This presentation on the UKCCSRC Call 1 project, UK Bio-CCS CAP, was presented at the Cranfield Biannual, 22.04.15. Grant number: UKCCSRC-C1-38.

This presentation on the UKCCSRC Call 1 project, UK Bio-CCS CAP, was presented at the Cardiff Biannual, 10.09.14. Grant number: UKCCSRC-C1-38.

This poster on the UKCCSRC Call 1 project Bio-CAP-UK: Air/oxy biomass combustion with CO2 capture technology was presented at the CSLF Call project poster reception, London, 27.06.16. Grant number: UKCCSRC-C1-38. Bio-CCS - bioenergy with carbon capture and storage - has the ability to achieve potential net negative CO2 emissions, vital for meeting legally binding and increasingly stringent emission targets and carbon budgets. Bio-CCS has a large and distinct potential for significantly lowering CO2 emissions from energy production; thus the key messages from this programme will have clear policy implications on decarbonisation strategies. The Bio-CAP-UK project aims to accelerate progress towards achieving operational excellence for flexible, efficient and environmentally sustainable bio-CCS thermal power plants by developing and assessing fundamental knowledge. This is being achieved through extensive multi-scale experimental work, including bench and pilot-plant tests, combined with system simulations, techno-economic analysis and life cycle studies. The programme focuses on comparing air-firing coupled with post-combustion carbon capture to oxy-fuel combustion.

To accelerate progress towards achieving operational excellence for flexible, efficient and environmentally sustainable Bio-CCS thermal power plants by developing and assessing fundamental knowledge, pilot plant tests and techno economic and life cycle studies. In terms of assessing CO2 capture, the UK CCS on-going research portfolio includes coal and gas-fired generation, whilst limited work is being conducted on the assessment of dedicated biomass to power with CCS, or indeed, of co-firing fossil fuel generation with higher rates of biomass with CCS. The project will also greatly expand the on-going research in SuperGen Bioenergy concerning supply chains of torrefied biomass and Bio-CCS. Grant number: UKCCSRC-C1-38.

This dataset contains sequential biomass harvests from a plant growth experiment carried out under controlled environmental conditions in Sheffield. The experiment was carried out in three parts in 2016 and 2017, and was designed to investigate differences in growth among grasses with the C3 and C4 photosynthetic pathways, and with annual and perennial life histories. Plants were harvested approximately weekly over a period of five weeks. The data include information on the dry biomass of roots and leaves, and the numbers of roots, leaves and shoot branches. Also included is an independent dataset of leaf anatomical characteristics derived from herbarium specimens, which was used to test how mechanical support scales with leaf size. Finally, the data include the phylogenetic relationships among species, which were used in analyses. The work was funded by NERC standard grant NE/N003152/1. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/cb0d7a37-45c5-4645-b5ef-ba097d92fc20

Data comprises of the uptake of the plant nutrient phosphorus (P) by seven common and often co-occurring herbaceous plants grown in limestone grassland soil in pots. P uptake is from one of three different sources of P that were injected into the soil, with the P sources being labelled with radio-isotope 33P, such that uptake of this could be quantified by assessing the radioactivity of the plant tissue. The plant species were grown in pots as monocultures, and as mixed communities containing all seven species. The 33P labelled P sources that were injected into the soil were orthophosphate, DNA and calcium phosphate. Assessment of the amount of 33P taken up was undertaken by harvesting and analysing plant shoots six days after the 33P source was injected into the soil. The datasets contain biomass of the harvested plant material, its radioactivity as assessed by scintillation counting, and the calculated proportion of the 33P supplied that was taken up into plant shoots. The data also contains % cover abundance values of the plant species from surveys undertaken at Wardlow Hay Cop, the limestone grassland from where the soil was sourced on which the plants were grown for the 33P addition study. Full details about this dataset can be found at https://doi.org/10.5285/87cdc267-a8c7-4f59-83b4-1bceaae837ad

