Biomedical subjects

Frederik A M Verdonck

Publications and source records attributed to Frederik A M Verdonck.

3 recordsLinked to original sources

PubMed2005

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.

Environmental Monitoring↗

PubMed2004

Probabilistic environmental risk assessment of zinc in Dutch surface waters.

In the framework of the European Union (EU) New and Existing Chemicals Policy, a regional risk assessment for Zn according to the current technical guidance documents and a probabilistic approach, by mathematically integrating both best-fitting exposure concentrations and species-sensitivity distributions into a probabilistic risk quotient distribution using Monte Carlo analysis, was explored for The Netherlands. Zinc is an essential element, and the current probability distributions may not adequately deal with this property. The threshold Pareto distribution provided the best fit to the chronic Zn toxicity data, resulting in a predicted-no-effect concentration (PNECadd) for dissolved Zn of 34.2 microg/L, whereas use of the conventional normal distribution resulted in a PNECadd for dissolved Zn of 14.6 microg/L. The extracted exposure data resulted in a regional predicted environmental concentration (PEC) for dissolved Zn in the Dutch surface waters of 20.1 microg/L and in PECadd values for dissolved Zn of between 15.5 and 17.3 microg/L, depending on the background correction used. The conventional deterministic risk characterization identified a regional risk for Zn in the Dutch surface waters. The more comprehensive probabilistic approach used in the present study, however, identified only very limited potential risks for the Dutch region. A probabilistic median risk, that the environmental concentration is greater than the no-observed-effect concentration of a species in Dutch surface waters (0.5-0.6%), depending on the inclusion of background correction, was obtained from the best-fitting distributions. Because probabilistic approaches provide a quantifiable and improved assessment of risk and quantification of the uncertainty associated with that assessment, these techniques may be considered as a way to improve the EU risk assessment procedures for data-rich substances.

Animals↗

PubMed2003

Limitations of current risk characterization methods in probabilistic environmental risk assessment.

In probabilistic environmental risk assessment, the likelihood and the extent of adverse effects occurring in ecological systems because of exposure(s) to substances are estimated. It is based on the comparison of an exposure/environmental concentration distribution, with a species sensitivity distribution derived from toxicity data. The calculation of a probabilistic risk can be performed in many ways (e.g., area under the curve in joint probability curves). However, several (hypothetical) examples and some theoretical considerations illustrate that the current risk characterisation methods have an integrative character and they focus on the statistical comparison of two distributions without properly considering the environmental interpretation of these underlying distributions. Several scenarios with varying exposure/environmental concentration distribution and species sensitivity distribution standard deviations are discussed.

Animals↗