Earth Tides and Lense–Thirring Effect

The general relativistic Lense—Thirring effect can be measured by inspecting a suitable combination of the orbital residuals of the nodes of LAGEOS and LAGEOS II and the perigee of LAGEOS II. The solid and ocean Earth tides affect the recovery of the parameter by means of which the gravitomagnetic signal is accounted for in the combined residuals. Thus an extensive analysis of the perturbations induced on these orbital elements by the solid and ocean Earth tides is carried out. It involves the l=2 terms for the solid tides and the l=2,3,4 terms for the ocean tides. The perigee of LAGEOS II turns out to be very sensitive to the l=3 part of the ocean tidal spectrum, contrary to the nodes of LAGEOS and LAGEOS II. The uncertainty in the solid tidal perturbations, mainly due to the Love number k ₂, ranges from 0.4% to 1.5%, while the ocean tides are uncertain at 5–15% level. The obtained results are used in order to check in a preliminary way which tidal constituents the Lense-Thirring shift is sensitive to. In particular it is tested if the semisecular 18.6-year zonal tide really does not affect the combined residuals. It turns out that, if modeled at the level of accuracy worked out in the paper, the l=2,4 m=0 and also, to a lesser extent, the l=3, m=0 tidal perturbations cancel out.This revised version was published online in October 2005 with corrections to the Cover Date.     

The Impact of the Static Part of the Earth's Gravity Field on Some Tests of General Relativity with Satellite Laser Ranging

In this paper we calculate explicitly the classical secular precessions of the node and the perigee of an Earth artificial satellite induced by the even zonal harmonics of the static part of the geopotential up to degree l = 20. Subsequently, their systematic errors induced by the mismodelling in the even zonal spherical harmonics coefficients J _l are compared to the general relativistic secular gravitomagnetic and gravitoelectric precessions of the node and the perigee of the existing laser-ranged geodetic satellites and of the proposed LARES. The impact of the future terrestrial gravity models from CHAMP and GRACE missions is discussed as well. Preliminary estimates with the recently released EIGEN-1S gravity model including the first CHAMP data are presented.     

Speciation and solubility of heavy metals in contaminated soil using X-ray microfluorescence, EXAFS spectroscopy, chemical extraction, and thermodynamic modeling

Synchrotron-based X-ray radiation microfluorescence (μ-SXRF) and micro-focused and powder extended X-ray absorption fine structure (EXAFS) spectroscopy measurements, combined with desorption experiments and thermodynamic calculations, were used to evaluate the solubility of metal contaminants (Zn, Cu, Pb) and determine the nature and fractional amount of Zn species in a near-neutral pH (6.5-7.0) truck-farming soil contaminated by sewage irrigation for one hundred years. Zn is the most abundant metal contaminant in the soil (1103 mg/kg), followed by Pb (535 mg/kg) and Cu (290 mg/kg). The extractability of Zn, Pb, and Cu with citrate, S,S-ethylenediaminedisuccinic acid (EDDS), and ethylenediaminetetraacetic acid (EDTA) was measured as a function of time (24 h, 72 h, 144 h), and also as a function of the number of applications of the chelant (5 applications each with 24 h of contact time). Fifty-three percent of the Zn was extracted after 144 h with citrate, 51% with EDDS and 46% with EDTA, compared to 69, 87, and 61% for Cu, and 24, 40, and 34% for Pb. Renewing the extracting solution removed more of the metals. Seventy-nine, 65, and 57% of the Zn was removed after five cycles with citrate, EDDS and EDTA, respectively, compared to 88, 100, and 72% for Cu, and 91, 65, and 47% for Pb. Application to the untreated soil of μ-SXRF, laterally resolved μ-EXAFS combined with principal component analysis, and bulk averaging powder EXAFS with linear least-squares combination fit of the data, identified five Zn species: Zn-sorbed ferrihydrite, Zn phosphate, Zn-containing trioctahedral phyllosilicate (modeled by the Zn kerolite, Si₄(Mg_1.65Zn_1.35)O₁₀(OH)₂ · nH₂O), willemite (Zn₂SiO₄), and gahnite (ZnAl₂O₄), in proportions of ∼30, 28, 24, 11, and less than 10%, respectively (precision: 10% of total Zn). In contrast to Cu and Pb, the same fractional amount of Zn was extracted after 24 h contact time with the three chelants (40-43% of the initial content), suggesting that one of the three predominant Zn species was highly soluble under the extraction conditions. Comparison of EXAFS data before and after chemical treatment revealed that the Zn phosphate component was entirely and selectively dissolved in the first 24 h of contact time. Preferential dissolution of the Zn phosphate component is supported by thermodynamic calculations. Despite the long-term contamination of this soil, about 79% of Zn, 91% of Pb, and 100% of Cu can be solubilized in the laboratory on a time scale of a few days by chemical complexants. According to metal speciation results and thermodynamic calculations, the lower extraction level measured for Zn is due to the Zn phyllosilicate component, which is less soluble than Zn phosphate and Zn ferrihydrite.     

