Kinetic and equilibrium studies of copper-dissolved organic matter complexation in water column of the stratified Krka River estuary (Croatia)

An interaction of dissolved natural organic matter (DNOM) with copper ions in the water column of the stratified Krka River estuary (Croatia) was studied. The experimental methodology was based on the differential pulse anodic stripping voltammetric (DPASV) determination of labile copper species by titrating the sample using increments of copper additions uniformly distributed on the logarithmic scale. A classical at-equilibrium approach (determination of copper complexing capacity, CuCC) and a kinetic approach (tracing of equilibrium reconstitution) of copper complexation were considered and compared. A model of discrete distribution of organic ligands forming inert copper complexes was applied. For both approaches, a home-written fitting program was used for the determination of apparent stability constants (K_i^equ), total ligands concentration (L_iT) and association/dissociation rate constants (k_i¹,k_i^- 1).A non-conservative behaviour of dissolved organic matter (DOC) and total copper concentration in a water column was registered. An enhanced biological activity at the freshwater–seawater interface (FSI) triggered an increase of total copper concentration and total ligand concentration in this water layer. The copper complexation in fresh water of Krka River was characterised by one type of binding ligands, while in most of the estuarine and marine samples two classes of ligands were identified. The distribution of apparent stability constants (log K₁^equ: 11.2–13.0, log K₂^equ:8.8–10.0) showed increasing trend towards higher salinities, indicating stronger copper complexation by autochthonous seawater organic matter.Copper complexation parameters (ligand concentrations and apparent stability constants) obtained by at-equilibrium model are in very good accordance with those of kinetic model. Calculated association rate constants (k₁¹:6.1–20 × 10³ (M s)^− 1, k₂¹: 1.3–6.3 × 10³ (M s)^− 1) indicate that copper complexation by DNOM takes place relatively slowly. The time needed to achieve a new pseudo-equilibrium induced by an increase of copper concentration (which is common for Krka River estuary during summer period due to the nautical traffic), is estimated to be from 2 to 4 h.It is found that in such oligotrophic environment (dissolved organic carbon content under 83 µM_C, i.e. 1 mg_CL^− 1) an increase of the total copper concentration above 12 nM could enhance a free copper concentration exceeding the level considered as potentially toxic for microorganisms (10 pM).     

Spread-F during the magnetic storm of 22 January 2004 at low latitudes: Effect of IMF-Bz in relation to local sunset time

The paper describes the results of spread-F at low latitude stations around the world during the magnetic storm starting at 0130 UT on 22 January 2004. The storm can be divided into two phases, first phase up to 1000 UT when interplanetary magnetic field IMF-Bz was highly fluctuating around a small positive value and the second phase after a sudden large southward turning of IMF-Bz at 1030 UT. The first phase produced strong spread-F at Jicamarca, Sao Luis, and Ascension Island and caused complete inhibition of spread-F at Thumba and Waltair in India. It generated weak spread-F at Ho Chi Minh City in Vietnam and strong spread-F at Hainan and Chung Li. The strong spread-F at Hainan and Chung Li were caused by the positive IMF-Bz during the first phase of the storm and not by the negative pulse of IMF-Bz at 1000 UT.     

Additional Analytical Data for Gabbro, GOG-1

Additional data for gabbro, GOG-1, were determined by instrumental-neutron-activation analysis, atomic-absorption spectrometry, and semi-quantitative spectrographic analysis. F ratios calculated in the analysis of variance for 26 sets of data for elements determined by the three methods were not significant, and hence the elements are distributed homogeneously among the bottles. The agreement between our data and the averages previously published ranges from very good to poor. More analytical data are necessary to establish reliable estimates of the concentrations of elements in GOG-1 and in two other gabbros so that three gabbros may be available to geochemists for use as standards.     

Cosmic ray ionization of the Jovian atmosphere

An approximate form of the Boltzmann equation has been used to obtain local ionization rates due to the absorption of galactic cosmic rays in the Jovian atmosphere. It is shown that the muon flux component of the cosmic ray-induced cascade may be especially importannt in ionizing the atmosphere at levels where the total number density exceeds 10¹⁹ cm^?3 (well below the ionospheric layers produced by solar euv). A model containing both positive and negative ion reactions has been employed to compute equilibrium electron and ion number densities. Peak electron number densities on the order of 10³ cm^?3 may be expected even at relatively low magnetic latitudes. The dominant positive ions are NH₄⁺ and C_nH_m⁺ cluster ions, with n ? 2; it is suggested that the absorption of galactic cosmic ray energy at such relatively high pressures in the Jovian atmosphere $\text{(M ? 10}{}^{18}\text{to}\text{10}{}^{20}\text{cm}{}^{\mathrm{?3}}\text{)}$ and the subsequent chemical reactions may be instrumental in the local formation of complex hydrocarbons.     

