Porphyry Cu can contain significant concentrations of platinum-group elements (PGE: Os, Ir, Ru, Rh, Pt, Pd). In this study, we provide a comprehensive in situ analysis of noble metals (PGE, Au, Ag) for (Cu-Fe)-rich sulfides from the Elatsite, one of the world's PGE-richest porphyry Cu deposits. These data, acquired using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), indicate that Pd was concentrated in all the (Cu-Fe)-rich sulfides at ppm-levels, with higher values in pyrite (~6 ppm) formed at the latest epithermal stage (i.e., assemblage) than in bornite and chalcopyrite (<5 ppm) from the hypogene ores. Likewise, Au is significantly more concentrated in pyrite (~5 ppm) than in the (Cu-Fe)-rich sulfides (≤0.08 ppm). In contrast, Ag reaches hundreds of ppm in pyrite and bornite (~240 ppm) but is in much lesser amounts in chalcopyrite (<25 ppm). The inspection of the time-resolved spectra collected during LA-IPC-MS analyses indicates that noble metals are present in the sulfides in two forms: (1) structurally bound (i.e., solid solution) in the lattice of sulfides and, (2) as nano- to micron-sized inclusions (Pd-Te and Au). These observations are further confirmed by careful investigations of the PGE-rich (Cu-Fe)-rich sulfides by combining high-spatial resolution of field emission scanning electron microscope (FESEM) and focused ion beam and high-resolution transmission electron microscopy (FIB/HRTEM). A typical Pd-bearing mineral includes the composition PdTe close to the ideal merenskyite but with a distinct crystallographic structure, whereas Au is mainly found as native element. Our detailed mineralogical study coupled with previous knowledge on noble-metal inclusions in the studied ores reveals that noble metal enrichment in the Elatsite porphyry ores was mainly precipitated from droplets of Au-Pd-Ag telluride melt (s) entrained in the high-temperature hydrothermal fluid. These telluride melts could separate at the time of fluid unmixing from the silicate magma or already be present in the latter either derived from deep-seated crustal or mantle sources. Significant enrichment in Pd and Au (the latter correlated with As) in low-temperature pyrite is interpreted as remobilization of these noble metals from pre-existing hypogene ores during the epithermal overprinting.

The aim of our study was to test whether surficial geochemical techniques are applicable under arctic conditions where pedogenesis is slow or absent, and where the vegetation is arctic dwarf shrub tundra. To this end, we sampled vegetation and topsoil at a known Zn-Pb-Ag anomaly at Kangerluarsuk, northwest Greenland. This Zn-Pb-Ag mineralization surfaces in part of the test area and is deeply buried in other parts. The surface mineralization could readily be identified by element analysis of the omnipresent plant . The strongest signal came from the pathfinder element Tl. The target elements Pb and Ag gave only weak signals and Zn gave no signal, probably because the cellular concentration of these elements is actively regulated by the plant. The use of regulated plant micronutrients as reference elements gave a small reduction of analytical noise in Tl/Cu and Tl/B concentration ratios at low Tl concentrations which improved identification of the deep mineralization. Pathfinder elements in plants may thus prove useful when combined with a detailed geophysical model. Tl, Zn, Pb and Ag concentrations in topsoil identified the surface mineralization but failed to identify the deep mineralization. This difference between samples of and topsoil is probably because target elements from the deep mineralization must be mobile to reach the surface. Mobile elements may be more accessible for ion-exchange and uptake into the plants compared to the recalcitrant and crystalline fraction in the topsoil.

The study of the relationships between two compositions is of paramount importance in geochemical data analysis. This paper develops a compositional version of canonical correlation analysis, called CoDA-CCO, for this purpose. We consider two approaches, using the centred log-ratio transformation and the calculation of all possible pairwise log-ratios within sets. The relationships between both approaches are pointed out, and their merits are discussed. The related covariance matrices are structurally singular, and this is efficiently dealt with by using generalized inverses. We develop compositional canonical biplots and detail their properties. The canonical biplots are shown to be powerful tools for discovering the most salient relationships between two compositions. Some guidelines for compositional canonical biplot construction are discussed. A geochemical data set with X-ray fluorescence spectrometry measurements on major oxides and trace elements of European floodplains is used to illustrate the proposed method. The relationships between an analysis based on centred log-ratios and on isometric log-ratios are also shown.

