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103. Bounded Attitude Control with Active Disturbance Rejection Capabilities for Multirotor UAVs

Author

Gerardo Mino-Aguilar, Lorenzo L. González Romeo, Sylvain Durand, José Fermi Guerrero-Castellanos, German Ardul Munoz-Hernandez, Nicolas Marchand, Wuiyevaldo F. Guerrero-Sánchez, Jesus Linares-Flores, Benemérita Universidad Autónoma de Puebla (BUAP), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), GIPSA - COntrol, PErception, Robots, navigation and Intelligent Computing (GIPSA-COPERNIC), GIPSA Pôle Sciences des Données (GIPSA-PSD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), Universidad Tecnológica de la Mixteca, Marchand, Nicolas, École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), and ANR-17-CE33-0008,e-VISER,Asservissement visuel événementiel(2017)

Subjects
Technology, 0209 industrial biotechnology, Disturbance (geology), QH301-705.5, Computer science, QC1-999, Stability (learning theory), bounded input, 02 engineering and technology, extended state observer, [SPI.AUTO]Engineering Sciences [physics]/Automatic, quaternion feedback, Attitude control, multirotor UAV, 020901 industrial engineering & automation, Control theory, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, 0202 electrical engineering, electronic engineering, information engineering, General Materials Science, State observer, Biology (General), Quaternion, QD1-999, Instrumentation, Fluid Flow and Transfer Processes, Physics, Process Chemistry and Technology, 020208 electrical & electronic engineering, General Engineering, Feed forward, Engineering (General). Civil engineering (General), ADRC, Computer Science Applications, Chemistry, [SPI.AUTO] Engineering Sciences [physics]/Automatic, Bounded function, TA1-2040, Multirotor, [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering
Abstract

This paper addresses an attitude tracking control design applied to multirotor unmanned aerial vehicles (UAVs) based on an ADRC approach. The proposed technique groups the endogenous and exogenous disturbances into a total disturbance, and then this is estimated online via an extended state observer (ESO). Further, a quaternion-based feedback is developed, which is assisted by a feedforward term obtained via the ESO to relieve the total disturbance actively. The control law is bounded, consequently, it takes into account the maximum capabilities of the actuators to reject the disturbances. The stability is analyzed in the ISS framework, guaranteeing that the closed loop (controller-ESO-UAV) is robustly stable. The simulation results allow validation of the theoretical features.

Published
2021
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104. Formation tracking of target moving on natural surfaces

Author

H. Nadour, Pierre Legreneur, Lionel Reveret, Nicolas Marchand, GIPSA - COntrol, PErception, Robots, navigation and Intelligent Computing (GIPSA-COPERNIC), GIPSA Pôle Sciences des Données (GIPSA-PSD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), Calcul des Variations, Géométrie, Image (CVGI), Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Laboratoire Interuniversitaire de Biologie de la Motricité (LIBM ), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), AirCap Regional project funded by French ARA Region, Capture and Analysis of Shapes in Motion (MORPHEO), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), and Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])

Subjects
Computer science, Real-time computing, 3D reconstruction, Swarm behaviour, UAVs control, Solid modeling, formation control, Collision, Tracking (particle physics), [SPI.AUTO]Engineering Sciences [physics]/Automatic, Sight, monitoring, Position (vector), [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, surveillance, target track-ing, Focus (optics), target tracking, film-making
Abstract

International audience; In this paper, we focus mainly on formation control of a swarm of UAV's tracking a moving target on a non regular mountainous surface. The main objective is to show how to dispatch the whole swarm of the quadrotors around the target (climber) with respect to the natural environment (mountain) taking advantage as much as possible from the free space surrounding the climber. The formation shape adapts with the neighbour environment topology, so that it avoids the collision with the environment and the concealing of the target from the UAV's cameras sights, and ensures as well the formation compactness and its closure to the target respecting the agent-agent and the agent-target security distances. The algorithm to define the free and safe hovering space (SHS) is then demonstrated with other two-steps algorithm to determine for each agent its desired position within the SHS. This work, that is considered as an introduction for upcoming works, does not miss to provide a simple control for each individual agent based on an established and corrected approximate dynamic model. The main idea to resolve this problem is explained in 2D and will be expanded for 3D environment, with other necessary and complementary enhancements. Keywords: UAVs control, formation control, target tracking, surveillance, film-making, 3D reconstruction, monitoring, quadrotor modeling.

Published
2021

106. Nonlinear control for ground-air trajectory tracking by a hybrid vehicle: theory and experiments

Author

Nicolas Marchand, Pedro Castillo, J. Colmenares-Vazquez, and D. Huerta-García

Subjects
0209 industrial biotechnology, Nonlinear system, Formalism (philosophy of mathematics), 020901 industrial engineering & automation, Control and Systems Engineering, Control theory, Computer science, 020208 electrical & electronic engineering, 0202 electrical engineering, electronic engineering, information engineering, Trajectory, 02 engineering and technology, Nonlinear control, Hybrid vehicle
Abstract

A nonlinear scheme for controlling a hybrid vehicle with capacities for terrestrial and aerial displacements is proposed in this paper. The nonlinear model of the vehicle is obtained from the Newton-Euler formalism taking into account two operation modes (ground and air). The attitude controller has been developed step by step for the full complete system and stabilizes both operation modes with the goal to produce a seamless transition between them. It has adaptive properties that helps to counteract the effects produced by the nonlinear uncertainties in the model. The nonlinear position controllers are conceived considering the gravity force for tracking an aerial or ground trajectory. Numerical simulations and real-time experiments are carried out for validating and verifying the good performance of the proposed algorithms.

