Pollution

Key messages related to Ecological Objectives 5 and 9

Quality status assessments of the Mediterranean regarding Common Indicators of Ecological Objectives 5 and 9

Assessment of IMAP Common Indicators 13 and 14 (Ecological Objective 5)

263. In the region of Mediterranean Sea, four main sub-regions have been recognized for practical reasons and for the purpose of the UNEP/MAP 2011 Initial Integrated Assessment and the Med QSR 2017 assessment, namely: the Western Mediterranean Sea, the Adriatic Sea, the Central Mediterranean, and the Aegean and Levantine Seas in the Eastern Mediterranean part. The sub- divisions (i.e., subareas/seas) for IMAP Pollution Cluster have been initially identified according to availability of database sources for the purpose of development of the assessment criteria for pollution and the assessments within the preparation of the 2017 MED QSR.

264. Sub-divisions were further analyzed to support optimal application of the assessment criteria in the four Mediterranean sub-regions by considering data aggregation for update of the assessment criteria, as well as relevant sources. The nesting scheme of the Mediterranean sub-regions and sub- divisions aggregation is as follows: (i) coastal/ onshore waters; (ii) national sub-divisions; (iii) regional sub-divisions; (iv) sub-regions; (v) Mediterranean Region.

265. The distribution of the assessment methodologies used for assessment of IMAP CIs 13, 14, 17, 18, 19, 20, 21, as well as for assessment of IMAP Candidate Common Indicators 26 and 27 in the four Mediterranean sub-regions and related sub-divisions is shown in Table 3.1.2.1.

289. Upon setting the reference conditions and the G/M threshold, each observation point, or area were classified in good or non- good status , by comparing the value of the indicator i.e., the satellite derived Chla to the G/M threshold, i.e. the back transformed 85th percentile of normalized distribution.

290. The results of CI 14 assessment using the satellite derived Chla data are presented in Tables 3.1.3.1.3.a. and 3.1.3.1.4.a., and Figure LEVS 3.1.3.1.5.E. The good status corresponds to the RC conditions, as well as to the values below the 85th percentile of normalized distribution set as good/non good statusboundary (i.e. blue coloured cells in the last column of Tables 3.1.3.1.3.a and 3.1.3.1.4.a). The good status corresponds to the class above G/M boundary limit (i.e. red coloured cell in the last column of Table 3.1.3.1.4.a.).

291. The assessment results show that all evaluated assessment zones can be considered in good status regarding assessment of the satellite derived Chla data. Further to good status assigned to the assessment zones, it can be preliminary found that only 1 out of 18 subSAUs is in non-good status. However, it must be noted that the present subSAUs are set at an insufficient level of fineness for a reliable assessment (Table 1.3.1.4 and Figure LEVS 3.1.3.1.5.E). This subSAU in non-good status is located in the OW in the southern part of the Eastern Levantine Sea. The local sources of pollution are probably the main driver contributing to the weakened status of this subSAU.

292. In addition, available literature indicates waters in front of Mersin and in the Iskenderun Bay as impacted areas. A slight impact can also be identified along the coast of Israel and in the OW in the southern part of the Eastern Levantine Sea, as well as in front of Port Said and Alexandria. The influence of the Nile River through the river Delta is weak and confirms the changes in the area caused by construction of the Aswan dam. There is also an indication of a coastal impact in the Tobruk area in the waters of Libya.

Figure AEL 3.1.3.1.5.E: The assessment results for CI 14 in the Levantine Sea Sub-division by applying he simplified G/M method at the level of SAUs

293. The assessment results show that all three evaluated assessment zones can be considered in good status regarding assessment of the satellite derived Chla data. Further to this likely good status assigned to the assessment zones, it can be preliminary found that only 2 out of 16 subSAUs are in noon- good status. However, it must be noted that the present subSAUs are set at an insufficient level of fineness for a reliable assessment (Table 3.1.3.1.4.b, and Figure AEL 3.1.3.1.5.E). The following two non-good status subSAUs are located in the CA SAU in the waters of Turkiye in the Aegean Sea: EGE09 (Izmir Bay) and EGE_C (coast strip south of Izmir Bay). The local sources of pollution are probably the main driver contributing to the weakened status of these two subSAUs.

294. In addition, available literature indicates the presence of drivers and pressures with impacts related to eutrophication in the areas as elaborated here-below.

295. In the Saronikos Gulf and Elfesis Bay, there is evidence of a few following drivers and pressures: i) extensive urbanization in the metropolitan areas of Athens and Piraeus hosting about 1/3 of the Greek population; ii) port activities and maritime traffic (Piraeus port); and iii) industries located in the coastal area of the Elefsis Bay, such as oil refineries, steel and cement industries, and Since 2012, the eastern Elefsis Bay receives treated domestic and industrial wastewaters from the Thriasio wastewater treatment plant. The small island of Psyttaleia hosts the wastewater treatment plant of metropolitan Athens, however with pre-treatment, primary and secondary treatment, including biological nitrogen removal, and sludge treatment. Treated wastewaters are discharged into the Inner Saronikos Gulf via a system of three pipelines to the south of the island, at 62m depth (Karageorgis et al., 2020 and references therein).

296. Similarly, the national assessment by applying the NEAT tool to Saronikos Gulf⁵⁵ classified this area into good status, with the pelagic habitat components contributing strongly to its overall environmental status. Sediment, benthic fauna and vegetation, mammals and alien species were the most impacted ecological components in Saronikos Gulf. The most affected areas, Elefsis Bay and Psittalia (wastewater submarine outfall), were assessed as in poor and moderate status, respectively.

297. There are also other areas where certain impacts are registered. In the Thessaloniki Bay, these are the Thessaloniki harbour, impacted by industrial, treated or partly treated sewage discharges; the Inner Thermaikos Gulf impacted by agricultural discharges from the heavily polluted Axios River, and fish and shellfish mariculture; as well as the Evoikos Gulf impacted by agriculture, mariculture, and industry. Industrial discharges, port activities, sewage discharges, aquaculture activities, and fishing are the most important pressures affecting the coastal areas of Greece. In fact, mariculture seems to have the highest impacts, and is followed by fishing, other activities and industrial discharges (Pavlidou et al., 2015).

298. A review of the existing pressures and assessment was provided by The analysis indicated the following drivers and pressures relevant to EO5: i) tourism population density; ii) urban wastewater; iii) agriculture; and iv) port operations, especially in Port of Izmir.

299. As for the Levantine Sea Sub-division, the results of the present CI 14 assessment in the Aegean Sea Sub-division represents only an indication of possible good/non-good status at the level of sub SAUs, whereby they are not set at the same level of spatial finesse.

Figure AEL 3.1.3.1.5.E: The assessment results for CI 14 in the Aegean Sea Sub-division by applying the simplified G/M method on the satellite-derived COPERNICUS data at the level of subSAUs

330. The overall status for CIs 13 and 14 on the sub-division level for SAS, CI 14 regarding the three parameters assessed i.e. TP, DIN and chlorophyll a, is in GES. Four out of 14 SAUs are classified under Good conditions the rest under High. The Good status is observed along the Italian coast

Figure ADR 3.1.3.2.6.E: The NEAT assessment results for CIs 13 and 14 in the Adriatic Sea sub- region. Aggregation of all contaminants per sub-SAU. Blank area corresponds to not evaluated subSAUs due to no available data or not established monitoring.

350. The assessment results show that all evaluated assessment zones can be considered likely in good status regarding the assessment of the satellite-derived Chl a Further to this good status assigned to the assessment zones, it can be preliminarily found that 7 out of 36 subSAUs are likely in non-good status. However, it must be noted that the subSAUs are set at an insufficient level of fineness for a reliable assessment (Tables 3.1.3.3.3 and 3.1.3.3.4). The likely non-good status subSAUs (GREA, GREAMB, GREPAT, LBY_E, LBY_W, LBY_W; TUN_B) are in the Eastern and the Southern parts of the CEN Sub-region.

351. The subSAU GREAMB is located in Ambracian Gulf and subSAU GREPAT in Gulf of Patras. These sites were also classified as moderate or a poor status by Greek research studies⁶¹. In subSAU GREAMB, the highest GM value of Chl a was observed (4,8 µg/L). The Northern subSAU GREA is probably influenced by the local sources of pollution (Igumenitsa port and intense aquaculture). The level of the finesse of the subSAU definition contributes to the lower confidence of the assessment findings, i.e., the assessment of the larger area is less confident. A finer-designed approach will contribute to a more accurate assessment of the local processes, contributing to the understanding of the very localized problem.

352. Along the coast of Libya, the marine waters impacted by eutrophication are located in the western part of Libyan OW (subSAU LBYW) and in the eastern part of CW (subSAU LBYE). It must be noticed that the G/M threshold for the Libyan waters is very low which questions the evaluation of the Southern part of the CEN Sub-region. The western part of the coast of Libya is influenced by the waters coming from the Gulf of Gabes where human activities contribute to the impacts of eutrophication⁶². The local influence of Tripoli should also be taken into account.

353. Further to calculations undertaken for the Gulf of Gabes, the subSAU TUNB located in CW can be indicated as an area in good status. However, it must be recognized that using the 50^th percentile for the development of the assessment criteria is not applicable in heavily impacted areas, such as the Gulf of Gabes. Therefore, an adjustment by using the 25th percentile of the calculated values resulted in the classification of the subSAU TUNB in non-good status, as also recognized in the existing literature.

354. The results of the present CI 14 assessment in the Central Mediterranean Sea Sub-region represent only an indication of possible good/non-good status at the level of the subSAUs, whereby they are not set at the same level of spatial finesse.

Figure CEN 3.1.3.3.3.E: The assessment results for CI 14 in the CEN Sub-region by applying the simplified G/M method at the level of subSAUs.

392. The results of CI 14 assessment using the satellite-derived Chl a data in the Central WMS Sub-division i.e., in the French waters are presented in Tables 3.1.3.4.6 and 3.1.3.4.7, and Figure WMS 1.3.4.4.E. Despite good status assigned to the assessment zones, it should be noted that in the French CW assessment zone, for which the finest SAUs were defined in line with WFD, one out of the 46 SubSAU namely EC03b (Golfe de Porto Vecchio) was in non-good status though the low number of pixels (n=13) included in the assessment reflects the high uncertainty associated to mean computation. The Gulf of Porto Vecchio is a small embayment characterised by the presence of both muddy and sandy sediments. In such shallow coastal environments, resuspension processes complexify water optical properties leading to overestimation of Chl a concentration when using satellite-derived products (Gohin et al. 2020⁷⁵). Also, Ganzin et al. (2010) observed that satellite- derived products in the area can be 30% higher than the mean values computed over a 6-year period. Water renewal is also very low in this area making it more sensitive to pressures and basin derived inputs.

393. Six out of 46 SubSAUs were above the G/M threshold (oN85) but were still classified in good status given the calculated values were very close to the G/M threshold (oN85), and taking also account of the water masses features. For the present assessment, the national G/nonG back transformed values (90^th percentile > GM, based on in situ measurements, corresponding to UNEP/MAP Decision 22/7) were also Amongst these 6 water masses, the four are located in the FRD-E assessment zone namely DC04 (Golfe de Fos), DC06A (Petite Rade de Marseille), DC07I (Cap de L’estéral – Cap de Brégançon) and DC08B (Ouest Fréjus- Saint Raphaël). The two revised water masses are located in Corsica Island (FRE) and correspond to EC04B (Golfe D’Ajaccio) and EC01C (Golfe de Saint Florent). Water mass DC04 (Golfe de Fos) is a highly modified water mass characterised by a high spatial heterogeneity in Chl a distribution. For other water masses (DC06A, DC07I and DC08B; EF04B and EC01C in Corsica), hydrodynamic studies revealed a very low annual renewal of water masses thus explaining slight accumulation of low phytoplankton biomass levels (Ganzin et al. 2010⁷⁶).

394. The results of the present CI 14 assessment in the French part of the CWMS represent only an indication of possible good/non-good status at the level of the subSAUs, whereby subSAUs are not set at the same level of spatial finesse. Namely, the reliability of the assessment was negatively affected by the lack of data reported by the CPs in IMAP IS, and therefore impossibility to use the IMAP NEAT GES assessment as applied to the Adriatic Sea Sub-region.

Figure WMS 3.1.3.4.4.E: The assessment results for CI 14 in the French waters of the CWMS.

395. The results of CI 14 assessment using the satellite-derived Chl a data in the Alboran Sea and Levantine-Balearic Subdivision of the WMA i.e., in the Spanish waters are presented in Tables 3.1.3.4.8. and 3.1.3.4.9., and Figure WMS 3.1.3.4.5.E.

396. The evaluation was performed on 70 out of 149 Despite good status assigned to the assessment zones, it should be noted that in the CW assessment zone, for which the finest subSAUs were defined in line with WFD, there are 8 out of 70 subSAUs which are in non-good status.

397 .These 8 subSAUs are located as follows: one subSAU close to the Mar Menor (ES070MSPF010300030) one subSAU ES080MSPFC017 of the Segura River mouth; two subSAUs (ES080MSPFC006 and ES080MSPFC0081) near Valencia; two subSAUs ES080MSPFC001 and ES100MSPFC32 close to the Ebro River mouth; one subSAU ES100MSPFC3 close to the French border; and one subSAU ES110MSPFMAMCp02 on the Mallorca Island in the Alcudia Gulf.

398. The local sources of pollution are probably the main driver contributing to the weakened status of most non-good The most important problem that needs to be addressed is the non- good status in the Mallorca Island area. A more detailed analysis indicates that the ranges of observed values in the Islands area is very low 0,05-0,20 µg/L. At narrow ranges the statistics is not always performed in acceptable manner. This suggests a necessity to use the satellite-derived data in these areas with caution or different elaboration strategies need to be provided.

399. As it is explained above for setting the good/non-good boundary limit there is a slight difference between the thresholds calculated from the satellite-derived data used for the present assessment and the assessment criteria calculated from in situ measurements, which resulted in the regional assessment findings which do not fully match the eutrophication evaluation performed by Spain by applying the assessment criteria calculated from in situ measurements.

400. The results of the present CI 14 assessment in the ALB and LEV-BAL Sub-divisions of the WMS represent only an indication of possible good/non-good status at the level of subSAUs, whereby the subSAUs are not set at the same level of spatial finesse.

Figure WMS 3.1.3.4.5.E: The assessment results for CI 14 in the Alboran Sea and Levantine- Balearic Subdivision of the WMS.

