Application of multifractal modeling technique in systematic geochemical stream sediment survey to identify copper anomalies: A case study from Ahar,Azarbaijan, Northwest Iran

This research is based on the application of stream sediments to mineral exploration. Identifying the geochemical anomalies from background is a fundamental task in exploration geochemistry. This paper applied the element concentration–area (C–A) model, to separating the geochemical anomalies from background based on a fractal approach and for the compilation of geochemical mapping from stream sediment samples (n = 620) of the Ahar region (Iran), where some Cu mineralization occurs. Comparisons of the known copper occurrences against the anomalous area created using thresholds from C–A method illustrate these hits. All of known Cu mineralizations and moreover defines two extra Cu anomaly districts. Additional sampling (n = 186) around new Cu anomaly confirms this anomaly within the district.     

A comparison study of the C–A and S–A models with singularity analysis to identify geochemical anomalies in covered areas

Fractal/multifractal modeling of geochemical data is an interesting topic in the field of applied geochemistry. Identification of weak anomalies for mineral exploration in covered areas is one of the most challenging tasks for utilization of geochemical data. In this study, three fractal models, consisting of the concentration–area (C–A), spectrum–area (S–A) and singularity index models were applied to identify geochemical anomalies in the covered area located in the Chaobuleng Fe polymetallic district, Inner Mongolia (China). The results show that (1) the grassland cover weakens the concentrations of geochemical elements; (2) the C–A model has a limitation to identify weak anomalies in covered areas; (3) the S–A model is a powerful tool to decompose mixed geochemical patterns into a geochemical anomaly map and a varied geochemical background map but suffers edge effects in an irregular shaped study area; and (4) the singularity index is a useful tool to identify weak geochemical anomalies.     

A New Model for Quantifying Anisotropic Scale Invariance and for Decomposition of Mixing Patterns

A new power–law function has been derived to represent the relationship between area of the set consisting of wave numbers with spectral energy density above S (A(>S)) on the two-dimensional frequency plane and S. The power–law relation holds if the field concerned possessing isotropic scale invariance or generalized scaling invariance involves rotational and ratio-scale changing transforms. The equation is valid for dealing with common exploration geophysical and geochemical fields encountered in mineral exploration and environmental assessment. This power–law function not only provides a new model for characterizing anisotropic scaling invariance for generalized scaling field, for example, estimating the power exponent of power spectrum of generalized scale invariance measure in frequency domain, but also forms a theoretical base for the S–A filtering technique developed for decomposing a mixing field into components on the basis of distinct scaling properties in the frequency domain. It is demonstrated that the method has potential to become a general technique for image processing and pattern recognition.     

Mapping geochemical singularity using multifractal analysis: Application to anomaly definition on stream sediments data from Funin Sheet,Yunnan, China

Most conventional statistical methods aiming at defining geochemical concentration thresholds for separating anomalies from background have limited effectiveness in areas with complex geological settings. This paper uses multifractal analysis to combine the characteristics of geochemical frequency distribution and spatial dispersion in order to map geochemical singularities instead of using conventional statistically derived concentration thresholds. The model, termed radius–areal Productivity (r–P) model, employs a stable measure and a scale-increasing method to estimate geochemical singularities spatially on geochemical landscape for delineating potential anomalies. The model is applied to geochemical data of regional stream sediments from the Funin Sheet, Yunnan, China.     

Geodynamics and underlying bedrock of the magnetically active crust layer of the Lut block,Eastern Iran

The Curie point depth map of Eastern Iran was constituted from spectral analysis of the aeromagnetic data. The reduction to pole (RTP) was applied to the magnetic anomaly data. The Curie point depth values from 165 overlapping blocks, 100 × 100 km in size, have been estimated. The Curie point depth method provides a relationship between the 2-D FFT power spectrum of the magnetic anomalies and the depth of magnetic sources by transforming the spatial data into the frequency domain. The centroid and top depth of the magnetic sources (respectively Z₀ and Z_t) is calculated from radially averaged log power spectrum for each block. Finally, the Curie point depth of Eastern Iran is obtained by Z_b = 2Z₀–Z_t. The highest value of 24 km is located in eastern and western boundaries of the Lut block, and the lowest value of 12 km is located at north of study area. The shallow depths in the Curie-point depth map are well correlated with the young volcanic areas and geothermal potential fields. Geothermal gradient ranging from 24 to 45°C/km. The deduced thermal structure in eastern Iran has a relationship with orogenic collapse associated with delamination of thickened lithospheric root between the Lut and Afghan continental blocks.     

