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2022

112 record(s)
 
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    The Seabed Geology 10k: Bristol Channel is a digital geological map portraying the distribution of the different geological substrate units (either of bedrock or unlithified deposits) present on the seabed at a 1:10 000 scale. Additionally, to the Seabed Substrate layer, this dataset also includes i) a Geomorphology layer, revealing the presence and distribution of seabed morphological and geomorphological features and ii) a Structural Geology layer, that delineates the principal structural features observed at rockhead. The bedrock geology is divided into seven stratigraphical units: Pembroke Limestone Group (PEMB); Mercia Mudstone Group (MMG); Penarth Group (PNG); the Lias Groups' St Mary’s Well Bay (STM), Lavernock Shales (LVN) and the Porthkerry (PO) members; and the Inferior Oolite Group (INO). The Lexicon code of the stratigraphical units is provided in parentheses, as defined in the ‘BGS Lexicon of Named Rock Units’. The superficial deposits mapped are comprised of only marine sediments that were classified based on their grain size. However, Folk classification was not used to define the sediment classes. The sediments are divided into Gravel (V); Sand and Gravel (XSG); Sand (S); Sand and Mud (XSM); Mud (M); and Gravel, Sand and Mud (XVSM). The RCS code of the stratigraphical units is provided in parentheses, as defined in the ‘BGS Rock Classification Scheme’.

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    BGS GeoScour v2 provides river scour susceptibility information for Great Britain using a three-tiered data provision allowing increasing levels of understanding at different resolutions from catchment to local (channel/reach) scales. GeoScour v2 includes 18 GIS layers, providing information on the natural characteristics and properties of catchment and riverine environments for the assessment of river scour in Great Britain. The dataset product fills a gap in current scour modelling, with the input of geological properties. It provides an improved toolkit to more easily assess and raise the profile of scour risk, now and in the future, to help infrastructure providers and funders prioritise resources, identify remedial works to preclude costly and prevent disruptive failures. The product has broad applications through its adaptation to suit multiple types of asset susceptible to fluvial erosion. GeoScour looks specifically at the geological factors that influence scour and does not consider any hydraulic or hydrodynamic factors. The GeoScour Dataset Product is designed to be used by multiple stakeholders with differing needs and therefore, can be interrogated at a number of levels. Tier 1 A catchment stability dataset provides a summary overview of the catchment characteristics, typical response type, and evolution. It can be used as a high-level overview for incorporation into catchment management plans, national reviews and catchment comparisons using Tier 2 datasets are available as smaller catchment areas and focusses on providing data for more detailed catchment management, natural flood management and similar uses. It analyses geological properties such as flood accommodation space, catchment run-off potential, geomorphology types, and additional summary statistics for worst, average, and best-case scenarios for underlying surface geology scour susceptibility, as well as additional summary statistics of key environmental parameters such as protected sites and urban coverage. Tier 3 datasets provide the detailed riverine information that is designed to be incorporated into more complex river scour models. It provides the baseline geological context for river scour development and processes and identifies important factors that should be considered in any scour model. Factors such as material mineralogy, strength and density are key properties that can influence a river’s ability to scour. In addition, an assessment of river fall, sinuosity and flood accommodation space is also provided. This data is of use to those assessing the propensity for river scour for any given reach of a river across Great Britain and can be used as an input into hydraulic/hydrodynamic models. Tier 1 and 2 datasets are Open Government Licence (OGL), Tier 3 is licenced.

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    The BGS Property Subsidence Assessment (PSA) dataset provides insurers and homeowners access to a better understanding of the shrink-swell hazard at both the individual property and/or postcode level for England and Wales. It builds upon the GeoSure shrink-swell data by mapping the hazard to the individual building polygon and considering the other susceptibility factors of building type, foundation depth, and drainage and tree proximity. The user receives GIS building polygons with an overall susceptibility to subsidence score between 1-100. Scores are also classified from non-plastic to very high. Each building polygon is also scored from 1-10 for each subsidence factor (geology, foundation, drainage, building type, building storey and tree proximity). Postcode data is also available as a table showing the ‘average’ PSA score for all buildings within the postcode. The identification of shrink-swell related subsidence prone areas, alongside the inclusion of potential sources to exacerbate this phenomena, can better inform insurers and homeowners and form the basis to make decisions concerning prevention and remediation. The product enhances geological information obtained from GIP and GeoSure via the inclusion of the crucial shrink-swell susceptibility factors (proximity to trees and foundation depth). This therefore allows the derivation of a risk element for the housing stock at Building level, which is then generalised to Postcode level.

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    The newGeoSure Insurance Product (newGIP) provides the potential insurance risk due to natural ground movement. It incorporates the combined effects of the 6 GeoSure hazards on (low-rise) buildings: landslides, shrink-swell clays, soluble rocks, running sands, compressible ground and collapsible deposits. These hazards are evaluated using a series of processes including statistical analyses and expert elicitation techniques to create a derived product that can be used for insurance purposes such as identifying and estimating risk and susceptibility. The evaluated hazards are then linked to a postcode database - the Derived Postcode Database (DPD), which is updated biannually with new releases of Ordnance Survey Code-Point® data (current version used: 2022.1). The newGIP is provided for national coverage across Great Britain (not including the Isle of Man). This product is available in a range of GIS formats including Access (*.dbf), ArcGIS (*.shp) or MapInfo (*.tab) on request. The newGIP is produced for use at 1:50 000 scale providing 50 m ground resolution.

