IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i12p2680-d186185.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/12/2680/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/12/2680/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Young Hwan Choi & Donghwi Jung, 2020. "Development of Cross-Domain Artificial Neural Network to Predict High-Temporal Resolution Pressure Data," Sustainability, MDPI, vol. 12(9), pages 1-17, May.
    2. Paul Poast, 2013. "Issue linkage and international cooperation: An empirical investigation," Conflict Management and Peace Science, Peace Science Society (International), vol. 30(3), pages 286-303, July.
    3. Dang, Hai-Anh & Carletto, Calogero & Gourlay, Sydney & Abanokova, Kseniya, 2024. "Addressing Soil Quality Data Gaps with Imputation: Evidence from Ethiopia and Uganda," GLO Discussion Paper Series 1445, Global Labor Organization (GLO).
    4. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    5. Meyer, Maximilian & Hulke, Carolin & Kamwi, Jonathan & Kolem, Hannah & Börner, Jan, 2022. "Spatially heterogeneous effects of collective action on environmental dependence in Namibia’s Zambezi region," World Development, Elsevier, vol. 159(C).
    6. Sabastine Ugbemuna Ugbaje & Thomas F.A. Bishop, 2020. "Hydrological Control of Vegetation Greenness Dynamics in Africa: A Multivariate Analysis Using Satellite Observed Soil Moisture, Terrestrial Water Storage and Precipitation," Land, MDPI, vol. 9(1), pages 1-15, January.
    7. Shige Song, 2013. "Prenatal malnutrition and subsequent foetal loss risk: Evidence from the 1959-1961 Chinese famine," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(26), pages 707-728.
    8. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2022. "Robust Dynamic Space-Time Panel Data Models Using ε-contamination: An Application to Crop Yields and Climate Change," Center for Policy Research Working Papers 254, Center for Policy Research, Maxwell School, Syracuse University.
    9. Joachim Eisenberg & Fabrice A. Muvundja, 2020. "Quantification of Erosion in Selected Catchment Areas of the Ruzizi River (DRC) Using the (R)USLE Model," Land, MDPI, vol. 9(4), pages 1-18, April.
    10. Lara Lopez & Fernando L. Vázquez & Ángela J. Torres & Patricia Otero & Vanessa Blanco & Olga Díaz & Mario Páramo, 2020. "Long-Term Effects of a Cognitive Behavioral Conference Call Intervention on Depression in Non-Professional Caregivers," IJERPH, MDPI, vol. 17(22), pages 1-24, November.
    11. Kobayashi, Yoshiharu & Heinrich, Tobias & Bryant, Kristin A., 2021. "Public support for development aid during the COVID-19 pandemic," World Development, Elsevier, vol. 138(C).
    12. Chantal M. J. Hendriks & Harry S. Gibson & Anna Trett & André Python & Daniel J. Weiss & Anton Vrieling & Michael Coleman & Peter W. Gething & Penny A. Hancock & Catherine L. Moyes, 2019. "Mapping Geospatial Processes Affecting the Environmental Fate of Agricultural Pesticides in Africa," IJERPH, MDPI, vol. 16(19), pages 1-22, September.
    13. Carlos Manuel Hernández & Aliou Faye & Mamadou Ousseynou Ly & Zachary P. Stewart & P. V. Vara Prasad & Leonardo Mendes Bastos & Luciana Nieto & Ana J. P. Carcedo & Ignacio Antonio Ciampitti, 2021. "Soil and Climate Characterization to Define Environments for Summer Crops in Senegal," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    14. Ravic Nijbroek & Kristin Piikki & Mats Söderström & Bas Kempen & Katrine G. Turner & Simeon Hengari & John Mutua, 2018. "Soil Organic Carbon Baselines for Land Degradation Neutrality: Map Accuracy and Cost Tradeoffs with Respect to Complexity in Otjozondjupa, Namibia," Sustainability, MDPI, vol. 10(5), pages 1-20, May.
    15. Leroux, L. & Falconnier, G.N. & Diouf, A.A. & Ndao, B. & Gbodjo, J.E. & Tall, L. & Balde, A.A. & Clermont-Dauphin, C. & Bégué, A. & Affholder, F. & Roupsard, O., 2020. "Using remote sensing to assess the effect of trees on millet yield in complex parklands of Central Senegal," Agricultural Systems, Elsevier, vol. 184(C).
    16. Rogna, Marco, 2023. "The Effects of Rising Prices on Corn Production in Western African Countries," 97th Annual Conference, March 27-29, 2023, Warwick University, Coventry, UK 334549, Agricultural Economics Society - AES.
    17. Berazneva, Julia & McBride, Linden & Sheahan, Megan & Guerena, David, 2016. "Perceived, measured, and estimated soil fertility in east Africa: Implications for farmers and researchers," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235466, Agricultural and Applied Economics Association.
    18. Rufino, Marta M. & Albouy, Camille & Brind'Amour, Anik, 2021. "Which spatial interpolators I should use? A case study applying to marine species," Ecological Modelling, Elsevier, vol. 449(C).
    19. Jean Baptiste Nsengiyumva & Geping Luo & Egide Hakorimana & Richard Mind'je & Aboubakar Gasirabo & Valentine Mukanyandwi, 2019. "Comparative Analysis of Deterministic and Semiquantitative Approaches for Shallow Landslide Risk Modeling in Rwanda," Risk Analysis, John Wiley & Sons, vol. 39(11), pages 2576-2595, November.
    20. Matilde Jeppesen, 2021. "What we hoped for and what we achieved: Tax performance of Semi‐Autonomous Revenue Authorities in sub‐Saharan Africa," Public Administration & Development, Blackwell Publishing, vol. 41(3), pages 115-127, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:12:p:2680-:d:186185. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.