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How to cite this report: Addamo Anna Maria, Brosich Alberto, Chaves Montero Maria del Mar, Giorgetti Alessandra, Hanke Georg, Molina Jack Maria Eugenia, Vinci Matteo, Marine litter database: Lessons learned in compiling the first pan-European beach litter database, EUR 29469 EN, Publications Office of the European Union, Luxembourg, 2018, ISBN 978-92-79-97866-1, doi:10.2760/68866, JRC112895.

Marine litter database - Lessons learned in compiling the first pan-European beach litter database - Study

Foreword

The Marine Directors of the European Union (EU), all EU Member States, acceding countries, candidate countries and European Free Trade Association (EFTA) countries have jointly developed a common strategy for supporting the implementation of Directive 2008/56/EC, the Marine Strategy Framework Directive (MSFD). The main aim of this strategy is to allow a coherent and harmonious implementation of the Directive. The focus of the strategy is on methodological questions related to a common understanding of the technical and scientific implications of the MSFD. In particular, one of the objectives of the strategy is the development of non-legally binding and practical documents, such as this report, on various technical issues of the Directive. In order to support and advise the policy development and implementation process, the MSFD Technical Group on Marine Litter (TG Litter hereafter) has been set up as part of the MSFD Implementation Strategy. The TG Litter is led by Directorate General Environment (DG ENV) and is chaired by the French Research Institute for Exploitation of the Sea (Ifremer), the German Environment Agency (UBA) and the European Commission Joint Research Centre (EC JRC) (¹)).

This report has been prepared by the EC JRC and EMODnet Chemistry Consortium, based on data and information collected through and revised by the TG Litter.

This publication is part of a series of technical reports on specific thematic topics, such as Top marine beach litter items in Europe: A review and synthesis based on beach litter data, Harm caused by marine litter, Identifying sources of marine litter, Riverine litter monitoring: Options and recommendations and Guidance on monitoring of marine litter in the European seas. These thematic reports are aimed at those experts who are directly or indirectly implementing the MSFD in the marine regions.

This technical report provides information to EU Member States on data quality and data management in support of the MSFD and other European policies in determining baselines and thresholds, implementing monitoring programmes and planning measures against marine litter.

Disclaimer:

This document has been developed through a collaborative programme involving the European Commission, all EU Member States, acceding countries, Norway, international organisations (including the Regional Sea Conventions and other stakeholders) and non-governmental organisations. The document should be regarded as presenting an informal consensus position on best practice agreed by all partners. However, the document does not necessarily represent the official, formal position of any of the partners. Hence, the views expressed in the document do not necessarily represent the views of the European Commission.

Acknowledgements

The authors would like to thank all Member States’ authorities, the Regional Sea Conventions (OSPAR commission, Barcelona convention UN Environment/MAP, Baltic Marine Environment Protection commission — Helsinki commission (Helcom), Black Sea commission), non-governmental organisations (NGOs), others who have contributed to the scope of this report by providing marine beach litter data, and all members of the TG Litter, and in particular David Fleet, Marta Ruiz, Lone Soederberg and Eva Blirberg for their comments and suggestions, which have contributed to this report.

Financial support was provided by EC DG MARE through the call for tender EASME/EMFF/2016/006, Operation, development and maintenance of a European marine observation and data network (EMODnet).

Service Contract No EASME/EMFF/2016/1.3.1.2/Lot4/SI2.749773.

For providing data, we would like to acknowledge:

Member State authorities

Bulgaria: Stela Barova and Violeta Slabakova, Black Sea Basin Directorate to the Ministry of Environment and Water, Department Marine Waters Protection and Monitoring.

Croatia: Pero Tutnam, Institute of Oceanography and Fisheries.

Denmark (Baltic Sea): Lone Munk Søderberg, Danish Ministry of the Environment and Food; Jakob Strand, Aarhus University, Department of Bioscience — Marine Diversity and Experimental Ecology.

Estonia: Marek Press, Keep the Estonian Sea Tidy Association; Agnes Unnuk and Katarina Oganjan, Ministry of the Environment of Estonia.

Finland: Suikkanen Sanna, Finnish Environment Institute.

France (Mediterranean Sea): Francois Galgani, French Research Institute for Exploitation of the Sea; Sophie Beauvais, French Biodiversity Agency; Camille Lacroix, French Centre of Documentation, Research and Experimentation on Accidental Water Pollution.

Germany (Baltic Sea): Dennis Gräewe, State Agency for Environment, Nature Conservation and Geology, Mecklenburg-Vorpommern, Division Geology, Water and Soil, Department Water Quality Inland and Coastal Water; Stefanie Werner, German Federal Environment Agency.

Greece: DeFishGear Project/MIO-ECSDE; Thomais Vlachogianni, Mediterranean Information Office for Environment, Culture and Sustainable Development.

Latvia: Janis Ulme, Foundation for Environmental Education; Baiba Zasa, Ministry of Environmental Protection and Regional Development of the Republic of Latvia.

Lithuania: Laura Lauciutė, Environment Protection Agency, Marine Research Department.

Poland: State Environmental Monitoring; Włodzimierz Krzymiński, Tamara Zalewska, National Research Institute, Institute of Meteorology and Water Management.

Romania: Elena Stoica, National Institute for Marine Research and Development ‘Grigore Antipa’.

Slovenia: Andreja Palatinus and Manca Kovač Viršek, Institute for Water of the Republic of Slovenia.

Spain: Marta Martínez-Gil Pardo de Vera, Ministry of Agriculture, Fisheries and Food. Directorate for Coast and Sea Sustainability.

Sweden (Baltic Sea): MARLIN Project; Eva Blidberg, Keep Sweden Tidy; Johanna Eriksson, Swedish Agency for Marine and Water Management; Per Nilsson, Swedish Institute for the Marine Environment.

Regional Sea Conventions and non-governmental organisations

OSPAR and Marine Conservation Society: Convention for the protection of the marine environment of the North-East Atlantic (OSPAR Commission) and Sue Kinsey, Marine Conservation Society, for providing data from Belgium, Denmark (including the Faroe Islands), Ireland, Spain, Germany, France, Iceland, the Netherlands, Norway, Portugal, Sweden and the United Kingdom (North-East Atlantic region).

Legambiente: Giorgio Zampetti and Stefania Divito for providing NGO data from Italy.

Isotech Ltd: Environmental research and consultancy for data collected in Cyprus.

Non-EU Member States

Georgia: Kakhaber Bilashvili, Institute of Oceanography and Hydrology of Ivane Javakhishvili Tbilisi State University (TSU).

Montenegro: Anna Castelli, Institute of Marine Biology.

Russia and Ukraine: EMBLAS II Project; Maria Pogojeva, State Oceanographic Institute (SOI).

Authors

Anna Maria, Addamo, European Commission DG Joint Research Centre, Directorate D — Sustainable Resources, Unit D.02 Water and Marine Resources, I-21027 Ispra (VA) — Italy.

Alberto, Brosich, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Borgo Grotta Gigante, 42/c, IT-34010 Sgonico (TS) — Italy.

María del Mar, Chaves Montero, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Borgo Grotta Gigante, 42/c, IT-34010 Sgonico (TS) — Italy.

Alessandra, Giorgetti, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Borgo Grotta Gigante, 42/c, IT-34010 Sgonico (TS) — Italy.

Georg, Hanke, European Commission DG Joint Research Centre, Directorate D — Sustainable Resources, Unit D.02 Water and Marine Resources, I-21027 Ispra (VA) — Italy.

Maria Eugenia, Molina Jack, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Borgo Grotta Gigante, 42/c, IT-34010 Sgonico (TS) — Italy.

Matteo, Vinci, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Borgo Grotta Gigante, 42/c, IT-34010 Sgonico (TS) — Italy.

Abbreviations

DeFishGear | Project on derelict fishing gear management system in the Adriatic region
DG ENV | Directorate-General for Environment
DG GROW | Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs
EC | European Commission
EFTA | European Free Trade Association
Emblas | Environmental monitoring of the Black Sea
EMODnet | European Marine Observation and Data Network
EU | European Union
GES | good environmental status
G7 | Group of Seven
G20 | Group of 20
Helcom | Baltic Marine Environment Protection Commission — Helsinki Commission
Ifremer | French Research Institute for Exploitation of the Sea
Inspire | Infrastructure for spatial information in Europe
JRC | Joint Research Centre
MARLIN | Project on Marine Littering the Baltic Sea Area
MIO-ECSDE | Mediterranean Information Office for Environment, Culture and Sustainable Development
MS | Member State
MSFD | Marine Strategy Framework Directive
NGO | non-governmental organisation
OSPAR | Convention for the protection of the marine environment of the North-East Atlantic Commission
PAME | Protection of the Arctic marine environment
SeaDataNet | Pan-European infrastructure for ocean and marine data management
TG Litter | MSFD GES Technical Group on Marine Litter
UBA | German environment agency
UNEP/MAP | United Nations Environment Programme/Mediterranean Action Plan Barcelona Convention

Abstract

Marine litter is a global concern that represents a threat to all life in the oceans and seas. Reducing litter in the marine environment is recognised as a priority challenge to help preserve the ecosystem and human health. Marine litter, in particular marine plastics, and its reduction is at the core of political action through the Marine Strategy Framework Directive (MSFD), the EU Strategy for Plastics in a Circular Economy and the EU Waste Legislation.

Quantifying the amount of litter items present in the marine ecosystem is a matter of concern for the MSFD and in general for policies that aim to tackle marine litter. EU marine litter data quality and data management are defined by a complex system of datasets, in which a heterogeneity of protocols are still in use at regional and national levels. In accordance with the implementation of Good Environmental Status (GES) and other aspects of the MSFD, adopting consistent and harmonised criteria and methodological standards ensures consistency of data and the possibility of meaningful comparison between marine regions and subregions.

Defining the best possible data management strategy and identifying the most valuable methodology have been pursued by the Joint Research Council (JRC) and the European Marine Observation and Data Network (EMODnet) Chemistry network, within the TG Litter, with the main goal of delivering a single database able to handle marine litter data at European scale. This report proposes a tailor-made standard procedure on a European scale and lists challenges and hindrances faced during the compilation of beach litter data collected by the countries bordering the European seas, generating the first pan-European beach litter database.

The analysis has primarily involved data from 22 European countries and four marine regions. In total 3 063 surveys were performed on 389 European beaches over the period 2012 to 2016. In addition, data from non-European countries facing the seas around Europe have also been included in the database.

The biggest challenge faced during the data-compiling phase was dealing with the heterogeneity related to differences in data formats, data quality and protocols used during the beach surveys. A huge effort has been made to handle a varied set of data to guarantee efficient management of the data. The resulting harmonised marine litter database will be made accessible through the EMODnet Chemistry website. A more dynamic and tailored set of products, including datasets and maps for other marine litter compartments, is currently in development.

Furthermore, this report gives a complete outlook on further harmonisation approaches in other marine litter topics. The report also provides inputs to develop and implement the most efficient management of data to facilitate data-driven decisions in European policies.

1   Introduction

Marine litter, or debris, is defined as any persistent, manufactured or processed solid material discarded, disposed of or abandoned in the marine and coastal environment (Cheshire et al., 2009; MSFD GES Technical Subgroup on Marine Litter, 2013; Schulz et al., 2017). The marine environment acts as a sink of anthropogenic litter, accumulating items from land-based and sea-based sources (see Van Acoleyen et al., 2013; Veiga et al., 2016), and marine litter is found in all marine compartments such as beaches, shallow and deep seafloors, sea surface layer and the water column. Furthermore, marine litter and in particular plastics cause harm to marine biota at different levels of biological organisation and habitats, namely through entanglement in, or ingestion of, litter items by individuals, through chemical transfer, as a vector for transport of biota and by altering or modifying assemblages of species (Werner et al., 2016).

Marine litter is recognised as a worldwide concern by the European Commission (EC) and by global initiatives, such as the United Nations Environment Programme (UNEP), G7 and G20 (²), who state the urgency of the threat that ocean plastic waste and marine litter pose to the ecosystem. It causes harm to the environment and generates adverse economic, health and aesthetic impacts.

Quantifying the real amount of litter items present in the marine ecosystem is also a matter of concern for the Marine Strategy Framework Directive (MSFD) and for European policies that aim to tackle marine litter.

