Global Coastline Plastic Emissions into the Oceans

Global
marine plastic pollution has become a major concern for
its negative effect on marine life and potential human health. However,
research on the distribution and quantification of coastal sources
remains limited, hindering the formulation of effective mitigation
strategies. Here, we developed a machine learning-based framework
using 25,892 data points from 3468 coastal sampling sites, incorporating
38 features including socioeconomic factors, plastic waste sectors,
and types. The framework further integrates coastal geomorphological
and tidal characteristics to account for the regulating effects of
natural processes on plastic emissions. To systematically characterize
pollution severity, we proposed the Coastal Plastic Pollution Index
(CPPI), which classifies coastal input sites into four levels (I–IV)
based on estimated emission. The model estimated global coastal plastic
emission in 2019 between 15.32 and 59.18 Kt, with per capita values
ranging from 2.17 to 8.38 g. Mismanaged plastic waste (MPW), plastic
waste generation (PWG), consumer and institutional products (CIP),
packaging (PAC) PET, and PP play dominant roles in coastal emissions.
After clustering the sampling data using unsupervised learning, we
found a high degree of consistency in CPPI distribution among countries
within the same cluster. Our findings offer robust scientific support
for both national and international policy actions.