Published
2019

107. Feedback Autonomic Provisioning for Guaranteeing Performance in MapReduce Systems

Author

Bogdan Robu, Damián Serrano, Sara Bouchenak, Nicolas Marchand, Mihaly Berekmeri, GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Distribution, Recherche d'Information et Mobilité (DRIM), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Grid'5000, ANR-11-LABX-0025,PERSYVAL-lab,Systemes et Algorithmes Pervasifs au confluent des mondes physique et numérique(2011), European Project: 610535,EC:FP7:ICT,FP7-ICT-2013-10,AMADEOS(2013), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, Computer Networks and Communications, business.industry, Computer science, Distributed computing, Node (networking), Big data, Feed forward, Workload, Provisioning, Cloud computing, 02 engineering and technology, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Computer Science Applications, Data modeling, 020901 industrial engineering & automation, Hardware and Architecture, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, 0202 electrical engineering, electronic engineering, information engineering, Benchmark (computing), 020201 artificial intelligence & image processing, business, Software, Information Systems
Abstract

International audience; Companies have a fast growing amounts of data to process and store, a data explosion is happening next to us. Currentlyone of the most common approaches to treat these vast data quantities are based on the MapReduce parallel programming paradigm.While its use is widespread in the industry, ensuring performance constraints, while at the same time minimizing costs, still providesconsiderable challenges. We propose a coarse grained control theoretical approach, based on techniques that have already provedtheir usefulness in the control community. We introduce the first algorithm to create dynamic models for Big Data MapReduce systems,running a concurrent workload. Furthermore we identify two important control use cases: relaxed performance - minimal resourceand strict performance. For the first case we develop two feedback control mechanism. A classical feedback controller and an evenbasedfeedback, that minimises the number of cluster reconfigurations as well. Moreover, to address strict performance requirements afeedforward predictive controller that efficiently suppresses the effects of large workload size variations is developed. All the controllersare validated online in a benchmark running in a real 60 node MapReduce cluster, using a data intensive Business Intelligenceworkload. Our experiments demonstrate the success of the control strategies employed in assuring service time constraints.

Published
2018

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

Author

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

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

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

Published
2021

109. New northern snowpack classification linked to vegetation cover on a latitudinal mega-transect across northeastern Canada

Author

Alexandre Langlois, Alain Royer, Florent Domine, Nicolas Marchand, Alexandre Roy, Gautier Davesne, Takuvik Joint International Laboratory ULAVAL-CNRS, Université Laval [Québec] (ULaval)-Centre National de la Recherche Scientifique (CNRS), Centre d'Etudes Nordiques (CEN), Université Laval [Québec] (ULaval), Université du Québec à Trois-Rivières (UQTR), Université de Sherbrooke (UdeS), and Université de Montréal (UdeM)

Subjects
010504 meteorology & atmospheric sciences, 0207 environmental engineering, propriétés de la neige, Climate change, 02 engineering and technology, Mega, snow cover classification, 01 natural sciences, Vegetation cover, interactions neigevégétation, Duration (project management), skin and connective tissue diseases, 020701 environmental engineering, Transect, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Ecology, snow-vegetation interaction, classification de la couverture de neige, 15. Life on land, Snowpack, snowpack properties, Snow, Latitudinal gradient, 13. Climate action, [SDE]Environmental Sciences, Environmental science, sense organs, Physical geography, Gradient latitudinal, human activities
Abstract

International audience; Changes in mass, extent, duration, and physical properties of snow are key elements for studying associated climate change feedbacks in northern regions. In this study, we analyzed snowpack physical properties along a 'mega' transect from 47°N to 83°N (4,000 km) in northeastern Canada, which includes marked transitions between ecozones from boreal forest to subarctic and arctic ecosystems. Our unique dataset of 391 detailed snowpits acquired over the last 20 years, complemented with snow data from weather stations, shows that snowpack properties such as snow water equivalent, snow depth, density, grain size and basal depth hoar fraction (DHF) are strongly linked to vegetation type. Based on these results, we propose an updated classification of snow types in three classes: boreal forest snow (47-58°N), tundra snow (58-74°N) and polar desert snow (74-83°N), which is more appropriate to the study area than the general north hemisphere classification commonly used. We also show that shrub presence along the transect contributes to a significant increase in DHF development which contributes most strongly to the thermal insulation properties of the snowpack. Overall, our analysis suggests that snow-vegetation interactions have a positive feedback effect on warming at northern latitudes.; Les changements dans la masse, l’étendue, la durée et les propriétés physiques du manteau neigeux sont des éléments clés pour l’étude des rétroactions du changement climatique dans les environnements nordiques. Dans cette étude, nous avons analysé les propriétés physiques du couvert nival le long d’un « méga » transect de 47°N à 83°N (4000 km) dans le nord-est du Canada, comprenant des transitions marquées entre l’écozone de la forêt boréale et les écosystèmes subarctiques et arctiques. Notre ensemble de données uniques de 391 puits de neige détaillés, acquis au cours des 20 dernières années, enrichi de données de neige provenant de stations météorologiques, montre que les propriétés du manteau neigeux telles que l’équivalent en eau de la neige (EEN), l’épaisseur de la neige, la densité, la taille des grains et la fraction de la couche de givre de profondeur sont fortement liées aux types de végétation. Ces résultats nous mènent à proposer une classification actualisée des types de neige en trois classes: neige de forêt boréale (47–58°N), neige de toundra (58–74°N) et neige de désert polaire (74–83°N), qui est plus appropriée à la région étudiée que la classification globalé de l’hémisphère nord généralement utiliséé. Nous mettons égalémént en évidence que la présence d’arbustes le long du transect contribue à une augmentation significative du développement de la couche basale du givre de profondeur. Globalement, notre analyse suggère que les interactions neige-végétation rétroagissent positivement sur le réchauffement nordique

