Interim report of the HELCOM CORESET project

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196 4. Policy relevance Nonylphenol and octylphenol are both listed under the HELCOM BSAP and under the EU Priority Substances. Descriptor 8, criterion 8.1 of the MSFD. BSAP, ecological objective Concentrations of hazardous substances close to natural levels. 5. Use of the indicator in previous assessments Thematic assessment of hazardous substances (HELCOM 2010). 6. Current monitoring Monitored by Denmark, Germany and Sweden. 7. Proposed or perceived target setting approach with a short justifi cation. Environmental Quality Standards. 4.25. Intersex or vitellogenin induction in male fi sh The candidate indicator for measuring the estrogenic activity and its effects is developed by the BONUS+ project BEAST. This report lacks a proper documentation for the indicator. Table 4.4. Overview of the use, monitoring, cause-effect relationships, assessment criteria and available guidance. Used by OSPAR CEMP or pre- CEMP MEDPOL 1) Used in national monitoring programmes in Baltic Sea countries 2) Research monitoring data available Studied in large Baltic Sea research projects 2) DE, SE, DK BEEP BEAST BAL- COFISH Biological Indication (BI) Cause/effect (C/E) relationship BI – exposure to estrogenic contaminants Availability of AC specifi c for the Baltic Sea (for detailes see Table 1 BAC, EAC under development (BEAST) Monitoring Guidelines, other important info QA Method costs (High-Medium- Low) ICES TIMES 31 QA–NO Low costs Abbreviations – BAC – Background Assessment Criteria – EAC – Environmental Assessment Criteria (concentrations above which there is concern that negative effects might be observed in marine organisms. EAC describes the direct linkage to adverse health effects of the individuals) – AC – Numerical Assessment Criteria – QA – Quality Assurance measures – CEMP – guidelines, quality assurance and assessment tools are in place - monitoring of the component is mandatory for OSPAR contracting parties – pre-CEMP – agreed to be included as components of the CEMP, guidelines, QA tools and/or assessment tools are currently not all in place. Monitoring of the components is voluntary Country codes: DK-Denmark, EE-Estonia, FI-Finland, DE-Germany, LV-Latvia, LT-Lithuania, PL-Poland, RU- Russia, SE-Sweden
4.26. Acetylcholinesterase (AChE) General information General properties The analysis of acetylcholinesterase (AChE; EC 3.1.1.7) activity and its inhibition in marine organisms has been shown to be a highly suitable method for assessing exposure to neurotoxic contaminants in aquatic environments. AChE activity method is applicable to a wide range of species and has the advantage of detecting and quantifying exposure to neurotoxic substances without a detailed knowledge of the contaminants present. AChE activity is a typical biomarker that can be used in in vitro bioassays and fi eld applications. Main impacts on the environment and human health AChE has traditionally been used as a specifi c biomarker of exposure to organophosphate and carbamate pesticides. More recently, its responsiveness has been demonstrated to various other groups of chemicals present in the marine environment including heavy metals, detergents and hydrocarbons. Its usefulness as a general indicator of pollution stress in mussels from the Baltic Sea has been shown within the EU-BEEP project. AChE inhibition mostly agreed well with the studied pollution gradients, especially in mussels. Seasonal differences in activity were notable in fl ounder, eelpout and mussels, possibly resulting from variations in the occurrence of affecting substances (e.g., pesticides from river input or run-off from agricultural sources) during the year. Additional fi eld studies and laboratory experiments showed that AChE in Baltic mussels is infl uenced by temperature and salinity, while also salinity has an effect on the uptake (and therefore on toxicity) of substances (Lehtonen et al. 2006). Status of a compound on international priority lists and other policy relevance OSPAR pre-CEMP, MED POL Phase IV (2º Tier). ICES SGIMC has recommended AChE in molluscs as biomarker to be included into the OSPAR Coordinated Environmental Monitoring Programme (pre-CEMP). AChE has been adopted by UNEP as part of the second tier of techniques for assessing harmful impact in the Mediterranean Pollution programme (MEDPOL Phase IV). GES boundaries and matrix The existence of extremely low thresholds for induction of inhibitory effects on AChE suggests that detection is possible after exposure to low concentrations of insecticides (0.1 to 1 μgl-1; ICES 2010). Standardisation of the sampling strategy and regular intercalibration exercises on specifi c organisms are still necessary before using AChE in routine pollution monitoring. No formal quality assurance programmes are currently run within the BEQUALM programme but one major intercalibration exercise was carried out during the BEEP project. Baseline levels of AChE in different marine species have been estimated from results derived from in the Atlantic Ocean, the Mediterranean and the Baltic Sea (Table 4.6; ICES 2010) and ongoing studies within Bonus+ BEAST. Generally it has been accepted that 20% reduction in AChE activity in fi sh and invertebrates indicates exposure to neurotoxic compounds. Depression in AChE activity more than 20% up to 50% indicates sublethal impact. In the fi eld, several species have baseline AChE activities within the same order of magnitude 197
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Baltic Sea Environment Proceedings
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2 Helsinki Commission Katajanokanla
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4 4.16. Cumulative impact on benthi
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6 descriptions of the indicators. T
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8 The CORESET expert group on biodi
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10 fi sh stocks and change in diet,
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12 Figure 2.3. The prevalence of pr
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14 Seasonal changes in blubber thic
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16 Blubber thickness suggestions Bl
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18 Weaknesses/gaps Monitoring of th
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20 2.3. Population growth rate of m
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22 Annual adult survival 1 0,95 0,9
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24 Existing monitoring data Informa
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26 References Bäcklin, B. M. 2011.
