Modelling-based strategy for the Prioritisation Exercise ... · 1 Nicola Chirico, Raquel N. Carvalho, Lidia Ceriani and Teresa Lettieri Modelling-based strategy for the Prioritisation

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Nicola Chirico, Raquel N. Carvalho, Lidia Ceriani and Teresa Lettieri

Modelling-based strategy for the

Prioritisation Exercise under the Water

Framework Directive

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Report EUR xxxxx xx

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European Commission

Directorate General Joint Research Centre

Institute for Environment and Sustainability

H01-Water Resources Unit

Contact information

Teresa Lettieri

Address: Joint Research Centre, Via E. Fermi, 2749 - TP 121 - 21027 Ispra (Varese), Italy E-mail: [email protected]

Tel.: +39 0332 789868

https://ec.europa.eu/jrc

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Abstract

The Water Framework Directive 2000/60/EC (WFD) aims to protect the aquatic environment at European level by achieving the good chemical

and ecological status of all water bodies. In order to reach the good chemical status of their waterbodies, Member states should monitor the

Priority Substances listed in Annex 10 of the WFD and they should ensure that the concentrations of these substances or groups of substances

in the aquatic environment do not exceed the related Environmental Quality Standards, set to protect human health and the environment

(Directive 2008/105/EC amended by Directive 2013/39/EU). Priority substances that are persistent, toxic and liable to bioaccumulate or which

give rise to a similar level of concern are identified as Priority Hazardous Substances. Under Article 16 (4) of the WFD, later amended by

Directive 2013/39/EU, the Commission is required to review the list of substances designated as Priority Substances and Priority Hazardous

Substances every six years. The ongoing prioritisation process is coordinated by JRC in collaboration with DG ENV and the expert sub-group of

the Working group chemicals. The process includes two approaches, the monitoring and modelling based exercises. The first has been

developed considering the available monitoring data and criteria for selection of substances undergoing this exercise. The latter has been

conceived for those substances for which either monitoring data are insufficient or completely missing. This report is focused on the

modelling-based exercise to explain the screening phase process and the models used to derive the Predicted Environmental Concentration

(PEC) required to determine the risk assessment based on the ratio between the PEC and Predicted No Effect Concentration (PNEC).

mailto:[email protected]

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Table of contents 1

1 Abbreviations .............................................................................................................................. 4 2

2 Background .................................................................................................................................. 6 3

3 Introduction ................................................................................................................................. 6 4

4 Initial list ....................................................................................................................................... 7 5

5 The Modelling-based exercise ............................................................................................. 12 6

5.1 Data collection for both the screening and the risk assessment phase ................................................ 12 7

5.2 The screening phase ........................................................................................................................... 12 8

5.2.1 Exposure score .............................................................................................................................. 13 9

5.2.2 Hazard score ................................................................................................................................. 15 10

5.2.3 The Scoring system ....................................................................................................................... 21 11

5.3 The Risk Assessment Phase ................................................................................................................ 22 12

5.3.1 Introduction .................................................................................................................................. 22 13

5.3.2 PEC for freshwater ........................................................................................................................ 24 14

5.3.3 PEC for sediment for substances passing the trigger value Log Koc and Log Kow 3 ..................... 27 15

5.3.4 PEC for biota ................................................................................................................................. 28 16

5.4 Hazard assessment – estimation of PNEC values ................................................................................ 29 17

5.4.1 PNEC derivation ............................................................................................................................ 29 18

6 Final Ranking ............................................................................................................................. 29 19

7 Final remarks ............................................................................................................................ 30 20

8 Acknowledgements ................................................................................................................. 30 21

9 References .................................................................................................................................. 31 22

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1 Abbreviations 25

ADI Acceptable Daily Intake 26

BCF Bioaccumulation Factor 27

BMF Biomagnification Factor 28

CIS Common Implementation Strategy 29

CLP Classification, Labelling and Packaging 30

CMR Carcinogenic, Mutagenic, toxic for Reproduction 31

CoRAP Community Rolling Action Plan 32

CRED Criteria for Reporting and Evaluating ecotoxicity Data 33

DB Data Base 34

DG EN Directorate-General for Environment 35

DNEL Derived No Effect Level 36

DSD Dangerous Substance Regulation 37

dw Drinking Water 38

ECETOC European Centre for Ecotoxicology and Toxicology of Chemical 39

ECHA European Chemical Agency 40

ECOSTAT Expert group for Ecological Status of water quality 41

EC10 Effect Concentration for 10% of the individuals in a toxicity test 42

ED Endocrine Disruptor 43

EFSA European Food Safety Authority 44

EMA European Medicines Agency 45

EMEA Former EMA acronym 46

EPA Environmental Protection Agency 47

ERC Environmental Release Category 48

ESVAC European Surveillance of Veterinary Antimicrobial Consumption 49

EQS Environmental Quality Standard 50

ESIS European chemical Substances Information System 51

ETUC European Trade Union Confederation 52

EqP Equilibrium partitioning method 53

FOCUS FOrum for the Co-ordination of pesticide fate models and their USe 54

fw ` Freshwater 55

hh Human Health 56

Koc Organic carbon adsorption coefficient 57

IARC International Agency for Research on Cancer 58

INERIS Institut National de l'Environnement Industriel et des Risques 59

IUCLID International Uniform Chemical Information Database 60

JDS2 Second Joint Danube Survey 61

LC50 Lethal Concentration for 50% of the individuals in a toxicity test 62

LD50 Lethal Dose for 50% of the individuals in a toxicity test 63

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LET Literature Evaluation Tool 64