Published
2021

110. Variability of the Atmospheric PM10 Microbiome in Three Climatic Regions of France

Author

Olivier Favez, Pierre Taberlet, Alexandre Thomasson, Gaëlle Uzu, Jean M.F. Martins, Jean-Luc Jaffrezo, Aurélie Bonin, Sébastien Conil, Benjamin Chazeau, Nicolas Marchand, Abdoulaye Samaké, Institut des Géosciences de l’Environnement (IGE), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire d'Ecologie Alpine (LECA ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Agence Nationale pour la Gestion des Déchets Radioactifs (ANDRA), Institut National de l'Environnement Industriel et des Risques (INERIS), ATMO Auvergne-Rhône-Alpes (ATMO-AURA), Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), and Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Microbiology (medical), 010504 meteorology & atmospheric sciences, Microorganism, lcsh:QR1-502, Beta diversity, 010501 environmental sciences, 01 natural sciences, Microbiology, bioaerosol, lcsh:Microbiology, DNA metabarcoding, Abundance (ecology), climatic gradient, Organic matter, bacteria, 0105 earth and related environmental sciences, Original Research, 2. Zero hunger, chemistry.chemical_classification, Ecology, sugar compounds, Vegetation, 15. Life on land, airborne microorganisms, Taxon, chemistry, Microbial population biology, 13. Climate action, [SDE]Environmental Sciences, regional sources, fungi, Bioaerosol
Abstract

Primary Biogenic Organic Aerosols (PBOA) were recently shown to be produced by only a few types of microorganisms, emitted by the surrounding vegetation in the case of a regionally homogeneous field site. This study presents the first comprehensive description of the structure and main sources of airborne microbial communities associated with temporal trends in Sugar Compounds (SC) concentrations of PM10 in 3 sites under a climatic gradient in France. By combining sugar chemistry and DNA Metabarcoding approaches, we intended to identify PM10-associated microbial communities and their main sources at three sampling-sites in France, under different climates, during the summer of 2018. This study accounted also for the interannual variability in summer airborne microbial community structure (bacteria and fungi only) associated with PM10-SC concentrations during a 2 consecutive years’ survey at one site. Our results showed that temporal changes in PM10-SC in the three sites are associated with the abundance of only a few specific taxa of airborne fungi and bacterial. These taxa differ significantly between the 3 climatic regions studied. The microbial communities structure associated with SC concentrations of PM10 during a consecutive 2-year study remained stable in the rural area. Atmospheric concentration levels of PM10-SC species varied significantly between the 3 study sites, but with no clear difference according to site typology (rural vs. urban), suggesting that SC emissions are related to regional rather than local climatic characteristics. The overall microbial beta diversity in PM10 samples is significantly different from that of the main vegetation around the urban sites studied. This indicates that the airborne microorganisms at these urban sites are not solely from the immediate surrounding vegetation, which contrasts with observations at the scale of a regionally homogeneous rural site in 2017. These results improve our understanding of the spatial behavior of tracers of PBOA emission sources, which need to be better characterized to further implement this important mass fraction of Organic Matter (OM) in Chemical Transport models (CTM).

Published
2021

111. Molecular characterization of gaseous and particulate oxygenated compounds at a remote site in Cape Corsica in the western Mediterranean basin

Author

Vincent Michoud, Elise Hallemans, Laura Chiappini, Eva Leoz-Garziandia, Aurélie Colomb, Sébastien Dusanter, Isabelle Fronval, François Gheusi, Jean-Luc Jaffrezo, Thierry Léonardis, Nadine Locoge, Nicolas Marchand, Stéphane Sauvage, Jean Sciare, Jean-François Doussin, 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), Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Ecole nationale supérieure Mines-Télécom Lille Douai (IMT Lille Douai), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'aérologie (LAERO), Université Toulouse III - Paul Sabatier (UT3), 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), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), 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), Cyprus International Institute for the Environment and Public Health, 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), Centre National de la Recherche Scientifique (CNRS)-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)-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 Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), 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 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
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], 13. Climate action
Abstract

The characterization of the molecular composition of organic carbon in both gaseous and aerosol is key to understanding the processes involved in the formation and aging of secondary organic aerosol. Therefore a technique using active sampling on cartridges and filters and derivatization followed by analysis using a thermal desorption–gas chromatography–mass spectrometer (TD–GC–MS) has been used. It is aimed at studying the molecular composition of organic carbon in both gaseous and aerosol phases (PM2.5) during an intensive field campaign which took place in Corsica (France) during the summer of 2013: the ChArMEx (Chemistry and Aerosol Mediterranean Experiment) SOP1b (Special Observation Period 1B) campaign. These measurements led to the identification of 51 oxygenated (carbonyl and or hydroxyl) compounds in the gaseous phase with concentrations between 21 and 3900 ng m−3 and of 85 compounds in the particulate phase with concentrations between 0.3 and 277 ng m−3. Comparisons of these measurements with collocated data using other techniques have been conducted, showing fair agreement in general for most species except for glyoxal in the gas phase and malonic, tartaric, malic and succinic acids in the particle phase, with disagreements that can reach up to a factor of 8 and 20 on average, respectively, for the latter two acids. Comparison between the sum of all compounds identified by TD–GC–MS in the particle phase and the total organic matter (OM) mass reveals that on average 18 % of the total OM mass can be explained by the compounds measured by TD–GC–MS. This number increases to 24 % of the total water-soluble OM (WSOM) measured by coupling the Particle Into Liquid Sampler (PILS)-TOC (total organic carbon) if we consider only the sum of the soluble compounds measured by TD–GC–MS. This highlights the important fraction of the OM mass identified by these measurements but also the relative important fraction of OM mass remaining unidentified during the campaign and therefore the complexity of characterizing exhaustively the organic aerosol (OA) molecular chemical composition. The fraction of OM measured by TD–GC–MS is largely dominated by di-carboxylic acids, which represent 49 % of the PM2.5 content detected and quantified by this technique. Other contributions to PM2.5 composition measured by TD–GC–MS are then represented by tri-carboxylic acids (15 %), alcohols (13 %), aldehydes (10 %), di-hydroxy-carboxylic acids (5 %), monocarboxylic acids and ketones (3 % each), and hydroxyl-carboxylic acids (2 %). These results highlight the importance of polyfunctionalized carboxylic acids for OM, while the chemical processes responsible for their formation in both phases remain uncertain. While not measured by the TD–GC–MS technique, humic-like substances (HULISs) represent the most abundant identified species in the aerosol, contributing for 59 % of the total OM mass on average during the campaign. A total of 14 compounds were detected and quantified in both phases, allowing the calculation of experimental partitioning coefficients for these species. The comparison of these experimental partitioning coefficients with theoretical ones, estimated by three different models, reveals large discrepancies varying from 2 to 7 orders of magnitude. These results suggest that the supposed instantaneous equilibrium being established between gaseous and particulate phases assuming a homogeneous non-viscous particle phase is questionable.

