Author: "Frédérik Meleux" - Searchworks@Jio Institute Digital Library Search Results

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53 results on '"Frédérik Meleux"'

1. Long-term health impact assessment of total PM2.5 in Europe during the 1990–2015 period

Author: Giancarlo Ciarelli, Augustin Colette, Simone Schucht, Matthias Beekmann, Camilla Andersson, Astrid Manders-Groot, Mihaela Mircea, Svetlana Tsyro, Hilde Fagerli, Alberto González Ortiz, Mario Adani, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Cornelis Cuvelier, Florian Couvidat, Frédérik Meleux, and Bertrand Bessagnet
Subjects: Environmental pollution, TD172-193.5, Meteorology. Climatology, QC851-999
Abstract: Several datasets of PM2.5 concentrations over Europe during the 1990–2015 period, were used to calculate health impacts from chronic exposure to total particle matter below 2.5 μm (i.e. PM2.5). The datasets used in the analysis include the European Topic Centre on Air Pollution and Climate Change Mitigation (ETC/ACM), the Copernicus Atmospheric Monitoring Service (CAMS), the Global Burden of Disease (GBD), the World Health Organization (WHO) as well as the EURODELTA-Trends (EDT) multi-model reanalysis developed specifically for Europe.The exposure to ambient PM2.5 concentrations was calculated as population weighted annual average PM2.5 concentrations by country. The calculated exposure to PM2.5 was later used as input in the health impact assessment (HIA) Alpha-RiskPoll (ARP) tool to retrieve the total number of premature deaths.Our results indicate a substantial reduction in the number of premature deaths from PM2.5 exposure in Europe over the 1990–2010 period, between nearly 30 and 50%. Putting all the data-sets together, even if they do not cover the whole period, a decrease of even around 60% is observed between 1990 and 2015. For the countries included in this study, the estimated number of premature deaths from PM2.5 in 1990 was found to be around 960 000 (median of all the available datasets), whereas in 2015 it was found to be around 445 000. However, the variability in the estimated premature deaths from the different PM2.5 datasets was found to be large during the early 90s (around a factor of 2). For the latest years of the investigated period (2005 onwards), where a relatively flat trend in the PM2.5 exposure was observed, the differences between the different datasets were smaller.Even though our results indicate a reduction in the number of premature deaths from chronic exposure to PM2.5, the numbers remain considerable in 2015, underlining the need to continue improving air quality in the future. Keywords: PM2.5, Health impact assessment, Exposure to air pollution, Chemical transport models
Published: 2019
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2. Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe

Author: Laurent Menut, Dmitry Khvorostyanov, Florian Couvidat, and Frédérik Meleux
Subjects: pollen, ragweed, transport, regional, modelling, CHIMERE, Meteorology. Climatology, QC851-999
Abstract: This study is dedicated to improving the daily release of ragweed pollen emission in the context of deterministic regional modelling for analysis and forecast. First, correlations are calculated between daily modelled meteorological variables (wind speed, temperature, humidity, precipitation, surface fluxes) and daily pollen counts at nine stations in Hungary, Croatia and France between 2005 and 2011. The 2 m temperature is the most correlated parameter, followed by convective velocity and incoming shortwave radiation, while precipitation rate and 2 m specific humidity act as limiting factors. Using these results, a ragweed pollen daily release formulation is proposed. This formulation is implemented in the CHIMERE chemistry-transport model and tested during the whole year of 2010. Results are compared to observations, and it is shown that the new formulation provides a more realistic day-to-day variability: the spatio-temporal correlation between surface measurements and modelled concentrations is 0.77, greater than two other known emission schemes.
Published: 2021
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3. Is the ozone climate penalty robust in Europe?

Author: Augustin Colette, Camilla Andersson, Alexander Baklanov, Bertrand Bessagnet, Jørgen Brandt, Jesper H Christensen, Ruth Doherty, Magnuz Engardt, Camilla Geels, Christos Giannakopoulos, Gitte B Hedegaard, Eleni Katragkou, Joakim Langner, Hang Lei, Astrid Manders, Dimitris Melas, Frédérik Meleux, Laurence Rouïl, Mikhail Sofiev, Joana Soares, David S Stevenson, Maria Tombrou-Tzella, Konstantinos V Varotsos, and Paul Young
Subjects: pollution, climate change, ozone, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: Ozone air pollution is identified as one of the main threats bearing upon human health and ecosystems, with 25 000 deaths in 2005 attributed to surface ozone in Europe (IIASA 2013 TSAP Report #10). In addition, there is a concern that climate change could negate ozone pollution mitigation strategies, making them insufficient over the long run and jeopardising chances to meet the long term objective set by the European Union Directive of 2008 ( Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 ) (60 ppbv, daily maximum). This effect has been termed the ozone climate penalty. One way of assessing this climate penalty is by driving chemistry-transport models with future climate projections while holding the ozone precursor emissions constant (although the climate penalty may also be influenced by changes in emission of precursors). Here we present an analysis of the robustness of the climate penalty in Europe across time periods and scenarios by analysing the databases underlying 11 articles published on the topic since 2007, i.e. a total of 25 model projections. This substantial body of literature has never been explored to assess the uncertainty and robustness of the climate ozone penalty because of the use of different scenarios, time periods and ozone metrics. Despite the variability of model design and setup in this database of 25 model projection, the present meta-analysis demonstrates the significance and robustness of the impact of climate change on European surface ozone with a latitudinal gradient from a penalty bearing upon large parts of continental Europe and a benefit over the North Atlantic region of the domain. Future climate scenarios present a penalty for summertime (JJA) surface ozone by the end of the century (2071–2100) of at most 5 ppbv. Over European land surfaces, the 95% confidence interval of JJA ozone change is [0.44; 0.64] and [0.99; 1.50] ppbv for the 2041–2070 and 2071–2100 time windows, respectively.
Published: 2015
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4. Technical note: Improving the European air quality forecast of the Copernicus Atmosphere Monitoring Service using machine learning techniques

Author: Jean-Maxime Bertrand, Frédérik Meleux, Anthony Ung, Gaël Descombes, and Augustin Colette
Subjects: Atmospheric Science
Abstract: Model output statistics (MOS) approaches relying on machine learning algorithms were applied to downscale regional air quality forecasts produced by CAMS (Copernicus Atmosphere Monitoring Service) at hundreds of monitoring sites across Europe. Besides the CAMS forecast, the predictors in the MOS typically include meteorological variables but also ancillary data. We explored first a “local” approach where specific models are trained at each site. An alternative “global” approach where a single model is trained with data from the whole geographical domain was also investigated. In both cases, local predictors are used for a given station in predictive mode. Because of its global nature, the latter approach can capture a variety of meteorological situations within a very short training period and is thereby more suited to cope with operational constraints in relation to the training of the MOS (frequent upgrades of the modelling system, addition of new monitoring sites). Both approaches have been implemented using a variety of machine learning algorithms: random forest, gradient boosting, and standard and regularized multi-linear models. The quality of the MOS predictions is evaluated in this work for four key pollutants, namely particulate matter (PM10 and PM2.5), ozone (O3) and nitrogen dioxide (NO2), according to scores based on the predictive errors and on the detection of pollution peaks (exceedances of the regulatory thresholds). Both the local and the global approaches significantly improve the performances of the raw ensemble forecast. The most important result of this study is that the global approach competes with and can even outperform the local approach in some cases. This global approach gives the best RMSE scores when relying on a random forest model for the prediction of daily mean, daily max and hourly concentrations. By contrast, it is the gradient boosting model which is better suited for the detection of exceedances of the European Union regulated threshold values for O3 and PM10.
Published: 2023

5. Technical note: Improving the European air quality forecast of Copernicus Atmosphere Monitoring Service using machine learning techniques

Author: Jean-Maxime Bertrand, Frédérik Meleux, Anthony Ung, Gaël Descombes, and Augustin Colette
Abstract: Model Output Statistics (MOS) approaches relying on machine learning algorithms were applied to downscale regional air quality forecasts produced by CAMS (Copernicus Atmosphere Monitoring Service) at hundreds of monitoring sites across Europe. Besides the CAMS forecast, the predictors in the MOS typically include meteorological variables but also ancillary data. We explored first a “local” approach where specific models are trained at each site. An alternative “global” approach where a single model is trained with data from the whole geographical domain was also investigated. In both cases, local predictors are used for a given station in predictive mode. Because of its global nature, the latter approach can capture a variety of meteorological situation within a very short training period and is thereby more suited to cope with operational constraints in relation with the training of the MOS (frequent upgrades of the modelling system, addition of new monitoring sites). Both approaches have been implemented using a variety of machine learning algorithms: random forest, gradient boosting, standard and regularized multi-linear models. The quality of the MOS predictions is evaluated in this work for four key pollutants, namely particulate matter PM10 and PM2.5, ozone O3 and nitrogen dioxide NO2, according to scores based on the predictive errors and on the detection of pollution peaks (exceedances of the regulatory thresholds). Both the local and the global approaches significantly improve the performances of the raw Ensemble forecast. The most important result of this study is that the global approach competes with and can even outperform the local approach in some cases. This global approach gives the best RMSE scores when relying on a random forest model, for the prediction of daily mean, daily max and hourly concentrations. By contrast, it is the gradient boosting model which is better suited for the detection of exceedances of the European Union regulated threshold values for O3 and PM10.
Published: 2022
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6. Estimating lockdown-induced European NO2 changes using satellite and surface observations and air quality models

Author: Marc Guevara, Renske Timmermans, Mathieu Joly, Laurence Rouil, Frédérik Meleux, Lennart Robertson, Richard Engelen, Svetlana Tsyro, Carlos Pérez García-Pando, Hervé Petetin, Michael Gauss, Mario Adani, Anna Benedictow, Dene Bowdalo, John Douros, Camilla Geels, Jacek W. Kaminski, Oriol Jorba, Rostislav Kouznetsov, Johannes Flemming, Antje Inness, Joanna Struzewska, Jesper H. Christensen, Augustin Colette, E. Friese, Jerome Barre, and Vincent-Henri Peuch
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Coronavirus disease 2019 (COVID-19), Sampling (statistics), 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Atmosphere, Troposphere, 13. Climate action, 11. Sustainability, Environmental science, Satellite, Gradient boosting, Air quality index, 0105 earth and related environmental sciences
Abstract: This study provides a comprehensive assessment of NO2 changes across the main European urban areas induced by COVID-19 lockdowns using satellite retrievals from the Tropospheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5p satellite, surface site measurements, and simulations from the Copernicus Atmosphere Monitoring Service (CAMS) regional ensemble of air quality models. Some recent TROPOMI-based estimates of changes in atmospheric NO2 concentrations have neglected the influence of weather variability between the reference and lockdown periods. Here we provide weather-normalized estimates based on a machine learning method (gradient boosting) along with an assessment of the biases that can be expected from methods that omit the influence of weather. We also compare the weather-normalized satellite-estimated NO2 column changes with weather-normalized surface NO2 concentration changes and the CAMS regional ensemble, composed of 11 models, using recently published estimates of emission reductions induced by the lockdown. All estimates show similar NO2 reductions. Locations where the lockdown measures were stricter show stronger reductions, and, conversely, locations where softer measures were implemented show milder reductions in NO2 pollution levels. Average reduction estimates based on either satellite observations (−23 %), surface stations (−43 %), or models (−32 %) are presented, showing the importance of vertical sampling but also the horizontal representativeness. Surface station estimates are significantly changed when sampled to the TROPOMI overpasses (−37 %), pointing out the importance of the variability in time of such estimates. Observation-based machine learning estimates show a stronger temporal variability than model-based estimates.
Published: 2021
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7. Improvement of the Vertical Mixing in Chemistry Transport Modeling Based on a 1.5-Order Turbulence Kinetic Energy-Based Eddy Diffusivity Closure Scheme

Author: Lei Jiang, Bertrand Bessagnet, Frédérik Meleux, Florian Couvidat, and Frédéric Tognet
Subjects: Atmospheric Science
Published: 2022
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8. What Can We Expect from Data Assimilation for Air Quality Forecast? Part II: Analysis with a Semi-Real Case

