We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Reduction scenarios of plastic waste emission guided by the probability distribution model to avoid additional ocean plastic pollution by 2050s
Summary
Researchers developed a probability distribution model to predict future marine macroplastic and microplastic abundances under various waste emission scenarios. The study suggests that to achieve zero additional ocean plastic pollution by 2050, global plastic waste emissions would need to be reduced by at least 32% relative to 2019 levels by around 2035, requiring stringent systemic changes in waste management.
Marine plastic pollution is progressing worldwide and will become increasingly serious if plastic waste emissions continue at the current rate or increase with economic growth. Here, we report a particle tracking-based probability distribution model for predicting the abundances of marine macroplastics and microplastics, which undergo generation, transport, and removal processes in the world's upper ocean, under various scenarios of future land-to-sea plastic waste emissions. To achieve the Osaka Blue Ocean Vision, which aims to reduce additional pollution by marine plastic litter to zero by 2050, plastic waste emission in ∼2035 should be reduced by at least 32 % relative to 2019. It is necessary to take stringent measures such as 'system change scenario' or 'improve waste management scenario' proposed in previous studies to reduce the marine plastic pollution by 2050.
Sign in to start a discussion.
More Papers Like This
Evaluating scenarios toward zero plastic pollution
Researchers modeled five different intervention scenarios for reducing global plastic pollution between 2016 and 2040 and found that even implementing all feasible solutions would only cut pollution rates by 40% compared to 2016 levels. Under a business-as-usual scenario, 710 million metric tons of plastic waste would still accumulate in ecosystems even with immediate action. The study makes clear that coordinated global efforts across consumption reduction, recycling, waste collection, and innovation are urgently needed.
Plastic waste discharge to the global ocean constrained by seawater observations
Researchers used ocean plastic concentration data combined with multiple ocean circulation models to estimate that approximately 0.7 million metric tons of plastic enter the ocean each year, though uncertainty spans nearly 1.5 orders of magnitude. The study emphasizes that improving emission inventories and ocean monitoring data are the highest priorities for reducing uncertainty in global plastic pollution estimates.
Forecasting global plastic production and microplastic emission using advanced optimised discrete grey model
Researchers used advanced mathematical models to forecast future global plastic production and microplastic emissions. Their projections suggest that both production and emissions will continue rising significantly in the coming decades if current trends hold. The study provides policymakers with quantitative predictions that could help guide strategies for reducing plastic pollution.
The crucial role of circular waste management systems in cutting waste leakage into aquatic environments
Researchers combined spatial modeling with global population and development projections to show that 70% of future plastic waste leaking into waterways will come from China, South Asia, Africa, and India, and that even aggressive circular economy strategies cannot fully eliminate this leakage before 2030. The findings underscore that preventing plastic from entering the waste stream — not just cleaning it up — is the most effective intervention.
How much are we responsible for removing ocean plastic pollution ?
Researchers developed an integrated system dynamics and input-output model to simulate global marine plastic waste trends through 2050, quantifying the economic effort required from producers and consumers to achieve plastic removal targets across shoreline, coastal, and offshore ocean domains.