A dataset of trace metal concentrations (As, Cu, Cr, Mn, Ni, Pb and Zn) in indoor dust from homes from 11 countries, along with a suite of potentially contributory residential characteristics. A household vacuum dust sample, collected by the study participant using their regular vacuum cleaner, was submitted to the laboratory for analysis by X-Ray fluorescence spectrometry (XRF) on the <250um sieved fraction, along with the completion of an online questionnaire survey. Dust sample collection took place between 2018 – 2021. The Home Biome project is affiliated to the DustSafe community science programme (see mapmyenvironment.com). Sample location data are provided at town/city and Country level. Health risk from exposure to potentially contaminant-laden dust has been widely reported. Given the amount of time people spend indoors, residential environments are an important but understudied environment with respect to human exposure to contaminants. Indeed, the nature of the hazard that house dust presents remains poorly characterized. These data will be of interest to those interested in human exposure to potentially toxic elements and environmental health, as well as to the participants, who received a bespoke report on their sample data and information on key sources and ways to reduce exposure to trace elements in indoor dust.

Analysed trace element data and radiocarbon data from five existing marine sediment cores from the NE Pacific margin (45-50N) that intersects the major water masses of the N Pacific, from a depth transect (700-3300m)

This dataset was acquired as part of a NERC-funded Doctoral Training Partnership (DTP) PhD Studentship at the University of Leicester and British Geological Survey between 2014-2018 [grant no. NE/L002493/1] (see also Emmings, 2018 unpublished PhD thesis). This research was conducted within the Central England NERC Training Alliance (CENTA) consortium. This dataset accompanies a manuscript titled "Late Palaeozoic Phytoplankton Blackout: A 100 Myr Record of Enhanced Primary Productivity". Co-authors and co-workers were: Joseph F. Emmings (University of Leicester, British Geological Survey); Sarah J. Davies (University of Leicester); Simon W. Poulton (University of Leeds); Michael H. Stephenson (British Geological Survey); Gawen R. T. Jenkin (University of Leicester); Christopher H. Vane (British Geological Survey); Melanie J. Leng (British Geological Survey, University of Nottingham) and Vicky Moss-Hayes (British Geological Survey). Nick Riley (Carboniferous Ltd) is thanked for sharing biostratigraphic expertise and assistance. Nick Marsh and Tom Knott are thanked for providing assistance during geochemical analyses. This dataset contains the following data (in Microsoft Excel format). 1) Fe species abundance data measured at the University of Leeds using the sequential extraction method of Poulton and Canfield (2005) and pyrite S extraction method of Canfield et al., (1986); 2) Total Fe, Si, Mn and Al major element concentrations (measured using x-ray fluorescence at the University of Leicester; XRF); 3) Total organic carbon (TOC) and inorganic C (MINC) data measured via Rock-Eval pyrolysis at the British Geological Survey; 4) Cu, Mo and U trace element concentration data (measured via XRF at the University of Leicester) and enrichment factors relative to Post-Archaean Average Shale (PAAS; Taylor and McLennan, 1985). Analyses were coupled on 99 sample powders from three positions in the Craven Basin and spanning ammonoid biozones P2c-d to E1c1. See also http://dx.doi.org/10.5285/9ceadcad-a93c-4bab-8ca1-07b0de2c5ed0 for additional sedimentological and geochemical data from Hind Clough, MHD4 and Cominco S9. These data were also interpreted together with 20 drill-core samples previously acquired from Hind Clough (‘HC01’ prefix). See http://dx.doi.org/10.5285/c39a32b2-1a30-4426-8389-2fae21ec60ad for further information regarding this drill-core dataset. References: Emmings, J. 2018. Controls on UK Lower Namurian Shale Gas Prospectivity: Understanding the Spatial and Temporal Distribution of Organic Matter in Siliciclastic Mudstones. Unpublished PhD Thesis. University of Leicester. Poulton, S. W. & Canfield, D. E. 2005. Development of a sequential extraction procedure for iron: implications for iron partitioning in continentally derived particulates. Chemical Geology 214, 209-221, doi:http://dx.doi.org/10.1016/j.chemgeo.2004.09.003. Canfield D., Raiswell R., Westrich J., Reaves CM, Berner RA. 1986. The use of chromium reduction in the analysis of reduced inorganic sulfur in sediments and shales. Chemical Geology, 54(1): 149-155. Taylor S, McLennan S. 1985. The Continental Crust: Its Composition and Evolution. Blackwell Scientific: London.

The data set presents major and trace element geochemical data obtained from ICP-MS measurements on micro-drilled subsamples of ferromanganese (Fe-Mn) crusts from Tropic Seamount, north-east Atlantic Ocean. The data represent detailed stratigraphic analysis of Fe-Mn crust samples 078_019 and 085_004. These samples were collected at 3100 and 1100 meters beneath sea level, respectively, during the JC142 expedition of the RRS James Cook for the MarineE-Tech project in 2016.

Major and trace element data of lava and tephra samples from the 2021 Tajogaite eruption. Major and select trace element collected by XRF, trace elements collected by ICPMS, both at the University of Granada. Data collected as part of NERC Urgency Grant led by K Chamberlain (Liverpool), in collaboration with M Pankhurst (INVOLCAN), J Scarrow (Granada), D Morgan (Leeds), J Hickey (Exeter), D Neave (Manchester), for understanding how eruptions begin, evolve and end. Samples analysed span the entire September - December 2021 eruptive sequence of Tajogaite, and data were collected between December 2021 and August 2022.