Author: Laurent Menut, Florian Couvidat, Frédérik Meleux, Bertrand Bessagnet, Sylvain Mailler, Guillaume Siour, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, AIR QUALITY, Air pollution, Ocean Engineering, ATMOSPHERIC COMPOSITION, 010501 environmental sciences, medicine.disease_cause, 01 natural sciences, Atmospheric composition, DATA ASSIMILATION, AIR POLLUTION, Data assimilation, REGIONAL MODELS, 13. Climate action, FORECASTING, [SDE]Environmental Sciences, medicine, Environmental science, Air quality index, 0105 earth and related environmental sciences
Abstract: Assimilation of observational data from ground stations and satellites has been identified as a technique to improve air quality model results. This study is an evaluation of the maximum benefit expected from data assimilation in chemical transport models. Various tests are performed under real meteorological conditions; the injection of various subsets of “simulated observational data” at the initial state of a forecasting period is analyzed in terms of benefit on selected criteria. This observation dataset is generated by a simulation with perturbed input data. Several criteria are defined to analyze the simulations leading to the definition of a “tipping time” to compare the behavior of simulations. Assimilating three-dimensional data instead of ground observations clearly adds value to the forecast. For the studied period and considering the expected best favorable data assimilation experiment, the maximum benefit is higher for particulate matter (PM) with tipping times exceeding 80 h; for ozone (O3) the gain is on average around 30 h. Assimilating O3 concentrations with a delta calculated on the first level and propagated over the vertical direction provides better results on O3 mean concentrations when compared with the expected best experiment corresponding to the injection of the O3 “observations” 3D dataset, but for maximum O3 concentrations the opposite behavior is observed. If data assimilation of secondary pollutant concentrations provides an improvement, assimilation of primary pollutant emissions can have beneficial impacts when compared with an assimilation of concentrations, after several days on secondary pollutants like O3 or nitrate concentrations and more quickly for the emitted primary pollutants. An assimilation of ammonia concentrations has slightly better performances on nitrate, ammonium, and PM concentrations relative to the assimilation of nitrogen or sulfur dioxides.
Published: 2019
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9. Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe

Author: Florian Couvidat, D. Khvorostyanov, Laurent Menut, Frédérik Meleux, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Processus et interactions de fine échelle océanique (PROTEO), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut National de l'Environnement Industriel et des Risques (INERIS), European Project: 282687,EC:FP7:ENV,FP7-ENV-2011,ATOPICA(2011), European Project: 607193,EC:FP7:SPA,FP7-SPACE-2013-1,UERRA(2014), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)
Subjects: Ragweed, Atmospheric Science, 010504 meteorology & atmospheric sciences, WRF, Context (language use), 010501 environmental sciences, Environmental Science (miscellaneous), medicine.disease_cause, Atmospheric sciences, 01 natural sciences, Wind speed, modelling, Pollen, Meteorology. Climatology, medicine, Shortwave radiation, Precipitation, ragweed, 0105 earth and related environmental sciences, biology, regional, Humidity, biology.organism_classification, regional modelling, 13. Climate action, Weather Research and Forecasting Model, pollen, transport, [SDE]Environmental Sciences, Environmental science, QC851-999, CHIMERE
Abstract: International audience This study is dedicated to improving the daily release of ragweed pollen emission in the context of deterministic regional modelling for analysis and forecast. First, correlations are calculated between daily modelled meteorological variables (wind speed, temperature, humidity, precipitation, surface fluxes) and daily pollen counts at nine stations in Hungary, Croatia and France between 2005 and 2011. The 2 m temperature is the most correlated parameter, followed by convective velocity and incoming shortwave radiation, while precipitation rate and 2 m specific humidity act as limiting factors. Using these results, a ragweed pollen daily release formulation is proposed. This formulation is implemented in the CHIMERE chemistry-transport model and tested during the whole year of 2010. Results are compared to observations, and it is shown that the new formulation provides a more realistic day-to-day variability: the spatio-temporal correlation between surface measurements and modelled concentrations is 0.77, greater than two other known emission schemes.
Published: 2021
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10. Supplementary material to 'Air Control Toolbox (ACT_v1.0): a machine learning flexible surrogate model to explore mitigation scenarios in air quality forecasts'

Author: Augustin Colette, Laurence Rouïl, Frédérik Meleux, Vincent Lemaire, and Blandine Raux
Published: 2021
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11. Air Control Toolbox (ACT_v1.0): a machine learning flexible surrogate model to explore mitigation scenarios in air quality forecasts

Author: Frédérik Meleux, Vincent Lemaire, Laurence Rouil, Augustin Colette, and Blandine Raux
Subjects: Flexibility (engineering), Computer science, business.industry, Air pollution, Grid, medicine.disease_cause, Machine learning, computer.software_genre, Toolbox, Surrogate model, medicine, Artificial intelligence, Sensitivity (control systems), User interface, business, Air quality index, computer
Abstract: We introduce the first toolbox that allows exploring the benefit of air pollution mitigation scenarios in the every-day air quality forecasts through a web interface. Chemistry-transport models (CTMs) are required to forecast air pollution episodes and assess the benefit that shall be expected from mitigation strategies. However, their complexity prohibits offering a high level of flexibility. The Air Control Toolbox relies on machine learning methods to cope with this limitation. It consists of a surrogate model trained on a limited set of sensitivity scenarios to allow exploring any combination of mitigation measures. As such we take the best of the physical and chemical complexity of CTMs, operated on high performance computers for the everyday forecast, but we approximate a simplified response function that can be operated through a website to emulate the main sensitivities of the atmospheric system for a given day and location. The numerical experimental plan to design the structure of the surrogate model is detailed by increasing level of complexity. The selected structure of the surrogate is a quadrivariate polynomial of first order for residential heating emissions, and second order for agriculture, industry and traffic emissions with three interaction terms. It is fitted to 12 sensitivity CTM simulations, at each grid point and every day for PM10, PM2.5, O3 (both as daily mean and daily maximum) and NO2. The validation study demonstrates that we can keep relative errors below 2 % at 95 % of the grid points and days for all pollutants. Various applications of the toolbox are presented for air quality episode analysis, source apportionment, and chemical regime analysis.
Published: 2021

12. Dispersion and impact of smoke plumes from industrial fires: the case of Lubrizol

Author: Benjamin Truchot, Laurence Rouil, Frédérik Meleux, Guillaume Leroy, Augustin Colette, Frédéric Tognet, and Institut National de l'Environnement Industriel et des Risques (INERIS)
Subjects: 13. Climate action, Health, Toxicology and Mutagenesis, pollution atmosphérique, [SDE]Environmental Sciences, Public Health, Environmental and Occupational Health, dispersion, incendie, modélisation, risques accidentels
Abstract: International audience; Cet article expose, à travers l’exemple des travaux scientifiques menés dans le cadre de la gestion de l’incendie de l’usine Lubrizol (Rouen) en septembre 2019, les enjeux associés à la modélisation de la dispersion des panaches de fumées générés par les accidents industriels de grande ampleur. Selon la nature des composés chimiques transportés par ces panaches, les conséquences en termes d’impacts environnementaux et sanitaires sont plus ou moins importantes et diffèrent dans l’espace et dans le temps. Nous proposons une classification des questionnements suscités par la gestion d’une situation d’urgence environnementale (phases accidentelle et post-accidentelle) et une revue des outils de simulation numériques mobilisables pour y répondre. La valeur ajoutée de ces modèles et leurs limites sont discutées. Le cas de l’incendie de Rouen en septembre 2019 est particulièrement instructif à ce titre puisque les différentes approches ont été mises en œuvre et questionnées par l’Institut national de l’environnement industriel et des risques (Ineris), qui fut mobilisé auprès des pouvoirs publics pendant toute la crise. Il a permis de mettre en exergue la maturité des modèles et leurs incertitudes pour simuler des conditions réelles, en particulier celles liées au terme source. De fait, leur mise en œuvre en situation d’urgence se justifie avant tout par une logique de surveillance des impacts plutôt que d’évaluation de risques.
Published: 2021
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13. Do alternative inventories converge on the spatiotemporal representation of spring ammonia emissions in France?

Author: Audrey Fortems-Cheiney, Lieven Clarisse, Sophie Genermont, Frédérik Meleux, Florian Couvidat, Gilles Foret, Jean-Marc Gilliot, Pierre-François Coheur, Guillaume Siour, Karine Dufosse, Cathy Clerbaux, Martin Van Damme, Gaëlle Dufour, Matthias Beekmann, Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut National de l'Environnement Industriel et des Risques (INERIS), Université libre de Bruxelles (ULB), 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 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), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), 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), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Amp'Air Project ADEME 1660C0013, PolQA Primequal Project 1662C0023, 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), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), and Laboratoire Interuniversitaire des Systèmes Atmosphériques, UMR CNRS 7583, Université Paris Est Créteil et Université de Paris, Institut Pierre Simon Laplace, Créteil, France
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, engineering.material, Atmospheric sciences, 01 natural sciences, lcsh:Chemistry, Phénomènes atmosphériques, Spring (hydrology), National level, Soil properties, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], geography, geography.geographical_feature_category, Particulates, lcsh:QC1-999, lcsh:QD1-999, 13. Climate action, Soil water, [SDE]Environmental Sciences, engineering, Environmental science, Stage (hydrology), Fertilizer, Scale (map), [CHIM.OTHE]Chemical Sciences/Other, lcsh:Physics
Abstract: Agriculture is the main source of ammonia (NH3) in France, an important gaseous precursor of atmospheric particulate matter (PM). National and global emission inventories are known to have difficulty representing the large spatial and temporal variability inherent to atmospheric NH3. In this study, we compare NH3 emissions in France during spring 2011 from one reference inventory, the TNO inventory, and two alternative inventories that account in different manners for both the spatial and temporal variabilities of the emissions: (i) the NH3SAT satellite-derived inventory based on IASI NH3 columns and (ii) the CADASTRE-CIT inventory that combines NH3 emissions due to nitrogen fertilization calculated with the mechanistic model VOLT'AIR on the database of the CADASTRE_NH3 framework and other source emissions from the CITEPA. The total spring budgets, from March to May 2011, at the national level are higher when calculated with both alternative inventories than with the reference, the difference being more marked with CADASTRE-CIT. NH3SAT and CADASTRE-CIT inventories both yield to large NH3 spring emissions due to fertilization on soils with high pH in the northeastern part of France (65 and 135 ktNH3, respectively, vs. 48 ktNH3 for TNO-GEN), while soil properties are not accounted for by the TNO-GEN methodology. For the other parts of France, the differences are smaller. The timing of fertilization and associated ammonia emissions is closely related to the nitrogen requirements and hence the phenological stage of the crops, and therefore to the crop year's specific weather conditions. Maximum emissions are observed in March for 2011 for some regions for both alternative inventories, while April is the period with maximum emissions for the reference inventory regardless of the region or the year. Comparing the inventories at finer temporal resolutions, typically at daily scale, large differences are found. The convergence of alternative, independent and complementary methods on the spatiotemporal representation of the spring NH3 emissions, particularly over areas where the contribution of mineral fertilizer spreading to the spring budget is strong, encourages further developments in both prospective complementary directions, as this will help improve national NH3 emission inventories., SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2020
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14. An additive geostatistical model for mixing total and partial PM10 observations with CHIMERE rCTM

Author: Chantal de Fouquet, Maxime Beauchamp, Laure Malherbe, Frédérik Meleux, Bertrand Bessagnet, Anthony Ung, Institut National de l'Environnement Industriel et des Risques (INERIS), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL), Centre de Géosciences (GEOSCIENCES), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
Subjects: Atmospheric Science, education.field_of_study, 010504 meteorology & atmospheric sciences, Population, Univariate, CHEMISTRY-TRANSPORT MODEL, COKRIGING, Particulates, Spatial distribution, 01 natural sciences, 010104 statistics & probability, PARTICULATE MATTER, 13. Climate action, Kriging, [SDE]Environmental Sciences, Statistics, Environmental science, Fraction (mathematics), Limit (mathematics), 0101 mathematics, education, Air quality index, 0105 earth and related environmental sciences, General Environmental Science
Abstract: International audience; European Legislation (Directive, 2008/50/EC) requires the Member State to identify the areas where limit or target values are exceeded and to estimate the population exposed to these exceedances. The monitoring network of particulate matter with diameter less than 10 μs (PM10) and 2.5 μm (PM2.5) is homogeneous enough in Western Europe to describe accurately their daily spatial distribution. Daily mapping is required to correctly quantify the population exposed to the exceedances. Geostatistical methods are commonly used in Air Quality to interpolate the observations by taking into account the spatial dependencies between the data. The case of particulate matter is specific: in addition to the total PM10 observations, there are, for historical reasons, measurements of the so-called non-volatile fraction of the particles. The non-volatile fraction dataset is corrected and used as an observation of the total PM applied for mapping. It provides therefore a meaningful information on the chemical composition of the particles. Along this line, PM2.5 data, which are a subset of PM10, also bring an important information on the spatial distribution of the PM10, and conversely. This work demonstrates the importance of keeping an information considered as secondary in the monitoring network and how it is possible to improve the estimation of PM concentrations. An additive modelling for PM10 and its subset is used to link the explanatory variables between them and the related cokriging is presented. Maps and scores are shown and confronted to univariate kriging estimations throughout the first three months of 2015 in metropolitan France.
Published: 2018
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15. Is atmospheric pollution exposure during pregnancy associated with individual and contextual characteristics? A nationwide study in France

