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Atmospheric Conditions

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  • This dataset comprises observations of snowline from the Snow Survey of Great Britain (SSGB) at 140 sites across Scotland . Daily observations were made between 1945 and 2007. Observations were made by a ground observer who looked out from a given location at 0900 GMT each day and noted the elevation at which snow cover was greater than 50%. The initial aim was to 'secure representative data relating to the occurrence of snow cover at different altitudes in the various upland districts over the period October to June'. The data were collated by the British Glaciological Society until 1954 and thereafter by the Met Office. It has been transcribed from paper records held in the Met Office archives in Edinburgh. Full details about this dataset can be found at https://doi.org/10.5285/caf989a5-82d7-4db7-b6ff-c0475fdae07e

  • This dataset consists of monthly ammonia (NH3) measurements from ALPHA® (Adapted Low-cost Passive High Absorption) samplers co-located with UKEAP DELTA sites from January 2021 to December 2021. The UK Eutrophying and Acidifying Atmospheric Pollutants (UKEAP) network measures air pollutants at rural sites across the UK. Originally the purpose of these measurements was for validation of new PTFE membrane for ALPHA® samplers prepared at UKCEH Edinburgh research laboratory. Full details about this dataset can be found at https://doi.org/10.5285/3590613d-c462-4972-a27b-d2245e0e93a0

  • This dataset consists of monthly ammonia (NH3) measurements from ALPHA® (Adapted Low-cost Passive High Absorption) samplers co-located with UKEAP DELTA sites from January 2022 to December 2022. The UK Eutrophying and Acidifying Atmospheric Pollutants (UKEAP) network measures air pollutants at rural sites across the UK. Originally the purpose of these measurements was for validation of a new PTFE membrane for ALPHA® samplers prepared at UKCEH Edinburgh research laboratory. Full details about this dataset can be found at https://doi.org/10.5285/86b3ca4a-143f-4a96-b6cd-38544e118f81

  • This dataset consists of ammonia (NH3) measurements at two sites in a rural location in South Lanarkshire. The sites are located in a dwelling, one site is inside and the other is outside in the garden area. The garden backs onto grassland which is part of a large dairy farm. The ammonia measurements are taken from a set of UKCEH ALPHA® (Adapted Low-cost Passive High Absorption) samplers from January 2021 to December 2021. Samplers are exposed in monthly cycles at the beginning of each month. Full details about this dataset can be found at https://doi.org/10.5285/366dee48-80c1-44a2-8a8d-2723a0fc3985

  • This dataset consists of ammonia (NH3) measurements at two sites in a rural location in South Lanarkshire. The sites are located in a dwelling, one site is inside and the other is outside in the garden area. The garden backs onto grassland which is part of a large dairy farm. The ammonia measurements are taken from a set of UKCEH ALPHA® (Adapted Low-cost Passive High Absorption) samplers from January 2022 to December 2022. Samplers are exposed in monthly cycles at the beginning of each month. Full details about this dataset can be found at https://doi.org/10.5285/122e87db-7269-4d6a-bc99-9a826fda3885

  • This dataset provides UK maps of baseline prior uncertainty (UQ) in fluxes of Greenhouse Gases (GHGs) carbon dioxide, CO2 (2014-15) and methane, CH4 (2015). Spatial maps of these GHG emissions are produced annually in the National Atmospheric Emissions Inventory (NAEI) but it is important to quantify uncertainty in these maps. These uncertainty estimates come from sectoral uncertainty data provided by the NAEI. Here, we propagate the uncertainty in the maps for each of the sectors contributing to the emissions using a Monte Carlo method, in order to quantify the uncertainty in the total emissions spatially. The Monte Carlo method employed here uses a novel approach (Nearest Neighbour Gaussian Process) to make calculations computationally affordable. These estimate the influence on the overall uncertainty of unknown errors in the model structure. Further details of the methodology used here can be found in the supporting documentation included with this data. In the near term, this methodology will be used and developed further in the NERC-funded project, DARE-UK (NE/S003614/1), to update UQ in maps of CO2 and CH4 for the UK. For that work and in general, it is useful to have a baseline prior uncertainty quantification against which future UK maps of uncertainty in CO2 and CH4 fluxes can be compared. Full details about this dataset can be found at https://doi.org/10.5285/739c65a5-12c0-439b-bbcd-1252a4086e87

  • This dataset contains fire emissions from Equatorial Asia for the years 2004, 2006, 2009, 2012, 2014 and 2015. The data is based on the Fire Inventory from National Center for Atmospheric Research with the addition of emissions from Indonesian peat fires, which contribute substantially to fire emissions in the region. The files for each year contain daily information on the area burned and emissions of several species, including CO, CO2 and PM2.5. Data is given for individual fires at 1km resolution. Fire emissions are provided for each year both for fires as measured, and under a scenario where degraded peatland in the region has been partially restored, reducing fire emissions. Full details about this dataset can be found at https://doi.org/10.5285/fdae44ed-8b22-4935-b889-b4b271138385

  • Data comprise relative humidity measured at an automatic monitoring buoy located in Blelham Tarn, UK. Data are provided from January 2012 to December 2019. Hourly averages are given, calculated from measurements taken every four minutes. All data is given in GMT (Greenwich Mean Time). This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/3df05e85-2c56-4bd9-9918-44b760e20b2e

  • This data resource consists of two files: (a) 1x1 km resolution Average Accumulated Exceedance (AAE) data summarising the exceedances of acidity critical loads for eight habitats; (b) 1x1 km resolution AAE data summarising the exceedances of nutrient nitrogen critical loads for thirteen habitats. The data provide information on the amount of excess acid or nitrogen deposition above the critical load values set to protect acid- and nitrogen-sensitive habitats in the UK. The AAE has been calculated using UK 5x5 km Concentration Based Estimated Deposition (CBED) data for 2013-15 - https://doi.org/10.5285/fd8151e9-0ee2-4dfa-a254-470c9bb9bc1e . The data were generated under Defra-funded work to assess the potential areas of acid and nitrogen sensitive habitats at risk of adverse impacts from excess atmospheric acid and nitrogen deposition. Reducing the area and amount of critical load exceedance continues to be a driver of Government policy on reducing emissions of acidic and nitrogen-containing air pollutants (sulphur dioxide, nitrogen oxides and ammonia). Full details about this dataset can be found at https://doi.org/10.5285/e32745d2-fb56-4f91-a235-6b213a8b45cb

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset provides Concentration Based Estimated Deposition (CBED) values of sulphur and nitrogen atmospheric deposition for 1x1 kilometres (km) grid squares of the UK averaged over the years 2018 to 2020. The data consist of deposition values for sulphur, oxidised nitrogen and reduced nitrogen, and base cations. Total deposition is the sum of four components calculated separately: wet deposition, dry deposition of gases, dry deposition of particulate matter and cloud droplet deposition. Habitat-specific data are provided for (i) moorland/short vegetation everywhere, and (ii) forest everywhere. Additionally, the grid square average over multiple land cover types (i.e. arable, grassland, forest, moorland, urban) is also calculated. The habitat-specific data are recommended for use with critical loads for the calculation of critical load exceedances. The work in generating and compiling the dataset has been funded by the UK Centre for Ecology & Hydrology (UKCEH) and various Departments for Environment, Food & Rural Affairs (Defra) contracts. Full details about this dataset can be found at https://doi.org/10.5285/4a5a9140-96f1-4aee-b547-ef570238fdbd