Memo of the on-line meeting of the HELCOM EN … LITTER-92...The Meeting agreed that the HELCOM EN-Marine Litter will work on the treatment of national data to identify total number

Memo of the on-line meeting of the HELCOM EN-Marine Litter (24 March 2017)

A working meeting of the HELCOM EN-Marine Litter was held on 24 March 2017 as an online meeting. The list of participants is contained in Annex 1. The aim of the Meeting is:

- to note the informal notes of the TG ML workshop on marine litter baselines;- to consider the on-going work in relation to compilation of beach litter data;- to consider the preliminary analysis of beach litter data of the Baltic Sea region and the basis for

determination of a baseline and target values for GES assessment as prepared by Poland;- to consider the Swedish summary on the on-going work in relation to litter on the seafloor;- to consider the status of compilation of microlitter data.

Informal notes of the TG ML workshop on marine litter baselines

HELCOM SPICE is to contribute directly to the finalization of the ‘Second HELCOM Holistic Assessment of Ecosystem Health in the Baltic Sea'. One of the themes of the project aims at developing marine litter indicators towards operationalization and prepare a proposal for the assessment of marine litter in HOLAS II. Data on beach litter and litter on the seafloor are being compiled for further analysis aiming at defining a baseline for beach litter and explore the possibilities to define such a baseline for litter on the seafloor for the Baltic Sea.

The EU Technical Group on Marine Litter (TG ML) held a workshop on 14-15 March to discuss aspects of the marine litter baselines work that may be relevant in regard to next steps to be taken in the frame of HELCOM SPICE.

The Meeting took note of the informal notes of the TG ML workshop which were distributed to the HELCOM EN-Marine Litter as background information for the meeting (Annex 2).

On-going work on compilation of beach litter data The Meeting took note that a request was sent, as part of the SPICE project, to the HELCOM EN-Marine Litter (e-mail sent 30.1, reminder 20.2) to provide additional marine litter data and that the feedback received is as follows:

- Denmark: has provided data from 3 beaches monitored 4 times/year for 2015-2016;- Estonia: has provided data from 6 beaches during summer for 2016;- Finland: has provided data from 10 beaches during spring and summer 2016, and 6 during autumn;- Germany: has provided data from 6 beaches for 2016;- Lithuania: has provided data for 4 beaches monitored 4 times/year for 2012 and 2013;- Poland has provided data for 15 beaches monitored 4 times (spring, summer, autumn and winter)

per year 2016;- Sweden: has provided data for 10 beaches monitored in summer and autumn in 2016.

Polish analysis of beach litter data and initial proposal to define baseline and target values for GES assessment The Meeting took note of the proposal to define a baseline for beach litter distributed to the HELCOM EN-Marine Litter as background information for the meeting (Annex 3). The Meeting further noted:

- the analysis is conducted on available data from all countries (779) for the period 2012-2016 (aggregated);- there is on-going work to finalise the inclusion of additional data provided in the beach litter assessment i.e.

Estonian, Latvian and Lithuanian data. Additional German data will also be included once provided;- unclassified group of beach litter has not been included in the analysis because there were very little data;- data are expressed in number of items per 100m per 1 beach, thus considering the number of beaches

monitored.

The Meeting discussed the proposal and agreed to focus on the definition of beach litter baselines. The Meeting also agreed to follow the same approach as for litter on the seafloor, and focus on the analysis of regional litter

http://helcom.fi/helcom-at-work/projects/spice/

distribution. Poland offered revision of the preliminary statistical analysis taking into account all written comments as sent before the meeting.

The Meeting discussed the on-going process at EU level in relation to the definition of beach litter baselines. The meeting noted that the approach of focussing on 80% of the top items found in beaches aims at reducing uncertainties. The Meeting also noted that there is a need to further work on the identification of different items when using different master lists.

The Meeting agreed that the HELCOM EN-Marine Litter will work on the treatment of national data to identify total number of top 80% marine litter items per 100 m beach length.

Swedish summary on the on-going work in relation to litter on the seafloor The Meeting took note of the proposal to define a baseline for beach litter distributed to the HELCOM EN-Marine Litter as background information for the meeting (Annex 4).

The Meeting noted that a geographical analysis as well as an analysis of the influence of different types of seafloor (sandy versus rocky) as well as depth (20m to 400m) on the behaviour of seafloor litter will be conducted. The meeting also noted that data collected do not represent the total amount of litter on the seafloor but what it is ‘fished’, being therefore an index of litter on the seafloor. The meeting proposed to provide recommendations for seafloor litter data collection for those countries who are not covered by the trawls surveys.

The meeting agreed to conduct a power analysis for the trends to evaluate if a four year period is enough to set a robust baseline.

The meeting noted that the analysis will be redone after April, and that Danish data will be included. Data analysis on a yearly bases will be compared to analysis of aggregated data for the period 2012-2016. The Meeting was invited to provide further comments to the Swedish proposal at their earliest convenience ([email protected]).

Status of compilation of microlitter data The Meeting took note that a request was sent, as part of the SPICE project, to the HELCOM EN-Marine Litter (e-mail sent 10.2) to update information on available microlitter data. Feedback has been provided by Denmark, Estonia, Germany and Sweden. The Meeting encouraged contribution from the rest of the countries.

Any other business The Meeting noted that the next meeting of the TG Litter is to be held on 8-9 June 2017 in Gdansk (Poland) and encouraged participation of the HELCOM experts.

The Meeting agreed to hold an on-line meeting of the HELCOM EN-Marine Litter on May, and that the Secretariat will set a doodle for that purpose.

mailto:[email protected]

Annex 1 List of Participants

Name Organisation Email address Denmark Lone Munk Søderberg Danish Nature Agency [email protected] Jakob Strand Aarhus University, Department of Bioscience [email protected] Estonia Marek Press Keep the Estonian Sea Tidy Association [email protected] Finland Outi Setälä Finnish Environment Institute, SYKE [email protected] Germany Elke Fischer University of Hamburg elke.fischer@uni-

hamburg.de Lithuania Laura Lauciutė Environment Protection Agency, Marine Research

Department [email protected]

Poland Wlodzimierz Krzyminski Institute of Meteorology and Water Management,

National Research Institute [email protected]

Tamara Zalewska Institute of Meteorology and Water Management - National Research Institute, Maritime Branch

[email protected]

Sweden Per Nilsson Swedish Institute for the Marine Environment per.nilsson@havsmiljoinsti

tutet.se HELCOM Secretariat Marta Ruiz HELCOM Secretariat [email protected]







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Annex 2 - Informal notes of the EU Workshop on Marine Litter Baselines Brussels, Belgium,14-15 March 2017

Participants The list of participants is included in Annex 1.