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28 Reproduction in the Baltic eagle
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30 Breeding success The proportion
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32 of the real number of nestlings
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34 Gaps and weaknesses Minimum dete
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36 2.5. Abundance of wintering popu
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38 Table 2.10. Pressures affecting
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40 Refrences Skov et al. (2000) Bir
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42 termined by application of the 7
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44 Approach for defi ning GES All s
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46 Sampling It is suggested to incl
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48 2.7. Fish population abundance 2
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50 Coastal Fish - Community Abundan
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52 When a reference data set cannot
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54 well, but were not included in t
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56 Weighting For Nordic Costal mult
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58 12. Current monitoring Monitored
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60 Błeńska M., Osowiecki A., Kra
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62 10. Spatial considerations Fucus
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64 2.15. Trend in the arrival of ne
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66 jectives is to reach “No intro
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68 Sweden Figure 2.23 shows the rat
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70 Strengths and weaknesses of data
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72 need to be revisited in light of
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74 Considering the data set availab
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76 In Denmark, the highest contamin
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78 Status of a compound on internat
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80 A temporal analysis (EU-RAR 2006
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82 Pathways of PFOS to the Baltic e
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84 In regions less affected by anth
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86 3.4. Polychlorinated biphenyls a
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88 actions related to the environme
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90 The CORESET expert group decided
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92 pheric deposition pattern (lowes
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94 3.5. Polyaromatic hydrocarbons (
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96 GES boundaries and matrix Existi
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98 Quality Assurance of PAH metabol
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100 Ariese F, Burgers I, Oudhoff K,
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102 GES boundaries and matrices Exi
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104 3.7. Cesium-137 Authors: Jürge
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106 Figure 3.5. Average surface lev
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108 Temporal trends in concentratio
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110 Other important sources are glo
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112 Conceptual model of the sources
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114 3.8 Tributyltin (TBT) and the i
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116 GES boundaries and matrix Exist
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118 Monitoring the compound Status
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120 Recommendation TBT measurements
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122 3. Frogs have been shown to app
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124 not fi sh (Köhler et al. 2002;
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126 The use of different fi sh spec
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128 Kirchin, M.A. Moore, M.N. Dean,
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130 3.11. Fish Disease Index: Exter
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132 Confounding factors The multifa
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134 analyses ICES data from various
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136 An EAC is the threshold beyond
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138 3.12. Micronucleus test Authors
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140 main nuclei were not counted as
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142 ing national data sets. Note: t
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144 Baršienė J. Rybakovas A. 2006
Page 148 and 149: 146 3.13 A. Reproductive disorders
Page 150 and 151: 148 dead larvae can be induced by s
Page 152 and 153: 150 Strand, J, Dahllöf, I. (2005).
Page 154 and 155: 152 of contaminants in sediments wi
Page 156 and 157: 154 Eriksson Wiklund, A-K., and Sun
Page 158 and 159: 156 4. Candidate indicators for bio
Page 160 and 161: 158 Zooplankton-phytoplankton bioma
Page 162 and 163: 160 4.2. By-catch of marine mammals
Page 164 and 165: 162 4.3. Impacts of anthropogenic u
Page 166 and 167: 164 4.4. Fatty-acid composition of
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Page 170 and 171: 168 10. Spatial considerations Balt
Page 172 and 173: 170 4.10. Large fi sh individuals f
Page 174 and 175: 172 11. Temporal considerations Sam
Page 180 and 181: 178 A proposal for an approach to a
Page 182 and 183: 180 Technical data Metadata This is
Page 184 and 185: 182 F igure 4.1. Map showing the cu
Page 186 and 187: 184 4.17. Biomass of copepods 1. Wo
Page 188 and 189: 186 4.19. Zooplankton species diver
Page 190 and 191: 188 indirectly impacted by eutrophi
Page 192 and 193: 190 Notes for the GES boundary The
Page 194 and 195: 192 Step 3: Prepare a list of speci
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Page 204 and 205: 202 5.1. Summary of all supplementa
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Page 208 and 209: 206 5.5. Biopollution level index 1
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Page 212 and 213: 210 Balanus improvisus Baltic Katte
Page 214 and 215: 212 Figure 5.3. The scheme for asse
Page 216 and 217: 214 5.6. Organochlorine compounds G
Page 218 and 219: 216 EU Directive 2008/105/ EC Daugh
Page 220 and 221: 218 Table 5.4. Monitoring of HCB, H
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