Environmental quality standards for diclofenac derived under the European Water Framework Directive: 3. Marine ecotoxicity

Environmental quality standards for diclofenac derived under the European Water Framework Directive: 3. Marine ecotoxicity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Environmental quality standards for diclofenac derived under the European Water Framework Directive: 3. Marine ecotoxicity Dean Leverett, Iain Wilson, Lucy Kennelly, Tom Austin, Cameron Hird, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6295199/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Diclofenac is a nonsteroidal anti-inflammatory human and veterinary medicine widely detected in European waters downstream of Wastewater Treatment Plants. Proposed Environmental Quality Standards (EQS) for diclofenac, which include an assessment of toxicity to aquatic organisms, have been proposed by the European Commission to support the objectives of the Water Framework Directive, including EQS aimed at protecting marine species. In this paper, we present previously unpublished studies assessing the effects of diclofenac on four marine species, three echinoderms and an annelid worm. The results of these new tests were incorporated into the long-term marine ecotoxicity dataset for diclofenac and an updated marine EQS derived. Finally, these updated prospective EQS were compared with measured diclofenac concentrations in European marine waters to assess potential risk. Results Limited effects on fertilisation were measured in echinoderms at diclofenac concentrations beyond environmental relevance. However, fertilisation in the annelid worm Arenicola marina was found to be sensitive to diclofenac exposure, with a No Observed Effect Concentration of 578 ng/L. Using the updated marine ecotoxicity dataset for diclofenac, prospective marine EQS of 58 and 37 ng/L were derived, respectively, using deterministic and probabilistic (species sensitivity distribution) derivation approaches. The indicative compliance of European marine waters with the prospective EQS is 79–97%. Conclusions Comprehensive investigations into the potential of diclofenac to inhibit fertilisation on echinoderms and annelid worms failed to reproduce the extremely sensitive results previously reported in published studies. The reduced sensitivity observed here were potentially a result of methodological differences between the studies, such as pre-exposure of gametes versus exposure only during fertilisation, the time allowed for the fertilisation process, as well as the possibility of differential uptake of diclofenac owing to use of a solvent or pH variation. Compliance with the prospective EQS depended on the method used to treat the censored measured concentration data but was generally high across all monitored European marine waters. This entirely marine-focused hazard and risk assessment suggests that a proposed EU EQS of 4 ng/L, derived entirely from a single freshwater mesocosm study, is likely to be over-precautionary for European marine waters. Diclofenac Marine Environmental quality standard Ecotoxicity European Water Framework Directive Figures Figure 1 Background The European Water Framework Directive (WFD) (2000/60/EC) aims to restore all surface waters to ‘good’ status. One of the chemical metrics used to assess status is the Environmental Quality Standard (EQS). In Europe, EQS set centrally by the European Commission are legally binding and therefore drive regulatory action to reduce the concentrations of chemicals in surface waters. EQS are intended to be environmental matrix-specific; different EQS values are usually presented for fresh and marine waters although these are very often derived from the same (usually freshwater) data and separated only by the magnitude of the assessment factor applied. Diclofenac is a nonsteroidal anti-inflammatory (NSAID) human and veterinary medicine that has been widely detected in European surface waters, and which primarily enters these waters in discharges from Wastewater Treatment Plants (WWTPs)(Carvalho et al., 2016 ; Simon et al., 2022 ). Diclofenac behaves conservatively in conventional wastewater treatment processes, with relatively low levels of removal being achieved (Patrolecco et al., 2015 ; Tiedeken et al., 2017 ; Dos Santos et al., 2022 ). This means that long-term exposure of aquatic organisms to diclofenac in European waters occurs downstream of some WWTPs. In Parts 1 and 2 of the work on Environmental quality standards for diclofenac derived under the European Water Framework Directive (Leverett et al., 2021 ; Maack et al., 2022 ; Leverett et al., 2022 ; Peters et al., 2022 ) the approaches taken to derive EQS for diclofenac were evaluated, and issues highlighted with the derivations for direct toxicity and secondary poisoning biota proposed by the European Commission (EC)(EC 2022). In particular, the reliability and plausibility of some of the data underpinning the EC’s assessments were questioned, and alternatives suggested to the approaches applied by the EC. There is no intention to re-open that debate in this third manuscript on the effects of diclofenac on aquatic organisms, which focuses specifically on the marine environment. As part of the development of the chronic ecotoxicity dataset for diclofenac, intended to support the EQS derivation, a programme of new testing was established. This comprised a series of studies using freshwater and marine invertebrates, with primary objectives of filling clear taxonomic gaps in the long-term aquatic effects dataset for diclofenac. This included attempts to repeat some exceptionally sensitive ‘no effect’ concentrations previously published for reproductive effects in echinoderms and marine worms (Zanuri et al., 2017 ). The marine element of our testing programme comprised four GLP-compliant studies performed between 2019 and 2024, the long duration of the programme being a result of the Covid-19 pandemic, and related subsequent difficulties in obtaining test organisms of sufficient quality for the studies. All four of these studies were previously unpublished in the open scientific literature. The marine EQS proposed by the EC (EC 2022) is based directly on a single freshwater mesocosm study (Joachim et al., 2021 ), also used to deterministically derive the freshwater EQS. An Assessment Factor of 50 has been applied to a reported EC10 value of 0.2 µg/L for mortality in female stickleback, Gasterosteus aculeatus , giving a marine EQS of 0.004 µg/L (4 ng/L) diclofenac. However, as highlighted previously (Leverett et al., 2021 ; 2022 ), we do not consider these data sufficiently reliable for derivation of a freshwater or marine EQS for diclofenac. A small amount of long-term marine ecotoxicity data were included in the EC’s EQS assessment (EC 2022) however, it was not possible to undertake a statistical comparison to evaluate potential differences in sensitivity to diclofenac of freshwater and saltwater species. This had no impact on the final EQS proposed by the EC for fresh and marine waters (EC 2022) since the derivation approach applied did not ultimately utilise the long-term aquatic ecotoxicity dataset for fresh or marine waters. Materials and Methods The original intention in undertaking these studies was to repeat the studies reported by Zanuri and colleagues in 2017. However, some important differences between those studies (as reported) were applied, comprising: i) undertaking the studies in a highly controlled and quality-assured (GLP-compliant) laboratory environment; ii) increasing the resolution of effect/ no effect thresholds by an expansion of the diclofenac concentration to which the test organisms were exposed, and a decrease in the interval between test concentrations; iii) increasing environmental realism by exposing sperm and oocytes together during fertilisation, rather than individually and prior to mixing; iv) extending the fertilisation exposure period to ensure the maximal opportunity for fertilisation, and v) in two of the tests, evaluating the influence of a short (acute) pre-exposure of adult animals immediately prior to gamete collection for fertilisation assessments. Seawater The seawater used for organism husbandry and the diclofenac tests was obtained from Torbay, Devon, UK before undergoing treatment prior to use. The pH of the seawater was 8.0 ± 0.5, with a salinity 34.5 ± 1.5‰. Further detailed analysis of other parameters including a range of metals, pesticides, total organic carbon (TOC) and PCBs is conducted quarterly (under non-GLP conditions), and is provided in the supplementary material. On-site treatment typically included protein skimming, filtration to 10 µm and UV exposure. Additional filtration was applied immediately prior to use. Analytical method for determination of diclofenac in seawater The method used to determine the actual exposure concentrations of diclofenac in the test solutions (filtered natural seawater) was validated in accordance with the SANCO/3029/99 rev.4 11/07/00 guideline (Sanco 2000). The limit of quantification (LOQ) was determined as the lowest concentration tested at which an acceptable mean recovery (70–110%) with an acceptable relative standard deviation (RSD; <20%) was obtained. The LOQ of the method for seawater was set as 0.0050 µg/L. Seawater samples were extracted/concentrated using solid phase extraction (SPE) cartridges, eluted, and then analysed using LC-MS/MS. An internal standard was used to assess the acceptability of the method. The full analytical method is supplied in the supplementary material. Statistics For the sea urchin and marine worm tests, statistical analysis of fertilisation and embryo-larval development data was undertaken using the CETIS statistical package (versions 1.9.4.9 and 2.1.5.5, respectively). Statistical analysis in the starfish test was performed using the ToxRat solutions statistical package (version 3.3.0). A Bonferroni adjusted ttest and a Dunnett’s multiple comparison test was used for NOEC/LOEC determination in the sea urchin tests. The Jonckheere-Terpstra step-down trend test was used for NOEC/LOEC determination in the marine worm test. A step-down Cochran-Armitage trend test was used for NOEC/LOEC determination in the starfish test. Linear interpolation (ICPIN) was used in determining EC x values (where possible) for the sea urchin and marine worm tests. Linear regression (Weibull) was used in determining EC x values for the starfish test. The Species Sensitivity Distribution (SSD) used for derivation of prospective EQS was constructed using the Canadian SSD software package (shiny)ssdtools (Dalgarno ( 2018 ))(ssdtools version: 2.2.0, shinyssdtools version: 0.3.5). The key feature of (shiny)ssdtools is the use of a technique known as model averaging. In the context of SSD modelling, the approach fits multiple distributions to a toxicity dataset and uses the weights of the fits of each distribution to construct a model-averaged SSD. (shiny)ssdtools contains a set of ‘default’ distributions (currently the Gamma, Log-Gumbel, Log-Logistic, Log-Normal, Lognormal-Lognormal and Weibull) that are automatically used to construct a model-averaged SSD. Source of test organisms Adult Paracentrotus lividus and Psammechinus miliaris were obtained, respectively, from the Scottish Association for Marine Science (SAMS), Oban, UK, and an offshore mussel farm in Lyme Bay, Devon, UK. Both species of sea urchin were maintained at the Scymaris laboratory in filtered seawater under a 16L:8D (light:dark) photoperiod, held at 15°C and fed Laminaria sp. (kelp) ad hoc prior to use for testing. Adult starfish, Asterias rubens , were collected from the wild off the coast of Torbay, Devon in the UK, and maintained at the laboratory in filtered seawater under a 16L:8D (light:dark) photoperiod at 11°C, and fed blue mussels ( Mytilus edulis ) ad hoc . All echinoderms used for testing were sexed prior to the studies and then held in known sex groups for at least two weeks prior to use for testing. Adult lugworms, Arenicola marina , were collected from the wild population at Paignton Beach, Devon, UK, during the spawning season (October 2023). They were maintained in single-sex tanks using natural sediment from the collection site, under flow through conditions using filtered seawater at 12 ± 2°C, and fed with small granular pellets as required. Adult exposures In the tests with sea urchins, adult animals were exposed to diclofenac at an identical nominal concentration range as the gametes taken from the adults for subsequent fertilisation tests. Adult exposures lasted for 96 hours immediately prior to gamete collection. The studies using starfish and A. marina did not incorporate pre-exposure of adult animals before spawning. Full details are given in the supplementary material. Fertilisation tests For the fertilisation tests, ooctyes and sperm taken from adult animals were combined and exposed to a wide range of diclofenac concentrations for 3 to 4 hours. After this time, samples were removed from each replicate exposure and fixed using neutral buffered formalin. Numbers of fertilised embryos and unfertilised oocytes were then assessed in each sampler using light microscopy. Successful fertilisation was defined as division of the zygote. Full details are given in the supplementary material. Embryo-larval development test In the study with the sea urchin Paracentrotus lividus , fertilised embryos were exposed for a further 48 hours in order to assess embryo-larval development, at the same nominal diclofenac concentrations as applied in the fertilisation tests. Full details are given in the supplementary material. Searches for additional data to support EQS derivation Given the time elapsed since the EC’s EQS derivation for diclofenac (EC 2022), and in an attempt to supplement the long-term marine dataset included in the EC’s assessment, new literature searches for marine ecotoxicity data were undertaken for the present assessment. Full details are given in the supplementary material. In addition, three relatively recent review papers (Blasco and Trombini 2023 ; Bonnefille et al., 2017; Punginelli et al., 2024 )), dealing with the marine ecotoxicity of diclofenac, were also consulted as a further attempt to identify any further data that could be considered relevant to the present assessment. Results Ecotoxicity testing For the sea urchin Paracentrotus lividus , no statistically significant effects were measured for adult mortality over a 96-hour acute exposure, nor for 4-hour fertilisation of gametes taken from the exposure adults or 48-hour development of fertilised embryos, up to the maximum measured exposure concentrations (1810, 1840 and 1870 µg diclofenac sodium/L, respectively). Similarly, no mortality was observed in adults of a second sea urchin species, Psammechinus miliaris , exposed to measured diclofenac sodium concentration of 17400 µg/L for 96 hours. Statistically significant effects on fertilisation success were measured for gametes of P.milaris after 4 hours exposure at a measured exposure concentration of 19400 µg diclofenac sodium/L using gametes obtained from these adults (6% inhibition). Assessment of fertilisation success in P.milaris without pre-exposure of adults resulted in a similar slight, but statistically significant, effect on fertilisation (also 6%) at the maximum measured diclofenac concentration of 19400 µg/L. Lower diclofenac concentrations did not illicit statistically significant effects on fertilisation, resulting in an overall No Observed Effect Concentration (NOEC) for fertilisation of 8570 µg/L (mean measured concentration). Testing on a further echinoderm species, the starfish Asterias rubens , showed that fertilisation success was unimpaired after 4 hours exposure of gametes up to a measured diclofenac exposure concentration of 6480 µg/L (using gametes from unexposed adult animals). However, statistically significant reductions in fertilisation were observed for gametes exposed to higher diclofenac concentrations, with percentage reductions in fertilisation success ranging from 11 to 31% at