Predicting microplastic masses in river networks with high spatial resolution at country level

Abstract

Microplastics are a ubiquitous contaminant of natural waters, and a lot of field 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 different 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 different 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.

Macroplastic Fate and Transport Modeling: Freshwaters Act as Main Reservoirs

“…In summary, we estimated that about three-quarters of the input macroplastic emissions were retained through long-term accumulation in river environments. This contrasts with microplastic retention behavior, which was found to be dominated by lakes, e.g., refs and – but is supported by field observation of macroplastic litter on river banks, e.g., refs – .…”

“…In contrast to our findings for microplastics, the mass of macroplastic transported via the Rhône River (about 50 kg year –1 , average discharge false( Q x̅ false) = 338 m 3 s –1 ) toward France was about in the same order magnitude than other rivers with much lower discharges, e.g., Inn (62 kg year –1 , Q x̅ = 20 m 3 s –1 ) or Breggia (155 kg year –1 , Q x̅ = 1.2 m 3 s –1 ). Additionally, we calculated that about 20% of macroplastic mass was categorized as “flow into unknown”.…”

“…River Network Data and Input Emissions. In the presented model, we used the river network of Switzerland as developed for microplastic modeling in Mennekes and Nowack 21 and provided by swisstopo. The river network was connected according to the flow direction, including the flows through lakes.…”

“…Currently, macroplastic modeling approaches similar to microplastic models (e.g., nanoDUFLOW or The Full Multi) are missing. Based on existing knowledge, macroplastic fate and transport are expected to differ from microplastic fate and transport on a country scale. ,,, …”

Natural Factors of Microplastics Distribution and Migration in Water: A Review

“…However, it elaborated the concept of MPs for the first time, which also triggered the rapid growth of microplastic research in environmental media [2]. Plastic debris in the environment is a growing pollution problem, and a large number of studies have shown that MPs are ubiquitous on the planet and in polar regions, seawater, rivers, lakes, urban water bodies, underground water bodies, soils, the Qinghai-Tibet Plateau [3][4][5][6], food [7], and organisms [8]. "Plastics-the Fast Facts 2023" reported that global rate production rose from 1.7 million tons in 1950 to 367 million tons in 2020, in addition to 403 million tons in 2 of 21 2022 due to the COVID-19 pandemic in 2019 [9].…”