Published
2020

114. Measurement report: Long-term real-time characterisation of the submicronic aerosol and its atmospheric dynamic in a Mediterranean coastal city: Tracking the polluted events at the Marseille-Longchamp supersite

Author

Henri Wortham, Benjamin Chazeau, Nicolas Marchand, Grégory Gille, Barbara D'Anna, Boualem Mesbah, and Brice Temime-Roussel

Subjects
Pollution, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, Air pollution, Seasonality, Aethalometer, medicine.disease, Atmospheric sciences, medicine.disease_cause, 01 natural sciences, Aerosol, Sea breeze, Ultrafine particle, medicine, Environmental science, Mass concentration (chemistry), 0105 earth and related environmental sciences, media_common
Abstract

A supersite was recently implemented in Marseille to conduct intensive and advanced measurement studies for ambient aerosols. A Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) was deployed to investigate the chemical composition of submicronic aerosol over a 14-month period (1 February 2017–13 April 2018). Parallel measurements were performed with an Aethalometer, an ultrafine particle monitor and a suite of instruments to monitor regulated pollutants (PM2.5, PM10, NOx, O3 and SO2). The averaged PM1 chemical composition over the period was dominated by organics (49.7 %) and black carbon (17.1 %) while sulfate accounted for 14.6 %, nitrate for 10.2 %, ammonium for 7.9 % and chloride for 0.5 % only. Wintertime was found to be the season contributing the most to the annual PM1 mass concentration (30 %), followed by autumn (26 %), summer (24 %) and spring (20 %). During this season, OA and BC concentrations were found to contribute to 32 % and 31 % of their annual concentrations, respectively, as a combined result of heavy urban traffic, high emissions from residential heating, open combustion of green wastes and low planetary boundary layer (PBL) height. In summer, sulfate contribution to PM1 increased with an average and a maximum contribution to the PM1 of 24 % and 66 %. This is partly due to local photochemical production from its precursor SO2, locally emitted by shipping and industrial activities and advected to the city under sea breeze conditions. Results from backtrajectory cluster analysis suggest that, besides local anthropogenic activities, Mediterranean long-range transport contributes the most to the enrichment of the sulfate fraction. Another important feature of the summer season is that half of the most intense SO2 peaks happen at that time of the year and are associated to higher UFPs number. The fifteen days exceeding the target daily PM2.5 concentration value recommended by the World Health Organization (WHO) occurred during the cold period (late autumn-early spring). These episodes contribute to an increase of 6.5 % of the annual PM1 concentration. Local and long-range pollution episodes could be distinguished, accounting for 40 and 60 % of the exceedance days, respectively. Enhanced OA and BC concentrations, mostly originating from domestic wood burning under nocturnal land breeze conditions were observed during local pollution episodes, while high level of oxygenated OA and inorganic nitrate were associated to medium/long-range transported particles. In conclusion this supersite showed a high potential for the study of seasonality and pollution episodes phenomenology in Marseille over multiple geographic scales. The present paper highlights the significant contribution of regional transport of pollutants to the local air pollution that must be considered by local authorities in deploying effective PM abatement strategies.

Published
2020

116. Toward Cybersecurity of Unmanned Aircraft System operations under 'Specific' category

Author

Jean-Marc Thiriet, Amin El Mrabti, Trung Duc Tran, Nicolas Marchand, GIPSA - Safe, Controlled and Monitored Systems (GIPSA-SAFE), GIPSA Pôle Automatique et Diagnostic (GIPSA-PAD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), GIPSA - COntrol, PErception, Robots, navigation and Intelligent Computing (GIPSA-COPERNIC), GIPSA Pôle Sciences des Données (GIPSA-PSD), SOGILIS company [Grenoble], and Association Nationale Recherche Technologique (ANRT), 33 rue Rennequin -75017 Paris- SOGILIS company (France), 4 Avenue Doyen Louis Weil, 38000 Grenoble

Subjects
Cybersecurity, Computer science, Rulemaking, 020206 networking & telecommunications, 02 engineering and technology, SORA, Computer security, computer.software_genre, Critical infrastructure, Aviation safety, [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], Safety risk, Privacy, Specific Operation, Agency (sociology), 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], media_common.cataloged_instance, 020201 artificial intelligence & image processing, UAS, European union, Risk assessment, computer, media_common
Abstract

International audience; Nowadays, the increasing number of Unmanned Aircraft System (UAS) operations raises public concerns on cybersecurity issues. Therefore, it requires a methodology to address these issues during the UAS development. The Specific Operation Risk Assessment (SORA) is a risk assessment methodology developed by Joint Authorities for Rulemaking on Unmanned Aircraft System (JARUS). This methodology is endorsed by the European Union Aviation Safety Agency (EASA) as an acceptable means to fulfill the requirements of EU regulation related to UAS operations under the Specific category. The original SORA methodology focus on Safety risk scenarios only, which relate to unintentional threats and the harms to people’s life. In this paper, we introduce our solution to extend the methodology toward cybersecurity aspects. The extended methodology concerns risk scenarios relating to intentional digital threats and some other harms (e.g privacy violation, damage to critical infrastructure). A part of this solution is developed and is presented in this paper.