401. All the SAUs assessed in the Southern part of the CWMS Sub-division were in good status (Tables 3.1.3.4.10. and 3.1.3.4.11., and Figure WMS 3.1.3.4.6.E). The non-good status which would correspond to the class above G/M boundary limit was not found in the assessment of the Southern part of WMS. It must be noted that the assessment was not possible at the level of the finest spatial assessment units i.e., subSAUs, as for other sub-divisions in the WMS, therefore, resulting in a less confidential assessment, given the absence of finer water bodies delineation and related water typology characterization.

402. The results of the present CI 14 assessment in the Southern part of the WMS represent only an indication of possible good/non-good status at the level of SAUs, whereby the SAUs are not set at the same level of spatial Namely, the reliability of the assessment was negatively affected by the lack of data reported by the CPs in IMAP IS, as well as the lack of finer water bodies delineation, and therefore impossibility to use the IMAP NEAT GES assessment as applied to the Adriatic Sea Sub- region.

403. Due to a less confidential assessment in this part of the WMS, some specific examples of drivers and pressures were mapped from the scientific literature, for example, the Oran harbor (Algeria) which receives the discharge of wastewater; the Ghazaouet harbour which is exposed to chemicals coming mainly from industrial activities; the shoreline such as Bousfer under the impact of the seawater desalination plant in Oran Bay and the Beni Saf desalination plant.

Figure WMS 3.1.3.4.6.E: The assessment results for CI 14 in the Southern Part of the CWMS.

404. Despite likely good status assigned to the assessment zones in the waters of Italy, there are 9 out of 54 subSAUs that are in non-good status (Tables 3.1.3.4.12. & 1.3.4.13, and Figure WMS 3.1.3.4.7.E).

405. These 9 subSAUs are located as follows: in front of the Arno River mouth (ITCWTCD and ITOWTCD); in front of the Tiber River mouth (ITCWLZ and ITOWLZC); close to the Napoli urban agglomeration (ITOWCMC, ITOWCMD, ITCWCMC and ITCWCMD) and SW part of Sardinia Island (ITCWSDWB). The evaluation shows the impact of the Arno and Tiber Rivers, the two main rivers in the area related to their nutrient inputs’ contribution. Both the CW and OW are under impacts of the Napoli metropolitan area (4,250,000 residents), whereby the propagation of their effects toward the north is evident due to the water circulation7⁷⁷. The local effect of the Oristano lagoon, as anthropogenically heavily impacted area, probably contributes to the weakened classification of CW in SW Sardinia Island.

406. Further to the assessment of the CW in the area of Napoli, the subSAUs ITCWCMC and ITCWCMD can be indicated as in good status. However, it must be recognized that using the 50^th percentile for the development of the assessment criteria is not applicable in heavily impacted areas, such as the heavily impacted urban coastal areas. Therefore, an adjustment by using the 25^th percentile of the calculated values resulted in the classification of the subSAUs ITCWCMC and ITCWCMD B in non- good status, as also recognized in the existing literature sources.

407. Given the significant quantum of data reported in IMAP IS for the waters of Italy, the assessment results provided by the application of the simplified G/M comparison based on the use of satellite-derived Chl a data were complemented with the assessment results derived from the application of the EQR methodology.

408. The evaluation was possible only at the subSAU level since the SAU wider area of integration does not support the evaluation of different water types which coexist in the same Specifically, the water type IIIW cannot be evaluated by applying the EQR methodology, but by providing a simple comparison of the measured concentrations to a threshold. Namely, a five classes scale could not be set for water type IIIW since the discrimination limit between the two contiguous Chl a annual G_mean values would not allow for proper and safe classification (Giovanardi et al., 2018). Therefore, the boundary values for WT III are based on the H/G values for WT II. Mixing the assessment methods is not statistically permitted.

409. The results of assessment by applying the EQR methodology are presented in Table 3.1.3.4.14, and Figures WMS 1.3.4.8.E & 3.1.3.4.9.E. The 43 subSAUs were evaluated out of the 54 subSAUs. All evaluated subSAUs were in GES with the exception of one (ITCWLZC) located in front of the Tiber River mouth indicating the influence of freshwater input of nutrients in that area. As expected, a more accurate assessment is obtained at the level of monitoring stations. The non-GES is confirmed for the Tiber River mouth, both for CW and OW which are under the impact of the Napoli metropolitan area, as well as for CW in SW Sardinia Island close to Oristano lagoon which is an anthropogenically heavily impacted area.

410. The results obtained from an application of the simplified G/M comparison assessment methodology based on the use of satellite-derived Chl a data were confirmed by an application of the EQR methodology based on in situ Chl a data reported to IMAP IS, both at the level of subSAUs and monitoring stations. This confirms the accuracy of data obtained from the remote sensing for the assessment of This also encourages future decision-making regarding inclusion of an additional sub- indicator i.e., a parameter within the monitoring of CI 14. Namely, coupling of satellite-derived Chl a data with Chl a concentrations in situ measured would greatly enhance the IMAP monitoring and assessment.

Figure WMS 3.1.3.4.7.E: The assessment results for CI 14 in the Italian waters in the Tyrrhenian Sea and the CWMS.

Assessment of IMAP Common Indicator 17 (Ecological Objective 9)

420. For each measured parameter at each station a contamination ratio (CR) was calculated. Thresholds were the updated sub-regional AEL_BACs (Table 1.4.1.2.a). CHASE+ methodology in the AEGS was provided without spatial integration and aggregation of the areas of assessment and assessment results. Instead, aggregation was possible only for TM in sediments, and only partially. A contamination score (CS) aggregating 2-3 metals was further calculated. Table 3.1.4.1.3.a. summarizes the results of the CHASE+ application.

444. For each measured parameter at each station a contamination ratio (CR) was calculated. Thresholds were the updated sub-regional AEL_BACs (Table 3.1.4.1.2.b.). CHASE+ methodology in the LEVS was provided without spatial integration and aggregation of the areas of assessment and assessment results. Instead, aggregation was possible only for TM in sediments and in barbatus. A contamination score (CS) aggregating 2-3 metals was further calculated. Table 3.1.4.1.3.b. summarizes the results of the CHASE+ application.

478. For each measured parameter at each station a contamination ratio (CR) was calculated. Thresholds were the MED_BACs as explained CHASE+ assessment methodology in the CEN was provided without spatial integration and aggregation of the areas of assessment and assessment results. Instead, aggregation was possible only for TM in sediments, and only partially. A contamination score (CS) aggregating 2-3 metals was further calculated. Table 3.1.4.2.3 summarizes the results of the CHASE+ application, while detailed calculation of the assessment results is presented in Figures CEN 3.1.4.2.1.C. – CEN 3.1.4.2.3.C.

517. The results obtained from the NEAT tool are shown below in Tables 1.4.3.4.a and 3.1.4.3.4.b. Table 3.1.4.3.4.a provides detailed assessment results on the EO9/CI 17 level per contaminant and also spatially integrated within the nested scheme at i) the IMAP national SAUs & subSAUs, as the finest level; ii) the IMAP coastal and offshore assessment zones of sub-divisions (NAS Coastal, NAS Offshore, CAS Coastal, CAS Offshore, SAS Coastal, SAS Offshore); iii) the sub-division level (NAS, CAS, SAS) and iv) the sub-regional level (Adriatic Sea).

518. At the same time aggregation of all contaminants data is done in order to obtain one chemical status value (NEAT value) for all the levels of the nesting scheme. In other words data matrix in Table 3.1.4.3.4.b. shows the results per contaminant per habitat per SAU in the finest level which are i) integrated along the nesting scheme (in columns A – I bold lines); and ii) are aggregated for all contaminants and habitats per SAU (in rows) leading to one NEAT value per SAU (column EO9). The latter is further integrated along the nesting scheme (column EO9 bold lines).

519. The NEAT tool has the possibility also to provide assessment results by aggregating data per habitat in this case sediments and biota (mussels) and then spatially integrated within the nested scheme.

520. The final integrated result per SAU (NEAT value) is the same for the two ways of assessment (i.e. per contaminants (Table 3.1.4.3.4.a) or per habitats (Table 3.1.4.3.4.b) as expected.

521. The detailed status assessment results per contaminant per SAU at the 1^st level of assessment (no aggregation or integration) show that in most cases GES conditions are achieved (High, Good status) i.e., for 80% of SAUs, which are indicated by the blue and green cells in Table 3.1.4.3.4.a; 9% are classified under the moderate status, 6% under the poor and 5% under the bad. For the sediment matrix, the highest contamination is observed from PCBs, PAHs and Hg resulting in non-GES status for 60%, 57% and 27 % of sub-SAUs respectively. For the mussels matrix, the highest contamination is observed from PCBs which results in 39% of sub-SAUs in non-GES status. In the NAS, 19% of sub-SAUs are classified as non-GES, in the CAS 12% are classified as non-GES, while in the SAS 22 % are classified as non-GEs. The most affected sub-SAUs in the NAS are HRO-0313-BAZ, HRO-0412-PULP and HRO- 0423-RILP in Croatia; Emiglia-Romana’, ‘Fruili-Venezia-Giulia-1’ and ‘Veneto-1’ in Italy. Also, offshore SAUs IT-NAS-O and MAD-Sl-MRU-12. In the CAS, most affected sub-SAUs are HRO-0313- KASP, HRO-0313-KZ, HRO-0423-KOR in Croatia. In the SAS, affected sub-SAUs are HRO-0313-ZUC and HRO-0423-MOP in Croatia; and MNE-1-N, MNE-1-C, MNE-1-S, MNE-Kotor in Montenegro which are found in moderate conditions due to impacts of several contaminants. Regarding the status of subSAU MNE-1-C, the present assessment does not match the good environmental status corresponding to the status of Marine Protected Area Katic located in this assessment unit, due to non-harmonized data reporting among the countries, and consequent non-harmonized use of data from different types of monitoring stations including hot spot stations, along with non-optimally harmonized size of spatial assessment units among the countries which resulted in inaccurately downgraded status of the small MNE-1-C assessment unit from good to moderate class.

Figure ADR 3.1.4.3.6.C: The NEAT assessment results for IMAP CI17 in the Adriatic Sea sub-region. Aggregation of all contaminants per sub-SAU. Blank area corresponds to no available data/decision or not established monitoring.

554. The assessment was conducted in the Alboran Sea subdivision (ALBS) for Cd, Hg, Pb in sediments and biota and in the TYRS for Cd, Hg, Pb, Σ16PAHs and Σ7PCBs in sediments. The simplified application of the NEAT tool (1^st level nesting) was applied for the IMAP SAUs of the CWMS for which data on contaminants exist (Cd, Hg, Pb, Σ16PAHs and Σ7PCBs in sediments and biota).

555. The results obtained from the NEAT tool using the (xBAC) threshold for the ALBS are shown below in Table 3.1.4.4.4.

556. The detailed status assessment results per contaminant show that most SAUs achieve GES conditions (high, good status) indicated by the blue and green cells. Exceptions to this are moderate classifications for SAUs MO-East-C and ALBS-ES-C for Pb in sediments, MO-Gib2-C for Cd in sediments, and SAU ALBS-ES-C for Hg in mussels.

557. The results obtained from the NEAT tool using the (xBAC) thresholds for the Tyrrhenian Sea subdivision (TYRS) are shown below in Table 3.1.4.4.5.

558. Detailed assessment results for the TYRS subdivision show that SAUs IT-TYR-1-C, IT- TYR-3-C and IT-TYR-4-C fall into moderate status regarding Cd in sediments; regarding Hg in sediments SAUs IT-TYR-1-C and IT-TYR-3-C fall into moderate and poor statuses respectively. Finally, SAU IT-TYR-4-C is classified as moderate regarding Σ7PCBs.

559. The results obtained from the simplified application of NEAT for the coastal sub-SAUs with data in the CWMS are shown below in Table 3.1.4.4.6, and Figure WMS 3.1.4.4.6.C. Detailed assessments per contaminant per SAU indicate non-GES status for several cases. In sediments, SAU ES-CWM-LEV1-C is classified under moderate status for Pb and SAU FR-CWM_E2-C under poor for Hg. The Italian SAU IT-CWM-C is classified under moderate for Cd and under poor status for Σ16PAHs and Σ7 Monitoring data for mussels show that SAU FR-CWM-E2-C is classified under moderate status for Hg and Pb and under poor for Σ16PAHs; SAUs FR-CWM-C-C and FR- CWM-W-C are classified under poor and moderate status respectively regarding Σ16PAHs.

Table 3.1.4.4.4. Status assessment results of the NEAT tool applied on the 2 levels nesting scheme in the Alboran Sea Sub-division, using the xBAC as GES-nGES threshold for the assessment of EO9/CI17. The 2^nd level of spatial integration (nesting) on the coastal zone is marked in bold. Blank cells denote absence of data. The % confidence is based on the sensitivity analysis.

Table 3.1.4.4.5. Status assessment results of the NEAT tool applied on the 2 levels nesting scheme in the Tyrrhenian Sea Sub-division, using the xBAC as GES-non GES threshold for the assessment of EO9/CI17. The 2^nd level of spatial integration (nesting) on the coastal zone is marked in bold. Blank cells denote absence of data. The % confidence is based on the sensitivity analysis.

Table 3.1.4.4.6. Status assessment results of the NEAT tool applied on the 1^st level IMAP subSAUs in the Central part of the Western Mediterranean Sea Sub-division, using the xBAC as GES-non GES threshold for the assessment of EO9/CI17. Blank cells denote absence of data. The % confidence is based on the sensitivity analysis.

560. The aggregation of the chemical parameters data per SAU leads to the NEAT value per SAU which represents the overall chemical status of the SAUs for the ALBS, as shown in Table 3.1.4.4.4. (4^th column). It is clear that all SAUs achieve High or Good status and can be considered in GES regarding trace metals. Similarly, the aggregation-integration within the nested scheme for the coastal zone of the Alboran subdivision (ALBS-C), results in Good GES status regarding trace metals (shown in bold in Table 3.1.4.4.4).

561. The integration of SAUs data per chemical parameter (Table 3.1.4.4.4., 1^st line in bold), shows that the coastal zone of the Alboran Sea (ALBS-C) achieves High or Good status regarding trace metals with the exception of Hg in mussels for which it is classified under Moderate The aggregation-integration of data for the coastal zone of the Alboran sub-division (ALBS-C) results in Good GES status regarding trace metals.

562. The results of the assessment findings for the Alboran Sea provided per contaminants of EO9/CI 17 without aggregation per habitat, i.e. sediment and biota, as presented in Table 3.1.4.4.4. Also, the final GES assessment findings for the coastal IMAP SAUs in the Alboran Sea, as provided in Table 1.4.4.4.are shown by the respective color in the map included in the following Figure WMS 3.1.4.4.3.C. The map depicts the integrated NEAT value for each SAU (i.e. aggregated value for all contaminants assessed as provided in the 4^th column of Table 3.1.4.4.4).

