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 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 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

These data comprise input and output files from first principles molecular dynamics calculations on the soil mineral kaolinite, detailing its interactions with four different veterinary antibiotics, namely enrofloxacin, florfenicol, ciprofloxacin and florfenicol amine. The dataset includes the final, complete molecular dynamics trajectories of the sorption process of each antibiotic on the mineral surfaces (Al-terminated or Si-terminated). The data were collected as part of the NERC Exploring the Frontiers grant (Grant No. NE/X009572/1), ‘Antibiotic chemistry in agricultural soils: modelling mineral-antibiotic interactions from first principles’. The work fits within the broad field of ‘emerging contaminants’ in the environment, and understanding drivers of antimicrobial resistance (AMR). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/ce86e353-5068-48a6-99bc-4898201d6e6b

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

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

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”.

This poster on the UKCCSRC Call 2 project Novel Materials and Reforming Process Route for the Production of Ready-Separated CO2/N2/H2 from Natural Gas Feedstocks was presented at the CSLF Call project poster reception, London, 27.06.16. Grant number: UKCCSRC-C2-181. Large reserves of shale gas and unconventional gases worldwide will ensure that hydrogen remains produced mainly via the catalytic steam reforming process (C-SR) for the next few decades. In conventional C-SR, the most energy intensive step is the production of syngas (CO+H2) in the primary reformer which relies on fired heaters in large scale furnaces. SR plants need to be enormous in order to be economical due to syngas production stage and H2 purification steps.

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

This poster on the UKCCSRC Call 2 project, Investigating the radiative heat flux in small and large scale oxy-coal furnaces for CFD model development and system scale up, was presented at the Cardiff Biannual, 10.09.14. Grant number: UKCCSRC-C2-193.