A dataset of airborne particulate matter (PM10 and PM2.5) readings (every 3 minutes) collected by participating households in Northeast England in their kitchens and living rooms over the course of one week, along with data from a linked questionnaire survey and metal(oid)s data from a corresponding household vacuum dust sample collected by the study participant. Matched air monitoring and dust sample collection took place between June 2020 and August 2021. We increasingly spend time indoors and household air pollution results in an estimated 4.25 million premature deaths globally each year. The majority of these deaths are associated with fine particulate matter (PM), or dust. Exposure to PM can initiate or enhance disease in humans, yet the nature of the hazard that house dust presents remains poorly characterized. The data was collected to provide concentrations of PM2.5 and PM10 in a range of Northeast England households and concentrations of metal(oid)s in their house dust. It will be of interest to those interested in human exposure to potentially toxic elements and environmental health. We used factory calibrated Aeroqual 500 units for PM monitoring. Metal(oid)s data were generated using a SPECTROSCOUT X-Ray fluorescence spectrometer on the <250um sieved fraction of household vacuum dust. This dataset was part of NERC Grant NE/T004401/1.

The <250um fraction of 28 household vacuum dust samples were extracted using high throughput isolation of microbial genomic DNA (21 samples from a national campaign within the UK and 7 samples from Greece, providing samples from two contrasting bioclimatic zones). Both positive and negative reagent controls were included to ensure sterility throughout the processing and sequencing steps, and a randomly selected sample was run in triplicate (DSUK179). These data (raw fastq files: Target_gene 16S and Target_subfragment V4) are available from the European Nucleotide Archive via the study accession PRJEB46920 with individual sample accession numbers ERX6130460 to ERX6130493; https://www.ebi.ac.uk/ena/browser/view/PRJEB46920). A wide range of anthropogenic factors are likely to affect the indoor microbiome and to capture some of this heterogeneity participants were asked to complete a questionnaire. In addition, trace element data were generated using an X-Ray fluorescence spectrometry on the <250um sieved fraction of the household vacuum dust. Sample location data are provided at town/city, Country level. Indoor dust serves as a reservoir for environmental exposure to microbial communities, many of which are benign, some are beneficial, whilst some exhibit pathogenicity. Whilst non-occupational exposure to a range of trace elements and organic contaminants in house dust are a known risk factor for a range of diseases and poor health outcomes, we know far less about the microbial communities associated with our indoor home environments, and their interaction/impacts on human health. Our knowledge of indoor residential bacterial biodiversity, biogeography and their associated drivers are still poorly understood. The data were collected to improve our understanding of the home microbiome.

Major and trace element data for olivine- and plagioclase-hosted silicate melt inclusions, their host minerals, and associated matrix glasses, from Midfell, Snaefellsjokull and Oraefajokull, Iceland. Melt inclusion compositions are provided as measured, and corrected for post-entrapment crystallization. Reflected light images of the melt inclusions.

Water samples have predominantly been collected by the G-BASE (Geochemical Baseline Survey of the Environment) project at an average sampling density of one sample per 1.5 km square. Samples have been collected from approximately 85% of Great Britain but it is only from Wales and Humber-Trent southwards that a wide range of analytes have been determined. Currently G-BASE stream water samples collected from high order streams are determined by ICP-AES for 27 elements - Sr, Cd, Ba, Si, Mn, Fe, P, S (as SO42-), B, Mg, V, Na, Mo, Al, Be, Ca, Zn, Cu, Pb, Li, Zr, Co, Ni, Y, La, K and Cr; and by quadrupole ICP-MS for 24 trace elements - Li, Be, Al, V, Cr, Co, Ni, Cu, As, Rb, Y, Zr, Mo, Ag, Cd, Sn, Sb, Ba, La, Ce, Tl, Pb, Th and U. Automated colorimetric methods are used to determine Cl and NO3- and ion selective electrode is used to determine F. Waters are also analysed for non-purgeable organic carbon (NPOC) to determine dissolved organic carbon content. All samples have routinely been analysed for pH, conductivity and bicarbonate. Much of the UK coverage also includes uranium and fluoride analyses.

The database contains a range of geochemical data for metamorphosed limestones from the Dalradian of Scotland and Northern Ireland. The data include a) whole-rock geochemical analyses by XRF (X-Ray Fluorescence) for major oxides and a range of trace elements for several hundred samples, b) a number of whole-carbonate O (oxygen) and C (carbon) stable isotope and Sr (strontium) data, c) electron microprobe mineral data on carbonates and calc-silicate minerals and d) ion-probe O stable isotope and mineral trace element data for calcites in a small number of samples. The samples from which the data have been derived were collected from a wide range of outcrops within the Scottish and Irish Dalradian, mainly concentrated in the North East Grampian Highlands of Scotland. The data have been collected mainly to support the mapping and scientific work being undertaken in the Grampian Highlands by BGS since the early 1980s. The database includes some data from the literature. All samples are located by British National Grid coordinates to the nearest 10m or better. The isotope data were acquired as part of a PhD study by C W Thomas in the late 1990s. The database is not currently being added to, but is still being used in various studies. The combined data provide wide-ranging insights into marine chemistry contemporary with deposition of the limestones and the way in which this chemistry changed with time during the Neoproterozoic, and they elucidate subsequent effects of diagenesis and metamorphism and the outcrop and grain-scale. The data set is largely complete with regard to geochemical data, but still requires some editing to bring all fields up to date, particularly with regard to lithostratigraphical assignation. The data are currently held in MS Access tables and can conveniently be displayed via GIS or abstracted in tabular form and used in spreadsheets, statistical analysis and graphing software.