Published
2020

117. Event-Based Control for Online Training of Neural Networks

Author

Zilong Zhao, Nicolas Marchand, Bogdan Robu, Sophie Cerf, GIPSA - COntrol, PErception, Robots, navigation and Intelligent Computing (GIPSA-COPERNIC), GIPSA Pôle Sciences des Données (GIPSA-PSD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), GIPSA - Modelling and Optimal Decision for Uncertain Systems (GIPSA-MODUS), GIPSA Pôle Automatique et Diagnostic (GIPSA-PAD), ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019), SYSCO (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, 0209 industrial biotechnology, Control and Optimization, Neural Networks, Computer science, Machine Learning (stat.ML), 02 engineering and technology, 010501 environmental sciences, 01 natural sciences, Convolutional neural network, Image (mathematics), Machine Learning (cs.LG), 020901 industrial engineering & automation, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, Convergence (routing), [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY], Event Based Control, 0105 earth and related environmental sciences, Artificial neural network, Contextual image classification, Event (computing), Process (computing), Control and Systems Engineering, Control system, Gradient Methods, Algorithm
Abstract

International audience; Convolutional Neural Network (CNN) has become the most used method for image classification tasks. During its training the learning rate and the gradient are two key factors to tune for influencing the convergence speed of the model. Usual learning rate strategies are time-based i.e. monotonous decay over time. Recent state-of-the-art techniques focus on adaptive gradient algorithms i.e. Adam and its versions. In this paper we consider an online learning scenario and we propose two Event-Based control loops to adjust the learning rate of a classical algorithm E (Exponential)/PD (Proportional Derivative)-Control. The first Event-Based control loop will be implemented to prevent sudden drop of the learning rate when the model is approaching the optimum. The second Event- Based control loop will decide, based on the learning speed, when to switch to the next data batch. Experimental evaluation is provided using two state-of-the-art machine learning image datasets (CIFAR-10 and CIFAR-100). Results show the Event- Based E/PD is better than the original algorithm (higher final accuracy, lower final loss value), and the Double-Event-Based E/PD can accelerate the training process, save up to 67% training time compared to state-of-the-art algorithms and even result in better performance.

Published
2020

119. Leader-Following Consensus and Formation Control of VTOL-UAVs with Event-Triggered Communications †

Author

Victor R. Gonzalez-Diaz, Sylvain Durand, W. Fermin Guerrero-Sánchez, A. Vega-Alonzo, J. Fermi Guerrero-Castellanos, Nicolas Marchand, Josefina Castañeda-Camacho, Facultad de Ciencias de la Electrónica [Puebla] (FCE BUAP), Benemérita Universidad Autónoma de Puebla (BUAP), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), TOBACCO-ECOS NORD, Marchand, Nicolas, École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, and Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, VTOL-UAVs, Computer science, Control (management), Topology (electrical circuits), 02 engineering and technology, Biochemistry, Leader following, Article, event-triggered control, Analytical Chemistry, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Informatique [cs]/Automatique, 020901 industrial engineering & automation, Position (vector), Control theory, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, 0202 electrical engineering, electronic engineering, information engineering, cyber-physical systems (CPS), multi-agent systems, Electrical and Electronic Engineering, Instrumentation, ComputingMilieux_MISCELLANEOUS, Group (mathematics), Multi-agent system, 020208 electrical & electronic engineering, 16. Peace & justice, consensus and formation control, Atomic and Molecular Physics, and Optics, [SPI.AUTO] Engineering Sciences [physics]/Automatic, Bounded function, [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering
Abstract

This article presents the design and implementation of an event-triggered control approach, applied to the leader-following consensus and formation of a group of autonomous micro-aircraft with capabilities of vertical take-off and landing (VTOL-UAVs). The control strategy is based on an inner&ndash, outer loop control approach. The inner control law stabilizes the attitude and position of one agent, whereas the outer control follows a virtual leader to achieve position consensus cooperatively through an event-triggered policy. The communication topology uses undirected and connected graphs. With such an event-triggered control, the closed-loop trajectories converge to a compact sphere, centered in the origin of the error space. Furthermore, the minimal inter-sampling time is proven to be below bounded avoiding the Zeno behavior. The formation problem addresses the group of agents to fly in a given shape configuration. The simulation and experimental results highlight the performance of the proposed control strategy.

Published
2019
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120. Event-Based Boundary Control of a Linear <tex-math notation='LaTeX'>$2\times 2$ </tex-math> Hyperbolic System via Backstepping Approach

Author

Christophe Prieur, Nicolas Espitia, Antoine Girard, and Nicolas Marchand

Subjects
0209 industrial biotechnology, Computer science, Event (relativity), 010102 general mathematics, Boundary (topology), 02 engineering and technology, 01 natural sciences, Hyperbolic systems, Computer Science Applications, 020901 industrial engineering & automation, Exponential stability, Control and Systems Engineering, Control theory, Backstepping, Boundary value problem, 0101 mathematics, Electrical and Electronic Engineering
Abstract

In this paper, we introduce an event-based boundary control for a $2\times 2$ coupled linear hyperbolic system. We use a well-established backstepping controller which stabilizes the system along with a dynamic triggering condition which determines when the controller must be updated. The main contributions rely on the definition of an event-based controller under which global exponential stability of the system is achieved and, furthermore, the existence of a minimal dwell-time between two triggering times is guaranteed. The well-posedness of the system under the event-based controller is stated. A simulation example is presented to illustrate the results.

Published
2018

121. Primary emissions and secondary aerosol production potential from woodstoves for residential heating: Influence of the stove technology and combustion efficiency

Author

Emily A. Bruns, Jay G. Slowik, Henri Wortham, Amelie Bertrand, Imad El Haddad, André S. H. Prévôt, Brice Temime-Roussel, Nicolas Marchand, Simone M. Pieber, Giulia Stefenelli, Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), and Paul Scherrer Institute (PSI)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Air pollution, 010501 environmental sciences, medicine.disease_cause, Combustion, 7. Clean energy, 01 natural sciences, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Pellet, medicine, Mass concentration (chemistry), Air quality index, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Waste management, Chemistry, [SDE.ES]Environmental Sciences/Environmental and Society, Aerosol, 13. Climate action, Environmental chemistry, Stove, Combustor
Abstract