Estimation of seismic hazard and risks for the Himalayas and surrounding regions based on Unified Scaling Law for Earthquakes

To estimate seismic hazard, the basic law of seismicity, the Gutenberg–Richter recurrence relation, is applied in a modified form involving a spatial term: $\log N\left( {M,\;L} \right) = A - B\left( {M - 5} \right) + C\log L$ , where N(M,L) is the expected annual number of earthquakes of a certain magnitude M within an area of linear size L. The parameters A, B, and C of this Unified Scaling Law for Earthquakes (USLE) in the Himalayas and surrounding regions have been studied on the basis of a variable space and time-scale approach. The observed temporal variability of the A, B, and C coefficients indicates significant changes of seismic activity at the time scales of a few decades. At global scale, the value of A ranges mainly between ?1.0 and 0.5, which determines the average rate of earthquakes that accordingly differs by a factor of 30 or more. The value of B concentrates about 0.9 ranging from under 0.6 to above 1.1, while the fractal dimension of the local seismic prone setting, C, changes from 0.5 to 1.4 and larger. For Himalayan region, the values of A, B, and C have been estimated mainly ranging from ?1.6 to ?1.0, from 0.8 to 1.3, and from 1.0 to 1.4, respectively. We have used the deterministic approach to map the local value of the expected peak ground acceleration (PGA) from the USLE estimated maximum magnitude or, if reliable estimation was not possible, from the observed maximum magnitude during 1900–2012. In result, the seismic hazard map of the Himalayas with spatially distributed PGA was prepared. Further, an attempt is made to generate a series of the earthquake risk maps of the region based on the population density exposed to the seismic hazard.     

Identification of karst features with spectral analysis on the seismic reflection data

The use of high-resolution seismic tools to investigate karst terrain has had limited success due to the ambiguous seismic events caused by lateral heterogeneities of the sedimentary cover, as well as the superimposition of surface waves. To address these problems, a spectral analysis scheme is proposed on the seismic reflection data to characterize karst features in this paper. First, the S-transform is applied to suppress the ground roll. As a type of time–frequency transform, the S-transform provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum. Application of a filter based on the S-transform attenuates ground roll in a time–frequency domain. Then, the continuous wavelet transform is employed for the time–frequency mapping of potential karst features, which are featured as frequency differentiation anomalies. Synthetic model and real-data example validate the efficiency of the spectral analysis scheme for the detection of karst features.     

Comparison of U-spatial statistics and C–A fractal models for delineating anomaly patterns of porphyry-type Cu geochemical signatures in the Varzaghan district,NW Iran

The delineation of populations of stream sediment geochemical data is a crucial task in regional exploration surveys. In this contribution, uni-element stream sediment geochemical data of Cu, Au, Mo, and Bi have been subjected to two reliable anomaly-background separation methods, namely, the concentration-area (C–A) fractal and the U-spatial statistics methods to separate geochemical anomalies related to porphyry-type Cu mineralization in northwest Iran. The quantitative comparison of the delineated geochemical populations using the modified success-rate curves revealed the superiority of the U-spatial statistics method over the fractal model. Moreover, geochemical maps of investigated elements revealed strongly positive correlations between strong anomalies and Oligocene–Miocene intrusions in the study area. Therefore, follow-up exploration programs should focus on these areas.     