Box 1. Marine Strategy Framework Directive

The MSFD (European Parliament and Council of the European Union, 2008) provides the EU legal framework for the protection of the European seas. Marine litter is included as one of the descriptors for achieving and maintaining Good Environmental Status (GES) of European marine waters and protecting marine resources (see D10 in European Commission, 2010). GES should be achieved only when ‘properties and quantities of marine litter do not cause harm to the coastal and marine environment’. The revised European Commission Decision COM/2017/848 (European Commission, 2017a) provides details for the assessment of litter in the environment.

In particular, the European framework identified marine plastics and their reduction as the core of political action through the EU Strategy for Plastics in a Circular Economy and the EU Waste Legislation (³).

Box 2. EU Plastics Strategy

The EU Plastics Strategy (European Commission COM/2018/028, 2018), A European Strategy for Plastics in a Circular Economy, aims to address the challenges caused by plastic throughout its value chain, by taking its entire life cycle into account (DG ENV and DG GROW, 2017) in order to progress towards a European Circular Economy (European Commission, 2017b). Reducing the leakage of plastic into the environment requires sound scientific data and information in order to reinforce measures and ascertain progress.

EU marine litter data quality and data management are defined by a complex system of datasets in which a heterogeneity of marine litter monitoring protocols and standards are still in use at regional and national levels. In accordance with the implementation of GES and other aspects of the MSFD, adopting consistent and harmonised criteria and methodological standards ensures consistency of data and enables the meaningful comparison of marine litter data between marine regions and subregions.

The exercise of compiling a 2012-2016 beach litter dataset was set up in order to derive baselines for marine litter for the MSFD. Nevertheless, the worldwide attention to marine litter and the presence of several international initiatives (e.g. Environmental monitoring of the Black Sea (EMBLAS), Protection of the Arctic Marine Environment (PAME)) showed the importance and indeed the necessity of synergised and harmonised data. For this reason, the exercise has been extended to non-European countries facing the European seas. This geographical broadening of the marine litter database will provide an overall picture of litter information in European seas to the EC, which is going to take an active role in international collaborations on tackling the issue of marine litter.

The scope of this report is to define the best possible data management strategy, based on the lessons learned, and to identify the most valuable methodology for delivering a proposal for a single database able to handle marine litter data from beaches both at the European scale and beyond.

After the analysis of the available information and the data heterogeneity, a tailor-made standard procedure on a European scale has been proposed based on the best available reference documents for the beach litter compartment: adapting consolidated data formats to include all the available information. This report lists challenges and hindrances faced during the compilation of the first pan-European beach litter database. Once the critical issues have been resolved, the harmonised marine litter database will be made accessible through the European Marine Observation and Data Network (EMODnet) Chemistry website, in the data section (⁴).

Furthermore, a main outcome from the assessment of the available EU marine litter data was the contribution to the ongoing revision of the MSFD TG Litter Master List of Categories of Litter Items (TG Litter Master List, hereafter) with the aim of improving the data quality in future surveys.

The report gives a complete outlook on further harmonisation approaches in other marine litter topics, such as guidance of monitoring marine litter across EU, the ranking methodology for the identification of the top items and single-use plastics, and the set-up of baseline and threshold values. The report also provides inputs to develop and implement the most efficient data management system as an instrument for the right data-driven decisions in European policies.

1.1  Baseline concept and harmonised database

Several concepts of ‘baseline’ have been formulated over time: historical, binonomic, legal and shifting baselines (see Box 3). Nevertheless, a tailor-made definition of a marine litter baseline has been established as follows: a marine litter baseline is a starting point that provides a first large-scale comprehensive characterisation of marine litter in a specific year or time period and location. It is used to monitor, measure and assess progress and effectiveness during and after the implementation of measures or plans (⁵).

Box 3. Different baseline concepts

— HISTORICAL (ECOLOGICAL) BASELINE (Grinnel, 1910): refers to the ethnocentric view and the primeval wilderness in which the natural or ‘original’ (historical) conditions of ecosystems existed with a negligible anthropogenic impact.

— BINONOMIC (ECOLOGICAL) BASELINE (Shelford, 1931): refers to the use of relatively undisturbed environments as the reference point.

— LEGAL BASELINE (Ferraro and Pattanayak, 2006): refers to the use of directive/policy as a reference: 1) year of policy introduction or 2) before the measures came into force.

— SHIFTING BASELINE (Pauly, 1995): refers to the incremental lowering of standards, with respect to nature, in which each new generation 1) lacks knowledge of how the environment used to be; 2) redefines what is ‘natural’, according to personal experience; 3) sets the stage for the next generations’ shifting baseline. NB: a baseline that shifted before it was charted can cause a degraded state to be accepted as normal.

The quantification of litter and its impacts is needed to assess the state of the environment and to prioritise actions, including the monitoring of successful reduction measures, to achieve and maintain a GES. The setting of baseline values is therefore needed in order to provide a reference for trend analysis in marine litter. Deriving baselines on different spatial scales requires the availability of data with sufficient spatial and temporal coverage and a data quality process that is fit for purpose.

A global problem can be mitigated only through coordinated international action and comparable methodologies that facilitate comparison of occurrences and abundances. Moreover, developing a common single source of data should facilitate collaboration, avoid double efforts and reduce errors.

In this context, a consistent, harmonised dataset is crucial to be able to build an organised database, in which data can be used for performing comparative analyses and establishing baseline values of marine litter at any spatial-temporal scale needed.

Infrastructure for Spatial Information in Europe (Inspire) defines data harmonisation as the process of developing a common set of data product specifications in a way that allows the provision of access to spatial data through spatial data services in a representation that allows it to be combined with other harmonised data in a coherent way. This process includes agreements about coordinate reference systems, classification systems, application schemes, etc. (⁶).

1.2  Data guidance: template and vocabulary

The importance of collection, standardisation, aggregation and sharing of data lies in using the same template, terminology and definitions across Member States (MSs) (e.g. using a standard language). A standard approach allows the creation of a harmonised database and supports any calculation methodology used for comparative analysis.

Guidance and a template (⁷) for gathering and managing marine litter data have been recently developed to facilitate the integration of the data collected using the existing diverse protocols for marine litter monitoring. The main goal is to provide access to harmonised data and data products of marine litter on a European scale (Vinci et al., 2018). The guidance and template have included all the existing European information systems available for the marine litter. Regarding beach litter, all data provided for inclusion in the EMODnet Chemistry Beach Litter Database (⁸) are processed following the guidelines. The data and metadata ingested in the EMODnet Chemistry Beach Litter Database maintain the original information collected according to the protocol and reporting methodology used (OSPAR, UNEP/Mediterranean Action Plan Barcelona convention (MAP) and/or the MSFD).

Data collection for beach litter includes information related to beach metadata, survey metadata, litter data, and stranded or dead animals data (⁹). Each regularly monitored reference beach (¹⁰) is described with a series of metadata. These data include physical and geographical characteristics of the beach and also the uses and factors that can condition the presence of the litter on the beach. The same set of data should be recorded for the monitored beaches on the European coasts.

The lack of physical barriers in the marine environment leads to the consideration of the potential impact of marine litter from non-EU Member States and neighbouring countries. In developing a pan-European infrastructure for the management of large and diverse sets of marine data that originate from different countries bordering the European seas, it will be important to develop, adopt and have access to common terms and indexes, to create a vocabulary that might be improved and enlarged over time under a shared vision (e.g. SeaDataNet; Figure 1) (¹¹). The purpose of standard vocabularies is to make the different data providers (i.e. EU and non-EU countries) apply the same nomenclature, minimising subjectivity and normalising values and information.

Figure 1. Example of standard terms and indexes used for International Standard Organisation Countries (e.g. microlitter types)

Source: BODC Vocabulary Library, SeaDataNet, 2018.

NB: Figure 1 is an example of standard terms for microlitter types and should not be considered an alternative to the TG Litter Master List.

The introduction of a standard list of litter items and their definitions (i.e. the TG Litter Master List (¹²), a draft version of which was developed in the MSFD GES Technical Subgroup on Marine Litter, 2013) enables the comparison of results between regions and environmental compartments and can be used as a basis for preparing assessment protocols. If the list is detailed enough it will make it possible to infer the potential and/or most likely sources of litter, types of items or even the related potential harm that items can cause. This is a crucial step in helping to identify key priorities to tackle, design a programme of measures and support the monitoring of their effectiveness (MSFD GES Technical Subgroup on Marine Litter, 2013).

2   First pan-European beach litter database

This report provides insights into the technical hindrances to data compilation and comparability. These hindrances are related to methodological inconsistencies and the heterogeneity of data collection and/or sampling methods (e.g. the number of surveys, variable transect lengths and sampling units), data reporting or the use of different lists of litter items during the surveys (e.g. language issues and ad hoc coding), or the spatial-temporal distribution of data (e.g. no references, yearly/seasonal data).

Following both the agreement (⁵) on the approach for the scenario testing of marine beach litter baselines and the identification of available data, MSs, EMODnet Chemistry project partners and other stakeholders were invited to provide their data to the JRC through the TG Litter, and to the EMODnet Chemistry Consortium through the partnership.

2.1  Metadata of EU beach litter data

Metadata are an essential part of data quality management. They provide basic information about the data: what has been measured, who measured it and/or when/how data were gathered. They allow better organisation of the data and digital identification of the dataset, making resources visible. Therefore, together with quality flagging (which indicates the reliability of the data), they are key for the long-term preservation, use and reuse of the data long after the original measurement. For these reasons, the evaluation and choice of the format for the European beach litter database was focused on integrating the best set of information available.

The metadata included in the EMODnet Chemistry beach litter template (Galgani et al., 2018) are mainly derived from the Convention for the protection of the marine environment of the North-East Atlantic Commission (OSPAR) format, as it is the most complete and developed format available. This format was enriched with additional information to improve data management (i.e. information about data originator, data collator and project). Although the EMODnet Chemistry litter format is based on OSPAR, the template was defined after comparison and evaluation of all the available European beach litter data templates. Therefore, the final format is able to merge litter data from the different protocols and reference systems used by European countries:

• OSPAR: Guideline for monitoring marine litter on the beaches in the OSPAR maritime area, 2010;

• TG Litter: Guidance on monitoring of marine litter in European seas. MSFD Technical Subgroup on Marine Litter, 2013;

• UNEP: UNEP/IOC guidelines on survey and monitoring of marine litter, 2009;

• UNEP Project on marine littering the Baltic Sea area (MARLIN: Beach litter measurement method description (Appendix 1 in the final report of project Marlin — litter monitoring and raising awareness), 2011-2013.

The EMODnet Chemistry beach litter template (⁹) comprises an Excel file divided into four sheets that deal with the different topics separately: beach metadata, survey metadata, animals and litter data.

• The Beach sheet contains 43 fields and provides general information about the beach’s position and materials, features about its backshore, main currents and winds, developments on the beach, its usages and cleaning details.

• The Survey sheet contains 58 fields and provides general information about the survey date and position, the weather conditions, the presence and proximity of potential sources of pollution (rivers, cities, human activities) and if animals were found during the survey.

• The Animals sheet contains eight fields and provides specific information about the animals observed, such as the species, the age and sex of the animals and if they are entangled with litter items.

• The Litter sheet contains eight fields and provides specific information about the litter items found, such as the reference list used, litter code and description, and the quantity. The format foresees the chance to handle the original code and description of the item used by the surveyor and its conversion (when possible) to the official reference list (TG Litter Master List).

Standard vocabularies and definitions are used whenever possible to enable comparability. Some fields (such as those that deal with the data collator and originator) are managed using common vocabularies developed during EMODnet Chemistry activities (¹¹). These provide unambiguous descriptions of several kinds of information that are used all over Europe (¹³). For specific litter fields (such as those dealing with survey type and harbour type), dynamic online lists have been created to describe features related to beach litter data (¹⁴). The latter terms are evolving during the data collection but will be turned into common vocabulary terms when they are stable.

The pan-European beach litter database (containing the marine litter baselines dataset) currently comprises the data collected in the European (and some non-European) beach litter surveys performed between 2001 and 2017 (¹⁵). However, the dataset is growing continuously to capture all of the available information on this topic.