Agenda The agenda of the workshops is included in Annex 2.

Aim The MSFD TG Marine Litter Marine Baselines workshop aimed to identify key messages on which to conclude and to develop a working process towards a common approach for the baselines. In particular the workshop aimed at:

- elaborating the possibilities, options and scenarios for identifying "starting points" for trendassessments;

- present the basics of baseline setting, then derive a definition for their purpose and elaborate whichelements are needed (data, data quality, scales, etc.) in order to set baselines (i.e. also derivetrends...).

Welcome and workshop opening (Michel Sponar, DG ENV)The role of the circular economy package was highlighted regarding tackling plastics. Two studies to be launched soon on microplastics and macroplastics which will contribute to the Strategy of Plastics. The role of the MSFD was emphasized.

Introduction and policy background (MSFD + EU Plastics Strategy, Michail Papadoyannakis, DG ENV) (Presentation 1) The main EU policy responses were pointed out. The PRF Directive is under revision. The Ocean Governance Communication has a whole package on marine litter. It also stresses the need to do more on sea-based sources. The opinion of the Parliament will come up in April regarding the revision of the Commission Decision on the MSFD. Main changes: use amounts, instead of trends.

Commitments at EU at international level were detailed. The Plastic Strategy will be delivered at the end of 2017. It aims at reducing fishing gear (FG) to 30 % as well as top ten beach litter items by 2020. It is currently under discussion to elevate the G7 commitment to G20. To achieve these commitments there is a need to have baselines. The aim of the work starting today is indicated.

Marine litter baselines roadmap work planning and timeline (Georg Hanke, JRC) (Presentation 2) The need for reduction of plastic in the marine environment is indicated. The reasons why baselines are needed is indicated: verification of impacts of PoMs, and their further adaptation, starting point for reduction trend calculations, and of course quantification of the problem. The mandate of the TG Marine Litter has been renovated and it is now for 2016-2019, with possibilities of being extended afterwards. There is also available experience, coming from MS as well as from RSCs and research projects. The list of stakeholders was also detailed. The idea is to know if we are losing any kind of expertise. Everything is open for discussion in this WS: aiming at setting up what information we need, to set up the further work to be conducted, and to test the approach with real data in the upcoming months. By the end of 2017 the drafts concepts are to

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be available. The final goal is, if possible, to prepare a guidance, by the end of 2017. By early 2018 the process should be finished with the guidance for baseline setting.

Discussion - Who is to set the baselines?- Interim results are needed two months ahead so that they can be included in the Plastic Strategy.- How to calculate baselines is decisive, there is a technical discussion gap to be sorted out.- It was clarified that this is a WS and that its results will be shared with the TG ML meeting in June in

Poland.

Baseline scope, concept and definition (Anna M. Addamo, JRC, Presentation 3) The lack of agreement on concepts, scope and definition was emphasized. The initial proposal for a definition of a baseline is:

“A starting point that provides a final large-scale comprehensive characterization of marine litter in a specific year and place. It is against which to monitor, measure and assess and activity’s progress and effectiveness during and after the implementation of measures or plan is completed.”

Further discussion on the definition is envisaged during the WS. Are we talking about a range of time or a point in time?

Marine litter baseline: development elements and needs (Georg Hanke, JRC, Presentation 4) Elements of the baseline setting are described. The idea is to select reasonable scenarios to be tested. One scenario could concentrated on beach litter in 2015 in RSCs, another one on plastic bags. Once this scenario is decided, it will be tested with real data. The scale where the scenario is tested is relevant, since you may get different results depending on which scale is considered.

Break out groups to be set during the second day of the WS to define these scenarios. The next step will be to use the evaluation of the scenarios as basis for recommendations/guidance. The WS found the approach very useful.

Discussion - How to evaluate the scenarios?- To select items for which actions are already on-going nationally or/and regionally;- There is not enough knowledge to work on the establishment of microlitter baselines, since it is not

possible to establish thresholds;- It is difficult to link plastics in fulmars to measures.

EMODnet General introduction (Alessandra Giorgietti, INOGS Presentation 5) HELCOM and OSPAR also support EMODnet. There is a central portal (SeaDataNet), which distributes data to the users. In this 3rd phase (2017-2010) EMODnet will extend to marine litter (beach litter, seabed litter and microlitter), covering all European waters. In one year litter maps are to be produced. IFREMER (France) is responsible for the compilation of data. The contract assigning this work to EMODnet has recently been signed (March).

Marine litter data availability, coverage and quality: beach litter (macro + meso + micro) (Anna M. Addamo, JRC, Presentation 6, Excel file) There are more data available from the beach compartment than from any other one. This compiled information comes from countries, and there are some countries who have not provided the required information asked for in the basecamp. Spain is monitoring microlitter in the beach.

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Marine litter data availability, coverage and quality: floating litter (macro + meso + micro) (Daniel Gonzalez, JRC, Presentation 7, Excel file) There is a lack of protocol for floating litter. Floating microlitter is a criteria in Italy. Microplastics in sediment is to be considered as an indicator in the upcoming EIHA meeting in April.

Marine litter data availability, coverage and quality: seafloor litter (macro + meso + micro) and ingestion/entanglement (Anna M. Addamo & Daniel Gonzalez, JRC, Presentation 8, Excel file) 40m depth is considered deep sea for the seafloor litter.

Discussion - Fishing for litter data to be used or not. In OSPAR they have just changed the way of doing it, so only the

amount of litter is going to be quantified. - DOME database hosted by ICES contains data on microlitter in the sediment. - ICES wants to create a group dealing with marine litter next year. - Would there be a possibility to have a go with fishing gear considering the reduction target to be

achieved? Is it possible to monitor this information? It could be one of the scenarios to test. - Data from entanglement and ingestion may not be ready for using. It may not be appropriate to be

considered as a scenario, considering that is only used in the OSPAR area. - For beach litter, it may be possible to use the analysis tool already available. - There was a lot of controversial discussion on the understanding of the information provided by

countries.

Geographical and temporal scales of marine litter baselines: levels and frequencies (Anna M. Addamo, JRC, Presentation 9) Whatever scenarios are tested they have to be tested at different scales. There is a need to clarify the concepts of accuracy and precision. The scales under consideration are: site, municipalities, country region, member state, sub-regional level, sea region and EU.