measured concentrations between 11500 and 116000 µg diclofenac sodium/L. Fertilisation success in the annelid worm Arenicola marina was considerably more sensitive to diclofenac than the tested echinoderm species, generating a No Observed Effect Concentration (NOEC) of 0.578 µg diclofenac sodium/L, without any pre-exposure of the adults generating the gametes. Statistically significant reductions in fertilisation (35–95%) occurred at measured diclofenac concentrations between 1.96 and 2340 µg/L. The overall results of the marine studies with three species of echinoderm and one species of marine worm are summarised in Table 1 . A more detailed breakdown of the results for each study is given in the supplementary material. Table 1 EC10/ NOEC thresholds for fertilisation studies with three echinoderms and an annelid worm Species Duration Endpoint EC/LC10 NOEC Paracentrotus lividus 96 hours Adult mortality > 1810 µg/L 1810 µg/L 96 + 4 hours Fertilisation** > 1870 µg/L 1870 µg/L 96 + 48 hours Embryo-larval development** > 1840 µg/L 1840 µg/L Psammechinus miliaris 96 hours Adult mortality > 17.4 mg/L 17.4 mg/L 4 hours Fertilisation* > 19.4 mg/L 8.57 mg/L 96 + 4 hours Fertilisation** NA < 19.4 mg/L Asterias rubens 4 hours Fertilisation 13.0 mg/L (6.90–24.6 mg/L) 6.48 mg/L Arenicola marina 3 hours Fertilisation* 0.776 µg/L (CLs not calculable) 0.578 µg/L * Gametes obtained from unexposed adults ** Gametes obtained from adults exposed for 96 hours to the same nominal concentrations as the fertilisation/ embryo-larval study Search for additional marine ecotoxicity data Unfortunately, while some additional marine effects data were identified for a range of different taxonomic groups (bacteria, cyanobacteria, microalgae, echinoderms, crustaceans, and bivalve molluscs), the majority of these data either represented short-term acute effect endpoints or were considered to be unreliable or not relevant for EQS derivation according to study-specific assessments against the ‘CRED’ criteria proposed by Moermond et al. ( 2015 ). Only the new data on the inhibition of population growth rate in the cyanobacteria Synechocystis salina was considered sufficiently reliable and relevant to utilise in an updated marine EQS assessment (Kropidlowska and Caban 2023 ). Discussion The results of the sea urchin studies indicate that pre-exposure of adults (at least for a relatively short period) had a minimal influence on the effects of diclofenac on fertilisation in sea urchins. Indeed, and contrary to Zanuri et al. ( 2017 ), we found that diclofenac caused no impact on fertilisation in exposed echinoderm gametes (sea urchins and starfish) at concentrations well beyond what could be considered to be environmentally realistic in marine waters. In addition, while fertilisation in the marine worm A.marina was found to be considerably more sensitive to diclofenac exposure than in the tested echinoderm species, the NOEC of 0.578 µg/L was nevertheless still substantially higher than the NOEC for A. marina fertilisation reported by Zanuri et al. ( 2017 ) of less than 0.01 µg/L (reported Lowest Observed Effect Concentration (LOEC) of 0.01 µg/L) for fertilisation. Such differences in sensitivity for the same substance, species and endpoints are not uncommon when ecotoxicity tests are repeated under different conditions and at different times (e.g. EC 2022; Leverett et al., 2021 ). While the pre-exposure of oocytes and sperm in isolation prior to fertilisation process could be considered to be an environmentally unrealistic scenario (and indeed is the primary reason that the EC excluded the studies reported by Zanuri et al. ( 2017 ) from the dataset used to derive the diclofenac EQS (EC 2022)), the potential for impairment of gamete viability is obviously a valid population-relevant reproductive ecotoxicity endpoint, if such impairment leads to a lower proportion of ooctyes eventually becoming fertilised and developing into embryos. In an environmentally realistic scenario, sperm and oocytes will be released by adult animals and potentially exposed to substances present in seawater over the whole period of oocyte maturation, the swimming of sperm, and fertilisation. A proportion of gametes may be detrimentally affected by exposure prior to fertilisation to an extent which prevents their further contribution to the fertilisation process, but there will also be a proportion which are not affected, or not sufficiently inhibited, to prevent fertilisation. Thus, a high proportion of fertilised oocytes may still be the outcome. While sperm swimming ability was not investigated in the studies presented in the current paper, Zanuri et al. ( 2017 ) showed that sperm motility was particularly sensitive to diclofenac exposure (NOEC of 0.01 to 0.1 µg/L, depending on the species exposed). Therefore, in a one hour sperm-only exposure it might be expected that a high proportion of sperm will be impaired before they have any opportunity to effect fertilisation, and, by the time this opportunity for fertilisation is provided, few remain viable. Conversely, in the studies we have presented, sperm and eggs were exposed together and sufficient amounts of viable sperm could have been available to allow a high degree of fertilisation, even if the motility of a proportion of the sperm was also inhibited. It is also possible that, even without exposure, sperm may not remain motile for very long after release into seawater and therefore a one-hour pre-exposure could negatively affect fertilisation success. However, the potential for this outcome is obviously straightforward to discount if a high degree of fertilisation is observed in control (seawater-only) exposures, and 100% fertilisation was achieved by Zanuri et al., ( 2017 ) in their controls. A further consideration is the total length of the fertilisation phase for each study. Zanuri et al. ( 2017 ) allowed fertilisation (following mixing of sperm and ooctyes) for one to two hours, while our studies extended this period to three to four hours. It is possible that there wasn’t sufficient time allowed for the majority of exposed ooctyes to become fertilised by Zanuri et al. ( 2017 ), and that the additional time in our studies afforded for a much larger proportion of oocytes to become fertilised. Again, it might be argued that this potential effect might be resolved based on the high degree of control fertilisation achieved in the Zanuri et al. ( 2017 ) studies, although it may be that the effect inferred by diclofenac in this case is primarily to delay fertilisation rather than to prevent it entirely, and that fertilisation may have still occurred if sufficient time had been allowed for it to occur. Certainly, our studies showed that a high degree of fertilisation did indeed occur (at similar and much higher diclofenac concentrations) after three to four hours incubation. It is debatable whether a delay in fertilisation in such broadcast spawning marine invertebrates could be considered a detrimental population-relevant effect if a high proportion of fertilisation eventually still occurs. Amongst these methodological reasons for the differences in sensitivity shown between the tests presented in the current paper and those reported by Zanuri et al. ( 2017 ), the issue of diclofenac bioavailability should also be considered; Zanuri and colleagues employed a solvent (methanol) to assist in the dissolution of diclofenac which may have enhanced its bioavailability, while no solvents were used in the tests presented here. The pH of test media has also been shown to influence the bioavailability of ionisable pharmaceuticals (Bittner et al., 2018 ; Köhler et al., 2023 ; Schweizer et al., 2021 ) and differences in pH could therefore be another factor in the lack of comparability between the studies. Unfortunately, Zanuri et al. ( 2017 ) did not report the pH of their test media in their paper, so it is not possible to make a direct comparison in this regard. The influence of pH of the ecotoxicity of diclofenac is discussed further, in a more general sense, below. Finally, when considering these possible reasons for the considerable differences in outcomes between these two studies for the same organisms and endpoints, it is also worth noting that the % fertilisation successes achieved at the lowest exposure concentrations by Zanuri et al. ( 2017 ) were only very slightly reduced from the controls (e.g. <5% difference from controls at 0.01 and 0.1 µg/L, and < 10% at 1 µg/L for A.marina ). The authors report that ‘a significant decrease in fertilisation success was observed at diclofenac concentrations of 1 µg/L and above for all three species’, suggesting that significance was not reached for concentrations below 1 µg/L (despite a claim elsewhere in the paper that the LOECs in each case were equal to the lowest exposure concentration (0.01 µg/L)). The actual NOECs for the Zanuri et al. ( 2017 ) study therefore seem likely to lie in the 0.1 to 1 µg/L range, and while this remains substantially more sensitive than the effect-levels observed in our echinoderm studies, this would be comparable with the NOEC obtained in the A. marina test that we have presented in the current paper (= 0.578 µg/L). A request for the raw data from the Zanuri et al. ( 2017 ) studies was made with a view to potentially re-assessing the reported toxicity thresholds, but these data were unfortunately no longer available. The long‑term marine ecotoxicity dataset for diclofenac A relatively small amount of long-term marine ecotoxicity data were considered sufficiently reliable and relevant for utilisation in the EC’s EQS assessment for diclofenac (EC 2022). This dataset comprised only four truly marine (as opposed to brackish water) species, covering population growth in a marine microalgae (DeLorenzo and Fleming 2008), larval development in a crustacean (Gonzalez-Ortegon et al., 2015), byssus strength inhibition in a bivalve mollusc (Ericson et al., 2010 ), and fertilisation/ embryonic development in an echinoderm (Ribeiro et al., 2015 ). A further study on Paracentrotus lividus included in the EC’s assessment, and cited in EC 2022 as ‘Scymaris 2020b’ represented a preliminary trial for the study with the same species reported in the present paper, and is therefore superseded by the later, definitive, test reported here. A more extensive long-term dataset of marine effects was initially considered in the EC’s EQS assessment, covering a much wider range of species and effects, but evaluation according to the ‘CRED’ approach (Moermond et al., 2015 ) revealed a lack of relevance for EQS derivation (e.g. responses in individual organisms rather than population-level effects; exposure conditions environmentally unrealistic), or potential reliability issues with the performance or reporting of the studies (EC 2022). Amongst the excluded studies, the papers by Zanuri et al., ( 2017 ), Duarte et al., ( 2020 ) and Nunes et al., ( 2020 ) are particularly noteworthy in the context of the present paper. The studies reported by Zanuri et al. ( 2017 ), and the reasons for their exclusion from the EC’s assessment, are described in the previous sections. Duarte et al. ( 2020 ) reported the effects of diclofenac on growth and metabolic biomarkers in the marine fish Argyrosomus regius . The biomarkers were not regarded as relevant for EQS derivation by the EC because it was not possible to unequivocally associate any of the measured responses with population relevant parameters, and no dose-responses were observed. While growth was also measured, again no dose-response was evident and, with only two exposure concentrations, it was not possible to calculate an EC10 or derive a NOEC. Nunes et al. ( 2020 ) presented the responses of three enzymatic biomarkers (CAT, GST and AChE) in the marine worm Hediste diversicolor and marine fish Solea senegalensis after exposure to diclofenac. As with Duarte et al. ( 2020 ), such biomarker responses are generally not considered to be relevant for EQS derivation since they relate to responses in individual animals and may not translate directly to population-relevant effects such as survival, reproduction and growth. Since the studies reported by Duarte et al. ( 2020 ), Nunes et al. ( 2020 ) and Zanuri et al. ( 2017 ) were all considered insufficiently reliable/ relevant for EQS derivation, the long-term marine effects dataset utilised in the EC’s EQS assessment lacked any data for marine fish or annelid worms. This paper presents a reliable and relevant study on the marine worm, Arenicola marina , but truly marine fish remain a significant gap in the available long-term dataset for diclofenac. Indeed, the lack of reliable and relevant marine fish data is a particular problem for such an assessment since i) fish are one of the most sensitive taxonomic groups in the long-term freshwater dataset, and ii) the EC’s guidance on EQS derivation (EC 2018) requires that vertebrates (which for the marine environment essentially means fish) are represented in the ecotoxicity dataset applied in the EQS assessment. However, in their reviews of the effects of diclofenac (and other pharmaceuticals) in marine organisms, Bonnefille et al. (2017), Blasco and Trombini ( 2023 ), and Punginelli et al. ( 2024 ) all consider the brackish water species Oryzias latipes as a suitable representative of fish living in saline waters for the purposes of assessing the effects of pharmaceuticals. Therefore, given the lack of any data on the effects of diclofenac in truly marine fish that could be considered sufficiently reliable and relevant for EQS derivation, it would seem a defensible approach to utilise the available data for O. latipes in the marine EQS assessment. The full, updated long-term marine diclofenac ecotoxicity dataset as determined to be reliable and relevant for EQS derivation is shown in Table 2 . This dataset comprises EC10/ NOEC threshold concentrations for nine saltwater species, covering seven different higher taxonomic groups – microalgae, cyanobacteria, crustaceans, bivalve molluscs, echinoderms, annelid worms and fish. Where more than one value EC10/ NOEC is available for the same species (e.g. P. lividus ), the most sensitive value has been used. The lowest effect concentration in the dataset is 0.578 µg/L diclofenac for inhibition of fertilisation in the marine worm, A. marina , as presented in the current paper. Table 2 Long-term marine ecotoxicity dataset for diclofenac Taxonomic Group Species Lowest EC10/ NOEC (µg/L) Endpoint Reference Algae Dunaliella tertiolecta 25000 Population growth DeLorenzo and Fleming 2008 Cyanobacteria Synechocystis salina >=100000 Population growth Kropidlowska and Caban 2023 Crustaceans Palaemon longirostris 40 Larval development Gonzalez-Ortegon et al., 2015 Bivalve Molluscs Mytilus edulis trossulus 3.2 Byssus strength Ericson et al., 2010 Echinoderms Paracentrotus lividus 5.2 Larval length Ribeiro et al., 2015 Psammechinus miliaris 8570 Fertilisation This study Asterias rubens 5620 Fertilisation Annelid worms Arenicola marina 0.578 Fertilisation Fish Oryzias latipes 7.8 Reproduction Yokota et al., 2017 The EC highlighted the potential for a ‘bimodality’ in the original (combined freshwater and marine) dataset (EC 2022), although the dataset they applied in their statistical analysis of potential bimodality was not identical to the dataset used by Leverett et al. ( 2021 ), which included more data of ‘intermediate’ ecotoxicity to diclofenac, relative to the other datapoints in the dataset. Nevertheless, in both the freshwater and marine datasets, there does seems to be an apparent lack of available diclofenac ecotoxicity effect threshold data within the 10 to 100 µg/L range. Considerable variability in sensitivity to diclofenac can clearly occur for different endpoints in the same species (e.g. larval growth in echinoderms (Ribeiro et al., 2015 ) appears to be significantly more sensitive to diclofenac than fertilisation success, based on the studies reported in the present paper); thus endpoint selection and the limited range of endpoints investigated for each species in the dataset is likely