An estimated *** million metric tons of mismanaged plastic waste had accumulated in the world's oceans and rivers as of 2020. The stock of plastic waste accumulated in these aquatic environments is projected to double by 2040, to *** million metric tons.

The amount of plastic waste generated worldwide is projected to triple by 2060, to surpass *********** metric tons. This dramatic growth is set to be fueled by rising populations and economic growth. With so much plastic waste generated, proper waste management will be urgently needed to reduce environmental impact. However, projections show that landfilling will continue to be the main disposal method worldwide by 2060, with recycling accounting for less than ** percent. Much of the plastic waste generated over the coming **** decades will be caused by packaging.

These data are made of two files. One file provides the observed data we collected and cleaned from the World Bank database. The second file provides the simulation results from the STIRPAT model we designed based on the observed data abovementioned. Our results can be summarised as follows:

Since 2015, the detrimental effects of plastic pollution have attracted media, public, and governmental attention. Considering economic growth is inevitable and a key driver of plastic contamination, it is worthwhile to analyze the environmental Kuznets curve (EKC) relationship between economic development and plastic pollution. To this end, we contribute by being the first to (i) use the Stochastic Impacts by Regression on Population, Affluence, and technology model (STIRPAT model) to investigate this EKC relationship; (ii) provide a comprehensive analysis of how demographic factors affect plastic pollution; and (iii) use panel model techniques to examine the drivers of plastic pollution. Our empirical results support an inverted U-shaped relationship between plastic pollution and income. They show that at current trends, global plastic pollution (that is, annual discard of inadequately managed plastic waste) is expected to grow from 52 million tons per year in 2020 to 257 million tons per year in 2050.

Short description The annual rate of plastic debris emissions per person  Summary This indicator measures the release of plastic debris emissions, reported in kilograms per capita per year. It is modelled with the ‘Spatio-temporal quantification of plastic pollution origins and transport’ model (SPOT). The model begins at the point where waste is generated and discarded by the user and ends when these materials are either recycled, recovered, stored in disposal facilities or emitted into environment. The model focusses on macroplastic, referring to plastic particles larger than 5 mm, and includes both rigid and flexible formats.  Plastic emissions are defined as material that has moved from the managed or mismanaged systems (in which waste is subject to a form of control, however basic; contained state) to the unmanaged system (the environment; uncontained state) with no control. Plastic debris emissions are further classified as physical particles >5 mm that enter the environment. Sources for emissions were quantified with five land-based sources: (1) uncollected waste; (2) littering; (3) collection system; (4) uncontrolled disposal; and (5) rejects from sorting and reprocessing.  The study uses the UN-Habitat definition for MSW which includes discarded products and materials from households, commerce, and institutions, excluding waste from construction, demolition, industry, and sewage treatment. Additionally, textiles, electrical and electronic equipment waste, and waste material arising at sea were excluded.  The layer displays the mean value, and the modelled uncertainty, expressed as percentiles, can be seen in the pop up of each country.   Description Title: Plastic debris emissions per capita annually  Entity: University of Leeds, United Kingdom Source: University of Leeds: https://www.leeds.ac.uk/ Publication: Cottom, J.W., Cook, E. & Velis, C.A. A local-to-global emissions inventory of macroplastic pollution. Nature 633, 101–108 (2024). https://doi.org/10.1038/s41586-024-07758-6 Supplementary material: https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-024-07758-6/MediaObjects/41586_2024_7758_MOESM1_ESM.pdf Data: https://datadryad.org/stash/dataset/doi:10.5061/dryad.8cz8w9gxb Time Period: 2020 Methodology: The SPOT model is plastic pollution emissions inventory that operates at the municipal level to reflect the level at which waste is managed and where waste data is typically collected. The model uses existing published data on solid waste management to train a machine learning model, which in turn is used to predict solid waste management variables for all municipalities globally. These predictions are used to perform material flow analysis for each municipality, including quantifying plastic emissions. Results are aggregated from the municipal level to the global scale, with the national level results shown here. Frequency Update: Unknown Last Update: 08-11-2024 Geo-Coverage: Global Licensing: Public

