Analysis of undisturbed layers of a waste deposit landfill – Insights into the transformation and transport of organic contaminants

Comprehensive GC/MS analysis was applied to both the mobile liquid phase (seepage water) and the immobile solid matter of discrete layers derived from a waste deposit landfill. The vertical distribution of organic compounds supports information on the transport, transfer and transformation processes with depth and, consequently, with time.Numerous low molecular weight organic contaminants of natural and xenobiotic origin were identified and partially quantified. Several were selected to act as molecular indicators for different processes. Interpretation of their occurrence and concentration profiles (considering possible waste sources) and their molecular properties allowed us to (i) differentiate immobile and mobile fractions, (ii) reveal restrictions in the vertical transport by transfer processes between particulate and water phase, (iii) identify dynamic accumulations of individual contaminants and (iv) estimate approximate residence times. In addition, intensive degradation processes were pointed out for the natural fraction of the organic matter by way of determination of specific transformation products. Besides the transformation of natural components, transformation of numerous xenobiotics was recognised. In particular, with respect to an important group of contaminants, the phthalate-based plasticisers, a detailed view of (i) the influence of transfer and transport phenomena on transformation processes as well as (ii) the consecutive appearance of different degradation steps in both seepage water and solid waste was pointed out. The information provides a valuable base for the prediction of the long term behaviour of organic contaminants in waste deposit landfills.     

Predicting selenite adsorption by soils using soil chemical parameters in the constant capacitance model

The constant capacitance model, a chemical surface complexation model, was applied to selenite, Se(IV), adsorption on 36 soils selected for variation in soil chemical properties. The constant capacitance model was able to fit Se(IV) adsorption by optimizing one monodentate Se(IV) surface complexation constant and the surface protonation constant. A general regression model was developed for predicting these surface complexation constants for Se(IV) from easily measured soil chemical characteristics. These chemical properties were inorganic carbon content, organic carbon content, iron oxide content, aluminum oxide content, and surface area. The prediction equations were used to obtain values for the surface complexation constants for four additional soils, thereby providing a completely independent evaluation of the ability of the constant capacitance model to describe Se(IV) adsorption. The model’s ability to predict Se(IV) adsorption was quantitative on one soil and semi-quantitative on three soils. Incorporation of these prediction equations into chemical speciation-transport models will allow simulation of soil solution Se(IV) concentrations under diverse non-calcareous agricultural and environmental conditions without the requirement of soil specific adsorption data and subsequent parameter optimization.     

Cryptotephras in the Lateglacial ICDP Dead Sea sediment record and their implications for chronology

Due to a lack of visible tephras in the Dead Sea record, this unique palaeoenvironmental archive is largely unconnected to the well-established Mediterranean tephrostratigraphy. Here we present first results of the ongoing search for cryptotephras in the International Continental Drilling Program (ICDP) sediment core from the deep Dead Sea basin. This study focusses on the Lateglacial (~15–11.4 cal. ka BP), when Lake Lisan – the precursor of the Dead Sea – shrank from its glacial highstand to the Holocene low levels. We developed a glass shard separation protocol and counting procedure that is adapted to the extreme salinity and sediment recycling of the Dead Sea. Cryptotephra is abundant in the Dead Sea record (up to ~100 shards cm^-3), but often glasses are physically and/or chemically altered. Six glass samples from five tephra horizons reveal a heterogeneous geochemical composition, with mainly rhyolitic and some trachytic glasses potentially sourced from Italian, Aegean and Anatolian volcanoes. Most shards likely originate from the eastern Anatolian volcanic province and can be correlated using major element analyses with tephra deposits from swarm eruptions of the Süphan Volcano ~13 ka BP and with ashes from Nemrut Volcano, presumably the Lake Van V-16 volcanic layer at ~13.8 ka BP. In addition to glasses that match the TM-10-1 from Lago Grande di Monticchio (15 820±790 cal. a BP) tentatively correlated with the St. Angelo Tuff of Ischia, we further identified a cryptotephra with glass analyses which are chemically identical with those of the PhT1 tephra in the Philippon peat record (13.9–10.5 ka BP), and also a compositional match for the glass analyses of the Santorini Cape Riva Tephra (Y-2 marine tephra, 22 024±642 cal. a BP). These first results demonstrate the great potential of cryptotephrochronology in the Dead Sea record for improving its chronology and connecting the Levantine region to the Mediterranean tephra framework.     

Homogenization of the transport behavior of nonlinearly adsorbing pollutants in physically and chemically heterogeneous aquifers

This paper addresses the question of how spatial variability in the hydraulic and chemical properties of groundwater systems affects the transport and sorption behavior of pollutants at the field scale. In this paper, we limit our investigations on pollutants that adsorb according to an equilibrium controlled nonlinear Freundlich sorption isotherm. The new contribution of this paper is take into account not only spatially variable Freundlich distribution coefficients _KS$K_S$ but spatially variable Freundlich nonlinearity parameters p as well. Using a homogenization theory approach, we shortly review the impact of spatially variable hydraulic properties on the transport and extend the theory to spatially variable chemical properties. We show that spatially variable Freundlich exponents cause a very different field scale transport and sorption behavior than spatial variations in the distribution coefficients only since in the first case field scale Freundlich parameters and field scale dispersion coefficients become concentration dependent. In particular, field scale retardation is much larger than small-scale retardation.     