Vertical geochemical variations and arsenic mobilization in the shallow alluvial aquifers of the Chapai-Nawabganj District, northwestern Bangladesh: implication of siderite precipitation

Core sediments from three disturbed boreholes (JOR, GHAT, and RAJ) and two undisturbed boreholes (DW1 and DW2) were collected in the study area of the Chapai-Nawabganj district of northwestern Bangladesh for geochemical analyses. In the study area, groundwater samples from fourteen As-contained private wells and five nested piezometers at both the DW1 and DW2 boreholes were also collected and analyzed. The groundwater arsenic concentrations in the uppermost aquifer (10–40 m of depth) range from 3 to 315 μg/L (mean 47.73 ± 73.41 μg/L), while the arsenic content in sediments range from 2 to 14 mg/kg (mean 4.36 ± 3.34 mg/kg). An environmental scanning electron microscope (ESEM) with an energy dispersive X-ray spectrometer was used to investigate the presence of major and trace elements in the sediments. Groundwaters in the study area are generally the Ca–HCO₃ type with high concentrations of As, but low levels of Fe, Mn, NO₃ ^? and SO ₄ ^?2 . The concentrations of As, Fe, Mn decrease with depth in the groundwater, showing vertical geochemical variations in the study area. Statistical analysis clearly shows that As is closely associated with Fe and Mn in the sediments of the JOR core (r = 0.87, p < 0.05 for Fe and r = 0.78, p < 0.05 for Mn) and GHAT core (r = 0.95, p < 0.05 for Fe and r = 0.93, p < 0.05 for Mn), while As is not correlated with Fe and Mn in groundwater. The comparatively low Fe and Mn concentrations in some groundwater and the ESEM image revealed that siderite precipitated as a secondary mineral on the surface of the sediment particles. The correlations along with results of sequential extraction experiments indicated that reductive dissolution of FeOOH and MnOOH represents a mechanism for releasing arsenic into the groundwater.     

Mineralogy and mineral chemistry of Bi-minerals: Constraints on ore genesis of the Beiya giant porphyry-skarn gold deposit,southwestern China

The Beiya deposit, located in the Sanjiang Tethyan tectonic domain (SW China), is the third largest Au deposit in China (323 t Au @ 2.47 g/t). As a porphyry-skarn deposit, Beiya is related to Cenozoic (Himalayan) alkaline porphyries. Abundant Bi-minerals have been recognized from both the porphyry- and skarn- ores, comprising bismuthinite, Bi–Cu sulfosalts (emplectite, wittichenite), Bi–Pb sulfosalts (galenobismutite, cosalite), Bi–Ag sulfosalt (matildite), Bi–Cu–Pb sulfosalts (bismuthinite derivatives), Bi–Pb–Ag sulfosalts (lillianite homologs, galena-matildite series), and Bi chalcogenides (tsumoite, the unnamed Bi₂Te, the unnamed Ag₄Bi₃Te₃, tetradymite, and the unnamed (Bi, Pb)₃(Te, S)₄). Native bismuth and maldonite are also found in the skarn ores. The arsenopyrite geothermometer reveals that the porphyry Au mineralization took place at temperatures in the range of 350–450 °C and at log fS₂ in the range of − 8.0 to − 5.5, respectively. In contrast, the Beiya Bi-mineral assemblages indicate that the skarn ore-forming fluids had minimum temperatures of 230–175 °C (prevailing temperatures exceeding 271 °C) and fluctuating fS₂–fTe₂ conditions. We also model a prolonged skarn Au mineralization history at Beiya, including at least two episodes of Bi melts scavenging Au. We thus suggest that this process was among the most effective Au-enrichment mechanisms at Beiya.     