Marine litter item specific baselines: top items and category lists (Georg Hanke, JRC, Presentation 10, background document) There is a need to work with litter items to achieve reduction targets. Not to focus on fragments. The top 10 items (no fragments) across all lists:

- nets and ropes - plastic caps and lids - cigarette butts - crisp and sweet wrappers - lolly sticks - string and cord <1cm diameter - cotton bud sticks - plastic drink bottles - plastic food containers

There were some shortcomings in considering the different lists, but further work is envisaged on this list.

Litter analysis also provide information on the harm of the items. The EU report on harm of marine litter is about to be published in the near future.

By June the JRC hopes to present progress achieved on the update of the MSFD Master List.

http://ices.dk/marine-data/data-portals/Pages/DOME.aspx

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Regional Sea Convention Experiences with ML Baselines setting: OSPAR (Lex Oosterbaan, Presentation 11 and Thomas Maes, Presentation 12) OSPAR is to further develop an indicator on microplastics in sediments.

One option could be, for establishing baselines, to consider the worst data from 2012 on FG and from them establish the aim to achieve a reduction target.

The software is to be made free available in 2017.

For fulmars they are using a longer period of time to establish trends, since OSPAR uses a 10 years period. There is a threshold value already established for fulmars.

CEFAS is asking ICES to create a group on marine litter so that they can better address seafloor data within DATRAS database.

The report on the assessment of seafloor litter will be available in June once approved by EIHA.

Regional Sea Convention Experiences with ML Baselines setting: MAP (Christos Ioakeimidis Presentation 13) Baseline values on marine litter are a living document. Proposed baselines, which are a range, are established at regional level, then they are to be further define at a sub-regional level. Environmental targets on marine litter have also been established.

There is on-going work on developing a regional database on marine litter.

Regional Sea Convention Experiences with ML Baselines setting: Black Sea (Georg Hanke on behalf of the Black Sea, Presentation 14) An update of the on-going work was provided.

Regional Sea Convention Experiences with ML Baselines setting: HELCOM (Marta Ruiz, Presentation 15) An update of the on-going work was provided.

Marine litter baselines setting (Georg Hanke, JRC, Presentation 16) The WS was split up in three break-out groups aiming at (all of them):

- identify elements- identify options- select sets of options- consider priorities (measures)- proposed scenarios

Outcomes of the break-out groups Group 1 (Presentation 17) 1 General considerations:

- Measure baselines ( to assess efficiency of measures)- Flexibility in baseline setting as top 10 items may change over time (~ efficiency of measures) – 6-

yearly revision linked to monitoring reports (6-yearly)- Data availability ~ spatial scale to consider per baseline scenario (e.g. most data 2014-2015 at EU

scale)- Issue of uncertainty level in case of < 3-years data period

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2 Proposed scenarios on beach macrolitter: SCEN 1 a/b: TOTAL – subregion / SCEN 2a/b: TOTAL – 80% subregion • Item: Total number of ML items per 100 m / Total number of top 80% ML items per 100 m • Temporal + Spatial A: Average (2014-2015) per sub-region (OSPAR, HELCOM) (as best data

coverage) ; to be checked if relevant for MED (at least available for ES, FR, IT) & MED Adriatic (Defishgear data)

• Temporal + Spatial B: Average (2009 – 2014) per specific OSPAR and HELCOM (sub-basins) reporting units (geographical scale) where data are available (added value as testing)

SCEN 3-X: SPECIFIC ITEMS Directly related to measures • National (UK): bottles (best time series available) • Southern North Sea: dolly ropes • EU (all subregion): Cotton bud sticks (consumer pressure, related to sewage problem) • MED/ Black Sea: Cigarette buds

3 Proposed scenarios on seabed macrolitter: SCEN 6: PLASTIC BAGS – seabed litter • Plastic bags • Spatial: Subregional (all) • Temporal: average 2012-2015 (before implementation of measure? Differs per MS?) • Data:

o Data in HELCOM: data o Data in OSPAR: ICES data (Datras database) 2012-2016 o Data in MED: MEDITS data o Data in Black: ?

• Measure: plastic ban measure 4 Proposed scenarios on ingestion microlitter:

SCEN 4: PELLETS - FULMARS • Item: pellets found in fulmars • Spatial: Regional (OSPAR) (as not found in Baltic; no data for other regions): pellets • Temporal: longest time series available • Data: no data availability at the moment, except for projects and fulmars indicator (OSPAR); to

be checked: fulmar data can also be used before the last 3-years or acceptance to be asked to OSPAR as not published

• Measure: to assess the effectiveness of all the measures now set for industries 5 Further discussed: probably no mature in terms of data availability:

SCEN 5: PELLETS - BEACH

• Item: Total amount • Spatial: Sea Regions • Temporal: XXX • Data: Data availability? Consider Data 1 – 5 mm total amount results in order to harmonize

results: data in BALTIC (single studies) / Data in OSPAR: research project, Spain / Data in MED: check Defishgear project

• Measure: to assess the effectiveness of all the measures now set for industries FLOATING LITTER • Item: Floating litter • Spatial: example for Germany • Temporal:

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• Data: Data based on aerial observations: Germany data (Baltic, North sea)• Measure: XXX

BEACH/FLOATING/SEAFLOOR - FISHING GEAR • Item: Lost nets at sea• Spatial: XXX• Temporal:• Data:

- Ad hoc data- BE: potential fishing nets within wind farms are removed for safety reasons (ca. 10

interventions per year) based by the wind developers – to be further checked if it isreported in a systematic way

• Measure: 30% reduction target beach litter + fishing gear lost at seaGroup 2 (Presentation 18)

Group 3 (Presentation 19) General statements:

- Spatial scale is determine by purpose of baseline- Status/measures baseline- Fundamentally different methodologies lead to incomparability = separate baselines (need to

harmonise)- Baselines should be comparable

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- Status, follow-up of measures (scale depending)- Regional/Sub-regional/national: MSFD- EU/Regional/sub subregional/national/country region baseline: measures related- Few stations and no frequent sampling reduce power of analysis, though national data is more

homogenous- Scale depends on measurement methodology (fulmar, turtles).