Short description Total annual plastic emissions openly burnt  Summary This indicator quantifies total annual openly burned plastic emissions, measured in tonnes per year. It is modelled with the ‘Spatio-temporal quantification of plastic pollution origins and transport’ model (SPOT). The model begins at the point where waste is generated and discarded by the user and ends when these materials are either recycled, recovered, stored in disposal facilities or emitted into environment. The model focusses on macroplastic, referring to plastic particles larger than 5 mm, and includes both rigid and flexible formats.  Plastic emissions are defined as material that has moved from the managed or mismanaged systems (in which waste is subject to a form of control, however basic; contained state) to the unmanaged system (the environment; uncontained state) with no control. Openly burnt emissions are classified as mass combusted in open uncontrolled fires. For clarification, open burning emissions relate to the mass of material that is subjected to the practice, rather than the gaseous, liquid or solid matter emitted by the process. Sources for emissions were quantified with five land-based sources: (1) uncollected waste; (2) littering; (3) collection system; (4) uncontrolled disposal; and (5) rejects from sorting and reprocessing.  The study uses the UN-Habitat definition for MSW which includes discarded products and materials from households, commerce, and institutions, excluding waste from construction, demolition, industry, and sewage treatment. Additionally, textiles, electrical and electronic equipment waste, and waste material arising at sea were excluded.  The layer displays the mean value, and the modelled uncertainty, expressed as percentiles, can be seen in the pop up of each country.   Description Title: Plastic emissions openly burnt annually  Entity: University of Leeds, United Kingdom Source: University of Leeds: https://www.leeds.ac.uk/ Publication: Cottom, J.W., Cook, E. & Velis, C.A. A local-to-global emissions inventory of macroplastic pollution. Nature 633, 101–108 (2024). https://doi.org/10.1038/s41586-024-07758-6 Supplementary material: https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-024-07758-6/MediaObjects/41586_2024_7758_MOESM1_ESM.pdf Data: https://datadryad.org/stash/dataset/doi:10.5061/dryad.8cz8w9gxb Time Period: 2020 Methodology: The SPOT model is plastic pollution emissions inventory that operates at the municipal level to reflect the level at which waste is managed and where waste data is typically collected. The model uses existing published data on solid waste management to train a machine learning model, which in turn is used to predict solid waste management variables for all municipalities globally. These predictions are used to perform material flow analysis for each municipality, including quantifying plastic emissions. Results are aggregated from the municipal level to the global scale, with the national level results shown here. Frequency Update: Unknown Last Update: 08-11-2024 Geo-Coverage: Global Licensing: Public

The majority of adults in the United States agree that the country's recycling system for plastic needs improvement, with more than ** percent of respondents agreeing with this statement in 2022. It is estimated that just **** percent of U.S. plastic waste was recycled in 2021. The share of respondents that that agree that the U.S needs to reduce its reliance on plastic has increased from ** percent in 2020 to ** percent in 2022.

A global agreement on plastic should have quantitative reduction targets for the emissions of plastic pollution and regular measurements to track success. Here, we present a framework for measuring plastic emissions, akin to greenhouse gas emissions, and demonstrate its utility by calculating a baseline measurement for the City of Toronto in Ontario, Canada. We identify relevant sources of plastic pollution in the city, calculate emissions for each source by multiplying activity data by emission factors for each source, and sum the emissions to obtain the total annual emissions of plastic pollution generated. Using Monte Carlo simulations, we estimate that 3,531 to 3,852 tonnes (T) of plastic pollution were emitted from Toronto in 2020. Littering is the largest source overall (3,099 T), and artificial turf is the largest source of microplastic (237 T). Quantifying source emissions can inform the most effective mitigation strategies to achieve reduction targets. We recommend this framework be scaled up and replicated in cities, states, provinces, and countries around the world to inform global reduction targets and measure progress toward reducing plastic pollution.