563. The overall status for the coastal assessment zone of the Alboran Sea is Assessment is integrated for metals in sediments and biota.

Figure WMS 3.1.4.4.3.C: The NEAT assessment results for trace metals TM in sediments and biota in the coastal assessment zone of the Alboran Sea. Assessment conducted using the xBAC GES-non GES threshold. All IMAP SAUs are in GES characterized by High or Good status. Shaded area corresponds to no available data for the assessment. An absence of some SAUs assessment might also be related to the decision of the countries to monitor areas that are found relevant for the assessment of contaminants and therefore excluding the areas where problems were not historically observed.

564. The aggregation of the chemical parameters data per SAU leads to the NEAT value per SAU which represents the overall chemical status of the SAUs in the TYRS as shown in Table 1.4.4.5 (4^th column). . All SAUs achieve High or Good status and are in GES regarding contaminants assessed. Similarly, the aggregation-integration within the nested scheme for the coastal zone of the Tyrrhenian subdivision (TYRS-C) however, results in Good GES status regarding contaminants assessed (shown in bold in Table 3.1.4.4.5.).

565. The integration of SAUs data per chemical parameter (Table 3.1.4.4.5., 1^st line in bold), shows that the coastal zone of the Tyrrhenian Sea (TYRS-C) achieves High or Good status regarding chemical contaminants assessed. Similarly, the aggregation-integration within the nested scheme for the coastal zone of the Tyrrhenian subdivision (TYRS-C) as a whole indicates it can be considered in Good GES status regarding chemical contaminants assessed (shown in bold in Table 3.1.4.4.5.).

566. The final GES assessment findings per contaminants for sediments in the coastal IMAP SAUs in the Tyrrhenian Sea, as provided in Table 1.4.4.5., are shown by the respective color in the map included in Figure WMS 3.1.4.4.4.C. The map depicts the integrated NEAT value for each SAU (i.e. aggregated value for all contaminants assessed as provided in the 4^th column of Table 3.1.4.4.5).

567. The overall status for the coastal assessment zone of the Tyrrhenian Sea is Good regarding contaminants assessed. Assessment is integrated for metals, Σ16PAHs and Σ7PCBs in sediments.

568. The aggregation of the chemical parameters data per SAU in the CWMS leads to the NEAT value per SAU which represents the overall chemical status of the SAUs, as shown in Table 1.4.4.6. (4^th column) and Figure WMS 3.1.4.4.5.C for the CWMS. All SAUs achieve High or Good status and are in GES with the exception of SAU IT-CWM-C where only sediments are monitored, and the overall status for this SAU is moderate regarding contaminants assessed.

569. Based on the availability of data for contaminants as delivered by the CPs in the Western Mediterranean Sea Sub-region, the present integrated assessment status results produced by applying the NEAT tool on the sub-divisions ALBS and TYRS (shown in Tables 3.1.4.4.4. and 1.4.4.5; ) can only be considered as an example of how the tool works. This is related to the fact that offshore SAUs lack of data, hence integration is meaningful only up to the 2^nd level, i.e. the coastal assessment zone (ALBS-coastal and TYRS-coastal) ¹⁰². Furthermore, several coastal SAUs lack data or the countries eventually decided not to monitor the areas that are found irrelevant for the assessment of contaminants and therefore excluded the areas where problems were not historically observed (blank cells in Tables 3.1.4.4.4., 3.1.4.4.5 and 3.1.4.4.6).

Figure WMS 3.1.4.4.5.C. The NEAT assessment results for trace metals TM, Σ16PAHs and Σ7PCBs in sediments and mussels in the SAUs of France and Spain and in sediments in the SAU of Italy in the CWMS. Assessment conducted using the xBAC GES-nGES threshold. All IMAP SAUs are in GES characterized by High or Good status except sediments assessment in IT-CWM-C which shows moderate status. Shaded area corresponds to no available data for the assessment. An absence of some SAUs assessment might also be related to the decision of the countries to monitor areas that are found relevant for the assessment of contaminants and therefore excluding the areas where problems were not historically observed.

Assessment of IMAP Common Indicator 19 (Ecological Objective 9)

630. The assessments of the ten subdivisions (Table 1.6.1) have been aggregated (Figure MED 3.1.6.2.), in order to obtain the assessment for the four Sub-regions of the Mediterranean Sea. This resulted in the following integrated assessment findings:

1. 1. the (Entire) Western Mediterranean Sea (WMS) Sub-region, is assigned to “Moderate”, because this category prevails in its sub-divisions (WMS and TYRS), while the “Poor” status value characterises only the Alboran Sea (ALBS);
   2. “Moderate” has been assigned to the Adriatic Sea (ADR) Sub-region, considering the prevalence of this category in its sub-divisions (MADR and SADR).
   3. “Moderate” has been assigned to the (Entire) Central Mediterranean Sea (CEN) Sub-region, by qualitative averaging of the poor status of the Ionian Sea (IONS) and the good status of the Central Mediterranean (CEN);
   4. In the case of the Aegean and Levantine Seas (AEL) Sub-region, the qualitative average evaluation led to d a” poor” status for this Sub-region.

Figure MED 3.1.6.2. Map of the integrated assessment of the marine environment status for CI 19 in the four Sub-regions of the Mediterranean Sea

Assessment of IMAP Common Indicators 18, 20 and 21 (Ecological Objective 9)

Assessment of IMAP Common Indicator 18: Level of pollution effects of key contaminants where a cause and effect relationship has been established

570. The list of bibliographic studies on biomarkers used for the preparation of the 2023 MED QSR is sorted alphabetically by country as shown in Table 3.1.5.1.

571. Based on the literature search results it can be concluded that a comparison among the studies is hard or mostly impossible. This is due to the use of different biomarkers, with different biota species, using different tissues, and different methodologies. Moreover, as found in the 2017 QSR, there are confounding factors that hinders environmental status assessment such as species, gender, maturation status, season and temperature. In addition, an inherent bias exists in publications towards studies showing an Authors and journals do not usually publish studies showing lack of effect or response. Italy submitted national data for CI 18 following the Meeting of CorMon Pollution that took place in Athens, 1-2 March 2023¹⁰³.

Results of the IMAP Environmental Assessment of CI 18 in the Mediterranean region.

572. Given GES assessment was not possible for CI 18 within the preparation of the 2023 MED QSR, the regional overall assessment findings were provided for the Mediterranean as presented here- below. Instead of providing GES /non-GES classification, the assessment for IMAP CI 18 was based on the determination of biomarkers that were affected by contamination.

573. A summary of reviewed studies is sorted by sub-regions and countries. The biomarkers that were affected by contamination are marked in red, those that were not affected are marked in green, while inconclusive results are marked in blue. Moreover, the biomarkers included in the DDs and DSs are highlighted in yellow, but with no differentiation among species or tissues studied.

a) AEL sub-region (Egypt, Türkiye)

574. One study was reviewed. The effect of TM was studied in the mussel Ruditapes decussatus collected from Alexandrian Port and Port Said (Gabr et al. 2020). The concentrations of metals were higher in samples from the Alexandrian Port (Site I). Malondialdehyde (MDA) and SOD were higher in samples from Site I while GPx, Total protein and AChE were lower. The reported values in this study are considered as basic data to monitor of the anthropogenic influence on the coastal environment.

575. Türkiye. Two studies were reviewed for Türkiye: one from 2015 and one from 2022¹⁰⁴. The effect of TM and pesticides was studied on the molluscs Mytilus galloprovincialis and decussatus collected from Homa Lagoon (Aegean Sea). The study showed marked differences on the biomarkers (CAT, SOD, GPx, and AChE) but the differences were mainly attributed to seasonal variations and to differences among the two species (Uluturhan et al. 2019). The effect of TM was also studied in the fish barbatus, B. boops and T. trachurus collected along the coast of Türkiye in the Levantine and the Aegean Seas. Correlations were found between CAT and MDA and some of the trace metals measured in the fish specimens.

b) ADR sub-region (Italy)

576. One study reported the effect of PAHs in the fish Mullus barbatus collected in the northern Adriatic (Frapiccini et al. 2020). The expressions of CAT and GST in M. barbatus were dependent on the season, lower in the winter and higher in the summer. SOD expression did not depend on the season. LPO was higher in the winter. CAT showed a significant negative correlation with total PAH concentrations, especially total LMW-PAH, in individuals collected during winter. Both GST and SOD did not show any significant correlation with PAH levels.

c) CEN sub-region (Tunisia, Italy)

577. Seven studies were reviewed for Tunisia: 2 from the WMS, 3 from the CEN and 2 with data from both the WMS and the In the CEN, one mesocosm experiment was performed in Mytilus spp. exposed to sediment contaminated by PAH and TM collected from the Zarzis area (Ghribi et al. 2020), while the effects of hydrocarbons were studied in the mollusc Ruditapes decussatus collected from the southern Lagoon of Tunis (Mansour et al. 2021). The effect of TM on the mollusc Patella caerulea was studied in specimens collected from 4 sites in the CEN (Zaidi et al. 2022).

578. Mytilus spp exposed to contaminated sediments in a mesocosm experiment presented the highest values of the tested oxidative stress biomarkers (CAT, GST, GPx) and a significant inhibition of AChE activity in comparison with the unpolluted reference site.

579. Hydrocarbons were found to affect the biomarkers CAT, GR, SOD, MDA and AChE activities in Ruditapes decussatus.

580. SOD and GPx activities measured in caerulea were different among sites (higher in more affected stations), while CAT was similar on all four stations. MDA was inducted but no differences were found among the sites.

581. Italy. In the CEN, the effect of plastic ingestion was studies in the fish Trachurus trachurus collected for the Sicily straits (Chenet et al. 2021).

582. Vitellogenin was highly expressed in trachurus females as expected, there is also a significant expression of the VTG gene in 60% of the males analyzed, from both sampling sites. Moreover, females in Lampedusa island showed a lower expression of vitellogenin than in Mazara del Vallo (with one female sample, TT54, not expressing VTG at all). The endocrine disruption represented by the alteration of VTG expression in specimens observed in this work can be caused by microplastic ingestion, as well as by the interactions between the marine organisms and the wide variety of endocrine- disrupting chemicals possibly present in seawater.

d) WMS sub-region (Algeria, Spain, Tunisia, Italy)

583. Four studies reviewed for Algeria studied the effects of non-specific stressor in the mollusc Donax trunculus from Annaba Bay (Amamra et al. 2019) , in the fish Mullus barbatus along the Algerian west coast (Kristel, Oran, Ghazaouet) (Kaddour et al. 2021), on the mollusc Perna perna transplanted to the Gulf of Annaba initianorth-eastern coast) (Laouati et al. 2021) and on the mollusc Patella rustica affected by the brine of the Bousfer desalination plant in Oran Bay (Benaissa et al. 2020).

584. Donax trunculus specimens showed a significant inhibition of AChE and induction of GST and MDA in individuals of Sidi Salem and Echatt as compared to El Battah with significant effects of both site and season. The effects were more pronounced during summer and spring compared to the other seasons. In addition, the comparison between tissues revealed a more marked response in gonad than mantle and digestive gland.

585. In barbatus, a significant increase in the frequency of micronuclei (MN) occurrence in the summer period correlated with significantly shorter NRRT. In addition, the erythrocytes of M. barbatus populations from polluted areas presented statistically higher MN frequencies and shorter NRRT than those of the reference site.

586. GSH decreased in the gills and digestive glands of perna specimens transplanted to two of the sites affected by anthropogenic input while GST and CAT activities showed no significant variation. The MDA content in the mussel digestive glands, but not in the gills, increased significantly after the deployment period in the three caging sites, and were significantly different among the 3 sites. AChE activity was significantly inhibited registered in the gills of mussels from the 3 sites and in the digestive glands from one site.

587. A multibiomarker approach (oxidative stress, biotransformation enzyme, lipid peroxidation, neurotoxicity and genotoxicity) were applied in the soft tissue of rustica . This biomonitoring confirmed the negative impact of brine discharges of the desalination plant, with samples collected close to the outfall more affected. by all the environmental disturbances than ones from the other sites. CAT, TGPx, GR, GST, CSP-3like activities were increased in samples from the outfall. AChE was lower however not significantly different from samples collected from the reference site. Genotoxic effect revealed by ADN and lipid damages.

588. Five studies were reviewed for Spain: four studies studied the effect of microplastic ingestion and of plasticizers on the biomarker responses, while one studied the effect of anthropogenic items ingestion. Three studies were conducted in the Integrated Multi-Trophic Aquaculture cages in Palma de Majorca, where specimens of the mussel Mytilus galloprovincialis and of the fish Sparus aurata were transplanted to and analyzed at time 0, after 60 days (T60) and after 120 days (T120) of exposure (Capó et al. 2022, Capo et al. 2021, Rios-Fuster et al. 2022). One study was performed with S. dumerili collected around the Balearic Islands (Solomando et al. 2022). Anthropogenic items ingestion was studied in E. encrasicolus collected off Catalunia (Rodríguez-Romeu et al. 2022).

589. No effects of time were observed in CAT, SOD, and GRd activities galloprovincialis, but they were significantly higher in specimens sampled from the cages than in specimens from the controls. GST activity did not change with time, and it increased significantly only in samples for the cages at T60. In T120 activity was higher in the cages only if compared to one of the control sites. GPx activity was modulated by both sampling site and time: higher activities in specimens from the cages at T120. MDA was higher in samples from the cages compared to the controls at T60. In a different study with M. galloprovincialis higher expressions were observed in the biomarkers CAT, SOD, GPx and LPO in specimens from the aquaculture cages. Those could be triggered by the presence of bisphenol but also by other possible contaminant inputs from the aquaculture.

590. MDA increased throughout the study both in liver and blood cells of aurata but with a progressive decrease in plasma. EROD, BFCOD and CE, showed a comparable decrease at T60 with a slight recovery at T120. In contrast, GST activity was significantly enhanced at T60 compared to the other sampling stages.

591. SOD, CAT, and GST activity were significantly higher in dumerili with higher microplastic (MP) load, while no significant differences were observed for MDA, and EROD enzyme activity.

592. AChE, CAT and GST were lower in encrasicolus collected off Barcelona, compared to specimens collected Blanes and Tarragona; Terragona LDH, CE and EROD were higher in Terragona than in the other two locations; Blanes CS was higher than in Tarragona. These differences could not be correlated with any potential stressors nor with fish size Catalunia (Rodríguez-Romeu et al. 2022).

