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Here we analyse ambient noise (AN) data generated during drilling of exploration boreholes and recorded using a dense array deployed over one of the numerous shallow iron-ore mineralization targets in the Pilbara region (Western Australia). Drilling and drilling-related operations were reoccurring in a sequence as described by the drillers' field notes, which created the rare opportunity to analyse AN data in time segments when only one type of technical process was predominantly active. Consequently, most of the recorded AN sources did not overlap in time and space. We extract the recordings in 15-min-long segments matching the time-span of single field-note entry and identify individually acting AN sources associated with specific field operations. The temporal variations of noise spectrograms and AN cross-correlations show dependency on the sequence of a few consecutive field operations and specific frequency–amplitude patterns associated with single field operations. These changes are directly reflected by the events visible in the retrieved virtual-source gathers (VSG), implying significant changes in noise temporal and spatial stationarity. Some VSGs represent the mixed contributions of surface and air waves. To remove the contributions of these arrivals to the reflection imaging, we visually inspect all data and select only field operations acting as stationary-phase sources specifically for the reflection retrieval. This was done for different receiver configurations inside PilbArray, and as a result, we obtain a collection of VSGs containing coherent body-wave reflections. Database of visually inspected VSGs is used to develop and benchmark a semi-automatic curvelet-based method for accurate parametrization of the reflection events retrieved from passive data and to compare the imaging quality of the different field operations. Common-midpoint stacks from manually and automatically selected VSGs show reflectivity consistent with the one obtained from the active-source data and related to the structure hosting shallow iron mineralization. Our results demonstrate the capacity of AN seismic interferometry to retrieve body-wave reflections and image shallow mineralization. They also provide an intermediate step toward automating the passive reflection imaging with similar data sets. [ABSTRACT FROM AUTHOR]

Torfajökull volcano, Iceland, has not erupted since 1477. However, intense geothermal activity, deformation, and seismicity suggest a long‐lasting magmatic system. In this paper, we use ambient noise tomography to image the magmatic system beneath Torfajökull volcano. One hundred days of ambient noise data from 23 broadband seismometers show the consistent presence of double‐frequency microseism noise with significant power between ∼0.1 and 0.5 Hz. Beamforming results indicate microseism noise with persistent higher energy propagating from west and SE directions and apparent velocities below 3 km/s. We use ambient noise seismic interferometry to retrieve Rayleigh waves, and we introduce a method to estimate the reliability of the retrieved surface waves. We find stable estimation of surface wave phase velocities between 0.16 and 0.38 Hz. Azimuthal velocity variations show a trend of higher velocities in the NE/SW direction, the strike of the rift zone intersecting Torfajökull, and orientation of erupted lavas on a NE‐SW fissure swarm. Tomographic results indicate low‐velocity anomalies beneath the volcano caldera (between −5% and −10%) and even lower velocity variations in the southeast and southwest study area (below −10%), outside the volcano caldera. Low anomalies may indicate the existence of hot material, more prominent outside the caldera outskirts. High‐velocity variations (between 5% and 10%) outline the volcano caldera between 4‐ and 5‐km depth and more pronounced velocities (between 10% and 15%) up to 5‐km depth in the north of the volcano caldera. We interpret the former as possible caldera collapse structure and the latest as solidified intrusive magma from the old preferred magma paths. Plain Language Summary: Magmatic plumbing systems' characterization is one of the pillars for predicting volcanic eruptions. While most of the active volcanoes are being currently monitored, less is known about volcanoes that had not erupted recently. Torfajökull volcano, Iceland, has not erupted since 1477. However, intense geothermal activity, deformation, and seismicity suggest a long‐lasting magmatic system. We use ambient noise to produce a tomographic image of the magmatic system beneath Torfajökull volcano. This technique allows us to detect velocity variations/contrasts due to changes in composition, density, temperature, or pressure in the subsurface.We identify high‐velocity variations outlining the volcano caldera between 4‐ and 5‐km depth and more pronounced high‐velocities at shallower depths in the north of the volcano caldera. We interpret the former as possible caldera collapse structure and the latest as solidified (and dense) intrusive magma from the old preferred magma paths. The tomographic results also indicate low‐velocity anomalies beneath the volcano caldera and even lower‐velocity variations in the southeast and southwest study area, outside the volcano caldera. The most prominent low‐velocity features are located outside the volcano caldera outskirts. These low anomalies, or deceleration areas of wave velocity, may indicate the existence of hot material (molten or partially molten rock). Key Points: This article presents the first tomographic image (3‐D S wave velocities) of Torfajökull's magmatic system; we have derived a 3‐D S wave velocity field from ambient noise tomographyWe developed a new methodology for phase velocity estimation from retrieved surface waves applied to 100 days of recorded ambient noiseWe interpret the low‐/high‐velocity anomalies interpreted as molten or partial molten cavities/channels (low) and old dike intrusions/caldera forming (high) [ABSTRACT FROM AUTHOR]

