1. Air pollution modeling and exposure assessment during pregnancy in the French Longitudinal Study of Children (ELFE)
- Author
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Elsa Real, Laure Malherbe, Julien Bernard, Fabrice Dugay, Emmanuel Riviere, Emie Seyve, Damien Piga, Anne Laborie, Pierre-Yves Robic, Jonathan Virga, Jérôme Cortinovis, Marie Cheminat, Johanna Lepeule, Cécile Zaros, Agnès Hulin, Marie-Aline Charles, François Ducroz, Atmo Grand Est, Atmo Nouvelle-Aquitaine, Atmo Sud, AIRPARIF - Surveillance de la qualité de l'air en Île-de-France, Etude longitudinale française depuis l'enfance (UMS : Ined-Inserm-EFS) (ELFE), Institut national d'études démographiques (INED)-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Atmo Normandie, Air Pays de la Loire, ATMO, Institut National de l'Environnement Industriel et des Risques (INERIS), Atmo Occitanie, Institute for Advanced Biosciences / Institut pour l'Avancée des Biosciences (Grenoble) (IAB), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Civs, Gestionnaire, EFS-Institut national d'études démographiques (INED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])
- Subjects
[SDE] Environmental Sciences ,Atmospheric Science ,Longitudinal study ,010504 meteorology & atmospheric sciences ,Scale (ratio) ,Air pollution ,010501 environmental sciences ,medicine.disease_cause ,01 natural sciences ,Spearman's rank correlation coefficient ,11. Sustainability ,Statistics ,medicine ,COHORT ,0105 earth and related environmental sciences ,General Environmental Science ,Exposure assessment ,Pollutant ,Simulation modeling ,Atmospheric dispersion modeling ,EXPOSURE ASSESSMENT ,3. Good health ,AIR POLLUTION ,PREGNANCY ,13. Climate action ,[SDE]Environmental Sciences ,Environmental science ,DISPERSION MODELING - Abstract
We developed a nation-wide exposure model to NO2, PM10 and PM2.5 at a fine spatial and temporal resolution for France in order to study air pollutants exposure during pregnancy for the French Longitudinal Study of Children (ELFE). The exposure to air pollutants was estimated daily for years 2010 and 2011 by combining three simulation models at the national and regional scale (CHIMERE) and at the local urban scale (ADMS-Urban or SIRANE). The spatial resolution was 4 km for the national scale model, 3–4 km for regional models and from 10 to 200 m for urban-scale models. We developed a confidence index (from 0 to 10) based on the target plot to identify the best model to estimate exposure for a given address, year and pollutant. Air pollution exposure during pregnancy was then estimated using each modeling scale for the 17,427 women participating in the ELFE cohort. We described the exposure of the women during different time windows of pregnancy using each of the three models and using the most suitable model as estimated by the confidence index. The exposure estimates obtained from the three models were quite similar and highly correlated (spearman correlation between 0.64 and 0.96), especially for the national and regional models. For NO2 and PM10 predicted by the urban models, the minimum values were lower and the maximum values and the variability were higher, compared to the regional and national models. The averaged confidence indexes were comprised between 5.6 and 8 depending on the pollutant, year and exposure model considered. The best confidence index was observed for urban modeling (10) and the lowest for the regional modeling (0). In average during pregnancy, using the most suitable model, women were exposed to 21 μg/m3 for NO2, 16 μg/m3 for PM2.5 and 24 μg/m3 for PM10. To our knowledge, this is the first study combining three modeling tools available at different scales to estimate NO2, PM10 and PM2.5 concentrations at a fine spatial and temporal resolution over a large geographical area. The confidence index provides guidance in the choice of the exposure model. These exposure estimates will be used to investigate potential effects of air pollutants on the pregnant woman health and on health of the fetus and development of the child.
- Published
- 2019
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