Author: lcoffice

This overview paper describes a study conducted for the Belgian Federal Public Service of Health, Food Chain Safety and Environment during 2006–2007. Home-produced eggs from Belgian private owners of hens were included in a large study aiming to determine concentration levels of various environmental contaminants. By means of the analyses of soil samples and of kitchen waste samples, obtained from the same locations, an investigation towards the possible sources of contaminants was possible. Eggs, soils, faeces and kitchen waste samples were checked for the presence of dioxins, PCBs (including dioxin-like PCBs), organochlorine pesticides, trace elements, PAHs, brominated flame retardants and mycotoxins. The study design, sampling methodology and primary conclusions of the study are given. It was found that in some cases dioxin-like compounds were present at levels that are of concern for the health of the egg consumers. Therefore, measures to limit their contamination in eggs, produced by hens of private owners, were proposed and deserve further attention.

This paper investigates the estimation behavior of six increasingly complex ¹⁵N models, for estimating flux rates between phytoplankton and dissolved N pools in aquatic ecosystems. The development of these models over the last 40 years reflects increasing realism in the pools and fluxes that constitute the N cycle. The purpose of this paper is to assess how the model results are influenced by the underlying assumptions. For example, with respect to uptake of ¹⁵N by phytoplankton, is anything gained by assuming that regenerated N becomes isotopically enriched after the introduction of the ¹⁵N label, or is it just as accurate to assume that no source other than the initial ¹⁵N label contributes to the enrichment signal in phytoplankton? To conduct an objective assessment of the models, we compared them to (1) a set of reference values generated numerically by a process oriented model, and (2) real experimental data. The results show that for a number of ¹⁵N models, properties such as accuracy and precision cannot both be optimized under the same conditions, and a compromise must be struck. Oversimplified models risk bias when their underlying assumptions are violated, but overly complex models can misinterpret part of the random noise as relevant processes. Therefore, none of the ¹⁵N model solutions can a priori be rejected, but each should carefully be assessed with hypothesis testing. A backward regression strategy based on a statistical interpretation of the cost function (sum of the weighted least squares residuals) was used to select optimal solution subsets corresponding to a given data set.