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Characterization of Environmental Health Inequalities Due to Polyaromatic Hydrocarbon Exposure in France

Author

Listed:
  • Despoina Ioannidou

    (National Institute for industrial Environment and Risks (INERIS), Verneuil-en-Halatte 60550, France
    National Conservatory of Arts and Crafts (CNAM), Paris 75003, France)

  • Laure Malherbe

    (National Institute for industrial Environment and Risks (INERIS), Verneuil-en-Halatte 60550, France)

  • Maxime Beauchamp

    (National Institute for industrial Environment and Risks (INERIS), Verneuil-en-Halatte 60550, France)

  • Nicolas P.A. Saby

    (National Institute of Agronomic Research (INRA), US 1106, Orleans 45000, France)

  • Roseline Bonnard

    (National Institute for industrial Environment and Risks (INERIS), Verneuil-en-Halatte 60550, France)

  • Julien Caudeville

    (National Institute for industrial Environment and Risks (INERIS), Verneuil-en-Halatte 60550, France)

Abstract

Reducing environmental health inequalities has become a major focus of public health efforts in France, as evidenced by the French action plans for health and the environment. To evaluate environmental inequalities, routine monitoring networks provide a valuable source of data on environmental contamination, which can be used in integrated assessments, to identify overexposed populations and prioritize actions. However, available databases generally do not meet sufficient spatial representativeness to characterize population exposure, as they are usually not assembled for this specific purpose. The aim of this study was to develop geoprocessing procedures and statistical methods to build spatial environmental variables (water, air, soil, and food pollutant concentrations) at a fine resolution, and provide appropriate input for the exposure modelling. Those methods were designed to combine in situ monitoring data with correlated auxiliary information (for example, atmospheric emissions, population, and altitude), in order to better represent the variability of the environmental compartment quality. The MODUL’ERS multimedia exposure model developed by INERIS (French Institute for industrial Environment and Risks) was then used to assess the transfer of substances from the environment to humans, through inhalation and ingestion pathway characterization. We applied the methodology to a carcinogenic Polycyclic Aromatic Hydrocarbon substance, benzo[a]pyrene(B[a]P), to map spatialized exposure indicators, at the national scale. The largest environmental contribution corresponded to the ingestion pathway. Data processing algorithms and calculation of exposure will be integrated into the French coordinated integrated environment and health platform PLAINE (PLteforme intégrée d’Analyse des INégalités Environnementales) which has been developed to map and analyze environmental health inequalities.

Suggested Citation

  • Despoina Ioannidou & Laure Malherbe & Maxime Beauchamp & Nicolas P.A. Saby & Roseline Bonnard & Julien Caudeville, 2018. "Characterization of Environmental Health Inequalities Due to Polyaromatic Hydrocarbon Exposure in France," IJERPH, MDPI, vol. 15(12), pages 1-20, November.
  • Handle: RePEc:gam:jijerp:v:15:y:2018:i:12:p:2680-:d:186185
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    References listed on IDEAS

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    1. James Honaker & Gary King, 2010. "What to Do about Missing Values in Time‐Series Cross‐Section Data," American Journal of Political Science, John Wiley & Sons, vol. 54(2), pages 561-581, April.
    2. Haiying Chen & Sara A. Quandt & Joseph G. Grzywacz & Thomas A. Arcury, 2013. "A Bayesian multiple imputation method for handling longitudinal pesticide data with values below the limit of detection," Environmetrics, John Wiley & Sons, Ltd., vol. 24(2), pages 132-142, March.
    3. Göran Bengtsson & Niklas Törneman, 2009. "A Spatial Approach to Environmental Risk Assessment of PAH Contamination," Risk Analysis, John Wiley & Sons, vol. 29(1), pages 48-61, January.
    4. Tomislav Hengl & Gerard B M Heuvelink & Bas Kempen & Johan G B Leenaars & Markus G Walsh & Keith D Shepherd & Andrew Sila & Robert A MacMillan & Jorge Mendes de Jesus & Lulseged Tamene & Jérôme E Tond, 2015. "Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-26, June.
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