Spatial distribution and contamination assessment of heavy metals in surface soils of Hassi Messaoud, Algeria

An increase in heavy metal pollution in the soils of Hassi Messaoud (Algeria) due to intense industrialization and urbanization has become a serious environmental problem. There are three large industrial complexes that have been established in the region of Hassi Messaoud for petroleum extraction field and refinery. The region hosts several industrial facilities which are the main sources for hazardous wastes. Surface soil samples from 58 sampling sites (systematically sampled; 1 × 1 km regular grid), including different functional areas in Hassi Messaoud, were collected and analyzed. The results showed that the average concentrations of Cu, Ni, Mn, Pb and Zn in soil of Hassi Messaoud were up to 13.17, 35.78, 121.21, 130.97 and 61.08 mg/kg, respectively. Ni concentrations were comparable to background values, while Cu, Mn, Pb and Zn concentrations were higher than their corresponding background values. Among the functional areas, the industrial regions displayed the highest metal concentrations, while the lowest concentrations occurred in rural soil. Principal component analysis coupled with cluster analysis showed that: (1) Pb and Zn had anthropogenic sources; and (2) Ni, Cu and Mn were associated with parent materials. Contaminations in soils were classified as geoaccumulation index and enrichment factor. Pollution index values of Cu, Ni, Mn, Pb and Zn varied in the range of 0.04–5.41, 0.46–2.49, 0.01–5.73, 0.62–152.9 and 0.09–53.01, with mean values of 1.32, 1.08, 1.26, 5.64 and 3.1, respectively. The integrated pollution index (IPI) of all the analyzed samples varied from 0.42 to 31.59, with a mean of 2.48, and more than 5.45 % of samples are extremely contaminated; 18.18 % are heavily contaminated; 60 % are moderately contaminated; and others are low contaminated. The spatial distribution of IPI showed that desert and rural areas displayed relatively lower heavy metal contamination in comparison with other areas.     

Addressing Hurricane Intensity through Angular Momentum and Scale Energetics Approaches

This paper addresses two avenues for gaining insight into the hurricane intensity issue—the angular momentum approach and the scale interaction approach. In the angular momentum framework, the torques acting on a parcel's angular momentum are considered along an inflowing trajectory in order to construct the angular momentum budget. These torques are separable into three components: The pressure torque, the surface friction torque, and the cloud torque. All torques are found to diminish the angular momentum of an inflowing parcel, with the cloud torques having the most important role. In the scale interaction approach, energy exchanges among different scales within a hurricane are considered as a means of understanding hurricane intensity. It is found that the majority of kinetic energy contribution to the hurricane scales originates from potential-to-kinetic in-scale energy conversions. The contribution of mean-wave interactions in the kinetic energy varies with distance from the center and with the life stage of a storm. In the early stages, as the disorganized convection becomes organized on the hurricane scales, upscale energy transfers (i.e., from small to large scale) are found to take place in the outer radii of the storm. In a mature storm, the kinetic energy transfers are downscale, except for the inner radii.     

Seasonal transport pattern of chromium(III and VI) in a stream receiving wastewater from tanneries

Water, suspended matter and sediment samples from a system heavily impacted by wastewater from numerous small tanneries (the upper Dunajec River, southern Poland) were collected to establish the annual cycle of Cr. To study possible oxidation processes the speciation of Cr and Mn concentrations were also investigated. This study showed that Cr(III and VI) temporal and spatial distributions are regulated by coupled anthropogenic (source location and emissions) and hydrologic factors (water flow and particle transport). Chromium(III) concentrations in all compartments varied seasonally as a function of the hydrological regime, production cycle in tanneries and distance from the discharge location. Cr(III) was largely associated with the particulate phase and rapidly deposited in river bed sediments. Contaminated river sediments were however flushed during flood periods to the reservoir located downstream from tanneries. During the tanning season (November to March), Chromium(III) concentrations in the water column and total Cr concentration in sediments exceeded relevant ecotoxicological guidelines only upstream from the reservoir, which trapped about 70% of the annual Cr(III) load transported by the Dunajec river. A correlation between Cr(VI)/Cr(III) ratios and Mn concentration in sediments downstream from the reservoir suggests the possibility of Cr(III) oxidation in natural conditions.     

