Spatiotemporal dynamics of microplastics in an urban river network area

• Spatiotemporal dynamic of microplastics in an urban river network area was studied. • The microplastics abundance showed a strong temporal but smooth spatial variation. • Laser direct infrared was employed to identify microplastics as a novel method. • Silicone, rubber and PTFE were the main polymer types of the microplastics in the area. Microplastics contamination in the environment is a global problem, but little is known about their dynamics in urban river networks, an important site of microplastics occurrence and harboring complex transport pathways. In this study, we investigated the spatiotemporal dynamic of microplastics in a typical urban river network in eastern China from December 2018 to September 2019. microplastics abundance (mean ± standard deviation) in the river network ranged from 2.3 ± 1.2 to 104.6 ± 5.6 particles/L and was significantly higher during the wet than during the dry season. The distribution of microplastics in the upper, middle, and lower reaches of the river network did not significantly differ, nor did the abundance of microplastics in the surface water vs. the bottom water. However, high abundances were determined in commercial and industrial areas, at a wastewater treatment plant outlet, in an urban canal, and in an urban-rural fringe area. The seasonal dynamics of the overall abundance of microplastics could be explained by the hysteresis effect of urban plastic production and the variation in regional precipitation. 78.2% of the microplastics were < 330 µm in size; the most common colors were blue and black, and the most common shapes were fragments and fibers. The polymer types of the microplastics were assessed using laser direct infrared (LDIR), a novel chemical imaging system that identified silicone, rubber, polytetrafluoroethylene, and polypropylene as the main components of the microplastics. A non-metric multidimensional scaling analysis (NMDS) based on the abundance of the polymer components across samples showed aggregations of sampling sites, that indicated the possible sources of the microplastics. Our study provides insights into the spatiotemporal dynamics of microplastics in an urban river network and suggests the potential of LDIR in the accurate quantitative analysis of microplastics in the environment.