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1. Three-Dimensional Distribution of Biomass Burning Aerosols from Australian Wildfires Observed by TROPOMI Satellite Observations

Author

Farouk Lemmouchi, Juan Cuesta, Maxim Eremenko, Claude Derognat, Guillaume Siour, Gaëlle Dufour, Pasquale Sellitto, Solène Turquety, Dung Tran, Xiong Liu, Peter Zoogman, Ronny Lutz, Diego Loyola, 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 Paris Cité (UPCité), ARIA Technologies, Istituto Nazionale di Geofisica e Vulcanologia - Sezione di Catania (INGV), Istituto Nazionale di Geofisica e Vulcanologia, 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), 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), Harvard-Smithsonian Center for Astrophysics (CfA), Harvard University [Cambridge]-Smithsonian Institution, Minerva University, DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute (IMF), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), This work is funded by the Region Ile-de-France in the framework of the Domaine d’Intérêt Majeur Réseau de recherche Qualité de l’air en Ile-de-France (DIM QI2) through the programme Paris Region PhD (PRPHD), ARIA Technologies, the Programme National de Télédétection Spatiale (PNTS, http://programmes.insu.cnrs.fr/pnts (accessed on 20 April 2022), and grant no. PNTS-2016– 02, project 'AEROMETOP'), and the Centre National des Etudes Spatiales (CNES) through the SURVEYPOLLUTION project from TOSCA (Terre Ocean Surface Continental et Atmosphère), and supported by the Centre National de Recherche Scientifique—Institute National de Sciences de l’Univers (CNRS-INSU) and the Université Paris Est Créteil (UPEC).

Subjects
biomass burning, aerosol injection height, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Aerosols, fine particulate matter, black carbon, smoke, aerosol extinction vertical profile, 3D distribution of aerosols, Australian fire, TROPOMI, atmospheric_science, Sentinel-5P, General Earth and Planetary Sciences, Atmospheric Remote Sensing, Physics::Atmospheric and Oceanic Physics
Abstract

International audience; We present a novel passive satellite remote sensing approach for observing the three-dimensional distribution of aerosols emitted from wildfires. This method, called AEROS5P, retrieves vertical profiles of aerosol extinction from cloud-free measurements of the TROPOMI satellite sensor onboard the Sentinel 5 Precursor mission. It uses a Tikhonov–Phillips regularization, which iteratively fits near-infrared and visible selected reflectances to simultaneously adjust the vertical distribution and abundance of aerosols. The information on the altitude of the aerosol layers is provided by TROPOMI measurements of the reflectance spectra at the oxygen A-band near 760 nm. In the present paper, we use this new approach for observing the daily evolution of the three-dimensional distribution of biomass burning aerosols emitted by Australian wildfires on 20–24 December 2019. Aerosol optical depths (AOD) derived by vertical integration of the aerosol extinction profiles retrieved by AEROS5P are compared with MODIS, VIIRS and AERONET coincident observations. They show a good agreement in the horizontal distribution of biomass burning aerosols, with a correlation coefficient of 0.87 and a mean absolute error of 0.2 with respect to VIIRS. Moderately lower correlations (0.63) were found between AODs from AEROS5P and MODIS, while the range of values for this comparison was less than half of that with respect to VIIRS. A fair agreement was found between coincident transects of vertical profiles of biomass burning aerosols derived from AEROS5P and from the CALIOP spaceborne lidar. The mean altitudes of these aerosols derived from these two measurements showed a good agreement, with a small mean bias (185 m) and a correlation coefficient of 0.83. Moreover, AEROS5P observations reveal the height of injection of the biomass burning aerosols in 3D. The highest injection heights during the period of analysis were coincident with the largest fire radiative power derived from MODIS. Consistency was also found with respect to the vertical stability of the atmosphere. The AEROS5P approach provides retrievals for cloud-free scenes over several regions, although currently limited to situations with a dominating presence of smoke particles. Future developments will also aim at observing other aerosol species.

Published
2022
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2. Ensemble forecast of an index of the Madden–Julian Oscillation using a stochastic weather generator based on circulation analogs

Author

Meriem Krouma, Riccardo Silini, Pascal Yiou, 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), ARIA Technologies, Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), 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), Universitat Politècnica de Catalunya [Barcelona] (UPC), and European Project: 813844,CAFE

Subjects
[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, General Earth and Planetary Sciences, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology
Abstract

The Madden–Julian Oscillation (MJO) is one of the main sources of sub-seasonal atmospheric predictability in the tropical region. The MJO affects precipitation over highly populated areas, especially around southern India. Therefore, predicting its phase and intensity is important as it has a high societal impact. Indices of the MJO can be derived from the first principal components of zonal wind and outgoing longwave radiation (OLR) in the tropics (RMM1 and RMM2 indices). The amplitude and phase of the MJO are derived from those indices. Our goal is to forecast these two indices on a sub-seasonal timescale. This study aims to provide an ensemble forecast of MJO indices from analogs of the atmospheric circulation, computed from the geopotential at 500 hPa (Z500) by using a stochastic weather generator (SWG). We generate an ensemble of 100 members for the MJO amplitude for sub-seasonal lead times (from 2 to 4 weeks). Then we evaluate the skill of the ensemble forecast and the ensemble mean using probabilistic scores and deterministic skill scores. According to score-based criteria, we find that a reasonable forecast of the MJO index could be achieved within 40 d lead times for the different seasons. We compare our SWG forecast with other forecasts of the MJO. The comparison shows that the SWG forecast has skill compared to ECMWF forecasts for lead times above 20 d and better skill compared to machine learning forecasts for small lead times.

Published
2023
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3. Assessment of stochastic weather forecast of precipitation near European cities, based on analogs of circulation

Author

Meriem Krouma, Pascal Yiou, Soulivanh Thao, Céline Déandréis, 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), ARIA Technologies, Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), 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), European Project: 813844,CAFE, and This work is part of the EU International Training Network (ITN) 'Climate Advanced Forecasting of subseasonal Extremes' (CAFE). The project receives funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant (agreement no. 813844).

Subjects
Meteorology, [SDU]Sciences of the Universe [physics], Weather generator, Western europe, Quantitative precipitation forecast, Environmental science, Geopotential height, Forecast skill, General Medicine, Precipitation, Predictability, European region
Abstract

In this study, we assess the skill of a stochastic weather generator (SWG) to forecast precipitation in several cities in western Europe. The SWG is based on a random sampling of analogs of the geopotential height at 500 hPa (Z500). The SWG is evaluated for two reanalyses (NCEP and ERA5). We simulate 100-member ensemble forecasts on a daily time increment. We evaluate the performance of SWG with forecast skill scores and we compare it to ECMWF forecasts. Results show significant positive skill score (continuous rank probability skill score and correlation) compared with persistence and climatology forecasts for lead times of 5 and 10 d for different areas in Europe. We find that the low predictability episodes of our model are related to specific weather regimes, depending on the European region. Comparing the SWG forecasts to ECMWF forecasts, we find that the SWG shows a good performance for 5 d. This performance varies from one region to another. This paper is a proof of concept for a stochastic regional ensemble precipitation forecast. Its parameters (e.g., region for analogs) must be tuned for each region in order to optimize its performance.

