6 resultados para leaching and dissolution experiment

em Universidad de Alicante


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The total sea level variation (SLV) is the combination of steric and mass␣induced SLV, whose exact shares are key to understanding the oceanic response to climate system changes. Total SLV can be observed by radar altimetry satellites such as TOPEX/POSEIDON and Jason 1/2. The steric SLV can be computed through temperature and salinity profiles from in situ measurements or from ocean general circulation models (OGCM), which can assimilate the said observations. The mass-induced SLV can be estimated from its time-variable gravity (TVG) signals. We revisit this problem in the Mediterranean Sea estimating the observed, steric, and mass-induced SLV, for the latter we analyze the latest TVG data set from the GRACE (Gravity Recovery and Climate Experiment) satellite mission launched in 2002, which is 3.5 times longer than in previous studies, with the application of a two-stage anisotropic filter to reduce the noise in high-degree and -order spherical harmonic coefficients. We confirm that the intra-annual total SLV are only produced by water mass changes, a fact explained in the literature as a result of the wind field around the Gibraltar Strait. The steric SLV estimated from the residual of “altimetry minus GRACE” agrees in phase with that estimated from OGCMs and in situ measurements, although showing a higher amplitude. The net water fluxes through both the straits of Gibraltar and Sicily have also been estimated accordingly.

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The sea level variation (SLVtotal) is the sum of two major contributions: steric and mass-induced. The steric SLVsteric is that resulting from the thermal and salinity changes in a given water column. It only involves volume change, hence has no gravitational effect. The mass-induced SLVmass, on the other hand, arises from adding or subtracting water mass to or from the water column and has direct gravitational signature. We examine the closure of the seasonal SLV budget and estimate the relative importance of the two contributions in the Mediterranean Sea as a function of time. We use ocean altimetry data (from TOPEX/Poseidon, Jason 1, ERS, and ENVISAT missions) to estimate SLVtotal, temperature, and salinity data (from the Estimating the Circulation and Climate of the Ocean ocean model) to estimate SLVsteric, and time variable gravity data (from Gravity Recovery and Climate Experiment (GRACE) Project, April 2002 to July 2004) to estimate SLVmass. We find that the annual cycle of SLVtotal in the Mediterranean is mainly driven by SLVsteric but moderately offset by SLVmass. The agreement between the seasonal SLVmass estimations from SLVtotal – SLVsteric and from GRACE is quite remarkable; the annual cycle reaches the maximum value in mid-February, almost half a cycle later than SLVtotal or SLVsteric, which peak by mid-October and mid-September, respectively. Thus, when sea level is rising (falling), the Mediterranean Sea is actually losing (gaining) mass. Furthermore, as SLVmass is balanced by vertical (precipitation minus evaporation, P–E) and horizontal (exchange of water with the Atlantic, Black Sea, and river runoff) mass fluxes, we compared it with the P–E determined from meteorological data to estimate the annual cycle of the horizontal flux.

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In this study, we propose to estimate the steric sea-level variations over a < 2-year period (April 2002 through December 2003) by combining global mean sea level (GMSL) based on Topex/ Poseidon (T/P) altimetry with time-variable geoid averaged over the oceans, as observed by the GRACE (Gravity Recovery and Climate Experiment) satellite. In effect, altimetry-derived GMSL changes results from two contributions: Steric (thermal plus salinity) effects due to sea water density change and ocean mass change due to water exchange with atmosphere and continents. On the other hand, GRACE data over the oceans provide the ocean mass change component only. The paper first discusses the corrections to apply to the GRACE data. Then the steric contribution to the GMSL is estimated using GRACE and T/P data. Comparison with available thermal expansion based on in situ hydrographic data is performed.

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Time-variable gravity data from the Gravity Recovery And Climate Experiment (GRACE) mission are used to study total water content over Australia for the period 2002–2010. A time-varying annual signal explains 61% of the variance of the data, in good agreement with two independent estimates of the same quantity from hydrological models. Water mass content variations across Australia are linked to Pacific and Indian Ocean variability, associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), respectively. From 1989, positive (negative) IOD phases were related to anomalously low (high) precipitation in southeastern Australia, associated with a reduced (enhanced) tropical moisture flux. In particular, the sustained water mass content reduction over central and southern regions of Australia during the period 2006–2008 is associated with three consecutive positive IOD events.

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Chiral rhodium hybrid nanocatalysts have been prepared by covalent anchorage of pyrrolidine-based diphosphine ligands onto functionalized CNTs. This work constitutes the first attempt at covalent anchoring of homogeneous chiral catalysts on CNTs. The catalysts, prepared with two different chiral phosphines, were characterized by ICP, XPS, N2 adsorption and TEM, and have been tested in the asymmetric hydrogenation of two different substrates: methyl 2-acetamidoacrylate and α-acetamidocinnamic acid. The hybrid nanocatalysts have shown to be active and enantioselective in the hydrogenation of α-acetamidocinnamic acid. A good recyclability of the catalysts with low leaching and without loss of activity and enantioselectivity was observed.

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In autumn 2012, the new release 05 (RL05) of monthly geopotencial spherical harmonics Stokes coefficients (SC) from GRACE (Gravity Recovery and Climate Experiment) mission was published. This release reduces the noise in high degree and order SC, but they still need to be filtered. One of the most common filtering processing is the combination of decorrelation and Gaussian filters. Both of them are parameters dependent and must be tuned by the users. Previous studies have analyzed the parameters choice for the RL05 GRACE data for oceanic applications, and for RL04 data for global application. This study updates the latter for RL05 data extending the statistics analysis. The choice of the parameters of the decorrelation filter has been optimized to: (1) balance the noise reduction and the geophysical signal attenuation produced by the filtering process; (2) minimize the differences between GRACE and model-based data; (3) maximize the ratio of variability between continents and oceans. The Gaussian filter has been optimized following the latter criteria. Besides, an anisotropic filter, the fan filter, has been analyzed as an alternative to the Gauss filter, producing better statistics.