To reduce the influence of biomass burning on air quality, consumers are encouraged to replace their old woodstove with new and cleaner appliances. While their primary emissions have been extensively investigated, the impact of atmospheric aging on these emissions, including secondary organic aerosol (SOA) formation, remains unknown. Here, using an atmospheric smog chamber, we aim at understanding the chemical nature and quantify the emission factors of the primary organic aerosols (POA) from three types of appliances for residential heating, and to assess the influence of aging thereon. Two, old and modern, logwood stoves and one pellet burner were operated under typical conditions. Emissions from an entire burning cycle (past the start-up operation) were injected, including the smoldering and flaming phases, resulting in highly variable emission factors. The stoves emitted a significant fraction of POA (up to 80%) and black carbon. After ageing, the total mass concentration of organic aerosol (OA) increased on average by a factor of 5. For the pellet stove, flaming conditions were maintained throughout the combustion. The aerosol was dominated by black carbon (over 90% of the primary emission) and amounted to the same quantity of primary aerosol emitted by the old logwood stove. However, after ageing, the OA mass was increased by a factor of 1.7 only, thus rendering OA emissions by the pellet stove almost negligible compared to the other two stoves tested. Therefore, the pellet stove was the most reliable and least polluting appliance out of the three stoves tested. The spectral signatures of the POA and aged emissions by a High Resolution – Time of Flight – Aerosol Mass Spectrometer (Electron Ionization (EI) at 70 eV) were also investigated. The m/z 44 (CO2+) and high molecular weight fragments (m/z 115 (C9H7+), 137 (C8H9O2+), 167 (C9H11O3+) and 181 (C9H9O4+, C14H13+)) correlate with the modified combustion efficiency (MCE) allowing us to discriminate further between emissions generated from smoldering vs flaming conditions.

Published
2017

122. Comprehensive chemical characterization of industrial PM2.5 from steel industry activities

Author

Henri Wortham, Nicolas Marchand, Alexandre Sylvestre, Aurélie Mizzi, Sébastien Mathiot, Julien Dron, Fanny Masson, Boualem Mesbah, Jean Luc Jaffrezo, Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), and Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Atmospheric Science, Blast furnace, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, 010501 environmental sciences, engineering.material, 01 natural sciences, 7. Clean energy, chemistry.chemical_compound, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Organic matter, Sulfate, Chemical composition, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, chemistry.chemical_classification, Coke, Particulates, [SDE.ES]Environmental Sciences/Environmental and Society, chemistry, Iron ore, 13. Climate action, Ground granulated blast-furnace slag, Environmental chemistry, engineering
Abstract

Industrial sources are among the least documented PM (Particulate Matter) source in terms of chemical composition, which limits our understanding of their effective impact on ambient PM concentrations. We report 4 chemical emission profiles of PM 2.5 for multiple activities located in a vast metallurgical complex. Emissions profiles were calculated as the difference of species concentrations between an upwind and a downwind site normalized by the absolute PM 2.5 enrichment between both sites. We characterized the PM 2.5 emissions profiles of the industrial activities related to the cast iron (complex 1) and the iron ore conversion processes (complex 2), as well as 2 storage areas: a blast furnace slag area (complex 3) and an ore terminal (complex 4). PM 2.5 major fractions (Organic Carbon (OC) and Elemental Carbon (EC), major ions), organic markers as well as metals/trace elements are reported for the 4 industrial complexes. Among the trace elements, iron is the most emitted for the complex 1 (146.0 mg g −1 of PM 2.5 ), the complex 2 (70.07 mg g −1 ) and the complex 3 (124.4 mg g −1 ) followed by Al, Mn and Zn. A strong emission of Polycyclic Aromatic Hydrocarbons (PAH), representing 1.3% of the Organic Matter (OM), is observed for the iron ore transformation complex (complex 2) which merges the activities of coke and iron sinter production and the blast furnace processes. In addition to unsubstituted PAHs, sulfur containing PAHs (SPAHs) are also significantly emitted (between 0.011 and 0.068 mg g −1 ) by the complex 2 and could become very useful organic markers of steel industry activities. For the complexes 1 and 2 (cast iron and iron ore converters), a strong fraction of sulfate ranging from 0.284 to 0.336 g g −1 ) and only partially neutralized by ammonium, is observed indicating that sulfates, if not directly emitted by the industrial activity, are formed very quickly in the plume. Emission from complex 4 (Ore terminal) are characterized by high contribution of Al (125.7 mg g −1 of PM 2.5 ) but also, in a lesser extent, of Fe, Mn, Ti and Zn. We also highlighted high contribution of calcium ranging from 0.123 to 0.558 g g −1 for all of the industrial complexes under study. Since calcium is also widely used as a proxy of the dust contributions in source apportionment studies, our results suggest that this assumption should be reexamined in environments impacted by industrial emissions.

Published
2017

123. Event-switched control design with guaranteed performances

Author

Thibaut Raharijaona, Nicolas Marchand, Sylvain Durand, John J. Martinez, and B. Boisseau

Subjects
0209 industrial biotechnology, Mechanical Engineering, General Chemical Engineering, Event based, Feedback control, 020208 electrical & electronic engineering, Linear system, Biomedical Engineering, Aerospace Engineering, Control engineering, 02 engineering and technology, Invariant (physics), Industrial and Manufacturing Engineering, 020901 industrial engineering & automation, Control and Systems Engineering, Control theory, Bounded function, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Robust control, Event triggered, Control methods, Mathematics
Abstract

In this paper, a new event-switched control method is presented for controlling discrete-time linear systems subject to bounded disturbances. With this method, the nominal performance of the controlled system can be maintained although the control law does not have to be systematically updated. The feedback control loop can be opened as long a state-dependent event condition is satisfied. This condition is obtained using set theory approaches. In particular, the concept of robustly positive invariant sets is used to calculate the nominal performance and the event condition. The simulation presented and discussed here confirms the efficiency of the present approach. Issues relating to the real-time implementation of this approach are also discussed.