LOD Limit Of Detection 65

LOQ Limit Of Quantification 66

MACRO Model of water flow and solute transport in field soils 67

MS Member State 68

NOAEL No-Observed Adverse Effect Level 69

NOEC No-Observed Effect Concentration 70

OECD Organisation for Economic Co-operation and Development 71

OSPAR Protection of the marine Environment of the North-East Atlantic 72

PBT Persistent, Bioaccumulative and Toxic 73

PEC Predicted Environmental Concentration 74

PNEC Predicted No Effect Concentration 75

PHS Priority Hazardous Substance 76

PPP Plant Protection Product 77

PRZM Pesticide Root Zone Model 78

PS Priority Substance 79

RBSP River Basin Specific Pollutants 80

SPIN Substances in Preparations in Nordic Countries 81

REACH Registration, Authorisation and Restriction of Chemicals 82

RIWA Association of River Water Supply Companies 83

RIVM National Institute for Public Health and the Environment (NL) 84

RA Risk Assessment 85

RQ Risk Quotient (PEC/PNEC) 86

sec pois Secondary poisoning 87

sed Sediment 88

spERC Specific Environmental Release Category 89

STOT RE Specific Target Organ Toxicity Repeated Exposure 90

SVHC Substances of Very High Concern 91

SWASH Surface WAter Scenarios Help 92

TDI Tolerable Daily Intake 93

TNECS Technical Committee for New and Existing Substances 94

TG n. 27 Reference no. 18 95

TOXSWA TOXic substances in Surface WAters 96

TRA Targeted Risk Assessment 97

UBA Umwelt Bundesamt (Federal Environment Agency of Germany) 98

vB Very Bioaccumulative 99

vP Very Persistent 100

WFD Water Framework Directive 101

102

103

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2 Background 104

The Water Framework Directive 2000/60/EC (WFD) has established a strategy for water 105

protection that included specific measures for pollution control to achieve good ecological and 106

chemical status at European level. Good chemical status has been defined in terms of 107

compliance with European environmental quality standards (EQS) for substances of concern, to 108

make sure that the concentrations found in the environment are below a safety limit, not 109

causing any harmful effects to or via the aquatic environment. Annex I of the Directive 110

2013/39/EU [2] lists forty-five PS and Priority Hazardous Substances (PHS), which have been 111

selected amongst those which present a significant risk to or via the aquatic environment. 112

Under Article 16 (4) of the WFD, later amended by Directive 2013/39/EU, the Commission is 113

required to review the list of substances designated as Priority Substances and Priority 114

Hazardous Substances every six years. Currently, the adopted list of PS is under review with the 115

aim of identifying new substances for priority action at Union level, setting and revising EQS for 116

those newly identified substances, and for some existing substances, respectively. 117

118

3 Introduction 119

The scientific and technical methodology for the current review has been developed by the JRC 120

in consultation with DG ENV and the sub-group of experts for the review (or SG-R), sub-group of 121

the Working Group Chemicals. Two main steps characterise the present prioritisation exercise 122

which as the last time includes both the monitoring and modelling based exercises [3]. First, the 123

assembling of an initial list of substances which could potentially be harmful to the 124

environment, that was compiled using all available databases provided by institutions, 125

stakeholders and peer-reviewed papers. 126

The subsequent step consisted of splitting substances into the modelling and monitoring 127

exercises (see Figure 1, for a view of the whole process). All substances that have been 128

monitored in at least four MS were considered in the monitoring-based exercise. All the 129

remaining substances (the ones for which less than 4 MS provided monitored data) were 130

considered for the modelling based exercise, characterised by two serial processes, i.e. the 131

screening and the risk assessment phase. However, during the 3rd SG-R meeting, it was asked 132

whether the substances undergoing through the monitoring based exercise could be analysed 133

performing the screening phase process. 134

The screening phase is the process that ranks the substances using both exposure and hazard 135

scores. The exposure score is based on the tonnage and the use of a substance, while the hazard 136

score is based on both the environmental and organism toxicity. The substances with the 137

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highest score are included into the risk assessment phase, where both PEC (Predicted 138

Environmental Concentration) and PNEC (Predicted No-Effect Concentration) are derived, and 139

the corresponding Risk Quotient (PEC/PNEC, RQ) is calculated. The RQ is an estimate of the 140

exposure at which ecosystems are likely not suffer any harm [4]. 141

This report is focused on the modelling-based exercise to explain the screening phase process 142

and the models that are used to derive the PEC required for the RQ calculation. 143

144

145

Figure 1. Outline of the modelling based exercise. The present report will be focused on the modelling 146

based exercise, which comprises a screening phase and a risk assessment phase. 147

148

149

4 Initial list 150

In accordance with Art. 16 of the WFD [1], substances shall be prioritised for action on the basis 151

of risk to or via the aquatic environment. For this purpose, an initial list of 11549 substances, 152

which could potentially pose a risk to the environment, was compiled from several databases 153

(DB), reports and peer-reviewed papers. Inputs from stakeholders, international organizations 154

were collated as well. Specific lists have been assembled for biocides, endocrine disruptors (ED), 155

marine pollutants, illicit drugs, pesticides, human and veterinary medicines, and some cosmetic 156

ingredients. 157

Table 1 details the sources used and the respective number of substances. 158

159

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160

161

Source Description Number of substances

ECHA-SVHC [5] List of Substances of Very High Concern (SVHC) 149

ECHA-CoRAP [6] List of the substances included in the Community Rolling Action Plan (CoRAP) 2013-2015, amended with the CoRAP list 2015-2017

260

ECHA-Biocides [7] List of approved Biocidal active substances, updated 07/05/2015 82

EU Pesticides database [8]

List of substances approved, pending and not plant protection products 441

European Environment Agency [9]

State of the Environment reporting 630

ECOSTAT-RBSP [10]

Substances identified by Member States as River Basin Specific pollutants 377

ESIS-CLP [11] Substances CLP classified as H400, H410, H411, H412, H413 2196

Norman List [12] this list, identified by NORMAN, comprises the currently discussed emerging substances and emerging pollutants (latest update March 2011), such as surfactants, flame retardants, pharmaceuticals, personal care products, nanoparticles, gasoline additives and their degradation products, biocides, polar pesticides and their degradation products, and various confirmed or suspected ED compounds

913

INERIS Report from the previous review [13]

Substances of the previous Monitoring-based ranking exercise were collated as well

1014

OSPAR List of Substances of Possible Concern [14]

collection of hazardous substances which are of possible concern to the marine environment, developed by OSPAR

246

OSPAR List of Chemicals for Priority Action [15]

list of substances potentially persistent, liable to bioaccumulate and toxic 31

OECD High Production Chemicals DB [16]

list of all the High Production Volume (HPV) chemicals which have been or are being investigated in the Screening Information DataSet (SIDS) programme