to exert some influence on the spread of the datapoints, and it is therefore possible that the apparent ‘sensitivity gap’ is simply a function of the relatively small long-term ecotoxicity datasets for both freshwater and marine waters, and the choice of endpoint for each species. However, very wide variations in ecotoxicity threshold values also occur within the long-term ecotoxicity dataset for diclofenac across multiple tests with the same species and endpoint. While methodological differences may account for some of this variation (e.g. potentially the much reduced sensitivity of fertilisation success in the studies presented in this paper, as compared to those reported by Zanuri et al., 2017 ), this is unlikely to be the case where a more standardised test methodology is employed (e.g. EC/ NOEC thresholds for inhibition of reproduction in Daphnia magna after 21 days exposure ranging from 120 to 72000 µg/L (Leverett et al., 2021 )). Test media pH has been shown to play a role in the ecotoxicity of ionisable compounds such as diclofenac, with maximum bioavailability, and therefore toxicity, at approximately neutral pH (Bittner et al., 2018 ; Köhler et al., 2023 ; Schweizer et al., 2021 ). Köhler et al. ( 2023 ) demonstrated a strong correlation between the degree of effects in zebrafish embryos under different pH conditions, and the corresponding pH-dependent partitioning coefficient log D for a number of ionisable pharmaceuticals, including diclofenac. Kroll et al. (2023) highlighted this effect for diclofenac and proposed a model for the ‘normalisation’ of toxicity values according to the pH conditions of the test exposures, based on a log D correction to pH 6.5 and 7. Using this model to correct the values in the wider (freshwater and marine) chronic dataset for diclofenac, Kroll et al. (2023) were able to achieve a more statistically robust Species Sensitivity Distribution than that presented in the EQS dossier for diclofenac (EC 2022), and which partially addressed the ‘bimodality’ highlighted by the EC. It should be noted, however, that the dataset applied by Kroll et al. (2023) was substantially different from that applied by the EC (2022), with some data excluded on the basis of not reporting sufficient pH information or because of a differing view regarding the reliability/ relevance of specific studies. While this provides a plausible explanation for some of the disparity in results observed in the (primarily freshwater) chronic ecotoxicity dataset applied by the EC (2022) and Leverett et al. ( 2021 ), it is more difficult to extrapolate to the limited chronic marine dataset for diclofenac (Table 2 ). With the exception of the four tests reported here, pH data are missing or limited to such an extent as to make robust comparisons impossible. Using the model proposed by Knoll et al. (2023), the reported toxicity values for the four new studies (with a test media pH range of approximately 7.6 to 8.2) can be estimated to be between 6 and 9 times lower than the ‘low effect’ thresholds reported in Tables 1 and 2 , when adjusted to pH 6.5. However, these are tests using marine species and natural seawater, which generally has a pH between 7.5 and 8.5, and therefore the relevancy of adjusting to a pH in the range 6 to 6.5 is questionable. Nevertheless, the effect of pH on the uptake (and therefore toxicity) of ionisable pharmaceutical substances remains just as relevant for marine organisms as for those living in freshwaters. Hird ( 2021 ) demonstrated the influence of seawater pH on the uptake of diclofenac in the marine worm Hediste diversicolor , with almost twice as much uptake occurring in sea water at pH of 7.4 compared to 8.1, after 48 hours exposure to a diclofenac concentration of 50 µg/L. This suggests a ‘normalisation’ of marine ecotoxicity thresholds for diclofenac to an environmentally-realistic pH of maximum bioavailability for marine waters (e.g. 7.5) could be a useful approach for the future where the relevant pH data are available. Marine EQS Derivation The EQS TGD (EC 2018) allows for two approaches in deriving EQS: a deterministic method, whereby the lowest EC10/ NOEC in the dataset is divided by an Assessment Factor which accounts for the various uncertainties in the assessment; and a probabilistic (statistical) method in which a Species Sensitivity Distribution is constructed using the entire dataset or a subset of it, and the threshold representing the concentration of the substance predicted to affect 5% of species is extrapolated, again divided by an Assessment Factor to account for uncertainties in the prediction. Both approaches are intended to provide sufficient protection for the range of species/ taxonomic groups potentially exposed to the substance of interest in the environment, the overwhelming majority of which remain of unknown sensitivity. The most sensitive EC10/ NOEC from reliable and relevant long-term marine ecotoxicity dataset for diclofenac is 0.578 µg/L for inhibition of fertilisation in the annelid worm Arenicola marina (Table 2 ). For the deterministic approach, the EQS TGD (EC 2018) prescribes Assessment Factors of 10 to 10,000 dependent on the quantity of available long-term ecotoxicity data. In the case of the long-term marine dataset for diclofenac, the lowest Assessment Factor (= 10) is appropriate since it includes long-terms results for saltwater species representing three trophic levels (i.e. algae/ cyanobacteria, invertebrates and fish), as well as three long-term results for specific marine taxonomic groups (covering bivalve molluscs, echinoderms, and annelid worms). A deterministic marine EQS can thus be derived by dividing the lowest EC10/ NOEC in the dataset by an Assessment Factor of 10, to give 0.0578 µg/L or 58 ng/L. This value is over 10 times greater than the marine Annual Average (AA) EQS proposed by the EC (2022) of 4 ng/L, based on freshwater mesocosm data (Joachim et al., 2021 ) and an Assessment Factor of 50. The reliable and relevant long-term marine dataset for diclofenac (Table 2 ) does not meet the minimum requirements prescribed by the EQS TGD (EC 2018) for the use of a probabilistic approach to EQS derivation, of at least ten species covering at least eight higher taxonomic groups. The updated marine dataset represents nine species in seven taxonomic groups: algae, cyanobacteria, crustaceans, bivalve molluscs, echinoderms, annelid worms and fish. Thus, the minimum data quantity requirements of the EQS TGD (EC 2018) are not quite met in either case. The EQS TGD (EC 2018) also highlights that certain specific taxonomic groups should be represented in the dataset: at least - two species of fish, each in a different family (or one fish species and an amphibian species); one species of crustacean; two species of insect, each in different order (or one species of insect and a species of a phylum not otherwise represented in the dataset); one species of algae or cyanobacteria; one species of higher plant. The TGD also provides for allowances to be made when dealing with marine ecotoxicity data alone since data for amphibians, insects and higher plants are unlikely to be available, and these groups can be replaced with marine-specific taxa such as bivalve molluscs, echinoderms and annelid worms. Only a single (brackish water) fish species is represented, and predictably there are no insects or higher plants in the dataset. However, bivalve molluscs, echinoderms and annelid worms are all represented. Nevertheless, taking the limited dataset as a whole, it would likely be considered to be insufficient for derivation of a probabilistic marine EQS by most practitioners experienced with the EC’s EQS derivation process (EC 2018). While acknowledging this, a Species Sensitivity Distribution (SSD) has been constructed using the Canadian SSD software package ssdtools (Dalgarno ( 2018 ); Ministry of the Environment, British Columbia https://bcgov-env.shinyapps.io/ssdtools/ ), which requires a minimum of only eight datapoints to generate an SSD (Fig. 1 ). The software generates outputs for a number of different distribution models, along with statistics describing the degree of ‘fit’ of the data to each model. It also combines the various outputs into an ‘average’ prediction. The Hazardous Concentration predicted to effect 5% of exposed species (HC5) by the average of the distributions (gamma, log gimbel, log logistic, log normal and Weibull) is 0.183 µg/L, with 95% confidence limits of 0.0188 to 20.9 µg/L. The wide confidence limits in the assessment clearly highlight the high degree of uncertainty in this prediction. Applying the maximum Assessment Factor of 5 to the average HC5 value from these distributions as prescribed by the EQS TGD (EC 2018) for probabilistic EQS derivation gives 0.037 µg/L or 37 ng/L. This is slightly lower than the deterministic marine EQS of 58 ng/L, and still almost 10 times higher than the EC’s proposed marine EQS. Risk Assessment Diclofenac monitoring data for the assessment were obtained from European Union member state environment agencies from either online portals (for example France (Surval 2025 )), reports produced by agencies (for example Baltic Sea data (Hallgren and Wallberg 2015 )) or through direct contact (for example German data from the Lower Saxony Environment Agency (NLWKN 2022)). Additionally, data were obtained from the European Environment Agency (EEA) WISE State of the Environment database (EEA 2025) and the Black Sea Environmental Data Platform (EMBLAS 2024). Given diclofenac is now a Priority Substance under the WFD, member states will be expected to include it in their assessment of water body chemical status. The measured environmental data for the marine environment gathered here were not sufficient to allow an assessment of chemical status according to WFD legislation and guidance, with measurements generally not being of a high enough frequency or consistency of location to allow the requisite confidence and precision required. Nevertheless, an indicative compliance assessment has been performed for marine and transitional waters using the prospective marine EQSs of 37 and 58 ng/L derived above, as well as the proposed EU EQS of 4 ng/L. The compiled dataset of measured diclofenac concentrations consists of 311 samples of coastal or transitional water, with individual dataset sizes ranging from 1 sample for France and Iceland to 116 samples for the Black Sea. The degree of censoring in the dataset was variable with all samples above the limit of detection (LOD) for the Baltic Sea, France and Spain and 100% of samples below the LOD for Estonia, Germany, Iceland, Latvia, Malta and the Netherland (Table 3 ). Overall, the dataset was 69% censored (214 out of 311 samples) with quantified concentrations ranging from 0.03 ng/L (in the Baltic Sea) to 240 ng/L (in Spain). A compliance assessment was performed using three different data treatment scenarios against the deterministic method EQS (58 ng/L), the probabilistic method EQS (37 ng/L) and the proposed EU EQS (4 ng/L): Scenario 1; Samples < LOD set to the LOD, Scenario 2; Samples < LOD set to half the LOD, and Scenario 3; Quantified samples only assessed. These three different scenarios were selected to provide a full range of conclusions to be drawn from the indicative compliance assessment. A summary of the compliance assessment outcomes is shown in Table 3 , the full measured concentration dataset is provided in the supplementary information. Table 3 Summary of diclofenac marine compliance assessment Country # of Samples % Censored Percentage Compliance Scenario 1 a Scenario 2 b Scenario 3 c 4 ng/L 37 ng/L 58 ng/L 4 ng/L 37 ng/L 58 ng/L # d 4 ng/L 37 ng/L 58 ng/L Baltic Sea 68 0% 91% 97% 100% 91% 97% 100% 68 91% 97% 100% Belgium 24 63% 0% 0% 75% 0% 63% 75% 9 0% 0% 33% Black Sea 116 96% 100% 100% 100% 100% 100% 100% 5 100% 100% 100% Bulgaria 26 88% 58% 96% 100% 58% 96% 100% 3 0% 67% 100% Estonia 33 100% 0% 0% 100% 0% 100% 100% 0 - - - France 1 0% 100% 100% 100% 100% 100% 100% 1 100% 100% 100% Germany 18 100% 0% 100% 100% 0% 100% 100% 0 - - - Iceland 1 100% 100% 100% 100% 100% 100% 100% 0 - - - Ireland 2 50% 0% 100% 100% 0% 100% 100% 1 0% 100% 100% Italy 6 17% 0% 100% 100% 17% 100% 100% 5 0% 100% 100% Latvia 2 100% 0% 0% 100% 0% 100% 100% 0 - - - Malta 2 100% 0% 100% 100% 100% 100% 100% 0 - - - Netherlands 7 100% 0% 100% 100% 0% 100% 100% 0 - - - Spain 5 0% 0% 20% 40% 0% 20% 40% 5 0% 20% 40% Overall 311 69% 63% 79% 97% 64% 95% 97% 97 70% 84% 91% a Samples < LOD set to the LOD b Samples < LOD set to half the LOD c Quantified samples only assessed d Number of samples above LOD For the assessment performed using the probabilistically calculated prospective EQS, overall compliance ranged from 79% for Scenario 1 to 97% for Scenario 2 with country-specific compliance ranging from 0% (for Latvia and Estonia in Scenario 1) to 100% (Table 3 ). It is of note that for both Latvia and Lithuania that all samples are below the LOD and the LOD is of sufficient sensitivity for 100% compliance under Scenario 2. When the data are assessed using the prospective deterministic EQS of 58 ng/L, overall compliance increases to 97% for Scenarios 1 and 2 (from 79% and 95%, respectively) and to 91% for Scenario 3 (from 84%); with country-specific compliance ranging from 33% (Bulgaria in Scenario 3) to 100% (Table 3 ). Overall, compliance against both the probabilistic and deterministic EQS is high (Table 3 ) with 79% or higher compliance in all scenarios with either EQS; and when only Scenario 2 (LOD*0.5) is reviewed compliance rises to 95% − 97%. It is of note that it is a version of Scenario 2 that is used for substance prioritisation in Europe, when assessing substance suitability for inclusion on the EU Watchlist (Gomez Cortes et al., 2022 ). When compliance is assessed against the proposed EU EQS of 4 ng/L, it ranges from 63% for Scenario 1 to 70% for Scenario 3 (Table 3 ) which is considerably lower than compliance when the data are assessed against the EQS derived in the present paper. The issues of treatment of censored data and instrument sensitivity are more acute for this proposed EQS, since it is 9 to 15 times more sensitive. Overall, 84 samples (27% of the compiled dataset) are below the LOD with the LOD being greater than twice the proposed EU EQS of 4 ng/L (a criteria used in EU for removal of samples from prioritisation datasets (Gomez Cortes et al., 2022 )); no censored samples have a LOD greater than twice that of the probabilistic EQS. Conclusions Our comprehensive investigations into the potential of diclofenac to inhibit fertilisation on echinoderms and annelid worms failed to reproduce the extremely sensitive results previously reported (Zanuri et al., 2017 ). Only limited effects were induced in two species of sea urchin and a starfish at concentrations well beyond environmental realism, regardless of whether the adults from which gametes were sourced were pre-exposed. Fertilisation in the annelid worm A. marina was considerably more sensitive to diclofenac exposure than the echinoderm species tested, with a derived NOEC of 578 ng/L, although this was still over 50 times the LOEC reported by Zanuri et al., 2017 . Potential reasons for the differences in sensitivity observed include methodological disparities between the studies (e.g. pre-exposure of gametes with no exposure during fertilisation versus exposure only during fertilisation), a temporal lag in the fertilisation process caused by diclofenac exposure, and disparity in the uptake of diclofenac by gametes and embryos caused by the use of a solvent or variation in test media pH. Insufficient information is available to be certain of the exact reasons for the differences, which highlights the need for test reliability criteria (e.g. the CRED criteria proposed by Moermond et al. ( 2015 )) to be accounted for in the initial design of such studies and for raw effect data to be included in published materials. This is especially critical as regulatory assessments increasingly require an assessment of published studies (e.g. EMA 2024). This requirement also means that the publication of studies showing no or minimal effects is just as important as those highlighting significant effects at environmentally relevant concentrations of substances. The reliable and relevant long-term marine ecotoxicity dataset for diclofenac has been updated to include the studies reported in the present paper. This updated dataset comprises 9 saltwater species in 7 taxonomic groups – cyanobacteria, microalgae, crustaceans, bivalve molluscs, echinoderms, annelid worms and fish. Prospective deterministic and probabilistic EQS have been derived using this dataset of 58 and 37 ng/L, respectively. These prospective EQS have been compared with diclofenac measured concentration data from European marine waters to predict the degree of risks associated with diclofenac exposure. Compliance with the prospective EQS was dependent on the way in which censored (< LOD) monitoring data were treated in the assessment. However, if the approach generally applied in WFD annual average compliance assessments is used (samples results less than the LOD are set to 0.5*LOD), overall compliance with the prospective EQS was 95–97% (n = 311). Conversely, compliance with the proposed EU marine EQS (4 ng/L; EC 2022) was only 64%. Based on this prospective, but entirely marine-focused, hazard and risk assessment, the EU EQS - derived entirely from a single freshwater mesocosm study (Joachim et al., 2021 ) – may be over-precautionary. Declarations Acknowledgements The authors would like to acknowledge the input of Jim Ryan of GSK Consumer Healthcare. Authors’ contributions Each author made substantial contributions to the conception, analysis, and interpretation of data and assisted in drafting the work. Each author approved the submitted version (and any substantially modified version that involves the author’s contribution to the study) and agrees both to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. All authors read and approved the final manuscript. Funding The funding for this article was provided by Haleon Consumer Healthcare SARL. The funding for the ecotoxicological testing was provided by GlaxoSmithKline (GSK) Consumer Healthcare SARL. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Declarations Competing interests Dean Leverett, Iain Wilson and Lucy Kennelly are employees of a consultancy (wca Environment Ltd) which works for companies on projects focusing on the environmental risk assessment of chemicals, including pharmaceuticals. Tom Austin works for a company (Haleon) that produces diclofenac, sells products containing diclofenac, and submits pharmaceutical environmental risk assessments to regulatory authorities. Richard Maunder, Daniel Hill and Pete Johnson work for a Contract Research Organisation (Scymaris) that undertakes commercial ecotoxicological research. Cameron Hird previously worked at Scymaris. Ethics and Consent to Participate Not applicable. Consent to Publish Not applicable. 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Guidance for generating and reporting methods of analysis in support of pre-registration data requirements for Annex II (part A, Section 4) and Annex III (part A, Section 5) of Directive 91/414. Schweizer M, von der Ohe PC, Gräff T, Kühnen U, Hebel J, Heid C, Kundy L, Kuttler J, Moroff F-M, Schlösinger A-F, Schulze-Berge P, Triebskorn R, Panagopoulou E, Damalas DE, Thomaidis NS, Köhler HR (2021). Heart rate as an early warning parameter and proxy for subsequent mortality in Danio rerio embryos exposed to ionisable substances. Sci Total Environ 818. Simon E, Duffek A, Stahl C, Frey M, Scheurer M, Tuerk J, Gehrmann L, Könemann S, Swart K, Behnisch P, Olbrich D, Brion F,Aït-Aïssa S, Pasanen-Kase R, Werner I, Vermeirssen ELM (2022). Biological effect and chemical monitoring of Watch List substances in European surface waters: Steroidal estrogens and diclofenac – Effect-based methods for monitoring frameworks. Environment International, Volume 159. Surval. 2025. Access to marine and coastal environmental data; https://surval.ifremer.fr/Donnees/Donnees-par-parametre#/map. Source : Quadrige - Programme : EMERGENTSEA_POCIS. Etalab's Open License V2.0. Tiedeken EJ, Tahar A, McHugh B, Rowan NJ (2017) Monitoring, sources, receptors, and control measures for three European Union watch list substances of emerging concern in receiving waters—a 20 year systematic review. Sci Total Environ 574:1140–1163. Zanuri NBM, Bentley MG, Caldwell GS (2017) Assessing the impact of diclofenac, ibuprofen and sildenafil citrate (Viagra®) on the fertilisation biology of broadcast spawning marine invertebrates. Marine Environmental Research 127. Additional Declarations Competing interest reported. Dean Leverett, Iain Wilson and Lucy Kennelly are employees of a consultancy (wca Environment Ltd) which works for companies on projects focusing on the environmental risk assessment of chemicals, including pharmaceuticals. Tom Austin works for a company (Haleon) that produces diclofenac, sells products containing diclofenac, and submits pharmaceutical environmental risk assessments to regulatory authorities. Richard Maunder, Daniel Hill and Pete Johnson work for a Contract Research Organisation (Scymaris) that undertakes commercial ecotoxicological research. Cameron Hird previously worked at Scymaris. Supplementary Files DiclofenacMarinePaperSupplementaryInformation1FINAL.docx DiclofenacMarinePaperSupplementaryInformation2FINAL.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6295199","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":443421008,"identity":"afb14dde-d3f9-4b43-a87f-986d50c67d5a","order_by":0,"name":"Dean Leverett","email":"data:image/png;base64,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","orcid":"","institution":"wca Environment Ltd","correspondingAuthor":true,"prefix":"","firstName":"Dean","middleName":"","lastName":"Leverett","suffix":""},{"id":443421009,"identity":"1451da85-db73-4c0c-aef9-e9be86f38899","order_by":1,"name":"Iain Wilson","email":"","orcid":"","institution":"wca Environment Ltd","correspondingAuthor":false,"prefix":"","firstName":"Iain","middleName":"","lastName":"Wilson","suffix":""},{"id":443421010,"identity":"907f5083-bb93-4b32-b55f-45d7a9671c82","order_by":2,"name":"Lucy Kennelly","email":"","orcid":"","institution":"wca Environment Ltd","correspondingAuthor":false,"prefix":"","firstName":"Lucy","middleName":"","lastName":"Kennelly","suffix":""},{"id":443421011,"identity":"b475ba32-875e-40ed-a516-f21813de3c62","order_by":3,"name":"Tom Austin","email":"","orcid":"","institution":"Haleon CH SARL","correspondingAuthor":false,"prefix":"","firstName":"Tom","middleName":"","lastName":"Austin","suffix":""},{"id":443421012,"identity":"20842e87-276d-4440-b92f-bb0bebc23ae8","order_by":4,"name":"Cameron Hird","email":"","orcid":"","institution":"University of Plymouth","correspondingAuthor":false,"prefix":"","firstName":"Cameron","middleName":"","lastName":"Hird","suffix":""},{"id":443421013,"identity":"1a0da89a-3bcc-47b8-b1ce-f4126e11c5fd","order_by":5,"name":"Richard Maunder","email":"","orcid":"","institution":"Scymaris Ltd","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Maunder","suffix":""},{"id":443421014,"identity":"685d3caf-3ed2-486f-8e6b-942ee8a7e41f","order_by":6,"name":"Daniel Hill","email":"","orcid":"","institution":"Scymaris Ltd","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Hill","suffix":""},{"id":443421015,"identity":"91742e42-f755-454a-b95c-f40919c41294","order_by":7,"name":"Pete Johnson","email":"","orcid":"","institution":"Scymaris Ltd","correspondingAuthor":false,"prefix":"","firstName":"Pete","middleName":"","lastName":"Johnson","suffix":""}],"badges":[],"createdAt":"2025-03-24 12:08:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6295199/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6295199/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80883642,"identity":"5fc258dc-c9d2-4a90-9003-3fe9b335c4c9","added_by":"auto","created_at":"2025-04-18 08:17:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":325852,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSpecies Sensitivity Distribution (SSD) of reliable and relevant long-term marine ecotoxicity data for diclofenac\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"ssdtoolsmodelAveragePlot300.png","url":"https://assets-eu.researchsquare.com/files/rs-6295199/v1/648589bc5f13c39bd7cf12a0.png"},{"id":83727817,"identity":"b3360489-2320-4e3c-baaf-8ae5565916c6","added_by":"auto","created_at":"2025-06-01 10:46:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1327671,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6295199/v1/782b9b75-d47c-42fc-ba10-39863ca44483.pdf"},{"id":80883651,"identity":"8e11e620-b8a9-46b1-93bd-d32bb398db6b","added_by":"auto","created_at":"2025-04-18 08:17:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":7096170,"visible":true,"origin":"","legend":"","description":"","filename":"DiclofenacMarinePaperSupplementaryInformation1FINAL.docx","url":"https://assets-eu.researchsquare.com/files/rs-6295199/v1/f79ad02b5eab976e3fc54d39.docx"},{"id":80884347,"identity":"785642aa-c6b6-40ad-b758-009a61a7d4ed","added_by":"auto","created_at":"2025-04-18 08:25:23","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":38133,"visible":true,"origin":"","legend":"","description":"","filename":"DiclofenacMarinePaperSupplementaryInformation2FINAL.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6295199/v1/06946f236c3905decce8e22d.xlsx"}],"financialInterests":"Competing interest reported. Dean Leverett, Iain Wilson and Lucy Kennelly are employees of a consultancy (wca Environment Ltd) which works for companies on projects focusing on the environmental risk assessment of chemicals, including pharmaceuticals. Tom Austin works for a company (Haleon) that produces diclofenac, sells products containing diclofenac, and submits pharmaceutical environmental risk assessments to regulatory authorities. Richard Maunder, Daniel Hill and Pete Johnson work for a Contract Research Organisation (Scymaris) that undertakes commercial ecotoxicological research. Cameron Hird previously worked at Scymaris.","formattedTitle":"Environmental quality standards for diclofenac derived under the European Water Framework Directive: 3. Marine ecotoxicity","fulltext":[{"header":"Background","content":"\u003cp\u003eThe European Water Framework Directive (WFD) (2000/60/EC) aims to restore all surface waters to \u0026lsquo;good\u0026rsquo; status. One of the chemical metrics used to assess status is the Environmental Quality Standard (EQS). In Europe, EQS set centrally by the European Commission are legally binding and therefore drive regulatory action to reduce the concentrations of chemicals in surface waters. EQS are intended to be environmental matrix-specific; different EQS values are usually presented for fresh and marine waters although these are very often derived from the same (usually freshwater) data and separated only by the magnitude of the assessment factor applied. Diclofenac is a nonsteroidal anti-inflammatory (NSAID) human and veterinary medicine that has been widely detected in European surface waters, and which primarily enters these waters in discharges from Wastewater Treatment Plants (WWTPs)(Carvalho et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Simon et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Diclofenac behaves conservatively in conventional wastewater treatment processes, with relatively low levels of removal being achieved (Patrolecco et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Tiedeken et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Dos Santos et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This means that long-term exposure of aquatic organisms to diclofenac in European waters occurs downstream of some WWTPs.\u003c/p\u003e \u003cp\u003eIn Parts 1 and 2 of the work on \u003cem\u003eEnvironmental quality standards for diclofenac derived under the European Water Framework Directive\u003c/em\u003e (Leverett et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Maack et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Leverett et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Peters et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) the approaches taken to derive EQS for diclofenac were evaluated, and issues highlighted with the derivations for direct toxicity and secondary poisoning biota proposed by the European Commission (EC)(EC 2022). In particular, the reliability and plausibility of some of the data underpinning the EC\u0026rsquo;s assessments were questioned, and alternatives suggested to the approaches applied by the EC. There is no intention to re-open that debate in this third manuscript on the effects of diclofenac on aquatic organisms, which focuses specifically on the marine environment.\u003c/p\u003e \u003cp\u003eAs part of the development of the chronic ecotoxicity dataset for diclofenac, intended to support the EQS derivation, a programme of new testing was established. This comprised a series of studies using freshwater and marine invertebrates, with primary objectives of filling clear taxonomic gaps in the long-term aquatic effects dataset for diclofenac. This included attempts to repeat some exceptionally sensitive \u0026lsquo;no effect\u0026rsquo; concentrations previously published for reproductive effects in echinoderms and marine worms (Zanuri et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The marine element of our testing programme comprised four GLP-compliant studies performed between 2019 and 2024, the long duration of the programme being a result of the Covid-19 pandemic, and related subsequent difficulties in obtaining test organisms of sufficient quality for the studies.\u003c/p\u003e \u003cp\u003eAll four of these studies were previously unpublished in the open scientific literature.\u003c/p\u003e \u003cp\u003eThe marine EQS proposed by the EC (EC 2022) is based directly on a single freshwater mesocosm study (Joachim et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), also used to deterministically derive the freshwater EQS. An Assessment Factor of 50 has been applied to a reported EC10 value of 0.2 \u0026micro;g/L for mortality in female stickleback, \u003cem\u003eGasterosteus aculeatus\u003c/em\u003e, giving a marine EQS of 0.004 \u0026micro;g/L (4 ng/L) diclofenac. However, as highlighted previously (Leverett et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), we do not consider these data sufficiently reliable for derivation of a freshwater or marine EQS for diclofenac.\u003c/p\u003e \u003cp\u003eA small amount of long-term marine ecotoxicity data were included in the EC\u0026rsquo;s EQS assessment (EC 2022) however, it was not possible to undertake a statistical comparison to evaluate potential differences in sensitivity to diclofenac of freshwater and saltwater species. This had no impact on the final EQS proposed by the EC for fresh and marine waters (EC 2022) since the derivation approach applied did not ultimately utilise the long-term aquatic ecotoxicity dataset for fresh or marine waters.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe original intention in undertaking these studies was to repeat the studies reported by Zanuri and colleagues in 2017. However, some important differences between those studies (as reported) were applied, comprising: i) undertaking the studies in a highly controlled and quality-assured (GLP-compliant) laboratory environment; ii) increasing the resolution of effect/ no effect thresholds by an expansion of the diclofenac concentration to which the test organisms were exposed, and a decrease in the interval between test concentrations; iii) increasing environmental realism by exposing sperm and oocytes together during fertilisation, rather than individually and prior to mixing; iv) extending the fertilisation exposure period to ensure the maximal opportunity for fertilisation, and v) in two of the tests, evaluating the influence of a short (acute) pre-exposure of adult animals immediately prior to gamete collection for fertilisation assessments.