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Modélisation toxico-cinétique de la bioaccumulation de composés organiques persistants par des invertébrés benthiques d’eau douce

Abstract : The presence of chemicals in the aquatic environment raises the question of their toxicity to organisms. In environmental risk assessment, the effects of a contamination on organisms are evaluated in two steps. Firstly, the toxicokinetics (TK) of the compound of interest are studied, that is to establish the link between the exposure concentration and the bioaccumulated concentration by the organism. Secondly, a toxicodynamic (TD) study is carried out to establish the link between the concentration of the contaminant bioaccumulated in the body and its toxicity. Bioaccumulation is a variable phenomenon, which depends on the physico-chemical properties of chemicals, the species considered and the environmental conditions. Mathematical tools, such as TK models, have been developed to explain this variability and seem to overcome this difficulty. Nevertheless, implementing such models entailed to unlock several limitations, such as estimating biotransformation rates and metabolites’ fate. Another current limitation of TK models lies in the assessment of uncertainty related to TK parameters. This thesis has developed a generic model and inference framework for describing and simulating the bioaccumulation of persistent chemicals (hexachlorobiphenyl, hexabromocyclododecane, pentabromodiphenyl-ether, pyrene) by various freshwater benthic invertebrate species (an insect, Chironomus riparius, an amphipod, Gammarus fossarum, and a gastropod mollusk, Radix auricularia). This thesis was based on a series of laboratory experiments, which provided bioaccumulation data suitable for model calibration, as well as for testing various hypotheses on exposure pathways. Model TK parameters are estimated through Bayesian inference, which simultaneously estimates all the parameters from all the available data, in order to obtain precisely the uncertainty around their value and the predictions of the model. Each hypothesis tested on the basis of experimental data corresponds to a model, allowing then to compare the performance. These models provided an accurate estimate of the model parameters and their uncertainty. Overall, these models fit well the experimental data, except for HBCD. A biotransformation function was also successfully implemented on the basis of data from the literature (phytopharmaceuticals, drugs, PAH). In that case, Bayesian inference applied to the generic model yielded reduced uncertainty around the biotransformation rate compared to the original models which used classical inference. This generic modelling and inference framework can be adapted to various species-contaminant pairs, and appears as an effective tool for describing contaminant kinetics, as well as for assessing the uncertainty related to model parameter estimation, or for predictions
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Aude Ratier. Modélisation toxico-cinétique de la bioaccumulation de composés organiques persistants par des invertébrés benthiques d’eau douce. Ecologie, Environnement. Université de Lyon, 2019. Français. ⟨NNT : 2019LYSE1326⟩. ⟨tel-02612792⟩

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