Priority scenarios: - Beach (macro), 1 + 6 year average, data availability, 2012 2014/2015, top items (considering risk)

should be 80% of items, regional, sub-regional, national (priority)- Beach (macro), 1 + 6 years average, data availability, 2012 2014/2015, all items, regional, sub-

regional, national (priority)- Seafloor, 2012, region, items: total, plastic, fishing, regional, sub-regional, national (priority)- Floating, 2014, region, items: microlitter, regional, sub-regional, national (priority)

Other scenarios:

- [Beach (macro), 1 + 6 years average, data availability, 2012 2014/2015, fishing gear, regional, sub-regional, national (priority)]

- [Beach (macro), 1 + 6 years average, data availability, 2012 2014/2015, plastic, regional, sub-regional,national (priority)]

- No biota ingestion, entanglement.

Wrap up The further steps of the work to be conducted are compiled in Presentation 20. As a summary it can be indicated that:

- Data collection to be used in the scenarios testing: a new request will be submitted to countries tocomplement available data (Excel file). A new template will be provided for such purpose. Thedeadline to provide data is 15 April 2017.

- The scenarios proposed by Group 3 will be tested;- A progress report on the testing of the scenarios will be presented at the TG ML meeting to be held

on 9-10 June 2017, in Gdansk (Poland) (on-line participation is envisaged);- The EU informed that the European Parliament adopted 14 March 2017 amendments on the

proposal for a directive of the European Parliament and of the Council amending Directive2008/98/EC on waste. It is to point out in relation to marine litter reduction targets the following1:

‘Having regard to the environmental and economic benefits of preventing marine litter, Member States should establish specific marine litter prevention measures in their waste prevention programmes. With these measures, Member States should aim to achieve the Union-wide marine litter reduction targets of 30 % by 2025 and of 50 % by 2030. To measure progress towards these targets and to facilitate an exchange of good practices across the Union between Member States, uniform methodologies for the measurement of land-based marine litter should be established. Reporting on land-based marine litter levels should take place every year.’

1 Please find here further information about the process to be followed by the proposal.

http://www.europarl.europa.eu/sides/getDoc.do?pubRef=-//EP//TEXT+TA+20170314+ITEMS+DOC+XML+V0//EN&language=EN#sdocta6

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Annex 1 - List of participants

Name Institute Country Email

Georg Hanke JRC [email protected]

Francois Galgani IFREMER France [email protected]

David Michael Fleet

The Schleswig-Holstein Agency for Coastal Defence, National Park and Marine Conservation

Germany [email protected]

Susan Jane Kinsey Marine Conservation Society UK [email protected]

Thomas Maes CEFAS UK [email protected]

Alexander Oosterbaan Ministry of Infrastructure and Environment/Rijkswaterstaat NL [email protected]

Per Gunnar Nilsson The Swedish institute for the marine environment Sweden per.nilsson@havsmiljoinstitutet.

se

Maria Fernanda Dias Martins Ferreira

Coastal & Marine Union (EUCC) Nederland [email protected]

Emma Priestland Seas At Risk [email protected]

Antoine Brice Pierre BRUGE Surfrider Foundation Europe France [email protected]

Sandra Cláudia Santos Nogueira Pereira Moutinho

DGRM Portugal [email protected]

Štefan Trdan Institute for Water of the Republic of slovenia Slovenia [email protected]

Christos Ioakeimidis UNEP/MAP MEDPOL [email protected]

Lieve Victor L Jorens FPS Health, Food Chain Safety and Environment, Belgium Belgium [email protected]

Setälä, Outi Sirkka Soilikki Finnish Environment Institute Finland [email protected]

















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Elke Kerstin FISCHER University of Hamburg, CEN, Center of Earth System Research and Sustainability

Germany [email protected]

Marta Martínez-Gil Pardo de Vera

Ministry of Agriculture and Fisheries, Food and Environment

Spain [email protected]

Marta Ruiz Garcia HELCOM Secretariat [email protected]

Annemie Volckaert Arcadis Belgium Belgium [email protected]

Claeys Inge Arcadis Belgium Belgium [email protected]

Lorenza Babbini ISPRA Italy [email protected]

Dick Schaap MARIS Nederland [email protected]

Alessandra Giorgetti Istituto Nazionale di Oceanografia e di Geofisica Sperimentale - OGS

Italy [email protected]

Anna Addamo JRC [email protected]

Daniel Gonzalez JRC [email protected]

Michael Papadoyannakis European Commission EU [email protected]

opa.eu








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Annex 2 – Agenda of the workshop

Tuesday, March 14th

9:00 WELCOME AND WORKSHOP OPENING Michel Sponar, DG ENV

9:15 INTRODUCTION AND POLICY BACKGROUND MSFD + EU PLASTICS STRATEGY Michail Papadoyannakis, DG ENV

9:45 MARINE LITTER BASELINES ROADMAP WORK PLANNING AND TIMELINE Georg Hanke, JRC

10:15 BASELINE SCOPE, CONCEPT AND DEFINITION Anna M. Addamo, JRC + All

10:45 Coffee-break

11:00 ML BASELINE DEVELOPMENT ELEMENTS AND NEEDS Georg Hanke, JRC

11:30

11:45

EMODNET GENERAL INTRODUCTION Alessandra Giorgietti, INOGS

MARINE LITTER DATA AVAILABILITY COVERAGE + QUALITY Anna M. Addamo, Daniel Gonzalez, JRC + all

• BEACH LITTER (MACRO + MESO + MICRO)• FLOATING LITTER (MACRO + MESO + MICRO)

13:00 LUNCH 14:30 MARINE LITTER DATA AVAILABILITY – CONTINUED

COVERAGE + QUALITY Anna M. Addamo, Daniel Gonzalez, JRC + all

• SEAFLOOR LITTER (MACRO + MESO + MICRO)• INGESTION/ENTANGLEMENT

ROUND TABLE DISCUSSION 16:00 Coffee-break

16:15 GEOGRAPHICAL AND TEMPORAL SCALES OF ML BASELINES LEVELS AND FREQUENCIES Anna M. Addamo, JRC + All

17:15 ML ITEM SPECIFIC BASELINES TOP ITEMS AND CATEGORY LISTS Georg Hanke, JRC + All

18:00 END

Wednesday, March 15th

9:00 REGIONAL SEA CONVENTION EXPERIENCES WITH ML BASELINES SETTING • OSPAR Lex Oosterbaan• HELCOM Marta Ruiz• MAP Christos Ioakeimidis

ML BASELINES SETTING Discussion on specific topics

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10:00

Georg Hanke, JRC + All • IMPLICATIONS OF ML BASELINES • CALCULATION OF BASELINES • REFERENCE DATES • IMPLEMENTATION OF BASELINE SETTING APPROACHES • …

DISCUSSION AND SHORT PRESENTATIONS All

10:45 Coffee-break 11:00 ML BASELINE SETTING - CONTINUED

Georg Hanke, JRC + All 11:30

BREAKOUT DISCUSSIONS GROUP Working groups of 5-7 participants

• HINDRANCES IN ML BASELINE SETTING • SOLUTIONS AND WAYS FORWARD

13:00 LUNCH

14:30

CONCLUSIONS Identification of agreed messages and needs All

15:15

WORK ITEMS AND PROCESS Organisation of collaborative approach for baseline concept development and testing All

16:00

NEXT STEPS Who does what, when DG ENV + JRC

16:30 END

1. Data used:

a. All Danish, Finnish, Polish, Swedish updated data.

b. German and Estonian data as available in 2016.

