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Updated: May 20, 2026

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
Published on: November 11, 2020
Development of a spatial stochastic multimedia exposure model to assess population exposure at a regional scale
Julien Caudeville1, Roseline Bonnard, Céline Boudet
1INERIS (French National Institute for Industrial Environment and Risks), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte, France. Julien.CAUDEVILLE@ineris.fr
Abstract:
Analyzing the relationship between the environment and health has become a major focus of public health efforts in France, as evidenced by the national action plans for health and the environment. These plans have identified the following two priorities: - identify and manage geographic areas where hotspot exposures are a potential risk to human health; and - reduce exposure inequalities. The aim of this study is to develop a spatial stochastic multimedia exposure model for detecting vulnerable populations and analyzing exposure determinants at a fine resolution and regional scale. A multimedia exposure model was developed by INERIS to assess the transfer of substances from the environment to humans through inhalation and ingestion pathways. The RESPIR project adds a spatial dimension by linking GIS (Geographic Information System) to the model. Tools are developed using modeling, spatial analysis and geostatistic methods to build and discretize interesting variables and indicators from different supports and resolutions on a 1-km(2) regular grid. We applied this model to the risk assessment of exposure to metals (cadmium, lead and nickel) using data from a region in France (Nord-Pas-de-Calais). The considered exposure pathways include the atmospheric contaminant inhalation and ingestion of soil, vegetation, meat, egg, milk, fish and drinking water. Exposure scenarios are defined for different reference groups (age, dietary properties, and the fraction of food produced locally). The two largest risks correspond to an ancient industrial site (Metaleurop) and the Lille agglomeration. In these areas, cadmium, vegetation ingestion and soil contamination are the principal determinants of the computed risk.
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