EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

16,000 riverbank litter items – A data driven approach to optimizing riverine plastic monitoring

Finn Begemann1, Sjoukje de Lange1, Yvette Mellink1, Paul Vriend2, Paolo Tasseron1, and Tim van Emmerik1
Finn Begemann et al.
  • 1Hydrology & Quantitative Water Management, Wageningen University & Research, Netherlands
  • 2Independent Researcher

Macrolitter in aquatic environments is an emerging environmental risk, as it negatively impacts ecosystems, endangers aquatic species, and causes economic damage. One of the major reservoirs of macrolitter in aquatic environments are riverbanks. To effectively clean riverbanks and prevent future litter from accumulating in these reservoirs, robust monitoring techniques are needed that allow for quick, but reliable, assessments of the type, size and mass of macrolitter in these reservoirs. Here, we present a unique dataset of more than 16,000 anthropogenic litter items in the Dutch Rhine, Meuse and IJssel rivers. With this dataset, we facilitate making considered decisions for developing future monitoring strategies. Items were collected on 8 different riverbanks once per month for one year. Items were collected at upstream and downstream locations along the Dutch part of the rivers, and were categorized (river-OSPAR), weighed and measured. The dataset shows that the majority of the found items is plastic, especially fragments of foam, soft plastics (foils), and hard plastics. The composition of litter type varies more in space than in time, indicating that the spatial resolution of a future monitoring campaign outweighs the importance of the temporal resolution. We performed a Monte Carlo analysis to determine sample size requirements to calculate a representative number of average item mass. Up until 8,900 items are needed for an accurate representation of average items mass, depending on item category uniformity. Finally, a method is proposed to determine on which item size should be focused. The presented dataset can be used in future research, modelling practices and development of management strategies. 

How to cite: Begemann, F., de Lange, S., Mellink, Y., Vriend, P., Tasseron, P., and van Emmerik, T.: 16,000 riverbank litter items – A data driven approach to optimizing riverine plastic monitoring, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9060,, 2022.


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