John Libbey Eurotext

Environnement, Risques & Santé


Characterisation of environmental inequality in Picardie based on the linkage of a multimedia exposure model and a geographic information system Volume 10, issue 6, Novembre-Décembre 2011


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Ineris Parc technologique Alata BP 2 60550 Verneuil-en-Halatte France, Université de technologie de Compiègne (UTC) UMR 6599 Rue du Dr-Schweitzer 60200 Compiègne France

Meeting the priorities of the French national plans for environmental health appears to require the development of tools able to link and analyse environmental quality data and health indicators. The objective of this work is to develop a Geographic Information System (GIS)-based platform combining environment and population information to map environmental inequalities and characterise vulnerable populations. The essential combination of exposure assessment and spatial data requires the linkage of several databases to describe the global source-effect chain at a fine scale. A stochastic multimedia exposure model makes it possible to assess the transfer of contaminants from the environment (air, soil, water, and food chain) to different local populations. This article presents the example of a risk assessment of metal (lead and chromium) exposure at a resolution of 1 km in the French region of Picardie. The exposure pathways considered included ingestion of soil, drinking water, and food (vegetables, meat, egg, milk, and fish). Exposure scenarios were defined for different reference groups (age groups), according to the types of food eaten and the fraction of food produced locally. The results showed that the age group of 2-6 years old was always the most vulnerable, in the sense that their relative exposure was highest. In the areas we studied, lead in drinking water was the principal determinant of the risks calculated. The final aim of this project is an integrated tool that will link sources of contaminants, environmental media, risk assessments, and health data by a GIS platform that offers a set of statistical tools to analyze the relations between geography, environment and human health.