INERIS (French National Institute for Industrial Environment and Risks), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte, France.
Sci Total Environ. 2012 Aug 15;432:297-308. doi: 10.1016/j.scitotenv.2012.06.001. Epub 2012 Jun 28.
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.
分析环境与健康之间的关系已经成为法国公共卫生工作的重点，国家健康与环境行动计划就是证明。这些计划确定了以下两个优先事项：
确定和管理热点暴露地区，这些地区可能对人类健康造成潜在风险；
减少暴露不平等。本研究的目的是开发一个空间随机多媒体暴露模型，以检测脆弱人群，并在精细分辨率和区域尺度上分析暴露决定因素。法国国家工业环境与风险研究院（INERIS）开发了一种多媒体暴露模型，用于评估物质通过吸入和摄入途径从环境转移到人体的情况。RESPIR 项目通过将地理信息系统（GIS）与模型联系起来，增加了空间维度。该项目使用建模、空间分析和地质统计学方法开发工具，以便在 1 公里见方的规则网格上构建和离散不同来源和分辨率的有趣变量和指标。我们使用来自法国（北加莱海峡大区）的一个地区的数据，将该模型应用于金属（镉、铅和镍）暴露风险评估。考虑到的暴露途径包括大气污染物吸入和土壤、植被、肉类、蛋类、牛奶、鱼类和饮用水的摄入。针对不同的参考群体（年龄、饮食特性和本地生产的食物比例）定义了暴露场景。两个最大的风险对应于一个古老的工业场地（Metaleurop）和里尔城市群。在这些地区，镉、植被摄入和土壤污染是计算风险的主要决定因素。
