Search

Your search keyword '"Atmo Grand Est"' showing total 26 results
Start Over Author "Atmo Grand Est"
26 results on '"Atmo Grand Est"'

1. Nine-year trends of PM10 sources and oxidative potential in a rural background site in France

Author

Lucille Joanna Borlaza, Samuël Weber, Anouk Marsal, Gaëlle Uzu, Véronique Jacob, Jean-Luc Besombes, Mélodie Chatain, Sébastien Conil, Jean-Luc Jaffrezo, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Environnements, Dynamiques et Territoires de Montagne (EDYTEM), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Atmo Grand Est, Agence nationale pour le gestion des déchets radioactifs (ANDRA), and Agence nationale pour le gestion des déchets radioactifs - ANDRA

Subjects
Atmospheric Science, [SDE]Environmental Sciences
Abstract

Long-term monitoring at sites with relatively low particulate pollution could provide an opportunity to identify changes in pollutant concentration and potential effects of current air quality policies. In this study, 9-year sampling of PM10 (particles with an aerodynamic diameter below 10 µm) was performed in a rural background site in France (Observatoire Pérenne de l'Environnement or OPE) from 28 February 2012 to 22 December 2020. The positive matrix factorization (PMF) method was used to apportion sources of PM10 based on quantified chemical constituents and specific chemical tracers analysed on collected filters. Oxidative potential (OP), an emerging health metric that measures PM capability to potentially cause anti-oxidant imbalance in the lung, was also measured using two acellular assays: dithiothreitol (DTT) and ascorbic acid (AA). The sources of OP were also estimated using multiple linear regression (MLR) analysis. In terms of mass contribution, the dominant sources are secondary aerosols (nitrate- and sulfate-rich) associated with long-range transport (LRT). However, in terms of OP contributions, the main drivers are traffic, mineral dust, and biomass burning factors. There is also some OP contribution apportioned to the sulfate- and nitrate-rich sources influenced by processes and ageing during LRT that could have encouraged mixing with other anthropogenic sources. The study indicates much lower OP values than in urban areas. A substantial decrease (58 % reduction from the year 2012 to 2020) in the mass contributions from the traffic factor was found, even though this is not clearly reflected in its OP contribution. Nevertheless, the findings in this long-term study at the OPE site could indicate effectiveness of implemented emission control policies, as also seen in other long-term studies conducted in Europe, mainly for urban areas.

Published
2022
Full Text
View/download PDF

2. Arabitol, mannitol, and glucose as tracers of primary biogenic organic aerosol: the influence of environmental factors on ambient air concentrations and spatial distribution over France

Author

A. Samaké, J.-L. Jaffrezo, O. Favez, S. Weber, V. Jacob, T. Canete, A. Albinet, A. Charron, V. Riffault, E. Perdrix, A. Waked, B. Golly, D. Salameh, F. Chevrier, D. M. Oliveira, J.-L. Besombes, J. M. F. Martins, N. Bonnaire, S. Conil, G. Guillaud, B. Mesbah, B. Rocq, P.-Y. Robic, A. Hulin, S. Le Meur, M. Descheemaecker, E. Chretien, N. Marchand, G. Uzu, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Institut National de l'Environnement Industriel et des Risques (INERIS), Département S.A.G.E (SAGE), École des Mines de Douai (Mines Douai EMD), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Agence Nationale pour la Gestion des Déchets Radioactifs (ANDRA), Atmo Rhone-Alpes, Atmo-Sud, GeographR, ATMO Hauts de France [Lille], Atmo Occitanie, Atmo Nouvelle-Aquitaine, Atmo Normandie, Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Atmo Grand Est, Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre for Energy and Environment (CERI EE - IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Chimie Atmosphérique Expérimentale (CAE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre for Energy and Environment (CERI EE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, Spatial distribution, Atmospheric sciences, 01 natural sciences, GEOF, lcsh:Chemistry, chemistry.chemical_compound, Arabitol, environmental factors, Tracers, Relative humidity, 0105 earth and related environmental sciences, 2. Zero hunger, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Topsoil, polyols, Detritus, Vegetation, 15. Life on land, Debris, primary biogenic organic aerosol, lcsh:QC1-999, Aerosol, chemistry, lcsh:QD1-999, 13. Climate action, [SDE]Environmental Sciences, Environmental science, lcsh:Physics
Abstract

International audience; The primary sugar compounds (SCs, defined as glucose, arabitol, and mannitol) are widely recognized as suitable molecular markers to characterize and apportion primary biogenic organic aerosol emission sources. This work improves our understanding of the spatial behavior and distribution of these chemical species and evidences their major effective environmental drivers. We conducted a large study focusing on the daily (24 h) PM 10 SC concentrations for 16 increasing space scale sites (local to nationwide), over at least 1 complete year. These sites are distributed in several French geographic areas of different environmental conditions. Our analyses, mainly based on the examination of the short-term evolutions of SC concentrations, clearly show distance-dependent correlations. SC concentration evo-lutions are highly synchronous at an urban city scale and remain well correlated throughout the same geographic re-Published by Copernicus Publications on behalf of the European Geosciences Union. 11014 A. Samaké et al.: Arabitol, mannitol, and glucose as tracers of primary biogenic organic aerosol gions, even if the sites are situated in different cities. However , sampling sites located in two distinct geographic areas are poorly correlated. Such a pattern indicates that the processes responsible for the evolution of the atmospheric SC concentrations present a spatial homogeneity over typical areas of at least tens of kilometers. Local phenomena, such as the resuspension of topsoil and associated microbiota, do no account for the major emissions processes of SC in urban areas not directly influenced by agricultural activities. The concentrations of SC and cellulose display remarkably synchronous temporal evolution cycles at an urban site in Greno-ble, indicating a common source ascribed to vegetation. Additionally , higher concentrations of SC at another site located in a crop field region occur during each harvest periods, indicating resuspension processes of plant materials (crop de-tritus, leaf debris) and associated microbiota for agricultural and nearby urbanized areas. Finally, ambient air temperature, relative humidity, and vegetation density constitute the main effective drivers of SC atmospheric concentrations.

Published
2019
Full Text
View/download PDF

3. Air pollution modeling and exposure assessment during pregnancy in the French Longitudinal Study of Children (ELFE)

Author

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
Full Text
View/download PDF

4. Study protocol to explore the social effects of environmental exposure and lifestyle behaviours on pregnancy outcome: an overview of cohort of pregnant women study

Author

Valentin Simoncic, Virginie Hamann, Loriane Huber, Phillipe Deruelle, Nicolas Sananes, Christophe Enaux, Maxime Alter, Charles Schillinger, Severine Deguen, Wahida Kihal-Talantikite, Laboratoire Image, Ville, Environnement (LIVE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Les Hôpitaux Universitaires de Strasbourg (HUS), Biomatériaux et Bioingénierie (BB), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Atmo Grand Est, CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), and univOAK, Archive ouverte

Subjects
Adult, [SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, Infant, Newborn, Pregnancy Outcome, Bayes Theorem, Environmental Exposure, General Medicine, [SDV.MHEP.GEO]Life Sciences [q-bio]/Human health and pathology/Gynecology and obstetrics, Cohort Studies, [SDV.MHEP.GEO] Life Sciences [q-bio]/Human health and pathology/Gynecology and obstetrics, Pregnancy, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Humans, [SDV.EE.SANT] Life Sciences [q-bio]/Ecology, environment/Health, Female, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Pregnant Women, Prospective Studies, Child, Life Style
Abstract