Effects of an outer thin stably stratified layer on planetary dynamos

The presence of outer stably stratified layers in planetary cores has been suggested for Earth, Saturn and Mercury. In this study, we use a 3-D numerical dynamo model to investigate the effects of a thin stable layer surrounding a convecting interior on the produced magnetic field. We find that a stable layer can destabilize the field morphology through a thermal wind that produces unfavorable zonal flows throughout the core. The direction of these zonal flows is prograde in equatorial regions, unlike a model with no stable layer that has retrograde equatorial flows. Our models therefore suggest that the Earth does not have a stable layer since we observe a westward drift as opposed to an eastward drift. For Saturn, we find that due to coupling of the flows in the stable and unstable layers, the layer does not act to shear out the non-axisymmetry in the observed magnetic field, and therefore cannot explain Saturn’s axisymmetric magnetic field. For Mercury, we find that if the stable layer is thin, it can actively produce strong or weak surface fields and not necessarily attenuate smaller scale features through the skin effect.     

Semiparametric regression models for spatial prediction and uncertainty quantification of soil attributes

In many studies, the distribution of soil attributes depends on both spatial location and environmental factors, and prediction and process identification are performed using existing methods such as kriging. However, it is often too restrictive to model soil attributes as dependent on a known, parametric function of environmental factors, which kriging typically assumes. This paper investigates a semiparametric approach for identifying and modeling the nonlinear relationships of spatially dependent soil constituent levels with environmental variables and obtaining point and interval predictions over a spatial region. Frequentist and Bayesian versions of the proposed method are applied to measured soil nitrogen levels throughout Florida, USA and are compared to competing models, including frequentist and Bayesian kriging, based an array of point and interval measures of out-of-sample forecast quality. The semiparametric models outperformed competing models in all cases. Bayesian semiparametric models yielded the best predictive results and provided empirical coverage probability nearly equal to nominal.     

A Critical Analysis of Transverse Dispersivity Field Data

Transverse dispersion, or tracer spreading orthogonal to the mean flow direction, which is relevant e.g, for quantifying bio-degradation of contaminant plumes or mixing of reactive solutes, has been studied in the literature less than the longitudinal one. Inferring transverse dispersion coefficients from field experiments is a difficult and error-prone task, requiring a spatial resolution of solute plumes which is not easily achievable in applications. In absence of field data, it is a questionable common practice to set transverse dispersivities as a fraction of the longitudinal one, with the ratio 1/10 being the most prevalent. We collected estimates of field-scale transverse dispersivities from existing publications and explored possible scale relationships as guidance criteria for applications. Our investigation showed that a large number of estimates available in the literature are of low reliability and should be discarded from further analysis. The remaining reliable estimates are formation-specific, span three orders of magnitude and do not show any clear scale-dependence on the plume traveled distance. The ratios with the longitudinal dispersivity are also site specific and vary widely. The reliability of transverse dispersivities depends significantly on the type of field experiment and method of data analysis. In applications where transverse dispersion plays a significant role, inference of transverse dispersivities should be part of site characterization with the transverse dispersivity estimated as an independent parameter rather than related heuristically to longitudinal dispersivity.     

Strategies to improve the explanatory power of a dynamic slope stability model by enhancing land cover parameterisation and model complexity

Despite the importance of land cover on landscape hydrology and slope stability, the representation of land cover dynamics in physically based models and their associated ecohydrological effects on slope stability is rather scarce. In this study, we assess the impact of different levels of complexity in land cover parameterisation on the explanatory power of a dynamic and process-based spatial slope stability model. Firstly, we present available and collected data sets and account for the stepwise parameterisation of the model. Secondly, we present approaches to simulate land cover: 1) a grassland landscape without forest coverage; 2) spatially static forest conditions, in which we assume limited knowledge about forest composition; 3) more detailed information of forested areas based on the computation of leaf area development and the implementation of vegetation-related processes; 4) similar to the third approach but with the additional consideration of the spatial expansion and vertical growth of vegetation. Lastly, the model is calibrated based on meteorological data sets and groundwater measurements. The model results are quantitatively validated for two landslide-triggering events that occurred in Western Austria. Predictive performances are estimated using the Area Under the receiver operating characteristic Curve (AUC). Our findings indicate that the performance of the slope stability model was strongly determined by model complexity and land cover parameterisation. The implementation of leaf area development and land cover dynamics further yield an acceptable predictive performance (AUC ~0.71-0.75) and a better conservativeness of the predicted unstable areas (FoC ~0.71). The consideration of dynamic land cover expansion provided better performances than the solely consideration of leaf area development. The results of this study highlight that an increase of effort in the land cover parameterisation of a dynamic slope stability model can increase the explanatory power of the model. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.