Geochemical characterization of heavy metal contaminated area using multivariate factorial kriging

This paper describes a geostatistical method, known as factorial kriging analysis, which is well suited for analyzing multivariate spatial information. The method involves multivariate variogram modeling, principal component analysis, and cokriging. It uses several separate correlation structures, each corresponding to a specific spatial scale, and yields a set of regionalized factors summarizing the main features of the data for each spatial scale. This method is applied to an area of high manganese-ore mining activity in Amapá State, North Brazil. Two scales of spatial variation (0.33 and 2.0 km) are identified and interpreted. The results indicate that, for the short-range structure, manganese, arsenic, iron, and cadmium are associated with human activities due to the mining work, while for the long-range structure, the high aluminum, selenium, copper, and lead concentrations, seem to be related to the natural environment. At each scale, the correlation structure is analyzed, and regionalized factors are estimated by cokriging and then mapped.     

Origin of the Tongshankou porphyry–skarn Cu–Mo deposit,eastern Yangtze craton,Eastern China: geochronological,geochemical, and Sr–Nd–Hf isotopic constraints

The Tongshankou Cu–Mo deposit, located in the westernmost Daye district of the Late Mesozoic Metallogenic Belt along the Middle-Lower reaches of the Yangtze River, eastern China, consists mainly of porphyry and skarn ores hosted in the Tongshankou granodiorite and along the contact with the Lower Triassic marine carbonates, respectively. Sensitive high-resolution ion microprobe zircon U–Pb dating constrains the crystallization of the granodiorite at 140.6 ± 2.4 Ma (1σ). Six molybdenite samples from the porphyry ores yield Re–Os isochron age of 143.8 ± 2.6 Ma (2σ), while a phlogopite sample from the skarn ores yields an ⁴⁰Ar/³⁹Ar plateau age of 143.0 ± 0.3 Ma and an isochron age of 143.8 ± 0.8 Ma (2σ), indicating an earliest Cretaceous mineralization event. The Tongshankou granodiorite has geochemical features resembling slab-derived adakites, such as high Sr (740–1,300 ppm) and enrichment in light rare earth elements (REE), low Sc (<10 ppm), Y (<13.3 ppm), and depletion in heavy REE (<1.2 ppm Yb), and resultant high Sr/Y (60–92) and La/Yb (26–75) ratios. However, they differ from typical subduction-related adakites by high K, low MgO and Mg#, and radiogenic Sr–Nd–Hf isotopic compositions, with (⁸⁷Sr/⁸⁶Sr) _t  = 0.7062–0.7067, ɛ _Nd(t) = −4.37 to −4.63, (¹⁷⁶Hf/¹⁷⁷Hf) _t  = 0.282469–0.282590, and ɛ _Hf(t) = −3.3 to −7.6. The geochemical and isotopic data, coupled with geological analysis, indicate that the Tongshankou granodiorite was most likely generated by partial melting of enriched lithospheric mantle that was previously metasomitized by slab melts related to an ancient subduction system. Magmas derived from such a source could have acquired a high oxidation state, as indicated by the assemblage of quartz–magnetite–titanite–amphibole–Mg-rich biotite in the Tongshankou granodiorite and the compositions of magmatic biotite that fall in the field between the NiNiO and magnetite–hematite buffers in the Fe³⁺–Fe²⁺–Mg diagram. Sulfur would have been present as sulfates in such highly oxidized magmas, so that chalcophile elements Cu and Mo were retained as incompatible elements in the melt, contributing to subsequent mineralization. A compilation of existing data reveals that porphyry and porphyry-related Cu–Fe–Au–Mo mineralization from Daye and other districts of the Metallogenic Belt along the Middle-Lower reaches of the Yangtze River took place coevally in the Early Cretaceous and was related to an intracontinental extensional environment, distinctly different from the arc-compressive setting of the Cenozoic age that has been responsible for the emplacement of most porphyry Cu deposits of the Pacific Rim.     

The structure of the lower crust at the Argentine continental margin, South Atlantic at 44°S

It is well established that the Argentine passive margin is of the rifted volcanic margin type. This classification is based primarily on the presence of a buried volcanic wedge beneath the continental slope, manifested by seismic data as a seaward dipping reflector sequence (SDRS). Here, we investigate the deep structure of the Argentine volcanic margin at 44°S over 200 km from the shelf to the deep oceanic Argentine Basin. We use wide-angle reflection/refraction seismic data to perform a joint travel time inversion for refracted and reflected travel times. The resulting P-wave velocity-depth model confirms the typical volcanic margin structure. An underplated body is resolved as distinctive high seismic velocity (v_p up to 7.5 km/s) feature in the lower crust in the prolongation of a seaward dipping reflector sequence. A remarkable result is that a second, isolated body of high seismic velocity (v_p up to 7.3 km/s) exists landward of the first high-velocity feature. The centres of both bodies are 60 km apart. The high-velocity lower-crustal bodies likely were emplaced during transient magmatic–volcanic events accompanying the late rifting and initial drifting stages. The lateral variability of the lower crust may be an expression of a multiple rifting process in the sense that the South Atlantic rift evolved by instantaneous breakup of longer continental margin segments. These segments are confined by transfer zones that acted as rift propagation barriers. A lower-crustal reflector was detected at 3 to 5 km above the modern Moho and probably represents the lower boundary of stretched continental crust. With this finding we suggest that the continent–ocean boundary is situated 70 km more seaward than in previous interpretations.     