Introduction A growing number of international studies have highlighted the adverse consequences of lived experience in the first thousand days of pregnancy and early life on the probability of stillbirth, child mortality, inadequate growth and healthy development during both childhood and adulthood. The lived experience of the fetus inside the womb and at the birth is strongly related to both maternal health during pregnancy and maternal exposure to a set of environmental factors known as ‘exposome’ characteristics, which include environmental exposure, health behaviours, living conditions, neighbourhood characteristics and socioeconomic profile. The aim of our project is to explore the relationships between exposome characteristics and the health status of pregnant women and their newborns. We are particularly interested in studying the relationships between the social inequality of adverse pregnancy outcomes and (1) short-term exposure to atmospheric pollution (MobiFem project) and (2) pregnancy lifestyle (EnviFem project). Methods and analysis Ours is a prospective, observational and multisite cohort study of pregnant women, involving one teaching hospital across two sites in the Strasbourg metropolitan area. The research team at University Hospital of Strasbourg (HUS) Health collects data on outcomes and individual characteristics from pregnancy registries, clinical records data and questionnaires administered via email to study participants. Recruitment began in February 2021 and will be complete by December 2021. Participants are recruited from first trimester antenatal ultrasound examinations (conducted on weekdays across both sites); each woman meeting our inclusion criteria enters the cohort at the end of her first trimester. Study participants receive a total of three online questionnaires covering sociodemographic characteristics, travel behaviour patterns and lifestyle. Participants complete these questionnaires at recruitment, during the second and third trimester. The level of personal exposure to air pollution is characterised using a dynamic spatiotemporal trajectory model that describes the main daily movements of pregnant women and the time spent in each place frequented. Univariate, multilevel and Bayesian model will be used to investigate the relationships between exposome characteristics and the health status of pregnant women and their newborns. Ethics and dissemination Our research was approved by the Commission de Protection des Personnes (CPP) Ile de France VI (Paris) on 9 December 2020 (File reference No. 20.09.15.41703 ID RCB: 2020-A02580-39 and No. 20 080–42137 IDRCB 2020-A02581-38). The Agence Nationale de Sécurité du Médicament was informed of it on 15 December 2020. Findings from the study will be disseminated through publications and international conferences and through presentation at meetings with local stakeholders, researchers and policy-makers. Trial registration numbers NCT04705272 NCT04725734

Published
2022
Full Text
View/download PDF

5. Overview of the French Operational Network for In Situ Observation of PM Chemical Composition and Sources in Urban Environments (CARA Program)

Author

Joel Savarino, Jean-Eudes Petit, Gilles Levigoureux, Shouwen Zhang, Sabrina Pontet, Laurent Y. Alleman, Florie Chevrier, Carole Boullanger, Raphaële Falhun, Gaëlle Uzu, Jean-Luc Besombes, Nicolas Bonnaire, Samuël Weber, Deepchandra Srivastava, Abdoulaye Samaké, Dalia Salameh, Arnaud Papin, Valérie Gros, Véronique Riffault, Yunjiang Zhang, Anais Detournay, Caroline Marchand, Alexandre Albinet, Nicolas Marchand, Marta Dominik-Sègue, Céline Garbin, Mélodie Chatain, Eva Leoz-Garziandia, Véronique Ghersi, Sébastien Conil, Jérôme Rangognio, Tanguy Amodeo, Guillaume Grignion, Robin Aujay-Plouzeau, Jean-Luc Jaffrezo, Benjamin Chazeau, Olivier Favez, Institut National de l'Environnement Industriel et des Risques (INERIS), LCSQA - Laboratoire Central de Surveillance de la Qualité de l’Air, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Chimie Atmosphérique Expérimentale (CAE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT), Centre for Energy and Environment (CERI EE - IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), AtmoSud, Madininair, Atmo Grand Est, Atmo Nouvelle-Aquitaine, Atmo Bourgogne Franche-Comté (ATMO BFC), Atmo Normandie, Air Breizh, Gwad'air, AIRPARIF - Surveillance de la qualité de l'air en Île-de-France, Qualitair Corse, Air Pays de la Loire, ATMO Auvergne-Rhône-Alpes (ATMO-AURA), LIG'AIR- Surveillance de la Qualité de l'Air en Région Centre, ATMO Hauts de France [Lille], Environnements, Dynamiques et Territoires de Montagne (EDYTEM), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Observatoire Pérenne de l'Environnement, Agence Nationale pour la Gestion des Déchets Radioactifs (ANDRA), French Ministry of Environment, ADEME, CNRS, CEA, ACTRIS-France (CLAP national observation service), ANDRA, ENS Paris, CARA program (LCSQA), CPER CLIMIBIO, SOURCES project (1462C0064), DECOMBIO project (1362C0028), PM-DRIVE project (1162C0002), CAMERA project (1062c0008), INACS project (1262c0011), QAMECS project (1262c0011), ANR-11-LABX-0005,Cappa,Physiques et Chimie de l'Environnement Atmosphérique(2011), ANR-10-LABX-0056,OSUG@2020,Innovative strategies for observing and modelling natural systems(2010), European Project: 262254,EC:FP7:INFRA,FP7-INFRASTRUCTURES-2010-1,ACTRIS(2011), European Project: 654109,H2020,H2020-INFRAIA-2014-2015,ACTRIS-2(2015), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Centre for Energy and Environment (CERI EE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Atmo Bourgogne Franche-Comté, Environnements, Dynamiques et Territoires de la Montagne (EDYTEM), and Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])

Subjects
In situ, Atmospheric Science, source, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Aerosol chemical composition, lcsh:QC851-999, 010501 environmental sciences, Environmental Science (miscellaneous), Mineral dust, Reference laboratory, 01 natural sciences, 7. Clean energy, apportionment, Apportionment, 11. Sustainability, Air quality index, Chemical composition, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, aerosol chemical composition, business.industry, Environmental resource management, Quality control, source apportionment, Particulates, atmospheric_science, Aerosol, monitoring strategies, 13. Climate action, urban air quality, Environmental chemistry, Environmental science, lcsh:Meteorology. Climatology, France, business, Quality assurance
Abstract

The CARA program has been developed since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks to gain a better knowledge at the national level on the particulate matter (PM) chemistry and its diverse origins in urban environments. It results of strong collaborations with international-level academic partners, allowing to bring state-of-the-art, straightforward and robust results and methodologies within operational air quality stakeholders (and subsequently, decision makers). Here, we illustrate some of the main outputs obtained over the last decade thanks to this program, regarding methodological aspects (both in terms of measurement techniques and data treatment procedures) as well as acquired knowledge on the predominant PM sources. Offline and online methods are used following well-suited quality assurance and quality control procedures, notably including inter-laboratory comparison exercises. Source apportionment studies are conducted using various receptor modeling approaches. Overall, the results presented herewith underline the major influences of residential wood burning (during the cold period) and road transport emissions (exhaust and non-exhaust ones, all along the year), as well as substantial contributions of mineral dust and primary biogenic particles (mostly during the warm period). Long-range transport phenomena, e.g., advection of secondary inorganic aerosols from the European continental sector and of Saharan dust into the French West Indies, are also discussed in this paper. Finally, we briefly address the use of stable isotope measurements (δ15N) and of various organic molecular markers for a better understanding of the origins of ammonium and of the different organic aerosol fractions, respectively.

Published
2021
Full Text
View/download PDF

6. Maternal Ambient Exposure to Atmospheric Pollutants during Pregnancy and Offspring Term Birth Weight in the Nationwide ELFE Cohort

Author

Marion, Ouidir, Emie, Seyve, Emmanuel, Rivière, Julien, Bernard, Marie, Cheminat, Jérôme, Cortinovis, François, Ducroz, Fabrice, Dugay, Agnès, Hulin, Itai, Kloog, Anne, Laborie, Ludivine, Launay, Laure, Malherbe, Pierre-Yves, Robic, Joel, Schwartz, Valérie, Siroux, Jonathan, Virga, Cécile, Zaros, Marie-Aline, Charles, Rémy, Slama, Johanna, Lepeule, Civs, Gestionnaire, 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 (UGA), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), Atmo Grand Est, 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), Atmo Normandie, Air Pays de la Loire, AIRPARIF - Surveillance de la qualité de l'air en Île-de-France, Atmo Nouvelle-Aquitaine, Ben-Gurion University of the Negev (BGU), Unité de recherche interdisciplinaire pour la prévention et le traitement des cancers (ANTICIPE), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN)-Centre Régional de Lutte contre le Cancer François Baclesse [Caen] (UNICANCER/CRLC), Normandie Université (NU)-UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-UNICANCER-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de l'Environnement Industriel et des Risques (INERIS), Atmo Occitanie, Harvard T.H. Chan School of Public Health, Atmo-PACA, Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), EFS-Institut national d'études démographiques (INED)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Régional de Lutte contre le Cancer François Baclesse [Caen] (UNICANCER/CRLC), UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-UNICANCER, and 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)

Subjects
[SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, Air Pollutants, Nitrogen Dioxide, air pollution, spatial autocorrelation, Article, fluids and secretions, Maternal Exposure, Pregnancy, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, term birth weight, Birth Weight, Humans, Medicine, [SDV.EE.SANT] Life Sciences [q-bio]/Ecology, environment/Health, Environmental Pollutants, Female, Particulate Matter, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Longitudinal Studies, Child, doubly robust, propensity score
Abstract

