Trace elements in high-S subbituminous coals from the teruel Mining District, northeast Spain

The elemental composition of high temperature ash (750°C) and forms of S were studied in 25 coal seams from the Escucha Formation (Middle Albian) in the Teruel Mining District, northeast Spain. The principal analytical method was ICP-MS, but ICP-ES was also used in the determination of some trace elements. The analytical data show wide ranges of trace element cotnents among the coal seams studied, even in the vertical profile of a single coal seam. These wide ranges of the trace element concentrations are attributed to both syngenetic and epigenetic processes.When a comparison was made between the average trace element contents of the Teruel Mining District coals, and those of the average content in worldwide coals, the Teruel coals show slightly higher concentrations of Be and U, and lower concentrations of Ba, Cd, Mn, Pb, Sr and Zr. Further, three main groups of trace elements were differentiated on the basis of the inorganic/organic association: (1) trace elements with inorganic affinity; Ba, Ce, Co, Cr, La, Mn, Ni, Rb and Zr. Between these, Ba, Ce, Cr and Rb show a well defined correlation with the clay mineral content, and Co and Ni with pyritic-S content; (2) trace elements with an intermediate (mixed) affinity; As, Cd, Cu, Dy, Er, Eu, Gd, Ge, Ho, Lu, Mo, Nd, Pb, Pr, Sb, Sm, Sr, Tb, Th, Tm, U, Yb and Zn. In this group, As, Cd, Cu, Ge, Mo, Th, U and Zn show a weak trend associated with the mineral matter and Sr with the organic matter; and (3) Be shows an organic affinity. The high mineral matter content (21.3% HTA) of the Teruel coals may account for the great number of elements with inorganic affinity. This classification represents a general trend, but the results show that the affinities of some trace elements (e.g. As, Sb and Zn) may vary from one coal seam to another in the Teruel Mining District.     

Variance component estimation applied to satellite laser ranging

The variance component estimation (VCE) method as developed by Helmert has been applied to the global SLR data set for the year 1987. In the first part of this study the observations have been divided into two groups: those from ruby and YAG laser systems, and their weights estimated over several months. It was found that the weights of both sets of stations altered slightly from month to month, but that, not surprisingly, the YAG systems consistently outperformed those based on ruby lasers. The major part of this paper then considers the estimation of the variance components (i.e. weights) at each SLR station from month to month. These were tested using the F-statistic and, although it indicated that most stations had significant temporal variations, they were generally small compared with the differences between the stations themselves, i.e. the method has been shown to be capable of discriminating between the precision with which the various laser stations are operating. The station coordinates and baseline lengths computed using both a priori, and estimated, weights where also compared and this showed that changes in the weights can have significant effects on the estimation of the station positions, particularly in the z component, and on the baseline lengths - so proving the importance of proper stochastic modelling when processing SLR data.     

Seismic damage assessment based on regional synthetic ground motion dataset: a case study for Erzincan,Turkey

Estimation of seismic losses is a fundamental step in risk mitigation in urban regions. Structural damage patterns depend on the regional seismic properties and the local building vulnerability. In this study, a framework for seismic damage estimation is proposed where the local building fragilities are modeled based on a set of simulated ground motions in the region of interest. For this purpose, first, ground motion records are simulated for a set of scenario events using stochastic finite-fault methodology. Then, existing building stock is classified into specific building types represented with equivalent single-degree-of-freedom models. The response statistics of these models are evaluated through nonlinear time history analysis with the simulated ground motions. Fragility curves for the classified structural types are derived and discussed. The study area is Erzincan (Turkey), which is located on a pull-apart basin underlain by soft sediments in the conjunction of three active faults as right-lateral North Anatolian Fault, left-lateral North East Anatolian Fault, and left-lateral Ovacik Fault. Erzincan city center experienced devastating earthquakes in the past including the December 27, 1939 (Ms = 8.0) and the March 13, 1992 (Mw?=?6.6) events. The application of the proposed method is performed to estimate the spatial distribution of the damage after the 1992 event. The estimated results are compared against the corresponding observed damage levels yielding a reasonable match in between. After the validation exercise, a potential scenario event of Mw?=?7.0 is simulated in the study region. The corresponding damage distribution indicates a significant risk within the urban area.     

Fossil findings from the Sıcak Çermik fissure ridge-type travertines and possible hominid tracks,Sivas, Central Turkey

S?cak Çermik (Sivas) is an important geothermal and recent travertine formation area in Central Anatolia. The majority of travertines found in the region comprise fissure-ridge type travertines according to morphological classification. At the location called Tepe Çermik within the travertine area, fill containing fossil bone fragments of Equus sp., Bovidae and other abundant animals formed within the fracture axis of a N–S striking fissure-ridge travertine developed under control of tectonic forces. The finds of these fossils in fissure-ridge travertines linked to tectonic forces indicates formation of a unique fossil environment created under the control of these forces. The Accelerator Mass Spectrometry Radiocarbon Dating analyses of fossils from the study area determined the fills were older than 43,000 years. The U/Th age of a sample from the most recently-formed banded travertine in the axis of the fracture was identified as 278,540 ± 18,436 years. As a result, the ages of fossils found within this fill are thought to be between 43,000 and 278,540 ± 18,436 years old. The high amount of perissodactyla and artiodactyla fossils found within fill in the axis of the fissure-ridge travertine probably indicates the presence of hominids who chose the region for hunting or settlement. The Equus sp. and Bovidae fossil samples found in the axis of the fracture indicate that in the dry and cold glacial period the paleogeography in a large portion of Anatolia comprised desert-like steppe.     

A case study of in situ oil contamination in a mangrove swamp (Rio De Janeiro, Brazil)

Mangroves are sensitive ecosystems of prominent ecological value that lamentably have lost much of their areas across the world. The vulnerability of mangroves grown in proximity to cities requires the development of new technologies for the remediation of acute oil spills and chronic contaminations. Studies on oil remediation are usually performed with in vitro microcosms whereas in situ experiments are rare. The aim of this work was to evaluate oil degradation on mangrove ecosystems using in situ microcosms seeded with an indigenous hydrocarbonoclastic bacterial consortium (HBC). Although the potential degradation of oil through HBC has been reported, their seeding directly on the sediment did not stimulate oil degradation during the experimental period. This is probably due to the availability of carbon sources that are easier to degrade than petroleum hydrocarbons. Our results emphasize the fragility of mangrove ecosystems during accidental oil spills and also the need for more efficient technologies for their remediation.     

Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network （ML-CNN） is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.