Two years of daily monitoring of floating macro-litter at the River-Sea interface: Aarhus River, Denmark.

Marine litter is a global problem, with rivers acting as major pathways for land-based waste entering the oceans. Current estimates of riverine litter inputs in the EU often rely on short-term visual surveys from bridges or piers, which provide incomplete data and a coarse classification of litter types. This study presents, for the first time in Denmark and the wider Baltic region, high-resolution daily (24 h) monitoring of floating macro-litter in the Aarhus River using the SeaProtectorOne device that spans the entire river width. Litter was collected continuously over two one-year periods (2021/22 and 2024/25), enabling a detailed analysis of litter dynamics at the river-sea interface. A total of 63,035 litter pieces were collected in the first year and 18,725 in the second. On average across both years, plastics were consistently dominant, accounting for 60 % of all items, followed by paper and cardboard at 23 %. Single-use plastics (53 %) together with takeaway-related paper items such as bags, food wrappers, and trays made up the majority of inputs. Pollution peaked during weekends, particularly in summer and autumn, highlighting the influence of social and recreational activities in the city center on litter generation. The results demonstrate that continuous collection provides more accurate estimates of riverine litter fluxes than visual surveys and allows detailed identification of litter types, which can inform targeted prevention and reduction measures at local and regional scales. The marked decline in litter between the two periods likely reflects the effects of local prevention measures and increased public awareness.

• Publication year

  2025

• Venue

  Marine Pollution Bulletin

• Publication date

  2025-10-31

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.1016/j.marpolbul.2025.118913PMID 41175524
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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