This dataset contains information relating to the survival and persistence of Salmonella spp. on plastic and glass, under conditions simulant of environmental UV exposure. The data encompass bacterial strain identity, material type, timepoints (days), temperature (°C), bacterial concentration (CFU/ml), survival percentages, and regression parameters. Data were sampled over a 21-day period using culture-based approaches; and the ability of isolates to cause disease following their recovery was determined through the use of a Galleria mellonella model. This work was supported by the UKRI Natural Environment Research Council (NERC) as part of the GCRF SPACES project [grant number NE/V005847/1] and the Plastic Vectors project, “Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the ‘Plastisphere’” [grant number NE/S005196/1]. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/57ef148f-8cfb-4ba6-b673-114b22b21613

This dataset contains information relating to the survival and persistence of Salmonella spp. on plastic and glass, under conditions simulant of a peri-urban waste pile. The data encompass bacterial strain identity, material type, timepoints (days), temperature (°C), bacterial concentration (CFU/ml), survival percentages, and regression parameters. Data were sampled over a 28-day period using culture-based approaches; and the ability of isolates to cause disease following their recovery was determined through the use of a Galleria mellonella model. This work was supported by the UKRI Natural Environment Research Council (NERC) as part of the GCRF SPACES project [grant number NE/V005847/1] and the Plastic Vectors project, “Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the ‘Plastisphere’” [grant number NE/S005196/1]. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/9c3a1ae5-65d7-45c6-b6f3-1a955b17abff

The dataset comprises output data from a Life Cycle Assessment (LCA) model focused on compostable nappies. It includes detailed information on various life cycle stages (manufacture, transport, use, collection, and disposal) and the environmental impact associated with each. The data is structured as CSV files, detailing material inputs, energy consumption, and resulting environmental outputs. The dataset facilitates the analysis of different end-of-life scenarios for compostable nappies, including landfill, incineration, and composting. Full details about this dataset can be found at https://doi.org/10.5285/dcb5904b-0e5a-4065-842a-b8ee8ec8554e

The dataset contains the chemical composition of anaerobic digestates derived from source-segregated food waste & agro-waste, with and without biomass ash, after the addition commercial polymer to enhance dewaterability. A preliminary experiment was carried to determine the type of polymer and its optimum dose (WP1A1). Then, polymer was added to digestate and digestate/ash blends, let react for short-time and physically separated into their fiber and liquid fractions (WP1A2). These experiments were carried out in the laboratory during 2016, being measured via a combination of internal and external laboratories. Preliminary experiment (WP1A1) contains data on polymer type, dose and mass added as well as supernatant and solids separated. Main experiment contain data on masses (dry & total solids), supernatant volume, pH and plant macro-nutrients profile (total concentration of Ca, Mg, P, K, TKN and S). Full details about this dataset can be found at https://doi.org/10.5285/2977fc7b-f83e-4696-b06b-2f589ffa6965

This data resource contains information on anthropogenic litter from the Portoviejo River, in Ecuador, collected between years 2021 and 2022. This work is part of the Natural Environment Research Council project “Reducing the impacts of plastic waste in the Eastern Pacific Ocean” (NE/V005448/1). The purpose of collecting this dataset was to obtain consistent observational data of solid waste contamination in a South American river system using a newly developed clean-up technology called the Azure System. The dataset contains information of weight (in kilograms) of different categories of anthropogenic litter collected using the Azure System, a floating barrier designed as a litter extraction tool for rivers. The system was developed by Ichthion Limited (https://ichthion.com/), who were also responsible for data collection on site. The barrier was installed at the city of Portoviejo, where litter was collected from February 2021 until December 2022 and quantities were reported weekly for each month. Full details about this dataset can be found at https://doi.org/10.5285/e78e1cef-e30b-4313-8733-c03e1a7b7b2f

The dataset contains the chemical compositional changes occurred in anaerobic digestate, with and without biomass ash, simulating storage conditions during 128 days. Additionally, Sulphuric Acid (H2SO4) was added to these materials to test the effectivity on preventing nitrogen loss via acidification. Experiments were carried out in the laboratory during 2016, being measured via a combination of internal and external laboratories. The dataset provides data on chemical changes, namely: dry solids, pH, Kjeldahl nitrogen and total sulphur. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/e91e8c28-0176-4c5b-9b20-611eb505ab39