Mixtures of multiplicative cascade models in geochemistry

International audienceMultifractal modeling of geochemical map data can help to explain the nature of frequency distributions of element concentration values for small rock samples and their spatial covariance structure. Useful frequency distribution models are the lognormal and Pareto distributions which plot as straight lines on logarithmic probability and log-log paper, respectively. The model of de Wijs is a simple multiplicative cascade resulting in discrete logbinomial distribution that closely approximates the lognormal. In this model, smaller blocks resulting from dividing larger blocks into parts have concentration values with constant ratios that are scale-independent. The approach can be modified by adopting random variables for these ratios. Other modifications include a single cascade model with ratio parameters that depend on magnitude of concentration value. The Turcotte model, which is another variant of the model of de Wijs, results in a Pareto distribution. Often a single straight line on logarithmic probability or log-log paper does not provide a good fit to observed data and two or more distributions should be fitted. For example, geochemical background and anomalies (extremely high values) have separate frequency distributions for concentration values and for local singularity coefficients. Mixtures of distributions can be simulated by adding the results of separate cascade models. Regardless of properties of background, an unbiased estimate can be obtained of the parameter of the Pareto distribution characterizing anomalies in the upper tail of the element concentration frequency distribution or lower tail of the local singularity distribution. Computer simulation experiments and practical examples are used to illustrate the approach

Mineral exploration modeling and singularity analysis for geological feature recognition and mineral potential mapping in southeastern Yunnan mineral district, China

Nowadays, with the development in construction of geo-exploratory datasets and data processing techniques, mineral exploration modeling for recognition of mineralization associated geological features and mapping of mineral potentials become more dependent on GIS-based analysis and geo-information from multi-source datasets. Geological, geochemical and geophysical data as three main sources of geo-information in support of mineral exploration have long been employed in many researches. Spatial distributions of geological bodies or controlling factors associated with mineralization were frequently interpreted from these datasets. However, former characterizations of the controlling factors were simply focused on their location information; concerns on spatial variations of their geological signatures and controlling effects on mineralization were not sufficiently emphasized. Therefore, through a series of newly developed GIS-based manipulations, current study intends to demonstrate a comprehensive mineral exploration modeling process for more explicit recognition of controlling factors and their interactions on mineralization and delineation of hydrothermal mineral potentials in southeastern Yunnan mineral district, China. The hydrothermal mineralization as a nonlinear geo-process is accompanied with anomalous energy release and material accumulation in a narrow spatial-temporal interval. Simultaneously, it is a cascade process associated with various geological activities (e.g., magmatism, tectonism, etc.). Knowledge of these associated geo-activities is consequently beneficial to the exploration of hydrothermal mineralization. As the key point of this study, the singularity index mapping method in the context of fractal/multifractal efficient in separating geo-anomalies from both strong and weak background is applied to characterize variations of geological signatures of three controlling factors (i.e., granitic intrusions, faults and the Gejiu formation). With the guidance of multidisciplinary approaches, these geo-information derived from multi-source datasets is further integrated to produce the potential map. In comparison with traditionally used methods, the newly depicted predictor maps enhance weak geo-anomalies hidden within a strong variance of background. In addition, three geo-information integration methods including RGB composition, the principal component analysis and the weights of evidence method are implemented. By the weights of evidence method, the qualitatively and quantitatively interpretable result possessing advantages of the other two methods, simultaneously, is accepted as the final result of currently proposed mineral exploration modeling. Summarized experiences through this study will not only support future exploration in the study area, but also benefit the work in other areas

Geo-information identification for exploring non-stationary relationships between volcanic sedimentary Fe mineralization and controlling factors in an area with overburden in eastern Tianshan region, China

GIS-based spatial analysis has been a common practice in mineral exploration, by which mineral potentials can be delineated to support following sequences of exploration. Mineral potential mapping is generally composed of geo-information extraction and integration. Geological anomalies frequently indicate mineralization. Volcanic sedimentary Fe deposits in eastern Tianshan mineral district, China provide an example of such an indication. However, mineral exploration in this area has been impeded by the desert coverage and geo-anomalies indicative to the presence of mineralization are often weak and may not be efficiently identified by traditional exploring methods. Furthermore, geological guidance regarding to spatially non-stationary relationships between Fe mineralization and its controlling factors were not sufficiently concerned in former studies, which limited the application of proper statistics in mineral exploration. In this dissertation, geochemical distributions associated with controlling factors of the Fe mineralization are characterized by various GIS-based spatial analysis methods. The singularity index mapping technique is attempted to separate geochemical anomalies from background, especially in the desert covered areas. Principal component analysis is further used in integrating the geochemical anomalies to identify geo-information of geological bodies or geological activities associated with Fe mineralization. In order to delineate mineral potentials, spatially weighted principal component analysis with more geological guidance is tried to integrate these identified controlling factors. At the end, as the first time been introduced to mineral exploration, a geographically weighted regression method is currently attempted investigate spatially non-stationary interrelationships presented across the space. Based on the results, superimposition of these controlling factors can be qualitatively and quantitatively summarized that provides a constructive geo-information to Fe mineral exploration in this area. From the practices in this dissertation, GIS-based mineral exploration will not only be efficient in mapping mineral potentials but also be supportive to strategies making of following mineral exploration. All of these experiences can be suggested to future mineral exploration in the other regions

