Determination of cadmium(II), copper(II), manganese(II) and nickel(II) species in Antarctic seawater with complexing resins

The strong species of cadmium(II), copper(II), manganese(II) and nickel(II) in an Antarctic seawater sample are investigated by a method based on the sorption of metal ions on complexing resins. The resins compete with the ligands present in the sample to combine with the metal ions. Two resins with different adsorbing strengths were used. Very stable metal complexes were investigated with the strong sorbent Chelex 100 and weaker species with the less strong resin, Amberlite CG-50. Strong species were detected for three of the considered metal ions, but not for Mn(II). Cu(II) is completely linked to species with a side reaction coefficient as high as log α_M(I) = 11.6 at pH = 7.3. The ligand concentration was found to be similar to that of the metal ion, and the conditional stability constant was around 10²⁰ M^− 1. In the considered sample, only a fraction of the metal ions Cd(II) and Ni(II) is bound to the strong ligands, with side reaction coefficients equal to log α_M(I) = 5.5 and 6.5 at pH = 7.3 for Cd(II) and Ni(II), respectively. These findings were confirmed by the test with the weaker sorbent Amberlite CG-50. It can be calculated from the sorption equilibria that neither Mn(II) nor Ni(II) is adsorbed on Amberlite CG-50 under the considered conditions and, in fact, only a negligible fraction of Mn(II) and Ni(II) was adsorbed. A noticeable fraction of Cd(II) was adsorbed on Amberlite CG-50, meaning that cadmium(II) is partially linked to weak ligands, possibly chloride, while no copper(II) was adsorbed on this resin, confirming that copper(II) is only combined in strong species. These results are similar, but not identical, to those obtained for other seawater samples examined in previous investigations.     

An algorithm to resolve γ-rays from charged cosmic rays with DAMPE

The DArk Matter Particle Explorer(DAMPE),also known as Wukong in China,which was launched on 2015 December 17,is a new high energy cosmic ray and γ-ray satellite-borne observatory.One of the main scientific goals of DAMPE is to observe Ge V-Te V high energy γ-rays with accurate energy,angular and time resolution,to indirectly search for dark matter particles and for the study of high energy astrophysics. Due to the comparatively higher fluxes of charged cosmic rays with respect to γ-rays,it is challenging to identify γ-rays with sufficiently high efficiency,minimizing the amount of charged cosmic ray contamination. In this work we present a method to identify γ-rays in DAMPE data based on Monte Carlo simulations,using the powerful electromagnetic/hadronic shower discrimination provided by the calorimeter and the veto detection of charged particles provided by the plastic scintillation detector. Monte Carlo simulations show that after this selection the number of electrons and protons that contaminate the selected γ-ray events at～10 Ge V amounts to less than 1% of the selected sample.Finally,we use flight data to verify the effectiveness of the method by highlighting known γ-ray sources in the sky and by reconstructing preliminary light curves of the Geminga pulsar.     

Non-parametric Bayesian networks for parameter estimation in reservoir simulation: a graphical take on the ensemble Kalman filter (part I)

Reservoir simulation models are used both in the development of new fields and in developed fields where production forecasts are needed for investment decisions. When simulating a reservoir, one must account for the physical and chemical processes taking place in the subsurface. Rock and fluid properties are crucial when describing the flow in porous media. In this paper, the authors are concerned with estimating the permeability field of a reservoir. The problem of estimating model parameters such as permeability is often referred to as a history-matching problem in reservoir engineering. Currently, one of the most widely used methodologies which address the history-matching problem is the ensemble Kalman filter (EnKF). EnKF is a Monte Carlo implementation of the Bayesian update problem. Nevertheless, the EnKF methodology has certain limitations that encourage the search for an alternative method.For this reason, a new approach based on graphical models is proposed and studied. In particular, the graphical model chosen for this purpose is a dynamic non-parametric Bayesian network (NPBN). This is the first attempt to approach a history-matching problem in reservoir simulation using a NPBN-based method. A two-phase, two-dimensional flow model was implemented for a synthetic reservoir simulation exercise, and initial results are shown. The methods’ performances are evaluated and compared. This paper features a completely novel approach to history matching and constitutes only the first part (part I) of a more detailed investigation. For these reasons (novelty and incompleteness), many questions are left open and a number of recommendations are formulated, to be investigated in part II of the same paper.     

Parameters affecting maximum fluid transport in large aperture fractures

We present results of laboratory experiments to study the behavior of liquids moving in unsaturated wide-aperture fractures. A 5-mm-thick glass plate cut with a 1.7-mm aperture was used as a fractured rock analog to study behavior of film and capillary droplet flow modes. Flow rates ranged between 0.6 and 6.0 ml/min. Variability in the ambient barometric pressure, resulting from weather conditions, seemed to play a role in the natural selection of flow mode. For droplet mode, constant input conditions resulted in highly variable transport properties within the fracture. The advancing meniscus exhibited a dynamic contact angle that was a function of the droplet speed and much larger than the static contact angle. Flow rate was reduced due to the larger contact angle. Analytical expressions for droplet velocity and flow capacity are presented as a function of the dynamic rather than the static contact angle.     

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961–1990) and projections for the IPCC A2 high emission scenario for 2071–2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5°N–15°S band, both in summer and especially in winter, reaching up to 6–8°C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4°C and in winter between 3 and 5°C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil.