Spatio-temporal assessment of pregnant women exposure to chlorpyrifos at a regional scale

Autor: Frédéric Tognet, Laure Malherbe, Céline Brochot, Laurent Létinois, François Lestremau, Roseline Bonnard, Mohammed Guedda, Julien Caudeville, Véronique Bach, Karen Chardon, Florence Anna Zeman, Corentin Regrain, Emmanuelle Boulvert, Fabrice Marliere
Přispěvatelé: Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire Amiénois de Mathématique Fondamentale et Appliquée - UMR CNRS 7352 (LAMFA), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), Périnatalité et Risques Toxiques - UMR INERIS_I 1 (PERITOX), Université de Picardie Jules Verne (UPJV)-CHU Amiens-Picardie-Institut National de l'Environnement Industriel et des Risques
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Journal of Exposure Science and Environmental Epidemiology
Journal of Exposure Science and Environmental Epidemiology, Nature Publishing Group, In press, ⟨10.1038/s41370-021-00315-7⟩
ISSN: 1559-0631
1559-064X
DOI: 10.1038/s41370-021-00315-7⟩
Popis: BACKGROUND The aim of this study was to use an integrated exposure assessment approach, combining spatiotemporal modeling of environmental exposure and fate of the chemical to assess the exposure of vulnerable populations. In this study, chlorpyrifos exposure of pregnant women in Picardy was evaluated at a regional scale during 1 year. This approach provided a mapping of exposure indicators of pregnant women to chlorpyrifos over fine spatial and temporal resolutions using a GIS environment. METHODS Fate and transport models (emission, atmospheric dispersion, multimedia exposure, PBPK) were combined with environmental databases in a GIS environment. Quantities spread over agricultural fields were simulated and integrated into a modeling chain coupling models. The fate and transport of chlorpyrifos was characterized by an atmospheric dispersion statistical metamodel and the dynamiCROP model. Then, the multimedia model Modul'ERS was used to predict chlorpyrifos daily exposure doses which were integrated in a PBPK model to compute biomarker of exposure (TCPy urinary concentrations). For the concentration predictions, two scenarios (lower bound and upper bound) were built. RESULTS At fine spatio-temporal resolutions, the cartography of biomarkers in the lower bound scenario clearly highlights agricultural areas. In these maps, some specific areas and hotspots appear as potentially more exposed specifically during application period. Overall, predictions were close to biomonitoring data and ingestion route was the main contributor to chlorpyrifos exposure. CONCLUSIONS This study demonstrated the feasibility of an integrated approach for the evaluation of chlorpyrifos exposure which allows the comparison between modeled predictions and biomonitoring data.
Databáze: OpenAIRE