Waste management and recycling
Technical reports
D.1.4.2: Retrieving information on beach clean-up activities from social network sites. Socio-economic impact.
Responsible Partner: IEO
Date: September 2024
Download: report
Description: This report presents the design and implementation of an algorithm to obtain X and Instagram data related to beach and coastal clean-up activities. The objective is to obtain a dataset with information on this type of activities in the 4 countries of the Atlantic Area programme. This dataset will provide valuable information for understanding environmental awareness of the marine litter problem, as well as quantifying the social and economic impact associated with the development of beach and coastal clean-up campaigns.
Good practices
Good practices website
Responsible Partner: UBS
Date: December 2025
Website link: Link
Description: This webpage brings together the main outcomes of the Free LitterAT project, which focuses on analysing waste management practices in Atlantic ports. It introduces the project and presents an interactive map of the Atlantic seaboard showing the ports visited, alongside key figures on the fishing industry in the four partner countries. The website also features summary sheets of ports and initiatives, an infographic explaining the recycling stages of fishing gear and the stakeholders involved, as well as practical information and testimonials for port managers and fishermen.
Webinars
Webinar: ‘Fishing for Litter in the Frame of the PRF Directive: Experiences and Challenges in the Atlantic’
Responsible Partner: UBS
Date: 6 February 2026
Presentations: Link
Description: The objective of the second webinar of WP1 of the Free LitterAT project, held on 6 February 2026, was to review the implementation status of the PRF Directive (EU 2019/883) on port reception facilities for ship-generated waste and to share practical experiences from Fishing for Litter initiatives across the Atlantic region. The session aimed to analyse operational and strategic challenges related to the integration of passively fished waste into port waste management systems, highlighting the importance of adequate infrastructure, reliable traceability, and operational and economic sustainability. National experiences from Portugal, Spain, Ireland, and France were presented, along with best practices, tools, and resources developed by the project. The webinar also promoted dialogue among port authorities, waste managers, competent administrations, and fishermen, fostering coordination, training, and awareness. The activity contributed to identifying common challenges and opportunities for improvement, strengthening knowledge exchange and the harmonisation of practices across the Atlantic region.
Webinar: ‘Tackling plastic pollution in the Atlantic area – Moving forward in the implementation of the EPR for fishing gear’
Responsible Partner: UBS
Date: 13 November 2025
Presentations: Link
Description: The objective of the first webinar of WP1 of the Free LitterAT project, held on 13 November 2025, was to analyse the management of used fishing gear and the challenges associated with implementing Extended Producer Responsibility (EPR) for fishing gear containing plastics. The session addressed the context of the SUP and PRF Directives, examining their implementation in Spain, Portugal, Ireland, and France, focusing on the waste streams of plastic fishing gear and passively fished waste. The webinar aimed to provide practical recommendations, share experiences, and gather stakeholder input, fostering a dialogue to contribute to the reduction of marine plastic pollution and support the effective enforcement of relevant regulations.
Publications
Challenges of passive citizen science in ecology within a shifting social media landscape
Responsible Partner: IEO-CSIC
Date: June 2025
Download: Paper
Description: This Viewpoint article examines the current challenges associated with passive citizen science and underscores the need to strengthen this valuable approach to support regional solutions that account for linguistic diversity, multiple data sources, fluctuating user engagement, and the integration of artificial intelligence tools for the supervision and classification of images and text.