Curing of UV prints - Assessment of possible toxicological hazard for consumers.

In an experimental setting a laboratory analysis of substances migrating from UV prints under mechanical stress into sweat and saliva simulant was performed. The influence of paper type and curing degree on UV prints was investigated. Five substances were identified at concentrations above the limit of detection in the simulants PPG-3 glyceryl triacrylate, ethoxylated trimethylolpropane triacrylate, trimethylolpropane triacrylate, 2/4-isopropylthioxanthone (ITX), and 2,4-diethylthioxanthone (DETX). Migration of the acrylates and photoinitiators into saliva and sweat simulants were increased when the UV inks were printed on uncoated paper in comparison to coated paper. With an exposure scenario considering a person to leaf through 80 pages of UV-printed paper per day while touching each page with a licked fingertip, Risk Characterisation Ratios (RCR) for oral exposure well below 1 were obtained for all five substances indicating no risk for the general population. The three acrylates are classified for skin sensitisation. The migrated amounts per skin surface area of these three were compared with the EC3 value for a hypothetical substance that could be categorised as strong sensitiser (EC3 = 0.1%). The results show that the risk of skin sensitisation even under worst case conditions can be considered as negligible.

Analysis of risk assessment and risk management processes in the derivation of maximum levels for environmental contaminants in food.

Environmental contaminants originate from diverse sources and, owing to their ubiquitous presence in the environment, may appear in foods. Setting standards in food is increasingly important within the European Union and world-wide to protect consumers' health and to avoid trade barriers. This paper analyses how maximum levels for environmental contaminants in food were derived by the Codex Alimentarius Commission, by the European Union and by national authorities (USA, Germany). Both the risk assessment process (derivation of tolerable intake values and intake assessment by scientific bodies) and the risk management process (derivation of maximum levels by risk management bodies) are discussed. The various organizations show similar approaches and similar numerical values for maximum levels of the same contaminants in the same food items. In the area of decision-making for risk management, there was a noticeable lack of transparency in all the investigated systems. Recommendations are made for the development and harmonization of exposure assessment and communications between risk assessment and risk management processes, for improvements in documentation and for greater transparency within risk management decision-making processes.

Uncertainty in toxicological risk assessment for non-carcinogenic health effects.

Uncertainty in risk assessment results from the lack of knowledge on toxicity to the target population for a substance. Currently used deterministic risk assessment methods yield human limit values or margins of safety (MOS) without quantitative measurements of uncertainty. Qualitative and quantitative uncertainty analysis would enable risk managers to better judge the consequences of different management options. This article discusses sources of uncertainty and possibilities for quantification of uncertainty associated with different steps in the risk assessment of non-carcinogenic health effects. Knowledge gaps causing uncertainty in risk assessment are overcome by extrapolation. Distribution functions for extrapolation factors are based on empirical data and provide information about the extent of uncertainty introduced by these factors. Whereas deterministic methods can account only qualitatively for uncertainty of the resulting human limit value, probabilistic risk assessment methods are able to quantify several aspects of uncertainty. However, there is only limited experience with these methods in practice. Their acceptance and future application will depend on the establishment of evidence based distribution functions, flexibility and practicability of the methods, and the unambiguity of the results.