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    The BGS GeoCoast Dataset is a Geographic Information System (GIS)-based analysis for indicating multi-hazards and interdependencies within the coastal zone of Great Britain (not including Orkney and Shetland). GeoCoast represents the natural geological coastline (around the mainland of Great Britain) as if no coastal defences or made ground are present. This will be of particular value in areas where coastal defences are no longer maintained. GeoCoast will offer anyone with assets, or an interest in the coastline around Great Britain, access to easy-to-use datasets linked to geohazard data. This will allow users to interpret potential interdependencies in terms of erosion, flooding, habitat and other vulnerabilities. These datasets are divided into two data packages: Premium and Open datasets, which include the following information: The data is delivered in GIS ESRI point, polyline and polygon format (other formats available on request).

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    Reflectance Transformation Imaging files of specimen BGS GSM106352, a large (1.0 x 1.2m) display cast, made from Jesmonite AC-300 and coloured dark gray and showing several species typical of the fossil biota on the Bed B surface of Wilby et al. (2011) in Charnwood Forest. Wilby. P, Carney, J.N, Howe, M.P.A 2011 A rich Ediacaran assemblage from eastern Avalonia: Evidence of early widespread diversity in the deep ocean. https://doi.org/10.1130/G31890.1

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    The raster provide the output of a machine-learning random forest algorithm modelling the occurrence of ferromanganese (Fe-Mn) crust deposits in the world ocean. This raster constitutes a data-driven approach for mineral prospectivity mapping of Fe-Mn crusts that should be used in conjunction with other expert-driven prospectivity analysis to guide the assessment of Fe-Mn crust coverage in the world ocean and potential mineral exploration. The raster contains values between 0.07 and 0.92. Any values outside of that range (e.g., 0) are outside of the model prediction and should not be displayed. To reproduce data as displayed in the forthcoming associated publication, it is recommended to apply a 'Percent Clip' stretched 'Viridis' colour scheme.

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    A core scanning dataset from part of the Ellesmere Port-1 drill core that was drilled for unconventional hydrocarbons in 2014. Approximate 40 m of core from the Bowland Shale Formation in the Ellesmere Port-1 (1532.7 – 1663.15 m) was scanned for high-resolution optical images and X-ray fluorescence (XRF) downcore point measurements using the Itrax MC core scanner (Cox Analytical Systems) at the Core Scanning Facility (CSF) at the British Geological Survey. Core scanning was utilised as part of the commission phase of this facility.

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    The <250um fraction of 19 household vacuum dust samples (collected by citizen participants during 2019-2021) were extracted using high throughput isolation of microbial genomic DNA and sequenced using Illumina NextSeq (12 samples from a national campaign within the UK, 7 samples from Greece and a negative reagent control included to ensure sterility throughout the processing and sequencing steps). These data are available (following period of embargo) from the European Nucleotide Archive via the individual sample accession numbers ERS9609044 to ERS9609063, submitted under the study ID PRJEB49546. Sample location data are provided at town/city, country level. Given the amount of time people spend indoors, residential environments are perhaps the most important, but understudied environments with respect to human exposure to microbes and other contaminants. Across our urban environments, anthropogenic activities (both current and legacy) provide for multiple sources and pathways for the generation and distribution of microbes, inorganic and organic contaminants within the home environment, yet we know relatively little about the potential for dissemination of antibiotic resistance in microbial communities within indoor dust.

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    A Multiphysics model for a molten carbonate fuel cell (MCFC) developed in COMSOL. This is a multiphysics model for a MCFC. It has been built using COMSOL Multiphysics®. It enables the user to investigate the composition of the fuel and flue gases as well as the design parameters (e.g. the thickness of the electrolyte) on the performance of the fuel cell and the efficiency of CO2 capture. For example, the impact of CO2 concentration in the flue gas on the fuel cell performance and the carbon capture factor (which is a measure on how much CO2 has been concentrated from the flue gas) could be evaluated. One of the key findings show that the fuel cell performance improves and the carbon capture factor decreases with increasing CO2 in the flue gas. A process model for liquid fuel production through reverse water gas shift (RWGS) and Fischer-Tropsch (FT) developed in Aspen Plus. The model enables the user to examine the production of liquid fuels through CO2 hydrogenation followed by FT synthesis. The user can test different conditions for the RWGS such as H2/CO2 ratio and temperature and investigate how these changes affect the CO2 conversion. The product distribution for the FT follows the Anderson–Schulz–Flory (ASF) distribution. The ASF model is applied in a FORTRAN calculator and assumes a chain growth probability factor (α) of 0.9; the user may change the value of α and investigate how this affects the product distribution. A CO2 compression model developed in Aspen Plus. The model liquefies the captured CO2 stream through multistage compression with intermediate cooling and water condensation/removal. UKCCSRC Flexible Funds 2020.