Background: Studies have reported associations between maternal exposure to atmospheric pollution and lower birth weight. However, the evidence is not consistent and uncertainties remain. We used advanced statistical approaches to robustly estimate the association of atmospheric pollutant exposure during specific pregnancy time windows with term birth weight (TBW) in a nationwide study. Methods: Among 13,334 women from the French Longitudinal Study of Children (ELFE) cohort, exposures to PM2.5, PM10 (particles &lt, 2.5 µm and &lt, 10 µm) and NO2 (nitrogen dioxide) were estimated using a fine spatio-temporal exposure model. We used inverse probability scores and doubly robust methods in generalized additive models accounting for spatial autocorrelation to study the association of such exposures with TBW. Results: First trimester exposures were associated with an increased TBW. Second trimester exposures were associated with a decreased TBW by 17.1 g (95% CI, −26.8, −7.3) and by 18.0 g (−26.6, −9.4) for each 5 µg/m3 increase in PM2.5 and PM10, respectively, and by 15.9 g (−27.6, −4.2) for each 10 µg/m3 increase in NO2. Third trimester exposures (truncated at 37 gestational weeks) were associated with a decreased TBW by 48.1 g (−58.1, −38.0) for PM2.5, 38.1 g (−46.7, −29.6) for PM10 and 14.7 g (−25.3, −4.0) for NO2. Effects of pollutants on TBW were larger in rural areas. Conclusions: Our results support an adverse effect of air pollutant exposure on TBW. We highlighted a larger effect of air pollutants on TBW among women living in rural areas compared to women living in urban areas.

Published
2021
Full Text
View/download PDF

7. Allergies aux fruits

Author

Lefevre, S., Gregori, M., Astier, C., Rougé, Pierre, Kanny, G., Institut régional des pathologies allergologiques, environnementales et d'immunologie clinique [CHR Metz-Thionville], Centre hospitalier régional Metz-Thionville (CHR Metz-Thionville), Atmo Grand Est, Ecole Nationale Supérieure d'Agronomie et des Industries Alimentaires (ENSAIA), Université de Lorraine (UL), Pharmacochimie et Biologie pour le Développement (PHARMA-DEV), Institut de Recherche pour le Développement (IRD)-Institut de Chimie de Toulouse (ICT), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)

Subjects
Vegetal allergens, Pollen food cross-reactivity, Oral syndrome, Réactivité croisée pollen aliment, [SDV]Life Sciences [q-bio], Food allergy, Allergie alimentaire, Syndrome oral, Allergènes végétaux, Fruits
Abstract

International audience; Fruit allergies are frequent, representing for Rosaceae fruits 14 % of reported allergies and 5 % for fruits crossing with latex. They can be linked to a primary sensitization to pollens or isolated. The concept of fruit allergy is complex for the practitioner because of the difficulties in defining the fruit, variable according to classifications, the evaluation of the risk of cross-allergy and the particularities of the clinical expressions of a food allergy according to the allergens involved. This review specifies the botanical, culinary and allergological definitions of fruit, the main families of allergens responsible for food allergies, and the clinical, diagnostic and therapeutic particularities of fruit allergy. Sensitization can occur by respiratory sensitization (pollen-fruit cross-reactivity) or by primary sensitization to fruit by the digestive tract or by contact. Plant epitopes may be continuous or discontinuous. The thermal behaviour of allergens, their resistance to digestion and their stability in an acidic environment makes it possible to characterise their risk. Allergenicity often varies with the cultivar, the method of preservation, the food processing technologies used (cooking, canning, fermentation, texturisation, hydrolysis, filtration, etc.). The diagnosis is established on the basis of an algorithm based on anamnesis, prick-tests with native foods, the search for the specific IgE, the reintroduction test. The importance of using native foods for skin testing should be stressed because of the particular sensitivity of plant allergens to denaturation. The treatment is based on the removal of the offending fruit. Immunotherapy trials with fruit allergens are under study. Tolerance protocols using fruits at different cooking times are promising for thermolabile allergens.; Les allergies aux fruits sont fréquentes, représentant pour les fruits de Rosacées 14 % des allergies rapportées et 5 % pour les fruits croisant avec le latex. Elles peuvent être liées à une sensibilisation primaire aux pollens ou isolées. Le concept d’allergie aux fruits est complexe pour le praticien en raison des difficultés de définition du fruit variable selon les classifications, l’évaluation du risque d’allergie croisée et les particularités des expressions cliniques de l’allergie alimentaire en fonction des allergènes impliqués. Cette mise au point précise les définitions botanique, culinaire et allergologique du fruit, les principales familles d’allergènes responsables d’allergies alimentaires, les particularités cliniques, diagnostiques et thérapeutiques de l’allergie aux fruits. La sensibilisation peut survenir par sensibilisation respiratoire (réactivité croisée pollens-fruits) ou par sensibilisation primaire aux fruits par voie digestive ou par contact. Les épitopes végétaux peuvent être continus ou discontinus. Le comportement thermique des allergènes, leur résistance à la digestion, leur stabilité en milieu acide permettent de caractériser leur risque. L’allergénicité varie souvent avec le cultivar, le mode de conservation, les technologies agro-alimentaires utilisées (cuisson, appertisation, fermentation, texturisation, hydrolyse, filtration…). Le diagnostic s’établit sur la base d’un algorithme basé sur l’anamnèse, les prick tests aux aliments natifs, la recherche d’IgE spécifiques, le test de réintroduction. Il convient de souligner l’importance d’utiliser les aliments natifs pour la réalisation des tests cutanés en raison de la sensibilité particulière des allergènes végétaux à la dénaturation. Le traitement se base sur l’éviction des fruits incriminés. Des essais d’immunothérapie aux allergènes de fruits sont à l’étude. Les protocoles de tolérance utilisant des fruits à différents temps de cuisson sont prometteurs pour les allergènes thermolabiles.

Published
2020
Full Text
View/download PDF

8. Substantial brown carbon emissions from wintertime residential wood burning over France

Author

Valérie Gros, Griša Močnik, Véronique Jacob, Grégory Gille, Jean-Eudes Petit, Gilles Levigoureux, Florie Chevrier, Sabrina Pontet, Jean-Luc Jaffrezo, Yunjiang Zhang, Olivier Favez, Marta Dominik-Sègue, Eve Chretien, Alexandre Albinet, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Chimie Atmosphérique Expérimentale (CAE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Regional Network for Air Quality Monitoring, Atmo-PACA, ATMO Auvergne-Rhône-Alpes (ATMO-AURA), Atmo Grand Est, Atmo Normandie, University of Nova Gorica, Jozef Stefan Institute [Ljubljana] (IJS), European Project: 262254,EC:FP7:INFRA,FP7-INFRASTRUCTURES-2010-1,ACTRIS(2011), European Project: 654109,H2020,H2020-INFRAIA-2014-2015,ACTRIS-2(2015), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )

Subjects
Environmental Engineering, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Radiative effect, chemistry.chemical_compound, Environmental Chemistry, Multi sites, Brown carbon, Biomass burning, Waste Management and Disposal, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Mass absorption, integumentary system, Mass absorption efficiency, Levoglucosan, Residential wood burning, Pollution, 6. Clean water, chemistry, 13. Climate action, Geographic origin, Aerosol absorption, Environmental science, Wood burning, France
Abstract

International audience; levated concentrations of inorganic arsenic, one of the most potent environmental toxicants and carcinogens, have been detected in well water around Lake Poopó, Bolivia. This study aimed to assess human exposure to arsenic in villages around Lake Poopó, and also to elucidate whether the metabolism and detoxification of arsenic in this population is as efficient as previously indicated in other Andean areas. We recruited 201 women from 10 villages around Lake Poopó. Arsenic exposure was determined as the sum concentration of arsenic metabolites (inorganic arsenic; monomethylarsonic acid, MMA; and dimethylarsinic acid, DMA) in urine (U-As), measured by HPLC-HG-ICP-MS. Efficiency of arsenic metabolism was assessed by the relative fractions of the urinary metabolites. The women had a wide variation in U-As (range 12–407 μg/L, median 65 μg/L) and a markedly efficient metabolism of arsenic with low %MMA (median 7.7%, range: 2.2–18%) and high %DMA (80%, range: 54–91%) in urine. In multivariable-adjusted linear regression models, ethnicity (Aymara-Quechua vs. Uru), body weight, fish consumption and tobacco smoking were associated with urinary arsenic metabolite fractions. On average, the Uru women had 2.5 lower % (percentage unit) iAs, 2.2 lower %MMA and 4.7 higher %DMA compared with the Aymara-Quechua women. Our study identified several factors that may predict these women's arsenic methylation capacity, particularly ethnicity. Further studies should focus on mechanisms underlying these differences in arsenic metabolism efficiency, and its importance for the risk of arsenic-related health effects.