Multi-scale interactions of geological processes during mineralization: cascade dynamics model and multifractal simulation

Relations between mineralization and certain geological processes are established mostly by geologist's knowledge of field observations. However, these relations are descriptive and a quantitative model of how certain geological processes strengthen or hinder mineralization is not clear, that is to say, the mechanism of the interactions between mineralization and the geological framework has not been thoroughly studied. The dynamics behind these interactions are key in the understanding of fractal or multifractal formations caused by mineralization, among which singularities arise due to anomalous concentration of metals in narrow space. From a statistical point of view, we think that cascade dynamics play an important role in mineralization and studying them can reveal the nature of the various interactions throughout the process. We have constructed a multiplicative cascade model to simulate these dynamics. The probabilities of mineral deposit occurrences are used to represent direct results of mineralization. Multifractal simulation of probabilities of mineral potential based on our model is exemplified by a case study dealing with hydrothermal gold deposits in southern Nova Scotia, Canada. The extent of the impacts of certain geological processes on gold mineralization is related to the scale of the cascade process, especially to the maximum cascade division number <i>n</i><sub>max</sub>. Our research helps to understand how the singularity occurs during mineralization, which remains unanswered up to now, and the simulation may provide a more accurate distribution of mineral deposit occurrences that can be used to improve the results of the weights of evidence model in mapping mineral potential

Environmental geochemistry of Potentially Toxic Elements (PTEs) and Persistent Organic Pollutants (POPs) as a tool of exposure evaluation and chemical risk assessment

Environmental pollution is one of the most challenging environmental issues to tackle due to its impact to human health and the ecosystem. One of the main objectives of environmental geochemistry is to investigate, characterise, and reveal the patterns of organic compounds and inorganic elements and further unveil their possible sources. Geogenic features and anthropogenic activities are the main sources of environmental contamination which are likely to release these contaminants into atmospheric, soil and water media. Moreover, anthropogenic activities let out chemicals produced from industrial activities, domestic, livestock and municipal wastes (including wastewater), agrochemicals, and petroleum-derived products. Organic pollutants cover a large group of synthetized pollutants and Persistent Organic Pollutants (POPs) have received a specific attention due to their physico-chemical properties, high toxicity, and subject to long-range atmospheric transfer. Polychlorinated biphenyls (PCBs), Polycyclic Aromatic Hydrocarbons (PAHs) and Organochlorines Pesticides (OCPs) are the main POPs that are subject to different regulation schemes to their irreversible adverse effects to both human and wildlife health. Stockholm Convention, Rotterdam and Basel, World Health organisation (WHO) and United Nations Economic Commission for Europe POPs Protocol have so far addressed, threated and introduced legislation which ban or fix threshold’s values of these POPs into environment. Potentially Toxic Elements (PTEs) are widespread metals/metalloids related to geogenic and/or anthropogenic activities. PTEs are one of the major concerns in the environment because their concentrations are increasing due to accelerated population growth rate, higher level of urbanisation and industrialisation providing a great variety of anthropogenic contamination/pollution sources. They have often been given special emphasis because their accumulation in different matrices can cause soil and land degradation and they can be transferred into the human body as a consequence of dermal contact, inhalation and ingestion through food chain and drinking water. PTEs are generally non-biodegradable having long biological half-lives and tend to accumulate in soils being absorbed to clay minerals and organic matter. However, their bioavailability is influenced by different physicochemical processes (e.g. pH, Eh) and physiological adaptation. PTEs and POPs can be observed in different environmental media but soil is considered an important reservoir due to its physico-chemical properties which confer high retention capacity of these pollutants. Soil contamination has been increasing worldwide and has become the focus of attention in recent years. Several soil parent materials are natural sources of certain organic contaminants, elements, and these can pose a risk to the environment and human health at elevated concentrations. For that, various geostatistical computations have been used to identify source patterns of different pollutants related to underlying geological features and/or anthropogenic activities, and to further distinguish mineralisation from contamination. Several single and complex contamination/mineralisation indices such as Enrichment Factor, Geo-accumulation Index or Single Pollution Index have been elaborated to quantify the contamination or mineralisation status of different PTEs. They are generally based on intervention limits (thresholds) or background/baseline values of a single element based on National Legislation, as a reference. Indices based on intervention limits (thresholds) are easily interpretable and comparable, but they disregard the compositional nature of geochemical data; hence they can be biased and/or spurious. This PhD research project reveals novel geostatistical computations that will lay out sources patterns of Potentially Toxic Elements (PTEs) and Persistent Organic Pollutants (POPs), and assess the soils contamination levels in the central-southern Italy. Series of follow up studies have provided an invaluable baseline for these contaminants distribution in Italy to push towards an institutional response for more adequate regulation of these pollutants worldwide. A further ongoing research project is currently investigating the content and bioavailability of mercury and Potentially Toxic Elements (PTEs) in artisanal and small-scale gold mining (ASGM) districts of Kedougou (Senegal). This study in particular will represent a fundamental stepping stone to build a baseline review of PTEs in ASGM of Kedougou (Senegal) and evaluate human health risks from exposure of PTEs. It is envisaged that the results of this study should trigger more detailed surveys in contaminated areas as well as ad-hoc risk-based studies, which in the long-term will constitute a strong argument to cause an adequate institutional response by the Senegalese regulating authorities for a full application the Minamata convention