Author: Cécile Zaros, Ludivine Launay, Frédérik Meleux, Marie Cheminat, Rémy Slama, Emmanuel Riviere, Johanna Lepeule, Valérie Siroux, Laure Malherbe, Marion Ouidir, Marie-Aline Charles, 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)-Centre National de la Recherche Scientifique (CNRS)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut National de l'Environnement Industriel et des Risques (INERIS), Agence de surveillance de la qualité de l’air (ASPA), Etude longitudinale française depuis l'enfance (UMS : Ined-Inserm-EFS) (ELFE), and EFS-Institut national d'études démographiques (INED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Male, Rural Population, Longitudinal study, Urban Population, Epidemiology, 010501 environmental sciences, 01 natural sciences, Cohort Studies, 0302 clinical medicine, Pregnancy, Residence Characteristics, PARTICULATE MATTER, Medicine, 030212 general & internal medicine, Child, Neighbourhood (mathematics), Vehicle Emissions, 2. Zero hunger, Air Pollutants, 3. Good health, AIR POLLUTION, Social deprivation, Maternal Exposure, [SDE]Environmental Sciences, Cohort, INEQUALITIES, Female, France, Adult, 03 medical and health sciences, Urbanization, Environmental health, SOCIOECONOMIC STATUS, Humans, Socioeconomic status, 0105 earth and related environmental sciences, NITROGEN DIOXIDE, business.industry, Public Health, Environmental and Occupational Health, Environmental Exposure, Socioeconomic Factors, 13. Climate action, SOCIAL DEPRIVATION, Pregnant Women, Rural area, Environmental Pollution, business, URBANISATION, Body mass index
Abstract: BackgroundExposure 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.MethodAmong 14 921 women from the French nationwide ELFE (French Longitudinal Study of Children) mother-child cohort recruited in 2011, outdoor exposure levels of PM2.5, PM10 (particulate matter 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.ResultsPatterns 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.ConclusionWe 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.
Published: 2017
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16. Atmospheric ammonia variability and link with PM formation: a case study over the Paris area

Author: Enrico Dammers, Mark W. Shephard, Frédérik Meleux, Tianze Wang, Martin Van Damme, Lieven Clarisse, Cathy Clerbaux, Karen Cady-Pereira, Camille Viatte, Simon Whitburn, and Pierre-François Coheur
Subjects: geography, Plateau, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Atmospheric model, Seasonality, Infrared atmospheric sounding interferometer, Particulates, Atmospheric sciences, medicine.disease, 01 natural sciences, medicine, HYSPLIT, Environmental science, Spatial variability, Precipitation, 0105 earth and related environmental sciences
Abstract: The Paris megacity experiences frequent particulate matter (PM2.5, PM with a diameter less than 2.5 μm) pollution episodes in springtime (March–April). At this time of the year, large parts of the particles consist of ammonium sulfate and nitrate which are formed from ammonia (NH3) released during fertilizer spreading practices and transported from the surrounding areas to Paris. There is still limited knowledge on the emission sources around Paris, their magnitude and seasonality. Using space-borne NH3 observation records of 10-years (2008–2017) and 5-years (2013–2017) provided by the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-Track Infrared Sounder (CrIS) instrument, regional pattern of NH3 variabilities (seasonal and inter-annual) are derived. Observations reveal identical high seasonal variabilities with three major NH3 hot spots found from March to August. The high inter-annual variability is discussed with respect to atmospheric total precipitation and temperature. A detailed analysis of the seasonal cycle is performed using both IASI and the CrIS instrument data, together with outputs from the CHIMERE atmospheric model. For months of high NH3 concentrations (March to August) the CHIMERE model shows good correspondence with correlation slopes of 0.98 and 0.71 when comparing with IASI and CrIS, respectively. It is found that the model is only able to reproduce half of the observed atmospheric temporal NH3 variability in the domain. In term of spatial variability, the CHIMERE monthly NH3 concentrations in springtime show a slight underrepresentation over Belgium and the United-Kingdom and overrepresentation in agricultural areas in the French Brittany/Pays de la Loire and Plateau du Jura region, as well as in the north part of Switzerland. Using HYSPLIT cluster analysis of back-trajectories, we show that NH3 total columns measured in spring over Paris are enhanced when air masses are originated from the Northeast (e. g., Netherlands and Belgium), highlighting the long-range transport importance on the NH3 budget over Paris. Finally, we quantify the key meteorological parameters driving the specific conditions important for the PM2.5 formation from NH3 in the Ile-de-France region in springtime. Data-driven results based on surface PM2.5 measurements from the Airparif network and IASI NH3 observations show that a combination of the factors, e. g. a low boundary layer of ~500 m, a relatively low temperature of 5 °C and a high relative humidity of 70 %, contributes to favor PM2.5 and NH3 correlation.
Published: 2019

17. Toward an integrated system of risk forecasting for pollen allergy in France

Author: antonio spanu, Frédérik Meleux, Lynda Hamaoui-Laguel, Florian Couvidat, Nicolas Viovy, Vincent Auvigne, Gilles Olivier, Michel Thibaudon, Augustin Colette, Civs, Gestionnaire, and Institut National de l'Environnement Industriel et des Risques (INERIS)
Subjects: [SDE] Environmental Sciences, [SDE]Environmental Sciences
Abstract: Pollen allergy is a growing health problem with an increase of sensitized subjects enhanced by plants response adaptation to climate change and by exposure to high concentrations of air pollutants. Linking air quality forecast and pollen estimate is therefore fundamental to assess and reduce allergy risks related to the cocktail effect. Here we present an integrated modelling strategy designed for operational forecasts. The forecast chain is based on the coupling between the ORCHIDEE land surface model and the multi-scale chemistry-transport model CHIMERE. The coupled model allows a full description of pollen production based on plant phenology and climatic conditions and its emission and transport through the atmosphere. The forecast system contains a calibration and evaluation process using 15 years of ground station data of the French aerobiology network (RNSA). The development of such approach is done within the project PREVIPOL with the objective to strengthen the French air quality system PREV’AIR (www.prevair.org) including pollen forecasts. Finally, the outcomes of the modelling system are combained with clinical database to assess the health risk.
Published: 2019

18. Impact of Physics Parameterizations on High-Resolution Air Quality Simulations over the Paris Region

Author: Bertrand Bessagnet, Frédéric Tognet, Lei jiang, Frédérik Meleux, Florian Couvidat, Institut National de l'Environnement Industriel et des Risques (INERIS), Université Pierre et Marie Curie - Paris 6 (UPMC), and Centre interprofessionnel technique d'étude des pollutions atmosphériques (CITEPA)
Subjects: Pollution, Canopy, Atmospheric Science, 010504 meteorology & atmospheric sciences, Planetary boundary layer, media_common.quotation_subject, lcsh:QC851-999, 010501 environmental sciences, Environmental Science (miscellaneous), Atmospheric sciences, 01 natural sciences, Wind speed, URBAN CANOPY, HIGH RESOLUTION, MODELING, 11. Sustainability, Air quality index, 0105 earth and related environmental sciences, media_common, Physics, SURFACE LAYER, Chemistry, AIR QUALITY, Particulates, Lidar, 13. Climate action, Weather Research and Forecasting Model, [SDE]Environmental Sciences, lcsh:Meteorology. Climatology
Abstract: The accurate simulation of meteorological conditions, especially within the planetary boundary layer (PBL), is of major importance for air quality modeling. In the present work, we have used the Weather Research and Forecast (WRF) model coupled with the chemistry transport model (CTM) CHIMERE to understand the impact of physics parameterizations on air quality simulation during a short-term pollution episode on the Paris region. A lower first model layer with a 4 m surface layer could better reproduce the transport and diffusion of pollutants in a real urban environment. Three canopy models could better reproduce a 2 m temperature (T2) in the daytime but present a positive bias from 1 to 5 &deg, C during the nighttime, the multi-urban canopy scheme &ldquo, building effect parameterization&rdquo, (BEP) underestimates the 10 m windspeed (W10) around 1.2 m s&minus, 1 for the whole episode, indicating the city cluster plays an important role in the diffusion rate in urban areas. For the simulation of pollutant concentrations, large differences were found between three canopy schemes, but with an overall overestimation during the pollution episode, especially for NO2 simulation, the average mean biases of NO2 prediction during the pollution episode were 40.9, 62.2, and 29.7 &micro, g m&minus, 3 for the Bulk, urban canopy model (UCM), and BEP schemes, respectively. Meanwhile, the vertical profile of the diffusion coefficients and pollutants indicated an important impact of the canopy model on the vertical diffusion. The PBL scheme sensitivity tests displayed an underestimation of the height of the PBL when compared with observations issued from the Lidar. The YonSei University scheme YSU and Boulac PBL schemes improved the PBL prediction compared with the Mellor&ndash, Yamada&ndash, Janjic (MYJ) scheme. All the sensitivity tests, except the Boulac&ndash, BEP, could not fairly reproduce the PBL height during the pollution episode. The Boulac&ndash, BEP scheme had significantly better performances than the other schemes for the simulation of both the PBL height and pollutants, especially for the NO2 and PM2.5 (particulate matter 2.5 micrometers or less in diameter) simulations. The mean bias of the NO2, PM2.5, and PM10 (particulate matter 10 micrometers or less in diameter) prediction were &minus, 5.1, 1.2, and &minus, 8.6 &micro, 3, respectively, indicating that both the canopy schemes and PBL schemes have a critical effect on air quality prediction in the urban region.
Published: 2020
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19. Ammonia agricultural emissions over Europe as seen by IASI and impact on PM2.5 concentrations

Author: Audrey Fortems-Cheiney, Gaelle Dufour, Matthias Beekmann, Sophie Génermont, Frédérik Meleux, Cathy Clerbaux, Pierre-François Coheur, Martin van Damme, Lieven Clarisse, Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut National de l'Environnement Industriel et des Risques (INERIS), Civs, Gestionnaire, 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), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Spectroscopie de l'atmosphère, Service de Chimie Quantique et Photophysique, Université libre de Bruxelles (ULB), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Libre de Bruxelles [Bruxelles] (ULB), and Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut national des sciences de l'Univers (INSU - CNRS)
Subjects: [SDE] Environmental Sciences, [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences
Abstract: Ammonia (NH3), whose main source is agriculture, is an important gaseous precursor of atmospheric particulate matter (PM). However, NH3 is the most poorly understood pollutant regulated by EU directives for air quality, as flux quantification is highly uncertain and measurement of this compound at the surface of the earth is difficult. Here, we derived daily European ammonia emissions using NH3 total columns from the Infrared Atmospheric Sounding Interferometer (IASI) onboard Metop-A, at a relatively high spatial resolution (grid-cell of 0.5° x 0.5°) for the two years 2010 and 2011. This update of NH3, in magnitude with a relatively high spatio-temporal variability, allows for a better comparison with independent PM2.5 measurements. It shows a different seasonal cycle in 2011 with a strong peak in March 2011, rather than in April in the EMEP prior inventory. It also reveals a peak in August 2011, not described in the EMEP inventory. This preliminary study suggests that there are good promises for better quantifying NH3 emissions by atmospheric inversions, and particularly with the the 4D Bayesian variational inverse system PYVAR-CHIMERE -based on the adjoint model of CHIMERE- being adapted to NH3.
Published: 2018

20. Apport de l'observation satellitaire à l'analyse et à la prévision de la qualité de l'air

Author: Solène Turquety, Gaëlle Dufour, Gilles Foret, Marc Mallet, Jean-Luc Attié, Didier Tanré, Cathy Clerbaux, Philippe Ricaud, Matthias Beekmann, Laurent Menut, Frédérik Meleux, Juan Cuesta, Bertrand Bessagnet, Laaziz El-Amraoui, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Centre national de recherches météorologiques (CNRM), Météo France-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'aérologie (LA), Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, 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), Institut National de l'Environnement Industriel et des Risques (INERIS), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), 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), Laboratoire d'aérologie (LAERO), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), 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)-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)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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 Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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)-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)
Subjects: base de données, [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, 13. Climate action, panache de polluant, qualité de l'air, pollution atmosphérique, [SDE]Environmental Sciences, prévision, modèle de chimie-transport, assimilation des données, modèle d'aérosols, télédétection satellitaire
Abstract: International audience; This paper presents what can be achieved with the use of satellite observations in the framework of atmospheric composition studies, including for air quality analysis and forecast. The different measurements currently available are presented with their main strengths and limitations. On the basis of examples from recent studies, the use and the gain obtained by these observations are discussed.This includes analysis of pollutant transport events, refinement of the databases used in the models, modeling of satellite observations and data assimilation. The recent Copernicus service is detailed in this context and the prospects for using these observations are finally explained.; Cet article présente ce qu'apportent les observations satellitaires pour les études de la composition atmosphérique, notamment dans un cadre d'analyse et prévision de la qualité de l'air. Les différentes mesures aujourd'hui disponibles sont présentées avec leurs principales forces et limitations. À partir d'exemples d'études récentes, l'utilisation et le gain obtenu grâce à ces observations sont discutés. Cela inclut l'analyse d'événements de transports de panaches de polluants, le raffinement des bases de données utilisées dans les modèles, la modélisation des observables satellitaires et l'assimilation de données. Le récent service Copernicus atmosphère est détaillé dans ce contexte et les perspectives futures d'utilisation de ces observations sont finalement expliquées.
Published: 2017
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21. Comparison of tropospheric NO2 columns from MAX-DOAS retrievals and regional air quality model simulations