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSeawater\u003c/h2\u003e \u003cp\u003eThe seawater used for organism husbandry and the diclofenac tests was obtained from Torbay, Devon, UK before undergoing treatment prior to use. The pH of the seawater was 8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5, with a salinity 34.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u0026permil;. Further detailed analysis of other parameters including a range of metals, pesticides, total organic carbon (TOC) and PCBs is conducted quarterly (under non-GLP conditions), and is provided in the supplementary material.\u003c/p\u003e \u003cp\u003eOn-site treatment typically included protein skimming, filtration to 10 \u0026micro;m and UV exposure. Additional filtration was applied immediately prior to use.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalytical method for determination of diclofenac in seawater\u003c/h3\u003e\n\u003cp\u003eThe method used to determine the actual exposure concentrations of diclofenac in the test solutions (filtered natural seawater) was validated in accordance with the SANCO/3029/99 rev.4 11/07/00 guideline (Sanco 2000). The limit of quantification (LOQ) was determined as the lowest concentration tested at which an acceptable mean recovery (70\u0026ndash;110%) with an acceptable relative standard deviation (RSD; \u0026lt;20%) was obtained. The LOQ of the method for seawater was set as 0.0050 \u0026micro;g/L. Seawater samples were extracted/concentrated using solid phase extraction (SPE) cartridges, eluted, and then analysed using LC-MS/MS. An internal standard was used to assess the acceptability of the method. The full analytical method is supplied in the supplementary material.\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eFor the sea urchin and marine worm tests, statistical analysis of fertilisation and embryo-larval development data was undertaken using the CETIS statistical package (versions 1.9.4.9 and 2.1.5.5, respectively). Statistical analysis in the starfish test was performed using the ToxRat solutions statistical package (version 3.3.0). A Bonferroni adjusted ttest and a Dunnett\u0026rsquo;s multiple comparison test was used for NOEC/LOEC determination in the sea urchin tests. The Jonckheere-Terpstra step-down trend test was used for NOEC/LOEC determination in the marine worm test. A step-down Cochran-Armitage trend test was used for NOEC/LOEC determination in the starfish test. Linear interpolation (ICPIN) was used in determining EC\u003csub\u003ex\u003c/sub\u003e values (where possible) for the sea urchin and marine worm tests. Linear regression (Weibull) was used in determining EC\u003csub\u003ex\u003c/sub\u003e values for the starfish test.\u003c/p\u003e \u003cp\u003eThe Species Sensitivity Distribution (SSD) used for derivation of prospective EQS was constructed using the Canadian SSD software package (shiny)ssdtools (Dalgarno (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e))(ssdtools version: 2.2.0, shinyssdtools version: 0.3.5). The key feature of (shiny)ssdtools is the use of a technique known as model averaging. In the context of SSD modelling, the approach fits multiple distributions to a toxicity dataset and uses the weights of the fits of each distribution to construct a model-averaged SSD. (shiny)ssdtools contains a set of \u0026lsquo;default\u0026rsquo; distributions (currently the Gamma, Log-Gumbel, Log-Logistic, Log-Normal, Lognormal-Lognormal and Weibull) that are automatically used to construct a model-averaged SSD.\u003c/p\u003e\n\u003ch3\u003eSource of test organisms\u003c/h3\u003e\n\u003cp\u003eAdult \u003cem\u003eParacentrotus lividus\u003c/em\u003e and \u003cem\u003ePsammechinus miliaris\u003c/em\u003e were obtained, respectively, from the Scottish Association for Marine Science (SAMS), Oban, UK, and an offshore mussel farm in Lyme Bay, Devon, UK. Both species of sea urchin were maintained at the Scymaris laboratory in filtered seawater under a 16L:8D (light:dark) photoperiod, held at 15\u0026deg;C and fed \u003cem\u003eLaminaria\u003c/em\u003e sp. (kelp) \u003cem\u003ead hoc\u003c/em\u003e prior to use for testing. Adult starfish, \u003cem\u003eAsterias rubens\u003c/em\u003e, were collected from the wild off the coast of Torbay, Devon in the UK, and maintained at the laboratory in filtered seawater under a 16L:8D (light:dark) photoperiod at 11\u0026deg;C, and fed blue mussels (\u003cem\u003eMytilus edulis\u003c/em\u003e) \u003cem\u003ead hoc\u003c/em\u003e. All echinoderms used for testing were sexed prior to the studies and then held in known sex groups for at least two weeks prior to use for testing. Adult lugworms, \u003cem\u003eArenicola marina\u003c/em\u003e, were collected from the wild population at Paignton Beach, Devon, UK, during the spawning season (October 2023). They were maintained in single-sex tanks using natural sediment from the collection site, under flow through conditions using filtered seawater at 12\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C, and fed with small granular pellets as required.\u003c/p\u003e\n\u003ch3\u003eAdult exposures\u003c/h3\u003e\n\u003cp\u003eIn the tests with sea urchins, adult animals were exposed to diclofenac at an identical nominal concentration range as the gametes taken from the adults for subsequent fertilisation tests. Adult exposures lasted for 96 hours immediately prior to gamete collection. The studies using starfish and \u003cem\u003eA. marina\u003c/em\u003e did not incorporate pre-exposure of adult animals before spawning. Full details are given in the supplementary material.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFertilisation tests\u003c/h2\u003e \u003cp\u003eFor the fertilisation tests, ooctyes and sperm taken from adult animals were combined and exposed to a wide range of diclofenac concentrations for 3 to 4 hours. After this time, samples were removed from each replicate exposure and fixed using neutral buffered formalin. Numbers of fertilised embryos and unfertilised oocytes were then assessed in each sampler using light microscopy. Successful fertilisation was defined as division of the zygote. Full details are given in the supplementary material.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEmbryo-larval development test\u003c/h3\u003e\n\u003cp\u003eIn the study with the sea urchin \u003cem\u003eParacentrotus lividus\u003c/em\u003e, fertilised embryos were exposed for a further 48 hours in order to assess embryo-larval development, at the same nominal diclofenac concentrations as applied in the fertilisation tests. Full details are given in the supplementary material.\u003c/p\u003e\n\u003ch3\u003eSearches for additional data to support EQS derivation\u003c/h3\u003e\n\u003cp\u003eGiven the time elapsed since the EC\u0026rsquo;s EQS derivation for diclofenac (EC 2022), and in an attempt to supplement the long-term marine dataset included in the EC\u0026rsquo;s assessment, new literature searches for marine ecotoxicity data were undertaken for the present assessment. Full details are given in the supplementary material.\u003c/p\u003e \u003cp\u003eIn addition, three relatively recent review papers (Blasco and Trombini \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bonnefille et al., 2017; Punginelli et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)), dealing with the marine ecotoxicity of diclofenac, were also consulted as a further attempt to identify any further data that could be considered relevant to the present assessment.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEcotoxicity testing\u003c/h2\u003e \u003cp\u003eFor the sea urchin \u003cem\u003eParacentrotus lividus\u003c/em\u003e, no statistically significant effects were measured for adult mortality over a 96-hour acute exposure, nor for 4-hour fertilisation of gametes taken from the exposure adults or 48-hour development of fertilised embryos, up to the maximum measured exposure concentrations (1810, 1840 and 1870 \u0026micro;g diclofenac sodium/L, respectively).\u003c/p\u003e \u003cp\u003eSimilarly, no mortality was observed in adults of a second sea urchin species, \u003cem\u003ePsammechinus miliaris\u003c/em\u003e, exposed to measured diclofenac sodium concentration of 17400 \u0026micro;g/L for 96 hours. Statistically significant effects on fertilisation success were measured for gametes of \u003cem\u003eP.milaris\u003c/em\u003e after 4 hours exposure at a measured exposure concentration of 19400 \u0026micro;g diclofenac sodium/L using gametes obtained from these adults (6% inhibition). Assessment of fertilisation success in \u003cem\u003eP.milaris\u003c/em\u003e without pre-exposure of adults resulted in a similar slight, but statistically significant, effect on fertilisation (also 6%) at the maximum measured diclofenac concentration of 19400 \u0026micro;g/L. Lower diclofenac concentrations did not illicit statistically significant effects on fertilisation, resulting in an overall No Observed Effect Concentration (NOEC) for fertilisation of 8570 \u0026micro;g/L (mean measured concentration).\u003c/p\u003e \u003cp\u003eTesting on a further echinoderm species, the starfish \u003cem\u003eAsterias rubens\u003c/em\u003e, showed that fertilisation success was unimpaired after 4 hours exposure of gametes up to a measured diclofenac exposure concentration of 6480 \u0026micro;g/L (using gametes from unexposed adult animals). However, statistically significant reductions in fertilisation were observed for gametes exposed to higher diclofenac concentrations, with percentage reductions in fertilisation success ranging from 11 to 31% at measured concentrations between 11500 and 116000 \u0026micro;g diclofenac sodium/L.\u003c/p\u003e \u003cp\u003eFertilisation success in the annelid worm \u003cem\u003eArenicola marina\u003c/em\u003e was considerably more sensitive to diclofenac than the tested echinoderm species, generating a No Observed Effect Concentration (NOEC) of 0.578 \u0026micro;g diclofenac sodium/L, without any pre-exposure of the adults generating the gametes. Statistically significant reductions in fertilisation (35\u0026ndash;95%) occurred at measured diclofenac concentrations between 1.96 and 2340 \u0026micro;g/L.\u003c/p\u003e \u003cp\u003eThe overall results of the marine studies with three species of echinoderm and one species of marine worm are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A more detailed breakdown of the results for each study is given in the supplementary material.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEC10/ NOEC thresholds for fertilisation studies with three echinoderms and an annelid worm\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEndpoint\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEC/LC10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNOEC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eParacentrotus lividus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdult mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1810 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1810 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u0026thinsp;+\u0026thinsp;4 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFertilisation**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1870 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1870 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u0026thinsp;+\u0026thinsp;48 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmbryo-larval development**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1840 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1840 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ePsammechinus miliaris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdult mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;17.4 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.4 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFertilisation*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;19.4 mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.57 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u0026thinsp;+\u0026thinsp;4 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFertilisation**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;19.4 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAsterias rubens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFertilisation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.0 mg/L\u003c/p\u003e \u003cp\u003e(6.90\u0026ndash;24.6 mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.48 mg/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eArenicola marina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFertilisation*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.776 \u0026micro;g/L (CLs not calculable)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.578 \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* Gametes obtained from unexposed adults\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e** Gametes obtained from adults exposed for 96 hours to the same nominal concentrations as the fertilisation/ embryo-larval study\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSearch for additional marine ecotoxicity data\u003c/h2\u003e \u003cp\u003eUnfortunately, while some additional marine effects data were identified for a range of different taxonomic groups (bacteria, cyanobacteria, microalgae, echinoderms, crustaceans, and bivalve molluscs), the majority of these data either represented short-term acute effect endpoints or were considered to be unreliable or not relevant for EQS derivation according to study-specific assessments against the \u0026lsquo;CRED\u0026rsquo; criteria proposed by Moermond et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Only the new data on the inhibition of population growth rate in the cyanobacteria \u003cem\u003eSynechocystis salina\u003c/em\u003e was considered sufficiently reliable and relevant to utilise in an updated marine EQS assessment (Kropidlowska and Caban \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of the sea urchin studies indicate that pre-exposure of adults (at least for a relatively short period) had a minimal influence on the effects of diclofenac on fertilisation in sea urchins. Indeed, and contrary to Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), we found that diclofenac caused no impact on fertilisation in exposed echinoderm gametes (sea urchins and starfish) at concentrations well beyond what could be considered to be environmentally realistic in marine waters. In addition, while fertilisation in the marine worm \u003cem\u003eA.marina\u003c/em\u003e was found to be considerably more sensitive to diclofenac exposure than in the tested echinoderm species, the NOEC of 0.578 \u0026micro;g/L was nevertheless still substantially higher than the NOEC for \u003cem\u003eA. marina\u003c/em\u003e fertilisation reported by Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) of less than 0.01 \u0026micro;g/L (reported Lowest Observed Effect Concentration (LOEC) of 0.01 \u0026micro;g/L) for fertilisation.