Published
2021
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4. Evaluation and exploitation of an air quality forecast system over the kingdom of morocco

Author

Lacressonniere, G., Albergel, A., Elyakoubi, M., EDDAIF, H., BARICHEFF, D., CODDEVILLE, P., ARIA Technologies, École Nationale Supérieure des Mines de Rabat (ENSMR), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), and Institut Mines-Télécom [Paris] (IMT)

Subjects
[INFO]Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

5. On the ability of a global atmospheric inversion to constrain variations of CO2 fluxes over Amazonia

Author

Molina, L., Broquet, Grégoire, Imbach, P., Chevallier, Frédéric, Poulter, B., Bonal, Damien, Burban, Benoît, Ramonet, Michel, Gatti, L. V., Wofsy, S. C., Munger, J. W., Dlugokencky, E., Ciais, Philippe, 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), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), 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), Centro Agronomico Tropical de Investigacion y Enseñanza (CATIE), Montana State University (MSU), Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), Ecologie des forêts de Guyane (UMR ECOFOG), Université des Antilles (UA)-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA), ICOS-RAMCES (ICOS-RAMCES), Instituto de Pesquisas, Harvard University [Cambridge], National Oceanic and Atmospheric Administration (NOAA), ICOS-ATC (ICOS-ATC), ANR(ANR-10-LABX-0025), ARIA Technologies, Thales Alenia Space, Veolia, CEA, UVSQ, CNRS, CNES, INRA, French Ministry of Research, European Project: 283080,EC:FP7:ENV,FP7-ENV-2011,GEOCARBON(2011), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), and Harvard University

Subjects
lcsh:Chemistry, amazonie, lcsh:QD1-999, flux de gaz carbonique, [SDV]Life Sciences [q-bio], inversion atmosphérique, bassin amazonien, gaz carbonique atmosphérique, échange gazeux, co2 atmosphérique, lcsh:Physics, lcsh:QC1-999
Abstract

The exchanges of carbon, water and energy between the atmosphere and the Amazon basin have global implications for the current and future climate. Here, the global atmospheric inversion system of the Monitoring of Atmospheric Composition and Climate (MACC) service is used to study the seasonal and interannual variations of biogenic CO2 fluxes in Amazonia during the period 2002–2010. The system assimilated surface measurements of atmospheric CO2 mole fractions made at more than 100 sites over the globe into an atmospheric transport model. The present study adds measurements from four surface stations located in tropical South America, a region poorly covered by CO2 observations. The estimates of net ecosystem exchange (NEE) optimized by the inversion are compared to an independent estimate of NEE upscaled from eddy-covariance flux measurements in Amazonia. They are also qualitatively evaluated against reports on the seasonal and interannual variations of the land sink in South America from the scientific literature. We attempt at assessing the impact on NEE of the strong droughts in 2005 and 2010 (due to severe and longer-than-usual dry seasons) and the extreme rainfall conditions registered in 2009. The spatial variations of the seasonal and interannual variability of optimized NEE are also investigated. While the inversion supports the assumption of strong spatial heterogeneity of these variations, the results reveal critical limitations of the coarse-resolution transport model, the surface observation network in South America during the recent years and the present knowledge of modelling uncertainties in South America that prevent our inversion from capturing the seasonal patterns of fluxes across Amazonia. However, some patterns from the inversion seem consistent with the anomaly of moisture conditions in 2009.

Published
2015
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6. A Bayesian approach of the Source Term Estimate coupling retro-dispersion computations with a Lagrangian Particle Dispersion Model and the Adaptive Multiple Importance Sampling

Author

Rajaona, Harizo, Septier, François, Delignon, Yves, Armand, Patrick, Olry, Christophe, Albergel, Armand, DAM Île-de-France (DAM/DIF), Direction des Applications Militaires (DAM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut TELECOM/TELECOM Lille1, Institut Mines-Télécom [Paris] (IMT), and ARIA Technologies

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; This paper presents an enhanced version of a STE adaptive algorithm based on probabilistic Bayesian inference (AMIS) that estimates the parameters of an atmospheric pollution source term. After introducing the problem and presenting the initial results obtained with the first version of the algorithm, we describe an efficient way to reduce the computational load in its procedure by shifting the most time-consuming step outside the iterative loop. This is made possible by applying the duality relationship between forward and adjoint advection-diffusion equations, and is proven to work well on a synthetic example using Retro-SPRAY, the backward implementation of SPRAY, the Lagrangian particle dispersion model of the PMSS suite.

Published
2016

7. Application of ODEMS (Odorant Dispersion and Emissions Monitoring System) to Measure Odorous Emissions from Composting Plant

Author

Cariou, Stéphane, Fanlo, Jean-Louis, Stitou, Youssef, Buty, Didier, Samani, Didier, Akiki, Rony, Laboratoire de Génie de l'Environnement Industriel (LGEI), IMT - MINES ALES (IMT - MINES ALES), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), ISEO, ARIA Technologies, Alliance Environnement, and Environnement SA

Subjects
[SPI]Engineering Sciences [physics], lcsh:Computer engineering. Computer hardware, lcsh:TP155-156, lcsh:TK7885-7895, lcsh:Chemical engineering
Abstract

International audience; Odour annoyance represents a very important issue of societal and industrial perspective. It can be due to the intrinsic character of the odour, its frequency and the moment of the perception. Location of industries depends on their odour acceptability in the neighbourhood. As 13 to 20% of the population in European countries would be annoyed by environmental odours, stringent regulations are being enforced for odor monitoring and recently, several works have been carried out to determine suitable and valuable strategies/methods to limit odor annoyance. Industrial and agricultural activities generate atmospheric pollution and olfactive nuisances due to the emission of a complex mixture of volatile compounds. Hydrogen sulphide (H2S) and ammonia (NH3) are clearly identified within composting plants (Cabrol et al, 2012) and due to their high olfactory impact, have to be monitored as mentioned in a report of the French Environmental and Energy Management Agency (ADEME, 2012). ODEMS is a system composed by a network of miniature and autonomous sensors combined with reversed dispersion (Figure 1) and dispersion (Figure 2) modelling systems and enable to provide reliable spatial and temporal information down to the low ppbv level. The miniaturized cost-effective sensors Cairsens are based on amperometric detection and are developed by Cairpol company. Ammonia and hydrogen sulfide sensors have been deployed within a composting plant for determining the odorous sources and evaluating the real impact on the neighbourhood. After a period of data collection, considering weather conditions, this study revealed that this system is also able to predict the impact of a site-specific activity.

