13 research outputs found

    Dynamics of Disks and Warps

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    This chapter reviews theoretical work on the stellar dynamics of galaxy disks. All the known collective global instabilities are identified, and their mechanisms described in terms of local wave mechanics. A detailed discussion of warps and other bending waves is also given. The structure of bars in galaxies, and their effect on galaxy evolution, is now reasonably well understood, but there is still no convincing explanation for their origin and frequency. Spiral patterns have long presented a special challenge, and ideas and recent developments are reviewed. Other topics include scattering of disk stars and the survival of thin disks.Comment: Chapter accepted to appear in Planets, Stars and Stellar Systems, vol 5, ed G. Gilmore. 32 pages, 17 figures. Includes minor corrections made in proofs. Uses emulateapj.st

    Arsenic in agricultural and grazing land soils of Europe

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    Arsenic concentrations are reported for the <2 mm fraction of ca. 2200 soil samples each from agricultural (Ap horizon, 0\u201320 cm) and grazing land (Gr, 0\u201310 cm), covering western Europe at a sample density of 1 site/2500 km2. Median As concentrations in an aqua regia extraction determined by inductively coupled plasma emission mass spectrometer (ICP-MS) were 5.7 mg/kg for the Ap samples and 5.8 mg/kg for the Gr samples. The median for the total As concentration as determined by X-ray fluorescence spectrometry (XRF) was 7 mg/kg in both soil materials. Maps of the As distribution for both land-use types (Ap and Gr) show a very similar geographical distribution. The dominant feature in both maps is the southern margin of the former glacial cover seen in the form of a sharp boundary between northern and southern European As concentrations. In fact, the median As concentration in the agricultural soils of southern Europe was found to be more than 3-fold higher than in those of northern Europe (Ap: aqua regia: 2.5 vs. 8.0 mg/kg; total: 3 vs. 10 mg/kg). Most of the As anomalies on the maps can be directly linked to geology (ore occurrences, As-rich rock types). However, some features have an anthropogenic origin. The new data define the geochemical background of As in agricultural soils at the European scale

    The use of diffuse reflectance mid-infrared spectroscopy for the prediction of the concentration of chemical elements estimated by X-ray fluorescence in agricultural and grazing European soils .

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    The aim of this study was to develop partial least squares (PLS) models to predict the concentrations of 45 elements in soils extracted with aqua regia (AR) using mid-infrared (MIR) spectroscopy. A total of 4130 soils from the GEMAS European soil sampling program (geochemical mapping of agricultural soils and grazing land of Europe) were selected and MIR spectroscopy used for the development of models to predict Ag, Al, As, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hg, In, K, La, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, S, Sb, Sc, Se, Sn, Sr, Th, Ti, Tl, U, V, W, Y, Zn and Zr concentrations extracted by AR. From the full soil set, 1000 samples were randomly selected for the development of the calibration models, with the remaining 3130 samples used for model validation. Partial least-squares calibration models were used to relate the infrared (IR) spectra and the elemental concentrations in soils. The PLS calibrations were validated using cross validation and elements classified as a function of residual predictive deviation (RPD) values and R2 of the predictions. According to the RPD and R2 values of the validations, the 45 elements were allocated into two main groups; Group 1 (successful calibrations), 30 elements including those elements with RPD and R2 values equal or higher than 1.5 and 0.55, respectively: Ca (3.3, 0.91), Mg (2.5, 0.84), Al (2.4, 0.82), Fe (2.2, 0.79), Ga (2.2, 0.79), Co (2.1, 0.77), Sc (2.1, 0.77), Ni (2.0, 0.76), Ti (2.0, 0.75), Li (1.9, 0.73), Sr (1.9, 0.73), Cr (1.8, 0.69), Th (1.8, 0.69), K (1.8, 0.68), Be (1.7, 0.66), V (1.7, 0.63), S (1.6, 0.64), B (1.6, 0.62), Y (1.6, 0.61), Zn (1.6, 0.61), Rb (1.6, 0.61), Zr (1.6, 0.59), Na (1.5, 0.57), In (1.5, 0.57), Nb (1.5, 0.57), Cs (1.5, 0.57), Ce (1.5, 0.56), Cu (1.5, 0.56), Bi (1.5, 0.55) and Mn (1.5, 0.55); and group 2 for 15 elements with RPD and R2 values lower than 1.5 and 0.55, respectively: As (1.4, 0.52), La (1.4, 0.52), Ba (1.4, 0.52), Tl (1.4, 0.51), P (1.4, 0.46), U (1.4, 0.46), Sb (1.3, 0.46), Mo (1.3, 0.43), Pb (1.3, 0.42), Se (1.3, 0.40), Cd (1.3, 0.40), Sn (1.3, 0.39), Hg (1.2, 0.33), Ag (1.2, 0.32) and W (1.1, 0.19). The success of the PLS calibration models to predict AR extracted elemental concentrations in soils was found to be dependent on their relationships (directly or indirectly) with soil components that showed significant absorbances in the MIR region

    Mobile Metal Ion® analysis of European agricultural soils: bioavailability, weathering, geogenic patterns and anthropogenic anomalies

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    Two thousand one hundred and eight agricultural soils (0–20 cm depth) collected at a density of one sample per 2500 km2 under the auspices of the Geochemical Mapping of Agricultural Soils (GEMAS) project over most of the European continent have been analysed using the Mobile Metal Ion (MMI®) partial extraction technique with ICP-MS finish. For a number of elements, notably Ce, Ni, and Ca, coherent geogenic patterns have been observed which relate to underlying lithology. For Fe and Al, coherent patterns are also observed but the effects of weathering are evident, and provide a mechanism to explain the acidity of soils in high rainfall areas. Individual anomalies, many related to anthropogenic activity (mining, metallurgy, agriculture) have been observed for Ag, Au, Cu, Pb, Cd and Zn. Comparison of the results with aqua regia digestion and the equivalent National Geochemistry Survey of Australia (NGSA) provides insights into weathering processes and the concept of bioavailability

    GEMAS: Prediction of solid-solution partitioning coefficients (Kd) for cationic metals in soils using mid-infrared diffuse reflectance spectroscopy

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    Partial least squares regression (PLSR) models, using mid-infrared (MIR) diffuse reflectance Fourier-transformed (DRIFT) spectra,wereusedtopredictdistributioncoefficient(Kd)valuesforselectedaddedsolublemetalcations(Agþ,Co 2þ,Cu 2þ,Mn 2þ,Ni 2þ, Pb2þ, Sn 4þ, and Zn2þ) in 4813 soils of the Geochemical Mapping of Agricultural Soils (GEMAS) program. For the development of the PLSR models, approximately 500 representative soils were selected based on the spectra, and Kd values were determined using a singlepointsolublemetal orradioactiveisotopespike.Theoptimummodels, usingacombinationofMIR–DRIFTspectra andsoilpH,resulted ingoodpredictionsforlogKdþ1forCo,Mn,Ni,Pb,andZn(R20.83)butpoorpredictionsforAg,Cu,andSn(R2<0.50).Thesemodels wereappliedtothepredictionoflogKdþ1valuesintheremaining4313unknownsoils.ThePLSRmodelsprovidearapidandinexpensive tool to assess the mobility and potential availability of selected metallic cations in European soils. Further model development and validationwillbeneededtoenablethepredictionoflogKdþ1valuesinsoilsworldwidewithdifferentsoiltypesandpropertiesnotcovered in the existing mode
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