Author: Anne-Marlene Blechschmidt, Joaquim Arteta, Adriana Coman, Lyana Curier, Henk Eskes, Gilles Foret, Clio Gielen, Francois Hendrick, Virginie Marécal, Frédérik Meleux, Jonathan Parmentier, Enno Peters, Gaia Pinardi, Ankie J. M. Piters, Matthieu Plu, Andreas Richter, Mikhail Sofiev, Álvaro M. Valdebenito, Michel Van Roozendael, Julius Vira, Tim Vlemmix, and John P. Burrows
Abstract: Tropospheric NO2 is hazardous to human health and can lead to tropospheric ozone formation, eutrophication of ecosystems and acid rain production. It is therefore important to establish accurate data based on models and observations to understand and monitor tropospheric NO2 concentrations on a regional and global scale. In the present study, MAX-DOAS tropospheric NO2 column retrievals from four European measurement stations are compared to regional model ensemble simulations. The latter are based on regional air quality models which contribute to the European regional ensemble forecasts and reanalyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model validation, MAX-DOAS data is closer to the regional model data in terms of horizontal and vertical resolution and measurements are available during daylight. In general, there is a good agreement between simulated and retrieved NO2 column values for individual MAX-DOAS measurements with correlations between 45 and 75 % for tropospheric NO2 VCDs, indicating that the model ensemble represents the emission and tropospheric chemistry of NOx (NO + NO2) well. Pollution transport towards the stations is on average well represented by the models. However, large differences are found for individual pollution plumes. Seasonal cycles are overestimated, weekly cycles are reproduced well and diurnal cycles poorly represented by the model ensemble. In particular, simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals. Our results demonstrate that a large number of validation points are available from MAX-DOAS measurements, which should therefore be used more extensively in future regional air quality modelling studies.
Published: 2017
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22. Characterising an intense PM pollution episode in March 2015 in France from multi-site approach and near real time data : Climatology, variabilities, geographical origins and model evaluation

Author: Jean-Eudes Petit, Alexandre Ockler, Olivier Favez, Yann Pellan, Jean Sciare, Benoit Rocq, Tanguy Amodeo, Didier Grenier, Laurent Menut, Valérie Gros, Bertrand Bessagnet, Frédérik Meleux, 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), Air Lorraine, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), ATMO Picardie, Cyprus Institute (CyI), 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), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)
Subjects: Pollution, Atmospheric Science, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, FRANCE, 010501 environmental sciences, Aethalometer, 01 natural sciences, chemistry.chemical_compound, Nitrate, POLLUTION, Urban background, 11. Sustainability, AETHALOMETER, 0105 earth and related environmental sciences, General Environmental Science, media_common, Advection, Multi site, AEROSOL, Particulates, AEROSOL CHEMICAL SPECIATION MONITOR, Aerosol, MODEL, chemistry, 13. Climate action, Climatology, ACSM, [SDE]Environmental Sciences, Environmental science
Abstract: International audience; During March 2015, a severe and large-scale particulate matter (PM) pollution episode occurred in France. Measurements in near real-time of the major chemical composition at four different urban background sites across the country (Paris, Creil, Metz and Lyon) allowed the investigation of spatiotemporal variabilities during this episode. A climatology approach showed that all sites experienced clear unusual rain shortage, a pattern that is also found on a longer timescale, highlighting the role of synoptic conditions over Wester-Europe. This episode is characterized by a strong predominance of secondary pollution, and more particularly of ammonium nitrate, which accounted for more than 50% of submicron aerosols at all sites during the most intense period of the episode. Pollution advection is illustrated by similar variabilities in Paris and Creil (distant of around 100 km), as well as trajectory analyses applied on nitrate and sulphate. Local sources, especially wood burning, are however found to contribute to local/ regional sub-episodes, notably in Metz. Finally, simulated concentrations from Chemistry-Transport model CHIMERE were compared to observed ones. Results highlighted different patterns depending on the chemical components and the measuring site, reinforcing the need of such exercises over other pollution episodes and sites.
Published: 2017
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23. CHIMERE-2017 : from urban to hemispheric chemistry-transport modeling

Author: Régis Briant, Guillaume Siour, Augustin Colette, Laurent Menut, Dmitry Khvorostyanov, Solène Turquety, Laurent Letinois, Myrto Valari, Konstantinos Markakis, Sylvain Mailler, Paolo Tuccella, Florian Couvidat, Frédérik Meleux, Bertrand Bessagnet, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), École des Ponts ParisTech (ENPC), Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), and 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)
Subjects: geography, geography.geographical_feature_category, Vulcanian eruption, 010504 meteorology & atmospheric sciences, Scale (ratio), lcsh:QE1-996.5, Circumpolar star, 010501 environmental sciences, Mineral dust, Urban area, 01 natural sciences, Plume, lcsh:Geology, Atmospheric composition, 13. Climate action, Climatology, [SDE]Environmental Sciences, 0105 earth and related environmental sciences, Volcanic ash
Abstract: CHIMERE is a chemistry-transport model designed for regional atmospheric composition. It can be used at a variety of scales from local to continental domains. However, due to the model design and its historical use as a regional model, major limitations had remained, hampering its use at hemispheric scale, due to the coordinate system used for transport as well as to missing processes that are important in regions outside Europe. Most of these limitations have been removed in the CHIMERE-2017 version, allowing its use in any region of the world and at any scale, from the scale of a single urban area up to hemispheric scale, with or without polar regions included. Other important improvements have been made in the treatment of the physical processes affecting aerosols and the emissions of mineral dust. From a computational point of view, the parallelization strategy of the model has also been updated in order to improve model numerical performance and reduce the code complexity. The present article describes all these changes. Statistical scores for a model simulation over continental Europe are presented, and a simulation of the circumpolar transport of volcanic ash plume from the Puyehue volcanic eruption in June 2011 in Chile provides a test case for the new model version at hemispheric scale.
Published: 2017
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24. Long-term health impact assessment of total PM2.5 in Europe during the 1990–2015 period

Author: Andrea Cappelletti, Bertrand Bessagnet, Giancarlo Ciarelli, Matthias Beekmann, Hilde Fagerli, Gino Briganti, Alberto Ortiz, Frédérik Meleux, Mihaela Mircea, Massimo D'Isidoro, Astrid Manders-Groot, Mario Adani, Simone Schucht, Cornelis Cuvelier, Camilla Andersson, Svetlana Tsyro, Augustin Colette, Florian Couvidat, Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Paris (UP)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Swedish Meteorological and Hydrological Institute (SMHI), The Netherlands Organisation for Applied Scientific Research (TNO), Italian National agency for new technologies, Energy and sustainable economic development [Frascati] (ENEA), Norwegian Meteorological Institute [Oslo] (MET), IIS‑Fundación Jiménez Diaz‑Autonoma University [Madrid, Spain], Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Ciarelli, G., Colette, A., Schucht, S., Beekmann, M., Andersson, C., Manders-Groot, A., Mircea, M., Tsyro, S., Fagerli, H., Ortiz, A. G., Adani, M., Briganti, G., Cappelletti, A., D'Isidoro, M., Cuvelier, C., Couvidat, F., Meleux, F., and Bessagnet, B.
Subjects: Chronic exposure, Atmospheric Science, PM, 010504 meteorology & atmospheric sciences, Meteorologi och atmosfärforskning, Population, Air pollution, lcsh:QC851-999, 010501 environmental sciences, medicine.disease_cause, complex mixtures, 01 natural sciences, Chemical transport model, World health, lcsh:Environmental pollution, Urbanization, Environmental health, 11. Sustainability, medicine, Chemical transport models, education, Air quality index, 0105 earth and related environmental sciences, General Environmental Science, education.field_of_study, Exposure to air pollution, Health impact assessment, 2.5, 3. Good health, Term (time), Meteorology and Atmospheric Sciences, 13. Climate action, lcsh:TD172-193.5, [SDE]Environmental Sciences, Environmental science, lcsh:Meteorology. Climatology
Abstract: Several datasets of PM2.5 concentrations over Europe during the 1990–2015 period, were used to calculate health impacts from chronic exposure to total particle matter below 2.5 μm (i.e. PM2.5). The datasets used in the analysis include the European Topic Centre on Air Pollution and Climate Change Mitigation (ETC/ACM), the Copernicus Atmospheric Monitoring Service (CAMS), the Global Burden of Disease (GBD), the World Health Organization (WHO) as well as the EURODELTA-Trends (EDT) multi-model reanalysis developed specifically for Europe.The exposure to ambient PM2.5 concentrations was calculated as population weighted annual average PM2.5 concentrations by country. The calculated exposure to PM2.5 was later used as input in the health impact assessment (HIA) Alpha-RiskPoll (ARP) tool to retrieve the total number of premature deaths.Our results indicate a substantial reduction in the number of premature deaths from PM2.5 exposure in Europe over the 1990–2010 period, between nearly 30 and 50%. Putting all the data-sets together, even if they do not cover the whole period, a decrease of even around 60% is observed between 1990 and 2015. For the countries included in this study, the estimated number of premature deaths from PM2.5 in 1990 was found to be around 960 000 (median of all the available datasets), whereas in 2015 it was found to be around 445 000. However, the variability in the estimated premature deaths from the different PM2.5 datasets was found to be large during the early 90s (around a factor of 2). For the latest years of the investigated period (2005 onwards), where a relatively flat trend in the PM2.5 exposure was observed, the differences between the different datasets were smaller.Even though our results indicate a reduction in the number of premature deaths from chronic exposure to PM2.5, the numbers remain considerable in 2015, underlining the need to continue improving air quality in the future. Keywords: PM2.5, Health impact assessment, Exposure to air pollution, Chemical transport models
Published: 2019
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25. Socioeconomic and behavioral characteristics associated with exposure to atmospheric pollutants during pregnancy: a nation-wide study

Author: Valérie Siroux, Johanna Lepeule, Marie Cheminat, Rémy Slama, Marie-Aline Charles, Laure Malherbe, Marion Ouidir, Cécile Zaros, and Frédérik Meleux
Subjects: Pregnancy, Environmental health, Atmospheric pollutants, medicine, General Earth and Planetary Sciences, Environmental science, medicine.disease, Socioeconomic status, General Environmental Science
Published: 2016
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26. An unusual way to validate regional chemistry-transport models

Author: Lauren Menut, Bertrand Bessagnet, Frédérik Meleux, Sylvain Mailler, Guillaume Siour, Augustin Colette, and Florian Couvidat
Subjects: 010504 meteorology & atmospheric sciences, Statistics, Chemistry (relationship), 010501 environmental sciences, Temporal correlation, Reference Period, 01 natural sciences, Synchronization, 0105 earth and related environmental sciences
Abstract: A simple and exhaustive model evaluation technique for regional chemistry-transport is discussed. It is based on the concept that we can learn more on models performances by comparing the results to in situ measurements available for other time periods than the period originally targeted in the simulation. First, the usual scores (spatial and temporal correlation) are computed for a reference period, using the actual temporal synchronization and spatial location of measurements . Second, the same scores are calculated for several other years by conserving only the actual spatial locations and days of the year. The difference between the two score provides complementary insights to the following questions: (i) is the model performing well only because the situation is persistent? (ii) is the model representative enough of the measurements for all variables? (iii) if the pollutants concentrations are not well modelled, is it due to meteorology or chemistry? In order to synthetize the large amount of results, a new score is proposed: the "multi-year variability", designed to compare the several indicators between all the years of validation and to quantify if the studied period was well modelled and, if yes, for the good reasons.
Published: 2016
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27. Role of the boundary layer dynamics effects on an extreme air pollution event in Paris

