This statistic displays the public concerns about plastic pollution in the ocean in the United Kingdom (UK) in 2018. More than half of those surveyed were very concerned with the amount of plastic pollution in the ocean. Just *** percent were not concerned at all.

This statistic shows the results of surveys from 2016, 2017,2018 and 2019 on the perceived likelihood of ocean pollution affecting the United Kingdom within the next 50 years. According to the 2019 survey, ** percent of respondents believed that the seas surrounding the United Kingdom would be full of plastic. By comparison, ** percent believed there would be floating islands of rubbish.

The dataset includes coastal litter data acquired through voluntary environmental NGO initiatives, used to investigate the coastal pollution in Cyprus from 2014 to 2018— a period characterized by inactive national monitoring efforts, infrequent beach cleanups, and low public awareness of marine litter issues. This dataset provides the earliest documentation of coastal litter densities in Cyprus, while also underscoring the harmful and variable nature of certain types of debris. Although pollution rates were persistent over this timeframe, mainly driven by recreational activities, deliberate dumping, and sea-based transport, litter quantities declined in 2021, coinciding with behavioural changes induced by the COVID-19 pandemic.

Pacific data are limited, but existing data show high proportions of plastic in the waste stream (Table 29.1), as marine litter, and as microplastics present throughout Pacific marine ecosystems, including in the guts of fish and their prey (SPREP 2016, Markic et al. 2018). In a 2011 study, plastics formed 12% of the waste stream in Honiara (SPREP 2017).Call Number: [EL]Physical Description: 6 p.

Two README files are attached along with the raw data:

README.lichens_as_marine_bioindicators_metadata.xlsx details the definitions and units for the column headers in the raw data files

README.lichens_as_marine_bioindicators_analysis_procedures.docx details the code and procedures for the data analysis in the paper publication relating to these data (https://doi.org/10.3119/20)

TrashVisualization.RR code that merges and analyzes all of the data. SizesOfObjects:Table of sizes of objects we compare in the VR. WPP2017_POP_F01_1_TOT:United Nations, Department of Economic and Social Affairs, Population Division (2017). World Population Prospects: The 2017 Revision, DVD Edition.Population:Cleaned population data from UN data set above taking only 2015.1260352_SupportingFile:Jambeck JR, Geyer R, Wilcox C, Siegler TR, Perryman M, Andrady A, et al. Marine pollution. Plastic waste inputs from land into the ocean. Science. 2015 Feb 13;347(6223):768–71.DetailedSummary-Earth (+1-2):Coastal Cleanup Day Data from 2016-2018 https://www.coastalcleanupdata.org/WCD:World Cleanup Day Data for 2018https://www.letsdoitworld.org/wp-content/uploads/2019/01/WCD_2018_Waste_Report_FINAL_26.01.2019.pdfAnything with the word "Key":A key used for merging country names between data sets.

A dataset of 890 microplastics collected from the surface water of Laguna de Bay, Philippines in August and September 2018. Microplastics were collected in 3 sites of the bay: 1) Brgy. Napindan, Taguig City, Metro Manila; 2) Brgy. San Isidro, Tanay, Rizal; and 3.) Brgy. Sampiruhan, Calamba Laguna. The dataset contains the the ID of each microplastic fragment, collection month, site, sampling point, length (in micrometers), roundness score, and CIE color coordinates (L*, a*, and b*). The survey was done to assess the properties (length, roundness and color) of the microplastics in Laguna de Bay.

These data provide a snap shot of beach litter surveys submitted by Citizen Scientist ‘Monitoring Groups’ up to April, 2019. As defined by the United Nations Environment Programme (UNEP, 2009), marine litter is any persistent, manufactured or processed solid material discarded, disposed of, abandoned or lost in the marine and coastal environment. Marine litter washed onto beaches is one of the most obvious signs of marine pollution, and can have either land or sea-based origins. Land-based sources of marine litter include input from rivers, sewage and storm water outflows, tourism and recreation, illegal dumping, and waste disposal sites. Sea-based sources include commercial shipping, fisheries and aquaculture activities, recreational boating and offshore installations.

UNEP, 2009. Marine Litter: A Global Challenge. Nairobi: UNEP. 232 pp.

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Produced water is the water that occurs in the extraction of oil and natural gas as a byproduct. It contains dispersed oil, dissolved organic compounds, radioactive materials as well as production chemicals. Dispersed oil refers to the mixture of oil, emulsifier and solvents that enhance the flow of oil in oil spills. In 2019, an estimated ***** tons of dispersed oil and produced water were discharged into the sea on the United Kingdom Continental Shelf.

In order to assess pollution with large microplastics (L-MP, 500-5000 µm) in the Lower Weser and transition to the German North Sea, surface water samples were collected with the RV Otzum (ICBM, Institute for Chemistry and Biology of the Marine Environment), as well as with the RV Uthörn (AWI, Alfred-Wegener-Institute) in April 2018. Sampling was performed using a microplastic net (mesh size: 300 µm), followed by filtration in the laboratory over a 500 µm stainless steel sieve. Putative MP items in the size range 500-5000 µm were analysed by means of Attenuated Total Reflection - FTIR in order to determine the underlying synthetic polymer. Dominant polymer type in the L-MP sample fraction was polyethylene. Concentrations ranged between 1 × 10⁻² m⁻³ and 9.8 × 10⁻¹ m⁻³. The highest MP concentration was measured upstream the Weser Weir.

