This dataset includes individual passive detector measurements of radon Rn-222 in the air of artificial burrows, Rn-222 measurements by instrumentation in soil gas of interstitial soil pores and burrow air, gamma analyses results for soil samples and, soil moisture and temperature data. Estimates of absorbed dose rates to wildlife from exposure to natural background radionuclides are required to put estimates of dose rates arising from regulated releases of radioactivity and proposed benchmarks into context. These data are from a study conducted at seven sites in northwest England (comprising broadleaved and coniferous woodlands, scrubland and pastures). Passive track etch detectors were used to measure the Rn-222 concentrations in artificial burrows over a period of approximately one year (July 2009 to June 2010). Instrumented measurements of burrow air and soil pore gas were also conducted in October 2009. The data result from a study funded by NERC-CEH and the England & Wales Environment Agency. Full details about this dataset can be found at https://doi.org/10.5285/2641515F-5B76-445C-A936-1DA51BF365AD

[THIS DATASET HAS BEEN WITHDRAWN]. The dataset captures the temporal and spatial variability of dilution factors (DFs) around the world using geographically referenced data sets at 0.5 degree resolution and includes long term annual and monthly DFs grids. The dilution factor (DF) dataset is composed of 13 rasters: 1 annual and 12 monthly. DFs are a critical component in estimating concentrations of 'down-the-drain' chemicals which enter freshwaters following consumer use via the domestic waste water stream (e.g., pharmaceuticals, household cleaning products). The DF is defined as the ratio between flow and total domestic wastewater effluent generated within a catchment. The methodology was specifically developed to be applied across the world even within those countries where river flow data and/or wastewater effluent data is scarce. The present dataset has potential for a wide international community (including decision makers and pharmaceutical companies) to assess relative exposure to 'down-the-drain' chemicals released by human pollution in rivers and, thus, target areas of potentially high risk. Full details about this dataset can be found at https://doi.org/10.5285/42044391-a041-4884-bed7-67f67490224f