2. An analysis of temporal changes and trends of mean values of all aggregated data

for period from 2012 (where available) to 2016 (where available). Tables 1 and 2,

figures 1 to 8.

3. Assuming 10% yearly reduction of an average of litter items per 100 m within 6‐

year period, we obtain 60% reduction for the whole period, what yields with

target values based on trends analysis (table 3). In this table we can find target

values related to 15 and 25 percentiles and finally proposal for the values to

agree.

4. In the table 4 we can find preliminary assessment of GES/subGES achievement

and the littering status in the Baltic Sea for each of categories in basin wide

national waters in 2016 as prepared on the basis of proposed target values and

contamination (littering) ratio (see below).

Categories Proposed target values for GES

Artificial polymer materials 9

Rubber 1

Paper/cardboard 1

Cloth/textile 1

Processed/worked wood 1

Metal 1

Glass/ceramics 1

Sum 15

Contamination ratio Status

WS = Mean/Target value 0 < WS < = 0.5 Very good 0.5 < WS < = 1 Good 1 < WS < = 5 Moderate 5 < WS < = 10 Poor 10 < WS Bad

At the moment, an assessment for Estonian and Latvian beaches in 2016 is not

available.

Annex 3 - Analysis of beach litter data and initial proposal to define a baseline for beach litter

The preliminary beach litter data analysis of the Baltic Sea Region and the basins for

determination of a baseline and target values for GES assessment.

beach litter

Table 1. All Baltic countries aggregated data

Valid N

Mean Confidence -95%

Confidence +95%

Sum Minimum Maximum Lower percentile 25

Upper percentile

75

Percentile 15

Percentile 30

Std.Dev.

Artificial polymer materials 779 51.5 43.8 59.2 40128.4 0.0 1440.0 6.3 46.0 4.0 8.0 109.3 Rubber 779 1.7 1.4 2.0 1299.1 0.0 60.9 0.0 2.0 0.0 0.0 4.2 Cloth/textile 779 1.4 1.1 1.8 1124.5 0.0 86.0 0.0 1.0 0.0 0.0 4.4 Paper/cardboard 779 2.6 2.2 3.1 2043.3 0.0 96.0 0.0 2.3 0.0 0.0 6.4 Processed/worked wood 779 3.6 2.7 4.4 2795.3 0.0 175.1 0.0 2.0 0.0 0.0 12.0 Metal 778 3.9 3.3 4.6 3046.9 0.0 169.0 0.0 4.0 0.0 0.3 9.4 Glass/ceramics 779 3.9 3.2 4.5 3001.5 0.0 115.0 0.0 3.4 0.0 0.2 8.7 Sum of all catergories 779 68.6 59.5 77.7 53439.0 0.0 1571.0 11.0 65.0 6.6 12.6 129.4

Table 2. All Baltic countries yearly aggregated data

Year Valid N


Confidence

+95%

Sum Minimum Maximum Lower percentile

25

Upper percentile

75

Percentile 15

Percentile 30

Std.Dev.

Artificial polymer materials

2015 241 38.6 27.7 49.6 9314.6 0.0 803.0 5.0 31.0 3.1 6.3 86.7

Rubber 2015 241 1.2 0.9 1.5 292.7 0.0 26.0 0.0 1.0 0.0 0.0 2.5 Cloth/textile 2015 241 1.0 0.7 1.3 243.7 0.0 24.0 0.0 1.0 0.0 0.0 2.4 Paper/cardboard 2015 241 2.1 1.5 2.6 496.2 0.0 33.1 0.0 2.2 0.0 0.0 4.0 Processed/worked wood

2015 241 3.2 1.8 4.6 760.8 0.0 150.0 0.0 2.0 0.0 0.0 11.1

Metal 2015 240 2.5 2.0 3.0 603.4 0.0 25.0 0.0 3.0 0.0 0.1 3.9 Glass/ceramics 2015 241 2.8 2.0 3.6 669.8 0.0 45.0 0.0 2.4 0.0 0.0 6.2 sum 2015 241 51.4 38.9 63.8 12381.4 0.0 861.0 9.6 46.4 5.2 11.0 98.2 Artificial polymer materials

2016 132 42.7 29.6 55.7 5633.5 0.0 480.7 5.6 44.0 3.6 7.0 75.8

Rubber 2016 132 0.6 0.4 0.8 80.1 0.0 5.0 0.0 0.8 0.0 0.0 1.1 Cloth/textile 2016 132 0.9 0.5 1.2 114.3 0.0 16.0 0.0 1.0 0.0 0.0 2.1 Paper/cardboard 2016 132 2.7 1.5 3.8 352.1 0.0 53.6 0.0 2.1 0.0 0.0 6.6 Processed/worked wood

2016 132 4.6 1.6 7.6 605.3 0.0 175.1 0.0 2.0 0.0 0.1 17.2

Metal 2016 132 3.9 2.6 5.3 516.5 0.0 50.0 0.2 4.0 0.0 0.3 7.9 Glass/ceramics 2016 132 3.7 1.6 5.7 486.5 0.0 115.0 0.0 2.0 0.0 0.2 11.9 sum 2016 132 59.0 42.5 75.5 7788.2 0.0 532.0 9.2 62.3 5.4 11.3 95.6 Artificial polymer materials

2014 175 51.9 32.4 71.5 9089.8 0.0 1440.0 6.3 46.0 3.0 8.0 131.