Published
2016
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8. An adaptive Bayesian inference algorithm to estimate the parameters of a hazardous atmospheric release

Author

Christophe Olry, Yves Delignon, François Septier, Armand Albergel, Jacques Moussafir, Patrick Armand, Harizo Rajaona, Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), DAM Île-de-France (DAM/DIF), Direction des Applications Militaires (DAM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut TELECOM/TELECOM Lille1, Institut Mines-Télécom [Paris] (IMT), and ARIA Technologies

Subjects
Pointwise, Atmospheric Science, [STAT.AP]Statistics [stat]/Applications [stat.AP], Source term estimation, Computer science, Bayesian probability, Bayesian inference, Probabilistic logic, Markov chain Monte Carlo, Adaptive multiple importance sampling, Inverse problem, symbols.namesake, Monte-Carlo techniques, Prior probability, symbols, [STAT.CO]Statistics [stat]/Computation [stat.CO], Algorithm, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Importance sampling, General Environmental Science
Abstract

International audience; In the eventuality of an accidental or intentional atmospheric release, the reconstruction of the source term using measurements from a set of sensors is an important and challenging inverse problem. A rapid and accurate estimation of the source allows faster and more efficient action for first-response teams, in addition to providing better damage assessment.This paper presents a Bayesian probabilistic approach to estimate the location and the temporal emission profile of a pointwise source. The release rate is evaluated analytically by using a Gaussian assumption on its prior distribution, and is enhanced with a positivity constraint to improve the estimation. The source location is obtained by the means of an advanced iterative Monte-Carlo technique called Adaptive Multiple Importance Sampling (AMIS), which uses a recycling process at each iteration to accelerate its convergence.The proposed methodology is tested using synthetic and real concentration data in the framework of the Fusion Field Trials 2007 (FFT-07) experiment. The quality of the obtained results is comparable to those coming from the Markov Chain Monte Carlo (MCMC) algorithm, a popular Bayesian method used for source estimation. Moreover, the adaptive processing of the AMIS provides a better sampling efficiency by reusing all the generated samples.

Published
2015
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9. In situ, satellite measurement and model evidence on the dominant regional contribution to fine particulate matter levels in the Paris megacity

Author

Frank Drewnick, Nicolas Marchand, Véronique Ghersi, Agnès Borbon, Laurent Poulain, Amandine Rosso, F. Freutel, Andreas Stohl, Spyros N. Pandis, Sabine Eckhardt, Alexander Baklanov, Jay G. Slowik, Monica Crippa, Alfons Schwarzenboeck, Jean-Luc Jaffrezo, Peter Zotter, Stephan Borrmann, André S. H. Prévôt, Edith Rodriguez, Aurélie Colomb, Mark Lawrence, Qijie Zhang, S.-L. von der Weiden-Reinmüller, Urs Baltensperger, Sophie Moukhtar, Sönke Szidat, Johannes Schneider, A. Wiedensohler, Matthias Beekmann, M. Bressi, Christos Fountoukis, Valérie Gros, I. El Haddad, Hervé Petetin, H.A.C. Denier van der Gon, Steffen Beirle, Vincent Michoud, A. Megaritis, Pekka Kolmonen, Jean Sciare, 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), Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, 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), Institute of Computer Science (ICS-FORTH), Foundation for Research and Technology - Hellas (FORTH), TNO, Business Unit Environment, Health and Safety, Utrecht, Netherlands, Leibniz Institute for Tropospheric Research (TROPOS), AIRPARIF - Surveillance de la qualité de l'air en Île-de-France, Finnish Meteorological Institute (FMI), Institute of Chemical Engineering and High Temperature Processes (FORTH-ICEHT), University of Berne, ARIA Technologies, École des Mines de Douai (Mines Douai EMD), Institut Mines-Télécom [Paris] (IMT), Norwegian Institute for Air Research (NILU), Laboratoire Chimie Provence (LCP), Centre National de la Recherche Scientifique (CNRS)-Université de Provence - Aix-Marseille 1-Institut de Chimie du CNRS (INC), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Laboratoire de météorologie physique (LaMP), Centre National de la Recherche Scientifique (CNRS)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut national des sciences de l'Univers (INSU - CNRS), Johannes Gutenberg - Universität Mainz (JGU), Danish Meteorological Institute (DMI), 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), 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), Université de Provence - Aix-Marseille 1-Centre National de la Recherche Scientifique (CNRS), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), 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), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institute of Computer Science [FORTH, Heraklion] (ICS-FORTH), TNO Business Unit Environment, Health and Safety, The Netherlands Organisation for Applied Scientific Research (TNO), Universität Bern [Bern] (UNIBE), Université de Provence - Aix-Marseille 1-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU)

Subjects
Pollution, Atmospheric Science, Meteorology, Urban Mobility & Environment, media_common.quotation_subject, Air pollution, Urbanisation, Environment, medicine.disease_cause, Atmospheric sciences, lcsh:Chemistry, chemistry.chemical_compound, Nitrate, 540 Chemistry, 11. Sustainability, medicine, Sulfate, Air quality index, media_common, Advection, CAS - Climate, Air and Sustainability, lcsh:QC1-999, Aerosol, Megacity, lcsh:QD1-999, chemistry, 13. Climate action, [SDE]Environmental Sciences, ELSS - Earth, Life and Social Sciences, Environment & Sustainability, lcsh:Physics
Abstract

International audience; Published by Copernicus Publications on behalf of the European Geosciences Union. 9578 M. Beekmann et al.: Evidence for a dominant regional contribution to fine particulate matter levels Abstract. A detailed characterization of air quality in the megacity of Paris (France) during two 1-month intensive campaigns and from additional 1-year observations revealed that about 70 % of the urban background fine particulate matter (PM) is transported on average into the megacity from upwind regions. This dominant influence of regional sources was confirmed by in situ measurements during short intensive and longer-term campaigns, aerosol optical depth (AOD) measurements from ENVISAT, and modeling results from PMCAMx and CHIMERE chemistry transport models. While advection of sulfate is well documented for other megacities, there was surprisingly high contribution from long-range transport for both nitrate and organic aerosol. The origin of organic PM was investigated by comprehensive analysis of aerosol mass spectrometer (AMS), radio-carbon and tracer measurements during two intensive campaigns. Primary fossil fuel combustion emissions constituted less than 20 % in winter and 40 % in summer of carbonaceous fine PM, unexpectedly small for a megacity. Cooking activities and, during winter, residential wood burning are the major primary organic PM sources. This analysis suggests that the major part of secondary organic aerosol is of modern origin , i.e., from biogenic precursors and from wood burning. Black carbon concentrations are on the lower end of values encountered in megacities worldwide, but still represent an issue for air quality. These comparatively low air pollution levels are due to a combination of low emissions per inhabitant , flat terrain, and a meteorology that is in general not conducive to local pollution build-up. This revised picture of a megacity only being partially responsible for its own average and peak PM levels has important implications for air pollution regulation policies.

