We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
A local-to-global emissions inventory of macroplastic pollution
AI summary Read the abstract
Using machine learning and probabilistic material flow analysis, researchers built the first local-to-global inventory of macroplastic waste emissions, estimating 52.5 million metric tonnes are released annually worldwide — with over half burned in the open. The study pinpoints emission hotspots at the level of 50,000 individual municipalities, providing the most detailed evidence baseline yet to guide international plastic pollution treaty negotiations.
Abstract Negotiations for a Global Treaty on plastic pollution1 will shape policy on plastics production, use, and waste management for the coming decades. Parties will require a detailed baseline of waste flows and plastic emission sources at high resolution to enable identification of pollution hotspots and their causes2. Nationally aggregated waste management data can be distributed to smaller scale to identify generalised points of plastic accumulation and source phenomena3-11. However, it is challenging to use this type of spatial allocation to assess the conditions under which emissions take place12,13. To this, we developed a novel methodology for a global macroplastic waste inventory; creating an explanatory framework that combines conceptual modelling of emission mechanisms with measurable activity data. Using machine learning and probabilistic material flow analysis we identify hotspots worldwide (50,072 municipalities) from five land-based plastic waste emission sources. We estimate global plastic waste emissions at 52.5 million metric tonnes (Mt), of which 57% wt. are open burned. Highest contributions: India (9.7 Mt), Nigeria (3.5 Mt), and Indonesia (3.0 Mt). Uncollected waste is the dominant emissions source across Global South. This detailed evidence baseline can inform Treaty negotiations and help develop national and sub-national waste management action plans and source inventories.
More Papers Like This
A local-to-global emissions inventory of macroplastic pollution.
AI summary Read the abstract
This study developed a high-resolution global inventory of macroplastic pollution by distributing nationally reported waste management data down to sub-national and local scales, producing maps of plastic emission hotspots. The dataset is intended to support negotiations for a global plastics treaty by providing a data-driven baseline for identifying sources and prioritizing interventions.
Using Dynamic Release Modeling to Predict Historic and Current Macro- and Microplastic Releases
AI summary Read the abstract
Researchers developed a Dynamic Probabilistic Material Flow Analysis model coupled with a release model to quantify historic and current macro- and microplastic emissions in Switzerland, providing a dataset tracking plastic releases across product lifecycles.
Using Dynamic Release Modeling to Predict Historic and Current Macro- and Microplastic Releases
AI summary Read the abstract
Researchers developed a Dynamic Probabilistic Material Flow Analysis model coupled with a release model to quantify historic and current macro- and microplastic emissions in Switzerland, providing a companion dataset to a publication in Resources, Conservation and Recycling.
A proxy-based approach to predict spatially resolved emissions of macro- and microplastic to the environment
AI summary Read the abstract
Using land-use statistics, traffic data, and wastewater infrastructure as proxies, researchers created high-resolution maps of microplastic and macroplastic emissions across Switzerland at the regional level. The approach reveals that plastic pollution is concentrated near urban and high-traffic areas but varies substantially by polymer type and emission source.
Sources and fate of atmospheric microplastics revealed from inverse and dispersion modelling: From global emissions to deposition
AI summary Read the abstract
Researchers combined atmospheric observations and inverse modeling to estimate global microplastic emissions at 9.6 megatons per year, then used dispersion modeling to trace sources and deposition patterns from emissions to atmospheric fallout worldwide.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.