(93) In order to finalise the procedure in due time, the Agency should submit its opinions on the suggested action and its impact on the basis of a draft opinion prepared by a rapporteur.(94) In order to speed up the procedure for restrictions, the Commission should prepare its draft amendment within a specific time limit of receiving the Agency's opinions.(95) The Agency should be central to ensuring that chemicals legislation and the decision-making processes and scientific basis underlying it have credibility with all stakeholders and the public. The Agency should also play a pivotal role in coordinating communication around this Regulation and in its implementation. The confidence in the Agency of the Community institutions, the Member States, the general public and interested

The target lipid model (TLM) has been previously applied to predict the aquatic toxicity of hydrocarbons and other nonionic organic chemicals and for deriving the concentrations above which 95% of species should be protected (HC5 values). Several concerns have been identified with the TLM-derived HC5 when it is applied in a substance risk assessment context. These shortcomings were addressed by expanding the acute and chronic toxicity databases to include more diverse taxonomic groups and increase the number of species. The TLM was recalibrated with these expanded databases, resulting in critical target lipid body burdens and acute-to-chronic ratios that met the required guidelines for using species sensitivity distributions in substance risk assessment. The HC5 equation was further revised to consider covarying model parameters. The calculated HC5 values derived from the revised TLM framework were validated using an independent data set for hydrocarbons comprising 106 chronic values across plants, invertebrates, and fish. Assuming a sum binomial distribution, the 95% confidence limit for a 5% failure is between 0.8 and 9.2%. Eight chronic values fell below the HC5, corresponding to an excursion of 7.5%, which falls within the expected uncertainty bounds. Thus, calculated HC5s derived from the revised TLM framework were found to be consistent with the intended protection goals. Environ Toxicol Chem 2018;37:1579-1593. © 2018 SETAC.

1. Dose-excretion studies with cypermethrin (as a 1:1 cis/trans mixture) and alphacypermethrin (one of the two disastereoisomer pairs which constitute cis cypermethrin) were carried out with, in each case, two volunteers per dose level. The studies included (a) single oral alphacypermethrin doses of 0.25 mg, 0.50 mg and 0.75 mg followed by repeated alphacypermethrin doses at the same levels, daily for five days, (b) repeated oral cypermethrin doses of 0.25 mg, 0.75 mg and 1.5 mg daily for five days, and (c) a single dermal application of 25 mg cypermethrin to the forearm. Urine was monitored for the free and conjugated 3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropanecarboxylic acid before and after dosing. 2. Metabolism and rate of excretion of a single oral dose of alphacypermethrin was similar to that of cis cypermethrin, on average, 43% of the dose was excreted as the cyclopropanecarboxylic acid in the first 24 h urine. There was no increase in urinary metabolite excretion when alphacypermethrin was administered as a repeated oral dose. Subjects excreted, on average, 49% of the dose as the cyclopropanecarboxylic acid in the subsequent 24 h periods after dosing. 3. There was no increase in the urinary cyclopropanecarboxylic acid excretion when cypermethrin was administered as a repeated oral dose. Subjects excreted, on average, 72% of the trans isomer dose and 45% of the cis isomer dose respectively in the subsequent 24 h periods after dosing. 4. Approximately 0.1% of the applied dermal dose of 25 mg cypermethrin was excreted within 72 h as the urinary cyclopropanecarboxylic acid. No conclusions can be drawn from such urinary excretion data as to the concentration of cypermethrin and its metabolites in the skin or other organs, or the possibility of other routes of metabolism or excretion.

Surfactants are a commercially important group of chemicals widely used on a global scale. Despite high removal efficiencies during wastewater treatment, their high consumption volumes mean that a certain fraction will always enter aquatic ecosystems, with marine environments being the ultimate sites of deposition. Consequently, surfactants have been detected within marine waters and sediments. However, aquatic environmental studies have mostly focused on the freshwater environment, and marine studies are considerably underrepresented by comparison. The present review aims to provide a summary of current marine environmental fate (monitoring, biodegradation, and bioconcentration) and effects data of 5 key surfactant groups: linear alkylbenzene sulfonates, alcohol ethoxysulfates, alkyl sulfates, alcohol ethoxylates, and ditallow dimethyl ammonium chloride. Monitoring data are currently limited, especially for alcohol ethoxysulfates and alkyl sulfates. Biodegradation was shown to be considerably slower under marine conditions, whereas ecotoxicity studies suggest that marine species are approximately equally as sensitive to these surfactants as freshwater species. Marine bioconcentration studies are almost nonexistent. Current gaps within the literature are presented, thereby highlighting research areas where additional marine studies should focus. Environ Toxicol Chem

