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The data set encompasses the data generated through the 8 experimental runs on the 25 kWth calcium looping pilot plant at Cranfield University arranged into 8 functional Excel spreadsheets. The operational data are gathered by the acquisition with Labview software (the composition of the gas from the calciner and carbonator; temperatures of the electrical furnaces on the preheating lines and around the calciner; temperatures of the gas in the preheating lines and in the calciner) and Pico software (temperatures in the carbonator and lower loop seal and pressures in the calciner and in the carbonator). Moreover, the data from the experimental diary (inputs of gasses and solids into the rig) and the data from the post-processing of the extracted solids are included. All the data are combined into comprehensible charts that describe and explain the experimental runs together with the mass and energetic model of the system during steady state operations.
[This application is embargoed until March 31, 2022]. This dataset contains a water resource systems model for the Sutlej-Beas system in western Himalayas. It includes all the files required to run the model for the historical period 1989-2008 and climate change scenarios for the middle (2032-2050) and end of the century (2082-2100) considering the uncertainty associated to different Representative Concentration Pathways and Global Climate Models. The WEAP model was built within the “Sustaining Himalayan Water Resources in a Changing Climate” (SusHi-Wat) project (NE/N015541/1), funded by the UK Natural Environment Research Council and the Indian Ministry of Earth Sciences through the Newton-Bhabha Fund. Full details about this application can be found at https://doi.org/10.5285/715db0b2-1d63-4842-ab80-f0f33b39e5e0
This poster on the UKCCSRC Call 2 project UK Demonstration of Enhanced Calcium Looping and first Global Demonstration of Advanced Doping Techniques was presented at the CSLF Call project poster reception, London, 27.06.16. Grant number: UKCCSRC-C2-209. Calcium (carbonate) looping is a promising carbon capture technology, which has been successfully demonstrated using a slip stream from the exhaust of a large-scale power plant. CO2 is captured as CaCO3, and is then calcined to release a pure stream of CO2 suitable for storage. The main advantage of this cycle is that the exothermic CO2 capture stage takes place around 650°C and the heat released in the carbonation process can be used in a standard steam cycle. The aims of this project are: • To demonstrate the viability of enhanced calcium looping technologies for CCS using a pelletized spent lime stream. • To demonstrate the viability of calcium looping for the removal of CO2 from industrial gases (steel and iron industry and cement industry). • To explore the use of enhanced Ca looping using HBr as doping agent.
Experimental results used to parameterise and a test a mathematical model of uranium diffusion and reaction in soil. The exeperiments and model are described in Darmovzalova J., Boghi A., Otten W., Eades, L., Roose T. & Kirk G.J.D. (2019) Uranium diffusion and time-dependent adsorption-desorption in soil: a model and experimental testing of the model. Eur. J. Soil Sci., doi: 10.1111/ejss.12814. The research was funded by NERC, Radioactive Waste Management Ltd and the Environment Agency through the Radioactivity and the Environment (RATE) programme (Grant Ref NE/L000288/1, Long-lived Radionuclides in the Surface Environment (LO-RISE)).
This project contributes significantly to the de-risking of a technology which has a significantly lower efficiency penalty than post-combustion capture using Monoethanolamine (MEA) scrubbing. The work here specifically targets two industrial sectors where MEA scrubbing is at a significant disadvantage (only ~ 30 % of the low-grade heat required for MEA scrubbing is present in a cement plant, for example ), and in both cases the spent CaO is valuable as an input to the process itself (either as the main feedstock for cement clinker production, or as a flux in iron production). The project builds on several current projects at both Imperial College and Cranfield University and offers excellent value for money because of these synergies. Grant number: UKCCSRC-C2-209.
This poster on the UKCCSRC Call 2 project, UK demonstration of Enhanced Calcium looping, and first Global Demonstration of Advanced Doping Techniques, was presented at the Cardiff Biannual, 10.09.14. Grant number: UKCCSRC-C2-209.
Final report for UKCCSRC Call 2 project, UK demonstration of Enhanced Calcium looping, and first Global Demonstration of Advanced Doping Techniques. Grant number: UKCCSRC-C2-209.
