Global Plastic Waste Input into the Ocean between 1990-2015
Abstract:
We present a model to estimate the global plastic input to the ocean for the years 1990-2015 on a 0.1x0.1° raster. To this end, we first train two independent machine learning models (neural networks and random forests) and a linear mixed model to predict plastic waste production on country level, using data of municipal waste collection and several socio-economic predictor variables. We then estimate the amount of plastic waste that enters the environment, using high resolution population data and waste management data of each country. This is combined with distance-based probabilities of land and river transport to obtain the annual amount of plastic entering the ocean on a 0.1x0.1° spatial resolution. Several scenarios with different waste management practices were created and a sensitivity analysis on several parameters from the waste production models is performed to identify factors with a high influence on marine plastic input.
Our results indicate that global plastic waste production increased linearly between 1990 to 2015. However, estimating the amount of mismanaged waste and the subsequent transport towards the ocean is afflicted with high uncertainties.