PETRORISK is a modeling framework used to evaluate environmental risk of petroleum substances and human exposure through these routes due to emissions under typical use conditions as required by the European regulation for the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH). Petroleum substances are often complex substances comprised of hundreds to thousands of individual hydrocarbons. The physicochemical, fate, and effects properties of the individual constituents within a petroleum substance can vary over several orders of magnitude, complicating risk assessment. PETRORISK combines the risk assessment strategies used on single chemicals with the hydrocarbon block approach to model complex substances. Blocks are usually defined by available analytical characterization data on substances that are expressed in terms of mass fractions for different structural chemical classes that are specified as a function of C number or boiling point range. The physicochemical and degradation properties of the blocks are determined by the properties of representative constituents in that block. Emissions and predicted exposure concentrations (PEC) are then modeled using mass-weighted individual representative constituents. Overall risk for various environmental compartments at the regional and local level is evaluated by comparing the PECs for individual representative constituents to corresponding predicted no-effect concentrations (PNEC) derived using the Target Lipid Model. Risks to human health are evaluated using the overall predicted human dose resulting from multimedia environmental exposure to a substance-specific derived no-effect level (DNEL). A case study is provided to illustrate how this modeling approach has been applied to assess the risks of kerosene manufacture and use as a fuel.

1. An analytical method for monitoring human exposure to cypermethrin has been developed, based on the detection of the free and conjugated forms of the urinary metabolite, the cyclopropanecarboxylic acid. 2. Four male subjects were given a single oral dose, ranging from 0.25 mg to 1.5 mg, of a 1:1 cis/trans mixture of cypermethrin, and urine was monitored for the free and conjugated cyclopropanecarboxylic acid. Urinary excretion of the individual metabolites (cis and trans isomers) was similar for the different dosages. Subjects excreted, on average, 78% of the trans isomer dose, and 49% of the cis isomer dose respectively in 24 h. 3. Thus, as in other mammals, ester cleavage and elimination of the cis and trans cyclopropanecarboxylic acid moieties in the free and conjugated form is a major route of metabolism of cypermethrin in man.

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Background: Surfactants are widely used across the globe both in industrial and consumer products. The n-octanol/ water partition ratio or coefficient (log K ow) and n-octanol/water distribution coefficient (log D) are key parameters in environmental risk assessment of chemicals as they are often used to estimate the environmental fate and bioavailability and thus exposure and toxicity of a compound. Determining log K ow data for surfactants is a technical challenge due to their amphiphilic properties. Currently several existing experimental OECD methods (e.g. slow-stirring, HPLC, solubility ratio) and QSPR models are available for log K ow /D measurement or prediction. However, there are concerns that these methods have not been fully validated for surfactants and may not be applicable due to the specific phase behaviour of surfactants. Results: The current methods were evaluated for the four surfactant classes (non-ionic, anionic, cationic and amphoteric). The solubility ratio approach, based on comparative n-octanol and water solubility measurements, did not generate robust or accurate data. The HPLC method generates consistently higher log K ow values than the slowstirring method for non-ionics, but this positive bias could be removed using reference surfactants with log K ow values determined using the slow-stirring method. The slow-stirring method is the most widely applicable experimental method for generating log K ow /D data for all the surface-active test compounds. Generally, QSPR-predicted log K ow /D values do not correlate well with experimental values, apart for the group of non-ionic surfactants. Relatively, large differences in predicted log K ow /D values were observed when comparing various QSPR models, which were most noticeable for the ionised surfactants. Conclusions: The slow-stirring method is the most widely applicable experimental method for generating log K ow /D data for all the four surfactant classes. A weight of evidence approach is considered appropriate for non-ionic surfactants using experimental and model predications. However, it is more difficult to apply this approach to ionisable surfactants. Recommendations are made for the preferred existing QSPR predictive methods for determination of log K ow /D values for the surfactant classes. Investigation of newer alternative experimental log K ow methods as well