Sediment Organic Carbon in Todos Santos Bay, Baja California, Mexico

Sediment grain size and organic carbon (OC) data collected over the past 50 years, together with δ¹³C values of OC in recently collected samples, were analyzed to improve understanding of sediment OC distribution and abundance in Todos Santos Bay. Sediments in the submarine canyon at the mouth of the bay and in quiet-water locations along the shore are fine grained, high in OC, and have generally low δ¹³C values; sediments in high-energy environments are low in OC and have high δ¹³C values. A bivariate isotopic mixing model indicates that none of the sediments contain >50% terrigenous OC (average ~30%), and that the terrigenous OC content of the sediments is a small proportion of the OC content of local soils. Sediment OC composition is apparently controlled by energy-related sorting and deposition, oxidation of much of the original terrigenous OC, and replacement of some terrigenous OC by marine OC.     

A combined mathematical geophysical model for prediction of pyrite oxidation and pollutant leaching associated with a coal washing waste dump

The waste produced by coal washing process produces many environmental problems. In this study, the pollution problems associated with the waste produced by Alborz Sharghi Coal Washing Plant was investigated by mathematical modeling. The study area is located at 11 km. to Razmjah coal region and 45 km. to Tehran-Mashhad road in the north part od Iran. To achieve the goal, a few samples were taken from different depths at three points on the waste dump in order to investigate pyrite oxidation and pollution generation. The samples were then analysed, using an AA-670 Shimadzu atomic absorption to determine the fraction of pyrite remained within the waste particles. A numerical finite volume model using Phoenics package has been developed to simulate pyrite oxidation and pollution generation from the Alborz Sharghi coal washing waste dump. The pyrite oxidation reaction is described by the shrinking-core model. Gaseous diffusion is the main mechanism for the transport of oxygen through the waste. The results of numerical modelling were compared with the field observations and close agreement was achieved. A simple mathematical model incorporating advection and hydrodynamic dispersion processes was also presented in order to verify the results of geophysical time-laps method showing transportation of the pollutants through the downstream of the waste dump. Both mathematical model and geophysical time-laps method are agreed in the identification of pollutant transport emanated from the waste dump. The results of such investigations can be used for designing an effective environmental management program.     

First finds of Late Tithonian and middle-late Albian radiolarian assemblages in volcanogenic-siliceous rocks of the Amur River right lower reaches and their tectonic significance

The lithological-stratigraphic study of volcanogenic-siliceous rocks developed on the left side of the Machtovaya River, a right tributary of the Amur River, yielded the first radiolarian assemblages of the late Late Tithonian, the late Late Tithonian-early Valanginian, and the middle-late Albian age. It is established that the stratigraphic succession of volcanogenic-siliceous rocks in this area is composed of upper Tithonian-Valanginian dark red to red-brown cherts with basalts in the lower part of the section and Albian dark gray clayey cherts, olive-gray siliceous-tuffaceous argillites, and tufaceous siltstones in its upper part. The replacement of cherts by their clayey varieties likely occurred in the Aptian. The composition, structure, and age of these strata and the rocks constituting the Kiselevka-Manoma accretionary complex are different, which indicates their different tectonic origin.     

Geochemistry of magmatic rocks of the Koksharovka alkaline-ultrabasic massif,primorye, and results of trace-element modeling

New geochemical data are presented on the magmatic rocks of the Late Jurassic Koksharovka alkaline-ultrabasic massif, which is associated with deposits of vermiculite, apatite, V-bearing titanomagnetite, and placer isoferroplatinum. The REE geochemistry and strontium, oxygen, and carbon isotopic composition of carbonatites and related ijolites and pyroxenites, together with geological observations, point to the magmatic origin of the Koksharovka carbonatites. The origin of associated magmatic rocks is discussed. Trace element modeling of partial melting of mantle sources was conducted to decipher the genesis of the melts of the Koksharovka carbonatites and host titanite-kaersutite pyroxenites.     

A new concept of pedogenic nodule formation in landscapes of the Russian Far East

The typification of ferromanganese nodules (FMN) formed in subaqueous and subaerial settings and in residual materials, as well as FMN localization in various sediments and soils, is discussed. The genetic diversity of morphologically similar FMN and the transformation of FMN-bearing complexes with changes in landscapes have been established.     

Paleomagnetic studies of the Late Mesozoic deformation stage in the southern Primorye region

The analysis of paleomagnetic data available for the southern Primiorye region revealed that the studied objects were magnetized under regional remagnetization presumably during the Late Mesozoic folding and this magnetization can be interpreted as being synfolding. The interpretation is based on the parameter that characterizes the folding completion degree immediately before regional remagnetization. It is shown that the relaxation of Late Mesozoic horizontal stresses was irregular. The obtained estimates of the degree of folding completion are consistent with the available geological data and Talitskii’s model for tectonic deformations.     

Using Sequential Self-Calibration Method to Identify Conductivity Distribution: Conditioning on Tracer Test data

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases.     

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.     

Some Results on the Spatial Breakdown Point of Robust Point Estimates of the Variogram

The effect of outliers on estimates of the variogram depends on how they are distributed in space. The ‘spatial breakdown point’ is the largest proportion of observations which can be drawn from some arbitrary contaminating process without destroying a robust variogram estimator, when they are arranged in the most damaging spatial pattern. A numerical method is presented to find the spatial breakdown point for any sample array in two dimensions or more. It is shown by means of some examples that such a numerical approach is needed to determine the spatial breakdown point for two or more dimensions, even on a regular square sample grid, since previous conjectures about the spatial breakdown point in two dimensions do not hold. The ‘average spatial breakdown point’ has been used as a basis for practical guidelines on the intensity of contaminating processes that can be tolerated by robust variogram estimators. It is the largest proportion of contaminating observations in a data set such that the breakdown point of the variance estimator used to obtain point estimates of the variogram is not exceeded by the expected proportion of contaminated pairs of observations over any lag. In this paper the behaviour of the average spatial breakdown point is investigated for cases where the contaminating process is spatially dependent. It is shown that in two dimensions the average spatial breakdown point is 0.25. Finally, the ‘empirical spatial breakdown point’, a tool for the exploratory analysis of spatial data thought to contain outliers, is introduced and demonstrated using data on metal content in the soils of Sheffield, England. The empirical spatial breakdown point of a particular data set can be used to indicate whether the distribution of possible contaminants is likely to undermine a robust variogram estimator.