Published
2015
Full Text
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10. Estimating Source Term Parameters through Probabilistic Bayesian inference: An Approach based on an Adaptive Multiple Importance Sampling Algorithm

Author

Rajaona, H., Armand, P., François SEPTIER, Delignon, Y., Olry, C., Moussafir, J., LAGIS-SI, Laboratoire d'Automatique, Génie Informatique et Signal (LAGIS), Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS), Centrale Lille, DAM Île-de-France (DAM/DIF), Direction des Applications Militaires (DAM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut TELECOM/TELECOM Lille1, Institut Mines-Télécom [Paris] (IMT), and ARIA Technologies

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Statistics::Computation
Abstract

International audience; This paper presents an adaptive approach based on probabilistic Bayesian inference to estimate the parameters of an atmospheric pollution source term. After introducing the problem and assessing the computational framework, we present an Importance Sampling based algorithm called Adaptive Multiple Importance Sampling (AMIS). It performs an efficient calculation of the source parameter posterior distribution by iteratively upgrading the proposal's parameters and recycling all generations of weighted samples, thus allowing a faster convergence and reducing the number of necessary iterations. We highlight the results of the AMIS by comparing it to a MCMC estimation in a simple example.

Published
2014

11. Comparison of lidar-derived PM10 with regional modeling and ground-based observations in the frame of MEGAPOLI experiment

Author

J.-C. Raut, M. Beekmann, Q. J. Zhang, K. Sartelet, P. Chazette, P. Royer, 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), LEOSPHERE France, LEOSPHERE, Chimie Atmosphérique Expérimentale (CAE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre d'Enseignement et de Recherche en Environnement Atmosphérique (CEREA), École des Ponts ParisTech (ENPC)-EDF R&D (EDF R&D), EDF (EDF)-EDF (EDF), 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), ARIA Technologies, 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), 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), 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), 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
lcsh:Chemistry, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], lcsh:QD1-999, [SDE.MCG]Environmental Sciences/Global Changes, [SDE.ES]Environmental Sciences/Environmental and Society, lcsh:Physics, lcsh:QC1-999
Abstract

An innovative approach using mobile lidar measurements was implemented to test the performances of chemistry-transport models in simulating mass concentrations (PM10) predicted by chemistry-transport models. A ground-based mobile lidar (GBML) was deployed around Paris onboard a van during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009. The measurements performed with this Rayleigh-Mie lidar are converted into PM10 profiles using optical-to-mass relationships previously established from in situ measurements performed around Paris for urban and peri-urban aerosols. The method is described here and applied to the 10 measurements days (MD). MD of 1, 15, 16 and 26 July 2009, corresponding to different levels of pollution and atmospheric conditions, are analyzed here in more details. Lidar-derived PM10 are compared with results of simulations from POLYPHEMUS and CHIMERE chemistry-transport models (CTM) and with ground-based observations from the AIRPARIF network. GBML-derived and AIRPARIF in situ measurements have been found to be in good agreement with a mean Root Mean Square Error RMSE (and a Mean Absolute Percentage Error MAPE) of 7.2 μg m−3 (26.0%) and 8.8 μg m−3 (25.2%) with relationships assuming peri-urban and urban-type particles, respectively. The comparisons between CTMs and lidar at ~200 m height have shown that CTMs tend to underestimate wet PM10 concentrations as revealed by the mean wet PM10 observed during the 10 MD of 22.4, 20.0 and 17.5 μg m−3 for lidar with peri-urban relationship, and POLYPHEMUS and CHIMERE models, respectively. This leads to a RMSE (and a MAPE) of 6.4 μg m−3 (29.6%) and 6.4 μg m−3 (27.6%) when considering POLYPHEMUS and CHIMERE CTMs, respectively. Wet integrated PM10 computed (between the ground and 1 km above the ground level) from lidar, POLYPHEMUS and CHIMERE results have been compared and have shown similar results with a RMSE (and MAPE) of 6.3 mg m−2 (30.1%) and 5.2 mg m−2 (22.3%) with POLYPHEMUS and CHIMERE when comparing with lidar-derived PM10 with periurban relationship. The values are of the same order of magnitude than other comparisons realized in previous studies. The discrepancies observed between models and measured PM10 can be explained by difficulties to accurately model the background conditions, the positions and strengths of the plume, the vertical turbulent diffusion (as well as the limited vertical model resolutions) and chemical processes as the formation of secondary aerosols. The major advantage of using vertically resolved lidar observations in addition to surface concentrations is to overcome the problem of limited spatial representativity of surface measurements. Even for the case of a well-mixed boundary layer, vertical mixing is not complete, especially in the surface layer and near source regions. Also a bad estimation of the mixing layer height would introduce errors in simulated surface concentrations, which can be detected using lidar measurements. In addition, horizontal spatial representativity is larger for altitude integrated measurements than for surface measurements, because horizontal inhomogeneities occurring near surface sources are dampened.

Published
2011
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12. Méthodologie pour un bilan environnemental physique du transport de marchandises en ville

Author

Albergel, Armand, Segalou, Erwan, Routhier, Jean-Louis, De Rham, Casimir, Sefsaf, Martine, ARIA Technologies, Laboratoire d'économie des transports (LET), Université Lumière - Lyon 2 (UL2)-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), and Systems Consult

Subjects
zone urbaine, Transport de marchandises en ville (TMV), bilan environnemental, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, [SHS.ECO] Humanities and Social Sciences/Economics and Finance
Abstract

Collectivités auteurs : ADEME ; MELTM ; Laboratoire d'économie des transports ; CERTU. 88 p.Publication téléchargeable : www2.ademe.fr/servlet/getBin?name=1A3A72B3A0614A3AF52C73F204FA28BF1142499335947.pdf (Lien visité le 14.11.2006); Cet ouvrage pose les bases méthodologiques d'un bilan global des effets sur l'environnement des transports de marchandises en ville à l'échelle d'une agglomération. En s'appuyant sur les acquisitions de connaissances et les avancées méthodologiques les plus récentes, il permet pour la première fois de mesurer la part respective de la responsabilité sur le plan de la consommation énergétique et de l'environnement atmosphérique des différents segments de trafic urbains à savoir le transport de marchandises en ville (y compris les déplacements d'approvisionnement des ménages par leurs propres moyens et les flux générés par la gestion urbaine), les autres déplacements de voitures particulières au sein d'une agglomération ainsi que le transit d'agglomération. Cet ouvrage s'adresse essentiellement aux aménageurs urbains, collectivités locales et bureaux d'étude en charge des politiques locales du transport et de l'aménagement, notamment dans le cadre des plans de déplacement urbains. Il concerne plus généralement toute personne intéressée par la mise en œuvre des politiques de développement durable en milieu urbain.