593. Italy. Five studies were reviewed for Italy: 2 from the WMS, 1 from FAO zone 37 (not further specified), 1 from the CEN, 1 from the ADR . In the WMS, the effect of pesticides were studied in the fish Parablennius sanguinolentus from the port of Bagnara (western Calabria) (Parrino et al. 2020), and the effect of TM and PAHs on mollusc (Mytilus galloprovincialis) and fish (Mullus barbatus, Pagellus erythrinus and Diplodus vulgaris)from the bay of Pozzuoli (Naples)(Morroni et al. 2020). Microplastics and TM effects were studied on the fish Lepidopus caudatus collected from FAO area 37 (area not further specified) (Salvaggio et al. 2019).

594. AChE activity in the brain and BChE activity in blood were significantly inhibited in specimens of sanguinolentus from the affected port area, by 23.5 and 72.0%, respectively. The esterase inhibition was primarily due to carbamate and organophosphorus insecticides presence.

595. In the Bay of Pozzuoli, the effect of pollution varied by species and biomarkers. In galloprovincialis, there was a decreased LMS and increased MN at two sites compared to organisms from other areas while no variations were observed for the AChE in haemolymph, nor for MT in digestive gland of mussels from various sites. AChE activity was not affected in M. barbatus sampled in the industrial area while a decrease of this biomarker AChE was observed in P. erythrinus and D. vulgaris. The EROD enzymatic activity was significantly induced in M. barbatus and P. erythrinus sampled in the industrial area compared to specimens from the reference site, while the cytochrome P450 biotransformation pathway was unaffected in D. vulgaris. At the same time, all the fish species exhibited higher levels of aromatic metabolites, particularly B[a]P-like and pyrene-like, in organisms sampled in the industrial compared to reference area. MN increased in gills of M. barbatus from the industrial area.

596. Immunohistochemical analysis for anti-metallothionein 1 antibody in caudatus showed a strong positivity of liver cells, both in females and males, showing a strong stress that activated a cell detoxification system. The immunohistochemical analysis for the anti-vitellogenin antibody showed in females a strong positivity both in the liver cells, and in the gonads, as expected. The analysis of the liver and gonadal preparations of the male specimens was found to be always negative except for one specimen.

597. Seven studies were reviewed for Tunisia: 2 from the WMS, 3 from the CEN and 2 with data from both the WMS and the CEN. In the WMS, the effect of TM was studied in the mollusc Flexopecten glaber collected from the Bizerte Lagoon (Telahigue et al. 2022) and on the polychaete Perinereis cultrifera collected from the port of Tades and the Punic port of Carthage (Bouhedi et al. 2021). The following 2 studies have data from the two sub-regions: WMS and CEN. The effect of microplastic ingestion was studied in the fish Serranus scriba collected from 6 sites along the Tunisian coast (Zitouni et al. 2020) and on the seaworm Hediste diversicolor collected from 8 sites along the Tunisian coast (Missawi et al. 2020).

598. The distribution of most analyzed metals in glaber tissues varied significantly between sites, seasons, and organs. The highest levels were recorded at the polluted site during the warm period. Moreover, the digestive gland was found to accumulate greater concentrations of TM than the gills. The biomarkers (MDA, GSH, GPx, SOD, CAT) in gills were higher in the polluted site while MT was not affected. In the digestive gland, only CAT and MDA showed an increase activity in the polluted site.

599. Higher level of thiobarbituric acid were found in cultrifera specimens from polluted site. In addition, CAT, GST, SOD, glutathione and MT were enhanced and AChE activities decreased in specimens from the contaminated site compared to those from the reference (or less contaminated site).

600. Biomarkers of oxidative stress (MT, CAT, GST, MDA) and neurotoxicity (AChE) responses in scriba were dependent on site and on the size of the microplastic. High content of microplastic in the gastrointestinal track increased MT levels and GST activity. CAT activity and MDA accumulation were positively related with the medium size class MP A significant negative correlation was found between AChE activity and the small size class of microplastic (MP). The study could not rule out some influence of other pollutants that may be present in some of the sites on biomarker response.

601. In the seaworm Hediste diversicolor, responses increased with increased microplastic tissue concentration, in particular CAT but also MDA. A decrease of GST activity was reported in the same sites. AChE was significantly inhibited indicating neurotoxicity.

602. Figures 3.1.5.1 and 3.1.5.2 depict the sampling areas. Figure 3.1.5.1 shows the whole Mediterranean Sea, while Figure 1.5.2 shows in detail the study areas off eastern Algeria and Tunisia, where many of the reviewed studies were performed.

Figure 3.1.5.1. Areas of study for biomarkers, reviewed in the recent (since 2016) scientific literature for the Mediterranean Sea. When no coordinates were presented in the papers, the general area was marked in the map.

Figure 3.1.5.2. Detailed map of the study areas for biomarkers reviewed in the recent (since 2016) scientific literature for eastern Algeria and Tunisia coasts. Many stations were occupied in this area of the Mediterranean Sea.

603. Further to the above results based on a review of the studies by sub-regions and countries, it can be concluded that twenty-four studies were retrieved from the scientific literature as follows: 4 studies from Algeria (WMS), 1 from Egypt (AEL), 5 from Italy (2 from WMS, 1 from ADR, 1 from CEN and one from FAO zone 37), 5 from Spain (WMS), 7 from Tunisia (2 from WMS, 2 from CEN and 3 with data from both the WMS and CEN), and 2 from Türkiye (AEL).

604. The sub-region most represented is the WMS, followed by the In the CEN all studies except one were performed in Tunisia. There was one study from the ADR and three in the AEL.

605. The monitoring species, M. galloprovincialis and M. barbatus, appeared in 5 and 4 studies, In addition, 10 fish species, 6 mollusc species and 2 polychaeta species were also studied.

606. Of the mandatory biomarkers as defined in in the DDs and DSs for IMAP CI-18, AChE appeared in 13 studies, MT in 5 studies (2 with molluscs, 2 with fish and one with a polychaete species), MN in 2 and LMS-NRTT in 1 study.

607. Data from studies cannot be compared to BAC and EACs values as agreed by Decisions 22/7 and IG.23/6 (COP 19 and COP 20) because they were not measured in the specific tissue of M. galloprovincialis.

608. The most common additional biomarkers measured in the reviewed studies were: CAT (15 studies), MDA (12 studies), GST (11 studies), SOD (9 studies), and GPx (8 studies).

609. The anthropogenic stressors identified were: Trace metals (10), Plastic/microplastic (8), non- specific (4), PAHs (3), Pesticides (2), hydrocarbons (1), anthropogenic items, and one study with desalination brine as a source.

610. Drivers and pressures reported in the studies, encompassed the whole range of them: domestic and industrial discharges, agricultural and riverine runoff, fisheries, harbor and marina utilization, maritime activities, tourism. Most of the studies described the environmental conditions at the sampling The exemption was for microplastics, where the source was not determined, and microplastics were considered ubiquitous in the environment.

611. Most biomarkers studied showed a response to anthropogenic In the case of microplastics, the size of the microplastic also influenced the response.

612. Studies demonstrated that, in addition to anthropogenic stressors, biomarker responses were influenced also by seasonality, tissue analyzed, spawning status, and on species identity.

Assessment of IMAP Common Indicator 20. Actual levels of contaminants that have been detected and number of contaminants which have exceeded maximum regulatory levels in commonly consumed seafood

632. The two groups of data were collected e. i) data reported to IMAP – IS for CI-17 contaminants in biota, and ii) data from scientific literature. The relevant data from IMAP-IS consisted of the concentrations of trace metals (Cd, Hg and Pb) in fish and molluscs; PAHs in molluscs and PCBs in fish and molluscs. It should be emphasized that these data were collected within IMAP monitoring programs to assess the status of the marine environment and not to protect human health. Italy submitted CI 20 data after the Meeting of CorMon Pollution (1-2 March 2023, Athens) that included contaminants in different species of fish, molluscs, crustaceans, echinoderm and tunicates sampled in 2020¹⁰⁵

633. CI 17 data available from IMAP-IS for the monitoring species (M. galloprovincialis and barbatus) are shown in Table 3.1.7.1.

Table 3.1.7.1. Number of data points extracted from CI-17 database, relevant for CI-20 Assessment. MG – Mytilus galloprovincialis; MB- Mullus barbatus. Table is sorted by species and alphabetical order of CPs.

634. Relevant data for additional species other than the mandatory species reported to IMAP-IS were available as presented here-below under assessment of data reported for the mandatory monitoring

635. The literature search on seafood quality in the Mediterranean Sea focused on the studies that reported data from 2016/2017 onward, emphasizing contaminants that are regulated in the Previous studies have been used in the preparation of the 2017 MED QSR.

636. The bibliographic studies reported concentrations of contaminants and compared them to EU regulation while some also addressed national regulation as well as international regulations or advisories (De Witte et al. 2022). Most of the studies provided also risk assessments to human health from consumption of the seafood by calculating the estimated daily intake (EDI), target hazard quotient (THQ), total risk (HI), Cancer risk, among others.

637. This emphasizes the fact that the risk to human health (and hence GES- non GES statuses) should not be evaluated based on concentration of a single contaminant but evaluated together with other factors such as synergy with other contaminants, temporal and spatial scales.

638. Another point to make is that recent literature emphasizes the connection between seafood safety and quality and the presence of microplastics in the marine environment (i.e.Wakkaf et al. 2020 among many others). Human health may be impacted either by consuming seafood with microplastic content, or seafood with contaminants that were leached from the microplastic to the This sets an interrelation of CI 20 with CI 23 and should be further pursued.

639. Table 3.1.7.2 provides a summary of the studies published in the peer-reviewed literature. Thirty-six studies from 11 CPs were found relevant for the present work, with 1-4 studies each, except for Italy that had 14 studies. Most (25) reported concentrations of trace metals (TM) and 12 on organic contaminants (PAHs, PCBs, PBDEs, PCDD/Fs). Concentrations in fish were reported in 26 studies and concentrations in molluscs were reported in 17 studies.

Assessment of IMAP Common Indicator 21. Percentage of intestinal enterococci concentration measurements within established standards

672. In the 2017 MED QSR, it was recommended to prepare the future assessments of IMAP CI 21 based on the statistics from datasets submitted by national authorities or/and the corresponding However, only a few data sets were reported to the IMAP-IS. Those are presented in Table 3.1.8.1.

673. Given lack of data reported by the CPs prevents implementation of the recommendations of COP 19, the assessment of IMAP CI 21 within the 2023 MED QSR was performed using the approach applied for the 2017 MED QSR. Namely, it combines the assessment results as presented in the assessment report¹²¹ from the European Environment Agency (EEA) on the State of Bathing Water Quality in 2020¹²² and the assessment of monitoring data reported for IMAP CI 21 from Bosnia and Herzegovina, Israel, Lebanon, Montenegro and Morocco (Table 3.1.8.1).

674. Recent data of Croatia (2021-2022) and Slovenia (2021) were reported into IMAP-IS. However, for consistency, the status of Croatia and Slovenia were not re-assessed by applying the approach used for the dataset reported by Montenegro, Morocco and Lebanon and the assessment was based on the EEA 2020 assessment of the state of bathing water quality. Data were analyzed only to check for possible problem areas.

Quality status assessments of the Mediterranean regarding Common Indicators of Ecological Objective 11

Assessment of IMAP Candidate Indicator 26 (Ecological Objective 11)

704. For the year 2018 and for all the 4 species considered (bottlenose dolphin, fin whale, sperm whale, Cuvier’s beaked whale), 3 sub-regions are below threshold of affected habitat (ADR, CEN, WMS).

705. In 2018, the proportion of affected habitat was higher than 10% i.e. the GES/non GES boundary value/threshold in the Aegean and Levantine Sea Sub-region (AEL) considering sperm whale and Cuvier’s beaked whale habitats, but was lower than 10% considering the bottlenose dolphin habitat. AEL Sub-region presents the higher likelihood to be in non-tolerable i.e., non-GES based on available data and adapted assessment methodology (Figure 3.1.9.9).

706. The proportion of affected habitat was higher than 10% i.e. the GES/non GES boundary value/threshold in the Aegean and Levantine Sea Sub-region (AEL) considering sperm whale and Cuvier’s beaked whale habitats, but was lower than 10% considering the bottlenose dolphin habitat. AEL Sub-region presents the higher likelihood to be in non-tolerable e., non-GES based on available data and adapted assessment methodology (Figure 3.1.9.9).

707. Overall, for the Mediterranean Sea region, the environmental status is probably acceptable based on the present preliminary assessment findings, since the whole Mediterranean seems to comply with the 10% GES/non-GES boundary value of impacted habitat of cetaceans selected for this assessment. This conclusion is also supported by the computation of the simple coverage (i.e., without considering the habitat of cetaceans) of the Mediterranean Sea by impulsive noise events, which is below 10% for all year considered (Figures 3.1.9.7.and Figure 3.1.9.8).

708. Figures 3.1.9.9 and 3.1.9.10. provide a mapping of main assessment findings, especially highlighting potential non-GES situations found for the year 2018. It is noteworthy that the red areas highlighted in those maps do not correspond to non-tolerable, e., non-GES, positions, but are simply the position of all noise events for periods and areas considered (2018, all sub-regions). Tolerable or non-tolerable status is derived by dividing the extent of habitat of a species which is covered by impulsive noise events in the sub-region by the overall extent of the habitat area in that subregion.
Tolerable or non-tolerable status is therefore indicated by one number (i.e., the proportion of affected habitat, in % which is assigned to a sub-region plotted and is plotted in Figures 3.1.9.9 and 3.1.9.10. Beyond this, highlighting the areas that determine the exceedance of the 10% threshold (non-tolerable, i.e. non-GES areas) during a year will be possible when the ACCOBAMS International Noise Register will be fed with enough data to allow for an optimal assessment. However, from a management perspective the way the red areas are interpreted has little importance as bringing a sub-region below thresholds will imply to take measures to reduce the extent of the red areas, wherever they are found.

709. The refinement of the assessment, when the INR-MED will reach a higher level of completeness, should enable simulation of the effect of the concurrent activities of impulsive noise sources through appropriate simulation techniques (including acoustic modelling), and application of the optimal methodological framework.

Figure 3.1.9.10. Percentages of habitat exposed to impulsive noise events, in 2018, per four IMAP Sub-regions and considering Cuvier’s beaked whale habitat. Red grid cells indicate the position of noise events in 2018. The 4 sub-regions are indicated in different colours.