Hybrid outranking of geospatial data: Multi attributive ideal-real comparative analysis and combined compromise solution

Identifying mineralization areas with an acceptable level of reliability is a complex matter demanding the implementation of supervised methods for mapping mineralization exploration aims. In this study, further collecting all available exploratory information and data of the region of study, their good processing and analysis, and then integrating them with an appropriate method, multi-criteria decision-making (MCDM) approaches were utilized to outranking porphyry Cu mineralization areas. This paper describes an acceptable procedure for obtaining evidential layers for recognizing porphyry Cu mineralization, assigning weight to the layers, and combining them. For this aim, first, a data-driven multi-class index overlay (DMIO) approach is applied as it is a proven method with proper results in mineral prospectivity mapping (MPM) to integrate evidential layers (criteria and sub-criteria emanated from geoscience data including geological, geochemical, remote sensing, and geophysical datasets). After that, two recent MCDM models, combined compromise solution (CoCoSo) and multi attributive ideal-real comparative analysis (MAIRCA), were used to prioritize the porphyry Cu potential areas producing MPM. Concentration-area (C–A) fractal method and prediction-area (P–A) plots by considering the areas of occurrence of the known mineralization and normalized density (N_d) as traditional methods were applied for weighting and integration evidential layers and evaluation of the final maps in a data-driven manner. Consequently, verifying the verisimilitude of the MAIRCA prospectivity map (N_d = 3.17) is similar to the DMIO map in delimiting the priority areas. The results of the CoCoSo model (N_d = 2.7) show this methodology was also successfully applied in mapping the porphyry Cu mineralization areas in the study.     

Compositional data analysis in the study of integrated geochemical anomalies associated with mineralization

Geochemical data are typical compositional data which should be opened prior to univariate and multivariate data analysis. In this study, a frequency-based method (robust principal component analysis, RPCA) and a frequency-space-based method (spectrum–area fractal model, S–A) are applied to explore the effects of the data closure problem and to study the integrated geochemical anomalies associated with polymetallic Cu mineralization using a stream sediment geochemical dataset collected from the Zhongteng district, Fujian Province (China). The results show that: (1) geochemical data should be opened prior to RPCA to avoid spurious correlation between variables; (2) geochemical pattern is a superimposition of multi-processes and should be decomposed; and (3) the S–A fractal model is a powerful tool for decomposing the mixed geochemical pattern.     

Mapping mineral prospectivity for Cu polymetallic mineralization in southwest Fujian Province,China

In this study, both the fuzzy weights of evidence (FWofE) and random forest (RF) methods were applied to map the mineral prospectivity for Cu polymetallic mineralization in southwestern Fujian Province, which is an important Cu polymetallic belt in China. Recent studies have revealed that the Zijinshan porphyry–epithermal Cu deposit is associated with Jurassic to Cretaceous (Yanshanian) intermediate to felsic intrusions and faulting tectonics. Evidence layers, which are key indicators of the formation of Zijinshan porphyry–epithermal Cu mineralization, include: (1) Jurassic to Cretaceous intermediate–felsic intrusions; (2) mineralization-related geochemical anomalies; (3) faults; and (4) Jurassic to Cretaceous volcanic rocks. These layers were determined using spatial analyses in support by GeoDAS and ArcGIS based on geological, geochemical, and geophysical data. The results demonstrated that most of the known Cu occurrences are in areas linked to high probability values. The target areas delineated by the FWofE occupy 10% of the study region and contain 60% of the total number of known Cu occurrences. In comparison with FWofE, the resulting RF areas occupy 15% of the study area, but contain 90% of the total number of known Cu occurrences. The normalized density value of 1.66 for RF is higher than the 1.15 value for FWofE, indicating that RF performs better than FWofE. Receiver operating characteristics (ROC) were used to validate the prospectivity model and check the effects of overfitting. The area under the ROC curve (AUC) was greater than 0.5, indicating that both prospectivity maps are useful in Cu polymetallic prospectivity mapping in southwestern Fujian Province.     