The dataset currently includes information on 518 beaches from 4 772 surveys conducted in 29 countries (including non-European countries) during the last 17 years (see Table 1 and Figures 2-5). Several litter reference lists were used by the Member States to report their beach litter data: OSPAR, UNEP, UNEP MARLIN, and the TG Litter Master List of categories of litter items. The complete marine litter database will be made accessible through the EMODnet Chemistry website (http://www.emodnet-chemistry.eu).

Table 1. Number of beaches and surveys in the pan-European beach litter database

Country | Number of beaches | Number of surveys
Belgium | 3 | 75
Bulgaria | 8 | 32
Croatia | 4 | 16
Cyprus | 24 | 29
Denmark (incl. Greenland)¹ | 21 | 78
Estonia | 10 | 106
Faroe Islands² | 1 | 4
Finland | 14 | 158
France | 22 | 268
Georgia² | 3 | 3
Germany | 31 | 604
Greece | 6 | 21
Iceland² | 5 | 7
Ireland | 4 | 91
Italy | 162 | 162
Latvia | 41 | 187
Lithuania | 4 | 32
Montenegro² | 2 | 8
Netherlands | 4 | 312
Norway² | 7 | 49
Poland | 15 | 120
Portugal | 13 | 205
Romania | 3 | 9
Russian Federation² | 5 | 5
Slovenia | 5 | 132
Spain | 30 | 563
Sweden | 22 | 333
Ukraine² | 1 | 1
United Kingdom | 48 | 1162

Notes:

¹ Total number of beaches and surveys for Denmark [beaches (5), surveys (24)] and Greenland [beaches (16), surveys (54)].

² Non-EU MS. Data from these countries will not be included in the MSFD baseline setting.

The numbers of beaches and surveys performed during 2017 are incomplete. Data gathering is still ongoing. Data at 13/8/2018.

Figure 2. Total number of beaches and surveys by year in the pan-European beach litter database

NB: the total numbers of beaches and surveys for each country and year are available in Annex 5 of this report. The numbers of beaches and surveys performed during 2017 are incomplete. Data gathering is still ongoing. Data at 13/8/2018.

Figure 3. Total number of years with data for each country in the pan-European beach litter database

NB: the numbers of beaches and surveys performed during 2017 are incomplete. Data gathering is still ongoing. Data at 13/8/2018.

Figure 4. Range of years with data (in dark blue) and without data (in grey) for each country in the pan-European beach litter database

NB: the numbers of beaches and surveys performed during 2017 (in light blue) are incomplete. Data gathering is still ongoing. Data at 13/8/2018.

Figure 5. Spatial distribution of surveyed beaches in the pan-European beach litter database

NB: the online version is available at http://ec.oceanbrowser.net/emodnet/.

2.2  Challenges of and hindrances to data assembly

During the processing of datasets provided by Member States to the JRC for baseline processing, several hindrances were noticed and partially solved. These obstacles can be classified in two groups:

• Basic group: processing was made more difficult and time-consuming (e.g. the use of mother language, a different geographic coordinate system, several types of data template for beach litter reporting).

• Complex group: it hindered the ingestion process or made it impossible to compare survey results (e.g. different ways of reporting litter information depending on the item, missing survey length data or missing coordinates of the start/end of the transect, missing codes for the items reported, the number of items reported per survey or as a sum or average of sections, an undefined number of items, missing surveys for some seasons).

In general, data originator details are missing in most cases. Only 7 out of 22 European countries provided information on the source of data (originator), which is essential to clarify doubts or address inconsistencies in data.

For example, a direct dialogue with the originators of the Baltic data allowed understanding that some Baltic MSs follow an adapted UNEP protocol for the Baltic Sea (MARLIN, 2013). In this protocol (¹⁶) three different lengths are surveyed depending on the item type (e.g. cigarette butts) and size (> 50 cm or < 50 cm). This means that items can be reported over a different length basis, or data are recalculated to the unit ‘number of litter items per 100 m’. Major errors in future outputs can occur if there is no clear information about how quantities are reported: count, density or both (depending on the type of item).

According to data management rules followed by EMODnet Chemistry, inclusion of the data originator is mandatory (for acknowledgements, negotiations and clarifications) and it is strongly suggested that this information be integrated for all records in the future.

In addition, for some countries, survey length, survey width, survey protocol and survey coordinates were not always provided. The values of these data have been inferred from the protocol each country was supposed to follow (e.g. MSFD, OSPAR or UNEP/MARLINarlin protocols). If these assumptions are wrong, data outputs will be erroneous.

As the EMODnet Chemistry beach litter data format is derived from the OSPAR protocol, beach width was not considered in the template. In order to harmonise data in terms of quantities or densities, it may be useful to include beach width information.

Reference beaches as identified for the MSFD beach litter monitoring and type of activity (e.g. monitoring or clean-up event) were in some cases not classified because of the lack of this information.

It is important to clarify the definitions of ‘monitoring’ and ‘clean-up’. In agreement with the TG Litter and in support of the MSFD implementation, a monitoring event under the MSFD is a survey that should be done in comparison with the baseline values. However, the baselines have not yet been established, while beach-monitoring programmes have been already put in place. On the other hand, a clean-up event is an informal citizen engagement activity to collect litter from the beaches, raising awareness and recording data on litter.

According to European Environment Agency (EEA) Marine LitterWatch (¹⁷), monitoring events have to follow the MSFD monitoring protocol for beach litter. Monitoring events need to happen on a regular basis and take place at the same location on the beach. Given this, they require a community structure and set-up that will ensure proper quality assurance of the data. However, clean-up events may be ad hoc or periodic. The data generated through clean-ups will probably support assessments of the state of European coasts and seas, including those prepared by the EEA.

When the information about monitoring activities is missing in the original dataset, the repeat survey at the same beach has been considered and tagged as monitoring in the pan-European database.

Different lists of categories of litter items with different item codes have been used by MSs during the surveys (e.g. OSPAR, UNEP/MAP and Master List). Although a ‘Master List of all litter items for use in litter monitoring programme in the European marine environment is being produced on the basis of the comparison of lists, the structure and elaboration of the list is an ongoing process’ (MSFD Technical Subgroup on Marine Litter, 2013, p. 112). For this reason, the pan-European database includes the original code and name of litter items provided by Member States and the name and code of litter categories automatically converted in the TG Litter Master List.

As the comparison and conversion of litter item codes from one list to another is not always a 1:1 correspondence (Figure 6) (¹⁸), this information has been included in the Note column. This column has been used to register all the relevant comments related to the items.

Figure 6. Extract from comparative table of OSPAR, UNEP/MAP, TG Litter Master lists of item categories

Not found/not surveyed items: in the Member States’ datasets, missing items are either ‘not recorded’ at all (i.e. only found items are reported) or identified with ‘zero’ or ‘null’ (i.e. empty cells) values. In the pan-European beach litter database, data have been saved as originally reported by the data provider. However, there is no clear indication of the meaning of and difference between zero, null and not recorded values. No protocol or further clarification guarantees that ‘zero’ means surveyed but not found. In fact, surveys could be carried out by going to the beach and looking for all types of litter, meaning there are no ‘unsurveyed’ items but only different ways of expressing what has/has not been observed. If a survey has all the values equal to ‘null’, the survey is recorded but with the column ‘litter presence’ equal to ‘no’.

The inconsistencies due to the characteristics of different datasets (¹⁹) should be resolved and a decision on how to proceed in this regard should be taken.

2.3  European beach litter database

The pan-European beach litter database is a relational database with spatial features management, based on PostgresSQL and PostGIS. The data model has been designed to support the EMODnet Chemistry beach format, which allows the processing of datasets based on different protocols and reference systems. During the development phase of both the format and the database, the content of a variety of datasets in a range of formats was analysed. This was made in order to identify the key information and common aspects among the different methodologies with the objective of creating a database where the information is both classifiable and comparable.

The final structure of the database resembles the organisation of the EMODnet Chemistry beach litter template (⁹). The main table is ‘surveys’ and is linked to the parent table ‘beaches’. These two tables contain the information necessary to identify the beach, the survey transect and the surveying conditions. Litter information is stored in the ‘items’ table, while information about any animals found is stored in the ‘animals’ table. The rest of the tables contain the metadata and supporting information about reference lists, interrelations between tables and import records. In total, the database comprises 37 tables (the number of tables per heading is indicated in brackets):

• Beaches (2): beach ID, beach name, position, country and other metadata (beach geography, major usage, cleaning details, etc.) (Figure 7).

• Surveys (5): beach, survey ID, date, position, surveyor and other metadata (town, food outlets, harbours, etc.) (Figure 8).

• Animals (1): survey ID, animal description and retrieve conditions (Figure 9).

• Items (1): survey ID, original name given, quantity, list or lists used, litter code (Figure 10).

• Reference lists (14): item description, codes, relationship between lists (Figure 11).

• Accessory vocabularies and lists (13): referenced in the EMODnet Chemistry beach litter format (Figure 12).

• Import log (1): record of data importation into the database (Figure 13).

Figure 7. Beaches tables in the pan-European beach litter database

Figure 8. Survey tables in the pan-European beach litter database

Figure 9. Animals table in the pan-European beach litter database

Figure 10. Item table

Figure 11. Reference lists tables in the pan-European beach litter database

Figure 12. Accessory vocabularies and lists tables in the pan-European beach litter database

Figure 13. Import log table in the pan-European beach litter database

The aim of the database structure was to incorporate all the relevant and available datasets collected by Member States, to group all the information, to define what is available and the state of the art (protocols, standards, language used), to highlight gaps and hindrances, and to start, where possible, a comparison of the beach litter situation around all surveyed European beaches. Currently, 518 beaches and 4 772 surveys from 29 countries (including from a number of non-EU MSs) are included in the pan-European beach litter database.

The database was populated in several steps. A first group of datasets (from 15 countries) were collated by the JRC and then shared with EMODnet Chemistry for incorporation into the database. OSPAR data (from 13 countries) were directly downloaded by the available services and in contact with the Marine Conservation Society. Finally, another set of data (from six countries) was collected by the EMODnet Chemistry partners in direct contact with data originators.

Despite the main effort of gathering and compiling data being made to support the marine litter baseline process (i.e. the application of different scenarios on the dataset, the setting of baseline values as a reference for trend analysis), type and scale of the data are the important elements to consider in the baseline discussion. In particular, the data availability, quality, and accessibility, as well as temporal and spatial/geographical scale are the key drivers of the derived marine litter baseline.

While an international (i.e. Europe and beyond) database of marine litter, as outlined in this report, is a very useful resource to understand marine pollution in depth and tackle it, only a subset of the beach litter database that is approved by MSs will be used for deriving the baseline scenario testing at the European scale.

Not all of the beach litter data in the pan-European beach litter database have been acquired through MS-driven official monitoring activities: some have been acquired through other initiatives (e.g. ‘citizen science’ activities or clean-up events). As the definition of baselines is a process driven by MSs under the MSFD implementation procedure, an approved and fit for purpose database is essential for the baseline process. Therefore, a subset of the pan-European beach litter database should be created ad hoc for the marine litter baseline study. This should lead to an agreement within the TG Litter on the datasets that are needed to compose the baseline database and are to be used for the baseline scenario testing exercise.

3  Outlook and conclusion

This report aims to define the best possible data management strategy, based on the lessons learned from previous research, and to identify the most valuable methodology for delivering a proposal for a single database able to handle marine litter data from beaches both at the European scale and beyond (i.e. pan-European beach litter database) in order to support policy actions.

Available information and procedures for deriving the beach database show considerable lessons learned, challenges and hindrances (e.g. see Section 2). Nevertheless, the marine litter database reveals consistent and dynamic management of litter categories and types across Europe, providing valuable information that can be applied to other parameters of marine litter and enhances influence on data-driven decisions at different policy levels, in particular at EU level.

3.1  Contribution to further harmonisation

The creation of the pan-European database and data portal is an essential prerequisite for providing easy access to data and data products. In addition to setting the basis for other marine litter datasets, the database structure will directly influence the development of baselines, the setting of thresholds and the enhancement of monitoring guidance and litter category lists.

Indeed, the technicalities of data acquisition in terms of monitoring methods need to be further improved and harmonised in order to avoid the loss of existing data from any contributing country. The data collection process was rather challenging because of the different data sources (regional, NGOs, national, etc.), different survey approaches and different data formats. The outcomes of this report will be considered in the upcoming revision process of guidance on the monitoring of marine litter.