1469

Endocrine disruptor’s database (EU Commission) [17]

list of substances that showed (potential) evidence for ED effects. Only chemicals that belong to Category 1 and 2 were considered

277

Substitute It Now! (SIN) List [18]

the chemicals on the SIN List have been identified by ChemSec as Substances of Very High Concern (SVHC) based on the criteria established by the EU chemicals regulation REACH

772

Second Joint Danube Survey (JDS2) [19]

list of compounds identified in the surface water of the Danube River and its tributaries during the second monitoring survey along the Danube river

271

Scoping Prioritisation Report (2014) [20]

it describes a procedure proposal for the identification and prioritisation of PS built upon the outcome of the previous review of PS. Substances from table 4.2 of the report were included. These substances ranked high in either the monitoring- or the modelling-based exercises of the last review of PS, but were not short-listed for prioritization

81

TCNES’ PBT List [21]

list of substances whose PBT profile has been investigated by the Technical Committee for New and Existing Substances (TCNES) group

117

First and Second Priority List of Environment Canada [22]

list of substances that should be assessed on a priority basis to determine whether they pose a significant risk to the health of Canadians or to the environment

48

European Trade Union Confederation

list of the most urgent Substances of Very High Concern for inclusion in the Candidate List and, eventually, in the Annex XIV (the Authorisation List)

711

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(ETUC) List [23]

US EPA Priority Chemicals list [24]

list of PS identified by the Environmental Protection Agency (EPA). The American National Waste Minimization Program focuses efforts on reducing these Priority Chemicals found in their nation's products and wastes by finding ways to eliminate or substantially reduce the use of PS in production

18

Vewin-RIWA [25] Communication from Dutch and Belgian drinking water operators on substances which breach drinking water standards or the target values for rivers in Europe.

26

Environmentally classified pharmaceuticals 2014, Stockholm County Council [26]

list of pharmaceuticals assessed by the Stockholm County Council 37

EurEau-Pharma 2014 [27]

list of pharmaceuticals of concern to drinking water 24

MistraPharma DB [28]

the MistraPharma DB, also called WikiPharma DB, contains publicly available ecotoxicity data for pharmaceutical substances, focusing on human pharmaceuticals available on the Swedish market

159

Screening program 2013 - New bisphenols, organic peroxides, fluorinated siloxanes, or-ganic UV filters and selected PBT substances [29]

the occurrence and environmental risk of a number of new bisphenols, organic peroxides, fluorinated siloxanes, organic UV filters and selected PBT substances were reported for wastewater effluents and leacha-tes, as well as sediments and biota from Oslofjord and Lake Mjøsa

38

Wikipedia Sunscreen ingredients’ List [30]

list of FDA’s approved active ingredients in sunscreens 28

JRC-IES marine pollutants [31]

Marine pollutants from literature collection 131

Von der Ohe et al. 2011 [32]

risk assessment of 500 organic substances based on observations in the four European river basins of the Elbe, Scheldt, Danube and Llobregat.

499

Lopez-Roldan et al. 2013 [33]

development of several indicators based on toxicity (PNEC) and on legislation levels (EQS) for river aquatic ecosystems assessment for screening potential chemical stressors.

6

Pal et al. 2013 [34]

review of the occurrence and concentration levels of illicit drugs and their metabolites in different environmental compartments (e.g. wastewater, surface waters, groundwater, drinking water, and ambient air) and their potential impact on the ecosystem.

13

Kools et al. 2008 [35]

environmental risk-based ranking of veterinary medicinal products. Only substances with risk indices higher than 5 for the compartment water and aquatic organisms have been included in the initial list

77

Grung et al. 2008 [36]

environmental risk assessment of eleven pharmaceuticals was performed following the guidelines from the European Medicines Evaluation Agency (EMEA).

6

Bottoni et al. 2010 [37]

review article of the relevance of pharmaceuticals, for human and veterinary use as well as of their biologically active transformation products, as environmental micropollutants.

184

Roos et al. 2012 [38]

comparison of similarities and differences in overall ranking results of 582 Active Pharmaceutical Ingredient (APIs) from nine previously proposed prioritisation schemes, both risk and hazard-based.

47

Iatrou et al. 2014 [39]

estimation of the potential environmental risks associated with human consumption of antimicrobials were estimated in Greece.

8

Kostich & Lazorchak 2007 [40]

estimation of risks associated with exposure to human prescription pharmaceutical residues in wastewater from marketing and pharmacological data

4

Boxall et al. 2003 [41]

a two-stage prioritisation scheme was developed and applied to veterinary medicines in use in the UK.

52

Capleton et al. it proposes a method for prioritising veterinary medicine APIs according 34

10

2006 [42] to estimates of their potential for indirect human exposure via the environment and their toxicity profile, and demonstrates its feasibility using an initial set of 83 veterinary medicine APIs approved for use in the UK.

Zuccato et al. 2000 [43]

list of drugs thought to be putative priority pollutants according to selected criteria. Most drugs were measurable in drinking or river waters and sediments in Lombardy (Italy), suggesting that pharmaceutical products are widespread contaminants, with possible implications for human health and the environment.

16

Sarmah et al. 2006 [44]

review of the latest information available in the literature on the use, sales, exposure pathways, environmental occurrence, fate and effects of veterinary antibiotics (especially, tylosin, tetracycline, sulfonamides and, to a lesser extent, bacitracin) in animal agriculture.

14

Dong et al. 2013 [45]

paper on a prioritization approach on 200 most-prescribed drugs in the US (2009). The approach is based on the number of prescriptions and toxicity information, accounting for metabolism and wastewater treatment removal.