Hydrological monitoring data in this data collection result from dipwells installed at studied flood defence scheme, where electronic gauges monitored water-table fluctuations over time. Ecological data contain species sighting records of birds, butterflies, dragonflies and damselflies recorded during site visits to flood defence schemes in summer 2007. These data aim to show the relationship between water regimes and habitat potential.The study is part of the NERC Rural Economy and Land Use (RELU) programme. Agricultural Flood Defence Schemes in floodplain and coastal areas were once an important element of Government support for farmers in Britain. More recently, however, changing priorities in the countryside, concern about environmental quality and perceptions of increased flood risk in lowland areas, in part linked to climate change, have promoted a re-appraisal of land management options and policies for floodplain areas. Eight agricultural flood defence schemes, previously studied by the research team in the 1980s, have been re-examined to identify and explain changes in land and water management that have occurred over the last 40-years. This involved stakeholder and institutional analysis, farmer interviews, ecological surveys, field observations and modelling of hydrological and related ecological processes. Generic land use scenarios have been developed to consider management options that focus on single objectives, such as maximising agricultural production, maximising biodiversity and minimising flood risk in the catchment. The scenarios examined the impacts of changes in rural land use on ecosystem goods and services. The influence of agricultural policy, interacting with farmer circumstances and motivation, on land use has also been explored. The project also evaluated the impacts of the summer 2007 floods on agriculture and rural communities. The results revealed opportunities for achieving a wide range of benefits relating to farming, biodiversity, amenity, flood management, water quality and the wider rural economy. The study informed strategies for floodplain management, helping to develop approaches that are appealing to major stakeholders. Historical data on the studied flood defence schemes, farm business survey data and interviews with farmers at flood defence schemes, and interviews with farmers and rural businesses affected by summer floods in 2007 are available at the UK Data Archive under study number 6377 (see related resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).
This dataset consists of soil data for 64 field sites on paired farm sites, with 29 variables measured for soil texture and structural condition, aggregate stability, organic matter content, soil shear strength, fuel consumption, work rate, infiltration rate, water quality and hydrological condition (HOST) data. The study is part of the NERC Rural Economy and Land Use (RELU) programme. A move to organic farming can have significant effects on wildlife, soil and water quality, as well as changing the ways in which food is supplied, the economics of farm business and indeed the attitudes of farmers themselves. Two key questions were addressed in the SCALE project: what causes organic farms to be arranged in clusters at local, regional and national scales, rather than be spread more evenly throughout the landscape; and how do the ecological, hydrological, socio-economic and cultural impacts of organic farming vary due to neighbourhood effects at a variety of scales. The research was undertaken in 2006-2007 in two study sites: one in the English Midlands, and one in southern England. Both are sites in which organic farming has a 'strong' local presence, which we defined as 10 per cent or more organically managed land within a 10 km radius. Potential organic farms were identified through membership lists of organic farmers provided by two certification bodies (the Soil Association and the Organic Farmers and Growers). Most who were currently farming (i.e. their listing was not out of date) agreed to participate. Conventional farms were identified through telephone listings. Respondents' farms ranged in size from 40 to 3000 acres, with the majority farming between 100 and 1000 acres. Most were mixed crop-livestock farmers, with dairy most common in the southern site, and beef and/or sheep mixed with arable in the Midlands. In total, 48 farms were studied, of which 21 were organic farmers. No respondent had converted from organic to conventional production, whereas 17 had converted from conventional to organic farming. Twelve of the conventional farmers defined themselves as practicing low input agriculture. Farmer interview data from this study are available at the UK Data Archive under study number 6761 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).
The data set provides Computed Tomography based soil microstructures of a sandy loam soil (Invergowrie, Scotland) providing the distributions of soil, air and water. The images provide two water conditions (20±0.5 and 80±0.5% of the pore volume), with distribution at pore scale computed using a lattice-Boltzmann modelling approach, for five soil bulk densities (1.2, 1.3, 1.4, 1.5, 1.6 g cm-3), and three repetitions per bulk density (30 images). The domain size of the images is 512x512x512 voxels with a voxel resolution of 24 µm. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/0d290420-913a-4858-a090-fdbce616c247