Exposure history of the Torino meteorite

Abstract— We determined He, Ne, Ar, ¹⁰Be, ²⁶Al, ³⁶Cl, and ¹⁴C concentrations, as well as cosmic-ray track densities and halogen concentrations in different specimens of the H6 chondrite Torino, in order to constrain its exposure history to cosmic radiation. The Torino meteoroid had a radius of ～20 cm and travelled in interplanetary space for 2.5–10 Ma. Earlier, Torino was part of a larger body. The smallest possible precursor had a radius of 55 cm and a journey through space longer than ～65 Ma. If the first-stage exposure took place in a body with a radius of >3 m or in the parent asteroid, then it lasted nearly 300 Ma. The example of Torino shows that it is easy to underestimate first-stage exposure ages when constructing two-stage histories.     

Beryllium-10 in Australasian tektites: Constraints on the location of the source crater

By using accelerator mass spectrometry we have measured the ¹⁰Be concentrations of 86 Australasian tektites. Corrected to the time of tektite production ∼0.8 My ago, the ¹⁰Be concentrations (10⁶ atom/g) range from 59 for a layered tektite from Huai Sai, Thailand, to 280 for an australite from New South Wales, Australia. The average value is 143 ± 50. When tektites are sorted by country, their average measured ¹⁰Be concentrations increase slowly with increasing distance from Southeast Asia, the probable location of the tektite producing event, from 59 ± 9 for 6 layered tektites from Laos to 136 ± 20 for 20 splash-form tektites from Australia. The lowest ¹⁰Be concentrations for tektites fall on or within a contour centered off the shore of Vietnam, south of the Gulf of Tonkin (107°E; 17°N), but also encompassing two other locations in the area of northeastern Thailand previously proposed for the site of a single tektite-producing impact. The ¹⁰Be concentrations of layered tektites show only a weak anticorrelation (R ∼ −0.3) with the numbers of relict crystalline inclusions.Loosely consolidated, fine-grained terrestrial sediments or recently consolidated sedimentary rocks are the most likely precursor materials. Dilution of sediments with other kinds of rock raises problems in mixing and is not supported by petrographic data. Sedimentary columns that have the right range of ¹⁰Be concentrations occur off the coasts of places where sedimentation rates are high relative to those in the deep sea. A single impact into such a region, 15 to 300 m thick, could have propelled near-surface, high-¹⁰Be material farthest—to Australia—while keeping the deeper-lying, low-¹⁰Be layers closer to home. We do not rule out, however, other proposed mechanisms for tektite formation.     

Late Pleistocene baldcypress (Taxodium distichum) forest deposit on the continental shelf of the northern Gulf of Mexico

Approximately 13 km south of Gulf Shores, Alabama (United States), divers found in situ baldcypress (Taxodium distichum) stumps 18 m below the ocean surface. These trees could have only lived when sea level fell during the Pleistocene subaerially exposing the tectonically stable continental shelf. Here we investigate the geophysical properties along with microfossil and stratigraphical analyses of sediment cores to understand the factors that lead to this wood’s preservation. The stumps are exposed in an elongated depression (~100 m long, ~1 m deep) nested in a trough of the northwest–southeast trending Holocene sand ridges and troughs with 2–5 m vertical relief and ~0.5 km wavelength. Radiocarbon ages of the wood were infinite thus optically stimulated luminescence (OSL) dating was used to constrain the site’s age. Below the Holocene sands (~0.1–4 m thick), separated by a regional erosional unconformity, are Late Pleistocene mud-peat (72±8 ka OSL), mud-sand (63±5, 73±6 ka OSL), and palaeosol (56±5 ka OSL) facies that grade laterally from west to east, respectively. Foraminiferal analysis reveals the location of the terrestrial-marine transitional layer above the Pleistocene facies in an interbedded sand and mud facies (3940±30 (1σ) ¹⁴C a BP), which is part of a lower shoreface or marine-dominated estuarine environment. The occurrence of palaeosol and swamp facies of broadly similar ages and elevation suggests the glacial landscape possessed topographic relief that allowed wood, mud and peats to be preserved for ~50 ka of subaerial exposure before transitioning to the modern marine environment. We hypothesize that rapid sea-level rise occurring ~60 or ~40 ka ago provided opportunities for local flood-plain aggradation to bury the swamp thus preserving the stumps and that other sites may exist in the northern Gulf of Mexico shelf.     