On the correlation between spectra of solar microwave bursts and proton fluxes near the Earth

Studies of the extreme solar proton event of January 20, 2005 intensified the contest over of a long-standing problem: are solar cosmic rays arriving at the Earth accelerated by solar flares or by shocks preceding rapidly moving coronal mass ejections? Among the most important questions is the relationship between the energy spectra of the solar cosmic rays and the frequency spectra of flare microwave bursts. Some studies of previous solar-activity cycles have shown that such a relationship does exist, in particular, for protons with energies of tens of MeV. The present work analyzes this relation using data for 1987–2008. For flare events observed in the western half of the disk, there is a significant correlation between the index δ, which is equivalent to the power-law index of the integrated energy spectrum of 10–100 MeV protons detected near the Earth’s orbit, and radio burst parameters such as a ratio of peak fluxes S at two frequencies (for example, at 9 and 15 GHz) and a microwave peak frequency f _m . Proton fluxes with hard (flat) energy spectra (δ ≤ 1.5) correspond to hard microwave frequency spectra (S ₉/S ₁₅ ≤ 1 and f _m ≥ 15 GHz), while flares with soft radio spectra (S ₉/S ₁₅ ≥ 1.5 and f _m ≤ 5 GHz) result in proton fluxes with soft (steep) energy spectra (δ ≥ 1.5–2). It is also shown that powerful high-frequency bursts with the hardest radio spectra (f _m ≈ 30 GHz) can point at acceleration of significant proton fluxes in flares occurring in strong magnetic fields. These results argue that solar cosmic rays (or at least their initial impulses) are mainly accelerated in flares associated with impulsive and post-eruptive energy release, rather than in shocks driven by coronal mass ejections.     

Analysis of geological structure and anthropological factors affecting arsenic distribution in the Lahore aquifer,Pakistan

This study investigated the potential factors affecting arsenic concentration in the groundwater system of Lahore, Pakistan. The effects of several factors such as population density (PD), pumping rate (PR), impermeable land use (LU), surface elevation (SE), and water-table elevation (WL) on arsenic concentration were studied in 101 union councils of Lahore. Forty single and multi-factor models were established using geographic information system (GIS) techniques to develop an arsenic contamination map and to investigate the most effective combinations among factors. Additionally, statistical tests were used to evaluate arsenic concentration between classes of the same single factor. The arsenic concentration in the Lahore aquifer varied from 0.001 to 0.143 mg L^?1. The highest arsenic concentrations were detected in the Walled City and the town of Shahdara. Among the 40 raster models, groundwater arsenic concentration showed the best matching frequency with single-factor models for PD (50.70 %) and SE (47 %). Thus, PD and SE were used to develop an arsenic distribution raster map, and they were also used to study the effect of aquifer depth on arsenic concentration. PD was found to have hidden latent variables such as PR and LU. The shallow aquifer depth was negatively correlated with arsenic concentration (r?=??0.23) and positively with PR (r?=?0.15). Therefore, when there was high PR in wells with smaller aquifer depth, the arsenic concentration was high. The existing water treatment and alternative water resources are good options, which should be developed to deal with Lahore wells contaminated with arsenic at high concentrations.     

Influence of surface geology and mineral deposits on the spatial distributions of elemental concentrations in the stream sediments of Hokkaido,Japan