Published
2016

124. Feedback Control for Online Training of Neural Networks

Author

Nicolas Marchand, Sophie Cerf, Bogdan Robu, Zilong Zhao, GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019)

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, 050210 logistics & transportation, Artificial neural network, Contextual image classification, Computer science, business.industry, 05 social sciences, PID controller, Machine Learning (stat.ML), Convolutional neural network, Data modeling, Exponential function, Image (mathematics), Machine Learning (cs.LG), 03 medical and health sciences, 0302 clinical medicine, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, Robustness (computer science), 0502 economics and business, [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY], Artificial intelligence, business, 030217 neurology & neurosurgery
Abstract

International audience; Convolutional neural networks (CNNs) are commonly used for image classification tasks, raising the challenge of their application on data flows. During their training, adaptation is often performed by tuning the learning rate. Usual learning rate strategies are time-based i.e. monotonously decreasing. In this paper, we advocate switching to a performance-based adaptation, in order to improve the learning efficiency. We present E (Exponential)/PI (Proportional Integral)-Control, a conditional learning rate strategy that combines a feedback PI controller based on the CNN loss function, with an exponential control signal to smartly boost the learning and adapt the PI parameters. Stability proof is provided as well as an experimental evaluation using two state of the art image datasets (CIFAR-10 and Fashion-MNIST). Results show better performances than the related works (faster network accuracy growth reaching higher levels) and robustness of the E/PI-Control regarding its parametrization.

Published
2019

125. Importance of the PBOA fraction of PM10

Author

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

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

National audience

Published
2019

126. Event-triggered leader-following consensus of UAVs carrying a suspended load

Author

Nicolas Marchand, G. Mino-Azuilar, S. Durand, A. Vega-Alonzo, Victor R. Gonzalez-Diaz, José Fermi Guerrero-Castellanos, Benemérita Universidad Autónoma de Puebla (BUAP), GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, and Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, Eigenvalues and eigenfunctions, Decentralized control, Computer science, 020208 electrical & electronic engineering, Control (management), Stability (learning theory), 02 engineering and technology, Attitude control, Vehicle dynamics, Decentralised system, Collaboration, Unmanned aerial vehicles, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 020901 industrial engineering & automation, Control theory, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Radio frequency, 0202 electrical engineering, electronic engineering, information engineering, Suspended load, Connectivity, Information exchange
Abstract

International audience; This article presents the design and development of an event-triggered control strategy to solve the problem of leader-following consensus and formation problem for a group of UAVs carrying a suspended load individually. In this work, the vehicles exchange information through a network, which is represented by a directed and strongly connected graph. Then, employing a decentralized control law, each UAV decides when it has to send a new value to its neighbors. The stability of the complete system is carried out, and numerical results show the advantages wrt information exchange between UAVs, as well as excellent performance in the angular stabilization and the minimum swing for the suspended load.

Published
2019

127. Effect of Stove Technology and Combustion Conditions on Gas and Particulate Emissions from Residential Biomass Combustion

Author

Deepika Bhattu, Felix Klein, Peter Zotter, Nicolas Marchand, Imad El Haddad, Brice Temime-Roussel, André S. H. Prévôt, Jay G. Slowik, Josef Dommen, Thomas Nussbaumer, Giulia Stefenelli, Jun Zhou, Urs Baltensperger, Amelie Bertrand, Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), Lucerne University of Applied Sciences and Arts [Luzern], Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Inst Bioinformat & Syst Biol, Munich Informat Ctr Prot Sequences, Helmholtz-Zentrum München (HZM), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), and Helmholtz Zentrum München = German Research Center for Environmental Health

Subjects
Aerosols, Air Pollutants, Pellets, chemistry.chemical_element, General Chemistry, 010501 environmental sciences, Particulates, Combustion, 01 natural sciences, 7. Clean energy, Wood, [SDE.ES]Environmental Sciences/Environmental and Society, chemistry, 13. Climate action, Biomass combustion, Environmental chemistry, Stove, Environmental Chemistry, Environmental science, Particulate Matter, Oxygen rich, Biomass, Carbon, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract

We have systematically examined the gas and particle phase emissions from seven wood combustion devices. Among total carbon mass emitted (excluding CO2), CO emissions were dominant, together with nonmethane volatile organic compounds (NMVOCs) (10–40%). Automated devices emitted 1–3 orders of magnitude lower CH4 (0.002–0.60 g kg–1 of wood) and NMVOCs (0.01–1 g kg–1 of wood) compared to batch-operated devices (CH4: 0.25–2.80 g kg–1 of wood; NMVOCs: 2.5–19 g kg–1 of wood). 60–90% of the total NMVOCs were emitted in the starting phase of batch-operated devices, except for the first load cycles. Partial-load conditions or deviations from the normal recommended operating conditions, such as use of wet wood/wheat pellets, oxygen rich or deficit conditions, significantly enhanced the emissions. NMVOCs were largely dominated by small carboxylic acids and alcohols, and furans. Despite the large variability in NMVOCs emission strengths, the relative contribution of different classes showed large similarities among d...

Published
2019

128. Secondary Organic Aerosol Formation from Aromatic Alkene Ozonolysis: Influence of the Precursor Structure on Yield, Chemical Composition, and Mechanism

Author

Abdelwahid Mellouki, François Bernard, Nicolas Marchand, Gregory Eyglunent, Emilie Perraudin, Wuyin Zheng, Bénédicte Picquet-Varrault, Nicolas Maurin, Anne Monod, Annaïg Le Person, Jean-François Doussin, Laura Chiappini, Brice Temime-Roussel, 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 Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 (LASIRE), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut de Combustion, Aérothermique, Réactivité et Environnement (ICARE), Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut des Sciences de l'Ingénierie et des Systèmes (INSIS - CNRS), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille Institut (CLIL), Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut des Sciences de l'Ingénierie et des Systèmes (INSIS), 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)-Aix Marseille Université (AMU), Laboratoire de Spectrochimie Infrarouge et Raman - UMR 8516 (LASIR), and Centre National de la Recherche Scientifique (CNRS)-Université de Lille