Supergene geochemistry and crystal morphology of gold in a semiarid weathering environment: application to gold exploration

Oxidation of sulfide- and carbonate-rich vein gold deposits under semiarid conditions can be represented as a three-stage process, each creating supergene environments conducive to dissolution and reprecipitation of gold-silver alloys. The three-stage weathering process of sulfide-carbonate gold veins is depth-dependent, and develops from the relatively young, lowermost weathering horizon just below the water table, through an intermediate weathering horizon in the oxidation zone above the water table, and culminating in the oxide-rich upper saprolite and oxisol.Neoformed gold crystals in the weathering profile have distinct composition and morphologic characteristics from the hypogene gold crystals associated with the sulfide- and carbonate-rich ores. Two distinct types of secondary gold are present in the weathering profile: (1) gold crystals associated with sulfates and arsenates; and (2) gold crystals associated with iron and aluminum oxides/hydroxides, or with kaolinite. The distinct crystal morphologies and mineralogical associations of primary and secondary gold are useful in prospecting for gold deposits in weathered terrains.     

Tunneling of seismic body waves through thin high-velocity layers in complex structures

Summary The hybrid ray-reflectivity method is applied to the problem of the transmission of the reflected wave field through a thin high-velocity layer (or through a thin stack of high velocity layers), situated in the overburden of the reflector. In the hybrid ray-reflectivity method, the standard ray method is applied in the smooth parts of the model, and the reflectivity method is used locally at the thin high-velocity layer. With the exception of small epicentral distances, the standard ray method itself fails in such computations. The reason is that a considerable part of the energy for overcritical angles of incidence may be tunneled through the thin high-velocity layer along complex ray-paths, corresponding to inhomogeneous waves. The reflectivity method, applied locally at the thin high-velocity layer, automatically includes all inhomogeneous wave contributions. Thus, the hybrid ray-reflectivity method removes fully the limitations of the standard ray method, but still retains its main advantages, such as its applicability to 2-D and 3-D complex layered structures, flexibility, and low-cost computations. In the numerical examples, the hybrid ray-reflectivity synthetic seismograms are compared with standard ray synthetic seismograms and with full reflectivity computations. The numerical examples show that the hybrid ray-reflectivity method describes the tunneling of seismic energy through a thin high-velocity layer with sufficient accuracy.     

Ionospheric tomography using GNSS: multiplicative algebraic reconstruction technique applied to the area of Brazil

Experimental analysis was performed using multiplicative algebraic reconstruction technique (MART) to map the ionosphere over Brazil. Code and phase observations from the global navigation satellite system (GNSS) together with the international reference ionosphere (IRI) enabled the estimation of ionospheric profiles and total electron content (TEC) over the entire region. Twenty-four days of data collected from existing ground-based GNSS receivers during the recent solar maximum period were used to analyze the performance of the MART algorithm. The results were compared with four ionosondes. It was demonstrated that MART estimated the electron density peak with the same degree of accuracy as the IRI model in regions with appropriate geometrical coverage by GNSS receivers for tomographic reconstruction. In addition, the slant TEC, as estimated with MART, presented lower root-mean-square error than the TEC calculated by ionospheric maps available from the International GNSS Service (IGS). Furthermore, the daily variations of the ionosphere were better represented with the algebraic techniques, compared to the IRI model and IGS maps, enabling a correlation of the elevation of the ionosphere at higher altitudes with the equatorial ionization anomaly intensification. The tomographic representations also enabled the detection of high vertical gradients at the same instants in which ionospheric irregularities were evident.     

Bioaccumulation and depuration of Zn and Cd in mangrove oysters (Crassostrea rhizophorae, Guilding, 1828) transplanted to and from a contaminated tropical coastal lagoon

In order to study Zn and Cd accumulation and depuration, a set of oysters, Crassostrea rhizophorae, were transplanted to a metal contaminated coastal lagoon and another one was harvested there and transplanted to a non-polluted site. C. rhizophorae oysters and Perna perna mussels native from both sites were collected in order to monitor variability of metal concentration in resident populations. After three months exposure, oysters transplanted to the polluted site accumulated fourfold Zn (307-1319 microgg(-1)) without reaching the concentration level of resident oysters (9770 microgg(-1)). Cadmium concentrations had a slight but significant decrease during the same period (1.25-0.54 microgg(-1)). Oysters transplanted to the non-polluted site, showed threefold Zn depuration (6727-2404 microgg(-1)), while Cd had no significant variation (0.90-1.45 microgg(-1)). Results showed that transplanted oysters do not reach heavy metal concentrations in indigenous populations suggesting transplanted organisms would be better used to evaluate bioavailability instead of environmental concentrations.     

Conceptual fuzzy neural network model for water quality simulation

Artificial neural networks (ANNs) have been applied successfully in various fields. However, ANN models depend on large sets of historical data, and are of limited use when only vague and uncertain information is available, which leads to difficulties in defining the model architecture and a low reliability of results. A conceptual fuzzy neural network (CFNN) is proposed and applied in a water quality model to simulate the Barra Bonita reservoir system, located in the southeast region of Brazil. The CFNN model consists of a rationally‐defined architecture based on accumulated expert knowledge about variables and processes included in the model. A genetic algorithm is used as the training method for finding the parameters of fuzzy inference and the connection weights. The proposed model may handle the uncertainties related to the system itself, model parameterization, complexity of concepts involved and scarcity and inaccuracy of data. The CFNN showed greater robustness and reliability when dealing with systems for which data are considered to be vague, uncertain or incomplete. The CFNN model structure is easier to understand and to define than other ANN‐based models. Moreover, it can help to understand the basic behaviour of the system as a whole, being a successful example of cooperation between human and machine. Copyright © 2006 John Wiley & Sons, Ltd.