Al depth profile in Apollo 15 drill core

Cosmic-ray-produced²⁶Al (t_1/2 = 7.05 × 10⁵ years) has been measured in the Apollo 15 long core (surface to 390 g/cm²—218 cm) for study of galactic cosmic ray production profiles, using accelerator mass spectrometry. The results are in general accord with non-destructive counting data obtained earlier, but systematically lower, and significantly higher precision. From this experiment the half-attenuation length for²⁶Al production can be calculated to be 122 g/cm² (150–400 g/cm² region) after normalizing the data to average chemical composition. The⁵³Mn (t_1/2 = 3.7 × 10⁶ years) production profile in deep cores was also compiled to date. The half-attenuation length for⁵³Mn production was calculated to be 123 g/cm² (150–400 g/cm² region).     

Wind-forced continental shelf waves from a geographical origin

The response of a barotropic coastal ocean on a step-shaped continental shelf to a traveling sinusoidal wind stress forcing is predicted theoretically using a frictional force proportional to the alongshore current velocity. This theory is compared to a small set of observations from the northeast coast of Australia where a sudden widening of the continental shelf provides a geographical origin. The comparison is accomplished by means of frequency response functions relating alongshore wind stress with alongshore velocity. Amplitudes of the response functions are predicted to increase with alongshore distance equatorward and also to decrease with frequency at any location. These predictions are verified by the measurements. Predicted phase lags are generally less than about 30°, with observations agreeing with theory to within about 20°C. In general, the measurements provide reasonable evidence to support the theory of wind-forced continental shelf waves from a geographical origin.     

Boosting for Mineral Prospectivity Modeling: A New GIS Toolbox

With an increasing demand for raw materials, predictive models that support successful mineral exploration targeting are of great importance. We evaluated different machine learning techniques with an emphasis on boosting algorithms and implemented them in an ArcGIS toolbox. Performance was tested on an exploration dataset from the Iberian Pyrite Belt (IPB) with respect to accuracy, performance, stability, and robustness. Boosting algorithms are ensemble methods used in supervised learning for regression and classification. They combine weak classifiers, i.e., classifiers that perform slightly better than random guessing to obtain robust classifiers. Each time a weak learner is added; the learning set is reweighted to give more importance to misclassified samples. Our test area, the IPB, is one of the oldest mining districts in the world and hosts giant volcanic-hosted massive sulfide (VMS) deposits. The spatial density of ore deposits, as well as the size and tonnage, makes the area unique, and due to the high data availability and number of known deposits, well-suited for testing machine learning algorithms. We combined several geophysical datasets, as well as layers derived from geological maps as predictors of the presence or absence of VMS deposits. Boosting algorithms such as BrownBoost and Adaboost were tested and compared to Logistic Regression (LR), Random Forests (RF) and Support Vector machines (SVM) in several experiments. We found performance results relatively similar, especially to BrownBoost, which slightly outperformed LR and SVM with respective accuracies of 0.96 compared to 0.89 and 0.93. Data augmentation by perturbing deposit location led to a 7% improvement in results. Variations in the split ratio of training and test data led to a reduction in the accuracy of the prediction result with relative stability occurring at a critical point at around 26 training samples out of 130 total samples. When lower numbers of training data were introduced accuracy dropped significantly. In comparison with other machine learning methods, Adaboost is user-friendly due to relatively short training and prediction times, the low likelihood of overfitting and the reduced number of hyperparameters for optimization. Boosting algorithms gave high predictive accuracies, making them a potential data-driven alternative for regional scale and/or brownfields mineral exploration.