Le but du Projet de recherche sur les microplastiques du Canada atlantique (2017-2020) est de déterminer la quantité de microplastiques dans trois collectivités côtières du Canada atlantique. Les données serviront à mieux éclairer la conversation et à trouver des solutions concernant la pollution par les plastiques dans la région. Le projet est financé par Environnement et Changement climatique Canada et est en partenariat avec le projet Clean Annapolis River Project (CARP), l'ACAP Humber Arm et le Dr Max Liboiron du Civic Laboratory for Environmental Action Research (CLEAR) de l'Université Memorial de Terre-Neuve (MUN). Le Dr Max Liboiron est notre conseiller académique en chef dans le cadre du projet de 3 ans. Il aide à l'élaboration du projet, aux méthodes et au protocole ainsi qu'à la conception de l'échantillonnage. Le projet comprenait l'échantillonnage des eaux de surface et des sédiments de plage aux trois emplacements de l'étude. L'équipement de chalutage en eaux de surface a été construit à l'aide de la conception de l'instrument à faible débris aquatiques (LADI) de CLEAR. Des rapports de données sont disponibles pour les résultats des eaux de surface et des sédiments riverains de 2018. Les résultats restants de 2018 sur les sédiments et les données sur les points chaud de 2019 seront bientôt disponibles.

An estimated *********** metric tons of mismanaged plastic waste was generated worldwide during the COVID-19 pandemic, of which ****** metric tons was thought to have leaked into the ocean. Asia accounted for almost half of this mismanaged waste, while Europe was responsible for a quarter. The plastic waste comes from sources such as personal protective equipment (PPE) and COVID-19 test kits. Plastic waste pollution in the ocean was already a serious global issue prior to the pandemic, but it has only been worsened by the increased use of single-use plastic products.

Surface debris were collected with a metal trowel over a square of 1 m² within a historical accumulation zone of plastic debris. They were collected in one shot close to the Seine river mouth (North France; 49.46452, 0.43911), the 28th of february 2020. Plastic debris higher than 6 mm were sorted and classified using the updated international MSFD and OSPAR classifications, joined as the J-list. They were then counted, weighed and data were reported in a csv file. Those data help identifying historical plastic pollution and its sources for future mitigation policies. Figure showing the sampling localization. A, map of the Seine estuary with the sampling site (yellow star) and plastic producers (red stars). B, the sampled square meter. C, plastic debris collected and sorted in glass jars. D, plastic preproduction pellets. E, unidentified fragments 2.5 cm. Plastic debris classified by numb and by count according to the J-list (https://publications.jrc.ec.europa.eu/repository/handle/JRC121708).

This fileset underpins the data analysis described in Galaiduk, R., Lebreton, L., Techera, E. and Reisser, J., 2020. Transnational Plastics: An Australian Case for Global Action. Frontiers in Environmental Science, 8, p.115. doi: 10.3389/fenvs.2020.00115For comments/enquiries, please contact r.galaiduk@aims.gov.au

This dataset contains images of various plastic objects commonly found in everyday life. Each image is annotated with bounding boxes around the plastic items, allowing for object detection tasks in computer vision applications. With a diverse range of items such as milk packets, ketchup pouches, pens, plastic bottles, polythene bags, shampoo bottles and pouches, chips packets, cleaning spray bottles, handwash bottles, and more, this dataset offers rich training material for developing object detection models.

This dataset is collected by DataCluster Labs, India. To download the full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

The dataset is an extremely challenging set of over 4000+ original Plastic object images captured and crowdsourced from over 1000+ urban and rural areas, where each image is ** manually reviewed and verified** by computer vision professionals at Datacluster Labs.

Optimized for Generative AI, Visual Question Answering, Image Classification, and LMM development, this dataset provides a strong basis for achieving robust model performance.