Published
2020
Full Text
View/download PDF

9. La pollution atmosphérique et ses effets sur la santé respiratoire en France. Document d’experts du Groupe Pathologies pulmonaires professionnelles environnementales et iatrogéniques (PAPPEI) de la Société de pneumologie de langue française (SPLF)

Author

D. Charpin, L Malherbe, Denis Caillaud, A Bourin, J.-C. Dalphin, Bruno Housset, Isabella Annesi-Maesano, Thierry Chinet, F. De Blay, le Groupe Pathologies pulmonaires professionnelles environnementales et iatrogéniques, Gilles Dixsaut, A Colette, J. Kleinpeter, I Roussel, Service de Pneumologie et Allergologie, CHU Clermont-Ferrand, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre for Energy and Environment (CERI EE), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut Mines-Télécom [Paris] (IMT), Service de Pneumologie et d'Oncologie Thoracique [AP-HP Hôpital Ambroise-Paré], Hôpital Ambroise Paré [AP-HP], Institut National de l'Environnement Industriel et des Risques (INERIS), Centre Hospitalier Universitaire de Strasbourg (CHU de Strasbourg ), Service de physiologie explorations fonctionnelles, hôpital Cochin Hôtel Dieu et Fondation du Souffle contre les maladies respiratoires, Service de Pneumologie [CHI Créteil], CHI Créteil, Atmo Grand Est, Agence de surveillance de la qualité de l’air (ASPA), Faculté des sciences de Lille, Laboratoire Chrono-environnement - CNRS - UBFC (UMR 6249) (LCE), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Service de Pneumologie-Allergologie [Hôpital de la Timone - APHM], Université de la Méditerranée - Aix-Marseille 2-Assistance Publique - Hôpitaux de Marseille (APHM)-Hôpital Sainte-Marguerite [CHU - APHM] (Hôpitaux Sud ), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Centre for Energy and Environment (CERI EE - IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), and Laboratoire Chrono-environnement (UMR 6249) (LCE)

Subjects
Pulmonary and Respiratory Medicine, business.industry, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, 030228 respiratory system, 13. Climate action, Lung health, Environmental health, [SDE]Environmental Sciences, Medicine, 030212 general & internal medicine, business, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019
Full Text
View/download PDF

10. Sources and Geographical Origins of PM10 in Metz (France) Using Oxalate as a Marker of Secondary Organic Aerosols by Positive Matrix Factorization Analysis

Author

Cyril Pallares, Olivier Favez, Laurent Y. Alleman, Nicolas Bonnaire, Jean-Eudes Petit, Emmanuel Rivière, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Atmo Grand Est, Institut National de l'Environnement Industriel et des Risques (INERIS), LCSQA - Laboratoire Central de Surveillance de la Qualité de l’Air, Centre for Energy and Environment (CERI EE), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut Mines-Télécom [Paris] (IMT), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre for Energy and Environment (CERI EE - IMT Nord Europe), and Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe)

Subjects
Pollution, Atmospheric Science, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, [SDE.MCG]Environmental Sciences/Global Changes, lcsh:QC851-999, 010501 environmental sciences, Environmental Science (miscellaneous), Atmospheric sciences, 01 natural sciences, chemistry.chemical_compound, receptor modelling, Nitrate, Dominance (ecology), Nonnegative matrix, secondary organic aerosols, Sulfate, Biomass burning, 0105 earth and related environmental sciences, media_common, oxalate, Secondary organic aerosols, Aerosol, chemistry, 13. Climate action, positive matrix factorization, Environmental science, lcsh:Meteorology. Climatology, trajectory analysis
Abstract

International audience; An original source apportionment study was conducted on atmospheric particles (PM 10) collected in Metz, one of the largest cities of Eastern France. A Positive matrix factorization (PMF) analysis was applied to a sampling filter-based chemical dataset obtained for the April 2015 to January 2017 period. Nine factors were clearly identified, showing mainly contributions from anthropogenic sources of primary PM (19.2% and 16.1% for traffic and biomass burning, respectively) as well as secondary aerosols (12.3%, 14.5%, 21.8% for sulfate-, nitrate-, and oxalate-rich factors, respectively). Wood-burning aerosols exhibited strong temporal variations and contributed up to 30% of the PM mass fraction during winter, while primary traffic concentrations remained relatively constant throughout the year. These two sources are also the main contributors during observed PM 10 pollution episodes. Furthermore, the dominance of the oxalate-rich factor among other secondary aerosol factors underlines the role of atmospheric processing to secondary organic aerosol loadings which are still poorly characterized in this region. Finally, Concentration-Weighted Trajectory (CWT) analysis were performed to investigate the geographical origins of the apportioned sources, notably illustrating a significant transport of both nitrate-rich and sulfate-rich factors from Northeastern Europe but also from the Balkan region.

Published
2019
Full Text
View/download PDF

11. Importance of the PBOA fraction of PM10

Author

Abdoulaye Samaké, Jean-Luc Jaffrezo, Olivier Favez, Samuel Weber, Véronique Jacob, Alexandre Albinet, Véronique Riffault, Esperanza Perdrix, Antoine Waked, Benjamin Golly, Dalia Salameh, Florie Chevrier, Diogo Miguel Oliveira, Nicolas Bonnaire, Jean-Luc Besombes, Martins, Jean M. F., Sébastien Conil, Géraldine Guillaud, Boualem Mesbah, Benoit Rocq, Pierre-Yves Robic, Agnès Hulin, Sébastien Le Meur, Maxence Descheemaecker, Eve Chretien, Nicolas Marchand, Gaëlle UZU, Institut des Géosciences de l’Environnement (IGE), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Institut National de l'Environnement Industriel et des Risques (INERIS), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT), Centre for Energy and Environment (CERI EE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Chimie Atmosphérique Expérimentale (CAE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Agence Nationale pour la Gestion des Déchets Radioactifs (ANDRA), ATMO Auvergne-Rhône-Alpes (ATMO-AURA), Atmo-Sud, GeographR, ATMO Hauts de France [Lille], Atmo Occitanie, Atmo Nouvelle-Aquitaine, Atmo Normandie, LIG'AIR- Surveillance de la Qualité de l'Air en Région Centre, Atmo Grand Est, Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre for Energy and Environment (CERI EE - IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDE.MCG]Environmental Sciences/Global Changes, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2019

12. Comparison of PM10 Sources Profiles at 15 French Sites Using a Harmonized Constrained Positive Matrix Factorization Approach

Author

Jean-Luc Jaffrezo, Antoine Waked, Alexandre Albinet, Benoit Rocq, Laurent Y. Alleman, Olivier Favez, Géraldine Guillaud, Boualem Meshbah, Jean-Luc Besombes, Véronique Jacob, Agnès Hulin, Samuël Weber, Dalia Salameh, Marta Dominik-Sègue, Eve Chretien, Institut des Géosciences de l’Environnement (IGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut National de l'Environnement Industriel et des Risques (INERIS), Centre for Energy and Environment (CERI EE), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut Mines-Télécom [Paris] (IMT), Laboratoire LCME / Equipe Chimie de l'Environnement (LCME_CE), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), ATMO Auvergne-Rhône-Alpes (ATMO-AURA), ATMO Hauts de France [Lille], Atmo Nouvelle-Aquitaine, Atmo Normandie, Atmo Grand Est, Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre for Energy and Environment (CERI EE - IMT Nord Europe), and Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, PM, Air pollution, Context (language use), lcsh:QC851-999, 010501 environmental sciences, Environmental Science (miscellaneous), Atmospheric sciences, medicine.disease_cause, 01 natural sciences, Representativeness heuristic, GEOF, similarity assessment, 11. Sustainability, medicine, [CHIM]Chemical Sciences, Nonnegative matrix, Air quality index, 0105 earth and related environmental sciences, Mathematical model, Homogeneity (statistics), source apportionment, Particulates, uncertainties, 13. Climate action, [SDE]Environmental Sciences, Environmental science, lcsh:Meteorology. Climatology, aerosols
Abstract

Receptor-oriented models, including positive matrix factorization (PMF) analyses, are now commonly used to elaborate and/or evaluate action plans to improve air quality. In this context, the SOURCES project has been set-up to gather and investigate in a harmonized way 15 datasets of chemical compounds from PM10 collected for PMF studies during a five-year period (2012&ndash, 2016) in France. The present paper aims at giving an overview of the results obtained within this project, notably illustrating the behavior of key primary sources as well as focusing on their statistical robustness and representativeness. Overall, wood burning for residential heating as well as road transport were confirmed to be the two main primary sources strongly influencing PM10 loadings across the country. While wood burning profiles, as well as those dominated by secondary inorganic aerosols, present a rather good homogeneity among the sites investigated, some significant variabilities were observed for primary traffic factors, illustrating the need to better characterize the diversity of the various vehicle exhaust and non-exhaust emissions. Finally, natural sources, such as sea salts (widely observed in internal mixing with anthropogenic compounds), primary biogenic aerosols and/or terrigenous particles, were also found as non-negligible PM10 components at every investigated site.

