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将淡水 Fate 模型与 PBPK 模型相连接,以评估与饮用水相关的 B(a)P 人体内部剂量。

Linking fate model in freshwater and PBPK model to assess human internal dosimetry of B(a)P associated with drinking water.

机构信息

EDF, Division Recherche et Développement, Département Laboratoire National d'Hydraulique et Environnement, 6 quai Watier, 78401, Chatou, France.

出版信息

Environ Geochem Health. 2011 Aug;33(4):371-87. doi: 10.1007/s10653-011-9382-6. Epub 2011 Apr 2.

Abstract

In the present study, we demonstrate an integrated modeling approach for predicting internal tissue concentrations of chemicals by coupling a multimedia environmental model and a generic physiologically based pharmacokinetic (PBPK) model. A case study was designed for a region situated on the Seine river watershed, downstream of the Paris megacity, and for benzo(a)pyrene emitted from industrial zones in the region. In this case study, these two models are linked only by water intake from riverine system for the multimedia model into human body for the PBPK model. The limited monitoring data sets of B(a)P concentrations in bottom sediment and in raw river water, obtained at the downstream of Paris, were used to re-construct long-term daily concentrations of B(a)P in river water. The re-construction of long-term series of B(a)P level played a key role for the intermediate model calibration (conducted in multimedia model) and thus for improving model input to PBPK model. In order to take into account the parametric uncertainty in the model inputs, some input parameters relevant for the multimedia model were given by probability density functions (PDFs); some generic PDFs were updated with site-specific measurements by a Bayesian approach. The results of this study showed that the multimedia model fits well with actual annual measurements in sediments over one decade. No accumulation of B(a)P in the organs was observed. In conclusion, this case study demonstrated the feasibility of a full-chain assessment combining multimedia environmental predictions and PBPK modeling, including uncertainty and sensitivity analyses.

摘要

在本研究中,我们通过耦合多介质环境模型和通用生理药代动力学(PBPK)模型,展示了一种用于预测化学物质内部组织浓度的综合建模方法。设计了一个案例研究,针对位于塞纳河流域下游的巴黎大都市地区,以及该地区工业区域排放的苯并[a]芘(B(a)P)。在这个案例研究中,这两个模型仅通过多介质模型中的河流系统摄入水和 PBPK 模型中的人体摄入水进行连接。在巴黎下游获得的苯并[a]芘(B(a)P)在底泥和原河水中的有限监测数据集被用于重建河水中 B(a)P 的长期日浓度。B(a)P 水平的长期序列重建对中间模型校准(在多介质模型中进行)起到了关键作用,从而改善了对 PBPK 模型的模型输入。为了考虑模型输入中的参数不确定性,一些与多介质模型相关的输入参数通过概率密度函数(PDF)给出;一些通用 PDF 通过贝叶斯方法使用特定于地点的测量值进行了更新。这项研究的结果表明,多介质模型很好地拟合了过去十年中沉积物中的实际年度测量结果。未观察到 B(a)P 在器官中的积累。总之,这个案例研究展示了结合多介质环境预测和 PBPK 建模进行全链评估的可行性,包括不确定性和敏感性分析。

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