Author: Olivier Favez, Jordi Badosa, Jean-Charles Dupont, Vincent Crenn, Jean-Eudes Petit, Jean-Louis Bonne, Jean Sciare, Martial Haeffelin, Frédérik Meleux, Thierry Elias, Institut Pierre-Simon-Laplace (IPSL), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), 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), 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), Cyprus Institute (CyI), Agropole, Capgènes, École normale supérieure - Paris (ENS-PSL), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), 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 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)
Subjects: DYNAMICS, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, Irradiance, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Aerosol, Boundary layer, POLLUTION, 13. Climate action, Diurnal cycle, Wind shear, Turbulence kinetic energy, Radiative transfer, Environmental science, BOUNDARY LAYER DEPTH, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Optical depth, 0105 earth and related environmental sciences, General Environmental Science
Abstract: International audience; The physical and chemical aerosol properties are explored here based on ground-based observations in the Paris region to better understand the role of clouds, radiative fluxes and dynamics on aerosol loading during a heavy regional air pollution that occurred in March 2014 over North-Western Europe. This event is primarily characterized by a fine particle mass (PM2.5) increase from 10 to more than 120 μg m−3 and a simultaneous decrease of the horizontal visibility from 40 to 1 km, mainly due to significant formation of ammonium nitrate particles. The aerosol optical depth (AOD) at 550 nm increased steadily from about 0.06 on March 6 to more than 0.9 five days later. The scattering of the solar radiation by polluted particles induced, at the peak of the heavy pollution event, an instantaneous shortwave flux decrease of about 300 W m−2 for direct irradiance and an increase of about 150 W m−2 for diffuse irradiance (only scattering). The mean surface aerosol effect efficiency (effect per unit optical depth) is of about −80 W m−2 with a mean aerosol direct radiative effect of −23 W m−2. The dynamical and radiative processes that can be responsible for the diurnal cycle of PM2.5 in terms of amplitude and timing are investigated. A comparative analysis is performed for 4 consecutive days (between March 11 and 14), showing that the PM2.5 diurnal cycle can be modulated in time and amplitude by local processes such as the boundary layer depth development (ranging from 100 m to 1350 m), surface relative humidity (100%–35%), thermal structure (10 °C–16 °C for day/night amplitude), dynamics (wind speed ranging from 4 m s−1 to 1.5 m s−1) and turbulence (turbulent kinetic energy reaching 2 m2 s−2) near the surface and wind shear along the vertical. Finally, modeled and measured surface PM2.5 loadings are also compared here, notably illustrating the need of accurate boundary layer depth data for efficient air quality forecasts.
Published: 2016
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28. Presentation of the EURODELTA III intercomparison exercise – evaluation of the chemistry transport models\' performance on criteria pollutants and joint analysis with meteorology

Author: Claudio Carnevale, Anthony Ung, Florian Couvidat, Marta G. Vivanco, Armin Aulinger, R. Stern, Sebnem Aksoyoglu, Richard Kranenburg, Andrea Cappelletti, André S. H. Prévôt, Guido Pirovano, L. White, Laurence Rouil, Massimo D'Isidoro, Laurent Menut, Giancarlo Ciarelli, Johannes Bieser, Philippe Thunis, Bertrand Bessagnet, Giuseppe Calori, Hilde Fagerli, Gino Briganti, Maria-Teresa Pay, Mihaela Mircea, Lucia Gonzalez, Wenche Aas, Camillo Silibello, C. Cuvelier, Jean-Charles Dupont, José María Baldasano, Pete Roberts, Frédérik Meleux, Svetlana Tsyro, Astrid Manders, Sandro Finardi, Augustin Colette, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Universitat Politècnica de Catalunya. GReCT - Grup de Recerca de Ciències de la Terra, Institut National de l'Environnement Industriel et des Risques (INERIS), Ricerca sul Sistema Energetico (RSE), Italian National agency for new technologies, Energy and sustainable economic development [Frascati] (ENEA), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), The Netherlands Organisation for Applied Scientific Research (TNO), Norwegian Meteorological Institute [Oslo] (MET), Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid] (CIEMAT), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Norwegian Institute for Air Research (NILU), Institut Pierre-Simon-Laplace (IPSL), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), École normale supérieure - Paris (ENS-PSL), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), D'Isodoro, M., Cappelletti, A., Briganti, G., and Mircea, M.
Subjects: Atmospheric Science, Daytime, 010504 meteorology & atmospheric sciences, Meteorology, Planetary boundary layer, 010501 environmental sciences, 01 natural sciences, Química ambiental, Wind speed, Enginyeria química::Química del medi ambient::Química atmosfèrica [Àrees temàtiques de la UPC], lcsh:Chemistry, chemistry.chemical_compound, Diurnal cycle, Criteria air contaminants, Range (statistics), Nitrogen dioxide, air pollutants, meteorology, 0105 earth and related environmental sciences, Pollutants -- Analysis, Pollutant, Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia [Àrees temàtiques de la UPC], Contaminants -- Anàlisi, Aire -- Contaminació, Chemistry transport model, lcsh:QC1-999, lcsh:QD1-999, chemistry, 13. Climate action, Climatology, [SDE]Environmental Sciences, Environmental chemistry, lcsh:Physics, Air -- Pollution
Abstract: The EURODELTA III exercise has facilitated a comprehensive intercomparison and evaluation of chemistry transport model performances. Participating models performed calculations for four 1-month periods in different seasons in the years 2006 to 2009, allowing the influence of different meteorological conditions on model performances to be evaluated. The exercise was performed with strict requirements for the input data, with few exceptions. As a consequence, most of differences in the outputs will be attributed to the differences in model formulations of chemical and physical processes. The models were evaluated mainly for background rural stations in Europe. The performance was assessed in terms of bias, root mean square error and correlation with respect to the concentrations of air pollutants (NO2, O3, SO2, PM10 and PM2.5), as well as key meteorological variables. Though most of meteorological parameters were prescribed, some variables like the planetary boundary layer (PBL) height and the vertical diffusion coefficient were derived in the model preprocessors and can partly explain the spread in model results. In general, the daytime PBL height is underestimated by all models. The largest variability of predicted PBL is observed over the ocean and seas. For ozone, this study shows the importance of proper boundary conditions for accurate model calculations and then on the regime of the gas and particle chemistry. The models show similar and quite good performance for nitrogen dioxide, whereas they struggle to accurately reproduce measured sulfur dioxide concentrations (for which the agreement with observations is the poorest). In general, the models provide a close-to-observations map of particulate matter (PM2.5 and PM10) concentrations over Europe rather with correlations in the range 0.4–0.7 and a systematic underestimation reaching −10 µg m−3 for PM10. The highest concentrations are much more underestimated, particularly in wintertime. Further evaluation of the mean diurnal cycles of PM reveals a general model tendency to overestimate the effect of the PBL height rise on PM levels in the morning, while the intensity of afternoon chemistry leads formation of secondary species to be underestimated. This results in larger modelled PM diurnal variations than the observations for all seasons. The models tend to be too sensitive to the daily variation of the PBL. All in all, in most cases model performances are more influenced by the model setup than the season. The good representation of temporal evolution of wind speed is the most responsible for models' skillfulness in reproducing the daily variability of pollutant concentrations (e.g. the development of peak episodes), while the reconstruction of the PBL diurnal cycle seems to play a larger role in driving the corresponding pollutant diurnal cycle and hence determines the presence of systematic positive and negative biases detectable on daily basis.
Published: 2016
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29. Unaccounted variability in NH3 agricultural sources detected by IASI contributing to European spring haze episode

Author: Frédérik Meleux, Cathy Clerbaux, Gaëlle Dufour, Gilles Foret, Lynda Hamaoui-Laguel, Audrey Fortems-Cheiney, Markus Wallasch, Guillaume Siour, Pierre-François Coheur, M. Van Damme, Lieven Clarisse, Matthias Beekmann, Olivier Favez, 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), 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), Institut National de l'Environnement Industriel et des Risques (INERIS), Spectroscopie de l'atmosphère, Service de Chimie Quantique et Photophysique, Université Libre de Bruxelles [Bruxelles] (ULB), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Umweltbundesamt, Centre National d'Etudes Spatiales (CNES), European Union (EU), Belgian State Federal Ofﬁce forScientiﬁc, Technical and Cultural Affairs, European Project: 283576,EC:FP7:SPA,FP7-SPACE-2011-1,MACC II(2011), European Project: 282910,EC:FP7:ENV,FP7-ENV-2011,ECLAIRE(2011), 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-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Université libre de Bruxelles (ULB), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), German Federal Environmental Agency / Umweltbundesamt (UBA), 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 national des sciences de l'Univers (INSU - CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Haze, 010504 meteorology & atmospheric sciences, IASI, 010501 environmental sciences, Infrared atmospheric sounding interferometer, 01 natural sciences, 7. Clean energy, Troposphere, Spring (hydrology), 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, geography, geography.geographical_feature_category, business.industry, Grid cell, Particulates, On board, spreading practices, Geophysics, 13. Climate action, Agriculture, ammonia emissions, Climatology, [SDE]Environmental Sciences, General Earth and Planetary Sciences, Environmental science, business
Abstract: International audience; Ammonia (NH3), whose main source in the troposphere is agriculture, is an important gaseous precursor of atmospheric particulate matter (PM). We derived daily ammonia emissions using NH3 total columns measured from the Infrared Atmospheric Sounding Interferometer (IASI) on board Metop-A, at a relatively high spatial resolution (grid cell of 0.5° × 0.5°). During the European spring haze episodes of 24–31 March 2012 and 8–15 March 2014, IASI reveals NH3 total column magnitudes highlighting higher NH3 emissions over central Europe (especially over Germany, Czech Republic, and eastern France) from the ones provided by the European reference European Monitoring and Evaluation Programme inventory. These ammonia emissions exhibit in addition a large day-to-day variability, certainly due to spreading practices. The increase of NH3 emissions in the model, that reaches +300% locally, leads to an increase of both NH3 and PM2.5 surface concentrations and allows for a better comparison with independent measurements (in terms of bias, root-mean-square error, and correlation). This study suggests that there are good prospects for better quantifying NH3 emissions by atmospheric inversions.
Published: 2016
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30. 3-D evaluation of tropospheric ozone simulations by an ensemble of regional Chemistry Transport Model

Author: Martin G. Schultz, Christos Zerefos, Jean-Pierre Cammas, Matthias Beekmann, I. Kioutsioutkis, Laurent Menut, M. Razinger, Dimitrios Melas, Hendrik Elbern, A.M. Suttie, Maxime Eremenko, Vincent-Henri Peuch, Denis Zyryanov, Gilles Bergametti, Alvaro Valdebenito, Gilles Foret, Jean-Marie Flaud, E. Friese, O. Stein, P. Moinat, Johannes Flemming, Alberto Maurizi, Massimo D'Isidoro, Frédérik Meleux, Anastasia Poupkou, Gaëlle Dufour, Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'aérologie (LA), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), CNR Institute of Atmospheric Sciences and Climate (ISAC), Consiglio Nazionale delle Ricerche (CNR), Köln University, European Centre for Medium-Range Weather Forecasts (ECMWF), Aristotelian University of Thessaloniki, Aristotle University of Thessaloniki, Institut National de l'Environnement Industriel et des Risques (INERIS), Institut Pierre-Simon-Laplace (IPSL), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), 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), Institute for chemistry and dynamics of the Geoshere- 2: Troposphere, Forschungszentrum Jülich GmbH, Norwegian Meteorological Institute [Oslo] (MET), 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), Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Koln University, École normale supérieure - Paris (ENS Paris)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National d'Études Spatiales [Toulouse] (CNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Norwegian Meteorological Institute, Laboratoire d'aérologie (LAERO), Université de Toulouse (UT)-Université de Toulouse (UT)-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)-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), Istituto di Scienze dell'Atmosfera e del Clima (ISAC), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Rhenish Institute for Environmental Research (RIU), University of Cologne, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), 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), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Consiglio Nazionale delle Ricerche [Roma] (CNR), Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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)-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), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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 Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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), and École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris)
Subjects: Atmospheric Science, Ozone, 010504 meteorology & atmospheric sciences, Context (language use), 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Troposphere, lcsh:Chemistry, chemistry.chemical_compound, Altitude, Nadir, ddc:550, Tropospheric ozone, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDE.IE]Environmental Sciences/Environmental Engineering, lcsh:QC1-999, chemistry, lcsh:QD1-999, 13. Climate action, Climatology, Satellite, Tropopause, lcsh:Physics
Abstract: A detailed 3-D evaluation of an ensemble of five regional Chemistry Transport Models (RCTM) and one global CTM with focus on free tropospheric ozone over Europe is presented. It is performed over a summer period (June to August 2008) in the context of the GEMS-RAQ project. A data set of about 400 vertical ozone profiles from balloon soundings and commercial aircraft at 11 different locations is used for model evaluation, in addition to satellite measurements with the infrared nadir sounder (IASI) showing largest sensitivity to free tropospheric ozone. In the middle troposphere, the four regional models using the same top and boundary conditions from IFS-MOZART exhibit a systematic negative bias with respect to observed profiles of about −20%. Root Mean Square Error (RMSE) values are constantly growing with altitude, from 22% to 32% to 53%, respectively for 0–2 km, 2–8 km and 8–10 km height ranges. Lowest correlation is found in the middle troposphere, with minimum coefficients (R) between 0.2 to 0.45 near 8 km, as compared to 0.7 near the surface and similar values around 10 km. A sensitivity test made with the CHIMERE mode also shows that using hourly instead of monthly chemical boundary conditions generally improves the model skill (i.e. improve RMSE and correlation). Lower tropospheric 0–6 km partial ozone columns derived from IASI show a clear North-South gradient over Europe, which is qualitatively reproduced by the models. Also the temporal variability showing decreasing ozone concentrations in the lower troposphere (0–6 km columns) during summer is well reproduced by models even if systematic bias remains (the value of the bias being also controlled by the type of used boundary conditions). A multi-day case study of a trough with low tropopause was conducted and showed that both IASI and models were able to resolve strong horizontal gradients of middle and upper tropospheric ozone occurring in the vicinity of an upper tropospheric frontal zone.
Published: 2011
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31. 2004-2017 : Vers la mise en place de dispositifs français et européens pour la surveillance de la qualité de l'air

