Optimal spherical spline filters for the analysis and comparison of regional-scale tomographic models

Advances in seismic tomography lead to increasingly detailed models of the Earth that are often represented on irregular and resolution-adaptive grids. To take full advantage of such models, their assessment must progress beyond a purely visual analysis, and tools must become available for their quantitative comparison.We present a method for the spectral analysis and comparison of multi-scale tomographic models. The method is applicable to irregular grids on the sphere, and is more efficient that filters based on spherical-harmonic expansions or convolution integrals. The combination of a spherical spline representation of tomographic information with Abel-Poisson scaling enables the construction of targetted spatial filters by solving a nonlinear inverse problem for appropriate weighting coefficients. This can be readily achieved with a simulated annealing approach for the limited number of weights. Once suitable filters have been generated they can be employed to address issues such as the patterns of small-scale heterogeneity, transitional structures and comparison of independent models from a region.We illustrate our method in a series of applications where we use different bandpass filters to detect differences in the distribution of small-scale heterogeneity beneath central and eastern Europe, and to compare several recent tomographic models of the Australian region.     

Magnetic signature of hydrocarbon-contaminated soils and sediments at the former oil field H?nigsen, Germany

Magnetic properties of hydrocarbon (HC) containing soils and sediments from two sites (Site A and B) of the former oil-field H?nigsen were analyzed in order to determine whether magnetic methods can be employed to delineate HC contamination of soils and sediments. Magnetic parameters such as magnetic susceptibility and induced isothermal remanent magnetizations, as well as soil and sediment properties such as pH, iron content and water content, HC content and most probable number counts of iron-metabolizing microorganisms were determined. The magnetic concentration-dependent parameters for HC contaminated samples were 25 times higher in soils from Site A than in sediment samples from Site B. However, at Site B the magnetic susceptibility was still four times higher in comparison to lithologically similar non-contaminated sediment samples from a third Site C. Newly formed magnetite containing mainly single domain particles was responsible for the magnetic enhancement, whereas superparamagnetic grains represented only a minor component. Site A had an acidic pH compared to neutral pH at Site B, and a higher crystalline and bioavailable total iron content. Nevertheless, Site B samples contained significant numbers of both iron(II)-oxidizing and iron(III)-reducing microorganisms indicating that microbial iron cycling might have taken place at this site and potentially played a role for iron mineral transformation, including magnetite (trans)formation. The content of total non-polar hydrocarbons (TNPH) at Site A was one order of magnitude higher than at Site B. Only at Site A magnetic susceptibility correlated well with TNPH. Our results demonstrate that HC contaminated samples had an enhanced magnetite content compared to non-contaminated soils and sediments. Therefore, magnetic methods may provide a quick and cost-effective way to assess HC contamination in soils and sediments. However, more field sites and laboratory investigations are needed to reveal the complex nature of the processes involved.     

A contribution to risk analysis for leakage through abandoned wells in geological CO2 storage

The selection and the subsequent design of a subsurface CO₂ storage system are subject to considerable uncertainty. It is therefore important to assess the potential risks for health, safety and environment. This study contributes to the development of methods for quantitative risk assessment of CO₂ leakage from subsurface reservoirs. The amounts of leaking CO₂ are estimated by evaluating the extent of CO₂ plumes after numerically simulating a large number of reservoir realizations with a radially symmetric, homogeneous model. To conduct the computationally very expensive simulations, the ‘CO₂ Community Grid’ was used, which allows the execution of many parallel simulations simultaneously. The individual realizations are set up by randomly choosing reservoir properties from statistical distributions. The statistical characteristics of these distributions have been calculated from a large reservoir database, holding data from over 1200 reservoirs. An analytical risk equation is given, allowing the calculation of average risk due to multiple leaky wells with varying distance in the surrounding of the injection well. The reservoir parameters most affecting risk are identified. Using these results, the placement of an injection well can be optimized with respect to risk and uncertainty of leakage. The risk and uncertainty assessment can be used to determine whether a site, compared to others, should be considered for further investigations or rejected for CO₂ storage.     

