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1 BASF DocID 2010/ The use of aquatic species sensitivity distributions for Cypermethrin for the derivation of EQS values in the context of the Water Framework Directive Dr. Maike Habekost* and Dr. Lennart Weltje BASF SE, Crop Protection - Ecotoxicology, Speyerer Strasse 2, D Limburgerhof, Germany. *Phone: , maike.habekost@basf.com Limburgerhof, September 17, 2010 Introduction This statement presents a comparison of three published aquatic species sensitivity distributions (SSDs) for the pyrethroid insecticide cypermethrin. The use of SSDs is advised in the Technical Guidance Document (TGD) for deriving environmental quality standards (2010) as a means of refinement for EQS setting. The use of additional species data provides a sophisticated way of accounting for uncertainties related to the different sensitivities of species. In the reviewed publications hazardous concentrations for 5% of the species (HC 5 ) were calculated. The reviewed SSDs used various different data sources (partly overlapping) comprising in total an unusual high number of studies on sensitive taxa and thereby provide a reliable estimation of the range of non-target sensitivities. The most reliable HC 5 estimate would therefore be a conservative estimate which takes into account a multitude of studies. Based on the comparison of SSDs and the HC 5 value, recommendations are made for derivation of EQS values for cypermethrin as a candidate priority substance in the European Water Framework Directive (WFD). Due to the high lipophilicity of cypermethrin it only shortly resides in the water column and rapidly adsorbs to sediment and suspended matter. For this reason the focus for short-term risks should be on the MAC-EQS for surface water and for long-term risks on the sediment AA-EQS. Consequently, a long-term AA-EQS for surface water is less useful as already pointed out by Crane et al. (2007). Literature search and data selection A literature search was conducted reviewing publications in which SSDs for cypermethrin were presented. The following publications reported HC 5 values: Solomon et al. (2001), Maltby et al. (2005) and Bollmohr et al. (2007). Most of the endpoints that were used in the different SSDs come from tests with aquatic arthropods, typically the most sensitive group for insecticides. Also 1
2 in the case of cypermethrin (and for pyrethroids in general) arthropods provide the lowest endpoints that consequently drive the risk assessment and the EQS derivation. The following sources were used by the authors: Solomon et al. (2001) collected data from the U.S. Environmental Protection Agency Pesticide Toxicity Database (Oneliner Database), from the open scientific literature, and from industry (Pyrethroid Working Group members). Maltby et al. (2005) obtained the data from existing toxicity databases (e.g. AQUIRE, RIVM database), published literature and unpublished industry data. Bollmohr et al. (2007) collected data from the US Environmental Protection Agency AQUIRE database, restricting the data to papers published after The authors applied the following selection criteria: Selected endpoints were median lethal concentration (LC 50 ) or median effect concentration (EC 50 ) regarding immobility for animals and EC 50 regarding biomass or growth for plants and algae. The data used in the analysis of Bollmohr et al. (2007) and Solomon et al. (2001) were derived from acute assays conducted over periods from 24 to 96 h. In Maltby et al. (2005) the test duration was 2 to 21 d for fish, 1 to 7 d for invertebrates, 2 to 28 d for macrophytes, and 1 to 7 d for algae. Hence, Maltby et al. (2005) also covered at least partially chronic effects. If multiple data for the same species were available, the geometric mean toxicity values were used to represent the species in the distribution. Maltby et al. (2005) further stated that a genus-specific geometric mean was used when no specific names were provided (it is unclear if this was the case for cypermethrin). Toxicity values reported as a value greater than a certain concentration (e.g. the solubility limit) were excluded from the dataset. Solomon et al. (2001) also used data which were obtained from tests with formulated products. Toxicity data for formulated products were generally not very different from those for the technical material and, for this reason were included in the data set. In all cases, the effect concentration was converted to active ingredient to allow for combination and comparison. The following number of data points were used to calculate the SSDs: Solomon et al. (2001): all organisms: 58; arthropods: 42; vertebrates: 17 Maltby et al. (2005): all organisms: 65; arthropods: 41; non-arthropod invertebrates: 4; vertebrates 20 (P.J. van den Brink, personal