Published
2006

13. The Anemos Project : Next Generation forecasting of Wind power

Author

Georges Kariniotakis, Didier Mayer, Heinemann Detlev, Jens Tambke, Julio Usaola, Ignacio Marti, Henrik Madsen, Torben Skov Nielsen, Christine Lac, Waldl, H. P., Félix Dierich, Jim Halliday, Richard Brownsword, Gregor Giebel, Jake Badger, Jacques Moussafir, George Kallos, Petroula Louka, Thierry Jouhanique, Manuel Calleja, John Toefting, Ryan, M., Carrington, M., John Indorf, Antiopi Gigantidou, Gonzales, G., Barosso, E., Barquero, C., Seguardo, P., Ignacio Cruz, Ana Maria Palomares, Hatziargyriou, Nikos D., Centre Énergétique et Procédés (CEP), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), University of Oldenburg, Universidad Carlos III de Madrid [Madrid] (UC3M), Centro Nacional de Energías Renovables - Fundación CENER-CIEMAT (CENER), Technical University of Denmark [Lyngby] (DTU), Météofrance, Météo France, overspeed GmBh&CoKG, GmBh&CoKG, CCLRC Rutherford Appleton Laboratory (RAL), Risø National Laboratory, Danish Ministry of Science, Technology and Innovation, ARIA Technologies, Institute of Accelerating Systems and Applications [Athens] (IASA), EDF R&D (EDF R&D), EDF (EDF), EHN, ELSAM, ESB National Grid - Power System Operations, ESB National Grid - Power System Operation, Energieversorgung Weser-Ems AG (EWE AG), Public Power Corporation - Grèce (PPC), PPC, Red Eléctrica de España (REE), Red Eléctrica de España, IDAE - Spain, Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid] (CIEMAT), Institute of Communication and Computer Systems, Department of Electrical and Computer Engineering (ICCS), National Technical University of Athens [Athens] (NTUA), European Project: ENK5-CT-2002-00665,ANEMOS, Mines Paris - PSL (École nationale supérieure des mines de Paris), Danmarks Tekniske Universitet = Technical University of Denmark (DTU), 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), and 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)

Subjects
on-line software, numerical w eather predictions, short-term forecasting, [SPI.NRJ]Engineering Sciences [physics]/Electric power, wind energy, forecasting, Wind power, energy meteorology, renewable energy
Abstract

International audience; This paper presents the objectives and the research work carried out in the frame of the ANEMOS project on short-term wind power forecasting. The aim of the project is to develop accurate models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting, exploiting both statistical and physical modeling approaches. The project focus on prediction horizons up to 48 hours ahead and investigates predictability of wind for higher horizons up to 7 days ahead useful i.e. for maintenance scheduling. Emphasis is given on the integration of high-resolution meteorological forecasts. For the offshore case, marine meteorology is considered as well as information by satellite-radar images. Specific modules are also developed for on-line uncertainty and prediction risk estimation. An integrated software platform, 'ANEMOS', is developed to host the various models. This system will be installed by several end-users for on-line operation at onshore and offshore wind farms for prediction at a local, regional and national scale. The applications include different terrain types and wind climates, on- and offshore cases, and interconnected or island grids. The on-line operation by the utilities will allow validation of the models and an analysis of the value of wind prediction for a competitive integration of wind energy in the developing liberalized electricity markets.

Published
2004

14. Anemos : development of a next generation wind power forecasting system for the large-scale integration of onshore & offshore wind farms

Author

Georges Kariniotakis, Didier Mayer, Moussafir, J., Chevallaz-Perrier, R., Julio Usaola, Sanchez, I., Ignacio Marti, Henrik Madsen, Torben Skov Nielsen, Lac, C., Frayssinet, P., Waldl, H. P., Halliday, J., Gregor Giebel, Kallos, G., Ottavi, J., Ulrich Focken, Lange, M., Detlev Heinemann, Kintxo Ancin, J., Toefting, J., Donnel, P. O., Mc Coy, D., Collmann, M., Gigandidou, A., Gonzales-Morales, G., Barquero, C., Cruz, I., Hatziargyriou, Nikos D., Centre Énergétique et Procédés (CEP), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), ARIA Technologies, Universidad Carlos III de Madrid [Madrid] (UC3M), Departamento Ingeniería Telemática, CENER, Centro Nacional de Energias Renovables, Technical University of Denmark [Lyngby] (DTU), Météo-France [Paris], Météo France, overspeed GmBh&CoKG, GmBh&CoKG, CCLRC-RAL, Risø National Laboratory for Sustainable Energy (Risø DTU), National and Kapodistrian University of Athens (NKUA), IASA, EDF R&D (EDF R&D), EDF (EDF), Fachbereich Informatik - Oldenburg, Carl Von Ossietzky Universität Oldenburg, EHN, ELSAM, ESB Nat. Grid, ESB Nat. Grid., EWE - Germany, EWE, PPC - Greece, PPC, REE - Spain, IDAE - Spain, CIEMAT, Ministerio de la Ciencia y de la Innovacion, National Technical University of Athens [Athens] (NTUA), Centre Énergétique et Procédés ( CEP ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), Universidad Carlos III de Madrid [Madrid], Technical University of Denmark [Lyngby] ( DTU ), Risø National Laboratory for Sustainable Energy ( Risø DTU ), National and Kapodistrian University of Athens, EDF R&D ( EDF R&D ), EDF ( EDF ), University of Oldenburg, and National Technical University of Athens [Athens] ( NTUA )

Subjects
numerical weather predictions, on-line software, [ SPI.NRJ ] Engineering Sciences [physics]/Electric power, short-term forecasting, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Wind power, wind integration
Abstract

International audience; This paper presents the objectives and the research work carried out in the frame of the ANEMOS project on short-term wind power forecasting. The aim of the project is to develop accurate models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting, exploiting both statistical and physical modeling approaches. The project focus on prediction horizons up to 48 hours ahead and investigates predictability of wind for higher horizons up to 7 days ahead useful i.e. for maintenance scheduling. Emphasis is given on the integration of highresolution meteorological forecasts. For the offshore case, marine meteorology is considered as well as information by satellite-radar images. An integrated software platform, ‘ANEMOS', is developed to host the various models. This system will be installed by several utilities for on-line operation at onshore and offshore wind farms for prediction at a local, regional and national scale. The applications include different terrain types and wind climates, on- and offshore cases, and interconnected or island grids. The on-line operation by the utilities will allow validation of the models and an analysis of the value of wind prediction for a competitive integration of wind energy in the developing liberalized electricity markets in the EU.