Assessment of IMAP Candidate Common Indicator 26: Proportion of days and geographical distribution where loud, low, and mid-frequency impulsive sounds exceed levels that are likely to entail significant impact on marine animal

Assessment of IMAP Candidate Indicator 27 (Ecological Objective 11)

728. The computation of the extent of exposure results in non-tolerable i.e. in non GES for the Western Mediterranean Sea and the Aegean Levantine Sea Sub-regions e., % affected habitat > 20%, while the status is tolerable i.e., GES in the Adriatic Sea and Central Mediterranean Sea Sub-regions.

729. The overlap between continuous noise (median noise in July 2020) and the habitat of cetacean species clearly shows the exceedance of the 20% boundary value/threshold of the habitat area affected by continuous low frequency noise in the Western Mediterranean Sea and the Aegean Levantine Seas Sub-regions. Given that the implementation of the methodology for cCI 27 is overall complete for the month of July 2020, it can be concluded that these two sub-regions were in non- tolerable status e., non-GES during that one month. While it cannot be said much regarding the status during other months, one single month exceeding the 20%, is sufficient to induce non tolerable environmental status, i.e. nonGES for continuous noise, for the entire year. Therefore, the assessment finding for 2020 appears to be non-tolerable status, i.e. non-GES, for WMS and AEL sub-regions.

730. Figures 3.1.10.3 and 3.1.10.4 provide such mapped assessment findings. It is worth noting that tolerable/non tolerable, i.e. GES/non-GES status is indicated by the proportion of affected habitat to see whether the value is above the 20%. Red areas determine the non-tolerable status of a sub- region but are not to be considered non-GES However, from a management perspective the way red areas are interpreted has little importance as bringing a sub-region below thresholds will induce taking actions to reduce the extent of the red areas, wherever they are found.

731. For the Adriatic Sea (ADR) and Central Mediterranean (CEN) sub-regions, the result of the assessment was a tolerable status, i.e. GES for continuous noise, considering that the proportion of habitat of the species considered (bottlenose dolphin) affected by continuous noise was below 20%. As elaborated above, the summer months are those with the highest levels of vessel traffic and hence the analysis done on a month of July 2020 can be seen as the worst-case scenario. Therefore, even though quantitative data were not produced for other months, it is possible to conclude that if the month representing the worst case scenario results in tolerable status, i.e., GES for continuous noise, this result can be generalized for the entire year, i.e., the ADR and CEN sub-regions were likely in GES in 2020.

732. Finally, based on these preliminary results, the environmental status of the Mediterranean Sea region is not fully in tolerable status i.e., GES status since the Western Mediterranean Sea and the Aegean Levantine Sea Sub-regions do not comply with the 20% threshold of impacted habitat over the monthly scenario.

Figure 3.1.10.4. Percent of bottlenose dolphin habitat (PUHA) exposed to a monthly noise level higher than 125 dB re 1 µPa (LOBE) in the Western Mediterranean Sea Sub-region (WMS), Adriatic Sea (ADR), Central Mediterranean (CEN) and Aegean and Levantine Sea (AEL) sub-regions. The picture shows exceedance of thresholds (20% of habitat affected by continuous noise) in the WMS and AEL sub-regions, and compliance in the ADR and CEN sub-regions. Red cells indicate the area where the Level of Onset of Biological Effects (LOBE, set as median noise level = 125 dB re 1µPa) is exceeded for the month of July 2020. Different sub-regions are indicated in different colours.

Assessment of IMAP Candidate Common Indicator 27: Levels of continuous low frequency sounds with the use of models as appropriate

Marine Litter

779. Given the seriousness of the marine litter issue, most of the important relevant global and regional processes including the 2030 Agenda for sustainable Development and SDGs called for its assessments and urgent action to address it. In the Mediterranean, marine litter has been an issue of concern since 1970s and the importance of dealing with it was explicitly recognized by the Contracting Parties to the Barcelona Convention when adopting in 1980 the Protocol for the Protection of the Mediterranean Sea against Pollution from Land-Based Sources. Annex I of the Protocol, as amended in 1996, defined Litter as “any persistent manufactured or processed solid material which is discarded, disposed of, or abandoned in the marine and coastal environment”.

780. The Mediterranean Sea is one of the special areas established under MARPOL Annex V (Regulations for the Prevention of Pollution by Garbage from Ships). In April 2008, the Marine Environment Protection Committee (MPEC) of IMO adopted its Resolution MEPC.172(57) by which it decided “that the discharge requirements for Special Areas in regulation 5 of MARPOL Annex V for the Mediterranean Sea area Special Area shall take effect on 1 May 2009, in accordance with the requirements set out in regulation 5(4)(b) of MARPOL Annex V”.

781. At their 18^th Meeting (Istanbul, Decembre 2013), the Contracting Parties of the Barcelona Convention adopted the Regional Plan on the Management of Marine Litter in the It provides for programmes of measures and implementation timetables to prevent and reduce the adverse effects of marine litter on the marine and coastal environment.

782. In relation to the IMAP Ecological Objective 10 (Marine and coastal litter do not adversely affect coastal and marine environment), the Contracting Parties to the Barcelona Convention adopted the following Indicators:

Common Indicator 22: Trends in the amount of litter washed ashore and/or deposited on coastlines (CI22);

Common Indicator 23: Trends in the amount of litter in the water column including microplastics and on the seafloor (CI23);

Candidate Indicator 24: Trends in the amount of litter ingested by or entangling marine organisms focusing on selected mammals, marine birds, and marine turtles.

 783. Since 2016, the Mediterranean countries with the support of UNEP/MAP and the EU-funded EcAp MED II Project have supported the Mediterranean Countries to establish national IMAP-based monitoring programmes for the 2 IMAP Common Indicators, i.e., Common Indicator 22 (CI22) and Common Indicator 23 (CI23). The focus for CI22 has been given on monitoring beach macro litter, whereas the focus for CI23 has been given on monitoring seafloor macro-litter and floating microplastics. Monitoring for CI22 has been also supplemented by numerous pilots in the Adriatic and South Mediterranean areas, having as a prerequisite the inclusion and integration of the respective IMAP methodology. Moreover, the regional data repository (IMAP InfoSystem) has been developed and is operational, including the development of reporting templates for CI22 (M1 Module) and CI23 (M2 and M3 Modules).

784. Two additional EU-funded projects, i.e., the Marine Litter MED (2016-2019) and Marine Litter MED II (2020-2023) projects have supported IMAP implementation through the development of knowledge for IMAP Candidate Indicator 24, as well as touching upon, new novel aspects of marine litter monitoring (e.g., monitoring riverine inputs of marine litter and monitoring microplastics coming from wastewater treatment plants).

Monitoring Floating marine litter with aerial observation survey (ACCOBAMS)

The ACCOBAMS Survey Initiative (ASI) project was launched in 2016 and carried out large-scale surveys in summers 2018 and 2019 (ACCOBAMS, 2021). Its primary aim was to establish an integrated, collaborative and coordinated monitoring system for the status of cetaceans and other species of conservation concern at the whole ACCOBAMS area level (sea turtles, seabirds, fishes). The ASI project also aimed at better understanding the presence and distribution of anthropogenic activities (ships), as well as of floating marine litter (FML), known to acutely plague the Mediterranean.

The Mediterranean was divided into large blocks, subsequently divided into sub-blocks within which the observation transects were laid out. The data collection on the target species and floating marine litter was ensured by eight teams of trained observers each of them was associated to a plane, operating in a predefined sector of the survey. To ensure all observers follow the same principles and carry out the protocol similarly, training flights were operated to simulate real field conditions.

Application of the ΝΕΑΤ Assessment Tool for EO10 for the Adriatic Sub-region

The use of the NEAT tool for the Adriatic Sub-region should be considered as an example showing how the tool should be applied for GES assessment further to sufficient data reporting by the Contracting Parties. the nested approach ensures that a balance is achieved between a too broad scale, that can mask significant areas of impact in certain parts of a region or subregion, and a very fine scale that could lead to very complicated assessment processes. The first element that needs to be considered for the implementation of the nested approach is the delimitation of the areas of assessment based on the areas of monitoring.

The used methodologies as well as information about data availability are detailed in the following sections of Document UNEP/MED WG.550/12:

• • • • • GES Assessment / Alternative Assessment for IMAP EO10 Common Indicator 22
        • GES Assessment for Floating Microplastics (IMAP EO10 CI23
        • The Mediterranean litterscape assessed from the air during the ACCOBAMS survey initiative
        • Application of the ΝΕΑΤ Assessment Tool for EO10 for the Adriatic Sub-region.

785. Beach Litter (CI22) data are reported in the IMAP InfoSystem from 13 CPs covering all 4 sub-divisions (ADR, CEN, EM, WM). In total 191 beaches are monitored during the period 2017- 2021 in the following countries: Bosnia-Herzegovina, Croatia, Cyprus, France, Greece, Italy, Israel, Lebanon, Morocco, Montenegro, Spain, Slovenia, Türkiye. A total of 931 surveys were stored and uploaded to IMAP InfoSystem reflecting the collection and removal of ~300,000 marine litter items from the Mediterranean In line with the agreement of the Contracting Parties in 2021¹³⁵on a unified list of marine litter items under IMAP, the Secretariat for the purpose of this report discarded those items which could not be categorized in accordance with the IMAP/ MED POL list for beach marine litter items.

786. Concentrations of Beach Litter (items/100m) are highly variable fluctuating between 8 and 47,361 items /100m. Average beach litter concentration on the Mediterranean coastline is found equal to 961 ± 3664 items/100 m.

787. Following the assessment methodology explained in Chapter 2.2, and using the TV of 130 items/100m, temporal average data from the 191 beaches are compared against the threshold, resulting in their classification under 5 status classes (high, good, moderate, poor, bad) shown in Table 13.

788. Overall, 79% of the beaches monitored do not achieve GES, and most of them fall into the moderate (24 %) and poor (29 %) and bad (25 %) categories, e., beach litter concentrations are up to two to five times higher than the TV. In Table 14 the classification results are given for each sub- Region separately.

Table 13: The GES – nonGES classification of the 192 monitored beaches in the Mediterranean Region

789. On the sub-Region level, the Central Mediterranean appears the least affected by beach litter with 32 % out for the 22 beaches monitored falling into the GES category The Adriatic, Eastern and Western Mediterranean sub-regions show an equal distribution of beaches under GES (14 -16 %) and non-GES (84 -86 %) classes. These results are depicted spatially in the maps of Figure 23 to Figure 26.

Table 14: The GES – nonGES classification of the monitored beaches in the 4 Mediterranean sub-Regions

Figure 24: GES assessment classification of the beaches monitored for marine litter in the Adriatic and Central Mediterranean sub-regions.

Figure 26: GES assessment classification of the beaches monitored for marine litter in the Western Mediterranean sub-Region.

790. The average beach marine litter density from the 10 countries varied between a maximum of 5,716 to 105 items/100m. The average beach marine litter densities are presented hereunder (Table 15).

791. An analysis was undertaken on the Top-10 items that have been recorded in the respective countries. For 11 countries, the top-10 item list represents more than 70% of the collected litter items, and for 2 Countries represents slightly lower share (approximately 68-69%) of the collected litter items. Bosnia and Herzegovina gave an extreme value of 97.4%, followed by Lebanon (86.9%), Slovenia (81.6%), Croatia (81.1%), Italy (79.2%), France (78%), Cyprus (77.1%), Montenegro (73.8), Greece (72.2%), Israel (72.0%), Türkiye (71.5%), Spain (68.9%), and Morocco (67.7%). The analysis and detailed list of the Top-10 item list per country is provided hereunder

792.

Table 16: Top-10 item list of beach marine litter found in the Mediterranean Countries                        

793. The aforementioned analysis provides very interesting results for the top item list at the level of the Mediterranean. The Top-item lists from the 13 countries, extracts into 39 common items of which:

• • 3 items have a share of more than 10%, respectively: Plastic/polystyrene pieces 2.5 cm > < 50 cm (G76) with 6%, Cigarette butts and filters (G27) with 13.4%, and Plastic caps and lids (including rings from bottle caps/lids) (G21/24) with 10.7%.
  • 2 items have a share between 5-10%, respectively: Crisps packets/sweets wrappers/Lolly sticks (G30/31) with 6.2% and Other plastic/polystyrene items (identifiable) including fragments (G124) with 5.0%.
    10 items have a share between 5-1%: Cotton bud sticks (G95) with 4.8%, Foam sponge [items (i.e. matrices, sponge, etc.)] (G73) with 2.4%, Glass fragments >2.5cm (G208a) witg 2.4%, String and cord (diameter less than 1 cm) (G50) with 2.1%, Small plastic bags, e.g. freezer bags incl. pieces (G4) with 1.7%, Shopping bags incl. pieces (G3) with 1.5%, Straws and stirrers (G35) with 1.2%, Sheets, industrial packaging, plastic sheeting (G67) with 1.2%, Glass Bottles (including identifiable fragments) (G200), and Drink bottles (G7/G8) with 1.0%.
  • 24 items have a share of less than 1%, respectively: G45, G33, G26, G145, G5, G10, G37, G95, G100, G204, G178, G158, G153, G70, G–, G28. G158, G175, G154, G198, G165, G53, G152, G49.

2.1.4 GES Assessment for Floating Microplastics (IMAP EO10 CI23)

794. Floating microplastics (CI23) data are reported in the IMAP InfoSystem from 10 CPs covering all sub-divisions of the Mediterranean region (ADR, CEN, EM, WM). In total 679 surface manta net trawls/stations are monitored during the period 2016-2022 in the following countries: Bosnia-Herzegovina, Croatia, France, Greece, Israel, Italy, Lebanon, Türkiye, Slovenia, Spain.

795. Concentrations of Floating Microplastics (items/m²) are highly variable fluctuating between 0 and 31 items /m². Average floating microplastics concentration on the Mediterranean Sea surface is found equal to 0.355 ± 1.99 items/m².

796. Following the assessment methodology explained in Chapter 2.2 and using the TV of 0.000845 items/m², temporal average data from the 679 stations are compared against the TV, resulting in their classification under 6 status classes (high, good, moderate, poor, bad, very bad) shown in Table 17. Practically all stations monitored (99%) do not achieve GES, and most of them fall into the poor (5244 %) and bad (45 %) classes, i.e., floating microplastics litter concentrations are up to 100 and 1000 times higher than the TV respectively. In Table 15 the classification results are given for each sub-Region separately.

Table 17: The classification of the 679 stations monitored for surface floating microplastics in the Mediterranean Region

797. It is clear from Table 18 that all Mediterranean subregions suffer from elevated microplastics concentrations in surface waters 100 times and 1000 times higher than the IMAP TV. In particular, in the EM, the 44% of monitored stations exceed the bad class with concentrations more than 1000 times the TV and are classified as ‘very bad’. In the ADR and WM only 1% and 2 % of stations respectively are found above 1000xTV. These results are depicted spatially in the maps of Figure 27 to Figure 30.