Lithological and spatial controls on the distribution of quartz veins in andesite- and rhyolite-hosted epithermal Au–Ag deposits of the Hauraki Goldfield, New Zealand

Vein distributions in line samples from four epithermal Au–Ag deposits of the Hauraki Goldfield were logged and quantified by vein spacing, vein density, vein thickness and percentage of vein extension. One deposit is hosted in andesite lavas (Martha Hill), one in andesite lavas and dacite porphyry, dacitic tuffs and pyroclastic breccias (Golden Cross), and two in rhyolite lavas and rhyolitic tuffs with minor andesite lavas or andesite dikes (Ohui and Wharekirauponga). The vein systems in these deposits form fault-controlled arrays of extensional veins. Vein spacing distributions are non-fractal over two to three orders of magnitude (1 mm to 5 m), and therefore fractal dimension statistics are not applicable. The coefficient of variation (C_v) of vein spacing was used as a measure of the degree of vein clustering. Rock type has a marked influence on vein spacing distributions, with veining in rhyolite lava having lower average thickness and percentage extension, but a generally higher degree of vein clustering compared with veining in andesite lava in the same deposit. Vein spacing distributions in well-jointed lithologies, mainly andesite lava, have C_v values (0.8–1.2) that are indicative of anticlustered to weakly clustered patterns, particularly in the vein stockwork of the upper part of the Golden Cross deposit. These C_v values are consistent with field observations that joints are a major control on vein spacing. In the poorly jointed dacitic and rhyolitic rocks, the veins are weakly to strongly clustered as shown by higher C_v values (1.2–2.4), and are commonly associated with normal faults. Overall, andesite lava and dacite porphyry and pyroclastics host thicker and more persistent veins than rhyolite lava and tuff. These larger veins contain significant volumes of high-grade gold mineralisation. The higher chemical reactivity to hydrothermal fluids of andesite and dacite compared with rhyolite may have aided propagation and thickening of the veins in andesite-hosted deposits. Within an individual epithermal deposit, location close to thick veins, representing major fluid conduits, commonly overrides the effect of different lithologies. Sites that are deeper and located within or adjacent to major vein structures have higher average vein thickness, percentage extension and degree of vein clustering. Systematic collection and analysis of vein spacing, thickness and density data can be used to define trends that are useful in the exploration of gold-bearing epithermal vein deposits. Received: 25 August 1998 / Accepted: 23 December 1999     

StalAge – An algorithm designed for construction of speleothem age models

Here we present a new algorithm (StalAge), which is designed to construct speleothem age models. The algorithm uses U-series ages and their corresponding age uncertainty for modelling and also includes stratigraphic information in order to further constrain and improve the age model. StalAge is applicable to problematic datasets that include outliers, age inversions, hiatuses and large changes in growth rate. Manual selection of potentially inaccurate ages prior to application is not required. StalAge can be applied by the general, non-expert user and has no adjustable free parameters. This offers the highest degree of reproducibility and comparability of speleothem records from different studies. StalAge consists of three major steps. Firstly, major outliers are identified. Secondly, age data are screened for minor outliers and age inversions, and the uncertainty of potential outliers is increased using an iterative procedure. Finally, the age model and corresponding 95%-confidence limits are calculated by a Monte-Carlo simulation fitting ensembles of straight lines to sub-sets of the age data.We apply StalAge to a synthetic stalagmite ’sample’ including several problematic features in order to test its performance and robustness. The true age is mostly within the 95%-confidence age limits of StalAge showing that the calculated age models are accurate even for very difficult samples. We also apply StalAge to three published speleothem datasets. One of those is annually laminated, and the lamina counting chronology agrees with the age model calculated by StalAge. For the other two speleothems the resulting age models are similar to the published age models, which are both based on smoothing splines. Calculated uncertainties are in the range of those calculated by combined application of Bayesian chronological ordering and a spline, showing that StalAge is efficient in using stratigraphic information in order to reduce age model uncertainty.The algorithm is written in the open source statistical software R and available from the authors or as an electronic supplement of this paper.     