Automatic detection and tracking of pedestrians from a moving stereo rig

We report on a stereo system for 3D detection and tracking of pedestrians in urban traffic scenes. The system is built around a probabilistic environment model which fuses evidence from dense 3D reconstruction and image-based pedestrian detection into a consistent interpretation of the observed scene, and a multi-hypothesis tracker to reconstruct the pedestrians’ trajectories in 3D coordinates over time. Experiments on real stereo sequences recorded in busy inner-city scenarios are presented, in which the system achieves promising results.     

System identification and modeling of a dynamically tested and gradually damaged 10‐story reinforced concrete building

This paper discusses the dynamic tests, system identification, and modeling of a 10‐story reinforced concrete building. Six infill walls were demolished in 3 stages during the tests to introduce damage. In each damage stage, dynamic tests were conducted by using an eccentric‐mass shaker. Accelerometers were installed to record the torsional and translational responses of the building to the induced excitation, as well as its ambient vibration. The modal properties in all damage states are identified using 2 operational modal analysis methods that can capture the effect of the wall demolition. The modal identification is facilitated by a finite element model of the building. In turn, the model is validated through the comparison of the numerically and experimentally obtained modal parameters. The validated model is used in a parametric study to estimate the influence of structural and nonstructural elements on the dynamic properties of the building and to assess the validity of commonly used empirical formulas found in building codes. Issues related to the applicability and feasibility of system identification on complex structures, as well as considerations for the development of accurate, yet efficient, finite element models are also discussed.     

Using wind run to predict sand drift

Conventional aeolian sand transport models relate mass transport rate to wind speed or shear velocity, usually expressed and empirically tested on a 1-s time scale. Projections of total sand delivery over long time scales based on these models are highly sensitive to any small bias arising from statistical fitting on empirical data. We analysed time series of wind speed and sand transport rate collected at 14 independent measurement stations on a beach during a prior field experiment. The results show that relating total sand drift to cumulative above-threshold wind run yields models which are more statistically robust when fitted on empirical data, generating smaller prediction errors when projected to longer time scales. Testing of different power exponents indicates that a linear relationship between sand drift and above-threshold wind run yields the best results. These findings inspire a speculative novel phenomenological model relating the mass flow of air in the boundary layer to the mass transport of sand over the surface. © 2020 John Wiley & Sons, Ltd.     

Break of temporal symmetry in a stationary Markovian setting: evidencing an arrow of time,and parameterizing linear dependencies using fractional low-order joint moments

Stochastic Environmental Research and Risk Assessment - We demonstrate that “an arrow of time” that is being determined by the joint distributions of successive process variables, or...     

Geochemical and Sr-Nd isotopic evidence for petrogenesis and geodynamic setting of Lower-Middle Triassic volcanogenic rocks from central Greece: Implications for the Neotethyan Pindos ocean

Mineralogy and Petrology - Geochemistry and Sr-Nd isotopes were determined in Triassic calcalkaline metalava and metapyroclastic rocks from Attica and Argolida, central Greece, to ascertain their...     

In situ investigation of dissolution of heavy metal containing mineral particles in an acidic forest soil

We report the application of an in situ method to obtain field dissolution rates of fine mineral particles in soils. Samples with different metal-containing mineral and slag particles (lead oxide, copper concentrate and copper slag) from the mining and smelting industry were buried in the topsoil of an acidic forest soil for up to 18 months. In addition we studied the dissolution of these particles in samples of the same soil, in a sand matrix and in acid solution under constant temperature and moisture conditions in the laboratory. Under field conditions the PbO particles dissolved quite rapidly (2.4 ± 0.7 × 10⁻¹⁰ mol Pb m⁻² s⁻¹), whereas the copper concentrate (<1 × 10⁻¹¹ mol Cu m⁻² s⁻¹) and the copper slag particles (4.3 ± 0.8 × 10⁻¹¹ mol Cu m⁻² s⁻¹) proved to be more resistant to weathering. In addition to qualitative information on dissolution features (SEM), the method yielded quantitative data on in situ dissolution rates. The dissolution rates followed the order: sand with acid percolation (pH 3.5; lab) < soil (lab) < soil (field) < acid solution (pH 3.5; lab). Dissolution rates in soil were found to be lower under laboratory than under field conditions. The faster field rates may in part be attributed to the higher biological activity in the field soil compared to the same soil in the laboratory.