Can Sea Fog be Inferred from Operational GEM Forecast Fields?

Three cases of widespread sea fog in Lunenburg Bay, Nova Scotia were used to evaluate the suitability of operational regional GEM forecast fields for inferring advection fog occurrences. Verification scores suggest that the objective analyses contain significant departures from observations that will affect model accuracy, given the sensitivity of fog condensation microphysics. Dew point depression (ES) scores show larger differences compared to temperature, with both influenced by surface characteristics. For objective analyses and GEM forecasts ES < 2 C seems to match fog satellite images better than the physical threshold ES ≤ 0 C. In addition the GEM forecasts show a general tendency towards drier conditions near the surface, therefore reconfiguring GEM to better represent condensation in the boundary layer is proposed.     

Dynamical constraints on some orbital and physical properties of the WD0137-349A/B binary system

In this paper I deal with the WD0137-349 binary system consisting of a white dwarf (WD) and a brown dwarf (BD) in a close circular orbit of about 116 min. I, first, constrain the admissible range of values for the inclination i by noting that, from looking for deviations from the third Kepler law, the quadrupole mass moment Q would assume unlikely large values, incompatible with zero at more than 1-sigma level for i≲35 deg and i≳43 deg. Then, by conservatively assuming that the most likely values for i are those that prevent such an anomalous behavior of Q, i.e. those for which the third Kepler law is an adequate modeling of the orbital period, I obtain i=39±2 deg. Such a result is incompatible with the value i=35 deg quoted in literature by more than 2 sigma. Conversely, it is shown that the white dwarf’s mass range obtained from spectroscopic measurements is compatible with my experimental range, but not for i=35 deg. As a consequence, my estimate of i yields an orbital separation of a=(0.59±0.05)R_⊙ and an equilibrium temperature of BD of T _eq=(2087±154) K which differ by 10% and 4%, respectively, from the corresponding values for i=35 deg.     

Global sensitivity analysis through polynomial chaos expansion of a basin-scale geochemical compaction model

We present a model-driven uncertainty quantification methodology based on sparse grid sampling techniques in the context of a generalized polynomial chaos expansion (GPCE) approximation of a basin-scale geochemical evolution scenario. The approach is illustrated through a one-dimensional example involving the process of quartz cementation in sandstones and the resulting effects on the dynamics of the vertical distribution of porosity, pressure, and temperature. The proposed theoretical framework and computational tools allow performing an efficient and accurate global sensitivity analysis (GSA) of the system states (i.e., porosity, temperature, pressure, and fluxes) in the presence of uncertain key mechanical and geochemical model parameters as well as boundary conditions. GSA is grounded on the use of the variance-based Sobol indices. These allow discriminating the relative weights of uncertain quantities on the global model variance and can be computed through the GPCE of the model response. Evaluation of the GPCE of the model response is performed through the implementation of a sparse grid approximation technique in the space of the selected uncertain quantities. GPCE is then be employed as a surrogate model of the system states to quantify uncertainty propagation through the model in terms of the probability distribution (and its statistical moments) of target system states.     

Quantitative evaluation of multipath rejection capabilities of GNSS antennas

Multipath error remains the largest error source in many high precision GPS applications. To counteract this problem, solutions at both software and hardware level have been studied. Software processing by means of measurement redundancy or error predictability can be used in order to mitigate the multipath effects. In general, these techniques work properly only when the length of a reflection path exceeds that of the direct path by more than 10–20 m. Unfortunately, in most cases, reflections are generated in the area near the receiving antenna. For this reason, multipath rejection actuated at the antenna level is one of the most valid means to improve the accuracy of GPS systems. The scope of this work is twofold. First, a review of low-multipath reception requirements will be proposed for comparing different classes of high precision GNSS antennas. Based on this discussion, we introduce a quantitative evaluation of multipath rejection capabilities of a GNSS antenna. The proposed assessment technique is focused on the antenna pattern, but, in contrast to other parameters evaluating the antenna radiation characteristics, it is specifically conceived to capture the effects of multipath signals.