A further important point is the identification of items in the litter category list. The Master List needs to be further improved and reorganised, in a hierarchical and pragmatic structure, and single-use- and risk-based assessments should be included in the classification. The shortcomings faced in this report related to item classification have led to an improvement of the upcoming revision of the master list of categories of litter items (18¹⁸).

Finally, data availability, quality and accessibility, as well as the temporal and spatial scale are important elements that have to be considered in the baseline discussion. Only a long-term, large spatial scale, standard and harmonised data acquisition process can provide litter trend data that enable reasonable policy decisions for medium- and long-term strategies. The traceability of the data and quality control of the metadata will be key in the process for setting baseline and threshold values. The further work will then include the selection of items and item groups, spatial aggregation scales and types of scenarios, which are based on the final approved database of marine litter. An important note: while data collation is being finalised in a pan-European database of marine litter, including all the data available for beach litter, the selection of the sub-dataset that has to be used in the next baseline scenario analysis needs to be authorised by Member States.

3.2  Input to European policies

While data collection has been initiated in order to derive a Europe-wide comparable dataset for the establishing of baseline values in the context of the MSFD, the exercise also provides process-related information. The EU Plastics Strategy and related legislative tools depend on datasets for the identification of priority litter items and the verification of the successful implementation of measures. Policy depends on sound scientific information and on fit for purpose data that allow decisions to be made based on facts.

In close collaboration with the Regional Sea Conventions, such a data compilation exercise can provide a means for further harmonisation beyond Europe, as there is an obvious interest in providing comparable litter data in shared marine basins. Many litter issues are cross-border, so datasets that allow the evaluation of long-range litter transport and of sources are needed. This links to EU activities in neighbourhood policy and to collaboration with associated and other neighbouring countries. In addition, EU activities on the global scale, e.g. supporting UN Sustainable Development Goal (SDG) 14, are related, as monitoring approaches and database structures can also be used on a larger spatial scale.

3.3  Conclusion

An extensive effort has been made in data gathering and compilation of beach litter data, because of the incompatibility of data formats. The main bottlenecks observed during the data aggregation were spatial-temporal heterogeneity, inconsistencies in the different litter identification lists, and variability in the survey protocols, data sources (e.g. regional, NGOs, national), etc. The key to overcoming all of these challenges and moving towards effective and confirmed marine litter reduction is close collaboration at different technical and policy levels, endorsing European standards at an interdisciplinary scale.

While harmonisation and comparability of results across Europe are needed for the implementation of the MSFD, and to support the EU Plastics Strategy and waste legislation, it should be noted that there is increasing interest in global comparability of monitoring results that will enable prioritisation at a larger scale.

A global partnership on marine litter has been launched to prevent and reduce marine litter in order to preserve human health and the marine ecosystem, and to mitigate the economic cost and impact of marine litter. An international action plan on marine litter has been recognised as an urgent need by the G7, the G20 and UN SDG 14, and a strong commitment to take action towards a resource-efficient life-cycle management approach to plastics has recently been signed (²).

The European Union is fully engaged in these international action plans against plastic litter, and the pan-European database outlined in this report has an active role in contributing to global efforts to tackle marine litter.

References

Cheshire, A., Adler, E., Barbière, J., Cohen, Y., Evans, S., Jarayabhand, S., Jeftic, L., Jung, R. T., Kinsey, S., Kusui, E. T., Lavine, I., Manyara, P., Oosterbaan, L., Pereira, M. A., Sheavly, S., Tkalin, A., Varadarajan, S., Wenneker, B. and Westphalen, G., UNEP/IOC Guidelines on survey and monitoring of marine litter, UNEP Regional Seas Reports and Studies, No 186; IOC Technical Series No 83, 2009.

DG ENV and DG GROW, Roadmap Strategy on Plastics in a Circular Economy (Vol. 1), 2017. Retrieved from http://ec.europa.eu/environment/circular-economy/index_en.htm%0Ahttp://ec.europa.eu/environment/waste/plastic_waste.htm.

European Commission, Commission Decision of 1 September 2010 on criteria and methodological standards on good environmental status of marine waters (2010/477/EU), 11, 2010.

European Commission, Commission Decision (EU) 2017/848 of 17 May 2017 laying down criteria and methodological standards on good environmental status of marine waters and specifications and standardised methods for monitoring and assessment, and repealing Decision 2010/477/EU, Official Journal of the European Union, 2017, 43-74. 2017a.

European Commission, COM(2017) (33). Report from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions on the implementation of the circular economy action plan, Official Journal of the European Union, 1-14, 2017b.

European Commission, COM/2018/028. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions: A European strategy for plastics in a circular economy, Official Journal of the European Union, 2018.

European Commission, Towards a European integrated coastal zone management (ICZM) strategy: General principles and policy options, Office for Official Publications of the European Communities, Luxembourg, 1999.

European Parliament and Council of the European Union, Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (Marine Strategy Framework Directive), Official Journal of the European Union, 164, 19-40, 2008.

Galgani, F., Giorgetti, A., Le Moigne, M., Brosich, A., Vinci, M., Lipizer, M., Molina, E., Holdsworth, N., Schlitzer, R., Hanke, G., Moncoiffe, G., Schaap, D., Giorgi, G., Addamo, A. M., Chaves Montero, M. d. M., Guidelines and forms for gathering marine litter data. 2018. doi:10.6092/15c0d34c-a01a-4091-91ac-7c4f561ab508.

McKenna, J., MacLeod, M. J., Power, J. and Cooper, A., Rural beach management: A good practice guide, Donegal County Council, Lifford, 2000.

Marlin, Final report of Baltic marine litter project MARLIN: Litter monitoring and raising awareness 2011-2013, 2013.

MSFD GES Technical Subgroup on Marine Litter, Guidance on monitoring of marine litter in European seas,. EUR26113, Publications Office of the European Union, Luxembourg, 2013 doi:10.2788/99475.

Pauly, D., ‘Anecdotes and the shifting baseline syndrome of fisheries’, TREE, Vol 10 No 10, Oxford, 1995, p. 430.

Schulz, M., van Loon, W., Fleet, D. M., Baggelaar, P., and van der Meulen, E., ‘OSPAR standard method and software for statistical analysis of beach litter data’, Marine Pollution Bulletin, Vol. 122 No 1-2, 2017, pp. 166-175. https://doi.org/10.1016/j.marpolbul.2017.06.045.

Shelford, V. E., ‘Some concepts of bioecology’, Ecology, Vol 12, 1931, pp. 455-467.

Van Acoleyen, M., Laureysens, I., Stijn, L., Raport, L., Van Sluis, C., Kater, B., van Onselen, E., Veiga, J. and Ferreira, M., ARCADIS final report marine litter study to support the establishment of an initial quantitative headline reduction target, SFRA0025, European Commission DG Environment Project number BE0113.000668, 2013.

Veiga, J. M., Fleet, D., Kinsey, S., Nilsson, P., Vlachogianni, T., Werner, S., Galgani, F., Thompson, R. C., Dagevos, J., Gago, J., Sobral, P. and Cronin, R., Identifying sources of marine litter, MSFD GES Technical Group on Marine Litter Thematic Report; JRC technical report; EUR28309, Publications Office of the European Union, Luxembourg, 2016. https://doi.org/10.2788/018068.

Vinci, M., Giorgetti, A., Molina Jack, M. E., Brosich, A., Chaves Montero, M. d. M., Addamo, A. M., Hanke, G. and Galgani, F., ‘Enlarging the EMODnet Chemistry focus with the EU marine litter data challenge’, Bollettino di Geofisica Teorica ed Applicata, Vol. 59 (supplement 1), pp. 291-292, 2018.

Werner, S., Budziak, A., Van Fanneker, J. A., Galgani, F., Hanke, G., Maes, T., Matiddi, M. Nilsson, P., Oosterbaan, L., Priestland, E., Thompson, R., Veiga, J. and Vlachogianni, T., Harm caused by marine litter, MSFD GES Technical Group on Marine Litter — thematic report; JRC technical report; EUR28317 EN, Publications Office of the European Union, Luxembourg, 2016. https://doi.org/10.2788/690366.

Boxes

Box 1. Marine Strategy Framework Directive

Box 2. EU Plastics Strategy

Box 3. Different baseline concepts

Figures

Figure 1. Example of standard terms and indexes used for International Standard Organisation Countries (e.g. microlitter types)

Figure 2. Total number of beaches and surveys by year in the pan-European beach litter database

Figure 4. Range of years with data (in dark blue) and without data (in grey) for each country in the pan-European beach litter database

Figure 5. Spatial distribution of surveyed beaches in the pan-European beach litter database

Figure 7. Beaches tables in the pan-European beach litter database

Figure 8. Survey tables in the pan-European beach litter database

Figure 9. Animals table in the pan-European beach litter database

Figure 10. Item table

Figure 11. Reference lists tables in the pan-European beach litter database

Figure 12. Accessory vocabularies and lists tables in the pan-European beach litter database

Figure 13. Import log table in the pan-European beach litter database

Tables

Table 1. Number of beaches and surveys in the pan-European beach litter database

List of footnotes

(¹) Further information can be found on the website of the JRC MSFD Competence Centre: http://mcc.jrc.ec.europa.eu/dev.py?N=41&O=434&titre_chap=TG %20Marine %20Litter.

(²) UNEP — Sustainable Development Goals SDG 14. See https://sustainabledevelopment.un.org/sdg14 and http://www.unenvironment.org/explore-topics/oceans-seas/what-we-do/addressing-land-based-pollution/global-partnership-marine;

G7, Canada 2018 — Charlevoix blueprint for healthy oceans, seas and resilient coastal communities. See https://g7.gc.ca/en/official-documents/charlevoix-blueprint-healthy-oceans-seas-resilient-coastal-communities/#a1

G20, Germany 2017 — Marine Litter Action Plan. See https://www.g20germany.de/Content/DE/_Anlagen/G7_G20/2017-g20-marine-litter-en___blob=publicationFile&v=4.pdf

(³) EU Plastic Strategy. See http://ec.europa.eu/environment/circular-economy/pdf/plastics-strategy-brochure.pdf

EU Waste Legislation. See http://ec.europa.eu/environment/waste/legislation/a.htm

(⁴) See http://www.emodnet-chemistry.eu/data.

(⁵) A common definition of baseline and scenario testing was agreed in the TG Litter Marine Litter Baselines workshop, 14-15 March 2017, Brussels (Belgium).

(⁶) See further information at http://inspire.ec.europa.eu/data-specifications/2892

(⁷) Guidance and template for gathering marine litter data have been developed in 2018 and are available in http://www.emodnet-chemistry.eu/documents/projectdocuments.

(⁸) See further information at EMODnet Chemistry website, section DATA http://www.emodnet-chemistry.eu/data.

(⁹) EMODnet Chemistry Beach litter format template is available in Annexes 1-4 of this report and online at the EMODnet Chemistry website, section DOCUMENTS http://www.emodnet-chemistry.eu/doi/documents/Guidelines-Litter_Data_EMODnetChemistry3_rev_20180731.pdf.

(¹⁰) ‘Ideally, the selected sites should represent litter abundance and composition for a given region. Not any given coastal site may be appropriate, as they may be limited in terms of accessibility, suitability to sampling (sand or rocks/boulders) and beach cleaning activities’ (MSFD GES Technical Subgroup on Marine Litter, 2013)

(¹¹) See further information at https://www.seadatanet.org/ and https://www.bodc.ac.uk.

(¹²) Important NB: The TG Litter Master List, published in 2013 as part of guidance for the monitoring of marine litter, is being further developed. Additional information is being gathered for the ongoing revision of the TG Litter Master List. A process for the inclusion of newly found items and thus the mechanism for updating of the TG Litter Master List also needs to be set up.

(¹³) For example, beaches classified as rural, urban and peri-urban in the beach litter template refer to the following degrees of urbanisation: a) rural is a thinly populated area, a contiguous set of local areas belonging neither to a densely populated area nor to an intermediate area; b) urban is a densely populated area, a contiguous set of local areas, each of which has a population density > 500 inhabitants per square kilometre, where the total population for the set is at least 50 000 inhabitants; c) peri-urban is an intermediate area, a contiguous set of local areas, not belonging to a densely populated area, each of which has a population density > 100 inhabitants per square kilometre, and either with a total population for the set of at least 50 000 inhabitants or adjacent to a densely populated area. For further information, see European Commission (1999); McKenna et al. (2010).