Author: Frédérik Meleux, Sylvie Guidotti, Laurence Rouil, Matthieu Plu, Marion Pithon, and Augustin Colette
Abstract: EnglishSince 1996, French regulations led France to implement an ambitious air quality monitoring infrastructure now based upon monitoring networks operated by 18 local associations in charge of air quality monitoring (AASQA). In the early 2000s, modelling capacities developed and the PREV'AIR system was set up. This pioneering air quality forecasting system in Europe was a major contributor to the MACC and MACC II European projects and now to the Copernicus Atmosphere Monitoring Service (CAMS) designed to make available to all European citizens the required information to monitor their environment and raise their awareness. francaisEn 1996, la loi sur l'air et l'utilisation rationnelle de l'energie a conduit la France a mettre en place un dispositif de surveillance de la qualite de l'air ambitieux reposant sur un reseau aujourd'hui compose de 18 associations agreees de surveillance de la qualite de l'air. Au debut des annees 2000, ce dispositif s'est enrichi de techniques offertes par la modelisation et la prevision, avec la mise en place en 2004 du systeme national Prev'air. Ce systeme pionnier en Europe a ete un contributeur majeur des projets europeens Macc puis Macc II, et aujourd'hui du service Copernicus Atmosphere (Cams) visant a developper et mettre a disposition de tous les citoyens europeens les elements utiles a la surveillance de leur environnement. Ces dispositifs permettant egalement d'attirer l'attention sur ces problematiques.
Published: 2018
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32. Chronic effects of air pollution on lung function after lung transplant (SysCLAD)

Author: Sacha Mussot, Johanna Claustre, Carine Gomez, Christophe Pison, Claire Dromer, Jean-François Mornex, Laurent P. Nicod, Frédérik Meleux, Christiane Knoop, Romain Kessler, V. Boussaud, Olivier Brugière, Antoine Magnan, Antoine Roux, Meriem Benmerad, Rémy Slama, Laure Malherbe, Karine Botturi, Marcel Dahan, Valérie Siroux, and Isabelle Danner-Boucher
Subjects: medicine.medical_specialty, COPD, education.field_of_study, Lung, business.industry, medicine.medical_treatment, Population, Immunosuppression, medicine.disease, Gastroenterology, Cystic fibrosis, Surgery, chemistry.chemical_compound, medicine.anatomical_structure, chemistry, Internal medicine, Cohort, medicine, Nitrogen dioxide, business, education, Body mass index
Abstract: We studied the role of chronic exposure to ambiant air pollution on lung function level and evolution in lung transplant patients. The lung function of 525 lung transplant (LT) patients from the COLT cohort was followed-up. The 12-month average levels of air pollutants (Nitrogen dioxide (NO 2 ), fine particulate matters (PM 2.5 , PM 10 ) and ozone (O 3 )) were estimated at the home addresses of each patient. The effect of air pollutant exposure on FEV 1 level and change in FEV 1 both during the recovery and decline periodes were estimated using mixed linear regression models adjusted on recipient age, sex, smoking (donor and patient), body mass index, donor age, type of LT, underlying disease, sex and HLA mismatch, ischemia time, anti-HLA antibodies, Pseudomonas colonization, CMV infections, immunosuppression induction and acute rejection. The population included 54% of men and 81% of double LT (mean age 43yrs). The main underlying diseases were cystic fibrosis (40%), emphysema/COPD (34%) and pulmonary arterial hypertension (14%). Mean (sd) individual exposure levels were 15.2 (2.1), 22.1 (3.1), 18.1 (7.3) and 51.7 (8.2) µg/m 3 for PM 2.5 , PM 10 , NO 2 and O 3 , respectively. NO 2 exposure was significantly associated with lower FEV 1 levels measured during the recovery period and a non-significant trend was observed in the decline period (estimate (se) = -3.39(1.48) p=0.02 and -1.96(1.47) p=0.18). None of the air pollutants exposure was associated with change in FEV 1 . Our results suggest a potential deleterious effect of chronic exposure to NO 2 on FEV 1 level following LT and did not evidence an effect of air pollution on change in FEV 1 . Fundings: EU-FP7 SYSCLAD, Vaincre la Mucoviscidose, Association Gregory Lemarchal.
Published: 2015
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33. Prematurity And Maternal Exposure To Air Pollutants During Gestation In A Nation-Wide Study

Author: Johanna Lepeule, Clemence Baudin, Marion Ouidir, Cécile Zaros, Joel Schwartz, Marie-Aline Charles, Itai Kloog, Laure Malherbe, Remy Slama, Marie Cheminat, and Frédérik Meleux
Subjects: Air pollutants, business.industry, Environmental health, General Earth and Planetary Sciences, Gestation, Medicine, business, General Environmental Science
Published: 2015
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34. High-Resolution air quality forecasts with MOCAGE chemistry transport model

Author: Frédérik Meleux, Béatrice Josse, Joaquim Arteta, Mathieu Joly, Jonathan Guth, Matthieu Plu, 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), Institut National de l'Environnement Industriel et des Risques (INERIS), STEYN, Douw G., and CHAUMERLIAC, Nadine
Subjects: Meteorology, 13. Climate action, Climatology, 11. Sustainability, [SDE]Environmental Sciences, High resolution, Forcing (mathematics), Urban heat island, Air quality index
Abstract: MOCAGE is the 3D global off-line chemistry transport model (CTM) run at Meteo-France since 2005 for air quality operational forecasts. Three nested domains are used, with decreasing resolutions (globe, Europe, and France), and 47 vertical levels (from the surface to 5 hPa). For the global and the European domain, input meteorological forcing fields are Meteo-France ARPEGE forecasts. For France, and for the first day of forecast, MOCAGE uses the operational outputs of Meteo-France non-hydrostatic AROME model. This high-resolution (2.5 km) meteorological model is supposed to better represent urban processes (e.g., the urban heat island), which are of strong interest for air quality applications. The purpose of this study is to test the increase of resolution of the CTM MOCAGE over France from 0.1° to 0.025° (i.e. the native resolution of the input meteorological fields).
Published: 2015
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35. MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe

Author: Julius Vira, Pilvi Siljamo, Dmitry Khvorostyanov, Anna-Mari Pessi, Olga Ritenberga, Lennart Robertson, Michel Thibaudon, Karl-Christian Bergmann, Annika Saarto, Elena Severova, Victoria Rodinkova, Laurent Menut, E. Friese, Marje Prank, Richard Kranenburg, Vincent-Henri Peuch, E. Teinemaa, Carmen Galán, Robert Gehrig, Uwe Berger, U. Kumar, Joaquim Arteta, F. Cheroux, Hendrik Elbern, Jordina Belmonte, Mikhail Sofiev, Virginie Marécal, Birthe Marie Steensen, Frédérik Meleux, Arjo Segers, I. Sauliene, Finnish Meteorological Institute (FMI), 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), Federal Office of Meteorology and Climatology MeteoSwiss, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), The Netherlands Organisation for Applied Scientific Research (TNO), Royal Netherlands Meteorological Institute (KNMI), Institut National de l'Environnement Industriel et des Risques (INERIS), Swedish Meteorological and Hydrological Institute (SMHI), Norwegian Meteorological Institute [Oslo] (MET), Réseau National de Surveillance Aérobiologique (RNSA), 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), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)
Subjects: Atmospheric Science, medicine.medical_specialty, 010504 meteorology & atmospheric sciences, Urban Mobility & Environment, Climate, Aerobiology, Urbanisation, 010501 environmental sciences, medicine.disease_cause, 01 natural sciences, Flowering, lcsh:Chemistry, Pollen, ddc:550, medicine, Statistical dispersion, Aerosol, 0105 earth and related environmental sciences, Ensemble forecasting, Ensemble average, Modeling, CAS - Climate, Air and Sustainability, Miljövetenskap, lcsh:QC1-999, Europe, Birch pollen, lcsh:QD1-999, Habitat, Climatology, [SDE]Environmental Sciences, Late season, Environmental science, ELSS - Earth, Life and Social Sciences, Environment & Sustainability, lcsh:Physics, Environmental Sciences
Abstract: This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more, which is a known feature of the source term used in the study. Absolute pollen concentrations during the season were somewhat underestimated in the southern part of the birch habitat. In the northern part of Europe, a record-low pollen season was strongly overestimated by all models. The median of the multi-model ensemble demonstrated robust performance, successfully eliminating the impact of outliers, which was particularly useful since for most models this was the first experience of pollen forecasting.
Published: 2015
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36. Can further mitigation of ammonia emissions reduce exceedances of particulate matter air quality standards ?

Author: Maxime Beauchamp, Valentin L. Foltescu, Augustin Colette, Laurence Rouil, Bertrand Bessagnet, Svetlana Tsyro, PG Ruyssenaars, Ferd Sauter, Frédérik Meleux, Frank A.A.M. de Leeuw, C. Guerreiro, Guus J. M. Velders, John van Aardenne, Institut National de l'Environnement Industriel et des Risques (INERIS), Norwegian Institute for Air Research (NILU), National Institute for Public Health and the Environment [Bilthoven] (RIVM), and Norwegian Meteorological Institute [Oslo] (MET)
Subjects: 010504 meteorology & atmospheric sciences, AGRICULTURE, Geography, Planning and Development, PM2.5, 010501 environmental sciences, Management, Monitoring, Policy and Law, engineering.material, 7. Clean energy, 01 natural sciences, Human health, Ammonia, chemistry.chemical_compound, CHEMISTRY TRANSPORT MODEL, PM10, 11. Sustainability, Air quality index, 0105 earth and related environmental sciences, AMMONIA, GOTHENBURG PROTOCOL, Reference simulation, EMISSION SCENARIOS, Environmental engineering, Particulates, Manure, chemistry, 13. Climate action, [SDE]Environmental Sciences, engineering, Environmental science, Fertilizer
Abstract: Several studies point out the importance of agricultural emissions to particulate matter (PM) concentrations, and particularly of NH3 emissions to PM2.5. Our study used three different chemical transport models (CHIMERE, EMEP and LOTOS-EUROS) to quantify the reductions of PM2.5 and PM10 concentrations due to reductions of NH3 emissions beyond the Gothenburg Protocol (GP), as well as due to the GP alone compared to 2009. Simulations of PM2.5 and PM10 concentrations using 2009 meteorology were undertaken for five emission scenarios: 2009 emissions (as the reference simulation), GP emissions in 2020, and further 10%, 20% and 30% NH3 emission reductions in EU27 beyond the GP. The modelling results for the scenarios with further 10%, 20% and 30% NH3 agriculture emission reductions in EU27 beyond the GP show that the reduction achieved in PM concentrations is not linear with the emission reductions. In fact, the results from the study show that the impact of ammonia emissions reduction is significantly more efficient when the emission reduction rises. Moreover, based on the evaluation on 2009, the modelling study shows that the expected impact of ammonia emissions on the formation of particulate ammonium was underestimated by all models. This would imply that the role of ammonia on PM concentration and exceedances of PM2.5 and PM10 limit values is likely to be even larger than quantified in this study. This study shows that the implementation of the emission reductions imposed by the revised GP for 2020 will not suffice to achieve compliance with PM limit values everywhere in Europe; hence further European and local measures may be considered. NH3 emissions from agriculture can be further reduced with the implementation of proven and feasible measures (substitution of fertilizers, improved storage of manure, way fertilizer injections, etc., …), in order to reduce PM concentrations and their impacts on human health across Europe.
Published: 2014
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37. Improving ammonia emissions in air quality modelling for France

