• Geosciences, Vol. 7, Pages 134: Pyplis—A Python Software Toolbox for the Analysis of SO2 Camera Images for Emission Rate Retrievals from Point Sources

      Ultraviolet (UV) SO2 cameras have become a common tool to measure and monitor SO2 emission rates, mostly from volcanoes but also from anthropogenic sources (e.g., power plants or ships). Over the past decade, the analysis of UV SO2 camera data has seen many improvements. As a result, for many of the required analysis steps, several alternatives exist today (e.g., cell vs. DOAS based camera calibration; optical flow vs. cross-correlation based gas-velocity retrieval). This inspired the development of Pyplis (Python plume imaging software), an open-source software toolbox written in Python 2.7, which unifies the most prevalent methods from literature within a single, cross-platform analysis framework. Pyplis comprises a vast collection of algorithms relevant for the analysis of UV SO2 camera data. These include several routines to retrieve plume background radiances as well as routines for cell and DOAS based camera calibration. The latter includes two independent methods to identify the DOAS field-of-view (FOV) within the camera images (based on (1) Pearson correlation and (2) IFR inversion method). Plume velocities can be retrieved using an optical flow algorithm as well as signal cross-correlation. Furthermore, Pyplis includes a routine to perform a first order correction of the signal dilution effect (also referred to as light dilution). All required geometrical calculations are performed within a 3D model environment allowing for distance retrievals to plume and local terrain features on a pixel basis. SO2 emission rates can be retrieved simultaneously for an arbitrary number of plume intersections. Hence, Pyplis provides a state-of-the-art framework for more efficient and flexible analyses of UV SO2 camera data and, therefore, marks an important step forward towards more transparency, reliability and inter-comparability of the results. Pyplis has been extensively and successfully tested using data from several field campaigns. Here, the main features are introduced using a dataset obtained at Mt. Etna, Italy on 16 September 2015.

    • Geosciences, Vol. 7, Pages 130: Investigating the Apparent Seismic Diffusivity of Near-Receiver Geology at Mount St. Helens Volcano, USA

      We present an expanded approach of the diffusive approximation to map strongly scattering geological structures in volcanic environments using seismic coda intensities and a diffusive approximation. Seismic data from a remarkably consistent hydrothermal source of Long-Period (LP) earthquakes, that was active during the late 2004 portion of the 2004–2008 dome building eruption of Mount St. Helens Volcano, are used to obtain coefficient values for diffusion and attenuation, and describe the rate at which seismic energy radiates into the surrounding medium. The results are then spatially plotted as a function of near-receiver geology to generate maps of near-surface geological and geophysical features. They indicate that the diffusion coefficient is a marker of the near-receiver geology, while the attenuation coefficients are sensitive to deeper volcanic structures. As previously observed by other studies, two main scattering regimes affect the coda envelopes: a diffusive, multiple-scattering regime close to the volcanic edifice and a much weaker, single-to-multiple scattering regime at higher source-receiver offsets. Within the diffusive, multiple-scattering regime, the spatial variations of the diffusion coefficient are sufficiently robust to show the features of laterally-extended, coherent, shallow geological structures.

    • Geosciences, Vol. 7, Pages 133: Mercury Contamination of Cattle in Artisanal and Small-Scale Gold Mining in Bombana, Southeast Sulawesi, Indonesia

      The industrial mining sector is one of the main contributors to environmental damage and toxic metal pollution, although some contamination originates from natural geological sources. Due to their position at the top of the food chain, cattle tend to bioaccumulate mercury (Hg) in their bodies. We used analyses of cattle hair samples to investigate Hg contamination in cattle farmed within and outside of an artisanal and small-scale gold-mining area in Bombana, Southeast Sulawesi, Indonesia. We also examined the factors that might have influenced the toxicity, such as the environmental conditions, sex, and age of the cattle. A total of 63 hair samples were analyzed by particle-induced X-ray emission spectrometry. The mean Hg concentration was significantly higher in hair from cattle farmed within the artisanal and small-scale gold mining area (11.44 μg/g hair) than in those farmed outside the area (2.89 μg/g hair, p < 0.05). A possible cause of this is contamination by mercury persistent in terrestrial food chain. The results indicates that the level of toxic metals such as Hg need to be controlled in food sources to protect human health, especially in Bombana, Indonesia.

    • Geosciences, Vol. 7, Pages 132: Evaluating Conveyance-Based DEM Correction Technique on NED and SRTM DEMs for Flood Impact Assessment of the 2010 Cumberland River Flood