Chemical properties of coal largely determine coal handling, processing, beneficiation methods, and design of coal-fired power plants. Furthermore, these properties impact coal strength, coal blending during mining, as well as coal's gas content, which is important for mining safety. In order for these processes and quantitative predictions to be successful, safer, and economically feasible, it is important to determine and map chemical properties of coals accurately in order to infer these properties prior to mining. Ultimate analysis quantifies principal chemical elements in coal. These elements are C, H, N, S, O, and, depending on the basis, ash, and/or moisture. The basis for the data is determined by the condition of the sample at the time of analysis, with an "as-received" basis being the closest to sampling conditions and thus to the in-situ conditions of the coal. The parts determined or calculated as the result of ultimate analyses are compositions, reported in weight percent, and pose the challenges of statistical analyses of compositional data. The treatment of parts using proper compositional methods may be even more important in mapping them, as most mapping methods carry uncertainty due to partial sampling as well. In this work, we map the ultimate analyses parts of the Springfield coal from an Indiana section of the Illinois basin, USA, using sequential Gaussian simulation of isometric log-ratio transformed compositions. We compare the results with those of direct simulations of compositional parts. We also compare the implications of these approaches in calculating other properties using correlations to identify the differences and consequences. Although the study here is for coal, the methods described in the paper are applicable to any situation involving compositional data and its mapping.

The 76-element Geochemical Mapping (76 GEM) Project was undertaken in southwestern China in 2000 and in southeastern China in 2008. In this project, 5244 composite samples of stream sediment at a density of one composite sample for each 1:50,000-scale map sheet were prepared from sample archives of the China Regional Geochemistry-National Reconnaissance (RGNR) Project, which have been available since 1978. The 76 elements were analyzed by using inductively coupled plasma mass spectrometry (ICP-MS), X-ray fluorescence (XRF), and inductively coupled plasma atomic emission spectroscopy (ICP-AES). In the present study, a new quality-control method known as the visualized standard map method was applied to the results of the 76 GEM project. Mean value and background value, which indicate the average concentration of the 76 elements in southern China, were derived from statistical data. Moreover, geochemical maps were compiled to demonstrate the distribution of the 76 elements in southern China.

Groundwater in sedimentary deposits in China, Southern, and Southeast Asia down gradient from the Tibetan plateau contain elevated As concentrations on a regional scale. To ascertain the possibility of source region As enrichment, samples of water (n=86), stream sediment (n=77) and soil (n=73) were collected from the Singe Tsangpo (upstream of the Indus River), Yarlung Tsangpo (upstream of the Brahmaputra River) and other drainage basins in Tibet in June of 2008. The average arsenic concentration in stream waters, sediments and soils was 58±70 μg/L (n=39, range 2-252 μg/L), 42±40 mg/kg (n=37, range 12-227 mg/kg), and 44±27mg/kg (n=28, range 12-84 mg/kg) respectively for the Singe Tsangpo and was 11±17 μg/L (n=30, range 2-83 μg/L), 28±11 mg/kg (n=28, range 2-61 mg/kg), and 30±34 mg/kg (n=21, range 6-173 mg/kg) respectively for the Yarlung Tsangpo. A dug well contained 195 μg/L of As. In addition to elevated As levels in surface and shallow groundwater of Tibet, hot spring and alkaline salt lake waters displayed very high As levels, reaching a maximum value of 5,985 μg/L and 10,626 μg/L As, respectively. The positive correlation between [As] and [Na]+[K] in stream waters indicates that these surface water arsenic enrichments are linked to the hot springs and/or salt lakes. Further, 24% of As in stream sediment is reductively leachable, with bulk As displaying a positive correlation with stream water As, suggesting sorption from stream water. In contrast, the fraction of reductively leachable As is negligible for soils and several rock samples, suggesting that As in them are associated with unweathered minerals. Whether the pronounced As anomaly found in Tibet affects the sedimentary As content in deltas downstream or not requires further study.