Correlation between geology and concentration-volume fractal models: significance for Cu and Mo mineralized zones separation in the Kahang porphyry deposit (Central Iran)

ArticleThis study identifies the major mineralized zones including supergene enrichment and hypogene enrichment in the Kahang Cu-Mo porphyry deposit which is located in Central Iran based on subsurface data and utilization of the concentration-volume (C-V) fractal model. Additionally, a correlation between results achieved from a C-V fractal model and geological models consisting of zonation, mineralography and alteration have been conducted in order to have an accurate recognition and modification of the main mineralized zones. Log-log plots indicate five geochemical populations for Cu and Mo in the deposit which means that mineralization commences with 0.075 % and 13 ppm for Cu and Mo (as the first thresholds) respectively. The main mineralization began for Cu≥0.42 % and Mo≥100 ppm and also enriched mineralization containing Cu≥1.8 % and Mo≥645 ppm which is located in the central part of the deposit. According to the C-V model, the main Cu-Mo mineralized zones occur in the hypogene zone, especially in the central, NW and NE parts of the Kahang deposit. The supergene enrichment zone derived via the C-V model is smaller than that in the geological model and is located in the central and eastern parts of the deposit. Results analysed by the C-V fractal model certify that the interpreted zones based on the fractal model are accurate. To certify this, a logratio matrix has been employed to validate the C-V fractal model for the Cu and Mo main mineralized zones.The authors are grateful to the National Iranian Copper Industries Co. (NICICO) for their permission to have access to the Kahang deposit dataset. Additionally, the authors would like to thank Dr. A. Saad Mohammadi the former CEO of NICICO for his support. The authors would like to thank the reviewers of this paper for their comments and valuable remarks

EVALUATION OF HEAVY METALS CONCENTRATION IN JAJARM BAUXITE DEPOSIT IN NORTHEAST OF IRAN USING ENVIRONMENTAL POLLUTION INDICES

Heavy metals are known as an important group of pollutants in soil. Major sources of heavy metals are modern industries such as mining. In this study, spatial distribution and environmental behavior of heavy metals in the Jajarm bauxite mine have been investigated. The study area is one of the most important deposits in Iran, which includes about 22 million tons of reserve. Contamination factor (CF), the average concentration (AV), the enrichment factor (EF) and geoaccumulation index (GI) were factors used to assess the risk of pollution from heavy metals in the study area. Robust principal component analysis of compositional data (RPCA) was also applied as a multivariate method to find the relationship among metals. According to the compositional bi-plots, the RPC1 and RPC2 account for 57.55% and 33.79% of the total variation, respectively. The RPC1 showed positive loadings for Pb and Ni. Also, the RPC2 showed positive loadings for Cu and Zn. In general, the results indicated that mining activities in the bauxite mine have not created serious environmental hazards in the study area except for lead and nickel. Finding potential relations between mining work and elevated heavy metals concentrations in the Jajarm bauxite mine area necessitates developing and implementing holistic monitoring activities