Eye hazard classification according to UN GHS / EU CLP and the severity of eye symptoms caused by accidental exposures to detergents and cleaning products.

The use of lower cut-off values/concentration limits for the calculation of mixture classification in UN GHS/EU CLP versus the previous regulatory scheme (EU Dangerous Preparations Directive, DPD), has resulted in an increased number of classifications in the highest eye hazard category. Herein, a semi-quantitative categorisation of severity of eye effects, following accidental human exposures to detergents, was compared to the classification category of the products. Three schemes were evaluated: EU DPD; EU CLP (based on all available data and information, including weight of evidence); and EU CLP (based entirely on the calculation method). As reported by four EU Poison Centres, the vast majority of exposures had caused minor or no symptoms. Classification was a poor predictor of effects in man subjected to accidental exposure. Note however that this is also because effects are not only driven by the intrinsic hazard (as reflected in the classification), but also by the exposure conditions and mitigation (i.e. rinsing). EU CLP classification using all available data and information was more predictive of medically relevant symptoms than the EU CLP calculation method. The latter led to a poorer differentiation between irritating products versus products potentially causing serious eye damage.

Mode of action and aquatic exposure thresholds of no concern.

Threshold concepts of toxicological concern are based on the possibility of establishing an exposure threshold value for chemicals below which no significant risk is to be expected. The objective of the present study is to address environmental thresholds of no toxicological concern for freshwater systems (ETNCaq) for organic chemicals. We analyzed environmental toxicological databases (acute and chronic endpoints) and substance hazard assessments. Lowest numbers and 95th-percentile values were derived using data stratification based on mode of action (MOA; 1 = inert chemicals; 2 = less inert chemicals; 3 = reactive chemicals; 4 = specifically acting chemicals). The ETNCaq values were derived by multiplying the lowest 95th percentile values with appropriate application factors; ETNCaq,MOA1-3 is approximately 0.1 microg/L. A preliminary analysis with complete MOA stratification of the databases shows that in the case of MOA1 or MOA2, the ETNCaq value could be even higher than 0.1 microg/L. A significantly lower ETNCaq,MOA4 value was observed based on the long-term toxicity information in the European Centre for the Ecotoxicology and Toxicology of Chemicals database. Application of the ETNCaq value in a tiered risk-assessment scheme may help chemical producers to set data-generation priorities and to refine or reduce animal use. It also may help to inform downstream users concerning the relative risk associated with their specific uses and be of value in putting environmental monitoring data into a risk-assessment perspective.

A rule-based screening environmental risk assessment tool derived from EUSES.

Within the context and scope of the forthcoming European Union chemical regulations (REACH), there is a need to be able to prioritise the chemicals for evaluation. Therefore, a simple, pragmatic and adequately conservative approach for the identification of substances of very low or no immediate concern at an early stage is presented. The fundamental principles and basic concepts are derived from the EU Technical Guidance Document and EUSES, and are translated into an easy-to-use rule-based system. For this development, the effect on risk characterisation ratios (RCRs) of the key environmental parameters in EUSES was quantified (taking into account several standardised chemical release scenarios). Using statistical analysis, ranges were identified for each key parameter, within which the end result of the assessment was not significantly affected. This information was then translated into a lookup table from which environmental risk characterisation ratios can be directly read as a function of a few parameters.