(¹⁴) See http://www.emodnet-chemistry.eu/lists/beach

(¹⁵) NB: the numbers of beaches and surveys performed during 2017 are incomplete. Data gathering is still ongoing.

(¹⁶) See note in Annex 6 of this report. Further information is available in https://www.hsr.se/sites/default/files/appendix1_measurement_method.pdf.

(¹⁷) See https://www.eea.europa.eu/themes/water/europes-seas-and-coasts/thematic-assessments/marine-litterwatch/get-started/how

(¹⁸) A list of non-compatibilities of litter categories and further suggestions can be found in Annex 6 of this report.

(¹⁹) A list of detailed hindrances by country can be found in Annex 7 of this report.

Annexes

Annex 1. EMODnet Chemistry Beach Format Template — Beach Metadata

| Field | Description | Admitted values | Multiple values | Mandatory | Data type | Example
General Info | BeachCode | Code for the beach. In case you don’t have a code, it has to be created with the country code and a number code (6 digits) | alphanumeric sequences + “/” (slash), “-” (hyphen), “_” (underscore) | no | yes | character | FR0006
BeachName | Name of the beach |  | no | yes | character | Sein
Country | Identifier for the country that performed the survey from ISO countries reference code list | http://vocab.nerc.ac.uk/collection/C32/current/ | no | yes | character | FR
BeachlnfoAmendment | Is this an amendment to an existing beach info questionnaire? | {yes, no} | no | yes | boolean | no
FillingDate | Date when the questionnaire was filled in. Date format ISO 8601 (YYYY-MM-DD) |  | no | yes | date | 41065
FillingName | Name of the person who filled the questionnaire |  | no | no | character | Helen Smith
FillingPhone | Phone number of the person who filled the questionnaire |  | no | no | character | 331-705-960
FillingMail | E-mail of the person who filled the questionnaire |  | no | no | character | h.smith@gmail.com
FillingInstitute | Institution in charge of filling the questionnaire |  | no | no | character | Cedre
UrbanizationDegree | Degree of urbanization of the beach area (Urban: Densely populated area, 500 inhabitants/km2 and total population at least 50,000 inhabitants. Periurban: Intermediate area,100 inhabitants/km2 and at least 50,000 inhabitants or adjacent to a densely-populated area. Rural: Thinly-populated area) | {Rural, Urban, Periurban}¹ | no | no | enum | Rural
ReferenceBeach | Indicate if the beach is considered a sampling unit within any litter survey programme | {yes, no} | no | no | boolean | yes
Beach geography | BeachWidthLow | Beach width in metres at mean low spring tide |  | no | no | integer | 450
BeachWidthHigh | Beach width in metres at mean high spring tide |  | no | no | integer | 10
BeachLength | Total length of the beach in metres |  | no | no | integer | 500
BeachLatitude | Latitude of the beach position (Degree.Decimal Degree of latitude) | [-90.0, +90.0] | no | no | decimal | 48.039
BeachLongitude | Longitude of the beach position (Degree.Decimal Degree of latitude) | [-180.0, +180.0] | no | no | decimal | -4.85
CoordinateSystem | Coordinate reference system used: if not differently specified WGS84 (EPSG:4326) reference system is assumed. Please specify the “Identifier” | http://vocab.nerc.ac.uk/collection/L10/current/ | no | no | integer | 4326
BeachBack | Elements on the back of the beach | {Cliffs, Dunes, Rocks, Forest, Bush, Crops, Fields, BuiltupArea, Road, Other}¹ | yes | no | enum | Dunes
BeachBackOther | If the back beach category cannot be selected from the dropdown list (“BeachBack” field) it should be listed here. |  | yes | no | character | Promenade
BeachBackDevelopment | Is there any development behind the beach? | {yes, no} | no | no | boolean | No
DevelopmentDescription | Description of the development behind the beach |  | no | no | character |
PositionMeasurementDate | Date when the position of the beach was measured. Date format ISO 8601 (YYYY-MM-DD) |  | no | no | date | 41974
CurrentsDirection | Prevailing currents off the beach | {N, NE, E, SE, S, SW, W, NW}¹ | yes | no | enum | W
WindsDirection | Prevailing winds | {N, NE, E, SE, S, SW, W, NW}¹ | yes | no | enum | SW
BeachOrientation | In which direction the beach is facing when looking from the beach to the sea? | {N, NE, E, SE, S, SW, W, NW}¹ | no | no | enum | SW
BeachMaterial | Define beach sediment as in EMODnet Geology five class sediment categorization (Modified from Folk Triangle) | {MudToSandyMud, Sand, CoarseSediment, MixedSediment, RockAndBoulders}¹ | no | no | character | CoarseSediment
BeachTopography | Short description of the beach topography |  | no | no | character | slope 20%
Obstacles | Objects in the sea that influence the currents |  | yes | no | character | pier; reef
Major usage and access | Usage1 | Usage of the beach |  | no | no | character | Coastal walking
Usage1Seasonality | Is the usage seasonal? | {yes, no} | no | no | boolean | yes
Usage2 | Usage of the beach |  | no | no | character | Wildlife watching
Usage2Seasonality | Is the usage seasonal? | {yes, no} | no | no | boolean | no
Usage3 | Usage of the beach |  | no | no | character |
Usage3Seasonality | Is the usage seasonal? | {yes, no} | no | no | boolean |
BeachAccess | Possibilities of access to the beach | {Boat, Pedestrian, Vehicle}¹ | yes | no | enum | Vehicle; Pedestrian
Beach Cleaning | BeachCleaningSeasonality | Is the beach cleaning sesonal? | {yes, no} | no | no | boolean | no
SeasonalityMonths | List the number of the months in which the cleaning is accomplished | [1,12] | yes | no | integer | 2; 5; 8; 11
CleaningFrequency | Indicate the frequency of beach cleaning | {Daily, Weekly, Monthly, Other}¹ | no | no | enum | Other
OtherDescription | If frequency is “Other”, please describe it |  | no | no | character | 4 times/year
CleaningMethod | Used cleaning method | {Manual, Mechanical}¹ | no | no | enum | Manual
CleaningResponsible | Responsible for cleaning |  | no | no | character | Natural marine Parc of Iroise - PNMI (Parc naturel marin d'Iroise) agents, also in charge of the OSPAR survey
Other | Notes | Additional comments and observations about the beach |  | no | no | character |

NB:

¹ The updated lists of admitted values are in http://www.emodnet-chemistry.eu/lists/beach

— If data type is enum the unique admitted values for the field are listed in the field ‘admitted values’

— If data type is boolean only yes or no is admitted

— When multiple values are admitted, use ‘;’ (semicolon) to separate the different values

— Decimal numbers must be expressed with ‘.’ (dot) to separate the integer part from de decimal part

Annex 2. EMODnet Chemistry Beach Format Template — Survey Metadata

| Field | Description | Admitted values | Multiple values | Mandatory | Data type | Example
General info | BeachCode | Code for the beach referring Beach_metadata sheet. In case you don’t have a code, it has to be created with the country code and a number code (6 digits) | alphanumeric sequences + “/” (slash), “-” (hyphen), “_” (underscore) | no | yes | character | FR0006
SurveyCode | Number code that must be unique in the whole file |  | no | yes | integer | 1
SurveyType | Type of survey | {Cleaning, Monitoring}² | no | yes | enum | Monitoring
SurveyDate | Date of the survey. Date format ISO 8601 (YYYY-MM-DD) |  | no | yes | date | 2015-01-19
Originator | EDMO code for data originator organization | http://seadatanet.maris2.nl/v_edmo/welcome.a | no | yes | integer | 1887
Collator | EDMO code for data collator organization | http://seadatanet.maris2.nl/v_edmo/welcome.a | no | yes | integer | 2688
ProjectCode | Project code from EDMERP (European Directory of Marine Environmental Research Projects) | http://seadatanet.maris2.nl/v_edmerp/browse.asp | no | no | integer | 12038
SurveyStartLatitude | Latitude of the survey starting point (Degree.Decimal Degree of latitude) | [-90.0, +90.0] | no | yes¹ | decimal |
SurveyStartLongitude | Longitude of the survey starting point (Degree.Decimal Degree of latitude) | [-180.0, +180.0] | no | yes¹ | decimal |
SurveyEndLatitude | Latitude of the survey ending point (Degree.Decimal Degree of latitude) | [-90.0, +90.0] | no | yes¹ | decimal |
SurveyEndLongitude | Longitude of the survey ending point (Degree.Decimal Degree of latitude) | [-180.0, +180.0] | no | yes¹ | decimal |
CoordinateSystem | Coordinate reference system used: if not differently specified WGS84 (EPSG:4326) reference system is assumed. Please specify the “Identifier” | http://vocab.nerc.ac.uk/collection/L10/current/ | no | yes¹ | integer | 4326
SurveyLength | Length of the survey in metres |  | no | yes¹ | integer | 100
SurveyWidth | Width of the survey in metres |  | no | no | integer | 10
Surveyor1Name | Name of the surveyor 1 |  | no | no | character |
Surveyor1Phone | Phone number of the surveyor 1 |  | no | no | character |
Surveyor1Mail | E-mail of the surveyor 1 |  | no | no | character |
Surveyor2Name | Name of the surveyor 2 |  | no | no | character |
Surveyor2Phone | Phone number of the surveyor 2 |  | no | no | character |
Surveyor2Mail | E-mail of the surveyor 2 |  | no | no | character |
Nearest town/development/outlets/line/harbour/river | TownName | Name of the nearest town |  | no | no | character | Sein
TownDistance | Distance to the nearest town in kilometres |  | no | no | decimal | 0.3
TownPosition | Position of the town in relation to survey area | {N, NE, E, SE, S, SW, W, NW}² | no | no | enum | SE
TownPopulation | Residential population of the nearest town |  | no | no | integer | 200
WinterTourists | Number of tourists during winter |  | no | no | integer |
SpringTourists | Number of tourists during spring |  | no | no | integer | 150
SummerTourists | Number of tourists during summer |  | no | no | integer |
AutumnTourists | Number of tourists during autumn |  | no | no | integer |
FoodOutlets | Are there food and/or drink outlets on the beach? | {yes, no} | no | no | boolean | no
FoodOutletsDistance | Distance of the nearest food/drink outlet in kilometres in relation to survey area |  | no | no | decimal | 0.05
FoodOutletsSeasonality | Is the opening seasonal? | {yes, no} | no | no | boolean | yes
SeasonalityMonths | List the number of the months in which the outlets are present | [1,12] | yes | no | integer | 6;7;8
FoodOutletsPosition | Position of the nearest food outlet in relation to survey area | {N, NE, E, SE, S, SW, W, NW}² | no | no | enum | N
ShippingLaneDistance | Distance from the beach to the nearest shipping lane in kilometres |  | no | no | decimal | 30.0
ShippingLaneTraffic | Estimated traffic of the shipping lane (number of ships/year) |  | no | no | integer | 450
ShippingLaneTypes | Type of ships that navigate along this lane | {Passengers, Merchant, Fishing, Military, Recreational, Other, AllKinds}² | yes | no | enum | Merchant; Passengers
ShippingLanePosition | Position of the nearest shipping lane in relation to survey area | {N, NE, E, SE, S, SW, W, NW}² | no | no | enum | E
HarbourName | Name of the nearest harbour |  | no | no | character |
HarbourDistance | Distance from the beach to the nearest harbour in kilometres |  | no | no | decimal | 50.0
HarbourPosition | Position of harbour in relation to survey area | {N, NE, E, SE, S, SW, W, NW}² | no | no | enum | N
HarbourType | Type of Harbour | {Passengers, Merchant, Fishing, Military, Recreational, Other, AllKinds}² | yes | no | enum | Fishing
HarbourSize | Total number of ships |  | no | no | integer | 100
RiverName | Name of the nearest river |  | no | no | character | Le Goyen
RiverDistance | Distance from the beach to the nearest river mouth in kilometres |  | no | no | decimal | 30.0
RiverPosition | Position of river mouth in relation to survey area | {N, NE, E, SE, S, SW, W, NW}² | no | no | enum | E
WasteWaterDischarges | Is the beach located near waste water discharges? | {yes, no} | no | no | boolean | no
WasteWaterDistance | Distance from the beach to the nearest discharge point in kilometres |  | no | no | decimal | 3.0
WasteWaterPosition | Position of the nearest discharge point in relation to survey area | {N, NE, E, SE, S, SW, W, NW}² | no | no | enum | N
Additional Info | LitterPresence | Was litter collected during this survey? | {yes, no} | no | no | boolean | yes
LastCleaning | When was the beach last cleaned. Date format ISO 8601 (YYYY-MM-DD) |  | no | no | date | 41963
WeatherConditions | Did any weather conditions affect the data of the surveys? | {Wind, Rain, Snow, Ice, Fog, SandStorm, ExceptionallyHighTide, Other}² | yes | no | enum | Rain
WeatherConditionsOther | If any other weather conditions affected the survey, describe it |  | yes | no | character |
AnimalsFound | Did you find stranded or dead animals? | {yes, no} | no | no | boolean | yes
AnimalsNumber | If so, how many |  | no | no | integer | 2
SurveyCircumstances | Any circumstances influencing the survey (e.g. tracks on the beach…) |  | no | no | character |
SpecialEvents | Events that lead to unusual types and/or amounts of litter on the beach |  | no | no | character | New Year Eve party
Notes | Additional comments and observations about the survey |  | no | no | character |