43

162

Table 1. List of data sources for compiling the initial list of substances to be reviewed in the current 163

prioritisation exercise 164

165

Congeners of substances were considered separately for the initial list, and an eventual 166

grouping of substances was considered only at a later stage. Mixtures were not included, since 167

the risk assessment process for these category is not yet finalised and clear. 168

In this way, the starting number of 11549 substances was reduced to 6525 whose 573 169

substances went through the monitoring-based exercise, and the remaining 5952 through the 170

modelling-based exercise. 171

A summary of all the sources and the related number of substances is illustrated in Figure 2. 172

173

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174

175

Figure 2. Summary of the sources of data used for the substances’ collection, with the respective 176

logarithmic number of substances considered. 177

178

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5 The Modelling-based exercise 179

5.1 Data collection for both the screening and the risk assessment phase 180

The exposure and toxicological data were retrieved by several sources required both for the 181

screening phase and the risk assessment phase. Several web-sites and databases were consulted 182

- ECHA portal, EFSA, RIVM, EMA, IARC, European Pesticides database, Footprint Pesticides 183

Properties database, EPA, IUCLID, Endocrine Disruptors Database. Generally, both the relevance 184

and reliability of the publications retrieved from the above sources, i.e. EFSA Conclusions, 185

REACH Dossiers, European Review Reports, IARC Monographs, European Risk Assessment 186

Reports, EPA Reports, were deemed acceptable, since it was supposed that they had been 187

previously reviewed by a competent authority. The Classification, Labelling and Packaging 188

(CLP) classification of substances, officially made by ECHA, is used for the definition of a 189

substance as carcinogenic, mutagenic, and toxic to reproduction (CMR scoring). 190

Data collected for the exposure assessment and PEC calculation comprised physical and 191

chemical properties (molecular weight, water solubility, vapour pressure, biodegradability, 192

sorption potential and bioaccumulation potential), tonnage (of use, manufacture and import) 193

and specific Environmental Release Category (spERC) codes. These codes provide indication of 194

the usages of a substance allowing then to know the percentages of dispersion in the 195

environmental compartments for the modelling tools. 196

Concerning the risk assessment phase, the collection of hazard data for the aquatic and 197

sediment compartments included acute and chronic toxicity data, typically the most sensitive 198

LC/EC50 or NOEC/EC10 endpoints. Regarding mammalian or human toxicity effects from oral 199

exposure, data were collected for repeated dose toxicity, carcinogenicity, mutagenicity and 200

repro-toxicity tests, focusing on typical endpoints such as NOAEL, DNEL, ADI and TDI values. In 201

all those cases where new literature was considered in addition to the sources listed above, 202

reliability assessment of the ecotoxicological data was done by using a literature evaluation tool 203

(LET) [46], based on the Criteria for Reporting and Evaluating ecotoxicity Data (CRED) check 204

list [47] and further relevant publications were searched for. 205

206

207

5.2 The screening phase 208

The number of substances (5952) that are listed for the modelling exercise needs to be ranked 209

to select the ones of most concern. To reach this goal, every substance is categorised according 210

to its dangerousness (hazard score) and the quantity that is expected to be found in the 211

environment (exposure score). These scores are used as the indexes of a matrix that combines 212

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the hazard with the exposure scores, such matrix gives the final risk score of a substance as a 213

result (details will be provided in the following paragraphs of the present report). 214

The exposure and hazard information searched for all the substances are shown in Table 2. 215

216

Exposure Amount produced (tonnage)

Use pattern

Hazard Persistency

Bioaccumulation

Toxicity

Carcinogenicity

Mutagenicity

Reproduction toxicity

Endocrine disruption potential

217

Table 2. Exposure and hazard properties collected for the screening phase. Exposure is defined by the 218

tonnage of the substance and its use pattern (that is the degree of dispersion). Hazard is defined by the 219

ecotoxicity of a substance (persistency, bioaccumulation and toxicity) and its toxicity (carcinogenicity, 220

mutagenicity, reproduction toxicity and endocrine disruption potential). 221

222

5.2.1 Exposure score 223

To determine the exposure score, both the use pattern and the total tonnage of a substance are 224

needed, the approach is the same used in the previous prioritisation exercise [48]. 225

The use pattern is associated with the degree of dispersion of a substance and a corresponding 226

use index is associated as shown in Table 3. 227

228

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229

Use pattern Use index

Used in the environment 1

Wide dispersive use (diffuse sources

and substances in wastewater)

0.75

Non-dispersive use (industrial,

controlled point sources)

0.5

Not known 0.25

Controlled system (isolated

intermediate)

0.1

230

Table 3. Use pattern and use index association. The use pattern corresponds to the degree of dispersion of 231

a substance that is here associated to a numerical value (use index). 232

233

Where available, the use pattern of the substances is taken from the worst case ERC 234

(Environmental Release Category) code associated with the substance, otherwise the use 235

pattern is assessed from any additional available sources (e.g. from literature), while in other 236

case is straightforward (e.g. PPPs are always expected to be used in the environment). 237

The exposure score is associated to the use assessment (that is the expected tonnage of a 238

substance found in the environment), split (distributed) in five value ranges, as shown on Table 239

4. Each exposure score is associated to the corresponding range of use assessment. The use 240

assessment is calculated multiplying the tonnage of a substance by the use index. 241

242

243

Use assessment (tons) Exposure score

0–1 0

1–10 1

10–100 2

100–1'000 3

>1'000 4

244

Table 4. Use assessment and corresponding exposure score. The exposure score is obtained looking at the 245

corresponding use assessment range (that is the tonnage of the substance expected to be found in the 246

environment). 247

248

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Tonnage values for Europe have been collected from several sources. Under a confidentiality 249

agreement with the European Chemicals Agency, the JRC can retrieve the information from the 250

submitted dossiers under the REACH regulation. Additionally, the Substances in Products in the 251

Nordic Countries (SPIN) database (countries are: Norway, Sweden, Denmark and Finland) has 252

been examined. To extrapolate an European tonnage values, the population statistics are used. 253

Data on pharmaceuticals consumption are available for six MS, France (Besse et al, 2008 [49]), 254

Greece (Iatrou et al, 2014 [39]), Germany (UBA report [50]), Portugal, Denmark and Latvia (the 255

agency of PT, DK and LV provided directly to JRC a list of pharmaceuticals sales/consumption). 256

These data are then used to extrapolate the total tonnage for Europe, based on population 257

number (human pharmaceuticals) or animal production (veterinary pharmaceuticals). 258

