Data Sources
The Global Plastics Hub Data Hub brings together the most comprehensive and authoritative datasets available on plastics across the lifecycle—from production and trade to waste management and environmental leakage. All data sources are selected for their global relevance, scientific rigor, and policy applicability. Where limitations exist, they are transparently documented to support informed interpretation and evidence-based decision-making.
Trade Data
Trade data are sourced from UNCTAD’s Global Trade in Plastics: Insights from the First Life-Cycle Trade Database, the first global initiative to systematically quantify and map plastic trade flows using UN Comtrade data and Harmonized System (HS) codes. The database categorizes plastics into five groups: plastics in primary forms, plastics in intermediate forms, intermediate manufactured plastic goods, final manufactured plastic goods, and plastic waste.
The Global Plastics Hub Data Hub extracts 28 indicators from this database and presents them through interactive global maps and country dashboards, enabling users to explore trade patterns, flows, and trends across regions and over time.
Limitations:
Comparative analysis by UNEP indicates that UNCTAD trade data tend to underestimate total plastic flows when compared with plastic waste generation datasets. This is largely due to the difficulty of capturing plastics embedded within other product categories—such as packaging associated with food and beverage products—which are not always explicitly reported as plastic trade.
▶️ More details: explanatory video
Waste Management Data
Waste management data in the Data Hub are compiled from multiple complementary global datasets to provide the most complete possible picture of municipal solid waste generation, management practices, and environmental outcomes.
UNEP’s Global Waste Management Outlook (2024) aggregates municipal solid waste (MSW) data from national and subnational sources, including the World Bank, UN Statistics Division, OECD, and Eurostat. The dataset applies linear regression to estimate future waste generation under three scenarios: business as usual, waste under control, and circular economy, and uses life-cycle assessment models to evaluate socioeconomic and environmental impacts.
Limitations:
Data availability varies significantly by country and year, resulting in gaps that are addressed through statistical estimation. Differences in national reporting standards and definitions affect comparability, and the dataset focuses on municipal solid waste, excluding industrial and hazardous waste streams.
UN-Habitat’s SDG 11.6.1 monitoring data tracks the proportion of municipal solid waste that is collected and managed in controlled facilities at the city level. Data are collected using the Waste Wise Cities Tool and are aligned with harmonized UNSD/UNECE definitions. Primary data collection includes household waste sampling, landfill composition surveys, facility interviews, and environmental control scoring.
Limitations:
The dataset is limited to cities and is collected only where resources permit, resulting in uneven geographic coverage. National-level datasets are not available, which constrains comparability and scalability.
▶️ More details: explanatory video
The World Bank’s What a Waste 2.0 database (1993–2017) provides country- and city-level information on waste generation, composition (including plastic content), collection, treatment, disposal, financing, and informal sector involvement. Data are compiled from municipal records, surveys, and secondary sources.
Limitations:
The dataset relies on secondary data collected at different times and under varying definitions. In some regions, particularly in Africa, available data are outdated, which can underestimate current waste generation and management challenges.
University of Leeds research published in Nature (2024) estimates macroplastic emissions from municipal solid waste systems across 50,702 municipalities. Using machine-learning techniques and probabilistic material flow analysis through the SPOT (Spatio-temporal Quantification of Plastic Pollution Origins and Transport) model, the study estimates global plastic waste emissions at approximately 52.1 million tonnes per year, with about 43% openly burned.
Limitations:
These estimates are model-based and rely on proxies derived from a limited training dataset, with extrapolation across regions. Local variability may not be fully captured, and some emission pathways may be underrepresented due to data constraints.
▶️ More details: explanatory video
Plastics in the Environment Data
Environmental data focus on the presence and distribution of plastics in marine and coastal environments, drawing on established monitoring initiatives and scientific repositories.
Japan’s Ministry of the Environment’s Atlas of Ocean Microplastics (AOMI) is a global, open-access database compiling surface-water microplastic data submitted by researchers, institutions, and government agencies worldwide. Data are organized by geographic location and survey period and undergo a four-level quality-control process aligned with international harmonization guidelines. Expert validation, unit conversion, logical checks, and spatial interpolation are applied to generate consistent global maps of microplastic abundance.
Limitations:
As the database aggregates data from studies using different sampling methods, equipment, mesh sizes, depths, and laboratory protocols, comparability across regions and datasets remains challenging.
NOAA’s National Centers for Environmental Information (NCEI) Marine Microplastics database aggregates microplastic concentration data from ocean surveys, citizen-science initiatives, and peer-reviewed literature, providing an open-access resource for research, education, and policy analysis.
Limitations:
Variability in sampling protocols and analytical techniques limits harmonization, making direct comparisons across regions and time periods more uncertain and introducing potential biases in global assessments.
NOAA’s Marine Debris Monitoring and Assessment Project (MDMAP) collects standardized shoreline debris data through regular surveys conducted by trained volunteers and partner organizations. Fixed transects are surveyed over time to track debris abundance, composition, and trends along coastlines.
Limitations:
The dataset is geographically focused on the United States and nearby regions and depends on volunteer participation, which can lead to uneven spatial and temporal coverage.
UNEP’s SDG Indicator 14.1.1.b (Marine Debris Density, particularly beach litter) compiles data reported by countries, regional seas conventions, and non-governmental organizations on plastic debris density in coastal environments. The methodology follows agreed SDG metadata standards and GESAMP guidelines, using measurements of plastic items per square meter.
Limitations:
Differences in national sampling protocols, survey frequency, and classification systems affect data harmonization. Reporting is voluntary, resulting in incomplete and uneven global coverage.
▶️ More details: explanatory video