NB:

¹ Either survey coordinates or survey length must be filled

² The updated lists of admitted values are available in http://www.emodnet-chemistry.eu/lists/beach

Annex 3. EMODnet Chemistry Beach Format Template — Litter Data

| Field | Description | Admitted values | Multiple values | Mandatory | Data type | Example
| SurveyCode | Number code referring Survey_metadata sheet that must be unique in the whole file |  | no | yes | integer | 1
| LitterReferenceList | Name of the Litter reference list used. It is strongly recommended the use of TSG_MLGeneral_code | {UNEP, OSPAR, C_TS_REV, RECO_LT, TSG_ML, UNEP_MARLIN, OSPAR_1000}¹ | no | yes | enum | TSG_ML
| ItemCode | Litter parameter code of the Litter Reference list used | Codes from the used list | no | yes | character | G1
| ItemName | Litter parameter name of the Litter Reference list used | Names for the list used | no | no | character | 4/6-pack yokes, six-pack rings
| ParameterOriginalName | Litter parameter name as reported by the surveyor (can be also in national original language) |  | no | no | character | 4/6-pack yokes
| NoItems | Number of items;for “other Pollutants” frequency (estimated number/m ); for Pellets (Y/N) |  | no | yes | integer/decimal/boolean | 4
| Notes | Special observations |  | no | no | character |

NB:

¹ The updated lists of admitted values are available in http://www.emodnet-chemistry.eu/lists/beach

Annex 4. EMODnet Chemistry Beach Format Template — Animals

| Field | Description | Admitted values | Multiple values | Mandatory | Data type | Example
| SurveyCode | Number code referring Survey_meta data sheet that must be unique in the whole file |  | no | yes | integer | 1
| Animal | Please describe the animal, or note the species name if known |  | no | yes | character | seagull
| State | Is it alive or dead? | {Alive, Dead}¹ | no | no | enum | Dead
| Sex | Please specify sex of the animal if known | {Female, Male}¹ | no | no | enum | Female
| Age | Please specify the age of the animal if known |  | no | no | integer |
| Entanglement | Is the animal entangled in litter? | {yes, no} | no | no | boolean | no
| EntanglementNature | If so please describe nature of the entanglement and type of litter |  | no | no | character |

NB:

¹ The updated lists of admitted values are available in http://www.emodnet-chemistry.eu/lists/beach

Annex 5. Number of beaches and surveys for each country and year.

Country | Year | Beaches | Surveys
Belgium | 2001 | 2 | 4
Belgium | 2002 | 2 | 8
Belgium | 2003 | 2 | 8
Belgium | 2004 | 2 | 8
Belgium | 2005 | 2 | 6
Belgium | 2006 | 2 | 5
Belgium | 2012 | 2 | 5
Belgium | 2013 | 2 | 7
Belgium | 2014 | 2 | 7
Belgium | 2015 | 2 | 9
Belgium | 2016 | 2 | 8
Bulgaria | 2015 | 8 | 24
Bulgaria | 2016 | 8 | 8
Croatia | 2014 | 4 | 4
Croatia | 2015 | 4 | 12
Cyprus | 2014 | 6 | 6
Cyprus | 2015 | 7 | 8
Cyprus | 2016 | 13 | 15
Denmark | 2001 | 1 | 1
Denmark | 2002 | 1 | 2
Denmark | 2003 | 2 | 3
Denmark | 2004 | 1 | 2
Denmark | 2005 | 1 | 4
Denmark | 2006 | 1 | 4
Denmark | 2011 | 1 | 2
Denmark | 2012 | 1 | 1
Denmark | 2013 | 1 | 2
Denmark | 2014 | 1 | 2
Denmark | 2015 | 5 | 15
Denmark | 2016 | 5 | 16
Denmark (Greenland) | 2016 | 16 | 24
Estonia | 2012 | 6 | 18
Estonia | 2013 | 6 | 18
Estonia | 2014 | 10 | 30
Estonia | 2015 | 10 | 30
Estonia | 2016 | 10 | 10
Faroe Islands | 2002 | 1 | 2
Faroe Islands | 2005 | 1 | 1
Faroe Islands | 2006 | 1 | 1
Finland | 2012 | 8 | 22
Finland | 2013 | 8 | 24
Finland | 2014 | 9 | 26
Finland | 2015 | 11 | 29
Finland | 2016 | 11 | 27
Finland | 2017 | 13 | 30
France | 2006 | 4 | 10
France | 2010 | 5 | 14
France | 2011 | 9 | 34
France | 2012 | 10 | 40
France | 2013 | 11 | 40
France | 2014 | 10 | 33
France | 2015 | 11 | 35
France | 2016 | 15 | 62
Georgia | 2015 | 2 | 2
Georgia¹ | 2016 | 1 | 1
Germany | 2002 | 5 | 15
Germany | 2003 | 5 | 14
Germany | 2004 | 4 | 10
Germany | 2005 | 4 | 16
Germany | 2006 | 4 | 15
Germany | 2007 | 4 | 5
Germany | 2008 | 4 | 13
Germany | 2009 | 4 | 14
Germany | 2010 | 4 | 15
Germany | 2011 | 4 | 15
Germany | 2012 | 14 | 48
Germany | 2013 | 27 | 95
Germany | 2014 | 30 | 115
Germany | 2015 | 27 | 103
Germany | 2016 | 26 | 96
Germany | 2017 | 15 | 15
Greece | 2014 | 6 | 6
Greece | 2015 | 6 | 9
Greece | 2016 | 6 | 6
Iceland | 2016 | 5 | 7
Ireland | 2008 | 4 | 8
Ireland | 2009 | 4 | 4
Ireland | 2011 | 4 | 12
Ireland | 2012 | 3 | 3
Ireland | 2013 | 4 | 16
Ireland | 2014 | 4 | 16
Ireland | 2015 | 4 | 16
Ireland | 2016 | 4 | 16
Italy | 2014 | 19 | 19
Italy | 2015 | 28 | 28
Italy | 2016 | 51 | 51
Italy | 2017 | 64 | 64
Latvia | 2012 | 35 | 35
Latvia | 2013 | 38 | 38
Latvia | 2014 | 38 | 38
Latvia | 2015 | 38 | 38
Latvia | 2016 | 38 | 38
Lithuania | 2012 | 4 | 16
Lithuania | 2013 | 4 | 16
Montenegro¹ | 2014 | 2 | 2
Montenegro¹ | 2015 | 2 | 6
Netherlands | 2001 | 4 | 5
Netherlands | 2002 | 4 | 30
Netherlands | 2003 | 4 | 10
Netherlands | 2004 | 4 | 24
Netherlands | 2005 | 4 | 22
Netherlands | 2006 | 4 | 16
Netherlands | 2007 | 4 | 16
Netherlands | 2008 | 4 | 16
Netherlands | 2009 | 4 | 22
Netherlands | 2010 | 4 | 27
Netherlands | 2011 | 4 | 33
Netherlands | 2012 | 4 | 23
Netherlands | 2013 | 4 | 16
Netherlands | 2014 | 4 | 16
Netherlands | 2015 | 4 | 21
Netherlands | 2016 | 4 | 15
Norway¹ | 2011 | 5 | 6
Norway¹ | 2012 | 6 | 9
Norway¹ | 2013 | 5 | 7
Norway¹ | 2014 | 5 | 10
Norway¹ | 2015 | 6 | 8
Norway¹ | 2016 | 6 | 9
Poland | 2015 | 15 | 47
Poland | 2016 | 15 | 64
Poland | 2017 | 9 | 9
Portugal | 2002 | 5 | 8
Portugal | 2003 | 6 | 12
Portugal | 2004 | 5 | 11
Portugal | 2005 | 7 | 22
Portugal | 2006 | 7 | 13
Portugal | 2011 | 1 | 1
Portugal | 2013 | 10 | 29
Portugal | 2014 | 9 | 38
Portugal | 2015 | 9 | 34
Portugal | 2016 | 9 | 37
Romania | 2015 | 3 | 7
Romania | 2016 | 1 | 2
Russian Federation¹ | 2016 | 3 | 3
Russian Federation¹ | 2017 | 2 | 2
Slovenia | 2007 | 3 | 19
Slovenia | 2010 | 3 | 6
Slovenia | 2011 | 3 | 28
Slovenia | 2012 | 5 | 32
Slovenia | 2013 | 5 | 29
Slovenia | 2014 | 3 | 3
Slovenia | 2015 | 3 | 15
Spain | 2001 | 2 | 4
Spain | 2002 | 2 | 8
Spain | 2003 | 2 | 8
Spain | 2004 | 3 | 10
Spain | 2005 | 3 | 10
Spain | 2006 | 2 | 8
Spain | 2007 | 4 | 8
Spain | 2008 | 6 | 24
Spain | 2009 | 6 | 23
Spain | 2010 | 6 | 24
Spain | 2011 | 6 | 24
Spain | 2012 | 2 | 5
Spain | 2013 | 25 | 104
Spain | 2014 | 26 | 107
Spain | 2015 | 26 | 96
Spain | 2016 | 26 | 100
Sweden | 2001 | 5 | 14
Sweden | 2002 | 6 | 14
Sweden | 2003 | 6 | 17
Sweden | 2004 | 5 | 11
Sweden | 2005 | 6 | 18
Sweden | 2006 | 6 | 12
Sweden | 2008 | 3 | 5
Sweden | 2009 | 3 | 5
Sweden | 2010 | 3 | 7
Sweden | 2011 | 6 | 14
Sweden | 2012 | 14 | 42
Sweden | 2013 | 14 | 42
Sweden | 2014 | 16 | 40
Sweden | 2015 | 16 | 45
Sweden | 2016 | 16 | 47
Ukraine¹ | 2017 | 1 | 1
United Kingdom | 2001 | 17 | 44
United Kingdom | 2002 | 19 | 51
United Kingdom | 2003 | 18 | 37
United Kingdom | 2004 | 20 | 57
United Kingdom | 2005 | 21 | 59
United Kingdom | 2006 | 19 | 66
United Kingdom | 2007 | 20 | 68
United Kingdom | 2008 | 16 | 36
United Kingdom | 2009 | 20 | 73
United Kingdom | 2010 | 19 | 62
United Kingdom | 2011 | 19 | 64
United Kingdom | 2012 | 29 | 68
United Kingdom | 2013 | 31 | 140
United Kingdom | 2014 | 31 | 157
United Kingdom | 2015 | 22 | 64
United Kingdom | 2016 | 31 | 116

NB:

¹ No European MS

Number of beaches and surveys performed during 2017 are incomplete, Data gathering is still on going, Data in the table at the date 13-08-2018.

Annex 6. List of non-compatibilities of litter categories and further suggestions.

TG Litter Master List is a complete and useful reference document to convert from one coding to another. Taking the opportunity of the ongoing revision of the Master List, the mapping between the different lists could be improved. Here is the list of suggestions (general and specific comments) for the revision of the Master List from the JRC-EMODnet Chemistry experience gained during the first year of marine litter data management.

