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9 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
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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
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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
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4. 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
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5. 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
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6. 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
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7. 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
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8. 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
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9. 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
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