approached the topic from two opposite sides. On the one hand, we studied the effects of diluting the alkali content of a Na-rich black liquor (BL) by blending it with pyrolysis oil (PO), and on the other hand, we investigated adding various amounts of alkali on more conventional types of biomass fuels. Most of the experiments were conducted on a laminar drop tube furnace but the reactivity of BL chars was also studied through thermogravimetric analysis.Alkali was found to catalyse heterogeneous gasification reactions (e.g. char) and to lead to much lower yields of C2 hydrocarbons, heavy tars and soot, favouring the presence of lighter species over large aromatic clusters. Alkali was hypothesized to reduce the quantity of soot by inhibiting the formation and growth of PAH, key intermediates on the road to soot. Besides, it was found that the initial contact between the alkali and the organic matrix was not critical, neither for gas impurities nor regarding char conversion, suggesting that the activity of alkali was a gas-induced phenomenon. The latter implied the existence of a vaporization-condensation cycle that could supply alkali into the char. Nonetheless, the beneficial effects by alkali were impaired by the affinity of Si to capture K and form potassium silicates which are inert. This interaction effect was particularly noticeable on char conversion as the silicates are not only inert but also liquid and viscous and prompt to encapsulate the char particles, thereby limiting mass transfer.The experiments with blends of BL and PO showed that the concentration of alkali in BL could be decreased by 30% without any sign of a decrease in the catalytic activity on char gasification, thus indicating the existence a saturation threshold. Furthermore, adding PO into BL lead to a further reduction on the quantities of tar and soot, this finding was attributed to changes in the fuel composition unrelated to alkali. In any case the experiments with BL-based fuels showed lower amounts of tar and soot than those from alkali-impregnated biomass powder. The difference was partially attributed to the content of S in BL. The subsequent investigation targeting the role of S confirmed that S possessed a soot inhibiting role similar to that of alkali, yet unlike K, it did not show a catalytic effect on char gasification.
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| 9. |
- Bagheri, Azam
(författare)
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Artificial Intelligence-Based Characterization and Classification Methods for Power Quality Data Analytics
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One of the important developments in the electric power system is the fast increasing amount of data. An example of such data is formed by the voltages and currents coming from power-quality measurements. Power quality disturbances like voltage dips, harmonics and voltage transient can have a serious negative impact on the performance of equipment exposed to such disturbances. Voltage dips, short duration reductions in voltage magnitude, are especially considered as important disturbances because they regularly lead to stoppages in industrial process installations and subsequently to high costs.The overall aim of this dissertation is the development of automatic analysis methods and other methods for extracting information from large amounts of power-quality data. This includes, methods to detect and extract event characteristics from recorded data and classify the events, for instance, based on their origins or their impact on equipment. The classification facilitates further analysis steps including reasoning and interpretation. Once the data corresponding to each class is available, a proper characterization method can be used to create more semantic data useful for information extraction. The resulting information can be used to improve the performance of the whole system, e.g., updating grid-codes, or immunity requirements of sensitive installations or processes.This dissertation proposes different methods to fulfil each one of the above-mentioned steps. It proposes particularly a space-phasor model (SPM) of the three phase-to-neutral voltages as basis for analytic methods. The SPM is especially suitable as it is a time-domain transform without loss of any information. Another important contribution of the work is that most of the developed methods have been applied to a large dataset of about 6000 real-world voltage dips measured in existing HV and MV power networks.The main contributions of this dissertation are as follows:A complete framework has been proposed for automatic voltage quality analysis based on the SPM. The SPM has been used before, but this is the first time it has been used in a framework covering a range of voltage quality disturbances. A Gaussian-based anomaly detection method is used to detect and extract voltage quality disturbances. A principal component analysis (PCA) algorithm is used for event characterization. The obtained single-event characteristics are used to extract additional information like origin, fault type and location. Two deep learning-based voltage dip classifier has been developed. In both classifier a 2D convolutional neural network (2D-CNN) architecture has been employed to perform automatic feature extraction task. The soft-max activation function fulfills supervised classification method in first classifier. The second classifier uses a semi-supervised classification method based on generative-discriminative model pairs in active learning context.The same SPM was shown to enable the effective extraction of dip characteristics for multi-stage voltage dips. Applying the k-means clustering algorithm, the event is clustered into its individual stages. For each stage of the dip, a logistic regression algorithm is used to characterize that stage. The proposed method offers a new solution to the problem with transition segments that is one of the main challenges of existing methods for characterization of multi-stage dips. It is also shown in the dissertation that the SPM is an effective method for voltage transient analysis. It is possible to extract corresponding sample data and get appropriate single-event characteristics.A systematic way has been developed and applied for comparing different sets of voltage dip characteristics. With this method, both measured and synthetic voltage dips are applied to generic models of sensitive loads. The best set of characteristics is the one most accurately reproducing the behavior of equipment when exposed to measured voltage dips.The dissertation further contains a number of practical applications of the before-mentioned theoretical contributions: a proposal to an international standard-setting group; energy storage for voltage-dip ride-through of microgrids; impact of different voltage dips on wind-power installations.
