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Northumbria University

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  • 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; 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.

  • Stratigraphic and ecological data from tidal marsh sites in south-central Chile. Includes stratigraphy, diatom assemblages and radiocarbon dates from fossil cores and diatom assemblages from modern tidal marsh samples. Data were collected to provide evidence for multiple great earthquakes in south-central Chile, and enable the reconstruction of vertical land-level changes associated with these earthquakes. Data are from tidal marsh sites within the 1960 earthquake rupture area along the Chilean subduction zone (37.5 - 46 degrees South).

  • Weather station data at five on-glacier stations in Peru and the ecohydrological model Tethys-Chloris. Data includes: - Hourly weather station data from Shallap Glacier, Artesonraju Glacier, Cuchillacocha Glacier, Quisoquipina Glacier and Quelccaya Ice Cap. Given as .csv files and as model input files. - The model code used to input the data and set the correct parameters for these sites. - The model code for the point version of Tethys-Chloris, an ecohydrological model which is used in this case to calculate glacier melt and mass balance. Full details about this dataset can be found at

  • Code to compare the mass and energy balance of five Peruvian glaciers, based on outputs from the energy balance model Tethys-Chloris. Also includes code to compare the results of climate sensitivity experiments (where the air temperature and precipitation were varied). The main outputs of the analysis at each of the sites are also stored. Full details about this dataset can be found at

  • Averaged outputs from the WRF (Weather Research and Forecasting) model for the Rio Santa and Vilcanota, Urubamba and Vilcabamba catchments in Peru. Averaging was applied over the entire model period from 1980 to 2018. Data includes: - Averaged precipitation and air temperature records and the related standard deviation at a 4km resolution (annually and for each season) for each catchment. Monthly averaged and monthly totals of air temperature and precipitation (averaged over each catchment). - WRF model input elevation for each catchment. - WRF total precipitation and maximum/minimum air temperature at the location of five on-glacier weather stations (Artesonraju Glacier, Shallap Glacier, Cuchillacocha Glacier, Quisoquipina Glacier and Quelccaya Ice Cap) at a daily resolution from 1980 to 2018. Full details about this dataset can be found at

  • The dataset consists of the transcripts of expert inputs considering how the conceptual thinking for both ‘smart’ and ‘natural or biophilic’ cities could combine to inform future urban discourses and critically reviewed a set of emerging characteristics that described the interface between these alternative discourses. These inputs include informed practice-based perspectives on themes identified in the literature and comparative assessments, testing the integrating principles identified in the research against business as usual silo approaches, which helped refine the research outcomes. Expert inputs were used to inform the identification of new ways of integrating urban futures discourses, in particular shaping the Smart City – Natural City interface, using Birmingham, UK as a case study. The files include the underlying data provided by a cohort of multi-disciplinary [anonymised] experts who contributed to the research; • the record of the group or table outputs from the Innovation Workshop of 12th September 2017 • copies of photographs of the collective ‘stickies’ contributions at the workshop • the original transcript record of the semi-structured interview conversations • records of Group telephone or meeting conversations • ‘work in progress’ collations of comments received; generated to share with contributors and with co-authors Full details about this dataset can be found at

  • The dataset includes data on vegetation composition, flower counts, berry availability over winter, pollinator visitation rates, invertebrate, hedge structure and hedgerow regrowth from a set of long running hedgerow experiments. There were three experiments in total. Experiment 1 was based in Monks Wood, Cambridgeshire, and was used to investigate the long-term effects of timing and frequency of cutting on resource provision for wildlife. Experiment 2 was based at 5 sites across Oxfordshire, Buckinghamshire and Devon and was used to investigate the effect of timing, intensity and frequency of hedgerow cutting. Experiment 3 was based at 5 sites across Cambridgeshire, Northamptonshire, Buckinghamshire and Oxfordshire and was used to investigate the effects of different rejuvenation techniques on hedgerows. All three experiments were randomised plot experiments (full details of plots and their treatments can be found in the supporting documentation. The majority of the data was collected between 2010 and 2016 but for one experiment there is data from 2005. The long running hedgerow experiments had two linked aims focused on management to maintain and restore the hedgerow resource under the agri-environment schemes: • to examine the effects of simple cutting management regimes promoted by Entry Level Stewardship (ELS) and Higher Level Stewardship (HLS) on the quality and quantity of wildlife habitat, and food resources in hedgerows; and • to identify, develop and test low-cost, practical options for hedgerow restoration and rejuvenation applicable at the large-scale under both ELS and HLS. This research was funded by Defra (project number BD2114: Effects of hedgerow management and restoration on biodiversity) and managed by the UK Centre for Ecology & Hydrology (UKCEH). Full details about this dataset can be found at