Environmental Risk Assessment of Chemical Substances
According to the OECD, it is estimated that some 70000 synthetic chemicals are in daily use. This number is still growing. Some of these products (e.g. polychlorinated biphenyls or chlorofluorocarbons) have gained great public attention due to their unexpected undesirable long-term impact on the ecosystem. The industrialized nations have therefore implemented and enforced stringent laws, in order to control the use of potentially harmful substances.
It is an almost impossible task to have the EU Base Set available for all existing substances. The EU and other organizations like OECD have therefore put together priority lists of potentially harmful high-volume chemicals which are assessed by experts. The last couple of years, a tremendous amount of work has been done to develop computer-based modeling systems to predict the environmental behavior and distribution of chemical substances.
There are models around (e.g. Mackay, USES, TGD EU, and others) to describe environmental distribution (Predicted Environmental Concentration (PEC)) of nonionic and nonpolar substances. For a first assessment, only a few physical properties (MP, BP, SOL, and possibly pKa) are needed. For ionic and/or polar substances, expert know-how is required.
For environmental toxicity (Predicted No Effect Concentration (PNEC)), however, the situation is far more complex. There are different modes of action for each trophic level (algae, crustacea, fish). Computer models with Quantitative Structure-Activity Relationship (QSAR) offer a scientifically attractive tool to predict aquatic toxicity and biodegradation. There are no models that are applicable to heterogeneous chemical classes without expert know-how. Further progress can therefore be expected.The result of an ERA for perchloroethylene with USES is presented, and the problems of the adequacy of the model parameters explained. Here too, a further improvement is addressed.
QSARs are attractive tools to design products with improved environmental compatibility at the research stage even before the first synthesis. In order to achieve such an ambitious aim, QSAR models that also include expert rules and evaluated results and their dependence on molecular structures will have to be further developed.
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