Predicting microplastic massesin river networks with highspatial resolution at country level

Microplastics are a ubiquitous contaminant of natural waters, and a lot of

feld monitoring is currently performed. However, what is missing so far

is a general understanding how emissions of microplastics are linked to

environmental exposure, especially on larger geographic scales such as

countries. Here we coupled a high-resolution microplastic release model

with a fate model in rivers and lakes and parameterized it for Switzerland on

a country scale to predict masses of microplastics in each river section for

seven diferent polymers. The results show that catchment characteristics,

for example, distribution of releases within the catchment, location and

size of lakes or river connections, are as important as polymer properties

such as density. There is no simple linear function of microplastic retention

within a catchment in dependency of river length to the outlet. Instead, we

found that diferent catchments cover a wide range of retained fractions

for microplastics. Consequently, we argue that the availability and use

of spatially distributed release data and performing modelling on high

spatial resolution is of importance when estimating concentrations of

microplastics in large areas such as countries.