Distribution of some ions and minor gaseous components by concentrations in the atmospheric surface layer of some regions in Eastern Siberia and the Far East

We consider the resemblance between the ion composition of the fraction of soluble aerosols and gaseous admixtures in the atmospheric surface layer at the high-level Mondy station (East Sayan), those in the Listvyanka settlement south of Lake Baikal, in the city of Irkutsk, and at the Primorskaya station near the city of Ussuriysk (Primorskii krai). We use measurement data on the concentrations of the following ions: HCO ₃ ^? , SO ₄ ^2? , NO ₃ ^? , Cl^?, H⁺, Na⁺, K⁺, Mg²⁺, Ca²⁺ in the soluble fraction of aerosols and gases HNO₃, HCl, NH₃, and SO₂ in air samples over a 10-year period conducted in the mode of online monitoring. We found the lognormal form of distributions of concentrations of each of the abovementioned components according to the number of samples. A versatile scheme of the distribution of mean geometric concentrations of atmospheric components was proposed for all four groups.     

Stratigraphic evolution of a fluvial–eolian succession: The example of the Upper Jurassic—Lower Cretaceous Guará and Botucatu formations, Paraná Basin, Southernmost Brazil

The Guará and Botucatu formations comprise an 80 to 120 m thick continental succession that crops out on the western portion of the Rio Grande do Sul State (Southernmost Brazil). The Guará Formation (Upper Jurassic) displays a well-defined facies shift along its outcrop belt. On its northern portion it is characterised by coarse-grained to conglomeratic sandstones with trough and planar cross-bedding, as well as low-angle lamination, which are interpreted to represent braided river deposits. Southwards these fluvial facies thin out and interfinger with fine- to medium-grained sandstones with large-scale cross-stratification and horizontal lamination, interpreted as eolian dune and eolian sand sheets deposits, respectively. The Botucatu Formation is characterised by large-scale cross-strata formed by successive climbing of eolian dunes, without interdune and/or fluvial accumulation (dry eolian system). The contact between the Guará and the Botucatu formations is delineated by a basin-wide deflation surface (supersurface). The abrupt change in the depositional conditions that took place across this supersurface suggests a major climate change, from semi-arid (Upper Jurassic) to hyper-arid (Lower Cretaceous) conditions. A rearrangement of the Paraná Basin depocenters is contemporaneous to this climate change, which seems to have changed from a more restrict accumulation area in the Guará Formation to a wider sedimentary context in the Botucatu Formation.     

On characterizing the temporal dominance patterns of model parameters and processes

Diagnostic analyses of hydrological models intend to improve the understanding of how processes and their dynamics are represented in models. Temporal patterns of parameter dominance could be precisely characterized with a temporally resolved parameter sensitivity analysis. In this way, the discharge conditions are characterized, that lead to a parameter dominance in the model. To achieve this, the analysis of temporal dynamics in parameter sensitivity is enhanced by including additional information in a three‐tiered framework on different aggregation levels. Firstly, temporal dynamics of parameter sensitivity provide daily time series of their sensitivities to detect variations in the dominance of model parameters. Secondly, the daily sensitivities are related to the flow duration curve (FDC) to emphasize high sensitivities of model parameters in relation to specific discharge magnitudes. Thirdly, parameter sensitivities are monthly averaged separately for five segments of the FDC to detect typical patterns of parameter dominances for different discharge magnitudes. The three methodical steps are applied on two contrasting catchments (upland and lowland catchment) to demonstrate how the temporal patterns of parameter dynamics represent different hydrological regimes. The discharge dynamic in the lowland catchment is controlled by groundwater parameters for all discharge magnitudes. In contrast, different processes are relevant in the upland catchment, because the dominances of parameters from fast and slow runoff components in the upland catchment are changing over the year for the different discharge magnitudes. The joined interpretation of these three diagnostic steps provides deeper insights of how model parameters represent hydrological dynamics in models for different discharge magnitudes. Thus, this diagnostic framework leads to a better characterization of model parameters and their temporal dynamics and helps to understand the process behaviour in hydrological models. Copyright © 2015 John Wiley & Sons, Ltd.