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Summary of semi-quantitative whole-rock XRD analysis of hydrothermal alteration across the island of Milos, Greece. The samples were acquired during numerous field visits between 2010 and 2018 by the British Geological Survey and GW4+ Doctorial Training Partnership (NE/L002434/1). The data were acquired using a PANAlytical X’Pert Pro diffractometer at the British Geological Survey, Keyworth, UK. These data were primarily used to identify mineral phases to improve our understanding of regional and local paleo-hydrothermal activity. This may be useful within the metallic and industrial mineral mining sector and associated researchers. The data includes grid references (± 5 m), field observations and instrument running conditions. Samples from 2010 are supported by a grant award from the Natural Environment Research Council (GA/09F/139). Samples from 2016 - 2018 are supported by the GW4+ Doctoral Training Partnership (NE/L002434/1) grant award GA/09F/139 – RMS E3557, and the British Geological Survey’s University Funding Initiative (BUFI S345).
This dataset provides an overview of hydrothermal alteration samples from the island of Milos, Greece, that were analysed using a portable infrared mineral analyser (PIMA) or AgriSpec spectrometer. During data acquisition, spectrums were input into The Spectral Geologist (TSG) to provide an instant and estimated mineral identification using the shortwave infrared (SWIR) part of the electromagnetic spectrum. The samples were acquired during field visits between 2017 - 2019 by the British Geological Survey and the GW4+ Doctorial Training Partnership (NE/L002434/1). This data was primarily used to aid sample collection for further hydrothermal alteration analyses to improve our understanding of regional and local paleo-hydrothermal activity across the island. Identification by the TSG provides an estimation only, and the raw data files in .txt, .fos and .csv formats, are supplied for each analysis in the attached zipped file. This may be useful within the metallic and industrial mineral mining sector and associated researchers. The data includes grid references (± 5 m), TSG interpretations, and field/sample observations noted during data acquisition. GW4+ Doctoral Training Partnership (NE/L002434/1) is supported by grant award GA/09F/139 – RMS E3557, and the British Geological Survey’s University Funding Initiative (BUFI S345).
Shrink-swell is recognised as the most significant geohazard across Great Britain. This dataset identifies areas of shrink-swell hazard with increased potential due to changing climatic conditions based on forecasts derived from the UKCP18 climate projections. The dataset has been created at two levels of detail for RCP8.5 emissions scenario and dates up to 2070. The Basic dataset is an overview at 2Km grid resolution whilst the more detailed Premium dataset is generated at a 50m resolution. The Open versions are simplified versions of the premium versions and are shared via BGS GeoIndex. The premium versions are paid for products. UKCP18 - UK Climate Projections 2018 project RCP8.5 - A pathway where greenhouse gas emissions continue to grow unmitigated, leading to a best estimate global average temperature rise of 4.3°C by 2100. Representative Concentration Pathways (RCPs) are a method for capturing those assumptions within a set of scenarios.
Friction coefficient and frictional stability (rate & state parameter) data for triaxially compressed direct shear experiments on kaolinite-rich china clay and Mg-montmorillonite fault gouges (<2micron grain size). A total of 19 raw experimental datasets are presented as detailed in the index files: 13 on kaolinite-rich china clay, and 6 on cation-exchanged Mg-Montmorillonite. The raw data files, logged at either 1 or 2Hz, comprise confining pressures, upstream and downstream fluid pressures, force experienced by the direct shear assembly during triaxial compression, and absolute volumes of the confining pressure and fluid pressure reservoirs. Data is provided as measured by gauges in the pressure vessel in Volts, and also as calculated in MPa, kN and mm3. Also presented are the outputs of MATLAB models run to simulate the rate and state parameters k, a, b, dc and f0 for each experiment, with error data presented as 2sigma and standard error values. Parameters were determined using a non-linear least-squares fitting routine with the machine stiffness treated as a fitting parameter (c.f. Noda and Shimamoto, 2009). Data were fit by a single set of state variables (a, b, dc) with a linear detrend. Also presented are the outputs of Specific Thermogravimetric Analyses on kaolinite-rich china clay and Mg-montmorillonite.