\u003c/p\u003e \u003cp\u003eSuch differences in sensitivity for the same substance, species and endpoints are not uncommon when ecotoxicity tests are repeated under different conditions and at different times (e.g. EC 2022; Leverett et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While the pre-exposure of oocytes and sperm in isolation prior to fertilisation process could be considered to be an environmentally unrealistic scenario (and indeed is the primary reason that the EC excluded the studies reported by Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) from the dataset used to derive the diclofenac EQS (EC 2022)), the potential for impairment of gamete viability is obviously a valid population-relevant reproductive ecotoxicity endpoint, if such impairment leads to a lower proportion of ooctyes eventually becoming fertilised and developing into embryos. In an environmentally realistic scenario, sperm and oocytes will be released by adult animals and potentially exposed to substances present in seawater over the whole period of oocyte maturation, the swimming of sperm, and fertilisation. A proportion of gametes may be detrimentally affected by exposure prior to fertilisation to an extent which prevents their further contribution to the fertilisation process, but there will also be a proportion which are not affected, or not sufficiently inhibited, to prevent fertilisation. Thus, a high proportion of fertilised oocytes may still be the outcome. While sperm swimming ability was not investigated in the studies presented in the current paper, Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) showed that sperm motility was particularly sensitive to diclofenac exposure (NOEC of 0.01 to 0.1 \u0026micro;g/L, depending on the species exposed). Therefore, in a one hour sperm-only exposure it might be expected that a high proportion of sperm will be impaired before they have any opportunity to effect fertilisation, and, by the time this opportunity for fertilisation is provided, few remain viable. Conversely, in the studies we have presented, sperm and eggs were exposed together and sufficient amounts of viable sperm could have been available to allow a high degree of fertilisation, even if the motility of a proportion of the sperm was also inhibited. It is also possible that, even without exposure, sperm may not remain motile for very long after release into seawater and therefore a one-hour pre-exposure could negatively affect fertilisation success. However, the potential for this outcome is obviously straightforward to discount if a high degree of fertilisation is observed in control (seawater-only) exposures, and 100% fertilisation was achieved by Zanuri et al., (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) in their controls. A further consideration is the total length of the fertilisation phase for each study. Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) allowed fertilisation (following mixing of sperm and ooctyes) for one to two hours, while our studies extended this period to three to four hours. It is possible that there wasn\u0026rsquo;t sufficient time allowed for the majority of exposed ooctyes to become fertilised by Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and that the additional time in our studies afforded for a much larger proportion of oocytes to become fertilised. Again, it might be argued that this potential effect might be resolved based on the high degree of control fertilisation achieved in the Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) studies, although it may be that the effect inferred by diclofenac in this case is primarily to delay fertilisation rather than to prevent it entirely, and that fertilisation may have still occurred if sufficient time had been allowed for it to occur. Certainly, our studies showed that a high degree of fertilisation did indeed occur (at similar and much higher diclofenac concentrations) after three to four hours incubation. It is debatable whether a delay in fertilisation in such broadcast spawning marine invertebrates could be considered a detrimental population-relevant effect if a high proportion of fertilisation eventually still occurs. Amongst these methodological reasons for the differences in sensitivity shown between the tests presented in the current paper and those reported by Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the issue of diclofenac bioavailability should also be considered; Zanuri and colleagues employed a solvent (methanol) to assist in the dissolution of diclofenac which may have enhanced its bioavailability, while no solvents were used in the tests presented here. The pH of test media has also been shown to influence the bioavailability of ionisable pharmaceuticals (Bittner et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; K\u0026ouml;hler et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Schweizer et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and differences in pH could therefore be another factor in the lack of comparability between the studies. Unfortunately, Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) did not report the pH of their test media in their paper, so it is not possible to make a direct comparison in this regard. The influence of pH of the ecotoxicity of diclofenac is discussed further, in a more general sense, below. Finally, when considering these possible reasons for the considerable differences in outcomes between these two studies for the same organisms and endpoints, it is also worth noting that the % fertilisation successes achieved at the lowest exposure concentrations by Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) were only very slightly reduced from the controls (e.g. \u0026lt;5% difference from controls at 0.01 and 0.1 \u0026micro;g/L, and \u0026lt;\u0026thinsp;10% at 1 \u0026micro;g/L for \u003cem\u003eA.marina\u003c/em\u003e). The authors report that \u0026lsquo;a significant decrease in fertilisation success was observed at diclofenac concentrations of 1 \u0026micro;g/L and above for all three species\u0026rsquo;, suggesting that significance was not reached for concentrations below 1 \u0026micro;g/L (despite a claim elsewhere in the paper that the LOECs in each case were equal to the lowest exposure concentration (0.01 \u0026micro;g/L)). The actual NOECs for the Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) study therefore seem likely to lie in the 0.1 to 1 \u0026micro;g/L range, and while this remains substantially more sensitive than the effect-levels observed in our echinoderm studies, this would be comparable with the NOEC obtained in the \u003cem\u003eA. marina\u003c/em\u003e test that we have presented in the current paper (=\u0026thinsp;0.578 \u0026micro;g/L). A request for the raw data from the Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) studies was made with a view to potentially re-assessing the reported toxicity thresholds, but these data were unfortunately no longer available.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe long‑term marine ecotoxicity dataset for diclofenac\u003c/h2\u003e \u003cp\u003eA relatively small amount of long-term marine ecotoxicity data were considered sufficiently reliable and relevant for utilisation in the EC\u0026rsquo;s EQS assessment for diclofenac (EC 2022). This dataset comprised only four truly marine (as opposed to brackish water) species, covering population growth in a marine microalgae (DeLorenzo and Fleming 2008), larval development in a crustacean (Gonzalez-Ortegon et al., 2015), byssus strength inhibition in a bivalve mollusc (Ericson et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and fertilisation/ embryonic development in an echinoderm (Ribeiro et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). A further study on \u003cem\u003eParacentrotus lividus\u003c/em\u003e included in the EC\u0026rsquo;s assessment, and cited in EC 2022 as \u0026lsquo;Scymaris 2020b\u0026rsquo; represented a preliminary trial for the study with the same species reported in the present paper, and is therefore superseded by the later, definitive, test reported here.\u003c/p\u003e \u003cp\u003eA more extensive long-term dataset of marine effects was initially considered in the EC\u0026rsquo;s EQS assessment, covering a much wider range of species and effects, but evaluation according to the \u0026lsquo;CRED\u0026rsquo; approach (Moermond et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) revealed a lack of relevance for EQS derivation (e.g. responses in individual organisms rather than population-level effects; exposure conditions environmentally unrealistic), or potential reliability issues with the performance or reporting of the studies (EC 2022). Amongst the excluded studies, the papers by Zanuri et al., (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Duarte et al., (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Nunes et al., (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) are particularly noteworthy in the context of the present paper.\u003c/p\u003e \u003cp\u003eThe studies reported by Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and the reasons for their exclusion from the EC\u0026rsquo;s assessment, are described in the previous sections. Duarte et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported the effects of diclofenac on growth and metabolic biomarkers in the marine fish \u003cem\u003eArgyrosomus regius\u003c/em\u003e. The biomarkers were not regarded as relevant for EQS derivation by the EC because it was not possible to unequivocally associate any of the measured responses with population relevant parameters, and no dose-responses were observed. While growth was also measured, again no dose-response was evident and, with only two exposure concentrations, it was not possible to calculate an EC10 or derive a NOEC. Nunes et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) presented the responses of three enzymatic biomarkers (CAT, GST and AChE) in the marine worm \u003cem\u003eHediste diversicolor\u003c/em\u003e and marine fish \u003cem\u003eSolea senegalensis\u003c/em\u003e after exposure to diclofenac. As with Duarte et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), such biomarker responses are generally not considered to be relevant for EQS derivation since they relate to responses in individual animals and may not translate directly to population-relevant effects such as survival, reproduction and growth.\u003c/p\u003e \u003cp\u003eSince the studies reported by Duarte et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Nunes et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Zanuri et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) were all considered insufficiently reliable/ relevant for EQS derivation, the long-term marine effects dataset utilised in the EC\u0026rsquo;s EQS assessment lacked any data for marine fish or annelid worms.\u003c/p\u003e \u003cp\u003eThis paper presents a reliable and relevant study on the marine worm, \u003cem\u003eArenicola marina\u003c/em\u003e, but truly marine fish remain a significant gap in the available long-term dataset for diclofenac. Indeed, the lack of reliable and relevant marine fish data is a particular problem for such an assessment since i) fish are one of the most sensitive taxonomic groups in the long-term freshwater dataset, and ii) the EC\u0026rsquo;s guidance on EQS derivation (EC 2018) requires that vertebrates (which for the marine environment essentially means fish) are represented in the ecotoxicity dataset applied in the EQS assessment. However, in their reviews of the effects of diclofenac (and other pharmaceuticals) in marine organisms, Bonnefille et al. (2017), Blasco and Trombini (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and Punginelli et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) all consider the brackish water species \u003cem\u003eOryzias latipes\u003c/em\u003e as a suitable representative of fish living in saline waters for the purposes of assessing the effects of pharmaceuticals. Therefore, given the lack of any data on the effects of diclofenac in truly marine fish that could be considered sufficiently reliable and relevant for EQS derivation, it would seem a defensible approach to utilise the available data for \u003cem\u003eO. latipes\u003c/em\u003e in the marine EQS assessment.\u003c/p\u003e \u003cp\u003eThe full, updated long-term marine diclofenac ecotoxicity dataset as determined to be reliable and relevant for EQS derivation is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This dataset comprises EC10/ NOEC threshold concentrations for nine saltwater species, covering seven different higher taxonomic groups \u0026ndash; microalgae, cyanobacteria, crustaceans, bivalve molluscs, echinoderms, annelid worms and fish. Where more than one value EC10/ NOEC is available for the same species (e.g. \u003cem\u003eP. lividus\u003c/em\u003e), the most sensitive value has been used. The lowest effect concentration in the dataset is 0.578 \u0026micro;g/L diclofenac for inhibition of fertilisation in the marine worm, \u003cem\u003eA. marina\u003c/em\u003e, as presented in the current paper.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLong-term marine ecotoxicity dataset for diclofenac\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaxonomic Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLowest EC10/ NOEC (\u0026micro;g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEndpoint\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eDunaliella tertiolecta\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePopulation growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDeLorenzo and Fleming 2008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCyanobacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSynechocystis salina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;=100000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePopulation growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKropidlowska and Caban \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrustaceans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePalaemon longirostris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLarval development\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGonzalez-Ortegon et al., 2015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBivalve Molluscs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMytilus edulis trossulus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eByssus strength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEricson et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEchinoderms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eParacentrotus lividus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLarval length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRibeiro et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePsammechinus miliaris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFertilisation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAsterias rubens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFertilisation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnelid worms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eArenicola marina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFertilisation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eOryzias latipes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReproduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYokota et al., 2017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe EC highlighted the potential for a \u0026lsquo;bimodality\u0026rsquo; in the original (combined freshwater and marine) dataset (EC 2022), although the dataset they applied in their statistical analysis of potential bimodality was not identical to the dataset used by Leverett et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which included more data of \u0026lsquo;intermediate\u0026rsquo; ecotoxicity to diclofenac, relative to the other datapoints in the dataset. Nevertheless, in both the freshwater and marine datasets, there does seems to be an apparent lack of available diclofenac ecotoxicity effect threshold data within the 10 to 100 \u0026micro;g/L range. Considerable variability in sensitivity to diclofenac can clearly occur for different endpoints in the same species (e.g. larval growth in echinoderms (Ribeiro et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) appears to be significantly more sensitive to diclofenac than fertilisation success, based on the studies reported in the present paper); thus endpoint selection and the limited range of endpoints investigated for each species in the dataset is likely to exert some influence on the spread of the datapoints, and it is therefore possible that the apparent \u0026lsquo;sensitivity gap\u0026rsquo; is simply a function of the relatively small long-term ecotoxicity datasets for both freshwater and marine waters, and the choice of endpoint for each species. However, very wide variations in ecotoxicity threshold values also occur within the long-term ecotoxicity dataset for diclofenac across multiple tests with the same species and endpoint. While methodological differences may account for some of this variation (e.g. potentially the much reduced sensitivity of fertilisation success in the studies presented in this paper, as compared to those reported by Zanuri et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), this is unlikely to be the case where a more standardised test methodology is employed (e.g. EC/ NOEC thresholds for inhibition of reproduction in \u003cem\u003eDaphnia magna\u003c/em\u003e after 21 days exposure ranging from 120 to 72000 \u0026micro;g/L (Leverett et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eTest media pH has been shown to play a role in the ecotoxicity of ionisable compounds such as diclofenac, with maximum bioavailability, and therefore toxicity, at approximately neutral pH (Bittner et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; K\u0026ouml;hler et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Schweizer et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). K\u0026ouml;hler et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) demonstrated a strong correlation between the degree of effects in zebrafish embryos under different pH conditions, and the corresponding pH-dependent partitioning coefficient log D for a number of ionisable pharmaceuticals, including diclofenac. Kroll et al. (2023) highlighted this effect for diclofenac and proposed a model for the \u0026lsquo;normalisation\u0026rsquo; of toxicity values according to the pH conditions of the test exposures, based on a log D correction to pH 6.5 and 7. Using this model to correct the values in the wider (freshwater and marine) chronic dataset for diclofenac, Kroll et al. (2023) were able to achieve a more statistically robust Species Sensitivity Distribution than that presented in the EQS dossier for diclofenac (EC 2022), and which partially addressed the \u0026lsquo;bimodality\u0026rsquo; highlighted by the EC. It should be noted, however, that the dataset applied by Kroll et al. (2023) was substantially different from that applied by the EC (2022), with some data excluded on the basis of not reporting sufficient pH information or because of a differing view regarding the reliability/ relevance of specific studies.