The 2018 Environmental Performance Index (EPI) ranks 180 countries on 24 performance indicators in the following 10 issue categories: air quality, water and sanitation, heavy metals, biodiversity and habitat, forests, fisheries, climate and energy, air pollution, water resources, and agriculture. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2018 EPI, component scores, and time-series source data. The 2018 EPI was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum in January 2018. It is the result of collaboration of the Yale Center for Environmental Law and Policy (YCELP), Yale University, Columbia University Center for International Earth Science Information Network (CIESIN), and the World Economic Forum (WEF). The Interactive Website for the 2018 EPI is at https://epi.envirocenter.yale.edu/. To provide quantitative metrics for evaluating a country's environmental performance in different policy categories relative to clearly defined targets.

Colombia Water Pollution: Tax Revenue: USD: Pollution data was reported at 10.460 USD mn in 2020. This records an increase from the previous number of 7.408 USD mn for 2019. Colombia Water Pollution: Tax Revenue: USD: Pollution data is updated yearly, averaging 10.460 USD mn from Dec 2018 (Median) to 2020, with 3 observations. The data reached an all-time high of 224.453 USD mn in 2018 and a record low of 7.408 USD mn in 2019. Colombia Water Pollution: Tax Revenue: USD: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Colombia – Table CO.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Environmental Protection Domains: OECD Member: Annual.

France Water Pollution: Tax Revenue: % of GDP: Pollution data was reported at 0.068 % in 2022. This records a decrease from the previous number of 0.074 % for 2021. France Water Pollution: Tax Revenue: % of GDP: Pollution data is updated yearly, averaging 0.006 % from Dec 2014 (Median) to 2022, with 9 observations. The data reached an all-time high of 0.075 % in 2020 and a record low of 0.006 % in 2018. France Water Pollution: Tax Revenue: % of GDP: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s France – Table FR.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Environmental Protection Domains: OECD Member: Annual.

Colombia Water Pollution: Tax Revenue: % of GDP: Pollution data was reported at 0.004 % in 2020. This records an increase from the previous number of 0.002 % for 2019. Colombia Water Pollution: Tax Revenue: % of GDP: Pollution data is updated yearly, averaging 0.004 % from Dec 2018 (Median) to 2020, with 3 observations. The data reached an all-time high of 0.067 % in 2018 and a record low of 0.002 % in 2019. Colombia Water Pollution: Tax Revenue: % of GDP: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Colombia – Table CO.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Environmental Protection Domains: OECD Member: Annual.

In this data set we examined whether eDNA samples can detect similar numbers of species and community compositions as genetic continuous plankton recorder (CPR) samples. On the V4 voyage 2018 from Hobart to Macquarie island, small and large volume eDNA samples as well as genetic CPR samples were collected. All samples were sequenced with a metazoan specific cytochrome c oxidase I marker (folder "2018_08_28 eDNA V4 COI" contains all genetic CPR and small volume eDNA samples, folder "2019_05_08_eDNA_V4_CBR_Repeats_COI" contains some repeated small volume eDNA samples and all large volume eDNA samples (also called CBR samples)). Additionally, all eDNA samples were sequenced using an 18S rRNA marker (folder "2018_09_19 eDNA V4 18s Ramaciotti") to assess overall biodiversity. Each folder contains the raw sequencing data (fastq format) as well as data indexes and readme files. Please contact us if you are planning on using this data (leonie.suter@aad.gov.au).

More information about these datasets are contained in the readme files in the dataset.

E-PRTR data covering reporting for 2007 to 2018 by EU Member States, Iceland, Liechtenstein, Norway, Serbia and Switzerland.

This dataset presents microplastics in water samples collected from the underway system and CTD alongside the August 2019 zooplankton samples presented in https://doi.pangaea.de/10.1594/PANGAEA.950296. These samples were initially digested using a homogenising solution and then filtered in preparation for Fourier Transform Infrared spectroscopy (FTIR) analysis in combination with an automated polymer identification approach (SIMPLE software) to identify polymer types, shape and size. Microplastics were also visualised using a microscope to further determine shape and size, particularly of fibres. Data collected on the microplastics found includes; polymer type, shape, size, species ingestion and location.

This dataset is part of the 2018 Belgian submission for the Marine Strategy Framework Directive (MSFD) linked to descriptor 8, criterion 4. This dataset contains measurements on the 7-Ethoxyresorufin-O-deethylase (EROD) activity in Limanda limanda, Imposex (organotin in Mytilus edulis), fish diseases and counts of oiled common guillemots in the Belgian part of the North Sea.

In 2018, around *** thousand seaside villages in Indonesia experience water pollution. Indonesia has one of the largest sea areas and coastlines in the world.

This visualization product displays the total abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys.

EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale.

Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Some categories & some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some cases, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of items (normalized by 100 m) = Number of litter per items x (100 / survey length) Then, this normalized number of items is summed to obtain the total normalized number of litter for each survey. Finally, the median abundance for each beach and year is calculated from these normalized abundances per survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases.

Percentiles 50, 75, 95 & 99 have been calculated taking into account MSFD data for all years.

More information is available in the attached documents.

Warning: the absence of data on the map doesn't necessarily mean that it doesn't exist, but that no information has been entered in the Marine Litter Database for this area.