Published
2003

15. Atmospheric dispersion modelling and long-path UV DOAS measurements for air quality monitoring aler systems

Author

Delmas, Véronique, Bobbia, Michel, Menard, Tamara, Tatry, Véronique, Buty, Didier, Moussafir, Jacques, Thomas, Dominique, Coppalle, Alexis, Air Normand, Institut National de l'Environnement Industriel et des Risques (INERIS), ARIA Technologies, Environnement SA, Complexe de recherche interprofessionnel en aérothermochimie (CORIA), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), and Civs, Gestionnaire

Subjects
[SDE] Environmental Sciences, [SDE]Environmental Sciences
Published
1998

16. Towards Next Generation Short-term forcasting of Wind power - The Anemos Project

Author

Georges Kariniotakis, Moussafir, J., Buty, D., Usaola, J., Sanchez, I., Marti, I., Madsen, H., Nielsen, T. S., Lac, C., Frayssinet, P., H-P, Waldl, Dierich, F., Halliday, J., Brownsword, R., Giebel, G., Landberg, L., Kallos, G., Louka, P., Ottavi, J., Focken, U., Lange, M., Kintxo Ancín, J., Toefting, J., Mccoy, D., Fagan, E., Collmann, M., Thalassinakis, E., Gigandidou, A., Gonzales Morales, G., Barquero, C., Arriba, P., Cruz, I., Hatziargyriou, N., Sideratos, G., Centre Énergétique et Procédés (CEP), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), ARIA Technologies, Université Carlos III de Madrid, Centro Nacional de Energías Renovables - Fundación CENER-CIEMAT (CENER), Department of Informatics and Mathematical Modelling [Lyngby] (IMM), Technical University of Denmark [Lyngby] (DTU), Météo France, overspeed GmBh&CoKG, GmBh&CoKG, CCLRC Rutherford Appleton Laboratory (RAL), Risø National Laboratory for Sustainable Energy (Risø DTU), Institute of Accelerating Systems and Applications [Athens] (IASA), EDF (EDF), University of Oldenburg, EHN, ELSAM, ESB National Grid - Power System Operation, EWE - Germany, EWE, Public Power Corporation - Grèce (PPC), PPC, Red Eléctrica de España (REE), Red Eléctrica de España, IDAE - Spain, Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid] (CIEMAT), National Technical University of Athens [Athens] (NTUA), European Project: ENK5-CT-2002-00665,ANEMOS, Mines Paris - PSL (École nationale supérieure des mines de Paris), Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Météo-France Direction Interrégionale Sud-Est (DIRSE), and Météo-France

Subjects
numerical weather predictions, on-line software, short-term forecasting, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Wind power, wind integration, energy meteorology
Abstract

International audience; This paper presents the objectives and the research work carried out in the frame of the ANEMOS project on short-term wind power forecasting. The aim of the project is to develop accurate models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting, exploiting both statistical and physical modeling approaches. The project focus on prediction horizons up to 48 hours ahead and investigates predictability of wind for higher horizons up to 7 days ahead useful i.e. for maintenance scheduling. Emphasis is given on the integration of high-resolution meteorological forecasts. For the offshore case, marine meteorology is considered as well as information by satellite-radar images. Specific modules are also developed for on-line uncertainty and prediction risk estimation. An integrated software platform, 'ANEMOS', is developed to host the various models. This system will be installed by several end-users for on-line operation at onshore and offshore wind farms for prediction at a local, regional and national scale. The applications include different terrain types and wind climates, on-and offshore cases, and interconnected or island grids. The on-line operation by the utilities will allow validation of the models and an analysis of the value of wind prediction for a competitive integration of wind energy in the developing liberalized electricity markets in the EU.

17. Next Generation Short-Term Forecasting of Wind Power – Overview of the ANEMOS Project

Author

Kariniotakis, Georges, Halliday, J., Brownsword, R., Ignacio Marti, Palomares, Ana Maria, Cruz, I., Madsen, H., Nielsen, T. S., Nielsen, Henrik Aa, Focken, Ulrich, Lange, Matthias, Kallos, George, Louka, Petroula, Hatziargyriou, Nikos D., Frayssinet, P., Waldl, I., Dierich, Félix, Giebel, Gregor, Barthelmie, Rebecca Jane, Badger, Jake, Usaola, Julio, Sanchez, I., Heinemann, Detlev, Tambke, Jens, Moussafir, J., Descombes, G., Calleja, M., Jouhanique, T., Toefting, J., O Donnel, P., Ryan, M., Indorf, J., Barquero, C., Seguardo, P., Gigandidou, A., Thalassinakis, M., Gonzales, G., Bryans, L., Garrett, D., Centre Énergétique et Procédés (CEP), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), CCLRC-RAL, CENER, Centro Nacional de Energias Renovables, CIEMAT, Ministerio de la Ciencia y de la Innovacion, Department of Informatics and Mathematical Modeling [Lyngby] (DTU), Technical University of Denmark [Lyngby] (DTU), Fachbereich Informatik - Oldenburg, Carl Von Ossietzky Universität Oldenburg, National and Kapodistrian University of Athens (NKUA), National Technical University of Athens [Athens] (NTUA), Météo-France [Paris], Météo France, overspeed GmBh&CoKG, GmBh&CoKG, Risø National Laboratory for Sustainable Energy (Risø DTU), Universidad Carlos III de Madrid [Madrid] (UC3M), ARIA Technologies, Institut Mediterrani d'Estudis Avancats (IMEDEA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Universidad de las Islas Baleares (UIB), EDF R&D (EDF R&D), EDF (EDF), ELSAM, ESB Nat. Grid, ESB Nat. Grid., EWE - Germany, EWE, IDAE - Spain, PPC - Greece, PPC, REE, SONI, Centre Énergétique et Procédés ( CEP ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), Department of Informatics and Mathematical Modeling, Technical University of Denmark [Lyngby] ( DTU ), University of Oldenburg, National and Kapodistrian University of Athens, National Technical University of Athens [Athens] ( NTUA ), Risø National Laboratory for Sustainable Energy ( Risø DTU ), Universidad Carlos III de Madrid [Madrid], Institut Mediterrani d'Estudis Avancats ( IMEDEA ), Consejo Superior de Investigaciones Científicas [Spain] ( CSIC ) -Universidad de las Islas Baleares ( UIB ), EDF R&D ( EDF R&D ), and EDF ( EDF )

