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These data files represent simulations of hydrated cation vacancies in the mantle mineral forsterite (Mg2SiO4) undertaken using the CASTEP atomic scale simulation code (http://www.castep.org/). Results from these simulations allow the structure relative stability of different defect configurations to be compared. Three types of cation vacancies are considered (M1, M2 and Si) each decorated by hydrogen in order to charge balance the system. For M1 and M2 this results in multiple configurations (with hydrogen bonded to different oxygen atoms around the vacant site). For Si there is only one configuration as all four oxygen atoms are bonded to hydrogen for the charge neutral defect. For each configuration input files detail the initial atomic structure of the defect along with simulation parameters. Output files record the progress of the simulation, the final atomic structure, the energy of this structure, and various predicted properties of the structure. Only ASCII output data is included as binary data created by CASTEP is not intended to be portable, and can easily be recreated using the ASCII files.
These data consist of a spreadsheet containing 557 ground control points (GCPs) collected in the Everest region of Nepal between October 2015 and October 2016. GCPs were collected using a Leica GS10 differential Global Positioning System (dGPS), post-processed against base station data at Syangboche. These final data have sub-centimetre accuracy (in x, y and z) in all cases. Point positions are heavily concentrated around meltwater ponds on the glacier surface, and prominent features around the glacier margin. These data will be used by PhD students and staff in the School of Geography, University of Leeds, to provide ground control for fine-resolution satellite imagery and Structure-from-Motion surveys to assess mass loss processes on Khumbu Glacier.
This data set contains example input and output files from density functional theory calculations of rare earth systems, using the Vienna Ab initio Simulation Package (VASP), The data set it split into two parts. The first data set contains the input and output files of molecular dynamics simulations of MCl3 in solution, where (M = Nd, Gd and Er) at ambient conditions, which was modelled at 341 K using the optB88 exchange-correlation functional. The calculations were run in order to investigate speciation in rare earth chloride solutions, including trends across the row, using a light (Nd), medium (Gd) and heavy (Er) rare earth. These particular calculations were used to validate classical interatomic potentials that were used to perform more complex simulation on larger systems and longer timescales. Only the first 2 ps of the trajectories are deposited here, since the complete trajectories are large. The second data set contains example input and output files for lattice dynamics calculations of the thermodynamics properties (heat capacity and entropy) of Nd-monazite and Nd-xenotime at ambient conditions up to 1200 K. In addition, it includes scripts for processing and plots of final results. These are useful for thermodynamical modelling of rare earth systems. Only the input and output files for Nd are deposited here, since the files are large and input files for Gd and Er are identical, save for the change in element.
The datasets contains species presence and background points, and their associated environmental data for non-native common wall lizard (Podarcis muralis). These data are included for local and national scale modelling of likelihood of species presence, as used in the modelling software MaxEnt. The .asc files included are the raw spatial data of parameters (i.e., distance to nearest road) used in modelling at various local regions, from which SWD 'samples with data' were extracted. Outputs from the local MaxEnt models produced the .txt files included. These serve as landscape layer inputs (habitat suitability and movement cost layers) for modelling population growth and spatial spread in the Individual based modelling platform, RangeShifter. Subsequent outputs of projected population growth (number of individuals per landscape cell) and x/y coordinates for each cell, are presented in files with the prefix Pop.csv and avg.csv (averaged data over 50 replicate runs). Full details about this dataset can be found at https://doi.org/10.5285/8ae3f9ef-9a75-4237-afbd-e01abe02e75b
This data contains the results of student and professional perceptions surveys conducted in the UK before and after e-Learning training, as part of a project to determine the effectiveness of e-Learning as a training tool. The dataset include two surveys; before and after e-Learning training. Students and professionals were given two separate surveys which were combined to create one dataset. The surveys were collected between September 2015 and July 2018. The objective of the survey was to collect data on participants’ awareness, risk perceptions and self-reported behaviours on biosecurity for invasive species. The topics on both the before and after survey included age, role at institution, field of work/study, field activity environments, cleaning methods for equipment, outerwear/footwear and transport and awareness and perceptions of risk around invasive species and biosecurity campaigns. The data does not include the aggregated cleaning scores that were used for the analysis nor has it excluded any participants that were not used in the final data analysis. The dataset has been anonymised by removing names of respondents, email addresses, departments or organisations worked for or studied in, and text responses which could have made the participant identifiable. The research was funded by NERC project no NE/N008391/1. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/ac271791-b722-489c-9b68-b37316ec826c
