From 16 to 17 October 2025, the technical workshop “Free LitterAT Workshop on Geographic Source Identification of Marine Litter” took place in Porto Santo (Madeira, Portugal), organised by DRAM, the regional authority for environmental management and a key partner of the Free LitterAT project.
The event brought together 22 participants from eight countries, including representatives from project partners and invited experts in marine litter monitoring and analysis. The workshop aimed to advance the development of shared methodologies for identifying the geographical origin of marine litter accumulating along Atlantic coastlines.
Over the course of the workshop, participants combined theoretical sessions with extensive hands-on analysis. Using large batches of marine litter collected from remote accumulation sites, attendees conducted detailed sorting exercises based on the OSPAR classification system, resulting in more than 80 item categories. Practical demonstrations explored complementary approaches for determining the likely origin of specific items, including biofouling examination, fishing gear typology, labelling and traceability, and comparison with local fishing practices.
A central part of the workshop involved testing a probabilistic scoring matrix to assess the likelihood that different categories of litter originated from local, neighbouring, regional, or distant global areas, distinguishing between sea-based and land-based sources. The preliminary results will contribute to evaluating the effectiveness of existing EU and regional policies, and to identifying where strengthened international cooperation may be needed.
Beyond its technical outcomes, the workshop reinforced collaboration among institutions, researchers, and practitioners working to better understand and reduce marine litter across the Atlantic region. Results from this workshop will be integrated into upcoming project activities, including future field campaigns and regional guidance materials to support targeted prevention and reduction measures.