Subjects
numerical weather predictions, [ SPI.ENERG ] Engineering Sciences [physics]/domain_spi.energ, tools for wind integration, on-line software, [SPI.ENERG]Engineering Sciences [physics]/domain_spi.energ, short-term forecasting, Wind power
Abstract

International audience; The aim of the European Project ANEMOS is to develop accurate and robust models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced statistical, physical and combined modelling approaches were developed for this purpose. Priority was given to methods for on-line uncertainty and prediction risk assessment. An integrated software platform, 'ANEMOS', was developed to host the various models. This system is installed by several end-users for on-line operation and evaluation at a local, regional and national scale. Finally, the project demonstrates the value of wind forecasts for the power system management and market integration of wind power. Keywords: Wind power, short-term forecasting, numerical weather predictions, on-line software, tools for wind integration.

18. Changement climatique : Impacts sur la qualité de l’air

Author

Lacressonière, Gwendoline, ARIA Technologies, and Le Roux, Julien

Subjects
[SDE] Environmental Sciences, [SDE]Environmental Sciences
Abstract

National audience; La notion de « qualité de l’air » est apparue afin de quantifier les effets des polluants présents dans l’atmosphère sur la santé publique et la végétation. Depuis la fin des années 1970, la qualité de l’air se positionne comme une préoccupation majeure en Europe. Cette prise de conscience a engendré la mise en place de réglementations aux échelles Européennes, nationales et régionales pour quantifier les niveaux de polluants auxquels est soumise la population, évaluer l’efficacité des mesures prises pour limiter les émissions anthropiques de polluants, et informer la population sur la qualité de l’air. Ces mesures évoluent à mesure des nouvelles connaissances de l’impact sanitaire de ces polluants. Le changement climatique et la qualité de l’air s’influencent mutuellement. Ainsi, l’évolution du climat, en affectant notamment la dispersion atmosphérique, les émissions naturelles de feux et de biogéniques, les transformations chimiques et le transport de polluants, impacte la qualité de l’air et la santé des populations.Dans le cadre du projet Européen IMPACT2C, l’IPSL et ces laboratoires (LSCE, LISA) étaient partenaires, nous avons évalué les impacts d’une augmentation des températures globales à 2°C sur les concentrations de gaz et aérosols dans l’atmosphère. Plusieurs simulations numériques, conduites avec des modèles de chimie transport ont permis d’évaluer séparément les effets de réductions des émissions anthropiques (scénarios CLE*, MFR**) et du climat. Les résultats mettent en évidence que dans les décennies à venir, la qualité de l’air en Europe est principalement contrôlée par la réduction des émissions anthropiques. Ainsi une augmentation moyenne de la température de 2°C, et les effets climatiques associés, ne contrebalancent pas les effets bénéfiques des législations visant à réduire les émissions de polluants. Une étude complémentaire d’un réchauffement global de 3°C montre en revanche un impact très significatif sur les concentrations d’ozone en Europe. *Current Legislation Emissions **Maximum Feasible Reduction

19. Evaluation of Advanced Wind Power Forecasting Models – Results of the Anemos Project

Author

Ignacio Marti, Kariniotakis, Georges, Pinson, Pierre, Sanchez, I., Nielsen, T. S., Madsen, Henrik, Giebel, Gregor, Usaola, Julio, Palomares, Ana Maria, Brownsword, R., Tambke, Jens, Focken, Ulrich, Lange, Matthias, Sideratos, G., Descombes, G., CENER, Centro Nacional de Energias Renovables, Centre Énergétique et Procédés (CEP), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Departamento Ingeniería Telemática, Universidad Carlos III de Madrid [Madrid] (UC3M), Department of Informatics and Mathematical Modeling [Lyngby] (DTU), Technical University of Denmark [Lyngby] (DTU), Risø National Laboratory for Sustainable Energy (Risø DTU), CIEMAT, Ministerio de la Ciencia y de la Innovacion, CCLRC-RAL, Fachbereich Informatik - Oldenburg, Carl Von Ossietzky Universität Oldenburg, National Technical University of Athens [Athens] (NTUA), ARIA Technologies, Centre Énergétique et Procédés ( CEP ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), Universidad Carlos III de Madrid [Madrid], Department of Informatics and Mathematical Modeling, Technical University of Denmark [Lyngby] ( DTU ), Risø National Laboratory for Sustainable Energy ( Risø DTU ), University of Oldenburg, and National Technical University of Athens [Athens] ( NTUA )

Subjects
[ SPI.ENERG ] Engineering Sciences [physics]/domain_spi.energ, forecasting model, [SPI.ENERG]Engineering Sciences [physics]/domain_spi.energ, wind power
Abstract

Disponible : http://www.ewec2006proceedings.info/allfiles2/969_Ewec2006fullpaper.pdf; International audience; An outstanding question posed today by end-users like power system operators, wind power producers or traders is what performance can be expected by state-of-the-art wind power prediction models. This paper presents results of the first ever intercomparison of a number of advanced prediction systems performed in the frame of the European project Anemos. A framework for error characterization has been developed consisting by a measure- and a distribution-oriented approach. This comparison has given a perspective of the possibilities and limitations of the forecasts in the different test cases that were defined. At a second stage, the homogenous comparison process has permitted to evaluate the possibility of obtaining better performance by exploiting the merits of individual models through model combination. The paper presents the methodology and results from the combination approach.

20. Fast evaluation of three-dimensional gamma dose rate fields on non-equispaced grids for complex atmospheric radionuclide distributions.