An elucidation of the background levels of heavy metals, including certain toxic elements, is very essential to accomplish an important environmental assessment. A regional geochemical mapping in Hokkaido, Japan was undertaken by the Geological Survey of Japan, AIST as part of a nationwide geochemical mapping for this purpose. There were 692 stream sediments collected from the active channel (1 sample) / (100 km²) in Hokkaido and the fine fraction sieved through a 180 μm screen was analyzed using the AAS, ICP-AES, and ICP-MS techniques. The regional geochemical maps for 51 elements were created as a 2000 m mesh map using the geographic information system software. Spatial distribution patterns of elemental concentrations in stream sediments, particularly Neogene–Quaternary volcanic and pyroclastic rocks, are primarily determined by surface geology. The correspondence of elemental concentrations in stream sediments to parent lithology is clearly indicated by ANOVA and a multiple comparison. Sediment samples supplied from mafic volcanic and felsic–mafic pyroclastic rocks are significantly rich in MgO, Al₂O₃, P₂O₅, CaO, Sc, TiO₂, V, MnO, Total (T)-Fe₂O₃, Co, Zn, Sr, and heavy rare earth elements (REEs) (Y and Eu–Lu), but significantly lacking in alkali elements, Be, Nb, light REEs (La–Nd), Ta, Tl, Th, and U. Accretionary complexes with sedimentary rocks derived from sediments are in stark contrast to volcanic and pyroclastic rocks. Accretionary complexes with mafic–ultramafic rock have significantly elevated Nb, Ta, and Th abundances in sediments besides MgO, Cr, Ni, Co, and Cu. This inexplicable result is caused by the mixed distributions of granite and ultramafic–mafic rocks.The watersheds with mineral deposits relate to the high concentrations of certain elements such as Zn, As, and Hg. The geochemically anomalous pattern, which is a map of the regional anomalies, and a scatter diagram were applied to examine the contribution of mineral deposits to MnO, T-Fe₂O₃, Cr, Cu, Zn, As, Cd, Sb, Hg, Pb, and Bi concentrations. Consequently, they were grouped into four types: 1) Mineral deposits with no outliers resulting from mineralization (MnO, T-Fe₂O₃, and Cr), 2) sediments supplied from watersheds without metal deposits conceal high metal inputs from known mineral deposits (Cu), 3) deposits from a geochemically anomalous area that closely relates to the presence of mineral deposits (As, Sb, and Hg), and 4) deposits from the widely altered zone associated with the Kuroko as well as hydrothermal deposits corresponding to geochemically anomalous patterns (Zn, Cd, and Pb). This study provides an important regional geochemical database for a young island-arc setting and interpretational problems, such as complicated geology and active erosion, that are unique to Japan.     

Mobility and impact of trace metals in Barapukuria coal mining area, Northwest Bangladesh

Trace metals were analyzed in water and sediment samples from Barapukuria coal mine area of Bangladesh in order to evaluate their mobility and possible environment consequences. Cadmium is the most mobile element with an average partition coefficient (log K _d ) of 2.95 L/kg, while V is the least mobile element with a mean log K _d of 5.50 L/kg, and their order of increasing mobility is: V < As < Pb < Fe < Cr < Se < Mn < Ni < Zn < Cu < Ba < Sr < Cd. Contents of organic carbon in sediment samples shows strong positive correlations with most trace metals as revealed by the multivariate geostatistical analysis. The overall variation in concentration is mainly attributed to the discharge of effluents originating from the coal mining activities around the study area. Compared to their background, Ni and Cu are the most enriched while significant enrichment of As, Mn, Ba, Sr, Cr, and Pb is also observed in the sediments. Geoaccumulation indices (I _geo ) suggest sediments are moderately to heavily polluted with respect to Ni and Cu. The metal pollution index (MPI) varied from 91.91 to 212.01 and the highest value is found at site CM03 that is close to discharge point. The sediment quality guideline index (SQG-I _Intervention ) values (0.56–1.52) suggest that the sediments at the study area have moderate to high ecotoxicological risk.     

Characteristics of landslides in western Colorado,USA

Mass movement can be activated by earthquakes, rapid snowmelt, or intense rainstorms in conjunction with gravity. Whereas mass movement plays a major role in the evolution of a hillslope by modifying slope morphology and transporting material from the slope to the valley, it is also a potential natural hazard. Determining the relationships of frequency and magnitude of landslides are fundamental to understanding the role of landslides in the study of landscape evolution, hazard assessment, and determination of the rate of hillslope denudation. We mapped 735 shallow and active landslides in the Paonia to McClure Pass area of western Colorado from aerial photographs and field surveys. The study area covers ～815 km². The frequency–magnitude relationships of the landslides illustrate the flux of debris by mass movement in the area. The comparison of the probability density of the landslides with the double Pareto curve, defined by power scaling for negative slope (α), power scaling for positive slope (β), and location of rollover (t), shows that α?=?1.1, β?=?1.9, and t?=?1,600 m² for areas of landslides and α?=?1.15, β?=?1.8, and t?=?1,900 m³ for volumes of landslides. The total area of landslides is 4.8?×?10⁶ m² and the total volume of the landslides is 1.4?×?10⁷ m³. The areas (A) and the volumes (V) of landslides are related by V?=?0.0254?×?A ^1.45. The frequency–magnitude analysis shows that landslides with areas ranging in size from 1,600 to 20,000 m² are the most hazardous landslides in the study area. These landslides are the most frequent and also do a significant amount of geomorphic work. We also developed a conceptual model of hillslope development to upland plateau driven by river incision, shallow landsliding, and deep-seated large landsliding. The gentle slope to flat upland plateau that dominated the Quaternary landscape of the study area was modified to the present steep and rugged topography by the combined action of fluvial incision and glacial processes in response to rock uplift, very-frequent shallow landsliding, and less-frequent deep-seated landsliding.     