Table 18: The classification of the monitored stations for surface floating microplastics in all Mediterranean sub-Regions

Figure 28: GES assessment classification of the monitored stations for sea surface floating microplastics CI23 in the Adriatic Mediterranean sub-region.

Figure 30: GES assessment classification of the monitored stations for sea surface floating microplastics CI23 in the Western Mediterranean sub-region.

798. The data submitted for floating microplastics from the 10 countries, also provide interesting results regarding the qualitative composition and the different types of microplastics. Predominant in abundance are the Sheets (37%), followed by Filaments (30%), Pellets (21%), Fragments (7%), Foam (4%), and Granules (1%).

799. The graphs below are representing the qualitative composition (different types of microplastics) per respective country:

The Mediterranean litterscape assessed from the air during the ACCOBAMS survey initiative.

800. Detection and presence probabilities of mega-debris were estimated over the entire Mediterranean Sea and abundance estimate was eventually derived from the presence probability. Some 41,000 floating mega-litter items were recorded in total during the ASI (Figure 32), with an average encounter rate of 0.8 mega-litter per km (standard deviation 3.2), ranging between 0 and 111 debris per km. More than two thirds of the mega-litter recorded were identified as plastics (68.5%; e.g., plastic bags, bottles, tarpaulins, palettes, inflatable beach toys, etc.), while 1.7% were fishery debris and 1.9% were anthropogenic wood-trash. The remaining quarter (27.9%) was anthropogenic mega-debris of an undetermined nature. Plastic litter was largely dominant in all blocks. Beaufort sea state, turbidity and glare extent had a negative effect on detection, whereas subjective conditions had a positive one and detection probability differed among the eight observer teams. Overall, the estimated probability of detecting floating mega- litter during the ASI ranged from 0.1 in the worst conditions to 0.9 in optimal observation conditions: i.e., about 90% of debris actually present are not detected when seas are rough, while near perfect detection is probable when seas are calm, which was the case in 73% of the total survey effort.

801. During the ASI, only 20% of the Mediterranean was free of floating mega-litter. The estimated presence probability was highest in the central and western Mediterranean, in the Tyrrhenian, northern Ionian, and Adriatic Seas and in the Gulf of Gabes (> 80%). The lowest presence probabilities occurred in the Levantine basin, in the southern Ionian Sea and in the Gulf of Lion (< 50%). The total number of floating mega-litter was estimated at 2.9 million items (80% confidence interval was 2.7 to 3.1 million and average density 1.5±0.1 items per km²), taking into account imperfect detection. Considering that items larger than 30 cm represent only one fourth of the complete load of anthropogenic debris (>2 cm) in the Mediterranean, it scales up the estimate to 11.5 million floating debris.

802. The spatially explicit modelling of mega-litter presence revealed a very heterogeneous distribution of floating mega-debris during summer: highest densities of litter were observed in the central Mediterranean (Tyrrhenian Sea, Adriatic Sea, northern Ionian Sea, off north-eastern Algeria and the Gulf of Gabes; Fig.11), while the lowest densities were found in the eastern basin. Highest densities occurred along the Tyrrhenian coast of Italy and in the Adriatic Sea, with up to 20 items per km². This acute marine pollution might disrupt entire ecosystems through its impact on marine fauna (entanglement, ingestion, contamination), eventually impacting associated ecosystem services such as the tourism industry and the well-being of Mediterranean populations. The higher prevalence of litter in the western and central basin compared to the relatively spared eastern basin mimics that of the megafauna, which is both more abundant and more diversified in the western basin. This general overlap suggests that the threat to Mediterranean fauna would be maximum in the western

Figure 31: ACCOBAMS Survey Initiative (ASI) blocks, sampled transects and distribution of sighted floating mega-litter. Transects were sampled once by 14 different teams operating 8 planes simultaneously in different areas. There was no aerial survey effort off the coasts of Morocco, Libya, Egypt and east of Cyprus where the ASI survey was conducted by boat.

803. Many endangered or vulnerable species, some of them endemic to the area, are at risk of entanglement or of ingesting debris. This work sets a reference situation allowing the efficiency of future plastic pollution remediation strategies to be It constitutes the first ground-truthing of previous numerical simulations based on surface debris drifting simulations. On a methodological point of view, the present work showed that departing from sea-state 0 to 3 resulted in a drop of c. 31% in the detection probability of mega-debris, violating the assumption, inherent to strip transect approaches, that detection is perfect across the sampled strip.

804. Therefore, accounting for imperfect detection in density estimation procedure based on strip- transect visual surveys is crucial. The line-transect protocol, which is the standard methodology to be used in case of varying detectability of objects with distance from the transect line and observations conditions, cannot readily be implemented in aerial surveys for floating mega-debris, because those are too numerous to allow the necessary distance data to be collected without disrupting the observers’ observation capabilities. The use of strip-transect protocol has proven to be operationally effective for collecting debris along with marine fauna and anthropogenic activities, provided that the analytical procedure can take imperfect detection into account.

Figure 32: (A): Estimated presence probability (posterior mean) of floating mega-debris. (B): Uncertainty in estimated presence probability (coefficient of variation). Isolines corresponding to contours 20% probabilities are shown in dotted black lines and 80% contours in solid black lines. ASI survey blocks are shown in solid white lines.

GES Assessment for Seafloor Macrolitter (IMAP EO10 CI23)

805. Seafloor marine litter (CI23) data are reported in the IMAP InfoSystem from 11 CPs covering all sub-divisions of the Mediterranean region (ADR, CEN, EM, WM). In total 367 seafloor trawls/stations are monitored during the period 2017-2021 in the following countries: Croatia, Cyprus, France, Israel, Malta, Montenegro, Morocco, Slovenia, Spain, Tunisia, Türkiye. Most samplings (364) are situated on fishing grounds and were conducted by fishing trawls, thus in most of the cases in soft- bottom grounds, and only 3 samplings in Morocco were conducted by scuba diving in sub-littoral seafloor and correspond to maximum outlier seafloor macro-litter concentrations.

806. Concentrations of seafloor marine litter (items/km²) excluding the scuba diving outlier data are highly variable fluctuating between 0 and 28,228 items /km². Average seafloor litter concentration on the Mediterranean coastline is found equal to 570 ± 2,588 items/km². The outlier seafloor concentrations are 662,500 items/km², 1,882,500 items/km², and 372,500 items/km² and are not included in the analysis below because they are based on a different monitoring methodology.

807. Following the assessment methodology and using the TV of 38 items/km², temporal average data from the 367 seafloor stations are compared against the threshold, resulting in their classification under 5 status classes (high, good, moderate, poor, bad) shown in

808. Table 19. Overall, 88% of the seafloor stations monitored do not achieve GES, and most of them fall into the bad (53 %) and moderate (23 %) categories, e., seafloor litter concentrations are up to five times higher than the TV. In

811. Table 20 the classification results are given for each sub-Region separately.

Table 19: The classification of the 364 seafloor stations monitored in the Mediterranean Region         

812.  On the sub-region level the Western Mediterranean appears highly affected by seafloor marine litter since all stations monitored (100%) are classified in the nonGES category. The Central Mediterranean sub-region appears also highly affected with 81% of stations monitored classified under nonGES. The Adriatic and Eastern Mediterranean sub-regions follow with 65 and 68% of the stations monitored falling into the nonGES class respectively. The Eastern Mediterranean is the only area where a considerable percentage (24 %) of trawling stations achieve high status. These results are depicted spatially in the maps of Figure 33 to Figure 37 from where the uneven distribution of stations within each sub-region, attributed to limitations in data submission, can be seen, for example the CEN is covered only by Malta and Tunisia.

Figure 34: GES assessment classification of the seafloor stations monitored for marine litter in the Adriatic Mediterranean sub-regions.

813. Further to the submission of data for seafloor macro-litter, an analysis was undertaken with an explicit focus on fisheries-related items. The purpose of this analysis is to identify hotspot areas in the Mediterranean where high abundance rates can be associated with impact on biota (e.g., through ghost fishing, Abandoned Lost or Otherwise Discarded Fishing Gear (ALDFG). Seafloor litter can harm marine organisms of all sizes by various mechanisms, including entanglement, smothering (i.e., in soft bottom environments) and ingestion.

814. A small component (10%) of seafloor macrolitter was represented by fishery-related items. The most common items recorded from the trawl surveys are:

1. 1. “L1i – Synthetic ropes/strapping bands” (39%);
   2. “L1f – Fishing nets (polymers)” (27%);
   3. “L1g – Fishing lines (polymers)” (25%);
   4. “L5c – Natural fishing ropes” (6%);
   5. “L1h – Other synthetic fishing related” (2%); and
   6. “L3f – Fishing related (hooks, spears, )” (1%).

815. Fishery-related marine litter items varied among countries, from a mean value of approximately 26 items/km² in France to approximately 1 item/km² in Intermediate values have been recorded in Türkiye approx. 19 items/km², Malta approx. 15 items/km², Tunisia approx. 8, and Croatia with approx. 3 items/km².

816. In Morocco, fishery-related litter monitored through SCUBA diving represented just the 4% of all the items found. The most common litter item was “L1j – Fishing lines (polymers)” (34%), followed by “L1f – Fishing nets (polymers)” (19%), “L1h – Other synthetic fishing related” (12%), “L3f – Fishing related (hooks, spears, etc.) (12%), “L5c – Natural fishing ropes “ (12%) and “L1i – Synthetic ropes/strapping bands” (9%). The distribution of the fisheries-related items in 3 Mediterranean sub-regions is provided under Figure 38, Figure 39 and Figure 40, below:

Application of the ΝΕΑΤ Assessment Tool for EO10 for the Adriatic Sub-region

Defining the assessment areas

817. For IMAP EO10/CI 22, integration of assessments up to the subdivision level is considered meaningful. Three main subdivisions of the Adriatic Sea, namely, North, Central and South Adriatic have been chosen following the specific geomorphological features as available in relevant scientific sources (e.g., bottom depths and slope areas, existence of deep depression, salinity and temperature gradient, water mass exchanges).

818. Geographical data for the 3 Adriatic subdivisions have been retrieved from (Cushman-Roisin et , 2001). The coverage of the 3 sub-divisions is shown in Figure 41. The 3 sub-divisions are nested under the Adriatic Sea, while within each of them are nested the areas of assessment set further to the spatial coverage of the areas of monitoring of each of the CPs. Following the rationale of the IMAP national monitoring programmes as well as the methodology described in UNEP/MAP 2021, two zones for integration of areas of monitoring are defined. These two zones are set based on monitoring stations distribution and anticipation of the relevant IMAP monitoring areas as follows: (i) the coastal zone including monitoring stations within 1nm from the coastal line; and (ii) the offshore zone including monitoring stations beyond 1 nm up to 12nm from the coastal line (i.e., the area 1 nm < <12 nm).

819. For the nesting of the areas, these were first classified under the 3 subdivisions of the Adriatic Sea (North: NAS, Central: CAS, South: SAS), then a nesting scheme was followed. The approach followed for the nesting of the areas is 4 levels nesting scheme (1 – being the finest level, 4 – the highest): 1^st: nesting of all national IMAP SAUs & subSAUs under key IMAP assessment zones per country (i.e. coastal and offshore); 2^nd: IMAP assessment zones (i.e. coastal, offshore) on the subdivision level (NAS coastal, NAS offshore; CAS coastal, CAS offshore; SAS coastal, SAS offshore); 3^rd: under the 3 subdivisions (NAS, CAS, SAS); 4^th: under the Adriatic Sea Sub Region. Similarly, the integration of the assessment results is conducted as follows: 1^st Detailed assessment results per subSAUs and SAUs; 2^nd Integrated assessment results per NAS coastal, NAS offshore; CAS coastal, CAS offshore; SAS coastal, SAS offshore; 3^rd Integrated assessment results per subdivision NAS, CAS, SAS; 4^th Integrated assessment results for the Adriatic Sub Region.

820. The suggested nesting scheme of the IMAP SAUs leads to the aggregation of data on the subdivision level within the coastal and offshore IMAP monitoring/assessment zones and follows the regional/sub-regional approach as required by the IMAP. In line with the integrated assessment approach at the level of Pollution-Marine Litter Cluster, for EO10 CI22/CI23 the assessment is conducted for the same IMAP SAUs and subSAUs (the finest coastal assessment areas on the national level) and the respective nesting scheme, in line with the approach used for IMAP EO9 (Figure 42).
The NEAT assessment methodology is applied on the nesting scheme of SAUs and SubSAUs which has the ability to provide aggregated-integrated assessment results.

Data availability

821. Data on IMAP EO10/CI22-Beach Litter have been collected from 6 CPs bordering the Adriatic Sea for the years 2016 to 2021 (i.e. Albania, Bosnia & Herzegovina, Croatia, Italy, Montenegro, Slovenia), except from Beach Litter data used were either reported by the CP to the IMAP IS or shared with the IMAP Secretariat. Data on IMAP EO10/CI23- Seafloor Litter were reported to the IMAP IS only by Slovenia, Croatia and Montenegro. IMAP EO10/CI23- Sea surface floating microplastics (MPs) data sets were reported by 5 CPs (Bosnia & Herzegovina, Croatia, Greece, Italy, Slovenia).

Setting the assessment criteria

822. The baseline and threshold values for IMAP CI 22 in the Mediterranean Sea have been endorsed by COP22 (Antalya, Türkiye, 7-10 December 2021) and have been annexed to Decision IG.25/9. The respective values for IMAP CI23 in the Mediterranean were first submitted for review to the CORMON Meeting for Marine Litter Monitoring on 3 March 2023 and an updated version was prepared for the Integrated CORMON Meeting (27-28 June 2023). The threshold value between Good and non-Good Environmental Status used in the NEAT assessment is the TV equal to 130 items/100m for beach litter, the TV equal to 135 items/km² for seafloor litter, and the TV equal to 0.000845 items/m2 for floating microplastics.

823. According to the IMAP implementation all stations/beaches having concentrations equal or below the TVs are considered in GES, and those with concentrations higher than the TV value are considered not in GES (nonGES). Apart from the GES-nonGEs threshold/boundary values and their interrelation with the threshold/assessment criteria values, the NEAT tool requires also two more boundary values within the nonGES range of concentrations which defines the ‘worse’ conditions. In this way a 5-status class is produced which further discriminates the above GES threshold concentration range into two more classes depending on the distances from the GES threshold value. For this boundary (worse conditions) the maximum concentration value of the data set was used.