3 Rubber 2014 175 2.2 1.3 3.1 383.9 0.0 60.9 0.0 2.0 0.0 0.0 5.9 Cloth/textile 2014 175 1.4 0.9 1.9 247.8 0.0 26.0 0.0 1.0 0.0 0.0 3.3 Paper/cardboard 2014 175 2.2 1.5 2.9 388.0 0.0 37.3 0.0 2.0 0.0 0.0 4.5 Processed/worked wood

2014 175 2.9 1.3 4.5 500.7 0.0 113.0 0.0 1.3 0.0 0.0 10.7

Metal 2014 175 3.1 2.3 3.9 535.6 0.0 39.0 0.0 4.0 0.0 0.1 5.4 Glass/ceramics 2014 175 4.4 3.1 5.7 774.0 0.0 55.0 0.0 5.0 0.0 0.1 8.7

Year Valid N


Confidence

+95%

Sum Minimum Maximum Lower percentile

25

Upper percentile

75

Percentile 15

Percentile 30

Std.Dev.

sum 2014 175 68.1 45.9 90.3 11919.8 0.2 1571.0 10.0 64.0 6.5 13.0 148.

6 Artificial polymer materials

2012 90 89.2 59.8 118.6 8026.1 0.0 785.0 9.0 114.5 6.0 12.0 140.


2012 90 4.5 2.1 6.8 402.6 0.0 83.0 0.0 4.0 0.0 0.0 11.2


sum 2012 90 117.5 81.3 153.7 10574.4 0.0 907.0 13.0 161.0 9.0 22.3 173.

0 Artificial polymer materials

2013 141 57.2 38.4 76.0 8064.4 0.0 907.0 9.4 57.0 5.0 11.0 113.


2013 141 3.7 2.1 5.3 525.9 0.0 75.0 0.0 2.7 0.0 0.0 9.7


Sum 2013 141 76.4 53.3 99.6 10775.3 0.0 982.0 13.5 79.0 11.0 18.0 139.

1

Fig. 1 Temporal changes of yearly mean of artificial polymer materials per 100m

Fig. 2 Temporal changes of yearly mean of rubber per 100m

Mean = 89,3921-11,1545*x

2012 2013 2014 2015 2016

Year

20

40

60

80

100

120

140

Art

ifici

al p

oly

me

r m

ate

rials

Artificial polymer materials: F(4;774) = 3,878; p = 0,0040;KW-H(4;779) = 24,7185; p = 0,00006

Mean Mean±0,95 Conf. Interval

Mean = 3,2369-0,4927*x

2012 2013 2014 2015 2016

Year

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

Ru

bb

er

Rubber: F(4;774) = 5,3196; p = 0,0003;KW-H(4;779) = 11,1743; p = 0,0247


Fig. 3 Temporal changes of yearly mean of cloth/textiles per 100m

Fig. 4 Temporal changes of yearly mean of paper/cardboard per 100m

Mean = 3,0413-0,4805*x

2012 2013 2014 2015 2016

Year

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

4,5C

loth

/te

xtile

Cloth/textile: F(4;774) = 3,7339; p = 0,0051;KW-H(4;779) = 9,0443; p = 0,0600


Mean = 4,2433-0,4591*x

2012 2013 2014 2015 2016

Year

1

2

3

4

5

6

7

8

Pap

er/c

ardb

oard

Paper/cardboard: F(4;774) = 2,8812; p = 0,0219;KW-H(4;779) = 1,5574; p = 0,8164


Fig. 5 Temporal changes of yearly mean of processed/worked wood per 100m

Fig. 6 Temporal changes of yearly mean of metal per 100m

Mean = 3,8659-0,0348*x

2012 2013 2014 2015 2016

Year

1

2

3

4

5

6

7

8

Pro

cess

ed/w

ork

ed w

ood

Processed/worked wood: F(4;774) = 0,588; p = 0,6714;KW-H(4;779) = 6,378; p = 0,1726


Mean = 7,4298-1,0007*x

2012 2013 2014 2015 2016

Year

1

2

3

4

5

6

7

8

9

10

11

Me

tal

Metal: F(4;773) = 5,8812; p = 0,0001;KW-H(4;778) = 19,9615; p = 0,0005


Fig. 7 Temporal changes of yearly mean of glass/ceramics per 100m

Fig. 8 Temporal changes of yearly mean of all litter per 100m

Mean = 5,8786-0,5794*x

2012 2013 2014 2015 2016

Year

1

2

3

4

5

6

7

8

9

Gla

ss/c

era

mic

s

Glass/ceramics: F(4;774) = 2,683; p = 0,0305;KW-H(4;779) = 17,2597; p = 0,0017


Mean = 117,089-14,2028*x

2012 2013 2014 2015 2016

Year

20

40

60

80

100

120

140

160

sum

suma: F(4;774) = 4,6754; p = 0,0010;KW-H(4;779) = 23,0503; p = 0,0001


Table 3. Determination of target values

Number of items per 100 m

6 - years reduction

Target value based

on trends

analysis

Target value

based on 15th

percentile

target value

based on 25th

percentile

Combined target values

Artificial polymer materials 60% 20 4 6,3 9

Rubber - 1 0 0 1

Cloth/textile - 1 0 0 1

Paper/Cardboard - 1 0 0 1

Processed/worked wood - 1 0 0 1

Metal - 1 0 0 1

Glass/ceramics - 1 0 0 1

Sum of all categories items 60% 26 6,6 11 15

Table 4. An assessment of the Baltic basin wide status of the beach litter per 100m in 2016

Categories HELCOM subasin Mean GES/subGes

Contamination ratio


Bornholm Basin Polish Coastal waters 35,7 3,97

Rubber Bornholm Basin Polish Coastal waters 0,2 0,16

Paper/cardboard Bornholm Basin Polish Coastal waters 1,0 0,95

Cloth/textile Bornholm Basin Polish Coastal waters 0,3 0,27 Processed/worked wood