For antimicrobial substances used as veterinary pharmaceuticals the data have been retrieved 259

from the EMEA ESVAC reports [51-53] and used as main source of information. Since these data 260

reports only class of pharmaceuticals, the corresponding tonnage is applied to every single 261

pharmaceutical belonging to each class as a worst case assumption. 262

In all other cases, if it is not possible to extrapolate the tonnage due to the lack of data, the 263

substance would get a final exposure score of “0”. 264

265

5.2.2 Hazard score 266

A substance is evaluated considering the persistence, bioaccumulation and toxicity (clustered as 267

PBT), its carcinogenicity, mutagenicity and reproductive toxicity (clustered as CMR) and 268

endocrine disruptor potential (classified as ED). For the latter classification, a careful attention 269

should be devoted since at moment there is not yet a real and official classification as endocrine 270

disruptor. All these components are scored separately (i.e. P, B, T, C, M R, ED) and then summed 271

up to obtain the final hazard score. Sources of hazard data are listed in section 5.1, However 272

ECHA for industrial and inorganic chemicals, and EFSA for plant protection products, have been 273

the main sources. 274

In general, for each substance, more than one value/evaluation can be found for every 275

component of the assessment. In this case, after having assessed the reliability of the collated 276

data, the most hazardous value is chosen as a precautionary approach. 277

The criteria used to decide whether a substance has to be regarded as PBT or vPvB are provided 278

in the ECHA guidance for the PBT assessment Chapter R.11 [54]. For the purposes of hazard 279

assessment in the screening phase, whenever the respective P, or B, or T criteria are fulfilled, a 280

score of 1 was assigned to each property, respectively. If no data is available, a score of 0.1 is 281

assigned. The scoring system is summarized in Table 5. 282

283

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P score B score T score Meaning

1 1 1 yes

0 0 0 no

0.1 0.1 0.1 no data available

284

Table 5. P, B and T scoring system adopted. Persistence (P), bioaccumulatation (B) and toxicity (T) in the 285

environment are criteria that in this exercise are either fulfilled (yes, score 1) or not (no, score 0). When 286

there is no data available a score of 0.1 is assigned as default. Individual scores are summed in the hazard 287

score. 288

289

Following the aforementioned table, a substance classified as PBT will be score 3. Additionally, 290

substances that are very persistent and significantly bioaccumulative in the food chain (vPvB), 291

will also score 3, in order to account for the higher hazard they likely pose. The PBT and vPvB 292

criteria do not apply to inorganic substances, but shall apply to organo-metals. 293

PBT and vPvB assessment has been done following rules as shown in the figures 3-5. 294

In order to determine the persistence of a compound the ECHA guidance [54] has been followed. 295

The first run has been followed for PBT and vPvB criteria, according to section 1 of Annex III to 296

REACH. If not successful, section 3.1 has been applied and, if successful the criteria under study 297

has been reported as “indicative” (the score for the hazard assessment, anyway, does not 298

change, but “indicative” is reported for clarity). If a reliable dossier (e.g. from ECHA) reported a 299

PBT assessment its conclusions has been reported instead. 300

301

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302

Figure 3. Rules for assessing whether a substance is Persistence (P) and/or very persistence (vP). First 303

the rules for determining if a substance is vP are checked then if not fulfilled, the ones for P are followed. 304

If none of the aforementioned rules can be met, an “indication” for the P property is evaluated. These 305

rules are extracted from the ECHA guidance for PBT assessment [54] 306

307

308

309

310

311

312

18

313

Figure 4. Rules for assessing whether a substance is Bioaccumulative (B) and/or very bioaccumulative 314

(vB). First the rules for determining if a substance is vB are checked then if not fulfilled, the ones for B are 315

followed. If none of the aforementioned rules can be met, an “indication” for the B property is evaluated. 316

These rules are extracted from the ECHA guidance for PBT assessment [54] 317

318

319

320

321

322

323

324

325

326

327

328

329

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330

Figure 5. Rules for assessing whether a substance is Toxic (T). First the rules for determining if a 331

substance is T are checked then if not fulfilled, an “indication” for the T property is evaluated. These rules 332

are extracted from the ECHA guidance for PBT assessment [54] 333

334

335

336

337

338

Regarding the scoring system assigned to the CMR (Carcinogenicity, Mutagenicity, and 339

Reproduction Toxicity) properties, the IARC classification for carcinogenicity 340

(http://monographs.iarc.fr/ENG/Classification/), the older DSD (Dangerous Substance 341

directive) classification system and the CLP Regulation 342

(http://echa.europa.eu/en/regulations/clp) are mainly followed to classify the substance. DSD 343

classification is used (categories 1 to 3) however, to harmonise the different categories, table 6 344

shows the correlation values. Table 7 summarise the scores for each property. 345

346

20

347

Directive/Regulation DSD CLP IARC

Category 1 1a 1

2 1b 2a

3 2 2b

348

Table 6. Equivalence among classification systems of the different Regulations/directives, i.e. DSD, CLP, 349

IARC. Cat. 1 – known human carcinogen/mutagen/reproductive toxicant; Cat. 2 – presumed human 350

carcinogen/mutagen/reproductive toxicant; Cat. 3 – suspected human carcinogen/mutagen/reproductive 351

toxicant. 352

353

354

355

C score C MEANING M score M MEANING R score R MEANING

1 1:CAT. 1 1 1:CAT. 1 1 1:CAT. 1

0.75 0.75: CAT.2 0.75 0.75: CAT.2 0.75 0.75: CAT.2

0.5 0.5:CAT. 3 0.5 0.5:CAT. 3 0.5 0.5:CAT. 3

0.25 0.25: UNDER EXAMINATION/EXAMINED AND INSUFF INFO/NOT EXAMINED



0 0: EXAMINED AND NOT CLASSIFIED



356

Table 7. Scoring system used for the classification of substances according to the CMR properties (C 357

means carcinogenic, M means mutagenic and R means toxic for reproduction). For each property (CMR) a 358

score is associated to a DSD category (see Table 6 and the corresponding caption for more details). The 359

remaining scores are: 0 when the property is not being fulfilled or 0.25 (default value) when the 360

substance is under study or not sufficient data is available to assess the property. 361

362

Concerning pharmaceuticals, even though they are expected not being CMR (at least in human), 363

they are known to be highly biologically active. Since their impact in biota cannot be excluded in 364

principle, the default value (0.25: UNDER EXAMINATION/EXAMINED AND INSUFF INFO/NOT 365