Published
2019
Full Text
View/download PDF

13. Organic markers and OC source apportionment for seasonal variations of PM2.5 at 5 rural sites in France

Author

Jérôme Rangognio, Benjamin Golly, Pierre-Yves Robic, Jean-Luc Besombes, Véronique Jacob, Abdoulaye Samaké, Samuël Weber, Eve Chretien, Sébastien Conil, Jean-Luc Jaffrezo, Antoine Waked, M.-P. Vagnot, Laboratoire LCME / Equipe Chimie de l'Environnement (LCME_CE), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Agence Nationale pour la Gestion des Déchets Radioactifs (ANDRA), LIG AIR, Atmo Grand Est, Atmo Aura, and Atmo Occitanie

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Oxalic acid, Rural sites, Fraction (chemistry), PM2.5, 010501 environmental sciences, Organic markers, 01 natural sciences, GEOF, Oxalate, chemistry.chemical_compound, Arabitol, PSCF, [CHIM]Chemical Sciences, OC source apportionment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Total organic carbon, Primary (chemistry), Levoglucosan, Aerosol, chemistry, 13. Climate action, Environmental chemistry, [SDE]Environmental Sciences, Environmental science
Abstract

The chemical characterization of PM2.5 was conducted at 5 rural background sites in France for the year 2013. Chemical analysis of daily samples every sixth day included the measurements of organic carbon (OC), elemental carbon (EC), ionic species and several specific primary and secondary organic tracers such as levoglucosan, polyols, methane sulfonic acid (MSA) and oxalate. The sampling sites were spatially distributed in order to be representative of the French atmospheric background. The results showed well identified temporal variations common to all the 5 sampling sites, covering a large fraction of France. During winter, concentrations of the biomass burning marker levoglucosan are significantly increased with high synchronous temporal pattern, indicating the strong impact of this source at a regional scale. During summer, concentrations of primary biogenic markers such as polyols (arabitol, mannitol) increase due to higher biological activities while oxalate contributions to OC also increases, attributed to ageing processes. The sources of primary organic aerosol are investigated using mono-tracer approaches based on these compounds. Results indicate that the relative contributions of wood burning to OC are very high, reaching an average value of 90% during winter for some of the rural sites. Terrestrial primary biogenic organic fraction is significant in summer and fall with a monthly contribution ranging from 4.5 to 9.5% of OC in PM2.5. A synchronous increase is also observed for secondary organic tracers (MSA, oxalic acid) during warm period confirming the influence on the large scale of these compounds that can account for 10–20% and 5–7% of the OC mass, respectively.

Published
2019
Full Text
View/download PDF

14. Le projet Amp’Air : Amélioration de la représentation des émissions agricoles d'ammoniac pour une meilleure prévision de la qualité de l'air en France

Author

Génermont, Sophie, Dufour, Gaëlle, Crunaire, S., Meleux, Frédérik, Arteta, Joaquim, Fortems-Cheiney, Audrey, Chétien, Eve, Couvidat, Florian, Dufossé, Karine, Bigeard, Guillaume, Gilliot, Jean-Marc, Génermont, Sophie, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire Imagerie et Systèmes d'Acquisition (LISA), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Institut Mines-Télécom [Paris] (IMT), Eneris Environment Energy Consultants, Météo-France, Atmo Grand Est, and Programme PRIMEQUAL

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Ammoniac, [SDE.MCG] Environmental Sciences/Global Changes, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, Inventaire d'émissions, émissions agricoles, [SDE.MCG]Environmental Sciences/Global Changes, Chimie transport, Qualité de l'air, Réseau de mesures
Abstract

International audience; ContexteL’ammoniac, gaz émis à 94% par les activités agricoles, est impliqué dans la formation des particules secondaires de petite taille (PM2.5) et la réduction de ses émissions est un enjeu pour l’amélioration de la qualité de l’air en France. Cependant, des incertitudes fortes pèsent sur le bilan annuel des inventaires européens de référence et sont un frein à l’évaluation de la contribution des émissions d'ammoniac aux niveaux de pollution ambiante. Parallèlement, les modèles de qualité de l’air actuellement utilisés en prévision de la qualité de l’air (plateforme PREV’AIR) ne prennent en compte ni les conditions pédo-climatiques ni les conditions de la pratique agricole et de ce fait peinent à anticiper les forts épisodes de pollution particulaire.ObjectifsLe projet Amp’Air porte sur l’amélioration des approches intégrant les émissions d’ammoniac dans ces modèles pour une meilleure prévision de la contribution de l'agriculture à la qualité de l'air en France, en formulant deux hypothèses. La première est qu’une meilleure représentation spatiale et temporelle des émissions agricoles d’ammoniac est indispensable à une meilleure représentation des processus de chimie-transport dans l’atmosphère conduisant à la formation des particules. La deuxième est que la variabilité temporelle des émissions d'ammoniac est particulièrement liée à la fertilisation azotée. L’objectif du projet est de proposer une méthodologie permettant de mieux prendre en compte dans les modèles de prévision de la qualité de l’air la variabilité spatiale et temporelle des émissions d’ammoniac liées à la fertilisation azotée.MéthodologiesLa démarche d’amélioration est constituée de deux étapes principales, avec des étapes associées.La première étape consiste à mettre en œuvre, confronter et combiner de manière innovante deux des outils/méthodes les plus récemment mis au point pour décrire finement la variabilité spatiale et temporelle de ces émissions : -l’inversion des émissions utilisées dans CHIMERE à partir des concentrations estimées à partir des observations IASI (Fortems-Cheiney et al., 2016) ; -l’outil « CADASTRE_NH3 » basé sur le modèle Volt’Air et la description fine des données d’entrée (Ramanantenasoa et al., 2018 ; Génermont et al., 2018).Ces approches reposent sur une complémentarité entre des observations de diverses natures (enquêtes, expérimentations, observations satellitaires, réseaux de mesure…) et des simulations numériques à différentes échelles (parcelle agricole, petite région agricole, méso-échelle) (modèle 1D, 3D).L’utilisation en routine de ces outils complexes en prévision de la qualité de l’air opérationnelle est difficile. C’est pourquoi, parallèlement au premier objectif, ce projet a pour objectif de proposer des outils plus faciles à mobiliser. La démarche consiste à proposer des méta-modèles élaborés à partir des outils mentionnés précédemment, et dont la qualité prédictive est évaluée. Les approches de modélisation sont en effet des approches qui permettent de produire des modèles relativement simples tout en restant basées sur des connaissances des processus mécanistes.La deuxième étape consiste à valider la qualité effective des inventaires obtenus.Cette validation consiste à vérifier que l’utilisation par les modèles de prévision de la qualité de l’air des inventaires d’émissions corrigés permet effectivement une meilleure quantification dans le temps et dans l’espace des concentrations particulaires. Les simulations des concentrations de particules sont réalisées avec les modèles de chimie-transport CHIMERE et MOCAGE et comparées aux simulations utilisées actuellement. Les résultats sont confrontés au niveau local avec les mesures issues des campagnes de terrain menés spécifiquement pour le projet, et au niveau national avec les données remontées dans la base de données nationale (LCSQA : Laboratoire Central de Surveillance de la Qualité de l’Air) et les données du réseau CARA (CARActérisation chimique des particules). La validation à des échelles spatiales larges et sur des périodes longues des inventaires est un réel challenge, nécessitant la mise en place de réseaux de mesure de concentration en ammoniac à très bas coût financier et humain. Le projet Amp’Air a déployé spécifiquement des mesures de concentration en ammoniac au sol dans cet objectif et s’est donné pour objectif d’affiner la stratégie du déploiement de ces mesures de concentration en ammoniac à l’échelle d’une région.Conclusions et perspectivesLa poursuite parallèle de deux objectifs (amélioration et opérationnalité) est indispensable à l’implémentation dans la plateforme PREV’AIR d’une nouvelle chaîne de modélisation prenant en compte explicitement et opérationnellement la dynamique des émissions d’ammoniac. Le projet Amp’Air ne cherche cependant pas à répondre à la question des décisions à prendre pour réduire durablement les émissions d’ammoniac et pour limiter l’impact sanitaire des épisodes de pollution aux particules à forte composante nitrate d’ammonium ; c’est l’objectif du projet PolQA « POLitiques d’amélioration de la Qualité de l’air grâce aux pratiques Agricoles », porté par l’INERIS.