Fractal-Based Wavelet Filter for Separating Geophysical or Geochemical Anomalies from Background

The widely used wavelet filtering technique holds potential to approach anomaly–background separation in geophysical and geochemical data processing. Wavelet statistics provide crucial information on such filtering methods. In general, conventional (Gaussian-type) statistical modeling is insufficient to adequately describe the heavily tailed and sharply peaked (at zero) distribution of the wavelet coefficients of irregular geo-anomaly patterns. This paper demonstrates that the cumulative (frequency) number of the wavelet coefficient yields a power-law scaling relationship with the coefficient based on wavelet transform of a fractal/singular measure. This wavelet coefficient–cumulative number power-law model is proven to be more flexible and appropriate than the Gaussian model for characterizing the scaling nature of the coefficient distribution. Accordingly, a fractal-based filtering technique is developed based on the wavelet statistical model to decompose mixed patterns into components based on the distinct self-similarities identified in the wavelet domain. The decomposition scheme of the fractal-based wavelet filtering method considers not only the coefficient frequency distribution but also the fractal spectrum of singularities and the self-similarity of real-world features. Finally, a synthetic data test and real applications from two metallogenic provinces of China are used to validate the proposed fractal filtering method for anomaly–background separation and identification of geophysical or geochemical anomalies related to mineralization and other geological features.     

Groundwater transport of arsenic and chromium at a historical tannery,Woburn, Massachusetts,U.S.A.

The geochemical environment in hide piles at a historical tanning and rendering site (Woburn, Massachusetts, U.S.A.) is strongly reducing, as reflected by the presence of H₂S and CH₃HS in the pile offgas. The presence of a reducing environment in the Subjacent groundwater, along with DOC (≥ 100mg/l) from hide breakdown, results in reduction of As(V) to As(III), and subsequent methylation to monomethylarsonic acid (MMAA) and dimethylarsinic acid (DMAA). The reducing conditions also result in precipitation of FeS_(am), while hydrophilic organic acids have increased Cr(III) solubility. Three spatially sequential geochemical redox facies were recognized in groundwater downgradient from the hide piles. Typically, a reduced core zone was present adjacent to the hide piles, characterized by S²⁻ ≥ 1mg/l, Fe²⁺ <5mg/l,NH₃ ≥ 200mg/l and the presence of MMAA in conjunction with DOC (−30mg/l). This facies transitions through an intermediate zone, represented by Fe²⁺ > 20mg/l, NH₃ (5–200 mg/l) and the sporadic presence of measurable S²⁻ (1–2 mg/l), to an oxidizing peripheral zone characterized by conditions representative of background (i.e. DO> 1mg/l, Eh> 0mV, Fe²⁺ < 20mg/l, S²⁻ < 1mg/l,NH₃ < 5mg/l and NO₃⁻ >NH₃), accompanied by precipitation of amorphous ferric hydroxide, sorption of As and co-precipitation-sorption of Cu, Pb and Zn. Electron microprobe analysis of hide-pile materials demonstrated authigenic precipitation of amorphous ferric hydroxide and gypsum, in agreement with the results of geochemical modeling.