824. The 5 NEAT status classes for CI22 and CI23_SFL are: the high status with concentrations in the range 0 < ≤0.5xTV; the ‘good’ status with concentrations in the range 0.5xTV< ≤TV; the moderate status with concentrations in the range TV< ≤2xTV; the poor status with concentrations in the range 2xTV< ≤5xTV. Finally, the ‘bad’ status is defined by concentrations falling above the 5xTV boundary value. For CI23_ Sea surface MPs the boundary values for the 5 classes are modified as follows: high status with concentrations in the range 0 < ≤0.5xTV; the ‘good’ status with concentrations in the range 5xTV < ≤TV; the moderate status with concentrations in the range TV<≤10xTV; the poor status with concentrations in the range 10xTV< ≤100xTV. Finally, the ‘bad’ status is defined by concentrations falling above the 100xTV boundary value.

825. Following the IMAP methodology, NEAT class named ‘high’ is considered as ‘good’ sensu IMAP e., in GES; NEAT classes named ‘moderate’ and ‘poor’ sensu NEAT are considered as ‘Bad’ sensu IMAP i.e., not in GES. These boundary values and their relation to the IMAP and the NEAT status classes are shown in

826. Table 21 and Table 22.

Table 21: Relation of assessment status classes between the IMAP methodology and NEAT tool and respective colour coding. The position of the 3 required thresholds for the NEAT tool are shown.

827. A data matrix to be used for the NEAT software was prepared and given below in

828. Table 23.

Results of the NEAT tool for the Assessment of the IMAP EO10/CI22/CI23 status in the Adriatic subregion

829. The results obtained from the NEAT tool are shown in Table 24 and in Figure 43 to Error! Reference source not found.

830. On the individual parameter level the classification results of subSAUs regarding CI22- Beach Litter show that three subSAUs in Croatia are classified under ‘Good’ status (HRO-0423-KVJ, HRO-0423-KOR) and three under ‘Moderate’ (MAD-HRU-MRU-2, IT-Em-Ro-1, IT-Mo-1). All other subSAUs are classified under ‘Poor’ or ‘Bad’ status. For the case of CI-23 Seafloor Litter the subSAUs monitored in Slovenia and Montenegro (MAD-SI-MRU-12, MNE-12-C, MNE-12-S) are classified under’Good’ status while all other subSAUs are classified under ‘Poor’ or ‘Bad’ status. Finally, for CI23 Sea surface floating MPs all subSAUs monitored are classified as non-GEs and under ‘Poor’ and ‘Bad’ status classes.

831. Integration of data per each EO10 parameter on higher levels within the nesting scheme (bold lines in Table 7) shows that the NAS subdivision is classified under ‘Good’ status regarding Beach Litter, under ‘Bad’ regarding Seafloor Litter and Floating MPs. The CAS subdivision is classified as ‘Poor’ regarding Beach Litter and Sea surface Floating MPs and under ‘Bad’ regarding Seafloor Finally, the SAS subdivision is classified under ‘Poor’ status for Beach Litter, ‘Good’ status for Seafloor Litter and ‘Bad’ status for Sea surface Floating MPs.

832. When aggregating all EO10 parameters data per SubSAU, the SubSAUs HRO-0423-KVJ and MNE-12-C, MNE-12-S fall into ‘Good’ status class and the subSAUs IT-Mo-1, MAD-SI-MRU- 12 into ‘Moderate’. All other subSAUs are classified under ‘poor’ or ‘bad’ status classes.

833. Based on the data available the assessment results obtained by the NEAT methodology show that most areas of the Adriatic subregion do not achieve GES regarding EO10.

Table 24: Results of the NEAT tool on the assessment of IMAP EO10 in the Adriatic subregion (CI22_BL:Beach Litter; CI23_SFL:Seafloor Litter; CI23_MP:Floating Microplastics). The various levels of spatial integration within the nested scheme are shown in bold. Blank cells denote absence of data.

Sensitivity analysis of the assessment results

834. Based on the standard deviation of beach litter per SAU the NEAT tool provides a sensitivity analysis for calculating the uncertainty of the assessment results using a Monte-Carlo simulation model for 1000 iterations. In

835. Table 25 the results of the error analysis are presented.

836. In other words, 1000 assessments are run using different random combinations of the data. Instead of using the average value of the parameters inserted by the user, other random values are used by the tool to run the assessment. The selection of these random values is done based on the standard deviation and it is repeated 1000 times. The resulting assessment value of each of these 1000 assessment runs is recorded and may lead to a different assessment The number of times (out of 1000) of the appearance of these different assessments is given in

837. Table 25 For example, the overall status for the SAU MAD-HRU-MRU-3 is reported as ‘good’. However, from

838. Table 25 it is understood that out of 1000 iterations, 690 lead to Good status, and 164 to Moderate and 146 to High These results imply a rather high uncertainty (confidence 69%), in contrast to MAD-HRU-MRU-5 where all 1000 iterations led to High status (confidence 100%).

839. As for any assessment results, the accuracy of the results described above, is dependent also on the amount of data available for each Many subSAUs totally lack data, so that the integrated results on the SAU level actually reflect the status of one or two subSAUs and cannot be considered indicative of the overall SAU status with confidence.

Comparison of the two assessment methodologies applied for the Adriatic sub-region

840. Given the assessed data availability for EO10 CI22 and CI23 for the Mediterranean Sea as described in Chapters 2.1 and 2.2 the following approach is followed for the quality status For each CI and each measured parameter (Beach litter, Seafloor Litter, Floating Microplastics) temporal data are averaged per monitoring station. The resulting average value is compared against the respective TV and the score ratio (CR) is calculated. No further aggregation on the EO 10 level or spatial integration is conducted for the Mediterranean region as a whole. For the Adriatic sub-division, for which spatial assessment units have been defined in 2022 for the Eutrophication-Pollution and Marine litter cluster, the application of the NEAT methodology was made possible for the 2 IMAP Common Indicators on marine litter (CI22 and CI23).

841. For the Adriatic sub-region a comparison was made between the two assessment approaches, i.e. the assessment results on the CI level based on the CHASE+ methodology (Chapters 4.2.1; 4.2.2.1; 4.2.2.3) and the results on the EO10 level using the NEAT methodology (Chapter 4.3.1), further to the recommendations for the harmonization of the two assessment.

842. The first assessment approach on the CI level (Chapters 4.2.1; 4.2.2.1; 4.2.2.3) provides assessment per individual stations, while the second one, using NEAT, provides assessments either on the EO10 or CI level spatially integrated (Chapter 4.3.1) along a predefined hierarchical nesting scheme of assessment areas. Therefore, the comparison of the results obtained from the two methods was made possible only on the first level of aggregation i.e. on the subSAUs, for each of the EO10 components separately (CI22-BeachLitter, CI23-Seafloor Litter, CI23-Seasurface MPs). The score ratios (CR) for each of the EO10 components as obtained from the first assessment approach, were grouped for all stations belonging to a specific subSAU and averaged to get one CR per subSAU per EO10 component. Then the subSAU was classified following the rationale already described in Chapters 4.2.1; 4.2.2.1; 4.2.2.3 and shown here below in

843. Table 26 for both All thresholds used were identical in the two methodologies (

844. Table 26). The resulting classification is then compared to the respective NEAT value of the subSAU (Table 24). The two alternative assessment results per subSAU and per EO10 component are shown in Table 27.

Table 26: Assessment classification boundary limits/thresholds for a harmonized application of NEAT and simplified CHASE+ tools in the Adriatic Sea sub-region.

Table 27: Comparison of the two assessment methodologies applied in the Adriatic sub-region for the status assessment of EO10 components. Discrepancies in assessment results marked in bold.

845. The comparison of the two methodologies (Table 27) shows that out of the 45 individual assessments per subSAU per EO10 component only 6 discrepancies were found, most of them between the ‘poor’ and ‘bad’ The two methods agree on 87 % of cases, while the GES/nGES classification, with the exception of one SAU, is identical between methods and thus results can be considered comparable.

Key findings for IMAP EO10 Common Indicator 22:

1. 1. The monitoring efforts around the region and between the sub-regions vary significantly and further alignment and strengthening of IMAP EO CI22 is required from the Mediterranean
   2. Concentrations of beach marine litter are highly variable around the region ranging between 8 and 12,842 items/100m.
   3. Overall, 16% of the monitored beaches achieve GES, 79% do not achieve GES of which 29 % fall into the poor status class and 25% in to the bad (i.e., beach litter concentrations are up to two to five times higher than the TV).
   4. The Central Mediterranean appears the least affected by beach litter with 32% out for the 22 beaches monitored falling into the GES category.
   5. The Adriatic, Eastern and Western Mediterranean sub-regions show equal distribution between GES and non-GES classes with only ~14-16 %% of the beaches monitored falling into the GES class, with the highest percentages of beaches (34 – 38%) being classified under the poor or bad
   6. For 11 countries, the top-10 item list represents more than 70% of the collected litter items (Bosnia and Herzegovina Lebanon, Slovenia, Croatia, Italy, France, Cyprus, Montenegro, Greece, Israel, and Türkiye), and for 2 Countries represents slightly lower share (approximately 68-69%) (Spain and Morocco).
   7. At the level of the Mediterranean Plastic/polystyrene pieces (2.5 cm – 50 cm) are the most commonly found marine litter, followed by cigarette butts and filters, and plastic caps and These 3 items account for more than 60% of the recorded marine litter.
   8. The predominant source seems to be human activities on beaches, whereas the “beaching” process seems to play an important role, especially through the fragmentation process.

Key findings for IMAP EO10 Common Indicator 23:

A. Floating Marine Litter:

1. 1. Monitoring efforts are evident in several parts of the Mediterranean, however monitoring efforts for IMAP EO10 CI23 floating microplastics should be further strengthened also in the Southern part of the Mediterranean.
   2. Concentrations of Floating Microplastics (items/km²) are highly variable fluctuating between 0 and 31 items /m².
   3. Average floating microplastics concentration on the Mediterranean Sea surface is found equal to 0.36 ± 1.9 items/m².
   4. Almost all stations (99%) that have been monitored do not achieve GES, and most of them fall into the poor (44 %) and bad (49 %) classes (i.e., floating microplastics litter concentrations are up to 100 and 1000 times higher than the TV respectively).
   5. The Mediterranean region and its subregions suffer from elevated microplastics concentrations in surface waters, reaching up to 100 times and 1000 times higher than the IMAP TV.
   6. In the Eastern Mediterranean 44% of monitored stations exceed the bad class with concentrations more than 1000 times the TV and are classified as ‘very bad’.
   7. In the Western Mediterranean only 2 % of stations are found above 1000xTV.
   8. From the recorded floating microplastics, Sheets (39%) have been found to be predominant, followed by Filaments (29%), Pellets (21%), Fragments (5%), Foam (5%), and Granules (1%).
   9. The ACCOBAMS Survey Initiative (ASI), was the first international basin-wide survey of the Mediterranean Sea for floating mega-litter (>30cm) following an opportunistic approach while the main interest was to provide estimations about the mega-fauna.
   10. ACCOBAMS (ASI) has developed a well-elaborated monitoring protocol for monitoring mega- litter through aerial surveys.
   11. Some 41,000 floating mega-litter items were recorded in total during the ASI, with an average encounter rate of 0.8 mega-litter per km, ranging between 0 and 111 litter per km.
   12. The total number of floating mega-litter was estimated at 2.9 million items (80% confidence interval was 2.7 to 3.1 million) and average density 1.5±0.1 items per km².
   13. More than two thirds of the mega-litter recorded were identified as plastics (68.5%; g., plastic bags, bottles, tarpaulins, palettes, inflatable beach toys, etc.), while 1.7% were fishery debris and 1.9% were anthropogenic wood-trash. The remaining quarter (27.9%) was anthropogenic mega-debris of an undetermined nature.
   14. During the ASI, only 20% of the Mediterranean was free of floating mega-debris.
   15. Many endangered or vulnerable species, some of them endemic to the area, are at risk of entanglement or of ingesting debris.

B. Seafloor Marine Litter:

1. 1. Concentrations of seafloor marine litter are highly variable fluctuating between 0 and 28,228 items /km².
   2. The average seafloor litter concentration collected by seafloor trawling on the Mediterranean is found equal to 570± 2,588items/km².
   3. The majority (88%) of the seafloor stations monitored do not achieve GES, and most of them fall into the poor and bas categories (23 % and 53 % respectively) (i.e., seafloor litter concentrations are up to five times higher than the TV).
   4. The Western Mediterranean highly appears affected by seafloor marine litter since all stations monitored (100%) are classified in the nonGES category.
   5. The Central Mediterranean is highly affected by seafloor litter with 81 % of stations monitored classified under nonGES classes.
   6. In the Adriatic sub-region 65% of the stations monitored falling into the nonGES class with the highest percentage of seafloor stations to be classified under the moderate (35%) and poor (26 %) classes.
   7. The Eastern Mediterranean subregion is also affected by seafloor litter, since 68 % of the monitored stations are classified under nonGES class, with more or less equal share among the 3 nonGES classes.
   8. An uneven spatial distribution of stations within each sub-region is evident in the present study, for example the CEN is covered only by Malta and Tunisia.
   9. Fisheries-related items comprise up to 10% of the total recorded marine litter.
   10. 3 items are the most commonly recorded among fisheries related items : (i) Synthetic ropes/strapping bands (L1i) with 39%; Fishing nets (polymers) (L1f) with 27%; and Fishing lines (polymers) (L1g) with 25%.
   11. Another set of 3 items are recorded in minor percentages: (i) Natural fishing ropes (L5c) with 6%; (ii) Other synthetic fishing related” (L1h) with 2%; and (iii) Fishing related (hooks, spears, etc.) (L3f) with 1%.
   12. Interesting results have been obtained from limited scuba-dive surveys (972,500 ± 801,311 items/km²) and IMAP should further provide additional support and guidance to further expand this monitoring component for marine litter (IMAP EO10).

Measures and actions required to achieve GES

846. The legally binding Regional Plan on Marine Litter Management in the Mediterranean was introduced in 2013 (Decision IG.21/7, COP18); entered into force in 2014; and updated in COP 22 (Antalya, Turkey, 7-10 December 2022; Decision IG.25/9) to further reflect global and regional agenda relevant to marine litter management.

