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 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

These files represent the model build used to generate postcode level concentrations to estimate Aspergillus fumigatus exposure from outdoor composting activities in England between 2005 and 2014. Each file, named after the nearest SCAIL-Agriculture validated meteorological station used to model the outputs, contains modelled concentrations at composting sites within 4km of each composting site. These files, presented as.txt, are the .APL files used to model bioaerosol dispersion from every composting site in England, using ADMS 5. To use this file, please convert the .txt file extension to .APL and upload into ADMS. From there, press run. Model runs are likely to generate over 40GB of data per model run. The work was supported by the Natural Environment Research Council grants ((NE/P010806/1 and NE/M011631/1). Full details about this dataset can be found at https://doi.org/10.5285/9f1b307b-9b47-4a11-8e5b-e14008ad0032

This dataset is a model output from the European Monitoring and Evaluation Programme (EMEP) model applied to the UK (EMEP4UK) driven by Weather and Research Forecast model meteorology (WRF). It provides UK estimates annual averaged atmospheric composition at approximately 5Km grid for the year 2015 for a set of vegetation removal experiments. * UK current vegetation * UK no vegetation * UK Urban current vegetation * UK No urban vegetation * UK Urban 25% open greenspace conversion * UK Urban 50% open greenspace conversion The EMEP model version used here is the rv4.10 and rv4.17, and the WRF model version is the 3.7.1. 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 and the Office of National Statistics to support the ONS-Defra natural capital accounting programme in the UK. Full details about this dataset can be found at https://doi.org/10.5285/bad6721c-574b-4229-b023-c7b13ae4c099

These datasets provide Concentration Based Estimated Deposition (CBED) values of sulphur and nitrogen atmospheric deposition for 5x5 kilometres (km) grid squares of the UK averaged over the years 2017 to 2019. 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/10.5285/1efa692d-76ca-406e-8736-837a457e16ee

This dataset contains time series observations of land surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), methane (CH4) and meteorological observations measured at two locations in the Flow Country blanket bog complex, Caithness and Sutherland, UK. The tower over the area affected by wildfire after initial felling (UK-DKF) is located at 58.431, -3.96 and monitors across a footprint affected by a wildfire in early May 2019. The tower over the area felled for restoration after previous afforestation (UK-DKE-RESTORED, which was not affected by the wildfire) is located at 58.428, -3.967 and measures fluxes from a footprint identical in ground flora, topography, soil type and previous management to that of the FIRE tower, with the only exception that the fire did not reach as far as the footprint monitored. The dataset comprises eddy covariance CO2, water and energy fluxes, originally collected at 20Hz and processed to 30-minute data, as well as accompanying meteorological observations, originally collected at 15 min and processed to 30-minute data. The time period covered in this dataset is 25/09/2019 – 20/05/2021. Full details about this dataset can be found at https://doi.org/10.5285/d4a7ca90-0c62-4a31-986e-f433e1644bf3

The data offers insights to utility of single particle ultraviolet light- induced fluorescence (UV-LIF) measurements in providing quantification and spatio-temporal characterisation of bioaerosols alongside the size distribution and characteristics of biological materials in airborne particles based on intrinsic bio fluorophores signatures. A novel ultraviolet light-induced fluorescence (UV-LIF) based bioaerosol sensor unit (Spectral Intensity Bioaerosol Sensor (SIBS)) was evaluated. The SIBS measures size, number, shape, and resolved fluorescence emission across 16 wavelength bands from 298 - 735 nm for two excitation wavelengths (285 nm and 370 nm) for single particles in real-time. Measurements entailed the chamber-based studies and real world environments (composting, dairy farms, chicken farms, sewage treatment plants, urban background, agricultural). This data stems as a part of a project (Detection and characterisation of inflammatory agents associated with bioaerosol emitted from biowaste and intensive agriculture) funded by the Natural Environment Research Council [NE/M01163/1]. The award was made under the auspices of the Environmental Microbiology and Human Health programme. The principal purpose was to assess the capabilities of the SIBS to enhance understanding of the bioaerosols emission and dispersion from industrial processes. Full details about this dataset can be found at https://doi.org/10.5285/98970053-b34c-44da-97bd-fbfc38fa8b7a

This is a dataset of environmental data, vegetation cover, and community- and species-level invertebrate herbivory, sampled at 14 experimental soil plots in the Hengill geothermal valley, Iceland, from May to July 2017. The plots span a temperature gradient of 5-35 °C on average over the sampling period, yet they occur within 1 km of each other and have similar soil moisture, pH, nitrate, ammonium, and phosphate. Full details about this dataset can be found at https://doi.org/10.5285/da5d7028-2aec-4da2-96ff-f347a0dfa77e