General comments:

• There is not always a 1:1 correspondence between lists terms and this brings uncertainty in the conversion from one list to another (e.g. UNEP-PL09 Gloves vs. TG Litter-G39/G40 Gloves & Gloves washing up) and sometimes are mixed categories (e.g. UNEP-RB03 Rubber Gloves vs. TG Litter-G41 Artificial polymer materials) (Fig. A1).

• A unique Master List for all ML, should include all available lists (i.e. MEDITS, ICES etc.). TG Litter general name should be more comprehensive item description and include the item description present in other lists.

• Indication about whether item is a single use item should be considered as an extra column to add in the TG Litter Master List.

• Review the management of the information of litter items in a more useful order (e.g. by alphabetic? by function?) AND/OR flexible way with a set of hierarchic categories. The Master List manages at the same ‘level’ items categories with others that might be considered subcategories (e.g. TG Litter-G2 Bags/-G3 Shopping Bag) (Fig. A2). For further details, see paragraph Specific comments.

• Master List uses coarse microlitter categories that merges the material, type and size of the items. (e.g. TG Litter-G103-G111 Plastic fragments and pellets < 5 mm). A more flexible approach could be used following the example of guidelines for microlitter data management developed in the Chemistry project (Fig. A3).

Figure A1. Example of no 1:1 correspondence among lists of categories of litter items.

Figure A2. Example of hierarchical structure, suggested for the Master List of categories of litter items.

Figure A3. Example of hierarchical structure, suggested for categories of microlitter items.

NB:

- EMODnet Chemistry Guidance for microlitre: http://nodc.ogs.trieste.it/doi/documents/Proposal-EMODnet-TG-ML-Micro-Litter-Data-Gathering-20180221.pdf (from page 24-27.

- Level 1-Litter types:
http://seadatanet.maris2.nl/v_bodc_vocab_v2/browse.asp?order=conceptid&formname=search&screen=0&lib=h01&v0_0=&v1_0=conceptid %2Cpreflabel %2Caltlabel %2Cdefinition %2Cmodified&v2_0=0&v0_1=&v1_1=conceptid&v2_1=3&v0_

- Level 2-Shapes:
http://seadatanet.maris2.nl/v_bodc_vocab_v2/browse.asp?order=conceptid&formname=search&screen=0&lib=h02&v0_0=&v1_0=conceptid%2Cpreflabel%2Caltlabel%2Cdefinition%2Cmodified&v2_0=0&v0_1=&v1_1=conceptid&v2_1=3&v0_2=&v1_2=preflabel&v2_2=3&v0_3=&v1_3=altlabel&v2_3=3&v0_4=&v1_4=modified&v2_4=9&v0_5=&v1_5=modified&v2_5=10&x=8&y=22&v1_6=&v2_6=&v1_7=&v2_7=

- Level 3-Sizes:
http://seadatanet.maris2.nl/v_bodc_vocab_v2/browse.asp?order=conceptid&formname=search&screen=0&lib=h03&v0_0=&v1_0=conceptid %2Cpreflabel %2Caltlabel %2Cdefinition %2Cmodified&v2_0=0&v0_1=&v1_1=conceptid&v2_1=3&v0_2=&v1_2=preflabel&v2_2=3&v0_3=&v1_3=altlabel&v2_3=3&v0_4=&v1_4=modified&v2_4=9&v0_5=&v1_5=modified&v2_5=10&x=31&y=25&v1_6=&v2_6=&v1_7=&v2_7=

- Level 4-Colours:
http://seadatanet.maris2.nl/v_bodc_vocab_v2/browse.asp?order=conceptid&formname=search&screen=0&lib=h04&v0_0=&v1_0=conceptid %2Cpreflabel %2Caltlabel %2Cdefinition %2Cmodified&v2_0=0&v0_1=&v1_1=conceptid&v2_1=3&v0_2=&v1_2=preflabel&v2_2=3&v0_3=&v1_3=altlabel&v2_3=3&v0_4=&v1_4=modified&v2_4=9&v0_5=&v1_5=modified&v2_5=10&x=57&y=13&v1_6=&v2_6=&v1_7=&v2_7=

- Level 5-Polymer types:
http://seadatanet.maris2.nl/v_bodc_vocab_v2/browse.asp?order=conceptid&formname=search&screen=0&lib=h05&v0_0=&v1_0=conceptid %2Cpreflabel %2Caltlabel %2Cdefinition %2Cmodified&v2_0=0&v0_1=&v1_1=conceptid&v2_1=3&v0_2=&v1_2=preflabel&v2_2=3&v0_3=&v1_3=altlabel&v2_3=3&v0_4=&v1_4=modified&v2_4=9&v0_5=&v1_5=modified&v2_5=10&x=53&y=20&v1_6=&v2_6=&v1_7=&v2_7=

Specific comments:

Master List of Categories of Litter Item | NOTES from JRC-EMODnet Chemistry
TSG_ML General-Code | OSPAR- Code | UNEP- Code | General Name | Level1 - Materials | Core | Beach | Seafloor | Floating | Biota | It could be helpful to avoid these different ML compartements (i.e Beach, Seafloor, Floating, Biota, Core), and merges all compartments in one (e.g. Macro Litter). EXCEPT FOR Microlitter: it could be useful to have a specific dedicated list or column in the Masterlist.
G2 |  | PL07 | Bags | Artificial polymer materials | x |  | x | x |  | Should be considered CATEGORY
G3 | 2 | PL07 | Shopping Bags incl. pieces | Artificial polymer materials |  | x |  |  |  | Should be considered SUBCATEGORY of G2
G4 | 3 | PL07 | Small plastic bags, e.g. freezer bags incl. pieces | Artificial polymer materials |  | x |  |  |
G5 | 112 |  | Plastic bag collective role; what remains from rip-off plastic bags | Artificial polymer materials |  | x |  |  |
G36 | 23 |  | Fertiliser/animal feed bags | Artificial polymer materials |  | x |  |  |
G37 | 24 | PL15 | Mesh vegetable bags | Artificial polymer materials |  | x |  |  |
G101 | 121 |  | Dog faeces bag | Artificial polymer materials | x | x |  |  |
G6 | 4 | PL02 | Bottles | Artificial polymer materials | x |  | x | x |  | Should be considered CATEGORY
G7 | 4 | PL02 | Drink bottles <=0.5l | Artificial polymer materials |  | x |  |  |  | Should be considered SUBCATEGORY of G6
G8 | 4 | PL02 | Drink bottles >0.5l | Artificial polymer materials |  | x |  |  |
G13 | 12 | PL02 | Other bottles & containers (drums) | Artificial polymer materials | x | x |  |  |  | Should be considered as one CATEGORY with G18 (G13+G18)
G18 | 13 | PL13 | Crates and containers / baskets | Artificial polymer materials |  | x | x | x |
G9 | 5 | PL02 | Cleaner bottles & containers | Artificial polymer materials | x | x |  |  |  | Should be considered SUBCATEGORY of G13+G18
G10 | 6 | PL06 | Food containers incl. fast food containers | Artificial polymer materials | x | x | x |  |
G11 | 7 | PL02 | Beach use related cosmetic bottles and containers, e.g. Sunblocks | Artificial polymer materials |  | x |  |  |
G12 | 7 | PL02 | Other cosmetics bottles & containers | Artificial polymer materials | x | x |  |  |
G14 | 8 |  | Engine oil bottles & containers <50 cm | Artificial polymer materials |  | x |  |  |
G15 | 9 | PL03 | Engine oil bottles & containers >50 cm | Artificial polymer materials |  | x |  |  |
G16 | 10 | PL03 | Jerry cans (square plastic containers with handle) | Artificial polymer materials |  | x |  |  |
G17 | 11 |  | Injection gun containers | Artificial polymer materials |  | x |  |  |
G100 | 103 |  | Medical/Pharmace uticals containers/tubes | Artificial polymer materials |  | x |  |  |
G20 |  | PL01 | Plastic caps and lids | Artificial polymer materials |  |  | x |  |  | Should be considered CATEGORY
G21 | 15 | PL01 | Plastic caps/lids drinks | Artificial polymer materials |  | x |  |  |  | Should be considered SUBCATEGORY of G20 with better definition otherwise deleted
G22 | 15 | PL01 | Plastic caps/lids chemicals, detergents (nonfood) | Artificial polymer materials | x | x |  |  |
G23 | 15 | PL01 | Plastic caps/lids unidentified | Artificial polymer materials |  | x |  |  |
G24 | 15 | PL01 | Plastic rings from bottle caps/lids | Artificial polymer materials |  | x |  |  |
G30 | 19 |  | Crisps packets/sweets wrappers | Artificial polymer materials |  | x |  |  |  | it is difficult to consider them different categories if other lists merged them in a unique code
G31 | 19 |  | Lolly sticks | Artificial polymer materials |  | x |  |  |
G34 | 22 | PL04 | Cutlery and trays | Artificial polymer materials |  | x |  |  |  | it is difficult to consider them different categories if other lists merged them in a unique code
G35 | 22 | PL04 | Straws and stirrers | Artificial polymer materials |  | x |  |  |
G38 |  |  | Cover / packaging | Artificial polymer materials |  |  |  | x |  | Should be considered CATEGORY
G67 | 40 | PL16 | Sheets, industrial packaging, plastic sheeting | Artificial polymer materials |  | x | x | x |  | Should be considered SUBCATEGORY of G38
G39 |  | PL09 | Gloves | Artificial polymer materials |  |  | x | x |  | Should be considered CATEGORY and it should include also rubber gloves
G40 | 25 | PL09 | Gloves (washing up) | Artificial polymer materials | x | x |  |  |  | Should be considered SUBCATEGORY of G39
G41 | 113 | RB03 | Gloves (industrial/professional rubber gloves) | Artificial polymer materials | x | x |  |  |
G48 |  |  | Synthetic rope | Artificial polymer materials |  |  | x | x |  | Should be considered CATEGORY
G49 | 31 | PL19 | Rope (diameter more than 1cm) | Artificial polymer materials | x | x |  |  |  | Should be considered SUBCATEGORY of G48
G50 | 32 | PL19 | String and cord (diameter less than 1cm) | Artificial polymer materials | x | x |  |  |
G52 |  | PL20 | Nets and pieces of net | Artificial polymer materials | x | x |  |  |  | Should be considered CATEGORY
G51 |  | PL20 | Fishing net | Artificial polymer materials |  |  | x | x |  | Should be considered SUBCATEGORY of G52
G45 | 28 | PL15 | Mussels nets, Oyster nets | Artificial polymer materials |  | x |  |  |
G53 | 115 | PL20 | Nets and pieces of net < 50 cm | Artificial polymer materials |  | x |  |  |
G54 | 116 | PL20 | Nets and pieces of net > 50 cm | Artificial polymer materials |  | x |  |  |
G62 | 37 | PL14 | Floats for fishing nets | Artificial polymer materials | x | x |  |  |
G56 | 33 | PL20 | Tangled nets/cord | Artificial polymer materials |  | x |  |  |  | Should be separated and considered SUBCATEGORY of G52 and G48
G55 |  | PL18 | Fishing line (entangled) | Artificial polymer materials |  |  | x |  |  | Should be considered CATEGORY
G59 | 35 | PL18 | Fishing line/monofilament (angling) | Artificial polymer materials | x | x | x |  |  | Should be considered SUBCATEGORY of G55
G57 | 34 | PL17 | Fish boxes - plastic | Artificial polymer materials |  | x |  | x |  | Is there any real difference between plastic and expanded polystyrene categories? Should be considered to merged them in one category
G58 | 34 | PL17 | Fish boxes - expanded polystyrene | Artificial polymer materials |  | x |  | x |
G63 | 37 | PL14 | Buoys | Artificial polymer materials |  | x |  | x |  | Should be considered CATEGORY
G73 | 45 | FP01 | Foam sponge | Artificial polymer materials |  | x |  |  |  | Should be considered CATEGORY
G74 |  |  | Foam packaging/insulation/polyurethane | Artificial polymer materials |  |  |  | x |  | Should be considered SUBCATEGORY of G73
G112 |  | PL23 | Industrial pellets | Artificial polymer materials | x |  |  |  | x | Should be considered CATEGORY
G107 |  |  | cylindrical pellets <5mm | Artificial polymer materials |  |  |  |  |  | Should be considered SUBCATEGORY of G112 OR reconsider to avoid coarse microlitter categories that merges the material, type and size of the items.
G108 |  |  | disks pellets <5mm | Artificial polymer materials |  |  |  |  |
G109 |  |  | flat pellets <5mm | Artificial polymer materials |  |  |  |  |
G110 |  |  | ovoid pellets <5mm | Artificial polymer materials |  |  |  |  |
G111 |  |  | spheruloids pellets <5mm | Artificial polymer materials |  |  |  |  |
G123 |  |  | Polyurethane granules <5mm | Artificial polymer materials |  |  |  | x |
G103 |  |  | Plastic fragments rounded <5mm | Artificial polymer materials |  |  |  |  |
G104 |  |  | Plastic fragments subrounded <5mm | Artificial polymer materials |  |  |  |  |
G105 |  |  | Plastic fragments subangular <5mm | Artificial polymer materials |  |  |  |  |
G106 |  |  | Plastic fragments angular <5mm | Artificial polymer materials |  |  |  |  |
G122 |  |  | Plastic fragments (>1mm) | Artificial polymer materials |  |  |  |  | x | Should be considered CATEGORY + reconsider the range size
G75 | 117 |  | Plastic/polystyren e pieces 0 - 2.5 cm | Artificial polymer materials |  | x |  |  |  | Should be considered SUBCATEGORY of G122 + reconsider minimun size (e.g. value=zero?)
G78 |  |  | Plastic pieces 0 - 2.5 cm | Artificial polymer materials |  | x |  |  |  | Should be deleted because equal to G75 and should be considered SUBCATEGORY of G122
G81 |  |  | Polystyrene pieces 0 - 2.5 cm | Artificial polymer materials |  | x |  |  |
G76 | 46 |  | Plastic/polystyren e pieces 2.5 cm > < 50cm | Artificial polymer materials |  | x |  |  |  | Should be considered SUBCATEGORY of G123
G79 |  |  | Plastic pieces 2.5 cm > < 50cm | Artificial polymer materials |  | x |  | x |  | Should be deleted because equal to G76 and should be considered SUBCATEGORY of G123
G82 |  |  | Polystyrene pieces 2.5 cm > < 50cm | Artificial polymer materials |  | x |  | x |
G77 | 47 |  | Plastic/polystyren e pieces > 50 cm | Artificial polymer materials |  | x |  |  |  | Should be considered SUBCATEGORY of G124
G80 |  |  | Plastic pieces > 50 cm | Artificial polymer materials |  | x |  | x |  | Should be deleted because equal to G77and should be considered SUBCATEGORY of G124
G83 |  |  | Polystyrene pieces > 50 cm | Artificial polymer materials |  | x |  | x |
G135 |  | CL01 | Clothing (clothes, shoes) | Cloth/textile |  |  |  | x |  | Should be considered CATEGORY excluded shoes
G136 |  | CL01 | Shoes | Cloth/textile |  |  | x |  |  | Should be considered CATEGORY
G137 | 54 | CL01 | Clothing / rags (clothing, hats, towels) | Cloth/textile | x | x | x |  |  | should be redefined
G138 | 57 | CL01 | Shoes and sandals (e.g. Leather, cloth) | Cloth/textile |  | x |  |  |  | should be redefined
G145 | 59 | CL06 | Other textiles (incl. rags) | Cloth/textile |  | x | x | x |  | should be redefined
G146 |  |  | Paper/Cardboard | Paper/Cardboard |  |  | x |  |  | Should be deleted
G157 |  |  | Paper | Paper/Cardboard |  |  |  |  | x | should be redefined or deleted