communication). Bollmohr et al. (2007): all freshwater organisms: 57; freshwater arthropods: 38; freshwater fish: 16; marine organisms: 6 (5 arthropods and 1 fish). The calculations were done applying the following analysis: Solomon et al. (2001): the log-normal model was used for characterization of toxicity distributions. For the purpose of characterizing the toxicity profile, the distribution was described by a linear regression of the log-probability transformed data. Maltby et al. (2005): used the log-normal distribution model following Aldenberg and Jaworska (2000), as incorporated in the ETX software. The model fit was evaluated using the Anderson Darling goodness-of-fit test. Bollmohr et al. (2007): applied the program BurrliOz using the log-logistic distribution, unless another distribution was found that fitted the data better, with model fit being evaluated using the Anderson-Darling goodness-of-fit test. The method of Aldenberg and Jaworska (2000) was used to calculate 95% confidence limits. 2
3 Results of SSDs All authors calculated HC 5 values separately for aquatic vertebrates (mainly fish) and arthropods (insects and crustaceans). Freshwater and marine species differences in sensitivity were not significant (Maltby et al., 2005; Bollmohr et al., 2007). The resulting HC 5 refers to a 50% effect concentration for 5% of the species, because the input data of the SSD are L(E)C 50 values. The overall short duration of the studies fits to the short residence time of cypermethrin in the water column. Table 1. Mean hazardous concentrations (HC 5 values) and 95% confidence intervals in ng/l Reference All species Vertebrates Arthropods Solomon et al. (2001) 4.0 < Maltby et al. (2005) (50-420) Bollmohr et al. (2007) 3.3 ( ) 50 ( ) 3.0 ( ) 2.4 (0.3* - 18) *original publication value of 3.0 must be erroneous as it is higher than the HC 5 and was replaced by 0.3 The HC 5 values for vertebrates range from 50 ng/l to < 230 ng/l. Vertebrates are clearly less sensitive than arthropods for which the HC 5 estimates are almost identical, ranging from 2.4 to 3.0 ng/l, which is partly related to the use of the same data. Further, the HC 5 values for all species are almost identical to those of the arthropods, demonstrating that the latter are the most sensitive group and also that they contribute most of the data to the SSD. Hence, by focussing on the arthropods, the other taxonomic groups are covered. Judging by the statistical fit and the number of species accounted for, the HC 5 as derived by Maltby et al. (2005) is selected as the most reliable estimate. In addition, this value was confirmed by the HC 5 values of the other papers and validated by comparison with field studies. In contrast to the other papers, Maltby et al. (2005) also included chronic studies. Therefore, the best estimate of the HC 5 value for arthropods is 3.0 ng/l. Derivation of EQS values According to the TGD (2010) an SSD-based EQS is considered reliable if the database used for calculation contains preferably more than 15, but at least 10 endpoints. This criterion was introduced to ensure that the dataset for an SSD is statistically and ecologically representative of the community of interest. Further, the results of the most sensitive group of organisms (i.e. the arthropods containing crustaceans and insects) are very conclusive. The vast amount of data used for the SSD significantly reduces uncertainty around the toxicity of cypermethrin to aquatic organisms. It should be considered that for the most sensitive group of aquatic organisms there were 41 species represented in the SSD by Maltby et al. (2005). This significant reduction in uncertainty should be reflected in reduced assessment factors to obtain the EQS values. The HC 5 value can be used to derive the EQS by applying an assessment factor to this endpoint (cf. TGD, 2010). 3
4 For the derivation of a MAC-EQS the assessment factor on the HC 5 should normally be 10, unless other lines of evidence suggest that a higher or lower one is appropriate (TGD, 2010). The assessment factor can be lowered if the following cases are fulfilled: the diversity and representativity of the taxonomic groups covered by the database, and the extent to which differences in the life forms, feeding strategies and trophic levels of the organisms are represented; knowledge on presumed mode of action of the chemical (covering also long-term exposure). Details on justification could be referenced from structurally similar substances with established mode of action; statistical uncertainties around the HC 5 estimate, e.g., reflected in the goodness of fit or the size of confidence interval around the 5 th percentile, and consideration of different levels of confidence (e.g. by a comparison between the median estimate of the HC 5 with the lower estimate (90% confidence interval) of the HC 5 ) (TGD, 2010) For cypermethrin all of the above-mentioned cases are fulfilled. The representativeness of species is given, because the SSD was based on a high number of studies (more than 65, considering that non-sensitive species with greater than endpoints were excluded from the SSD and thus covered by the remaining sensitive species). Since the HC 5 is derived from arthropod endpoints, the most sensitive group of species is included with 41 species in the case of Maltby et al. (2005). The neurotoxic mode of action of cypermethrin in arthropods (i.e. modulation of sodium channels, causing hyperexcitation followed by paralysis) is well known. Further, the narrow confidence intervals indicate a good statistical fit of the used distribution model. Thus, the uncertainties around the derivation of the HC 5 are very small and a significant reduction of the assessment factor is therefore justified. According to Maltby et al. (2009) an AF of 1 is sufficiently protective to cover for short-term exposures (MAC-EQS) and an AF of 3 to cover for long-term exposures (AA-EQS). RACs for plant protection and biocide use Besides EQS values derived in the context of the WFD, other regulatory acceptable concentrations (RACs) for surface water and sediment have been published. In Table 2, the regulatory derived ecologically acceptable concentrations (EAC) for plant protection products containing alpha-cypermethrin or cypermethrin and the PNEC sw for the PT 8 biocidal use of cypermethrin are presented. According to the Aquatic Guidance Document for plant protection products (EC, 2002) The EAC is derived from an overall evaluation of a compound. In concept it is comparable to the Predicted No Effect Concentration (PNEC) defined for other chemical types in the EU framework (e.g. industrial chemicals, biocides, veterinary medicines, feed additives). These regulatory endpoints, derived from the submitted GLP studies can be interpreted as MAC-EQS if they were derived for plant protection product uses or as AA-EQS if they were derived from the biocide registration, since for biocidal products a continuous exposure is assumed (EC, 2003). 4
5 Table 2. Comparison of EQS values for cypermethrin, derived in the context of different regulatory frameworks MAC-EQS (ng/l) AA-EQS (ng/l) Endpoint Value (ng/l) Reference RAC EAC 15 / AF RAC EAC 50 / AF RAC HC / AF PNEC sw NOEC 50 / AF 5-10 RAC HC / AF PNEC sed EqP using PNEC sw 10 and K oc µg/kg EU Review Report alpha-cypermethrin, 2004 EU Review Report cypermethrin, 2005 Maltby et al., 2005 Maltby et al., 2009 EU CAR PT8 cypermethrin, 2010 Maltby et al., 2005 Maltby et al., 2009 EU CAR PT8 cypermethrin, 2010 Freshwater MAC-EQS For alpha-cypermethrin and cypermethrin MAC-EQS are available of 15 and 25 ng/l, respectively, derived from submitted GLP studies in a plant protection context. A third value is available based on GLP studies and public literature, which were used to derive an HC 5 by means of an SSD. This value was validated by comparison with mesocosm studies (Maltby et al., 2005) and also across various classes of pesticides comprising a total of 30 active ingredients (Maltby et al., 2009). Compared to the other MAC-EQS values of 15 and 25 ng/l, the proposed MAC-EQS of 3.0 ng/l is considered sufficiently conservative and endorsed here. Since marine arthropods are not significantly more sensitive to cypermethrin than freshwater arthropods (Maltby et al., 2005; Bollmohr et al., 2007) the same MAC-EQS can be used for marine waters. Freshwater AA-EQS Cypermethrin is highly lipophilic as indicated by its high logp ow. This indicates a strong tendency to sorb to sediment. This results in a fast dissipation of cypermethrin from the water column which makes the need for a water EQS-AA questionable (see also Crane et al., 2007). Nevertheless an AA-EQS water is derived because it is a prerequisite for the calculation of a sediment AA-EQS via the equilibrium portioning (EqP) method. For cypermethrin an AA-EQS of 10 ng/l is available derived from submitted GLP studies in a plant protection context. Maltby et al. (2009) compared the HC 5 from SSDs with mesocosm studies for 30 compounds and concluded that the median HC 5 estimate based on acute toxicity is generally protective for long-term exposure when a safety factor of 3 is applied. This approach would result in an AA-EQS of 1.0 ng/l. Compared to the other AA-EQS value of 10 ng/l, the proposed AA-EQS of 1.0 ng/l is considered sufficiently conservative and endorsed here for derivation of the AA-EQS for sediment (see below). 5