\u003c/p\u003e \u003cp\u003eWhile this provides a plausible explanation for some of the disparity in results observed in the (primarily freshwater) chronic ecotoxicity dataset applied by the EC (2022) and Leverett et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), it is more difficult to extrapolate to the limited chronic marine dataset for diclofenac (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). With the exception of the four tests reported here, pH data are missing or limited to such an extent as to make robust comparisons impossible. Using the model proposed by Knoll et al. (2023), the reported toxicity values for the four new studies (with a test media pH range of approximately 7.6 to 8.2) can be estimated to be between 6 and 9 times lower than the \u0026lsquo;low effect\u0026rsquo; thresholds reported in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, when adjusted to pH 6.5. However, these are tests using marine species and natural seawater, which generally has a pH between 7.5 and 8.5, and therefore the relevancy of adjusting to a pH in the range 6 to 6.5 is questionable. Nevertheless, the effect of pH on the uptake (and therefore toxicity) of ionisable pharmaceutical substances remains just as relevant for marine organisms as for those living in freshwaters. Hird (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) demonstrated the influence of seawater pH on the uptake of diclofenac in the marine worm \u003cem\u003eHediste diversicolor\u003c/em\u003e, with almost twice as much uptake occurring in sea water at pH of 7.4 compared to 8.1, after 48 hours exposure to a diclofenac concentration of 50 \u0026micro;g/L. This suggests a \u0026lsquo;normalisation\u0026rsquo; of marine ecotoxicity thresholds for diclofenac to an environmentally-realistic pH of maximum bioavailability for marine waters (e.g. 7.5) could be a useful approach for the future where the relevant pH data are available.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMarine EQS Derivation\u003c/h2\u003e \u003cp\u003eThe EQS TGD (EC 2018) allows for two approaches in deriving EQS: a deterministic method, whereby the lowest EC10/ NOEC in the dataset is divided by an Assessment Factor which accounts for the various uncertainties in the assessment; and a probabilistic (statistical) method in which a Species Sensitivity Distribution is constructed using the entire dataset or a subset of it, and the threshold representing the concentration of the substance predicted to affect 5% of species is extrapolated, again divided by an Assessment Factor to account for uncertainties in the prediction. Both approaches are intended to provide sufficient protection for the range of species/ taxonomic groups potentially exposed to the substance of interest in the environment, the overwhelming majority of which remain of unknown sensitivity.\u003c/p\u003e \u003cp\u003eThe most sensitive EC10/ NOEC from reliable and relevant long-term marine ecotoxicity dataset for diclofenac is 0.578 \u0026micro;g/L for inhibition of fertilisation in the annelid worm \u003cem\u003eArenicola marina\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For the deterministic approach, the EQS TGD (EC 2018) prescribes Assessment Factors of 10 to 10,000 dependent on the quantity of available long-term ecotoxicity data. In the case of the long-term marine dataset for diclofenac, the lowest Assessment Factor (=\u0026thinsp;10) is appropriate since it includes long-terms results for saltwater species representing three trophic levels (i.e. algae/ cyanobacteria, invertebrates and fish), as well as three long-term results for specific marine taxonomic groups (covering bivalve molluscs, echinoderms, and annelid worms). A deterministic marine EQS can thus be derived by dividing the lowest EC10/ NOEC in the dataset by an Assessment Factor of 10, to give 0.0578 \u0026micro;g/L or 58 ng/L. This value is over 10 times greater than the marine Annual Average (AA) EQS proposed by the EC (2022) of 4 ng/L, based on freshwater mesocosm data (Joachim et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and an Assessment Factor of 50.\u003c/p\u003e \u003cp\u003eThe reliable and relevant long-term marine dataset for diclofenac (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) does not meet the minimum requirements prescribed by the EQS TGD (EC 2018) for the use of a probabilistic approach to EQS derivation, of at least ten species covering at least eight higher taxonomic groups. The updated marine dataset represents nine species in seven taxonomic groups: algae, cyanobacteria, crustaceans, bivalve molluscs, echinoderms, annelid worms and fish. Thus, the minimum data quantity requirements of the EQS TGD (EC 2018) are not quite met in either case. The EQS TGD (EC 2018) also highlights that certain specific taxonomic groups should be represented in the dataset: at least - two species of fish, each in a different family (or one fish species and an amphibian species); one species of crustacean; two species of insect, each in different order (or one species of insect and a species of a phylum not otherwise represented in the dataset); one species of algae or cyanobacteria; one species of higher plant. The TGD also provides for allowances to be made when dealing with marine ecotoxicity data alone since data for amphibians, insects and higher plants are unlikely to be available, and these groups can be replaced with marine-specific taxa such as bivalve molluscs, echinoderms and annelid worms. Only a single (brackish water) fish species is represented, and predictably there are no insects or higher plants in the dataset. However, bivalve molluscs, echinoderms and annelid worms are all represented. Nevertheless, taking the limited dataset as a whole, it would likely be considered to be insufficient for derivation of a probabilistic marine EQS by most practitioners experienced with the EC\u0026rsquo;s EQS derivation process (EC 2018). While acknowledging this, a Species Sensitivity Distribution (SSD) has been constructed using the Canadian SSD software package ssdtools (Dalgarno (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); Ministry of the Environment, British Columbia \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bcgov-env.shinyapps.io/ssdtools/\u003c/span\u003e\u003cspan address=\"https://bcgov-env.shinyapps.io/ssdtools/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which requires a minimum of only eight datapoints to generate an SSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The software generates outputs for a number of different distribution models, along with statistics describing the degree of \u0026lsquo;fit\u0026rsquo; of the data to each model. It also combines the various outputs into an \u0026lsquo;average\u0026rsquo; prediction. The Hazardous Concentration predicted to effect 5% of exposed species (HC5) by the average of the distributions (gamma, log gimbel, log logistic, log normal and Weibull) is 0.183 \u0026micro;g/L, with 95% confidence limits of 0.0188 to 20.9 \u0026micro;g/L. The wide confidence limits in the assessment clearly highlight the high degree of uncertainty in this prediction. Applying the maximum Assessment Factor of 5 to the average HC5 value from these distributions as prescribed by the EQS TGD (EC 2018) for probabilistic EQS derivation gives 0.037 \u0026micro;g/L or 37 ng/L. This is slightly lower than the deterministic marine EQS of 58 ng/L, and still almost 10 times higher than the EC\u0026rsquo;s proposed marine EQS.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eRisk Assessment\u003c/h2\u003e \u003cp\u003eDiclofenac monitoring data for the assessment were obtained from European Union member state environment agencies from either online portals (for example France (Surval \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)), reports produced by agencies (for example Baltic Sea data (Hallgren and Wallberg \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)) or through direct contact (for example German data from the Lower Saxony Environment Agency (NLWKN 2022)). Additionally, data were obtained from the European Environment Agency (EEA) WISE State of the Environment database (EEA 2025) and the Black Sea Environmental Data Platform (EMBLAS 2024).\u003c/p\u003e \u003cp\u003eGiven diclofenac is now a Priority Substance under the WFD, member states will be expected to include it in their assessment of water body chemical status. The measured environmental data for the marine environment gathered here were not sufficient to allow an assessment of chemical status according to WFD legislation and guidance, with measurements generally not being of a high enough frequency or consistency of location to allow the requisite confidence and precision required.\u003c/p\u003e \u003cp\u003eNevertheless, an indicative compliance assessment has been performed for marine and transitional waters using the prospective marine EQSs of 37 and 58 ng/L derived above, as well as the proposed EU EQS of 4 ng/L.\u003c/p\u003e \u003cp\u003eThe compiled dataset of measured diclofenac concentrations consists of 311 samples of coastal or transitional water, with individual dataset sizes ranging from 1 sample for France and Iceland to 116 samples for the Black Sea. The degree of censoring in the dataset was variable with all samples above the limit of detection (LOD) for the Baltic Sea, France and Spain and 100% of samples below the LOD for Estonia, Germany, Iceland, Latvia, Malta and the Netherland (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Overall, the dataset was 69% censored (214 out of 311 samples) with quantified concentrations ranging from 0.03 ng/L (in the Baltic Sea) to 240 ng/L (in Spain). A compliance assessment was performed using three different data treatment scenarios against the deterministic method EQS (58 ng/L), the probabilistic method EQS (37 ng/L) and the proposed EU EQS (4 ng/L):\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eScenario 1; Samples\u0026thinsp;\u0026lt;\u0026thinsp;LOD set to the LOD,\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScenario 2; Samples\u0026thinsp;\u0026lt;\u0026thinsp;LOD set to half the LOD, and\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScenario 3; Quantified samples only assessed.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThese three different scenarios were selected to provide a full range of conclusions to be drawn from the indicative compliance assessment. A summary of the compliance assessment outcomes is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the full measured concentration dataset is provided in the supplementary information.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of diclofenac marine compliance assessment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e# of Samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e% Censored\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c13\" namest=\"c4\"\u003e \u003cp\u003ePercentage Compliance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eScenario 1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eScenario 2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eScenario 3\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e58 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e#\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e37 ng/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e58 ng/L\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaltic Sea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelgium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack Sea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulgaria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIceland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIreland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLatvia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eOverall\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e311\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e69%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e63%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e79%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e97%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e64%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e95%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e97%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e97\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e70%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e84%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e91%\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003csup\u003ea\u003c/sup\u003e Samples\u0026thinsp;\u0026lt;\u0026thinsp;LOD set to the LOD\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003csup\u003eb\u003c/sup\u003e Samples\u0026thinsp;\u0026lt;\u0026thinsp;LOD set to half the LOD\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003csup\u003ec\u003c/sup\u003e Quantified samples only assessed\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003csup\u003ed\u003c/sup\u003e Number of samples above LOD\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor the assessment performed using the probabilistically calculated prospective EQS, overall compliance ranged from 79% for Scenario 1 to 97% for Scenario 2 with country-specific compliance ranging from 0% (for Latvia and Estonia in Scenario 1) to 100% (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It is of note that for both Latvia and Lithuania that all samples are below the LOD and the LOD is of sufficient sensitivity for 100% compliance under Scenario 2.