Published
2019

15. Polyols and glucose particulate species as tracers of primary biogenic organic aerosols at 28 French sites

Author

A. Samaké, J.-L. Jaffrezo, O. Favez, S. Weber, V. Jacob, A. Albinet, V. Riffault, E. Perdrix, A. Waked, B. Golly, D. Salameh, F. Chevrier, D. M. Oliveira, N. Bonnaire, J.-L. Besombes, J. M. F. Martins, S. Conil, G. Guillaud, B. Mesbah, B. Rocq, P.-Y. Robic, A. Hulin, S. Le Meur, M. Descheemaecker, E. Chretien, N. Marchand, G. Uzu, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Université Grenoble Alpes (UGA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut National de l'Environnement Industriel et des Risques (INERIS), IMT Lille Douai, Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Université Lille Nord de France (COMUE), Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire LCME / Equipe Chimie de l'Environnement (LCME_CE), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Ctr Meuse Haute Marne - Observ Perenne Environm, DRD Observat Surveillance, Bure, France, Université Paris Diderot - Paris 7 (UPD7), Atmo Rhone-Alpes, Pôle métier Climat & Air du CRIGE-PACA, GeographR, ATMO Hauts de France [Lille], Atmo Occitanie, Atmo Nouvelle-Aquitaine, Atmo Normandie, Lig'air, Atmo Grand Est, Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre for Energy and Environment (CERI EE), Institut Mines-Télécom [Paris] (IMT), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Chimie Atmosphérique Expérimentale (CAE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Agence Nationale pour la Gestion des Déchets Radioactifs (ANDRA), Atmo Sud, LIG'AIR- Surveillance de la Qualité de l'Air en Région Centre, Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre for Energy and Environment (CERI EE - IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), and Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, 01 natural sciences, GEOF, lcsh:Chemistry, Atmosphere, chemistry.chemical_compound, Abundance (ecology), Arabitol, medicine, [CHIM]Chemical Sciences, Organic matter, Sugar, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, french sites, chemistry.chemical_classification, polyols, 15. Life on land, Particulates, primary biogenic organic aerosol, lcsh:QC1-999, Aerosol, tracers, lcsh:QD1-999, chemistry, 13. Climate action, [SDU]Sciences of the Universe [physics], Environmental chemistry, [SDE]Environmental Sciences, Environmental science, Mannitol, lcsh:Physics, medicine.drug
Abstract

A growing number of studies are using specific primary sugar species, such as sugar alcohols or primary saccharides, as marker compounds to characterize and apportion primary biogenic organic aerosols (PBOAs) in the atmosphere. To better understand their annual cycles, as well as their spatiotemporal abundance in terms of concentrations and sources, we conducted a large study focusing on three major atmospheric primary sugar compounds (i.e., arabitol, mannitol, and glucose) measured in various environmental conditions for about 5300 filter samples collected at 28 sites in France. Our results show significant atmospheric concentrations of polyols (defined here as the sum of arabitol and mannitol) and glucose at each sampling location, highlighting their ubiquity. Results also confirm that polyols and glucose are mainly associated with the coarse rather than the fine aerosol mode. At nearly all sites, atmospheric concentrations of polyols and glucose display a well-marked seasonal pattern, with maximum concentrations from late spring to early autumn, followed by an abrupt decrease in late autumn, and a minimum concentration during wintertime. Such seasonal patterns support biogenic emissions associated with higher biological metabolic activities (sporulation, growth, etc.) during warmer periods. Results from a previous comprehensive study using positive matrix factorization (PMF) based on an extended aerosol chemical composition dataset of up to 130 species for 16 of the same sample series have also been used in the present work. The polyols-to-PMPBOA ratio is 0.024±0.010 on average for all sites, with no clear distinction between traffic, urban, or rural typology. Overall, even if the exact origin of the PBOA source is still under investigation, it appears to be an important source of particulate matter (PM), especially during summertime. Results also show that PBOAs are significant sources of total organic matter (OM) in PM10 (13±4 % on a yearly average, and up to 40 % in some environments in summer) at most of the investigated sites. The mean PBOA chemical profile is clearly dominated by contribution from OM (78±9 % of the mass of the PBOA PMF on average), and only a minor contribution from the dust class (3±4 %), suggesting that ambient polyols are most likely associated with biological particle emissions (e.g., active spore discharge) rather than soil dust resuspension.

Published
2019
Full Text
View/download PDF

16. Investigation of the geographical origins of PM10 based on long, medium and short-range air mass back-trajectories impacting Northern France during the period 2009–2013

Author

Sandra Vermeesch, Vincent Michoud, Antoine Waked, Esperanza Perdrix, Jean-Eudes Petit, Stéphane Sauvage, Véronique Riffault, Laurent Y. Alleman, Aude Bourin, Tiphaine Delaunay, Centre for Energy and Environment (CERI EE), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut Mines-Télécom [Paris] (IMT), ATMO Hauts de France [Lille], Atmo Grand Est, Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), École des Mines de Douai (Mines Douai EMD), Département S.A.G.E (SAGE), Laboratoire d'écologie des hydrosystèmes (LEH), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Centre de Recherche en Cancérologie Nantes-Angers (CRCNA), Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM)-Hôtel-Dieu de Nantes-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Laennec-Centre National de la Recherche Scientifique (CNRS)-Faculté de Médecine d'Angers-Centre hospitalier universitaire de Nantes (CHU Nantes), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Planetary boundary layer, 010501 environmental sciences, 01 natural sciences, [SDE.ES]Environmental Sciences/Environmental and Society, Field (geography), Altitude, Megacity, 13. Climate action, Range (statistics), Environmental science, Parametrization (atmospheric modeling), Physical geography, Emission inventory, Air mass, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science
Abstract

Trajectory-based statistical models (TMs) are widely used to locate source areas responsible for atmospheric pollution at receptor sites. In order to study the influence of long, medium and short-range back-trajectories (BTs) on geographical sources location, an original approach was applied to daily PM10 concentrations measured for 5 years (2009–2013) at 12 receptor sites in the Hauts-de-France (HdF) region bounded on the south by the Paris megacity and on the north by the Benelux countries. The methodology used was based on two complementary TMs, Concentration Field (CF) and Potential Source Contribution Function (PSCF), and included several meaningful constraints in order to improve the spatial representativeness and the statistical significance of the potential source maps. The selection of BTs depending on the occurrence of scavenging precipitations (>1 mm h−1) during the transport of air masses and altitude limitations with respect to the planetary boundary layer height led to more realistic maps. The variability of the density of BT endpoints was accounted for by a weighting function which highlighted medium-distant yet recurring (e.g. Benelux and West of Germany) potential sources of PM10. Investigating the effect of short-range BTs (75% of endpoints within a radius of 500 km from the receptor sites) pointed out at nearby large conurbations (Lille and Paris areas). Comparing our potential source maps with European PM10 emission inventory maps as well as PM10 measurements at European background monitoring stations for similar periods confirmed our results for Central Europe, the Benelux and the East of Germany. This study showed how the combination of several receptor sites enables the determination of potential source areas impacting a whole region. It pointed out also that the fine-tuned parametrization of the CF and PSCF TMs may considerably help improving the knowledge on geographical location of sources related to long, medium and short-range BTs and could be easily implemented for other regions of interest.

