Long-term dietary exposure to lead in young European children: comparing a pan-European approach with a national exposure assessment

Long-term dietary exposures to lead in young children were calculated by combining food consumption data of 11 European countries categorised using harmonised broad food categories with occurrence data on lead from different Member States (pan-European approach). The results of the assessment in children living in the Netherlands were compared with a long-term lead intake assessment in the same group using Dutch lead concentration data and linking the consumption and concentration data at the highest possible level of detail. Exposures obtained with the pan-European approach were higher than the national exposure calculations. For both assessments cereals contributed most to the exposure. The lower dietary exposure in the national study was due to the use of lower lead concentrations and...

Reconstruction of spatiotemporal capture data by means of orthogonal functions: the case of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic

[EN] The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) on captures of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic has a number of limitations, such as gaps in the statistics for certain fleets and the level of spatiotemporal detail at which catches are reported. As a result, the quality of these data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatiotemporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction, applied here for the first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions decomposition performed with a Lanczos method. DINEOF was tested with different amounts of missing data, intentionally removing values from 3.4% to 95.2% of data loss, and then compared with the same data set with no missing data. These validation analyses show that DINEOF is a reliable methodological approach of data reconstruction for the purposes of fishery management advice, even when the amount of missing data is very high.