Author

Fang S, Li X, Wu N, Li J, Liu Y, Xue N, Li H, Liu J, Xiong W, Zhang Q, and Albergel A

Subjects
Algorithms, Fourier Analysis, Gamma Rays, Radiation Monitoring, Radioisotopes analysis
Abstract

The gamma dose rate caused by airborne radionuclides is a major concern in the mitigation of nuclear accidents. Unfortunately, there is no fast method for calculating the three-dimensional (3D) gamma dose rate field near the source, because the corresponding airborne radionuclide distribution is usually calculated on non-equispaced grids and existing fast methods are only suitable for equispaced grids. This paper presents a method that accurately calculates the 3D dose rate field on non-equispaced grids, accelerating the computation by around two orders of magnitude. This method splits the time-consuming 3D integral in the dose rate model into a large convolution with a regularized smooth function and a small correction term. A nonuniform fast Fourier transform (NFFT) is used to rapidly calculate the convolution, which significantly enhances the computational speed. Our approach is applied to different grids and is compared with the FFT-based convolution method in two complex air dispersion simulations and a field experiment. The results show that the proposed method is in good agreement with the original 3D integral method and avoids grid-dependent interpolation errors in the FFT-based convolution method. This method enables a coupled analysis of wind, radioactivity, and dose rate on arbitrary grids, which is important for simplifying the emergency response in the case of small modular reactors., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Published
2020
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21. Validation and sensitivity study of Micro-SWIFT SPRAY against wind tunnel experiments for air dispersion modeling with both heterogeneous topography and complex building layouts.

Author

Wang S, Li X, Fang S, Dong X, Li H, Zhang Q, Nibert M, Buty D, and Alberge A

Subjects
Models, Theoretical, Nuclear Power Plants, Radioisotopes, Air Pollutants, Radiation Monitoring
Abstract

Micro-SWIFT SPRAY (MSS) is a 3D Lagrangian particle dispersion model that maintains a good balance between accuracy and computational cost. However, its capabilities for air dispersion modeling in the presence of both complex topography and high building densities have not been investigated for nuclear emergency response. In this study, MSS is systematically evaluated against two wind tunnel experiments that simulate a typical Chinese nuclear power plant with the above two features. The MSS predictions are compared with both 2D horizontal and vertical measurements. Sensitivity studies are performed with respect to the particle number, the lower bound of the turbulence intensity, and the horizontal and vertical grid size. The results demonstrate that ground-level predictions of both wind and radionuclide concentrations are in satisfactory agreement with the measurements under optimized parameter values. The vertical predictions exhibit site-dependent accuracy, but generally consistent tendencies. The default lower bound of the turbulence intensity in MSS may be insufficient for reproducing the correct plume width observed in the wind tunnel experiments. An increased lower bound is suggested to solve this problem. In addition, artificially high concentrations may arise near steep slopes if large horizontal/vertical grid sizes are used. Suitable parameters for preventing this problem are also provided., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Published
2020
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22. Particulate matter pollution in Kunshan High-Tech zone: Source apportionment with trace elements, plume evolution and its monitoring.

Author

Zhang S, Zhang Q, Albergel A, Buty D, Yu L, Wang H, Bi W, Cheng P, Chen F, Fang J, Hou R, Luan X, Shu C, and Su J

Subjects
Industry, Trace Elements analysis, Air Pollutants analysis, Air Pollution statistics & numerical data, Environmental Monitoring, Particulate Matter analysis
Abstract

Particulate matter (PM) in the Kunshan High-Tech zone is studied during a three-month campaign. PM and trace elements are measured by the online pollution monitoring, forecast-warning and source term retrieval system AS3. Hourly measured concentrations of PM 10 , PM 2.5 and 16 trace elements in the PM 2.5 section (Ca, Pb, Cu, Cl, V, Cr, Fe, Ti, Mn, Ni, Zn, Ga, As, Se, Sr, Ba) are focused. Source apportionment of trace elements by Positive Matrix Factorization modeling indicates that there are five major sources, including dust, industrial processing, traffic, combustion, and sea salt with contribution rate of 23.68%, 21.66%, 14.30%, 22.03%, and 6.89%, respectively. Prediction of plume dispersion from concrete plant and traffic emissions shows that PM 10 pollution of concrete plant is three orders of magnitude more than that of the traffic. The influence range can extend to more than 3km in 1hr. Because the footprint of the industrial plumes is constantly moving according to the local meteorological conditions, the fixed monitoring sites scattered in a few hundred meters haven't captured the heaviest pollution plume at the local scale of a few km 2 . As a more intensive monitoring network is not operationally possible, the use of online modeling gives accurate and quantitative information of plume location, which increases the spatial pollution monitoring capacity and improves the understanding of measurement data. These results indicate that the development of the AS3 system, which combines monitoring equipment and air pollution modeling systems, is beneficial to the real-time pollution monitoring in the industrial zone., (Copyright © 2018. Published by Elsevier B.V.)

Published
2018
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23. An air quality forecasting system in Beijing--application to the study of dust storm events in China in May 2008.

Author

Zhang Q, Laurent B, Velay-Lasry F, Ngo R, Derognat C, Marticorena B, and Albergel A

Subjects
Air Pollutants analysis, China, Air analysis, Dust analysis, Environmental Monitoring methods, Forecasting methods
Abstract

An air pollution forecast system, ARIA Regional, was implemented in 2007-2008 at the Beijing Municipality Environmental Monitoring Center, providing daily forecast of main pollutant concentrations. The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results. Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area. A dust episode having occurred at the end of May 2008 was analyzed in this article, and its impact of particulate matter on the Chinese air pollution index (API) was evaluated. Following our estimation, about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China, transporting towards southeast. This episode of dust storm influenced a large part of North China and East China, and also South Korea. The model result was then evaluated using satellite observations and in situ data. The simulated daily concentrations of total suspended particulate at 6:00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index. Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth (AOD) calculated from the simulations with AOD derived from MODIS satellite products. Finally, the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into account mineral dust correctly.

Published
2012
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24. Short-range evaluation of air pollution near bus and railway stations.

Author

Corfa E, Maury F, Segers P, Fresneau A, and Albergel A

Abstract

In the early morning, during workdays, intensive activity is observed at both bus and railway stations. This particular time is critical because of the combination of three factors: (1) simultaneous departure of many buses and trains, (2) cold engines, and, quite frequently, (3) stable meteorological conditions. In our approach, we use ARIA Local, a simulation package applying CFD tools to air pollution modeling, to study different scenarios. The CFD model used in this study is the MERCURE model, developed by Electricite de France. For a bus station, we simulate a typical morning peak hour situation and study in detail how the pollution is accumulated in the station courtyard and the impact on the close vicinity. Two scenarios are presented: one with classical diesel engine and one with buses using AQUAZOL or NGV fuel. The definition of the sources inside the Eulerian grid is described as static linear sources. The total emission is averaged over the mean path driven by the bus from the bus stop to the exit of the bus station. For a railway station, we simulate a situation in a real railway station within the city of Paris. The emission from a diesel "locomotive" and its impact on air quality is computed and compared to the impact of other nonmobile emissions. In this case, the definition of sources is described as mobile point sources following the trajectory of the train. These two scenarios are discussed in an urban context, taking into account the flow around buildings and different meteorological conditions.

Published
2004
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