      This study assessed the uncertainty in flood impact assessment (FIA) that may be introduced by errors in moderate resolution regional and moderate resolution global Digital Elevation Models (DEM). One arc-second National Elevation Dataset (NED) and one arc-second Shuttle Radar Topography Mission (SRTM) DEMs were selected to represent moderate resolution regional and global DEMs. The relative performance for scenarios based on each of the DEMs was compared to a “control” terrain (combination of surveyed river bathymetry and a 1/3 arc-second LiDAR for floodplains)-based scenario. Furthermore, a conveyance-based DEM correction technique was applied to the DEMs for investigating the suitability of the technique on selected DEMs, and determining subsequent improvement in the FIA. The May 2010 flood on the Cumberland River near Nashville, TN, was selected as the case study. It was found that the hydraulic properties necessary to implement the selected DEM correction technique could be more readily estimated from NED compared to SRTM. However, this study also prescribed alternate methods to extract necessary hydraulic properties if the DEM quality was compromised. NED-based hydrodynamic modeling resulted in a high overestimation of the simulated flood stage, but the SRTM-based model was unable to produce any reasonable result prior to DEM correction. Nevertheless, after DEM correction, both models became stable and produced less error. Error in simulated flood consequence (i.e., total structures affected and total loss in dollars) also dropped accordingly, following the DEM correction. Therefore, application of this conveyance-based correction technique is reasonably effective on both moderate-resolution regional and global DEMs. The effectiveness of the technique on moderate resolution global DEM underscores the potential for users of remote and data-poor areas.

    • Geosciences, Vol. 7, Pages 131: Assessment by Portable Gamma Spectrometry of External Gamma Radiation Hazard due to Granitic Materials and Indoor Space Typology

      Building materials can contribute to ionizing radiation hazards due to their variable content in radioactive isotopes. Uranium, thorium, and potassium radioisotopes are present in various building materials due to their presence in raw materials: minerals and rocks. Among natural building materials, granite is one of those deserving more attention in terms of radioactive hazards. Granites are commonly used in historical buildings of NW Portugal and NW Spain, due to the geological characteristics of these areas. However, radioactive isotopes are present in variable proportions in granites, and thus, in relation to other potential building materials, granites might present a higher radiological hazard. This work discusses multivariate analysis results obtained by spectrometry of a portable range in indoor spaces, presenting different proportions of granite used as a building material in order to evaluate a typology proposed for assessing gamma radiation hazards.

    • Planning spatial sampling of the soil from an uncertain reconnaissance variogram

      Planning spatial sampling of the soil from an uncertain reconnaissance variogram R. Murray Lark, Elliott M. Hamilton, Belinda Kaninga, Kakoma K. Maseka, Moola Mutondo, Godfrey M. Sakala, and Michael J. Watts SOIL, 3, 235-244,, 2017 An advantage of geostatistics for mapping soil properties is that, given a statistical model of the variable of interest, we can make a rational decision about how densely to sample so that the map is sufficiently precise. However, uncertainty about the statistical model affects this process. In this paper we show how Bayesian methods can be used to support decision making on sampling with an uncertain model, ensuring that the probability of meeting certain levels of precision is high enough.

    • Hot regions of labile and stable soil organic carbon in Germany – Spatial variability and driving factors

      Hot regions of labile and stable soil organic carbon in Germany – Spatial variability and driving factors Cora Vos, Angélica Jaconi, Anna Jacobs, and Axel Don SOIL Discuss., https//,2017 Manuscript under review for SOIL (discussion: open, 0 comments) Soil organic carbon sequestration can be facilitated by agricultural management, but its influence is not the same on all soil carbon pools. We assessed how soil organic carbon is distributed among C pools in Germany, identified factors influencing this distribution and identified regions with high vulnerability to C losses. Explanatory variables were soil texture, C / N ratio, soil C content and pH. For some regions, the drivers were linked to the land-use history as heathlands or peatlands.

    • Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models

      Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models Madlene Nussbaum, Lorenz Walthert, Marielle Fraefel, Lucie Greiner, and Andreas Papritz SOIL, 3, 191-210,, 2017 Digital soil mapping (DSM) relates soil property data to environmental data that describe soil-forming factors. With imagery sampled from satellites or terrain analysed at multiple scales, large sets of possible input to DSM are available. We propose a new statistical framework (geoGAM) that selects parsimonious models for DSM and illustrate the application of geoGAM to two study regions. Straightforward interpretation of the modelled effects likely improves end-user acceptance of DSM products.

    • Opportunities and limitations related to the application of plant-derived lipid molecular proxies in soil science

      Opportunities and limitations related to the application of plant-derived lipid molecular proxies in soil science Boris Jansen and Guido L. B. Wiesenberg SOIL, 3, 211-234,, 2017 The application of lipids in soils as molecular proxies, also often referred to as biomarkers, has dramatically increased in the last decades. Applications range from inferring changes in past vegetation composition to unraveling the turnover of soil organic matter. However, the application of soil lipids as molecular proxies comes with several constraining factors. Here we provide a critical review of the current state of knowledge on the applicability of molecular proxies in soil science.

    • Quantitative imaging of the 3-D distribution of cation adsorption sites in undisturbed soil

      Quantitative imaging of the 3-D distribution of cation adsorption sites in undisturbed soil Hannes Keck, Bjarne W. Strobel, Jon Petter Gustafsson, and John Koestel SOIL, 3, 177-189,, 2017 Several studies have shown that the cation adsorption sites in soils are heterogeneously distributed in space. In many soil system models this knowledge is not included yet. In our study we proposed a new method to map the 3-D distribution of cation adsorption sites in undisturbed soils. The method is based on three-dimensional X-ray scanning with a contrast agent and image analysis. We are convinced that this approach will strongly aid the development of more realistic soil system models.

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