Annex 7. Specific hindrances by country*.

Dataset
Country
Data originator
Data collator
Hindrances

OSPAR
Belgium, Denmark, France, Germany, Ireland, Netherlands, Portugal, Sweden, United Kingdom
MISSING

Except for

- Portugal: Direcção Genral do Ambiente (Ministry of Environment)

- Denmark_Atlantic: KIMO Danmark

EMODnet

• Complete set of metadata. OSPAR coding was used. Flat text format for metadata fields is not always easy to adapt to DB structure, though almost all metadata were ingested into the DB.

• Survey length of 1km and 100m have been included in the DB. Survey width is variable:transect width follow OSPAR Guidance. the beach width and for most of the beach is total from low tide line to the background of the beach dunes or cliffs.

Bulgaria
Bulgaria
Black Sea Basin Directorate – Varna
JRC

• Dataset only contained basic metadata but everything was clear. TGML coding was used, including OSPAR and UNEP/MAP coding. However, some additional UNEP codes were missing and have been inserted by JRC-EMODnet. Multiple TGML code assigned cannot be considered in the data entering, thus TGML general code for general material/item has been used e.g. G2 Plastic bag and detailed note has been added in the dataset.

• Survey length: 1000 m were reported on the original dataset, additionally explained with “data is collected from 2 or 3 sections and assessed for all of them”. Following MSFD protocol it was considered a survey length of 300 m (3 sections x 100 m). This point has already been clarified with MS contact.

Croatia
Croatia
IOF, Institute of Oceanography and Fisheries
JRC

• Complete dataset with extended metadata. OSPAR template was used to perform the surveys but TGML coding was used.

• Beach width registered as both low and high tide, but has been indicated only coordinates start/end for transect 100m length x 10m width. These coordinates have been included in the marine litter dataset.

Cyprus
Cyprus
Isotech Ltd
JRC

• This dataset did not come from an official Member State body but from a private monitoring company (Isotech Ltd).

• Very incomplete dataset with some important missing information as survey length or the use of a standard reference list to describe the items.

• Survey length is provisionally “0” where it was missing in order to ingest data into DB.

• There was a lack of item codes. UNEP litter reference list codes were derived from item names found in the original file. This has been done in order to be able to code items and enter them in the DB.

Denmark_Baltic
Denmark_Baltic
Danish Environmental Protection Agency. Aarhus University, DCE (Danish Centre for Environment and Energy)
JRC
• Dataset only contained basic metadata but everything was clear. TGML coding was used.

Estonia
Estonia
Keep the Estonian Sea Tidy Association
JRC

• Dataset was initially sent without survey coordinates and survey length. After further contacts with data originator this information was provided. No survey width was provided.

• UNEP-MARLIN¹ protocol and coding was used to perform the survey. According to the protocol, three different measurement areas were provided. The same type of item has been counted over a 100 m length (area 2) and 1000 m (area 3) length. Data for the three areas were aggregated during ingestion in the DB. The same type of item has been counted over a 100 m length (area 2) and 1000 m (area 3) length.

Finland
Finland
Keep the Estonian Sea Tidy Association
JRC

• File from JRC was replaced with file from EMODnet partner because it is more complete.

• UNEP-MARLIN¹ protocol and coding was used. From the information obtained by the EMODnet partner (that was in direct contact with the originator) we understood that cigarette butts were counted over a different length basis than the survey length provided. All other items were counted over 100 meter basis (area 2). When presenting results, only 100 m survey should be considered and therefore areas 1 and 3 should be recalculated to the unit: number of litter items per 100 m.

France _Mediterranean Sea
France _Mediterranean Sea
Cedre
JRC

• Data was provided in original language.

• Generally, OSPAR coding was used. For one beach double coding (OSPAR and TGML) was used depending on convenience. It is uncertain in this case which protocol was used to perform the survey.

• Survey width values are missing. Geographic coordinate for Golo beach were missing, later provided by data originator.

• Metadata will be improved thanks to EMODnet French partner (IFREMER), dataset under processing.

Germany_Baltic
Germany_Baltic
State Agency for Environment, Nature and Geology, Mecklenburg-Vorpommern, EUCC - The Coastal Union Germany (EUCC-D), National Park Authority Vorpommern, Jordsand Association, Nature and Biodiversity Conservation Union Germany (NABU), Regional School "Windland" Altenkirchen, Southeast Rügen Biosphere Reserve Office
JRC

• UTM coordinates were converted into geographical coordinates.

• OSPAR coding was used.

• Survey width values and type of protocol are missing.

Greece
Greece
MISSING
JRC

• Surveys with 0 data for all item types were found. Were the surveys without data actually performed and no litter was found, or were they not performed?

• Survey date without day value (i.e., only season is indicated). To ingest data, it was decided to use 1st day of the month of the season indicated in the data set (i.e. Winter = 1st of January; Spring = 1st of April; Summer= 1st of July; Autumn= 1st of October).

• Average values of items were provided in the beginning; later they were replaced with original counts provided by data originator.

Italy
Italy
Legambiente
JRC

• Data were not provided by the official national body (i.e. Ministry of Environment) but by Legambiente NGO.

• Dataset only contained basic metadata but everything was clear. TSG-ML coding was used.

• Survey width values are missing.

• Survey locations are always on different beaches, which are indicated only with specific code per each region. No names are available (already requested). It is not clear if it is monitoring data or cleaning.

Latvia
Latvia
Foundation for Environmental Education FEE Latvia
JRC

• Data was provided in original language.

• UNEP-MARLIN¹ protocol and coding was used. It must be clarified how UNEP-MARLIN protocol was used and which length basis was used to count items.

• Important missing information on the original dataset as: day and month of survey date, survey length/coordinates. This information has been found in the project report.

• Survey width:from water line to first stable vegetation (differs every time).

• To enter data into DB survey date was assumed 1st of July in all cases.

Lithuania
Lithuania
MISSING
JRC

• OSPAR coding was used.

• Item quantities for OSPAR categories 3, 4 and 6 are often repeated in the same survey. Values were ingested as they were in the original file.

Poland
Poland
MISSING
JRC

• TGML coding was used but multiple codes were provided for some items. Data ingestion was not possible. It was decide to proceed aggregating items.

• Reporting quantities not admissible by the DB were provided. As before a provisional decision was taken.

• Metadata included useful survey width but sometimes reported in approximate ranges or preceded by ca. (circa), so it is not acceptable by the DB.

• Data had different lines considering size that were aggregated and info related to size was kept in notes.

Romania
Romania
National Institute for Marine Research and Development "Grigore Antipa" (NIMRD)
National Institute for Marine Research and Development "Grigore Antipa" (NIMRD)
• File from JRC was replaced with file from EMODnet data provider (NIMRD) because it was more complete.

Slovenia
Slovenia
Institute for Water of the Republic of Slovenia
JRC

• UNEP and TGML coding were used. Depending on the item description one or multiple codes from TGML were provided. Data ingestion was not possible. It was decided to use only UNEP coding and to search equivalent UNEP codes where they were missing. Therefore, the complete UNEP coding was used for the data ingestion into DB.

• Some survey dates were missing. To enter data into the DB, the survey date was assumed to be 15th as most of the other surveys were performed around the half of the month.

Spain
Spain
MISSING
JRC

• Data was provided in original language and through MS-Access database.

• OSPAR coding was used. TGML coding was recorded in the DB as alternative coding.

• Survey width values are missing.

• Data IDs with empty survey ID were present and ignored (request already sent).

• Different codes for beaches with same name were found. Only one code was maintained.

Sweden_Baltic
Sweden
MISSING
JRC

• UNEP-MARLIN¹ protocol and coding was used to perform the survey. Original dataset had three different measurement areas that were aggregated during DB ingestion.

• The same type of item has been counted over a 100 m length (area 2) and 1000 m (area 3) length. During DB ingestion these data were aggregated. However, this issue should be clarified in order to know if these data can be aggregated and which survey length must be considered.

• Errors on beach codes were detected and corrected before ingestion.

NB:

*Data gathering is still on going Data in the table at the date 31-10-2018.

¹ Survey areas (1-2-3) and type of items are collected according to UNEP MARLIN protocol. In this protocol three different lengths are surveyed depending on the item types (e.g. cigarette butts) and size (>50cm or <50 cm). This means that items are reported over a different length basis. While transect width is variable and based on the beach, transect length is set up based on litter item size: Area 1 (green) is for cigarette butts and snus measured on 10 metre length beach. Area 2 (orange) is for the ordinary litter between 2,5 cm to 50 cm on 100 m beach and Area 3 (red) is for larger litter items >50 cm measured on 1000 m beach. This difference is considered by Baltic countries when they report their data at regional level, but it needs to be accounted when using the data for comparison at EU level. See figure below:

Source: Final report of Baltic marine Litter project Marlin — litter monitoring and raising awareness, 2011-2013. (https://www.hsr.se/sites/default/files/appendix1_measurement_method.pdf)