Dataset Features

• Dataset size: 4000+
• Captured by: Over 1000+ crowdsource contributors
• Resolution: 99.9% images HD and above (1920x1080 and above)
• Location: Captured across 500+ cities
• Diversity: Various lighting conditions like day, night, varied distances, different material view points etc.
• Device used: Captured using mobile phones in 2020-2022
• Usage: Plastic object detection, Recycling and waste management, Garbage segregation, Trash segregation, etc.

Available Annotation formats

COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

Forecast: Plastics Waste Imports Intra-EU27 (2020) Italy 2024 - 2028 Discover more data with ReportLinker!

Description of the dataset:

This dataset was created in 2021 and 2023. It was first made open in 2023 and later updated in 2024.

Lapland_Sampling.xlsx contains all sampling dates and coordinates alongside with sample names, volumes, area descriptions and codes used to describe the samples in the article.

Lapland_RawData.xlsx contains all the raw data for all the samples. This includes polymer types, particle sizes and an estimation of particle mass. Furthermore, the file contains a table with all the polymer types and their counts from all samples.

Data creation and processing:

The raw data was created by measuring filtered water samples with FPA-FTIR . The spectral analysis was done with siMPle (Primpke et al. 2020, Applied Spectroscopy, 74, 1127-1138, https://doi.org/10.1177/0003702820917760).

Switzerland Exports of waste, parings, scrap of plastics to Ukraine was US$358 during 2020, according to the United Nations COMTRADE database on international trade. Switzerland Exports of waste, parings, scrap of plastics to Ukraine - data, historical chart and statistics - was last updated on July of 2025.

European Plastics Waste Imports Extra-EU27 (2020) by Country, 2023 Discover more data with ReportLinker!

Agricultural plastic mulch films are a major source of plastic pollution of croplands. In China, which uses about 68% of the plastic mulch film produced globally (ca. 1.4 million tonnes y-1), soils have been heavily contaminated with mulch fragments. Here, we collected a national dataset of macroplastic residues (> 5 mm) in soil, including 3145 sampling sites, and provincial plastic film usage from 1992 to 2019 in China, and we established a linear model between the residue amount and historical cumulative usage within each province. We quantified the amount of plastic mulch residues in Chinese croplands on a national scale during the past 30 years and predicted plastic pollution until 2050. Our results reveal the total national amount of plastic mulch residue in 2020 to be 2.07 million tonnes with a 95% CI of [1.67, 2.58]. This accumulated amount of plastic in Chinese soils roughly equals the annual amount of plastic films used globally (2.08 million tonnes in 2018), which is about ..., , # Plastic film usage and mulching area from 1992 to 2022 Dataset DOI: 10.5061/dryad.6hdr7srcd

Description of the data and file structure

The dataset is mainly used to understand the temporal and spatial distribution of plastic film use and residue in China.

Each row of the Excel represents the plastic film usage and mulching area for each province in China from 1992 to 2022, while each column indicates the data for a specific year regarding plastic film usage or mulching area for all provinces.

Files and variables

File: Data_S1.zip

Description:Â Data S1 includes data on the usage (thousand tonnes) and mulching area (thousand hectares) of plastic mulch film for 33 provincial-level administrative regions in China from 1992 to 2022, excluding Hong Kong, Macau, and Taiwan.

Access information

Data was derived from the following sources:

• https://www.stats.gov.cn/,

In February 2025, exports of plastic waste from the United Kingdom amounted to nearly ****** metric tons. The previous year, in March, figures reached the highest value in the period in consideration, having surpassed *******metric tons. Annual plastic waste exports from the United Kingdom have been on a mostly downward trend since they peaked in 2011.

United States Imports from Russia of Waste, Parings, Scrap of Plastics was US$12.12 Thousand during 2020, according to the United Nations COMTRADE database on international trade. United States Imports from Russia of Waste, Parings, Scrap of Plastics - data, historical chart and statistics - was last updated on July of 2025.