847. The Updated Regional Plan on Marine Litter Management includes stronger links to global agenda, i.e. the United Nations Environmental Assembly (UNEA) Resolutions on marine plastic litter, microplastics and single-use plastic products pollution; UNEP marine litter partnerships and initiatives like the Global Partnership on Marine Litter (GPML) and the Clean Seas Campaign; the IMO Action Plan to Address Marine Plastic Litter from Ships; the Basel Convention – Plastic Waste Partnership (PWP); as well as the EU Policies on Marine Litter and Plastic.

848. The Updated Regional Plan on Marine Litter Management:

1. 1. Introduces a number of new, region-wide agreed definitions on marine litter (e.g., ALDFG, BAT-BEP, Circular Economy, EPR, Fishing Gear, Lightweight plastic carrier bags, monitoring, micro-litter/plastics, primary/secondary microplastics, SUPs etc.);
   2. Expands the scope of measures in four key areas: (i) economic instruments, (ii) circular economy of plastics, (iii) land-based and (iv) sea-based sources of marine litter;
   3. Introduces ambitious, amended targets for plastic waste and microplastics; and
   4. Introduces two new appendices with lists on (i) single-use-plastic items, and (ii) chemical additives of concern used in plastic production further to the Stockholm Convention.

849. The Regional Plan also incorporates a number of additional, important principles and measures, including:

• • Phasing out single-use plastic items and promote reuse options;
  • Setting targets for plastic recycling and other waste items;
  • Introducing economic instruments such as environmental taxes, bans and design requirements, and Extended Producer Responsibility (EPR) schemes (land and sea-based sources);
  • Promoting new technologies and measures for the removal of marine litter;
  • Applying prevention measures to achieve a circular economy for plastics addressing the whole life cycle of plastics;
  • Reducing packaging;
  • Promoting voluntary agreements with industry;
  • Integrating the informal sector into regulated waste collection and recycling schemes;
  • Strengthening measures related to Sustainable Consumption and Production (SCP) programmes;
  • Phasing-out chemical additives used in plastic products, in particular those under Stockholm Convention;
  • Introducing concrete measures on microplastics reduction;
  • Implementing measures to prevent and reduce marine litter in Marine Protected Areas (MPAs);
  • Minimizing the input of marine litter associated with fisheries and aquaculture;
  • Establishing national marine litter monitoring programmes as part of IMAP EO10, including on riverine inputs and wastewater treatment plants (WWTP);
  • Enhancing public awareness and education; and
  • Introducing measures to Specially Protected Areas of Mediterranean Importance in the (SPAMIs) to combat marine litter.

850. Monitoring and assessment should be further linked and connected with the implementation of measures. Specific and well-elaborated findings can provide the basis for the implementation of targeted measures.

851. The presence of marine litter in the Mediterranean is variable, however tackling few items may yield promising and encouraging results pertinent to the health status of the marine and coastal environment.

852. Based on the assessment findings for both IMAP CI22 and CI23, most of the stations are under nonGES status and urgent action is required.

853. Cigarette butts and filters are predominant in the Mediterranean beaches and primarily require a behavioral change along with the implementation of strong anti-smoking policies and measures, including a strengthen communication campaign linking the damage in human health with the damage in the marine Cigarette filters do not contain only plastic, but also a cocktail of toxic substances (e.g., arsenic, lead, nicotine and pesticides, etc.) for which their effects in the marine biota and the marine environment still are unknown. The engagement of the cigarette companies in this process is of great importance, including their potential inclusion in a “polluters- pay” principle.

854. The vast presence of plastic bottles is documented by the third main item on the Mediterranean beaches, comprising of plastic caps and The introduction of sound alternatives and incentivizing the use of re-use caps could be among the possible options. Strengthening recycling and Extended Producer Responsibility schemes, targeted and tailored to tackle plastic bottles are also part of the solution, including the minimization of the small-sized bottles (<0.5 liters) which are easier to escape in the marine and coastal environment.

855. Microplastics of various types and shapes are escaping into the marine and coastal environment through wastewater treatment plants (WWTP). At the Mediterranean level, the Contracting Parties to the Barcelona Convention in their 22^nd COP (Antalya, Turkey, 7-10 December 2021) adopted Decision IG.25/8 related to the Regional Plans on Urban Wastewater Treatment and Sewage Sludge Management in the framework of Article 15 of the Land-based Sources Protocols. Among several measures to ensure their sustainable and safe use and discharge of wastewaters, the regional plan on wastewater treatment addresses for the first time in its scope microplastics. The updated Regional Plan calls for the introduction of emission limit values for emerging pollutants considering the identification of potential microplastic sources and adoption of related policy and methodology further to state of the art on related research on this topic.

856. The Regional Plan on Sewage Sludge Management gives particular attention to the presence and effective management of microplastics on Pharmaceuticals and Personal Care Products (PPCP) (e.g., lotions, soaps, facial and body scrubs and toothpaste) being present in sewage sludge and proposes methods for reduction at the source as provided hereunder:

1. 1. Regulatory approvals for new products potentially harmful to the environment to be introduced for most/all of personal care materials or However, the said measure may be difficult to be applied for medication products.
   2. Education on the correct use of substances containing drugs, and especially the use of the right dose without excess, including ecolabels to raise awareness of ecological impacts of PPCPs.
   3. Encouraging the return of unused or expired pharmaceuticals to specific collection points; and
   4. Subjecting wastewater originating from pharmaceutical industries, hospitals or healthcare centres to regulations that limit the concentration of organic pollutants in their effluents.

857. Wastewater treatment plants (secondary + tertiary levels of treatment with adequate sludge management) to efficiently remove microplastics from sewage, trapping the particles in the sludge and preventing of entrance into aquatic environments. Treatment plants are essentially taking the microplastics out of the wastewater and concentrating them in the sludge (Corradini et al., 2019). Therefore, sludge management is of great importance for microplastic removal. Controls should be exercised however on the subsequent use of sludge.

858. Measures that can contribute toward reducing sewage concentrations of microplastics include:

1. 1. 1. Bans on single-use plastics and microplastics in personal care and cosmetic products;
      2. Behavior changes and campaigns to reduce the use of such products;
      3. Certain textile designs can reduce microfibre generation during washing;
      4. Development of household-based systems to prevent microplastics from being released into sewer lines or directly into the environment; and
      5. Incineration of sewage sludge to avoid soil and water contamination by microplastics. Care should be exercised however to monitor and regulate pollutants in air emissions with a view to minimise these emissions as much as possible.

859. As rivers in most of the cases is the final repository of litter coming from the various land- based sources the application of measures on land are very relevant for the control and effective management of litter in riverine systems.

860. A Conceptual flow of plastic from production to consumption, waste management and leakage into the environment (i.e., land, rivers and ocean), including possible points of action for policies should be considered. Minimizing leakage on land will subsequently minimize the riverine inputs deriving from wind and rain transportation, as well as from direct dumping and sewerage, and will further reduce the amount of plastics (incl. microplastics) entering the ocean.

861. The updated Regional Plan on Marine Litter Management in the Mediterranean:

1. 1. Takes into consideration the occurrence and extent of marine litter accumulations, and calls for identification and assessment by the year 2025, on the impacts of these accumulations in upstream regions of rivers and their tributaries, and to apply measures to prevent or reduce their leakage into the Mediterranean, particularly during flood seasons and other extreme weather events;
   2. Envisages the application of enforcement measures to prevent, reduce and sanction illegal dumping and illegal littering in accordance with national and regional legislation, in particular on coastal zones and rivers, in the areas of application of the Regional Plan; and
   3. Couples the aforementioned provisions with aspects related to monitoring of marine litter originating from riverine inputs.

862. Storm water is an important contributor of riverine inputs of marine litter especially for the Mediterranean where seasonal, on several occasions extreme, weather events take place such as flash floods. And with the impacts of climate change, this aspect is becoming more significant as the Mediterranean is experiencing rainfalls, more intense and in shorter periods of time, the impact of which is less infiltration into the ground and more surface run-off.

863. A more systematic approach should be also offered when developing urban storm water management plans. Those plans typically address how urban storm water quantity and quality should be managed to protect ecological, social/cultural, and economic values. Urban storm water management plans are used to assist decision making to ensure that remedial measures (structural and non-structural) in existing developed areas are undertaken in a cost-effective, integrated and coordinated manner, and that decisions in relation to areas of new expansion (including redevelopment) are made with the implications for storm water impacts taken into account in order to achieve the quality goals for water bodies.

864. Urban storm water management (USWM) plans have been developed to a various extent across the This ranges from major cities having USWM Plans to smaller municipalities where such plans are non-existent, or at best are under preparation. USWM Plans in the Mediterranean mostly include only flooding control segments, i.e., no pollution control, while segments on risk management and information on location of land-based activities are covered only on a basic level. In some cases, some elements of the USWM plans are incorporated into Urban Plans but only to a limited extent, such as collection systems layout, principles and recommended techniques regarding flood and pollution control management, as well as principles on how to achieve environmental water quality goals for water bodies.

865. The Establishment of separate collection systems for surface water run-off should be also promoted. A separate storm water sewer system is a collection of structures, including retention basins, ditches, roadside inlets and underground pipes, designed to gather storm water from built-up areas and discharge it, with or without treatment, into local water bodies, e.g., streams, rivers, coastal waters (National Research 2009). Separate collection prevents the overflow of sewer systems and treatment stations during rainy periods and the mixing of the relatively little polluted surface run- off with chemical and microbial pollutants from municipal wastewater. Separate storm water systems allow for design of sewers and treatment plants that consider the volume of the wastewater only, while surface run-off and rainwater can be reused after a simplified treatment (e.g., for landscaping or agriculture).

866. Measures for combined collection systems are of great importance. Combined collection systems are sewer networks designed to collect rainwater runoff, domestic sewage, and industrial wastewater in the same pipe. Most of the time, combined sewer systems transport all of their wastewater to a wastewater treatment plant (WWTP) where it is treated and then discharged to a water body (National Research Council, 2009). During periods of heavy rainfall, however, the wastewater volume in a combined collection system can exceed the capacity of the sewer system or the treatment facilities, for which reason the combined collection systems are designed to overflow occasionally and discharge excess wastewater directly into nearby streams, flood drainage canals rivers, lakes or coastal waters.

867. A variety of additional measures could be also proposed with the aim of reducing the occurrence and impacts of storm water overflows and associated floods and pollution (Milieu, 2016), including the following:

1. 1. 1. End-of-pipe solutions such as building water storage capacity to optimising the use of the wastewater treatment plant and sewer system (e.g., using sewer networks for additional storage and optimising pumping operations);
      2. Reduction of clean storm water entering a sewer system (e.g., de-connecting impervious areas from combined sewer systems);
      3. Alternative green infrastructures as potentially cost-effective measures to reduce storm water (e.g., retention basins, infiltration trenches).

868. In addition, it would be valuable to close the knowledge gaps by gathering comparable information across the Mediterranean on the extent of storm water overflows from combined collection systems, which should include inventory of the locations of overflow structures, inventory of functioning of the overflow structures, inventory of sewage storage capacity structures (e.g. starting with agglomerations of more than 100,000 p.e.), with the aim of acquiring better understanding of the occurrence of storm water overflows and their impacts on the quality of receiving water bodies.

869. Promoting Sustainable Urban Drainage Systems (SUDS) is another measure which aims to minimize the impervious cover by promoting infiltration, ponding, and harvesting of storm water runoff. Furthermore, in this decentralized management approach, storm water runoff and pollution are primarily controlled by measures located near the source to strive towards well-integrated measures that perform multiple functions, including flood protection, pollution removal and groundwater recharge, as well as recreation, biodiversity and urban aesthetics.

870. The Fisheries sector, including both fishing and aquaculture activities have a contribution on marine litter generation.

871. In the past years, considerable attention has been brought to the scale of abandoned, lost and discarded fishing gear (ALDFG), the impacts on the marine environment through ghost fishing, and possible measures for reducing its occurrence like the FAO Voluntary Guidelines on the Marking of Fishing Gear. Given that aquaculture now supplies over half the seafood produced worldwide, it is considered of great importance that this issue is also examined at farm level, especially given the continued expansion of global aquaculture development (Huntington, 2019).

872. Measures targeting specifically on aquaculture farming should focus on overall recommendations and to propose measures scoping to reduce marine litter from aquaculture, block the relevant pathways to the marine environment and reduce the contribution to marine plastic pollution by Moreover, a second level of measures should be introduced touching upon the specific requirements and standards to be applied on a mandatory basis for aquaculture practices.

873. Measures that can contribute to reduced generation of marine litter from aquaculture include the following:

1. 1. Replace to the extent possible plastic infrastructure components with other of physical nature.
   2. Use higher density plastics (e.g., Polyethylene terephthalate (PET) or Ultra-high molecular weight polyethylene (UHMWPE)) which are more resistant to fragmentation, UV-irradiation.
   3. Reduce single-use plastic with the introduction of relevant alternatives and invest in developing recovery, cleaning and re-distribution schemes.
   4. Minimize the use of plastic types with low levels of recyclability.
   5. Reduce to the extent possible the use of equipment consisting of different types of plastic (i.e., different lifespan and different approach for collection and recycling).
   6. Ensure to the extent possible that all packaging is reusable or recyclable.
   7. Reduce to the extent possible packaging and over-packaging to minimize packaging waste.
   8. Develop awareness raising trainings for aquaculture staff similar to those offered from the shipping sector (e.g., HELMEPA).
   9. Reduce to the extent possible the use of single-use plastics and establish relevant policies;
   10. Minimize the use of plastic types with low levels of recyclability;
   11. Reduce to the extent possible the use of equipment consisting of different types of plastic (i.e., different lifespan and different approach for collection and recycling).

874. Moreover, aquaculture should ideally apply a circular approach planning considering the whole life cycle of the used High procurement standards should be introduced, especially when dealing with purchasing of equipment, packaging, polystyrene boxes and other types of consumables and equipment.

875. With regards to plastic pollution, the updated Regional Plan on Marine Litter Management calls for:

1. 1. 1. Innovative business practices to prevent plastic waste generation in line with the Extended Producer Responsibility approach through the establishment of Deposit/Refund System for expandable polystyrene boxes in the commercial and recreational fishing and aquaculture sectors; and
      2. Prevention measures aiming to achieve, to the extent possible, a circular economy for plastics (Regulate the use of primary microplastics, Implement Sustainable Procurement Policies, Establish voluntary agreements, Establish procedures and manufacturing methodologies, Identify single-use plastic products, Set targets to phase out production and use, increase the reuse and recycling, Phase-out chemical additives used in plastic products, Promote the use of recycled plastics, substitute plastics, Implement standards for product labelling, Establish dedicated collection and recycling schemes, minimize the amount of marine litter associated with fishing/aquaculture, Scale-up and replicate sustainable models).