Author: Pierre Cellier, Frédérik Meleux, Laurent Letinois, Bertrand Bessagnet, Lynda Hamaoui-Laguel, Sophie Genermont, Matthias Beekmann, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Environnement et Grandes Cultures (EGC), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, 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), AgroParisTech-Institut National de la Recherche Agronomique (INRA), and Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut national des sciences de l'Univers (INSU - CNRS)
Subjects: Pollution, Atmospheric Science, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, Ammonium nitrate, [SDV]Life Sciences [q-bio], 010501 environmental sciences, engineering.material, 7. Clean energy, 01 natural sciences, ammonia, modelling, chemistry.chemical_compound, Ammonia, PM10, Soil pH, Air quality index, 0105 earth and related environmental sciences, General Environmental Science, media_common, agriculture, 2. Zero hunger, Environmental engineering, emissions, Particulates, air quality, Aerosol, chemistry, 13. Climate action, engineering, ammonium nitrate, Environmental science, Fertilizer
Abstract: We have implemented a new module to improve the representation of ammonia emissions from agricultural activities in France with the objective to evaluate the impact of such emissions on the formation of particulate matter modelled with the air quality model CHIMERE. A novel method has been set up for the part of ammonia emissions originating from mineral fertilizer spreading. They are calculated using the one dimensional 1D mechanistic model “VOLT'AIR” which has been coupled with data on agricultural practices, meteorology and soil properties obtained at high spatial resolution (cantonal level). These emissions display high spatiotemporal variations depending on soil pH, rates and dates of fertilization and meteorological variables, especially soil temperature. The emissions from other agricultural sources (animal housing, manure storage and organic manure spreading) are calculated using the national spatialised inventory (INS) recently developed in France. The comparison of the total ammonia emissions estimated with the new approach VOLT'AIR_INS with the standard emissions provided by EMEP ( European Monitoring and Evaluation Programme ) used currently in the CHIMERE model shows significant differences in the spatiotemporal distributions. The implementation of new ammonia emissions in the CHIMERE model has a limited impact on ammonium nitrate aerosol concentrations which only increase at most by 10% on the average for the considered spring period but this impact can be more significant for specific pollution episodes. The comparison of modelled PM10 (particulate matter with aerodynamic diameter smaller than 10 μm) and ammonium nitrate aerosol with observations shows that the use of the new ammonia emission method slightly improves the spatiotemporal correlation in certain regions and reduces the negative bias on average by 1 μg m −3 . The formation of ammonium nitrate aerosol depends not only on ammonia concentrations but also on nitric acid availability, which is often a limiting factor in rural regions in France, and on meteorological conditions. The presented approach of ammonia emission calculation seems suitable for use in chemistry–transport models.
Published: 2014
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38. CHIMERE 2013 : a model for regional atmospheric composition modelling

Author: Jean-Louis Monge, Frédérik Meleux, Bertrand Bessagnet, Robert Vautard, Myrto Valari, Gabriele Curci, Matthias Beekmann, Isabelle Pison, Alma Hodzic, Solène Turquety, Marta G. Vivanco, Guillaume Siour, Augustin Colette, Nadège Blond, Gilles Foret, Isabelle Coll, Laurent Menut, Sylvain Mailler, D. Khvorostyanov, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Image, Ville, Environnement [Strasbourg] (LIVE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi dell'Aquila = University of L'Aquila (UNIVAQ), Atmospheric Chemistry Division [Boulder], National Center for Atmospheric Research [Boulder] (NCAR), 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), ICOS-RAMCES (ICOS-RAMCES), 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), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Environment Department, Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid] (CIEMAT), Université de Strasbourg (UNISTRA), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Università degli Studi dell'Aquila (UNIVAQ), 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), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), 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), Università degli Studi dell'Aquila [L'Aquila] (UNIVAQ.IT), and 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)
Subjects: 2003 HEAT-WAVE, Pollution, ORGANIC AEROSOL FORMATION, CHEMISTRY-TRANSPORT MODEL, GENERAL-CIRCULATION MODEL, AIR-QUALITY MODELS, PHASE TROPOSPHERIC CHEMISTRY, 2003 HEAT-WAVE, PARTICULATE MATTER, DRY-DEPOSITION, PARIS AREA, OZONE CONCENTRATIONS, 010504 meteorology & atmospheric sciences, Meteorology, media_common.quotation_subject, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Troposphere, PARTICULATE MATTER, AIR-QUALITY MODELS, PHASE TROPOSPHERIC CHEMISTRY, OZONE CONCENTRATIONS, GENERAL-CIRCULATION MODEL, Reference model, 0105 earth and related environmental sciences, media_common, Pollutant, DRY-DEPOSITION, [SDE.IE]Environmental Sciences/Environmental Engineering, Scale (chemistry), lcsh:QE1-996.5, CHEMISTRY-TRANSPORT MODEL, 6. Clean water, Aerosol, Trace gas, ORGANIC AEROSOL FORMATION, lcsh:Geology, PARIS AREA, Deposition (aerosol physics), 13. Climate action
Abstract: Tropospheric trace gas and aerosol pollutants have adverse effects on health, environment and climate. In order to quantify and mitigate such effects, a wide range of processes leading to the formation and transport of pollutants must be considered, understood and represented in numerical models. Regional scale pollution episodes result from the combination of several factors: high emissions (from anthropogenic or natural sources), stagnant meteorological conditions, kinetics and efficiency of the chemistry and the deposition. All these processes are highly variable in time and space, and their relative contribution to the pollutants budgets can be quantified with chemistry-transport models. The CHIMERE chemistry-transport model is dedicated to regional atmospheric pollution event studies. Since it has now reached a certain level a maturity, the new stable version, CHIMERE 2013, is described to provide a reference model paper. The successive developments of the model are reviewed on the basis of published investigations that are referenced in order to discuss the scientific choices and to provide an overview of the main results.
Published: 2014
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39. Ensemble Forecasting Coupled with Data Assimilation, and Threshold Exceedance Detection on Prev’Air

Author: Laure Malherbe, Bertrand Bessagnet, Vivien Mallet, Laurence Rouil, Edouard Debry, and Frédérik Meleux
Subjects: Data assimilation, Geography, Ensemble forecasting, Meteorology, Coupling (computer programming), Air quality index, Physics::Atmospheric and Oceanic Physics
Abstract: In this study the benefits of coupling data assimilation with ensemble forecasting are demonstrated for the production of improved air quality forecasts and detection of threshold exceedances.
Published: 2013
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40. A Statistical Approach to Improve Air Quality Forecasts in the PREV’AIR System

Author: Bertrand Bessagnet, Laure Malherbe, Frédérik Meleux, and Anthony Ung
Subjects: Meteorology, Simulated data, Atmospheric pollutants, Environmental science, Air quality index, Mixing (physics)
Abstract: Since 2003, the national PREV’AIR system (www.prevair.org) has been delivering daily air quality forecasts of atmospheric pollutants (O3, NO2, PM10, PM2.5) over Europe and France. Those products are based on chemistry-transport modeling and in particular on the outputs from CHIMERE model. Analysed air quality maps of the previous day are also produced by mixing observed and simulated data through a geostatistical approach.
Published: 2013
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41. Trace gas/aerosol boundary concentrations and their impacts on continental-scale AQMEII modeling domains

Author: Shawn J. Roselle, Johannes Flemming, Kenneth L. Schere, Bertrand Bessagnet, Charles Chemel, Stefano Galmarini, Ranjeet S. Sokhi, Rong-Ming Hu, S. Trivikrama Rao, Robert Vautard, Augustin Colette, Frédérik Meleux, Christian Hogrefe, Rohit Mathur, ORD, National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division, US Environmental Protection Agency (EPA), European Centre for Medium-Range Weather Forecasts (ECMWF), 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), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), 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 Atmospheric and Instrumentation Research [Hatfield] (CAIR), University of Hertfordshire [Hatfield] (UH), Institut National de l'Environnement Industriel et des Risques (INERIS), Bureau of Air Quality Analysis and Research, New York State Department of Environmental Conservation (NY DEC), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), 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 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)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, Mesoscale meteorology, Boundary (topology), AQMEII, 010501 environmental sciences, 01 natural sciences, Trace gas, Aerosol, Latitude, MODEL EVALUATION, 13. Climate action, [SDE]Environmental Sciences, Environmental science, Satellite, AIR QUALITY MODELING, Longitude, BOUNDARY CONCENTRATIONS, Air quality index, GEMS, 0105 earth and related environmental sciences, General Environmental Science
Abstract: International audience; Over twenty modeling groups are participating in the Air Quality Model Evaluation International Initiative (AQMEII) in which a variety of mesoscale photochemical and aerosol air quality modeling systems are being applied to continental-scale domains in North America and Europe for 2006 full-year simulations for model inter-comparisons and evaluations. To better understand the reasons for differences in model results among these participating groups, each group was asked to use the same source of emissions and boundary concentration data for their simulations. This paper describes the development and application of the boundary concentration data for this AQMEII modeling exercise. The European project known as GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) has produced global-scale re-analyses of air quality for several years, including 2006 (http://gems.ecmwf.int). The GEMS trace gas and aerosol data were made available at 3-hourly intervals on a regular latitude/longitude grid of approximately 1.9° resolution within 2 'cut-outs' from the global model domain. One cut-out was centered over North America and the other over Europe, covering sufficient spatial domain for each modeling group to extract the necessary time- and space-varying (horizontal and vertical) concentrations for their mesoscale model boundaries. Examples of the impact of these boundary concentrations on the AQMEII continental simulations are presented to quantify the sensitivity of the simulations to boundary concentrations. In addition, some participating groups were not able to use the GEMS data and instead relied upon other sources for their boundary concentration specifications. These are noted, and the contrasting impacts of other data sources for boundary data are presented. How one specifies four-dimensional boundary concentrations for mesoscale air quality simulations can have a profound impact on the model results, and hence, this aspect of data preparation must be performed with considerable care.
Published: 2012
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42. Forecasting urban air quality over cities by statistical adaptation of deterministic Chemistry Transport Model outputs

Author: Cécile Honore, Frédérik Meleux, Laure Malherbe, Charlotte Songeur, Anthony Ung, Civs, Gestionnaire, STEYN, D.G., and TRINI CASTELLI, Silvia
Subjects: Data set, Pollution, [SDE] Environmental Sciences, Index (economics), Geography, Meteorology, media_common.quotation_subject, Linear regression, Econometrics, Adaptation (computer science), Scale (map), Air quality index, media_common
Abstract: Within the European CITEAIR II project, deterministic and statistical forecasting approaches are combined to forecast an air quality index in European cities. The idea is to benefit both from chemistry-transport modelling, which provides large scale information about the evolution of photo-oxidizing pollution, and from local measurements of pollution levels. In addition to usual predictors, numerical outputs from the PREV’AIR system are used in multiple linear regression to forecast O3, NO2 and PM10 concentrations at urban stations and derive the city-level forecast index. The methodology was applied to Rotterdam, Sevilla and Prague with 2008 data set and validated against 2009 one. It can be extended to any European city involved in CITEAIR II, in particular to those having not implemented their own forecasting system yet.
Published: 2012

43. Improving ammonia emissions in air quality models

Author: Lynda Hamaoui-Laguel, Frédérik Meleux, Matthias Beekmann, Bertrand Bessagnet, Sophie Génermont, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Environnement et Grandes Cultures (EGC), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, 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), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Civs, Gestionnaire, and Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut national des sciences de l'Univers (INSU - CNRS)
Subjects: [SDE] Environmental Sciences, [SDE]Environmental Sciences
Abstract: Agriculture is the main source of atmospheric ammonia. This compound reacts with nitric acid to form ammonium nitrate aerosols. Under specific meteorological conditions, these aerosols can contribute to high particulate matter concentrations in the low troposphere, which can be responsible for adverse health effects. In spring 2007, the forecasts delivered by the chemical transport model (CTM) CHIMERE within the French operational platform for air quality monitoring and forecasting PREV'AIR were underestimating PM10 levels. In-situ observations on the aerosol composition suggested that was due to a lack of ammonium nitrate aerosol production. To increase the model capability to capture such particulate episode, we have built a coupled approach between CHIMERE and the mechanistic model VOLT'AIR (INRA). This method improves the ammonia emissions by providing a high description (spatially and temporally) of the use of manure and fertilizer spreading and it then allows to get a more precise assessment of ammonia availability in soil. These new emission data are then used in CHIMERE to simulate the particulate matter levels in the atmosphere. The set-up of this new modelling approach will be presented, with details about the input data and the modelling tools. Results of the study carried out for France from March to April 2007 show large spatio-temporal variations of ammonia emissions. Under favourable meteorological conditions, high ammonia emissions contribute largely to aerosol formation. The comparison of results with the previously used method indicates significant differences in the spatial distribution and magnitude of ammonia emissions and therefore of secondary aerosol formation.
Published: 2011