Bornholm Basin Polish Coastal waters 1,5 1,54

Metal Bornholm Basin Polish Coastal waters 4,7 4,70

Glass/ceramics Bornholm Basin Polish Coastal waters 2,0 1,96

All categories Bornholm Basin Polish Coastal waters 45,3 3,02


Eastern Gotland Basin Polish Coastal waters

8,8 0,98

Rubber Eastern Gotland Basin Polish Coastal waters

0,4 0,40

Paper/cardboard Eastern Gotland Basin Polish Coastal waters

1,1 1,13

Cloth/textile Eastern Gotland Basin Polish Coastal waters

1,4 1,35

Processed/worked wood

Eastern Gotland Basin Polish Coastal waters

1,1 1,08

Metal Eastern Gotland Basin Polish Coastal waters

1,3 1,30

Glass/ceramics Eastern Gotland Basin Polish Coastal waters

1,2 1,15

All categories Eastern Gotland Basin Polish Coastal waters

15,2 1,01


Gdansk Basin Polish Coastal waters 9,7 1,08


Contamination ratio

Rubber Gdansk Basin Polish Coastal waters 0,2 0,20

Paper/cardboard Gdansk Basin Polish Coastal waters 0,4 0,44

Cloth/textile Gdansk Basin Polish Coastal waters 0,3 0,28 Processed/worked wood

Gdansk Basin Polish Coastal waters 7,7 7,72

Metal Gdansk Basin Polish Coastal waters 1,1 1,08

Glass/ceramics Gdansk Basin Polish Coastal waters 1,3 1,30

All categories Gdansk Basin Polish Coastal waters 20,7 1,38


Bothnian Bay Swedish Coastal waters 35,8 3,98

Rubber Bothnian Bay Swedish Coastal waters 0,3 0,33

Paper/cardboard Bothnian Bay Swedish Coastal waters 4,8 4,78

Cloth/textile Bothnian Bay Swedish Coastal waters 0,0 0,00 Processed/worked wood

Bothnian Bay Swedish Coastal waters 3,3 3,33

Metal Bothnian Bay Swedish Coastal waters 4,4 4,35

Glass/ceramics Bothnian Bay Swedish Coastal waters 0,0 0,00

All categories Bothnian Bay Swedish Coastal waters 48,6 3,24


Northern Baltic Proper Swedish Coastal waters

10,3 1,15

Rubber Northern Baltic Proper Swedish Coastal waters

0,3 0,33

Paper/cardboard Northern Baltic Proper Swedish Coastal waters

0,0 0,00

Cloth/textile Northern Baltic Proper Swedish Coastal waters

0,7 0,67


Northern Baltic Proper Swedish Coastal waters

0,0 0,00

Metal Northern Baltic Proper Swedish Coastal waters

2,3 2,33

Glass/ceramics Northern Baltic Proper Swedish Coastal waters

0,0 0,00

All categories Northern Baltic Proper Swedish Coastal waters

13,7 0,91


Western Gotland Basin Swedish Coastal waters

4,4 0,49

Rubber Western Gotland Basin Swedish Coastal waters

0,0 0,00

Paper/cardboard Western Gotland Basin Swedish Coastal waters

0,0 0,00

Cloth/textile Western Gotland Basin Swedish Coastal waters

0,0 0,00


Western Gotland Basin Swedish Coastal waters

0,3 0,33

Metal Western Gotland Basin Swedish Coastal waters

0,0 0,03

Glass/ceramics Western Gotland Basin Swedish Coastal waters

0,0 0,00

All categories Western Gotland Basin Swedish Coastal waters

4,8 0,32


Eastern Gotland Basin Swedish Coastal waters

65,4 7,26

Rubber Eastern Gotland Basin Swedish Coastal waters

1,3 1,33


Contamination ratio

Paper/cardboard Eastern Gotland Basin Swedish Coastal waters

3,1 3,05

Cloth/textile Eastern Gotland Basin Swedish Coastal waters

2,8 2,83


Eastern Gotland Basin Swedish Coastal waters

8,3 8,33

Metal Eastern Gotland Basin Swedish Coastal waters

17,3 17,27

Glass/ceramics Eastern Gotland Basin Swedish Coastal waters

3,5 3,50

All categories Eastern Gotland Basin Swedish Coastal waters

101,7 6,78


Bornholm Basin Swedish Coastal waters

11,0 1,22

Rubber Bornholm Basin Swedish Coastal waters

0,3 0,33

Paper/cardboard Bornholm Basin Swedish Coastal waters

2,3 2,33

Cloth/textile Bornholm Basin Swedish Coastal waters

0,7 0,67


Bornholm Basin Swedish Coastal waters

0,7 0,67

Metal Bornholm Basin Swedish Coastal waters

0,7 0,67

Glass/ceramics Bornholm Basin Swedish Coastal waters

1,7 1,67

All categories Bornholm Basin Swedish Coastal waters

17,3 1,16


Arkona Basin Swedish Coastal waters 17,7 1,96

Rubber Arkona Basin Swedish Coastal waters 1,7 1,67

Paper/cardboard Arkona Basin Swedish Coastal waters 0,7 0,67

Cloth/textile Arkona Basin Swedish Coastal waters 1,3 1,33 Processed/worked wood

Arkona Basin Swedish Coastal waters 1,3 1,33

Metal Arkona Basin Swedish Coastal waters 2,4 2,40

Glass/ceramics Arkona Basin Swedish Coastal waters 2,0 2,00

All categories Arkona Basin Swedish Coastal waters 27,1 1,80


The Sound Swedish Coastal waters 209,6 23,29

Rubber The Sound Swedish Coastal waters 2,7 2,67

Paper/cardboard The Sound Swedish Coastal waters 11,0 11,00

Cloth/textile The Sound Swedish Coastal waters 5,3 5,33 Processed/worked wood

The Sound Swedish Coastal waters 4,3 4,33

Metal The Sound Swedish Coastal waters 5,7 5,67

Glass/ceramics The Sound Swedish Coastal waters 1,7 1,67

All categories The Sound Swedish Coastal waters 240,2 16,02


Kattegat Swedish Coastal waters 4,7 0,52

Rubber Kattegat Swedish Coastal waters 0,0 0,00

Paper/cardboard Kattegat Swedish Coastal waters 0,1 0,07

Cloth/textile Kattegat Swedish Coastal waters 0,0 0,00


Contamination ratio


Kattegat Swedish Coastal waters 0,3 0,33

Metal Kattegat Swedish Coastal waters 0,0 0,00

Glass/ceramics Kattegat Swedish Coastal waters 0,3 0,33

All categories Kattegat Swedish Coastal waters 5,4 0,36


Arkona Basin Danish Coastal waters 91,7 10,19

Rubber Arkona Basin Danish Coastal waters 2,2 2,17

Paper/cardboard Arkona Basin Danish Coastal waters 2,3 2,33

Cloth/textile Arkona Basin Danish Coastal waters 0,5 0,50 Processed/worked wood

Arkona Basin Danish Coastal waters 3,3 3,33

Metal Arkona Basin Danish Coastal waters 5,3 5,33

Glass/ceramics Arkona Basin Danish Coastal waters 33,8 33,83

All categories Arkona Basin Danish Coastal waters 139,2 9,28


Kattegat Danish Coastal waters 59,3 6,58

Rubber Kattegat Danish Coastal waters 0,5 0,50

Paper/cardboard Kattegat Danish Coastal waters 2,8 2,75