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| 10. |
- Bauer, Susanne
(författare)
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Dissolved and suspended transport of tungsten, molybdenum, and vanadium in natural waters
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Some transition metals and metalloids occur primarily as oxyanions in natural waters including antimony, arsenic, chromium, molybdenum, tungsten and vanadium. These oxyanions can pass through cell walls along the same pathways as phosphate or sulfate. Some of these oxyanions are essential for life, but in high concentrations they become all toxic. Recent studies showed that tungsten probably is posing a risk to human health. The growing use of tungsten in industrial and military applications probably leads to an increased release of tungsten to the environment. It has also been shown that the use of studded winter tires in Sweden significantly increases tungsten concentrations in road runoff. Still, little is known about the geochemical cycling of tungsten in the environment as it has been considered to be a more or less inert element. Only a few studies deal with tungsten in natural waters. For example, for the Baltic Sea no concentration data have been published before this work and data on the suspended particulate fraction of tungsten in terrestrial and marine waters are scarce.This thesis contributes to the understanding of the distribution and behavior of tungsten, molybdenum and vanadium in natural waters under changing redox conditions, varying pH and different seasons. Particular attention is paid to the suspended particulate fraction of these elements, which is often neglected even though it can be of great importance. Tungsten, molybdenum and vanadium primarily occur as oxyanions in solution and can be adsorbed to particles, which determines their mobility.Molybdenum usually is very mobile, while vanadium has a tendency to adsorb to iron oxyhydroxides or to form organic complexes. Tungsten has many similarities with molybdenum, but it seems to be less mobile than molybdenum in natural waters.Tungsten and molybdenum have a similar abundance in the upper continental crust, but in the ocean molybdenum is almost 2000 times more abundant. A strong fractionation of these two elements occurs from land to the ocean, indicating a removal of W during mixing of river and seawater.This study comprises data from small streams in the boreal landscape of northern Sweden, major rivers (Kalix River and Råne River) and their estuaries discharging into the Baltic Sea. In the marine environment, sediment cores from the Bothnian Bay and water profiles at the stratified Landsort Deep have been studied. Apart from the spatial distribution, the temporal behavior of tungsten, molybdenum, and vanadium in was investigated. In the boreal environment snowmelt is playing a major role for their transport.All water samples were filtered through 0.22 pore size filters to define dissolved and suspended particulate fractions. The particulate fraction of all studied elements increases from streams to rivers. Especially during spring flood, particle transport becomes even more important. About 80% tungsten, 70% vanadium and 30% molybdenum occur in the particulate fraction during this event. During estuarine mixing, tungsten and molybdenum are released from the particles again. However, vanadium seems to be removed in both fractions, probably due to a different adsorption behavior. In the dissolved fraction molybdenum increased and vanadium decreased from land to the sea, while tungsten showed small variation in all surface waters.All three elements are affected by manganese redox cycling at the transition zone between oxic and sulfidic water at the Landsort Deep in the Baltic Sea. Adsorption of these oxyanions to the freshly formed manganese oxides plays an important role for their transport to the sulfidic zone. In contrast to molybdenum, dissolved tungsten is accumulated in the sulfidic environment. There is no effective removal mechanisms like for molybdenum, which is adsorbed to sulfides. Also in the sediment, redox cycling of manganese and iron affects the distribution of tungsten and molybdenum close to the water-sediment interface.
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