44. Assessing in near real time the impact of the April 2010 Eyjafjallajökull ash plume on air quality

Author: Laurent Menut, Olivier Favez, Yohann Morille, Martial Haeffelin, Laura Chiappini, Laurence Rouil, Arnaud Papin, Eva Leoz, Augustin Colette, Laure Malherbe, Bertrand Bessagnet, Frédérik Meleux, Institut National de l'Environnement Industriel et des Risques (INERIS), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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 Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), École normale supérieure - Paris (ENS Paris), Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), École normale supérieure - Paris (ENS Paris)-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 Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, Air pollution, 010501 environmental sciences, Particulates, Atmospheric dispersion modeling, Chemistry transport modelling, medicine.disease_cause, 01 natural sciences, [SDE.ES]Environmental Sciences/Environmental and Society, Aerosol, Plume, Troposphere, Long range transport, Eyjafjallajökull, 13. Climate action, Air quality, medicine, Environmental science, Lidar remote sensing, Air quality index, 0105 earth and related environmental sciences, General Environmental Science, Volcanic ash
Abstract: 5 p.; International audience; The eruption of the Eyjafjallajökull in April 2010 led to the injection in the troposphere of an important quantity of volcanic ash whose advection towards densely populated areas raised serious concerns regarding potential impacts on air quality. Here we investigate to what extent air quality in France was altered using exclusively quantitative data that was available in near real-time. We rely on a combination of atmospheric dispersion modelling, ground-based remote sensing, and chemical characterization of airborne particles. One week after the onset of the eruption we were able to conclude that the Eyjafjallajökull ash plume was locally responsible for an increase of up to 30 +/- 10 µgm-3 of total PM10 (particulate matter finer than 10 µm) that reached 65 mg m-3 on 18 and 19 April 2010. The methodology presented in this letter offers promising perspectives in terms of emergency response strategy when facing such unforeseen atmospheric dispersion events.
Published: 2010
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45. Assessment of the impact of the Eyjafjallajokull's eruption on surface air quality in France

Author: Augustin Colette, Nicolas Alsac, Bertrand Bessagnet, Hugues Biaudet, Laura Chiappini, Olivier Favez, Emeric FREJAFON, François Gautier, Fabrice Godefroy, Martial Haeffelin, Eva Leoz, Laure Malherbe, Frédérik Meleux, Laurent Menut, Yohann Morille, Arnaud Papin, Christophe Pietras, Martine Ramel, Laurence Rouil, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), and Civs, Gestionnaire
Subjects: [SDE] Environmental Sciences, [SDE]Environmental Sciences
Published: 2010

46. Modeling agricultural ammonia emissions : impact on particulate matter formation

Author: Lynda Hamaoui-Laguel, Frédérik Meleux, Matthias Beekmann, Laurent Letinois, Edouard Debry, Bertrand Bessagnet, Sophie Génermont, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Environnement et Grandes Cultures (EGC), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, 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), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Civs, Gestionnaire, and Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut national des sciences de l'Univers (INSU - CNRS)
Subjects: [SDE] Environmental Sciences, [SDE]Environmental Sciences
Published: 2010

47. Combining deterministic and statistical approaches for PM10 forecasting in Europe

Author: Gilles Foret, I.B. Konovalov, Frédérik Meleux, A.L. Dutot, Matthias Beekmann, Institute of Applied Physics of RAS, Russian Academy of Sciences [Moscow] (RAS), Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut National de l'Environnement Industriel et des Risques (INERIS), and 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)
Subjects: Atmospheric Science, Coefficient of determination, 010504 meteorology & atmospheric sciences, Artificial neural network, Mean squared error, Meteorology, STATISTICAL MODEL, AIR QUALITY, Statistical model, NEURAL NETWORK, 010501 environmental sciences, 01 natural sciences, Data assimilation, DATA ASSIMILATION, 13. Climate action, Adverse health effect, PARTICULATE MATTER, Linear regression, Statistics, [SDE]Environmental Sciences, CTM, Environmental science, Air quality index, 0105 earth and related environmental sciences, General Environmental Science
Abstract: International audience; Well documented adverse health effects of airborne particulate matter (PM) stimulate intensive research aimed at understanding and forecasting its behaviour. Forecasting of PM levels is commonly performed with either statistical or deterministic chemistry-transport models (CTM). In this study, we investigate advantages of combining deterministic and statistical approaches for PM10 forecasting over Europe one day ahead. The proposed procedure involves statistical postprocessing of deterministic forecasts by using PM10 monitoring data. A series of experiments is performed using a state-of-the-art CTM (CHIMERE) and statistical models based on linear regressions. It is found that performance of both CTM simulations and "pure" statistical models is inferior to that of the combined models. In particular, the root mean squared error of the deterministic forecasts can be reduced, on the average, by up to 45 percent (specifically, from 12.8 to 6.9 mu g/m(3) at urban sites in summer) and the coefficient of determination can be almost doubled. Importantly, it is found that the combined models for rural sites in summer and for urban and suburban sites in both summer and winter are representative, on the average, not only for a given monitoring site used for their training, but also of territories of similar type of environment (rural, suburban or urban) within several hundreds of kilometers away.
Published: 2009
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48. Is the ozone climate penalty robust in Europe?

Author: Ruth M. Doherty, Jesper H. Christensen, Joakim Langner, Astrid Manders, Magnuz Engardt, Alexander Baklanov, Eleni Katragkou, Paul Young, Hang Lei, Maria Tombrou-Tzella, Christos Giannakopoulos, Camilla Geels, Konstantinos V. Varotsos, Dimitris Melas, Joana Soares, Bertrand Bessagnet, Laurence Rouil, David Stevenson, Camilla Andersson, Frédérik Meleux, Mikhail Sofiev, Augustin Colette, G. B. Hedegaard, and Jørgen Brandt
Subjects: Pollution, Ozone, 010504 meteorology & atmospheric sciences, Meteorology, media_common.quotation_subject, Air pollution, Climate change, 010501 environmental sciences, medicine.disease_cause, 7. Clean energy, 01 natural sciences, chemistry.chemical_compound, 11. Sustainability, medicine, media_common.cataloged_instance, Ecosystem, European union, Robustness (economics), 0105 earth and related environmental sciences, General Environmental Science, media_common, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, Miljövetenskap, Term (time), chemistry, 13. Climate action, Climatology, Environmental science, Environmental Sciences
Abstract: Ozone air pollution is identified as one of the main threats bearing upon human health and ecosystems, with 25 000 deaths in 2005 attributed to surface ozone in Europe (IIASA 2013 TSAP Report #10). In addition, there is a concern that climate change could negate ozone pollution mitigation strategies, making them insufficient over the long run and jeopardising chances to meet the long term objective set by the European Union Directive of 2008 (Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008) (60 ppbv, daily maximum). This effect has been termed the ozone climate penalty. One way of assessing this climate penalty is by driving chemistry-transport models with future climate projections while holding the ozone precursor emissions constant (although the climate penalty may also be influenced by changes in emission of precursors). Here we present an analysis of the robustness of the climate penalty in Europe across time periods and scenarios by analysing the databases underlying 11 articles published on the topic since 2007, i.e. a total of 25 model projections. This substantial body of literature has never been explored to assess the uncertainty and robustness of the climate ozone penalty because of the use of different scenarios, time periods and ozone metrics. Despite the variability of model design and setup in this database of 25 model projection, the present meta-analysis demonstrates the significance and robustness of the impact of climate change on European surface ozone with a latitudinal gradient from a penalty bearing upon large parts of continental Europe and a benefit over the North Atlantic region of the domain. Future climate scenarios present a penalty for summertime (JJA) surface ozone by the end of the century (2071-2100) of at most 5 ppbv. Over European land surfaces, the 95% confidence interval of JJA ozone change is [0.44; 0.64] and [0.99; 1.50] ppbv for the 2041-2070 and 2071-2100 time windows, respectively.
Published: 2015
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49. Increase in summer European Ozone amounts due to climate change

Author: Filippo Giorgi, Fabien Solmon, Frédérik Meleux, Civs, Gestionnaire, Institut National de l'Environnement Industriel et des Risques (INERIS), and Abdus Salam International Centre for Theoretical Physics [Trieste] (ICTP)
Subjects: PUBLIC INFORMATION, [SDE] Environmental Sciences, Atmospheric Science, Ozone, 010504 meteorology & atmospheric sciences, Cloud cover, CLIMATE CHANGES, Climate change, 010501 environmental sciences, 01 natural sciences, 7. Clean energy, chemistry.chemical_compound, Effects of global warming, Precipitation, Air quality index, 0105 earth and related environmental sciences, General Environmental Science, Pollutant, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], OZONE, AIR QUALITY, MODELLING, chemistry, 13. Climate action, Climatology, Greenhouse gas, [SDE]Environmental Sciences, Environmental science
Abstract: Code Ineris : EN-2007-312; International audience; The local and regional distribution of pollutants is significantly influenced by weather patterns and variability along with the spatial patterns of emissions. Therefore, climatic changes which affect local meteorological conditions can alter air quality. We use the regional air quality model CHIMERE driven by meteorological fields from regional climate change simulations to investigate changes in summer ozone mixing ratios over Europe under increased greenhouse gas (GHG) forcing. Using three 30-year simulation periods, we find that daily peak ozone amounts as well as average ozone concentrations substantially increase during summer in future climate conditions. This is mostly due to higher temperatures and reduced cloudiness and precipitation over Europe and it leads to a higher number of ozone events exceeding information and warning thresholds. Our results show a pronounced regional variability, with the largest effects of climate change on ozone concentrations occurring over England, Belgium, Germany and France. The temperature-driven increase in biogenic emissions appears to enhance the ozone production and isoprene was identified as the most important chemical factor in the ozone sensitivity. We also find that summer ozone levels in future climate projections are similar to those found during the exceptionally warm and dry European summer of 2003. Our simulations suggest that in future climate conditions summer ozone might pose a much more serious threat to human health, agriculture and natural ecosystems in Europe, so that the effects of climate trends on pollutant amounts should be considered in future emission control measures.
Published: 2006
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50. Impact of Physics Parameterizations on High-Resolution Air Quality Simulations over the Paris Region

Author: Lei Jiang, Bertrand Bessagnet, Frederik Meleux, Frederic Tognet, and Florian Couvidat
Subjects: modeling, high resolution, air quality, urban canopy, surface layer, Meteorology. Climatology, QC851-999
Abstract: The accurate simulation of meteorological conditions, especially within the planetary boundary layer (PBL), is of major importance for air quality modeling. In the present work, we have used the Weather Research and Forecast (WRF) model coupled with the chemistry transport model (CTM) CHIMERE to understand the impact of physics parameterizations on air quality simulation during a short-term pollution episode on the Paris region. A lower first model layer with a 4 m surface layer could better reproduce the transport and diffusion of pollutants in a real urban environment. Three canopy models could better reproduce a 2 m temperature (T2) in the daytime but present a positive bias from 1 to 5 °C during the nighttime; the multi-urban canopy scheme “building effect parameterization” (BEP) underestimates the 10 m windspeed (W10) around 1.2 m s−1 for the whole episode, indicating the city cluster plays an important role in the diffusion rate in urban areas. For the simulation of pollutant concentrations, large differences were found between three canopy schemes, but with an overall overestimation during the pollution episode, especially for NO2 simulation, the average mean biases of NO2 prediction during the pollution episode were 40.9, 62.2, and 29.7 µg m−3 for the Bulk, urban canopy model (UCM), and BEP schemes, respectively. Meanwhile, the vertical profile of the diffusion coefficients and pollutants indicated an important impact of the canopy model on the vertical diffusion. The PBL scheme sensitivity tests displayed an underestimation of the height of the PBL when compared with observations issued from the Lidar. The YonSei University scheme YSU and Boulac PBL schemes improved the PBL prediction compared with the Mellor–Yamada–Janjic (MYJ) scheme. All the sensitivity tests, except the Boulac–BEP, could not fairly reproduce the PBL height during the pollution episode. The Boulac–BEP scheme had significantly better performances than the other schemes for the simulation of both the PBL height and pollutants, especially for the NO2 and PM2.5 (particulate matter 2.5 micrometers or less in diameter) simulations. The mean bias of the NO2, PM2.5, and PM10 (particulate matter 10 micrometers or less in diameter) prediction were −5.1, 1.2, and −8.6 µg m−3, respectively, indicating that both the canopy schemes and PBL schemes have a critical effect on air quality prediction in the urban region.
Published: 2020
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