In this submission we Include three data sets collected as part of a NERC Urgency programme. Data were collected from a key field site within the Marlborough Fault Zone (MFZ), New Zealand. The Mw 7.8 Kaikoura Earthquake of 14th November 2016 was characterised by a surprising degree of spatial complexity in the surface displacement field in the Marlborough region, South Island, New Zealand. This complexity includes movement on up to 12 faults, besides a high degree of variability in apparent slip along strike of individual faults over relatively short distances. The Urgency programme included rapid collection of Terrestrial Laser Scanning (TLS), Structure from Motion (SfM) and Global Navigation Satellite System (GNSS) data immediately after this event. We include data for one of our field sites for which data collection succeeded, and processing has been completed. For a summary of the key initial findings from this data set, see the following EGU 2018 Abstract and summary: https://meetingorganizer.copernicus.org/EGU2018/EGU2018-6847.pdf

These dataset files show the calibration of a sensor for mercury (II) ions using a Fluorimeter and either HgCl2 or HgNO3. A range of different sample conditions are tested, including sensor concentrations and relative proportions of water and a methanol co-solvent (required for solubility of the probe). Also tested was the ability of acid to affect the probes sensitivity to mercury as nitric acid is needed for the stability of HgNO3 as an analyte. File names listed show the concentration of sensor and the ratio of water to methanol tested. Inductively coupled plasma mass spectrometry (ICP-MS) data are also given these are used to validate the sensors calibration and also to monitor the levels of soluble mercury content of dental amalgam samples held at either (11⁰C or 37⁰C) in water and saliva. The supernatant of these suspensions is filtered and measured using ICP-MS to give the data as reported. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/bc82f15b-8db6-4398-bfec-655a1eecf2d7

The data comprise outcomes from questionnaire surveys conducted with greenspace users on their perceptions of experimentally manipulated urban meadows (varying levels of diversity and vegetation height of sown wildflower meadows), and associated socio-economic data of respondents to the questionnaire surveys. The experimental meadows were located in Bedford and Luton. Data was collected by the data authors, and participants gave informed consent before completing the questionnaires. The work was initially completed under the Fragments, functions and flows NERC BESS project in 2014. The scaling of biodiversity and ecosystem services in urban ecosystems was funded by grant NE/J015369/1 from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. Subsequent analysis was carried out under the NERC grant ‘Location, Configuration, Distribution: the Role of Landscape Pattern and Diversity in Ecosystem Services’ (NE/K015508/1). Full details about this dataset can be found at https://doi.org/10.5285/29d6345f-9f53-4894-8f60-80843f49c017

This data collection results from abundance surveys of 7 species of weeds in ca. 500 lowland arable fields in 49 farms over three years. Each field was divided into large grids of 20x20 metre cells, and the density of seven species was estimated three times a year. The study is part of the NERC Rural Economy and Land Use (RELU) programme. In the context of changing external and internal pressures on UK agriculture, particularly those associated with the ongoing reform of the EU Common Agricultural Policy, it is imperative to determine whether all of the various dimensions of sustainability - including the relevant economic and environmental objectives as well as social and cultural values - can be integrated successfully at the farm and landscape levels. Although the ways in which economic, technological, and regulatory changes are likely to affect the profitability and management of farms of varying size are reasonably well understood, there is not the knowledge or understanding to predict the resulting effects on biodiversity. For example, the effect of changes in arable farming practices on field weeds and, in turn, on habitats and food supply required to sustain farm birds is a case in point. This knowledge is critical, however, if we are to understand the ecological consequences of changes in agricultural policy. Furthermore, it is also important if we are to design and justify changes in farming methods that can not only enhance nature conservation, but do this is ways that are practical and appealing from a farmer's point of view. This understanding is essential if we are to achieve an agriculture that is sustainable in both economic and environmental terms and is widely perceived to have social and cultural value. A consistent theme in all components of this research project is to understand the behaviour (of farmers, weeds or birds) and then use this information to produce predictive models. Whilst there have been a number of models of economic behaviour, weed populations and bird populations - including many by the research team here - the really novel component of this research is to integrate these within one framework. Farmer interviews on economic attitudes and preferences associated with and importance of different land-use objectives to lowland arable farmers are available at the UK Data Archive under study number 6728 (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).