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This dataset contains anaerobic ammonium oxidation (anammox) and denitrification activity of riverine sediments in the Hampshire Avon catchment (UK). Nine rivers within sub-catchments of contrasting geology (clay, sand, chalk) were investigated. Data were obtained via laboratory incubations (potential data) and direct, field-based measurements (in situ data) in summer 2013. Also included are chemical parameters determined in porewaters prior to in situ rate measurements. Full details about this dataset can be found at https://doi.org/10.5285/d1b08279-68a8-4d93-afa2-576e903cc04d
Between 1980 and 2009, marine macronutrient concentrations (silicate, Si(OH)4-Si; phosphate, PO4-P; nitrate, NO3-N; ammonium, NH4-N; and nitrite, NO2-N) and concurrent temperature and salinity were measured by British Antarctic Survey researchers as part of an integrated ecosystem investigation. Areas sampled included South Georgia and the wider Scotia Sea, around the Antarctic Peninsula, and in the Bellingshausen Sea. The data were collected from aboard the RRS John Biscoe or the RRS James Clark Ross during all months of the year with the exceptions of May and June. Samples were collected from CTD water bottles (vertical profiles) to maximum depth of 5400 m, and by monitoring continuously the ship''s non-toxic seawater supply (intake at 6 - 7 m) while the vessel was transecting. Analyses were performed immediately aboard ship and logged to computer while full data analysis was performed post-cruise using custom written software programmes. The data collection was enabled through Natural Environment Research Council National Capability funding to the British Antarctic Survey. This was organised through a series of BAS programmes including the Offshore Biological Research programme, the DYNAMOE programme and the ECOSYSTEMS programme. Data creation was facilitated through a combination of NERC funding for Antarctic Logistics and Infrastructure (ALI) Science and the NERC Science Multi-Centre Round 2 (NCSM2) programme BIOPOLE (NE/W004933/1).
This data set comprises of hourly water quality monitoring and flow data of a site within the River Loddon catchment, UK, from September 2017 to September 2018. Parameters measured were temperature, conductivity, pH, ammonium, turbidity, dissolved oxygen, UV-Vis spectral scan from 197-720nm. Daily samples were also taken at 9am GMT and occasional storm samples were taken hourly and then analysed in the laboratory for pH, conductivity, turbidity, total suspended solids, non-purgeable organic carbon, UV-Vis spectral scan from 200-800nm and 12 pesticide concentrations: 2-4-D, Bentazone, Carbendazim, Carbetamide, Chlorotoluron, Clopyralid, MCPA, Mecoprop, Metaldehyde, Propyzamide, Quinmerac and Metazachlor. This data was created as part of the TWENTY65 project, funded by the Engineering and Physical Sciences Research Council (Grant number: EP/N010124/1) and with some additional funding from Affinity Water and Syngenta. Full details about this dataset can be found at https://doi.org/10.5285/331659d7-da72-48a2-9b52-63c003557990
This dataset contains nitrogen data from nitrate, ammonium and nitrite, total nitrogen and carbon data, and elemental composition data from anaerobic digestate and biomass ash from UK bioenergy production. Anaerobic digestate was sampled 8 times from different industrial scale plants across the UK between January 2015 and January 2018 and biomass ash was sampled in January 2015 and June 2016. Anaerobic digestate was sourced from segregated food waste (mainly household waste), pig slurry, maize silage, vegetables waste, sweet corn waste, aerobically treated food waste, food manufacturer waste and other biodegradable sludge from within the UK. Biomass ash, both fly and bottom ash, from virgin and recycled wood was sourced from three sites within the UK and one from Spain. All laboratory analyses were undertaken at Lancaster University using standardised methods. The data were collected as part of the research grant, Developing a suite of novel land conditioners and plant fertilizers from the waste streams of biomass energy generation. The research was funded by NERC, award NE/L014122/1. Full details about this dataset can be found at https://doi.org/10.5285/990c54f6-5c92-4054-8bfa-953533a89149