EXAMINED) has been assigned as a precautionary approach. 366

Finally, endocrine disrupting (ED) properties are investigated as well, although this information 367

is often missing. The corresponding scoring system is shown in Table 8. It is here recalled that 368

no official definition of endocrine disruptors have been so far provided, thus choosing the score 369

of a substance using Table 8 has an inherent uncertainty. 370

21

371

ED ED MEANING

1 1: PROVEN ED EFFECTS

0.5 0.5: SUSPECT ED EFFECTS

0.25 0.25: NOT EXAMINED

0 0: EXAMINED AND NOT CLASSIFIED AS ED

372

Table 8. Scoring system used for the classification of possible endocrine disruptor substances [55]. 373

374

Data on ED are mainly retrieved from the EDS database and other sources, e.g. literature. This 375

information is evaluated case by case ad a score is associated. 376

Once obtained, the final hazard score is given by the sum of the PBT, CMR and ED scores so far 377

detailed. 378

379

5.2.3 The Scoring system 380

Once the hazard score and the exposure score are obtained their values have to be used in order 381

to select an appropriate risk score. In the previous prioritisation exercise a matrix [48] was used 382

for this purpose as reported in Table 9. 383

384

385

386

Table 9. Risk scores matrix used in the previous prioritization exercise. 387

388

In order to obtain the risk score of a substance, both the hazard and the exposure scores are 389

used to select the respective risk value from the matrix. Lower is the risk score obtained from 390

the matrix, higher is the concern about the substance. Because of the range of the hazard 391

assessment score from 0 to 7, the above matrix has been rescaled in the present exercise. In this 392

way, 5 classes of hazard score range are generated, as shown in the Table 10. 393

394

Exposure assessment score

22

Ha

zard

ass

ess

me

nt

sco

re

4 3 2 1 0

Class 4 (5.6 to <= 7.0) 1 1 2 3 5

Class 3 (4.2 to < 5.6) 1 2 2 3 5

Class 2 (2.8 to < 4.2) 2 2 3 4 5

Class 1 (1.4 to < 2.8) 3 3 4 4 5

Class 0 (0.0 to < 1.4) 5 5 5 5 5

395

Table 10. Rescaled risk scores matrix using ranges of hazard scores. Red numbers are for the molecules 396

of the highest concern, which will be thus surely selected in this exercise. 397

398

Substances with the lowest score in the matrix will be selected for the RA phase of the 399

modelling-based exercise upon discussions with the sub-expert group for the prioritisation 400

exercise. 401

402

5.3 The Risk Assessment Phase 403

5.3.1 Introduction 404

Modelling tools are used to calculate the predicted environmental concentrations (PEC). In a 405

broad sense, they are based on mathematical methodologies which simulate the environmental 406

scenario where a substance is supposed to be applied. Different classes of substances are 407

usually simulated by different tools because they are differently expected to be released into 408

environment. For example, a pesticide requires a scenario which is different comparing with a 409

human pharmaceutical, since the first one is directly applied to the environment, while the 410

second one is expected to be released in the sewage system. 411

For substances that are expected to be released directly in the environment (plant protection 412

products and veterinary pharmaceuticals in the present exercise), the FOCUS surface water 413

scenario tools have been chosen. Basically, these tools simulate the fate of substances upon 414

virtual scenarios based on real data. 415

The FOCUS tools (FOCUS stands for FOrum for the Co-ordination of pesticide fate models and their 416

USe) allow calculations for four levels of a tiered approach, spanning from level 1 -the simplest 417

that requires minimum input data, giving the highest PECs because is set as the worst case 418

scenario - to level 4, which is the most refined one. In this exercise, level 3 has been selected as 419

the best compromise between required input data and accuracy of the prediction. Ten 420

representative EU scenarios, with their related hydrology, soil type and weather conditions, are 421

simulated. For the chosen scenario(s), the crop type, and the pattern of application of a 422

23

substance are crucial, because they both have an impact on the substance fate. FOCUS steps do 423

not require the tonnage of the applied substance. 424

Due to the likely entry route of veterinary pharmaceuticals into environment, i.e. by direct 425

release to the soil, or as manure application, it is possible to estimate the application rate of 426

these substances, and therefore to also carry out PEC calculations with the FOCUS tools - Step 3. 427

For the inorganic compounds, industrial substances and biocides, the ECETOC Targeted Risk 428

Assessment (TRA) tool, developed by the ECETOC organisation, has been chosen for PEC 429

calculations. The simulated scenarios are based on default environmental release codes (ERC), 430

which were developed by ECHA. The ERCs are industrial and consumers use descriptors which 431

set specific substance release percentages into the environmental compartments (air, water and 432

soil). However, in the present exercise, specific ERC (spERC) codes are used as a refinement of 433

the ERC-based emission estimation. In this way, more realistic default values of the fractions 434

released to water, air, and soil are considered. The main issue of using ECETOC is represented 435

by the need of tonnages as input data. 436

The last class of substances considered are human pharmaceuticals. In this case, the related 437

exposure scenario consists of substances that are released in the sewage, and thus ending in the 438

wastewater treatment plant. For the PEC calculation of human pharmaceuticals a simple 439

formula, taken from the publication of Besse et al. [49], is applied. 440

The following Table 11 details the tools used in this exercise for the aforementioned class of 441

substances. 442

443

Class of substances PEC calculation method Compartment involved

Plant Protection Products (PPPs) FOCUS Step 3 Water, Sediment

Biocides ECETOC – Tier 2 Water, Sediment

Generic industrial uses ECETOC – Tier 2 Water, Sediment

Inorganic compounds ECETOC – Tier 2 Water, Sediment

Veterinary pharmaceuticals FOCUS Step 3 Water, Sediment

Human pharmaceuticals Simplified EMA equation Water

444

Table 11. Methods used for calculating PEC values of the different classes of substances. FOCUS is a set of 445

tools and scenarios that simulates the fate of substances released in the environment (FOCUS is tailored 446

for plant protection products, but can also be adapted for veterinary pharmaceuticals). ECETOC Tier 2, 447

