Electrodialytic remediation of CCA-treated waste wood in pilot scale

When chromated copper arsenate (CCA)-treated wood is removed from service and turns into waste, the contents of Cu, Cr and As remain high due to the strong fixation of CCA in the wood. This high content of toxic compounds presents a disposal challenge. Incineration of CCA-treated waste wood is not allowed in Denmark; instead, the wood is to be land-filled until new methods for handling the wood are available. Since the amounts of CCA-treated wood being removed from service is expected to increase in the years to come, the need for finding alternative handling methods is very relevant. In this study, the usefulness of Electrodialytic Remediation was demonstrated for handling of CCA-treated waste wood in pilot scale. The electrodialytic remediation method, which uses a low-level direct current (DC) as the cleaning agent, combines electrokinetic movement of ions in the wood matrix with the principles of electrodialysis. It has previously been shown that it is possible to remove Cu, Cr and As from CCA-treated wood using electrodialytic remediation in laboratory scale, but until now, the method had not been studied in large scale. The pilot-scale plant used in this study was designed to contain up to 2 m³ wood chips. Six remediation experiments were carried out. In these experiments, the process was up-scaled stepwise by increasing the distance between the electrodes from initially 60 cm to finally 150 cm. The remediation time was varied between 11 and 21 days, and phosphoric acid and/or oxalic acid was used to facilitate the desorption of CCA from the wood. In the most successful of the experiments carried out, the concentration of CCA in the wood was reduced by up to 82% for Cr, 88% for Cu and at least 96% for As.     

Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.     

Supervised classification of electric power transmission line nominal voltage from high-resolution aerial imagery

For many researchers, government agencies, and emergency responders, access to the geospatial data of US electric power infrastructure is invaluable for analysis, planning, and disaster recovery. Historically, however, access to high quality geospatial energy data has been limited to few agencies because of commercial licenses restrictions, and those resources which are widely accessible have been of poor quality, particularly with respect to reliability. Recent efforts to develop a highly reliable and publicly accessible alternative to the existing datasets were met with numerous challenges – not the least of which was filling the gaps in power transmission line voltage ratings. To address the line voltage rating problem, we developed and tested a basic methodology that fuses knowledge and techniques from power systems, geography, and machine learning domains. Specifically, we identified predictors of nominal voltage that could be extracted from aerial imagery and developed a tree-based classifier to classify nominal line voltage ratings. Overall, we found that line support height, support span, and conductor spacing are the best predictors of voltage ratings, and that the classifier built with these predictors had a reliable predictive accuracy (that is, within one voltage class for four out of the five classes sampled). We applied our approach to a study area in Minnesota.     

The pole of (51) Nemausa

The complex lightcurves make (51) Nemausa a good case for the study of general methods for pole determination. From six lightcurves the pole is determined to 20^h24^m; +53° (1950); the rotation is retrograde with period 7^h.782936 ± 0^h.000005. Presence of nongeometric scattering is proved by a significant 0.008 mag amplitude. Formulae and photometric elements are given for predictions of the shapes of lightcurves in future oppositions. The precision of the Fourier coefficients may be reduced below the present ±0.003 mag level by avoiding the systematic errors in the observations due to phase factor variations and discontinuities when changing comparison stars.     

Orbit determination by four observations

An elliptic orbit is determined from two short-arc pairs of observations at different oppositions by the angular momentum integral. Other methods for initial orbit determination than the classical do exist.     

High-precision stellar abundances of the elements: methods and applications

Efficient spectrographs at large telescopes have made it possible to obtain high-resolution spectra of stars with high signal-to-noise ratio and advances in model atmosphere analyses have enabled estimates of high-precision differential abundances of the elements from these spectra, i.e. with errors in the range 0.01–0.03 dex for F, G, and K stars. Methods to determine such high-precision abundances together with precise values of effective temperatures and surface gravities from equivalent widths of spectral lines or by spectrum synthesis techniques are outlined, and effects on abundance determinations from using a 3D non-LTE analysis instead of a classical 1D LTE analysis are considered. The determination of high-precision stellar abundances of the elements has led to the discovery of unexpected phenomena and relations with important bearings on the astrophysics of galaxies, stars, and planets, i.e. (i) Existence of discrete stellar populations within each of the main Galactic components (disk, halo, and bulge) providing new constraints on models for the formation of the Milky Way. (ii) Differences in the relation between abundances and elemental condensation temperature for the Sun and solar twins suggesting dust-cleansing effects in proto-planetary disks and/or engulfment of planets by stars; (iii) Differences in chemical composition between binary star components and between members of open or globular clusters showing that star- and cluster-formation processes are more complicated than previously thought; (iv) Tight relations between some abundance ratios and age for solar-like stars providing new constraints on nucleosynthesis and Galactic chemical evolution models as well as the composition of terrestrial exoplanets. We conclude that if stellar abundances with precisions of 0.01–0.03 dex can be achieved in studies of more distant stars and stars on the giant and supergiant branches, many more interesting future applications, of great relevance to stellar and galaxy evolution, are probable. Hence, in planning abundance surveys, it is important to carefully balance the need for large samples of stars against the spectral resolution and signal-to-noise ratio needed to obtain high-precision abundances. Furthermore, it is an advantage to work differentially on stars with similar atmospheric parameters, because then a simple 1D LTE analysis of stellar spectra may be sufficient. However, when determining high-precision absolute abundances or differential abundance between stars having more widely different parameters, e.g. metal-poor stars compared to the Sun or giants to dwarfs, then 3D non-LTE effects must be taken into account.     

Economic gains of liberalising access to fishing quotas within the European Union

This paper analyses the extent to which specialisation gains can be achieved by liberalising access to fishing quotas within the European Union (EU). Fishing quotas are today exchanged between EU member states at a rate of 4% of total turnover in EU fisheries. Germany, Belgium, Denmark and the Netherlands are the most active. Only one fourth of these exchanges are permanent. With the management systems in EU fisheries differing among countries, comparative advantages in fisheries exist in member states with the best management practices. Hence, although positive but small specialisation gains exist in EU fisheries today, these gains might potentially be increased by liberalising access to fishing quotas and allowing transferability of quotas between individuals from different countries on a permanent basis. Increasing the gains might, however, affect relative stability.     

Nonlinear random wave-induced drag force on a vegetation field

This paper provides a practical method by which the drag force on a vegetation field beneath nonlinear random waves can be estimated. This is achieved by using a simple drag formula together with an empirical drag coefficient given by Mendez et al. (Mendez, F.J., Losada, I.J., Losada, M.A., 1999. Hydrodynamics induced by wind waves in a vegetation field. J. Geophys. Res. 104 (C8), 18383–18396). Effects of nonlinear waves are included by using Stokes second order wave theory where the basic harmonic motion is assumed to be a stationary Gaussian narrow–band random process. An example of calculation is also presented.