Laboratory simulation of infrared astrophysical features

Laboratory infrared emission and absorption spectra have been taken of terrestrial silicates, meteorites and lunar soils in the form of micrometer and sub-micrometer grains. The emission spectra were taken in a way that imitates telescopic observations. The purpose was to see which materials best simulate the 10 m astrophysical feature.The emission spectra of dunite, fayalite and Allende give a good fit to the 10 m broadband emission feature of comets Bennett and Kohoutek. A study of the effect of grain size on the presence of the 10 m emission feature of dunite shows that for particles larger than 37 m no feature is seen.The emission spectrum of the Murray meteorite, a Type 2 carbonaceous chondrite, is quite similar to the intermediate resolution spectrum of comet Kohoutek in the 10 m region. Hydrous silicates or amorphous magnesium silicates in combination with high-temperature condensates, such as olivine or anorthite, would yield spectra that match the intermediate resolution spectrum of comet Kohoutek in the 10 m region. Glassy olivine and glassy anorthite in approximately equal proportions would also give a spectrum that is a good fit to the cometary 10 m feature.Invited contribution to the Proceedings of a Workshop onThermodynamics and Kinetics of Dust Formation in the Space Medium held at the Lunar and Planetary Institute, Houston, 6 8 September, 1978.     

A study on mechanical properties and fracturing behavior of Carrara marble with the flat-jointed model

Overcoming two inherent limitations presented by the standard bonded-particle model (BPM), the flat-jointed model still lacks extensive application. This study hereby conducts a comprehensive investigation on the application of the flat-jointed model in rock mechanics study. First, after a careful examination on the mechanical behavior of the flat-joint contact, a systematic calibration has been conducted to build numerical models matching the mechanical properties of Carrara marble. Second, the validated model is used to simulate the fracturing behavior of marble specimens containing a single or en-echelon flaws. Finally, the appearance of particle flow code (PFC) models has been compared with the results obtained from optical observation in order to establish a possible correlation between PFC models and real marble regarding microcracking behavior. Discussions suggest that to remove the particle size effect, the model resolution (ratio of sample dimension to the average particle diameter) should be larger than 30 in the flat-jointed model and 150 in the BPM, respectively. Results from the above investigations suggest that the flat-jointed model is capable of matching both the mechanical properties and fracturing behavior of Carrara marble. The numerical model is more reliable to predict the fracturing path at the instant of initiation than at failure. Development of initial fractures is not only controlled by the magnitude of tension force but also influenced by the extent of distribution of tension force. The appearance and components of a fracture in flat-jointed models probably reveal not only its property (tensile or shear) but also the corresponding microcracking behavior of real rocks.     

Kernel Principal Component Analysis for Efficient,Differentiable Parameterization of Multipoint Geostatistics

This paper describes a novel approach for creating an efficient, general, and differentiable parameterization of large-scale non-Gaussian, non-stationary random fields (represented by multipoint geostatistics) that is capable of reproducing complex geological structures such as channels. Such parameterizations are appropriate for use with gradient-based algorithms applied to, for example, history-matching or uncertainty propagation. It is known that the standard Karhunen–Loeve (K–L) expansion, also called linear principal component analysis or PCA, can be used as a differentiable parameterization of input random fields defining the geological model. The standard K–L model is, however, limited in two respects. It requires an eigen-decomposition of the covariance matrix of the random field, which is prohibitively expensive for large models. In addition, it preserves only the two-point statistics of a random field, which is insufficient for reproducing complex structures. In this work, kernel PCA is applied to address the limitations associated with the standard K–L expansion. Although widely used in machine learning applications, it does not appear to have found any application for geological model parameterization. With kernel PCA, an eigen-decomposition of a small matrix called the kernel matrix is performed instead of the full covariance matrix. The method is much more efficient than the standard K–L procedure. Through use of higher order polynomial kernels, which implicitly define a high-dimensionality feature space, kernel PCA further enables the preservation of high-order statistics of the random field, instead of just two-point statistics as in the K–L method. The kernel PCA eigen-decomposition proceeds using a set of realizations created by geostatistical simulation (honoring two-point or multipoint statistics) rather than the analytical covariance function. We demonstrate that kernel PCA is capable of generating differentiable parameterizations that reproduce the essential features of complex geological structures represented by multipoint geostatistics. The kernel PCA representation is then applied to history match a water flooding problem. This example demonstrates that kernel PCA can be used with gradient-based history matching to provide models that match production history while maintaining multipoint geostatistics consistent with the underlying training image.     

gLucifer: next generation visualization framework for high-performance computational geodynamics

High-performance computing provides unprecedented capabilities to produce higher resolution 4-D models in a fraction of time. Thus, the need exists for a new generation of visualization systems able to maintain parity with the enormous volume of data generated. In attempting to write this much data to disk, each computational step introduces a significant performance bottleneck, yet most existing visualization software packages inherently rely on reading data in from a dump file. Available packages make this assumption of postprocessing at quite a fundamental level and are not very well suited for plotting very large numbers of specialized particles. This necessitates the creation of a new visualization system that meets the needs of large-scale geodynamic modeling. We have developed such a system, gLucifer, using a software framework approach that allows efficient reuse of our efforts in other areas of research. gLucifer is capable of producing movies of a 4-D data set “on the fly” (simultaneously with running the parallel scientific application) without creating a performance bottleneck. By eliminating most of the human efforts involved in visualizing results through postprocessing, gLucifer reconnects the scientist to the numerical experiment as it unfolds. Data sets that were previously very difficult to even manage may be efficiently explored and interrogated without writing to disk, and because this approach is based entirely on memory distributed across as many processors as are being utilized by the scientific application, the visualization solution is scalable into terabytes of data being rendered in real time.