available as a set of Excel files, is a set of models that simulate the fate of substances and is tailored for 448

industrial/indoor use of substances. 449

450

24

5.3.2 PEC for freshwater 451

5.3.2.1 Plant protection products 452

FOCUS Step 3 has been selected for the PEC calculation of plant protection products (PPP). The 453

exposure assessment of PPPs is performed according to the Generic guidance for FOCUS surface 454

water Scenarios - Version 1.4 (May 2015), available online at 455

http://esdac.jrc.ec.europa.eu/projects/surface-water. A tiered approach is used to assess the 456

exposure assessment of PPPs in surface water, and the guidance document [56] details how to 457

choose the appropriate application windows, crop interception factors, degradation rates and 458

coefficient of distribution Koc of the substance. The FOCUS SWASH shell (Step 3), which handles 459

the input data and the requested tools, is adopted for estimating concentrations of PPPs in 460

ditches, ponds and streams based on ten different European scenarios. The SWASH shell 461

coordinates models which simulate runoff (R scenarios) and erosion (PRZM), leaching to field 462

drains (D scenarios) (MACRO), spray drift (internal in SWASH) and finally aquatic fate in 463

ditches, ponds and streams (TOXSWA). These simulations provide detailed assessments of 464

potential aquatic concentrations in a range of water body types for up to ten separate 465

geographic and climatic settings. 466

Once physical-chemical parameters of the substances to be assessed are provided to SWASH, 10 467

EU representative soil-climate scenarios are available for simulations and, for each scenario, a 468

set of representative crops can be selected. Location of scenarios are showed on Figure 6. In 469

order to obtain reasonable PECs using FOCUS, crops and typical pesticide application rates are 470

of pivotal importance. These data are obtained from the Good Agricultural Practice (GAP), 471

available from EFSA Conclusions or European Review reports of the active substances. The 472

highest resulting PEC value among R and D scenarios will be selected for the subsequent RQ, as 473

worst case assumption. 474

25

475

476

Figure 6. FOCUS EU scenario locations for surface water PEC calculations (D = drainage, R = runoff). 477

Details and representativeness of the scenarios can be found in the generic guidance for FOCUS surface 478

water scenario [56]. 479

5.3.2.2 Biocides, metals and generic industrial uses compounds 480

The ECETOC Targeted Risk Assessment (TRA) tool has been selected for the PEC calculation of 481

biocides, inorganics and generic industrial uses compounds. This tool handles scenarios that 482

correspond to the different ERC/spERC codes which are based on substance’s usage. Tonnages 483

and usage information are retrieved from IUCLID and the SPIN DB. This type of information is 484

crucial for the outcome of the exercise, since ECETOC needs tonnage values. For inorganic 485

compounds, modelled/measured Kp water-soil or water-sediment is used, along with biotic and 486

abiotic degradation rates set to 0. 487

For every substance more than one ERC/spERC code may be available, as it can be seen in the 488

example shown in Figure 7. For each of them, the PEC is calculated and the worst-case value is 489

selected for the calculation of the final RQ. 490

26

491

492

493

Figure 7. Example of part of ECETOC input about tonnages and sp/ERC codes. 494

495

5.3.2.3 Veterinary pharmaceuticals 496

As outlined in the EMA guidance [57], VetCalc model and the suite of models developed by the 497

FOCUS are the two main available options for refined PECfw calculations. In the current 498

prioritisation exercise, FOCUS models were selected as the tool of choice for the exposure 499

assessment of veterinary pharmaceuticals. In fact, although being specifically developed for 500

plant protection products (PPPs), FOCUS models’ predictions can also be used for veterinary 501

pharmaceuticals, with appropriate precautions and model settings (see Table 7). This is due to 502

the similarities between the field application of PPPs and the spreading of veterinary 503

pharmaceuticals (by means of manure or grazing animals) to the soil. The available scenario 504

that is deemed appropriate for the EMA setup (i.e. winter cereals) is used and the corresponding 505

PECs is calculated. 506

507

27

508

Parameter Input values considered

Crop Winter cereals

Application timing Pre-emergence application dates

Application rate (AR) Calculated from PECsoil,initial (in general, use of PECsoil calculated for intensively

reared animals, or pasture animals) by using EMA equation.

DT50 of substance Experimental value, if available. Otherwise, set to zero.

Crop uptake None

Application method Soil or granular incorporation

Wash-off factor Wash-off factor (m-1): ≥ 10-6, even if there is no wash-off.

Depth (m) Soil depth used to calculate PECsoil

509

Table 12. FOCUS model settings for exposure assessment of veterinary pharmaceuticals [57] 510

511

5.3.2.4 Human pharmaceuticals 512

For human pharmceuticals, PEC values is calculated using the following equation A [49] 513

514

PECfw= (consumption × Fexcreta) / (WWinhab × hab × dilution × 365) (A) 515

516

where WWinhab is the volume of wastewater per person per day (default value of 200 517

[L/(hab*day]), hab is the number of inhabitants, Fexcreta is the excretion factor of the active 518

substance (retrieved from the same publication), dilution is the dilution factor (default value of 519

10), consumption is the quantity (mg/year) of active ingredient consumed by the population 520

during 1 year. 521

This simplified approach can be chosen because of the relatively simple scenario when 522

modelling human pharmaceutical fate (wastewater is the most common fate because of the 523

excretion of these substances). Consumption is the most difficult value to be found because data 524

is available only for few MS (see Screening phase section for more details) and often only for a 525

limited number of substances. As a consequence the tonnage for the Europe is extrapolated for 526

the EU total population. In the previous Watch List exercise [46], the worst case PEC value 527

among those estimated for each antibiotic was selected for the risk quotient (RQ) calculation. 528

5.3.3 PEC for sediment for substances passing the trigger value Log Koc and Log Kow 3 529

For the calculation of the PECsed ECETOC results is used for inorganic compounds and generic 530

industrial substances, whenever tonnages values are available, and FOCUS Step 3 is adopted for 531

PPPs and veterinary pharmaceuticals. Lastly, both for those substance whose information is 532

lacking for the correct use of ECETOC, and for human pharmaceuticals, the sediment 533

28

equilibrium partition method (EqB) will be used for PECfw calculation, following the TG n. 27- 534

