Microplastics in China’s surface water systems: Distribution, driving forces and ecological risk

Abstract

Comprehensively understanding the distribution, driving forces and ecological risk of microplastics (MPs) in China’s surface water systems is crucial for future prevention and control of MPs pollution, particularly in the context of regional differences. Nevertheless, traditionally localized investigation and the limited MPs data availability hinder more comprehensive estimation of MPs pollution in surface water systems of China. This study presents a robust dataset, which consists of 14285 samples from 32 provincial districts, describing the MPs pollution characteristics using a data mining method combined with a machine learning model. The results show that the developed model has high accuracy in predicting the abundance, colors, shapes, and polymer types of MPs, with the coefficient of determination (R²) ranging from 0.825 to 0.978. MPs abundance varied greatly in China’s surface water systems, ranging over 1–5 orders of magnitude due to the complex influence of anthropogenic activities and natural conditions. Human activities and natural conditions mutually impact the dynamics of MPs in China’s surface water systems. Watersheds in almost all provinces of China are contaminated by high and extremely high ecological risk levels, highlighting the urgency for sustainable MPs management.