\u003c/p\u003e \u003cp\u003eWhen the data are assessed using the prospective deterministic EQS of 58 ng/L, overall compliance increases to 97% for Scenarios 1 and 2 (from 79% and 95%, respectively) and to 91% for Scenario 3 (from 84%); with country-specific compliance ranging from 33% (Bulgaria in Scenario 3) to 100% (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, compliance against both the probabilistic and deterministic EQS is high (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) with 79% or higher compliance in all scenarios with either EQS; and when only Scenario 2 (LOD*0.5) is reviewed compliance rises to 95% \u0026minus;\u0026thinsp;97%. It is of note that it is a version of Scenario 2 that is used for substance prioritisation in Europe, when assessing substance suitability for inclusion on the EU Watchlist (Gomez Cortes et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen compliance is assessed against the proposed EU EQS of 4 ng/L, it ranges from 63% for Scenario 1 to 70% for Scenario 3 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) which is considerably lower than compliance when the data are assessed against the EQS derived in the present paper. The issues of treatment of censored data and instrument sensitivity are more acute for this proposed EQS, since it is 9 to 15 times more sensitive. Overall, 84 samples (27% of the compiled dataset) are below the LOD with the LOD being greater than twice the proposed EU EQS of 4 ng/L (a criteria used in EU for removal of samples from prioritisation datasets (Gomez Cortes et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)); no censored samples have a LOD greater than twice that of the probabilistic EQS.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur comprehensive investigations into the potential of diclofenac to inhibit fertilisation on echinoderms and annelid worms failed to reproduce the extremely sensitive results previously reported (Zanuri et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Only limited effects were induced in two species of sea urchin and a starfish at concentrations well beyond environmental realism, regardless of whether the adults from which gametes were sourced were pre-exposed. Fertilisation in the annelid worm \u003cem\u003eA. marina\u003c/em\u003e was considerably more sensitive to diclofenac exposure than the echinoderm species tested, with a derived NOEC of 578 ng/L, although this was still over 50 times the LOEC reported by Zanuri et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e.\u003c/p\u003e \u003cp\u003ePotential reasons for the differences in sensitivity observed include methodological disparities between the studies (e.g. pre-exposure of gametes with no exposure during fertilisation versus exposure only during fertilisation), a temporal lag in the fertilisation process caused by diclofenac exposure, and disparity in the uptake of diclofenac by gametes and embryos caused by the use of a solvent or variation in test media pH. Insufficient information is available to be certain of the exact reasons for the differences, which highlights the need for test reliability criteria (e.g. the CRED criteria proposed by Moermond et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)) to be accounted for in the initial design of such studies and for raw effect data to be included in published materials. This is especially critical as regulatory assessments increasingly require an assessment of published studies (e.g. EMA 2024). This requirement also means that the publication of studies showing no or minimal effects is just as important as those highlighting significant effects at environmentally relevant concentrations of substances.\u003c/p\u003e \u003cp\u003eThe reliable and relevant long-term marine ecotoxicity dataset for diclofenac has been updated to include the studies reported in the present paper. This updated dataset comprises 9 saltwater species in 7 taxonomic groups \u0026ndash; cyanobacteria, microalgae, crustaceans, bivalve molluscs, echinoderms, annelid worms and fish. Prospective deterministic and probabilistic EQS have been derived using this dataset of 58 and 37 ng/L, respectively. These prospective EQS have been compared with diclofenac measured concentration data from European marine waters to predict the degree of risks associated with diclofenac exposure. Compliance with the prospective EQS was dependent on the way in which censored (\u0026lt;\u0026thinsp;LOD) monitoring data were treated in the assessment. However, if the approach generally applied in WFD annual average compliance assessments is used (samples results less than the LOD are set to 0.5*LOD), overall compliance with the prospective EQS was 95\u0026ndash;97% (n\u0026thinsp;=\u0026thinsp;311). Conversely, compliance with the proposed EU marine EQS (4 ng/L; EC 2022) was only 64%. Based on this prospective, but entirely marine-focused, hazard and risk assessment, the EU EQS - derived entirely from a single freshwater mesocosm study (Joachim et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) \u0026ndash; may be over-precautionary.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the input of Jim Ryan of GSK Consumer Healthcare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach author made substantial contributions to the conception, analysis, and interpretation of data and assisted in drafting the work. Each author approved the submitted version (and any substantially modified version that involves the author\u0026rsquo;s contribution to the study) and agrees both to be personally accountable for the author\u0026rsquo;s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe funding for this article was provided by Haleon Consumer Healthcare SARL. The funding for the ecotoxicological testing was provided by GlaxoSmithKline (GSK) Consumer Healthcare SARL.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eDeclarations\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDean Leverett, Iain Wilson and Lucy Kennelly are employees of a consultancy (wca Environment Ltd) which works for companies on projects focusing on the environmental risk assessment of chemicals, including pharmaceuticals. Tom Austin works for a company (Haleon) that produces diclofenac, sells products containing diclofenac, and submits pharmaceutical environmental risk assessments to regulatory authorities. Richard Maunder, Daniel Hill and Pete Johnson work for a Contract Research Organisation (Scymaris) that undertakes commercial ecotoxicological research. Cameron Hird previously worked at Scymaris.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBittner L, Teixido E, Seiwert B, Escher BI, Kl\u0026uuml;ver N (2018) Influence of pH on the uptake and toxicity of \u0026beta;-blockers in embryos of zebrafish, \u003cem\u003eDanio rerio\u003c/em\u003e. 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Selection of substances for the 4th Watch List under the Water Framework Directive, Publications Office of the European Union, Luxembourg, 2022, doi:10.2760/01939, JRC130252.\u003c/li\u003e\n\u003cli\u003eGonzalez-Ortegon E, Blasco J, Nieto E, Hampel M, Le Vay L, Gimenez L (2016) Individual and mixture effects of selected pharmaceuticals on larval development of the estuarine shrimp \u003cem\u003ePalaemon longirostris\u003c/em\u003e. Sci Total Environ 540:260\u0026ndash;266.\u003c/li\u003e\n\u003cli\u003eHallgren P, Wallberg P. 2015. Background report on pharmaceutical concentrations and effects in the Baltic Sea. Policy Area Hazards of the EU Strategy for the Baltic Sea Region. Swedish Environmental Protection Agency, Stockholm, Sweden.\u003c/li\u003e\n\u003cli\u003eHird. 2021. Ecotoxicology of Active Ingredients in Changing Marine Environments. University of Exeter. 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Ecotoxicology and Environmental Safety 211.\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;hler H-R, Gr\u0026auml;ff T, Schweizer M, Blumhardt J, Burkhardt J, Ehmann L, Hebel J, Heid C, Kundy L, Kuttler J, Malusova M, Moroff F-M, Schl\u0026ouml;singer A-F, Schulze-Berge P, Panagopoulou EI, Damalas DE, Thomaidis NS, Triebskorn R, Maletzki D, K\u0026uuml;hnen U, von der Ohe PC (2023) LogD-based modelling and \u0026Delta;logD as a proxy for pH-dependent action of ionizable chemicals reveal the relevance of both neutral and ionic species for fish embryotoxicity and possess great potential for practical application in the regulation of chemicals. Water Research 235.\u003c/li\u003e\n\u003cli\u003eKroll A, von der Ohe PC, K\u0026ouml;hler HR, Sellier O, Junghans M (2024) Aquatic thresholds for ionisable substances, such as diclofenac, should consider pH-specific differences in uptake and toxicity. Science of the Total Environment 908. \u003c/li\u003e\n\u003cli\u003eKropidlowska K, Caban M (2023) Effect of salinity on the toxicity of diclofenac, ibuprofen and naproxen toward cyanobacterium \u003cem\u003eSynechocystis salina\u003c/em\u003e. Chemosphere 338.\u003c/li\u003e\n\u003cli\u003eLeverett D, Merrington G, Crane M, Ryan J, Wilson I (2021) Environmental quality standards for diclofenac derived under the European Water Framework Directive: 1. Aquatic organisms. Environmental Sciences Europe 33:133\u003c/li\u003e\n\u003cli\u003eLeverett D, Merrington G, Crane M, Wilson I (2022) Response to commentary article on environmental quality standards for diclofenac derived under the European water framework directive: 1. Aquatic organisms, by Maack et al. 2022. Environmental Sciences Europe (2022) 34:119.\u003c/li\u003e\n\u003cli\u003eMaack G, \u0026Auml;yst\u0026ouml; L, Carere M, Clausen H, James A, Junghans M, Junttila V, Hollender J, Marinov D, Stroomberg G,Triebskorn R, Verbruggen E, Lettieri T (2022) Comment on Environmental quality standards for diclofenac derived under the European Water Framework Directive: 1. Aquatic organisms. Environmental Sciences Europe 34: 24.\u003c/li\u003e\n\u003cli\u003eMerrington G, Leverett D, Peters RJ (2020) Perspectives on relevancy assessment for non-standard ecotoxicity data in environment quality standard derivation: examples for Diclofenac. Bull Environ Contaminat Toxicol. 105: 665\u0026ndash;670.\u003c/li\u003e\n\u003cli\u003eMoermond CTA, Kase R, Korkaric M, Agerstrand M (2015) CRED: criteria for the reporting and evaluating ecotoxicity data. Environ Toxicol Chem 35:1297\u0026ndash;1309.\u003c/li\u003e\n\u003cli\u003e[NLWKN] Lower Saxony State Office for Water Management, Coastal and Nature Conservation. 2022. Diclofenac monitoring data obtained 18/08/2022. Data License Germany - Attribution - Version 2.0\u003c/li\u003e\n\u003cli\u003eNunes B, Daniel D, Gon\u0026ccedil;alves Canelas G, Barros J, Teodorico Correia A (2020) Toxic effects of environmentally realistic concentrations of diclofenac in organisms from two distinct trophic levels, \u003cem\u003eHediste diversicolor\u003c/em\u003e and \u003cem\u003eSolea senegalensis\u003c/em\u003e. Comparative Biochemistry and Physiology Part C: Toxicology \u0026amp; Pharmacology 231.\u003c/li\u003e\n\u003cli\u003ePatrolecco L, Capri S, Ademollo N (2015) Occurrence of selected pharmaceuticals in the principal sewage treatment plants in Rome (Italy) and in the receiving surface waters. Environ Sci Pollut Res Int 22:5864\u0026ndash;5876.\u003c/li\u003e\n\u003cli\u003ePeters A, Crane M, Merrington G, Ryan J (2022) Environmental quality standards for diclofenac derived under the European water framework directive: 2. Avian secondary poisoning. Environmental Sciences Europe 34:28.\u003c/li\u003e\n\u003cli\u003ePunginelli D, Maccotta A, Savoca D (2024) Biological and Environmental Impact of Pharmaceuticals on Marine Fishes: A Review. Journal of Marine Science and Engineering 12,1133.\u003c/li\u003e\n\u003cli\u003eRibeiro S, Torres T, Martins R, Santos MM (2015) Toxicity screening of diclofenac, propranolol, sertraline and simvastatin using \u003cem\u003eDanio rerio\u003c/em\u003e and \u003cem\u003eParacentrotus lividus\u003c/em\u003e embryo bioassays. Ecotoxicol Environ Saf 114:67\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eSANCO/3029/99 rev.4 11/07/00 (2000). 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Biological effect and chemical monitoring of Watch List substances in European surface waters: Steroidal estrogens and diclofenac \u0026ndash; Effect-based methods for monitoring frameworks. Environment International, Volume 159.\u003c/li\u003e\n\u003cli\u003eSurval. 2025. Access to marine and coastal environmental data; https://surval.ifremer.fr/Donnees/Donnees-par-parametre#/map. Source : Quadrige - Programme : EMERGENTSEA_POCIS. Etalab\u0026apos;s Open License V2.0.\u003c/li\u003e\n\u003cli\u003eTiedeken EJ, Tahar A, McHugh B, Rowan NJ (2017) Monitoring, sources, receptors, and control measures for three European Union watch list substances of emerging concern in receiving waters\u0026mdash;a 20 year systematic review. Sci Total Environ 574:1140\u0026ndash;1163.\u003c/li\u003e\n\u003cli\u003eZanuri NBM, Bentley MG, Caldwell GS (2017) Assessing the impact of diclofenac, ibuprofen and sildenafil citrate (Viagra\u0026reg;) on the fertilisation biology of broadcast spawning marine invertebrates. Marine Environmental Research 127. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diclofenac, Marine, Environmental quality standard, Ecotoxicity, European Water Framework Directive","lastPublishedDoi":"10.21203/rs.3.rs-6295199/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6295199/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDiclofenac is a nonsteroidal anti-inflammatory human and veterinary medicine widely detected in European waters downstream of Wastewater Treatment Plants. Proposed Environmental Quality Standards (EQS) for diclofenac, which include an assessment of toxicity to aquatic organisms, have been proposed by the European Commission to support the objectives of the Water Framework Directive, including EQS aimed at protecting marine species. In this paper, we present previously unpublished studies assessing the effects of diclofenac on four marine species, three echinoderms and an annelid worm. The results of these new tests were incorporated into the long-term marine ecotoxicity dataset for diclofenac and an updated marine EQS derived. Finally, these updated prospective EQS were compared with measured diclofenac concentrations in European marine waters to assess potential risk.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eLimited effects on fertilisation were measured in echinoderms at diclofenac concentrations beyond environmental relevance. However, fertilisation in the annelid worm \u003cem\u003eArenicola marina\u003c/em\u003e was found to be sensitive to diclofenac exposure, with a No Observed Effect Concentration of 578 ng/L. Using the updated marine ecotoxicity dataset for diclofenac, prospective marine EQS of 58 and 37 ng/L were derived, respectively, using deterministic and probabilistic (species sensitivity distribution) derivation approaches. The indicative compliance of European marine waters with the prospective EQS is 79\u0026ndash;97%.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eComprehensive investigations into the potential of diclofenac to inhibit fertilisation on echinoderms and annelid worms failed to reproduce the extremely sensitive results previously reported in published studies. The reduced sensitivity observed here were potentially a result of methodological differences between the studies, such as pre-exposure of gametes versus exposure only during fertilisation, the time allowed for the fertilisation process, as well as the possibility of differential uptake of diclofenac owing to use of a solvent or pH variation. Compliance with the prospective EQS depended on the method used to treat the censored measured concentration data but was generally high across all monitored European marine waters. This entirely marine-focused hazard and risk assessment suggests that a proposed EU EQS of 4 ng/L, derived entirely from a single freshwater mesocosm study, is likely to be over-precautionary for European marine waters.\u003c/p\u003e","manuscriptTitle":"Environmental quality standards for diclofenac derived under the European Water Framework Directive: 3. 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