CIS WFD [58] 535

536

𝑃𝐸𝐶𝑠𝑒𝑑−𝑤𝑤 =Ksed-water

RHOsed PECfw 1000 (𝐵) 537

538

RHOsed is the bulk density of wet sediment, Ksed-water is the partition coefficient between 539

sediment and water and 1000 is the conversion factor from m3 to litre. 540

Since the final PECsed is calculated in terms of dry weight, a conversion step is required, by using 541

the following equations C and D. 542

543

𝐶𝑂𝑁𝑉𝑠𝑒𝑑 =𝑅𝐻𝑂𝑠𝑒𝑑

𝐹𝑠𝑜𝑙𝑖𝑑𝑆𝑒𝑑 𝑅𝐻𝑂𝑠𝑜𝑙𝑖𝑑 (𝐶) 544

545

𝑃𝐸𝐶𝑆𝑒𝑑 = 𝐶𝑂𝑁𝑉𝑠𝑒𝑑 𝑃𝐸𝐶𝑠𝑒𝑑−𝑤𝑤 (𝐷) 546

547

For the calculation of KSed-water, the following equation E will be used. 548

549

𝐾𝑠𝑒𝑑−𝑤𝑎𝑡𝑒𝑟 = 𝐹𝑎𝑖𝑟𝑠𝑒𝑑𝐾𝑎𝑖𝑟−𝑤𝑎𝑡𝑒𝑟 + 𝐹𝑤𝑎𝑡𝑒𝑟𝑠𝑒𝑑 + 𝐹𝑠𝑜𝑙𝑖𝑑𝑠𝑒𝑑 𝐾𝑝𝑆𝑒𝑑

1000 𝑅𝐻𝑂𝑠𝑜𝑙𝑖𝑑 (𝐸) 550

551

Default values for Fairsed, RHOsolid, Fwatersed, Fsolidsed and Focsed are taken from TG n. 27 - CIS 552

WFD [58]. The given default value for Fairsed is zero [58]. 553

554

5.3.4 PEC for biota 555

PEC for biota is calculated considering the bioaccumulation through the food chain, for fresh 556

water organisms, exemplified as BCF →aquatic organisms→BMF→fish→fish eating predators. 557

BCF is the bioconcentration factor that accounts for the concentration of the substance from 558

water to the organism while BMF is the biomagnification factor that accounts for the increasing 559

of the substance concentration in the organism through the food chain. 560

For the calculation of the PEC for biota (PECbiota) the following equation is used [59]. 561

562

𝑃𝐸𝐶𝑏𝑖𝑜𝑡𝑎 = 𝑃𝐸𝐶𝑓𝑤 𝐵𝐶𝐹 𝐵𝑀𝐹 (𝐹) 563

564

29

5.4 Hazard assessment – estimation of PNEC values 565

5.4.1 PNEC derivation 566

Substance risk assessment in the water compartment is relevant for the protection of organisms 567

inhabiting the water column. Therefore, the protection threshold concentrations PNECfw is 568

estimated for the substances that will be selected from the screening phase. 569

The PNEC value is the concentration of a substance for which it is expected no harm for the 570

environment, in our case water bodies (in this exercise only long-term PNEC, i.e. those for 571

chronic effect, are considered). 572

Whenever sufficient data are available, the probabilistic approach is carried out for the 573

derivation of the PNEC. An adequate AF is then applied to the derived HC5 (Hazardous 574

Concentration to 5 % of species), following the 5 recommendations set in the ECHA guidance 575

(Chapter R 10, 2008). 576

When there is not enough data available, the deterministic approach is used. For the calculation 577

of the PNEC, representative trophic levels have to be considered - algae, crustaceans and fishes, 578

which mimic a typical hypothetical food chain of a fresh water body. For each trophic level, the 579

highest toxicity level of a representative species is considered. For each substance, according to 580

its properties, a PNEC value for fresh water-sediment (PNECsed) (TG n. 27- CIS WFD [58] and the 581

ECHA Guidance (2008) [60]) and PNEC values for secondary poisoning in biota (PNECbiota, sec pois) 582

are calculated for all substances with a potential to bioaccumulate, following the TG n. 27 - CIS 583

WFD [58]. 584

Drinking water is a possible route of human exposure to substances in water, and the PNEC for 585

human drinking water (PNECdw, hh) have been derived for all substances, based on human 586

toxicity data. If available, WHO [61] or EU [62] drinking water standards have been used as the 587

PNECdw, hh values for that substance. When a WHO drinking water standard is not available, the 588

PNECdw, hh is calculated as detailed in the TG n. 27 - CIS WFD [58]. 589

590

591

6 Final Ranking 592

Risk quotients (RQ) will be estimated for all the relevant receptors at risk, i.e. RQfw, RQsed, 593

RQbiota,secpois , RQbiota,hh, RQdw,hh, and for the respective group of substances considered, i.e. human 594

pharmaceuticals, veterinary pharmaceuticals, biocides, inorganic compounds, generic industrial 595

uses and PPPs. Measured Environmental Concentrations (MEC) will be used as a decision-596

supporting information whether available for the selection of the most toxic substances. 597

Moreover, feedbacks from the experts of the SG-R and Working Group of Substances will also be 598

30

taken on board for the final ranking of the most hazardous compounds according to the current 599

modelling based risk assessment. 600

601

7 Final remarks 602

The approach described in this report, although validated on representative data, has to be 603

intended as a proposal since some details could change during the finalisation of the procedure, 604

when applied to the whole initial list. The number of the substances in the initial list is also 605

expected to change slightly because of possible further refinements and updates. 606

607

8 Acknowledgements 608

We are grateful for the collaboration with ECHA and EFSA, and for their support on data 609

collection. 610

Sales data on human pharmaceuticals were kindly provided by the State Agency of Medicines of 611

the Republic of Latvia, the INFARMED National Authority of Medicines and Health Products of 612

Portugal, the Federal Environment Agency of Germany, the Statens Serum Institut and the DHI 613

group of Denmark. 614

Finally, we would like to thank Helen Clayton and Stephanie Schaan for helpful discussion and 615

for the revision of the report. 616

617

618

31

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620

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