6 Since marine arthropods are not significantly more sensitive to cypermethrin than freshwater arthropods (Maltby et al., 2005; Bollmohr et al., 2007) the same AA-EQS can be used for marine waters. Sediment AA-EQS Derivation of a sediment AA-EQS makes more sense than deriving an AA-EQS for water, because cypermethrin, like all pyrethroids, has only a short residence time in surface water (see also Crane et al., 2007). Assuming equilibrium between overlying water and sediment, a sediment AA-EQS can be derived based on the EqP theory. This requires input of the surface water AA-EQS and a K oc (e.g as determined by Maund et al., 2002). Based on the AA-EQS of 1.0 ng/l and the afore-mentioned K oc the AA-EQS for sediment is 17.5 µg/kg dry sediment. For the biocide use a K oc of was used as input parameter for the EqP method and resulted in a PNEC sed of 125 µg/kg. This PNEC is equivalent to an AA-EQS for sediment, since for biocides continuous exposure is assumed. The proposed AA-EQS of 17.5 µg/kg is endorsed here, since it is considered sufficiently conservative compared to the AA-EQS value of 125 µg/kg. The TGD (2010) states that "when the QS sediment has been calculated using EqP and log K ow > 5 for the compound of interest, QS sediment is divided by 10. This correction factor is applied because EqP only considers uptake via the water phase. Extra uncertainty due to uptake by ingestion of food should be covered by the applied assessment factor of 10". Since the logp ow of cypermethrin is > 5 this aspect needs consideration. In the case of pyrethroids, there is ample evidence that their toxicity is governed by the water phase. Apparently there is no contribution of food as an additional route of exposure leading to enhanced toxicity. In contrast, organic food (detritus, algae) to which pyrethroids can adsorb, reduce their toxicity as was demonstrated for daphnids (Day, 1991; Barry et al., 1995) and amphipods (Smith and Lizotte, 2007). For sediment-dwellers such as chironomids, known to be very sensitive to pyrethroids, it was also shown that the toxicity depends on the water phase and not on the sediment (Conrad et al., 1999; Maund et al, 2002). Therefore, by using the EqP, the toxicity of pyrethroids such as cypermethrin is correctly described. Since the toxicity is not underestimated an additional assessment factor is not required. Since marine arthropods are not significantly more sensitive to cypermethrin than freshwater arthropods (Maltby et al., 2005; Bollmohr et al., 2007) the same AA-EQS can be used for marine sediment. 6
7 References Aldenberg T. and Jaworska J.-S. (2000). Uncertainty of the hazardous concentration and fraction affected for normal species sensitivity distributions. Ecotoxicology and Environmental Safety 46(1): Barry, M.J., Logan, D.C., Ahokas, J.T. and Holdway, D.A. (1995) Effect of algal food concentration on toxicity of two agricultural pesticides to Daphnia carinata. Ecotoxicol Environ Safety, 32: Bollmohr, S., Day, L.A. and Schulz, R. (2007) Temporal variability in particle-associated pesticide exposure in a temporarily open estuary, Western Cape, South Africa. Chemosphere 68: Conrad, A.U., Fleming, R.J. and Crane, M. (1999) Laboratory and field response of Chironomus riparius to a pyrethroid insecticide. Wat Res, 33: Crane, M., Johnson, I., Sorokin, N., Atkinson, C. and Hope, S.-J. (2007) Proposed EQS for Water Framework Directive Annex VIII substances: cypermethrin. Science Report: SC040038/SR7, Environment Agency. Day, K.E. (1991) Effects of dissolved organic carbon on accumulation and acute toxicity of fenvalerate, deltamethrin and cyhalothrin to Daphnia magna (Straus). Environ Toxicol Chem, 10: EC (2002) Guidance document on aquatic ecotoxicology. Sanco/3268/2001 rev. 4. EC (2003) TGD on risk assessment. Part II. In support of Directive 98/8/EC. Maltby, L., Blake, N., Brock, T.C.M. and van den Brink, P. (2005) Insecticide Species Sensitivity Distribution: Importance of test species selection and relevance to aquatic ecosystems. Environmental Toxicology and Chemistry 24: Maltby, L., Brock, T.C.M. and van den Brink, P. (2009) Fungicide Risk Assessment for Aquatic Ecosystems: Importance of Interspecific Variation, Toxic Mode of Action, and Exposure Regime. Environ Sci Technol, 43: Maund, S.J., Hamer, M.J., Lane, M.C.G., Farrelly, E., Rapley, J.H., Goggin, U.M. and Gentle, W.E. (2002) Partitioning, bioavailability, and toxicity of the pyrethroid insecticide cypermethrin in sediments. Environ Toxicol Chem 21 (1): Smith Jr, S. and Lizotte Jr, R.E. (2007) Influence of Selected Water Quality Characteristics on the Toxicity of λ-cyhalothrin and γ-cyhalothrin to Hyalella azteca. Bull Environ Contam Toxicol, 79: Solomon, K.R, Giddings J.M. and Maund, S.J. (2001) Probabilistic risk assessment of cotton pyrethroids: I. Distributional analysis of laboratory aquatic toxicity data. Environmental Toxicology and Chemistry 20: TGD (2010) Technical guidance for deriving environmental quality standards. Draft version 5.0 7
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