\Abstract{
Marine plastic pollution is an increasing global concern, as plastic particles are found in the most remote parts of the ocean and pose various threats to marine life. First estimates quantify the contemporary coastal or riverine plastic input at the country-level, but little is known about the spatio-temporal distribution of its sources and sinks at the global scale.\\
We use machine learning algorithms to estimate the global plastic input to the ocean from coastal sources and riverine input for the years 1990-2015 on a 0.1x0.1° grid. Using neural network and random forest models, we predict the waste generation per country from socio-economic factors such as population density or energy consumption. We then apply population size, waste management and waste composition, as well as distance-based probabilities of land and river transport to derive the plastic flux to the ocean. Additionally, the effect of several waste management practise scenarios on plastic fluxes as well as a future projections assuming a business as usual scenario for 2030 and 2050 are assessed. Finally, we determine the fate of the floating marine plastic debris using a Lagrangian particle simulator driven by geostrophic current data.\\
In line with previous findings, predicted global plastic input increased from 13.4 Mt in 1990 to 18.7 Mt in 2015 with 94\% and 6\% entering via the coasts and rivers respectively in 2015. While middle-income countries (representing 58\% of the world's population) account for 90\% of the global marine plastic input in 2015, high-income countries (31\% of the population) account for 9\% and low-income (11\% of the population) for 1\%. In 2015, most plastic enters the oceans in Asia (84\%) while Europe and Africa account for 5\% each, North and South America for 3\% each and Oceania for 0.2\%. Our models also suggest an increase of marine plastic input in several African, East Asian and South American countries in the time period observed while European and Northern American countries generally show a decrease.
Our results show the temporal and spatial development of marine plastic debris generation and the influence of the socio-economic factors. This helps to assess where possible measures to reduce plastic pollution will be most effective.
}