Cloth/textile Kattegat Danish Coastal waters 1,0 1,00 Processed/worked wood

Kattegat Danish Coastal waters 3,5 3,50

Metal Kattegat Danish Coastal waters 2,0 2,00

Glass/ceramics Kattegat Danish Coastal waters 1,0 1,00

All categories Kattegat Danish Coastal waters 70,0 4,67


Arkona Basin German Coastal waters 15,3 1,70

Rubber Arkona Basin German Coastal waters 0,3 0,33

Paper/cardboard Arkona Basin German Coastal waters 0,0 0,00

Cloth/textile Arkona Basin German Coastal waters 0,7 0,67 Processed/worked wood

Arkona Basin German Coastal waters 0,3 0,33

Metal Arkona Basin German Coastal waters 0,3 0,33

Glass/ceramics Arkona Basin German Coastal waters 0,7 0,67

All categories Arkona Basin German Coastal waters 17,7 1,18


Mecklenburg Bight German Coastal waters

20,0 2,22

Rubber Mecklenburg Bight German Coastal waters

1,0 1,00

Paper/cardboard Mecklenburg Bight German Coastal waters

4,0 4,00

Cloth/textile Mecklenburg Bight German Coastal waters

1,0 1,00


Mecklenburg Bight German Coastal waters

1,0 1,00

Metal Mecklenburg Bight German Coastal waters

4,0 4,00

Glass/ceramics Mecklenburg Bight German Coastal waters

3,0 3,00

All categories Mecklenburg Bight German Coastal 34,0 2,27


Contamination ratio

waters


Bornholm Basin German Coastal waters

45,0 5,00

Rubber Bornholm Basin German Coastal waters

4,0 4,00

Paper/cardboard Bornholm Basin German Coastal waters

6,0 6,00

Cloth/textile Bornholm Basin German Coastal waters

3,0 3,00


Bornholm Basin German Coastal waters

4,0 4,00

Metal Bornholm Basin German Coastal waters

1,0 1,00

Glass/ceramics Bornholm Basin German Coastal waters

0,0 0,00

All categories Bornholm Basin German Coastal waters

63,0 4,20


Northern Baltic Proper Finnish Coastal waters

75,0 8,33

Rubber Northern Baltic Proper Finnish Coastal waters

1,2 1,17

Paper/cardboard Northern Baltic Proper Finnish Coastal waters

7,0 6,97

Cloth/textile Northern Baltic Proper Finnish Coastal waters

2,1 2,07


Northern Baltic Proper Finnish Coastal waters

9,4 9,36

Metal Northern Baltic Proper Finnish Coastal waters

4,6 4,60

Glass/ceramics Northern Baltic Proper Finnish Coastal waters

5,3 5,31

All categories Northern Baltic Proper Finnish Coastal waters

104,5 6,97


Gulf of Finland Finnish Coastal waters 85,3 9,48

Rubber Gulf of Finland Finnish Coastal waters 0,3 0,29

Paper/cardboard Gulf of Finland Finnish Coastal waters 2,3 2,29

Cloth/textile Gulf of Finland Finnish Coastal waters 0,1 0,14 Processed/worked wood

Gulf of Finland Finnish Coastal waters 10,1 10,14

Metal Gulf of Finland Finnish Coastal waters 5,0 5,00

Glass/ceramics Gulf of Finland Finnish Coastal waters 6,0 6,00

All categories Gulf of Finland Finnish Coastal waters 109,1 7,27


Bothnian Bay Finnish Coastal waters 24,3 2,70

Rubber Bothnian Bay Finnish Coastal waters 0,2 0,20

Paper/cardboard Bothnian Bay Finnish Coastal waters 15,9 15,94

Cloth/textile Bothnian Bay Finnish Coastal waters 1,2 1,18 Processed/worked wood

Bothnian Bay Finnish Coastal waters 1,7 1,74

Metal Bothnian Bay Finnish Coastal waters 4,2 4,23

Glass/ceramics Bothnian Bay Finnish Coastal waters 1,9 1,87

All categories Bothnian Bay Finnish Coastal waters 49,5 3,30

Annex 4 - Proposal for baseline and GES analysis of litter on the seafloor Interrim report 170316 Per Nilsson

Data availability a) ICES has added a new output format for DATRAS litter data, making it easier to work

withb) Denmark has found a solution for the format of some old DK data, and will upload

them to the ICES DATRAS database within a couple of weeksc) This means that analyses on the full dataset will start in early april

Proposed analyses Baselines

Variable Unit Temporal scale Spatial scale

Total number of items Items/km2 Individual years + period 2012-2016

Sub-regions combined

Total number in main material categories Items/km2 Individual years + period 2012-2016


Total number of items Items/km2 Individual years + period 2012-2016

Individual sub-regions

Total number in main material categories Items/km2 Individual years + period 2012-2016


Proportions of different material categories

Percent Individual years + period 2012-2016



Percent Individual years + period 2012-2016


Temporal trends Variable Unit Temporal scale Spatial scale Statistical method

Total number of items Items/km2 Time trend 2012-2016 Sub-regions combined Regression/ correlation

Total number main material categories Items/km2 Time trend 2012-2016 Individual sub-regions Regression/ correlation

Total numer of items Items/km2 Time trend 2012-2016 Sub-regions combined Regression/ correlation

Total number main material categories Items/km2 Time trend 2012-2016 Individual sub-regions Regression/ correlation


Percent Time trend 2012-2016 Sub-regions combined Regression/ correlation


Percent Time trend 2012-2016 Individual sub-regions Regression/ correlation

Geographical analyses • Maps of surveys (Images + shape-files) • Representativity analysis hauls per sub-region (number of hauls /km2/region)• Representativity analysis hauls per bottom type, using e.g Balance or EUNIS classification.(number of hauls /km2/bottom type)

Other Statistical Analyses • Comparisons among sub-regions – amounts and proportions? • Statistiical analysis of number and composition per bottom type? • Comparison spring-autumn surveys? Work so far I have tested all the suggested analyses suggested above on DATRAS data retrieved late february 2017, but I will wait for the Danish supplementary data to do the “real” analysis.

Documents

Memo of the on-line meeting of the HELCOM EN … LITTER-92...The Meeting agreed that the HELCOM EN-Marine Litter will work on the treatment of national data to identify total number