The dataset provides transcripts from focus groups in Salima, Mangochi and Zomba (Malawi). The focus groups' discussions concern the monthly agricultural activities in association with the climate services and extreme weather events. The data were produced as part of NERC Program Science for Humanitarian Emergencies and Resilience (SHEAR). Grant reference - Improving Preparedness to Agro-Climatic Extremes in Malawi (IPACE-Malawi). Full details about this dataset can be found at https://doi.org/10.5285/2b8cb09f-9348-4115-a90e-818eade599af
The dataset provides transcripts from focus groups in Salima, Mangochi and Zomba (Malawi). The focus groups' discussions focused on important monthly agricultural activities in association with the climate services and extreme weather events. This outlined how climatic factors affected agricultural decision-making. The data were produced as part of NERC Program Science for Humanitarian Emergencies and Resilience (SHEAR). Grant reference - Improving Preparedness to Agro-Climatic Extremes in Malawi (IPACE-Malawi). Full details about this dataset can be found at https://doi.org/10.5285/199b0046-79a3-4e74-8152-17f10c376671
This dataset contains 204 ascending and 300 descending Sentinel-1 geocoded unwrapped interferograms and coherence, and 70 ascending and 102 descending Re-sampled Single Look Complex (RSLC) images for each acquisition date. This data set also includes the original size Digital Elevation Model (DEM) used during InSAR processing. Data used by: Moore et al, 2019, “The 2017 Eruption of Erta 'Ale Volcano, Ethiopia: Insights into the Shallow Axial Plumbing System of an Incipient Mid-Ocean Ridge”.
The world's population is predicted to grow from the current 7 billions to a plateau of approximately 9.2 billions to be reached within the next 60 years, representing roughly a 30 % increase in a not so distant future. The need for more energy efficient methods of producing synthetic fertilisers to meet the resulting increases in food demand and in crude (and bio) oils refining operations -on crudes of ever poorer quality- motivates the scientific community to reconsider the limitations of the mature technologies of synthetic fertilisers production and hydro-refining processes (HDS, HDN, HDM, HDO, hydrocracking) which both rely on the supply of hydrogen. Synthetic fertilisers necessitate hydrogen and nitrogen as feedstocks to make ammonia, which represents the building block for other fertilisers such as urea or ammonium nitrate. The current cheapest and most common means of producing hydrogen is natural gas steam reforming. With an abundance of natural gas reserves becoming exploitable worldwide in recent years via the hydraulic fracturing of shale gas, and given the ever more severe regulations on atmospheric pollution caused by flaring of associated gas from refineries and oil extraction operations, the production of hydrogen is very likely to remain dominated in the years to come by the process of steam reforming using natural gas as its feedstock (aka 'steam methane reforming' or 'SMR'). Conventional SMR technology usually features many unit operations (desulphurisation, pre-reforming, primary reforming, furnace, high and low temperature water gas shift (HT-WGS, LT-WGS), and final separation, with as many heat integration steps in between the units in order to reach an energy efficiency of roughly 80%. This efficiency is only attainable thanks to economies of scale, and SMR plants are consequently enormous. To avoid storage and transport costs of H2, the ammonia/ammonium nitrate/urea plants, or refinery operations are usually conducted near the site of SMR, therefore the production of the final products of fertilisers or clean fuels is very centralised, and thus vulnerable, as well as incurring large distribution costs. With sources of natural gas becoming more remote, widely distributed, shorter lived and quickly relocated, the process of converting natural gas to the final products fertiliser/clean fuel should become more mobile, down-scaleable, as fracking gas wells see their production decay with time and move to different sites. This proposal seeks to reduce significantly the energy and materials demand for the conversion of natural gas feedstocks into ready separated streams of the H2, N2 and CO2 products of steam reforming (the building blocks of urea production) by coupling the in-situ high temperature CO2 capture during the reforming reactions on a solid sorbent (a process called 'sorption enhancement') with the process of chemical looping steam reforming. A process is proposed with only two reactors, a reformer and a pressure/temperature swing separator, appropriate for the new, mobile, small scale industrial utilisation of natural gas, through realising the multiple synergies that are unique to the coupled process, and through the avoidance of expensive materials and awkward reformer geometries. Grant number: UKCCSRC-C2-181.
Dupont, Valerie (2017) Data associated with "Chemical equilibrium analysis of hydrogen production from shale gas using sorption enhanced chemical looping steam reforming" in Fuel Processing Technology. University of Leeds. Data file containing datasets used to generate the figures and tables in the paper. [Dataset] https://doi.org/10.5518/149. [Publication] http://doi.org/10.1016/j.fuproc.2017.01.026