Published
2018
Full Text
View/download PDF

17. Etude des déterminants des concentrations en PM10 dans le nord de la France

Author

Oliveira, Diogo Miguel, Perdrix, Esperanza, Sauvage, Stephane, Favez, Olivier, Riffault, Véronique, Alleman, Laurent, Bonnaire, Nicolas, Delaunay, Tiphaine, Rocq, Benoit, Chretien, Eve, Lemeur, Sébastien, Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT), Centre for Energy and Environment (CERI EE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ATMO Hauts de France [Lille], Atmo Grand Est, Atmo Normandie, Centre for Energy and Environment (CERI EE - IMT Nord Europe), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Nord Europe), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDE.MCG]Environmental Sciences/Global Changes, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2017

18. Modelling oxidative potential of atmospheric particle: A 2-year study over France.

Author

Vida M, Foret G, Siour G, Jaffrezo JL, Favez O, Cholakian A, Cozic J, Dupont H, Gille G, Oppo S, Zhang S, Francony F, Pallares C, Conil S, Uzu G, and Beekmann M

Abstract

The oxidative potential (OP) of particulate matter (PM) has emerged as a promising indicator of the adverse effects of PM on human health. In particular, OP is an indicator for oxidative stress in biological media through formation of reactive oxygen species. To provide a mapping of the spatial and temporal OP variability over France, we have developed a strategy to simulate the volume-normalized oxidative potential (OP v ) in the state-of-the-art CHIMERE air quality model over the metropolitan French territory for the years 2013 and 2014. To do so, we combined a measurement-derived and source specific intrinsic OP (OP i ) receptor modelling approach with Particle Source Apportionment Technology (PSAT) in CHIMERE. First, the model's ability to reproduce PM 10 concentrations and speciation was verified using in situ observations in mainland France. Furthermore, a mostly satisfying correspondence between receptor model and PSAT outputs was obtained considering their source specific chemical profiles. Simulated versus observed OP v values showed median correlations ranging from 0.35 to 0.60 and mean fractional biases from -30 % to zero, depending on the OP assay considered (ascorbic acid AA, or dithiothreitol DTT) and the PM sources taken into account (i.e. two methods with different PM sources have been used, the reduced and the extended set methods). The modelled two-year average OP v fields show greater spatial hot spots over large urban areas (especially along roadsides) compared to those for PM 10 distributions, due to elevated intrinsic OP i values for the primary anthropogenic sources such as traffic and biomass burning. These effects are stronger for the AA compared to the DTT assays, and for a method with a reduced set compared to an extended set of sources. Overall, through the OP apportionment, these results advocate for reinforcing action plans to reduce emissions from road traffic as well as biomass burning emissions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Reports a relationship with that includes:. Has patent pending to. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2025
Full Text
View/download PDF

19. Variability of ambient air ammonia in urban Europe (Finland, France, Italy, Spain, and the UK).

Author

Liu X, Lara R, Dufresne M, Wu L, Zhang X, Wang T, Monge M, Reche C, Di Leo A, Lanzani G, Colombi C, Font A, Sheehan A, Green DC, Makkonen U, Sauvage S, Salameh T, Petit JE, Chatain M, Coe H, Hou S, Harrison R, Hopke PK, Petäjä T, Alastuey A, and Querol X

Subjects
Ammonia analysis, Spain, Finland, Europe, France, Italy, Environmental Monitoring methods, United Kingdom, Air Pollutants analysis, Air Pollution analysis
Abstract

This study addressed the scarcity of NH 3 measurements in urban Europe and the diverse monitoring protocols, hindering direct data comparison. Sixty-nine datasets from Finland, France, Italy, Spain, and the UK across various site types, including industrial (IND, 8), traffic (TR, 12), urban (UB, 22), suburban (SUB, 12), and regional background (RB, 15), are analyzed to this study. Among these, 26 sites provided 5, or more, years of data for time series analysis. Despite varied protocols, necessitating future harmonization, the average NH 3 concentration across sites reached 8.0 ± 8.9 μg/m 3 . Excluding farming/agricultural hotspots (FAHs), IND and TR sites had the highest concentrations (4.7 ± 3.2 and 4.5 ± 1.0 μg/m 3 ), followed by UB, SUB, and RB sites (3.3 ± 1.5, 2.7 ± 1.3, and 1.0 ± 0.3 μg/m 3 , respectively) indicating that industrial, traffic, and other urban sources were primary contributors to NH 3 outside FAH regions. When referring exclusively to the FAHs, concentrations ranged from 10.0 ± 2.3 to 15.6 ± 17.2 μg/m 3 , with the highest concentrations being reached in RB sites close to the farming and agricultural sources, and that, on average for FAHs there is a decreasing NH 3 concentration gradient towards the city. Time trends showed that over half of the sites (18/26) observed statistically significant trends. Approximately 50 % of UB and TR sites showed a decreasing trend, while 30 % an increasing one. Meta-analysis revealed a small insignificant decreasing trend for non-FAH RB sites. In FAHs, there was a significant upward trend at a rate of 3.51[0.45,6.57]%/yr. Seasonal patterns of NH 3 concentrations varied, with urban areas experiencing fluctuations influenced by surrounding emissions, particularly in FAHs. Diel variation showed differing patterns at urban monitoring sites, all with higher daytime concentrations, but with variations in peak times depending on major emission sources and meteorological patterns. These results offer valuable insights into the spatio-temporal patterns of gas-phase NH 3 concentrations in urban Europe, contributing to future efforts in benchmarking NH 3 pollution control in urban areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Published
2024
Full Text
View/download PDF

20. Improvement of downscaled ozone concentrations from the transnational scale to the kilometric scale: Need, interest and new insights.

Author

Gauthier-Manuel H, Mauny F, Boilleaut M, Ristori M, Pujol S, Vasbien F, Parmentier AL, and Bernard N

Subjects
Environmental Monitoring methods, Air Pollutants analysis, Air Pollution analysis, Ozone analysis
Abstract

Background: Ground-level ozone is a major public health issue worldwide. An accurate assessment of ozone exposure is necessary. Modeling tools have been developed to tackle this issue in large areas. However, these models could present inaccuracies at the local scale., Objectives: The objective of this study was i) to assess whether O 3 concentrations estimated by transnational modeling at the kilometric scale (9 km 2 ) could be improved, ii) to propose a potential correction of these downscaled ozone concentrations and iii) to evaluate the efficiency and applicability of such a correction., Method: The present work was carried out in three phases. First, the performance of a transnational modeling platform (PREV'EST) was assessed at 6 geographic points by comparison with data from 6 air quality monitoring stations. Performance indicators were used for this purpose (MBE (mean bias error), MAE (mean absolute error), RMSE (root mean square error), r (Pearson correlation coefficient), and target plots). Second, several corrections were developed using MARS (multivariate adaptive regression splines) and integrating different sets of variables (mean temperature, relative humidity, rainfall amount, wind speed, elevation, and date). Their performance was evaluated. Third, external validation of the corrections was conducted using the data from six additional air quality monitoring stations., Results: The uncorrected PREV'EST model presented a lack of exactitude and precision. These concentrations did not reproduce the interday variability of the measurements, leading to a lack of temporal contrast in exposure data. For the best performance enhancement, the correction applied improved MBE, MAE, RMSE and r from 14.67, 19.23, 23.18 and 0.67 to 0.00, 8.00, 10.19 and 0.91, respectively. External validation confirmed the efficiency of the corrections at the regional scale., Conclusions: We propose a validated and efficient methodology integrating local environmental variables. The methodology is adaptable according to the context, needs and data available., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Published
2022
Full Text
View/download PDF

21. Maternal Ambient Exposure to Atmospheric Pollutants during Pregnancy and Offspring Term Birth Weight in the Nationwide ELFE Cohort.

Author

Ouidir M, Seyve E, Rivière E, Bernard J, Cheminat M, Cortinovis J, Ducroz F, Dugay F, Hulin A, Kloog I, Laborie A, Launay L, Malherbe L, Robic PY, Schwartz J, Siroux V, Virga J, Zaros C, Charles MA, Slama R, and Lepeule J

Subjects
Birth Weight, Child, Female, Humans, Longitudinal Studies, Maternal Exposure adverse effects, Nitrogen Dioxide analysis, Nitrogen Dioxide toxicity, Particulate Matter analysis, Particulate Matter toxicity, Pregnancy, Air Pollutants analysis, Air Pollutants toxicity, Air Pollution adverse effects, Air Pollution analysis, Environmental Pollutants
Abstract

Background: Studies have reported associations between maternal exposure to atmospheric pollution and lower birth weight. However, the evidence is not consistent and uncertainties remain. We used advanced statistical approaches to robustly estimate the association of atmospheric pollutant exposure during specific pregnancy time windows with term birth weight (TBW) in a nationwide study., Methods: Among 13,334 women from the French Longitudinal Study of Children (ELFE) cohort, exposures to PM 2.5 , PM 10 (particles < 2.5 µm and <10 µm) and NO 2 (nitrogen dioxide) were estimated using a fine spatio-temporal exposure model. We used inverse probability scores and doubly robust methods in generalized additive models accounting for spatial autocorrelation to study the association of such exposures with TBW., Results: First trimester exposures were associated with an increased TBW. Second trimester exposures were associated with a decreased TBW by 17.1 g (95% CI, -26.8, -7.3) and by 18.0 g (-26.6, -9.4) for each 5 µg/m 3 increase in PM 2.5 and PM 10 , respectively, and by 15.9 g (-27.6, -4.2) for each 10 µg/m 3 increase in NO 2 . Third trimester exposures (truncated at 37 gestational weeks) were associated with a decreased TBW by 48.1 g (-58.1, -38.0) for PM 2.5 , 38.1 g (-46.7, -29.6) for PM 10 and 14.7 g (-25.3, -4.0) for NO 2 . Effects of pollutants on TBW were larger in rural areas., Conclusions: Our results support an adverse effect of air pollutant exposure on TBW. We highlighted a larger effect of air pollutants on TBW among women living in rural areas compared to women living in urban areas.