Digital databases on 444 stations were used to carry out statistical analysis of regularities in the spatial distribution of Barents Sea water pollution. The analysis was focused on the concentrations in water of heavy metals (Cd, Cr, Cu, Hg, Ni, Pb, and Zn) and toxic organic compounds: hexachlorocyclohexanes, hexachlorobenzene, chlordans, DDT, polychlorbiphenyls, polycyclic aromatic hydrocarbons, and normal paraffins. The statistical analysis of data on pollutants was carried out along two major directions in their distribution: the vertical-in the surface and bottom water layers; and the horizontal-over water masses. Reliable differences were identified in the pollution level of different water masses of the Barents Sea. The frontal zone was found to concentrate pollution. [ABSTRACT FROM AUTHOR]

Seismic interferometry (SI) enables the retrieval of virtual sources at the location of receivers. In the case of passive SI, no active sources are used for the retrieval of the reflection response of the subsurface, but ambient-noise recordings only. The resulting retrieved response is determined by the illumination characteristics of the recorded ambient noise.Characteristics like geometrical distribution and signature of the noise sources, together with the complexity of the medium and the length of the noise records, determine the quality of the retrieved virtual-shot events. To retrieve body wave reflections, one needs to correlate body-wave noise. A source of such noise might be regional seismicity. In regions with notable human presence, the dominant noise sources are generally located at or close to the surface. In the latter case, the noise will be dominated by surface waves and consequently also the retrieved virtual common-source panels will contain dominant retrieved surface waves, drowning out possible retrieved reflections. In order to retrieve reflection events, suppression of the surface waves becomes the most important pre-processing goal.Because of the reasons mentioned above, we propose a fast method to evaluate the illumination characteristics of ambient noise using the correlation results from ambient-noise records. The method is based on the analysis of the so-called source function of the retrieved virtual-shot panel, and evaluates the apparent slowness of arrivals in the correlation results that pass through the position of the virtual source and at zero time. The results of the diagnosis are used to suppress the retrieval of surface waves and therefore to improve the quality of the retrieved reflection response. We explain the approach using modelled data from transient and continuous noise sources and an example from a passive field data set recorded at Annerveen, Northern Netherlands. [ABSTRACT FROM AUTHOR]

We discuss a model which parameterizes the cosmic-ray (CR) spectrum at different physical conditions, which include the most important effects controlling the CR intensity, like convection-diffusion and energy losses. By a suitable choice of parameters the proposed model results in two approximations: one close to a 'force-field' model (describing the energy losses of CRs in the inner heliosphere) and a 'convection-diffusion' equation (giving the reduction of CR intensity in the outer heliosphere). The BESS ( Balloon-borne Experiment with Superconducting Spectrometer) experimental spectra of galactic protons and helium nuclei are fitted by the model spectra. The calculation of the unknown parameters is performed using a constrained least squares method as an alternative to the standard chi-square minimization method, because the data contain not only random errors, but also systematic ones. The CR spectrum approximation (CRSA) model is compared to the Moscow State University (MSU) model and the Badhwar and O'Neill (Badhwar and O'Neill, Adv. Space. Res. 14, 749, ; Adv. Space Res. 17, 7, ) model; we show that depending on the choice of the model parameters it can be examined in the context of one of these two models. We derive a relation between the parameters of the CRSA and MSU models for rigidities above about 10 GV (drift effects are ignored) during periods of low to approximately average levels of solar activity. The drawbacks of the proposed approximation are that: i) the model parameters do not depend on rigidity and ii) the model does not take into account general trends in the variations of the heliospheric magnetic field; thus, the influence of the drift effects on the shape of the spectral curves for different magnetic field polarity swings is ignored. [ABSTRACT FROM AUTHOR]

The human paraoxonase (PON) gene family consists of three members, PON1, PON2, and PON3, aligned next to each other on chromosome 7. By far the most-studied member of the family is the serum paraoxonase 1 (PON1), a high-density lipoprotein-associated esterase/lactonase. Early research focused on its capability to hydrolyze toxic organophosphates, and its name derives from one of its most commonly used in vitro substrates, paraoxon. Studies in the last 2 decades have demonstrated PON1’s ability to protect against atherosclerosis by hydrolyzing specific derivatives of oxidized cholesterol and/or phospholipids in oxidized low-density lipoprotein and in atherosclerotic lesions. Levels and genetic variability of PON1 influence sensitivity to specific insecticides and nerve agents, as well as the risk of cardiovascular disease. More recently, the other two members of the PON family, PON2 and PON3, have also been shown to have antioxidant properties. A major goal in present research on the paraoxonases is to identify their natural substrates and to elucidate the mechanism(s) of their catalytic activities. [ABSTRACT FROM AUTHOR]