Controlling persistent organic pollutants: what next?

Within the context of current international initiatives on the control of persistent organic pollutants (POPs), an overview is given of the scientific knowledge relating to POP sources, emissions, transport, fate and effects. At the regional scale, improvements in mass balance models for well-characterised POPs are resulting in an ability to estimate their environmental concentrations with sufficient accuracy to be of help for some regulatory purposes. The relevance of the parameters used to define POPs within these international initiatives is considered with an emphasis on mechanisms for adding new substances to the initial lists. A tiered approach is proposed for screening the large number of untested chemical substances according to their long-range transport potential, persistence and bioaccumulative potential prior to more detailed risk assessments. The importance of testing candidate POPs for chronic toxicity (i.e. for immunotoxicity, endocrine disruption and carcinogenicity) is emphasised as is a need for the further development of relevant SAR (structure activity relationship) models and in vitro and in vivo tests for these effects. Where there is a high level of uncertainty at the risk assessment stage, decision-makers may have to rely on expert judgement and weight-of-evidence, taking into account the precautionary principle and the views of relevant stake-holders. Close co-operation between the various international initiatives on POPs will be required to ensure that assessment criteria and procedures are as compatible as possible

Quantifying uncertainty in critical loads: (A) literature review

Critical loads are the basis for policies controlling emissions of acidic substances in Europe. The implementation of these policies involves large expenditures, and it is reasonable for policymakers to ask what degree of certainty can be attached to the underlying critical load and exceedance estimates. This paper is a literature review of studies which attempt to estimate the uncertainty attached to critical loads. Critical load models and uncertainty analysis are briefly outlined. Most studies have used Monte Carlo analysis of some form to investigate the propagation of uncertainties in the definition of the input parameters through to uncertainties in critical loads. Though the input parameters are often poorly known, the critical load uncertainties are typically surprisingly small because of a "compensation of errors" mechanism. These results depend on the quality of the uncertainty estimates of the input parameters, and a "pedigree" classification for these is proposed. Sensitivity analysis shows that some input parameters are more important in influencing critical load uncertainty than others, but there have not been enough studies to form a general picture. Methods used for dealing with spatial variation are briefly discussed. Application of alternative models to the same site or modifications of existing models can lead to widely differing critical loads, indicating that research into the underlying science needs to continue