Published
2021
Full Text
View/download PDF

22. Prioritizing the provision of urban ecosystem services in deprived areas, a question of environmental justice.

Author

Selmi W, Selmi S, Teller J, Weber C, Rivière E, and Nowak DJ

Subjects
Cities, France, Trees, Air Pollution, Ecosystem
Abstract

The distribution of urban ecosystem services (UES) is often uneven across socioeconomic groups, leading to environmental justice issues. Understanding the distribution of UES across a landscape can help managers ensure an equitable distribution of services. While many past studies have focused on the distribution of green spaces in relation to socioeconomic variables, this research analyzes the distribution of UES provided by these green spaces. This research quantified air pollution removal, atmospheric carbon reduction, and surface runoff mitigation provided by urban trees in Strasbourg city (France). The provision of these three UES was studied at the census block scale by creating an index of UES delivery, which was contrasted with a constructed social deprivation index. Our results show that there is no significant association between the delivery of UES and social deprivation. Some deprived populations benefit from high UES delivery. Results also suggest that mapping associations between UES delivery and social deprivation should be integrated with future development plans to enhance the equitable distribution of UES. This study provides insights into the French context where studies about the distribution of UES at a small-area level remain lacking.

Published
2021
Full Text
View/download PDF

23. Substantial brown carbon emissions from wintertime residential wood burning over France.

Author

Zhang Y, Albinet A, Petit JE, Jacob V, Chevrier F, Gille G, Pontet S, Chrétien E, Dominik-Sègue M, Levigoureux G, Močnik G, Gros V, Jaffrezo JL, and Favez O

Abstract

Brown carbon (BrC) is known to absorb light at subvisible wavelengths but its optical properties and sources are still poorly documented, leading to large uncertainties in climate studies. Here, we show its major wintertime contribution to total aerosol absorption at 370 nm (18-42%) at 9 different French sites. Moreover, an excellent correlation with levoglucosan (r 2  = 0.9 and slope = 22.2 at 370 nm), suggesting important contribution of wood burning emissions to ambient BrC aerosols in France. At all sites, BrC peaks were mainly observed during late evening, linking to local intense residential wood burning during this time period. Furthermore, the geographic origin analysis also highlighted the high potential contribution of local and/or small-regional emissions to BrC. Focusing on the Paris region, twice higher BrC mass absorption efficiency value was obtained for less oxidized biomass burning organic aerosols (BBOA) compared to more oxidized BBOA (e.g., about 4.9 ± 0.2 vs. 2.0 ± 0.1 m 2  g - 1 , respectively, at 370 nm). Finally, the BBOA direct radiative effect was found to be 40% higher when these two BBOA fractions are treated as light-absorbing species, compared to the non-absorbing BBOA scenario., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Griša Močnik was employed by the manufacturer of the AE33 during the measurements, but not during the data analysis or writing of the manuscript., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2020
Full Text
View/download PDF

24. Short-Term Effects of Air Pollution on Coronary Events in Strasbourg, France-Importance of Seasonal Variations.

Author

Vaudrey B, Mielcarek M, Sauleau E, Meyer N, Marchandot B, Moitry M, Robellet P, Reeb T, Jesel L, Ohlmann P, Bourdrel T, and Morel O

Abstract

The aim of this study, is to investigate the effects of a short-term exposure to air pollutants, as assessed by Nitrogen dioxide (NO 2 ), Particulate Matter PM 2,5 and PM 10 concentrations, on coronary event onsets in Strasbourg, France. An observational, analytical, retrospective, epidemiological study was conducted in Strasbourg between 1 January 2012 and 31 December 2014. Higher daily coronary events rates were evidenced when NO 2 concentrations were measured above 40 µg/m 3 (1.258 (95% CI 1.142-1.374) vs. 1.110 (95% CI 1.033-1.186); p = 0.015). The NO 2 concentration was higher than 30 µg/m 3 for 677 days (61.8%). Higher daily coronary events rates were evidenced when NO 2 concentrations were measured above 30 µg/m 3 (1.208 (95% CI 1.128-1.289) vs. 1.067 (95% CI 0.961-1.172) p = 0.009). A marked seasonality of NO 2 , PM 2.5 , and PM 10 concentrations characterized by an increase during winter and a decrease during the summer could be established. The seasonality of coronary events was evidenced simultaneously. After adjustments were made to account for the time and the month, no independent impact of NO 2 , PM 2.5 or PM 10 on daily coronary events could be demonstrated.

Published
2020
Full Text
View/download PDF

25. [Outdoor pollution and its effects on lung health in France. Expert document from the Groupe Pathologies pulmonaires professionnelles environnementales et iatrogéniques (PAPPEI) of the Société de pneumologie de langue française (SPLF)].

Author

Caillaud D, Annesi-Maesano I, Bourin A, Chinet T, Colette A, De Blay F, Dixsaut G, Housset B, Kleinpeter J, Malherbe L, Roussel I, Dalphin JC, and Charpin D

Subjects
Climate Change, Environmental Illness epidemiology, Environmental Monitoring methods, Environmental Monitoring standards, Environmental Pollution analysis, Environmental Pollution prevention & control, Environmental Pollution statistics & numerical data, France epidemiology, Government Regulation, Humans, Iatrogenic Disease, Legislation, Medical organization & administration, Legislation, Medical standards, Legislation, Medical trends, Lung Diseases epidemiology, Occupational Diseases epidemiology, Occupational Diseases prevention & control, Pulmonary Medicine methods, Pulmonary Medicine organization & administration, Pulmonary Medicine trends, Societies, Medical organization & administration, Societies, Medical standards, Environmental Illness etiology, Environmental Pollution adverse effects, Lung Diseases etiology, Occupational Diseases etiology, Pulmonary Medicine standards
Published
2019
Full Text
View/download PDF

26. Is atmospheric pollution exposure during pregnancy associated with individual and contextual characteristics? A nationwide study in France.

Author

Ouidir M, Lepeule J, Siroux V, Malherbe L, Meleux F, Rivière E, Launay L, Zaros C, Cheminat M, Charles MA, and Slama R

Subjects
Adult, Child, Cohort Studies, Female, France, Humans, Male, Maternal Exposure, Nitrogen Dioxide adverse effects, Particulate Matter adverse effects, Pregnancy, Pregnant People, Rural Population, Urban Population, Vehicle Emissions, Air Pollutants adverse effects, Environmental Exposure adverse effects, Environmental Pollution adverse effects, Residence Characteristics, Socioeconomic Factors, Urbanization
Abstract

Background: Exposure to atmospheric pollutants is a danger for the health of pregnant mother and children. Our objective was to identify individual (socioeconomic and behavioural) and contextual factors associated with atmospheric pollution pregnancy exposure at the nationwide level., Method: Among 14 921 women from the French nationwide ELFE (French Longitudinal Study of Children) mother-child cohort recruited in 2011, outdoor exposure levels of PM 2.5 , PM 10 (particulate matter <2.5 µm and <10 µm in diameter) and NO 2 (nitrogen dioxide) were estimated at the pregnancy home address from a dispersion model with 1 km resolution. We used classification and regression trees (CART) and linear regression to characterise the association of atmospheric pollutants with individual (maternal age, body mass index, parity, education level, relationship status, smoking status) and contextual (European Deprivation Index, urbanisation level) factors., Results: Patterns of associations were globally similar across pollutants. For the CART approach, the highest tertile of exposure included mainly women not in a relationship living in urban and socially deprived areas, with lower education level. Linear regression models identified different determinants of atmospheric pollutants exposure according to the residential urbanisation level. In urban areas, atmospheric pollutants exposure increased with social deprivation, while in rural areas a U-shaped relationship was observed., Conclusion: We highlighted social inequalities in atmospheric pollutants exposure according to contextual characteristics such as urbanisation level and social deprivation and also according to individual characteristics such as education, being in a relationship and smoking status. In French urban areas, pregnant women from the most deprived neighbourhoods were those most exposed to health-threatening atmospheric pollutants., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Published
2017
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results