Subjects
chemistry.chemical_classification, Chemical ionization, Ozonolysis, Ozone, 010304 chemical physics, Double bond, Chemistry, Alkene, 010402 general chemistry, Photochemistry, Mass spectrometry, 01 natural sciences, 0104 chemical sciences, [CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistry, chemistry.chemical_compound, 13. Climate action, Criegee intermediate, 0103 physical sciences, Physical and Theoretical Chemistry, Indene, [CHIM.OTHE]Chemical Sciences/Other
Abstract

International audience; The influence of the precursor chemical structure on secondary organic aerosol (SOA) formation was investigated through the study of the ozonolysis of two anthropogenic aromatic alkenes: 2-methylstyrene and indene. Experiments were carried out in three different simulation chambers: ICARE 7300L FEP Teflon chamber (ICARE, Orléans, France), EUPHORE FEP Teflon chamber (CEAM, Valencia, Spain), and CESAM evacuable stainless steel chamber (LISA, Créteil, France). For both precursors, SOA yield and growth were studied on a large range of initial concentrations (from ∼60 ppbv to 1.9 ppmv) and the chemical composition of both gaseous and particulate phases was investigated at a molecular level. Gas phase was described using FTIR spectroscopy and online gas chromatography coupled to mass spectrometry, and particulate chemical composition was analyzed (i) online by thermo-desorption coupled to chemical ionization mass spectrometry and (ii) offline by supercritical fluid extraction coupled to gas chromatography and mass spectrometry. The results obtained from a large set of experiments performed in three different chambers and using several complementary analytical techniques were in very good agreement. SOA yield was up to 10 times higher for indene ozonolysis than for 2-methylstyrene ozonolysis at the same reaction advancement. For 2-methylstyrene ozonolysis, formaldehyde and o-tolualdehyde were the two main gaseous phase products while o-toluic acid was the most abundant among six products detected within the particulate phase. For indene ozonolysis, traces of formic and phthalic acids as well as 11 species were detected in the gaseous phase and 11 other products were quantified in the particulate phase, where phthaldialdehyde was the main product. On the basis of the identified products, reaction mechanisms were proposed that highlight specific pathways due to the precursor chemical structure. These mechanisms were finally compared and discussed regarding SOA formation. In the case of 2-methylstyrene ozonolysis, ozone adds mainly on the external and monosubstituted double bond, yielding only one C8- and monofunctionalized Criegee intermediate and hence more volatile products as well as lower SOA mass than indene ozonolysis in similar experimental conditions. In the case of indene, ozone adds mainly on the five-carbon-ring and disubstituted C═C double bond, leading to the formation of two C9- and bifunctionalized Criegee intermediates, which then evolve via different pathways including the hydroperoxide channel and form highly condensable first-generation products.

Published
2019

130. Source apportionment of carbonaceous aerosols in the vicinity of a Mediterranean industrial harbor: A coupled approach based on radiocarbon and molecular tracers

Author

Edouard Bard, Jean-Luc Jaffrezo, Alexandre Sylvestre, Henri Wortham, Lise Bonvalot, Yoann Fagault, Boualem Mesbah, Nicolas Marchand, Thibaut Tuna, Laboratoire d'Instrumentation et Sciences Analytiques (LISA), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Chaire Evolution du climat et de l'océan, Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Atmo-Sud, GeographR, Institut des Géosciences de l’Environnement (IGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Collège de France - Chaire Evolution du climat et de l'océan, Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Collège de France (CdF)-Institut national des sciences de l'Univers (INSU - CNRS)-Aix Marseille Université (AMU)-Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), and Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)

Subjects
Pollution, Atmospheric Science, Carbonaceous particles, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, Air pollution, Levoglucosan, Biomass, chemistry.chemical_element, PM2.5, 010501 environmental sciences, medicine.disease_cause, 01 natural sciences, law.invention, chemistry.chemical_compound, law, medicine, Radiocarbon dating, 0105 earth and related environmental sciences, General Environmental Science, media_common, Total organic carbon, Mediterranean basin, Seasonality, medicine.disease, Radiocarbon, chemistry, 13. Climate action, Environmental chemistry, [SDE]Environmental Sciences, Environmental science, [CHIM.OTHE]Chemical Sciences/Other, Carbon
Abstract

International audience; Located in the Mediterranean Basin and close to Marseilles (France), Fos-sur-Mer is situated in the vicinity of industrial harbor and agricultural lands. Its location makes it prone to mixed pollution contributions. To characterize the background pollution and identify its multiple origins, carbonaceous particles are investigated using a coupled approach based on analyses of radiocarbon, elemental to total carbon ratio (EC/TC) and various molecular tracers such as levoglucosan. The measurements in about 30 samples collected during summer and fall/winter 2013, allow the detection of a strong seasonality of the pollution: the fall/winter PM2.5 concentration equals to three times the summer concentration and we observe a significant fluctuation of the relative contributions of fossil and non-fossil fractions (fNF is ≈ 0.83 for fall/winter samples and ≈ 0.59 for summer samples). Significant correlations between radiocarbon, levoglucosan and different methoxyphenols, allow the quantification of a major influence of biomass burning emissions during fall and winter. Biomass burning organic carbon (OCBB) and elemental carbon (ECBB) contribute to 44.5 % and 8.1 % of the TC, respectively, whereas their total contribution is only 3 % in summer samples. Biogenic emission are the main sources of carbon during summer. Significant correlations with malic acid and DL glyceric acid suggest a secondary origin. These correlations are not observed for the cold season samples, suggesting a different source for OCbio. Fossil carbons (ECF and OCF) from vehicular, shipping and industrial sources are relatively high during summer, with a predominance of the fossil origin in elemental carbon (98%). Nevertheless, the total fossil carbon concentration remains significant throughout the year, which is the signature of an important traffic and industrial activity during both seasons. Overall, our study based on radiocarbon and molecular tracers illustrates the power of a coupled approach in order to identify and quantify biomass burning, biogenic, traffic and industrial sources of carbonaceous aerosols.

Published
2019

131. Identification and quantification of particulate tracers of exhaust and non-exhaust vehicle emissions

Author

Nicolas Marchand, Jean-Luc Besombes, Jean-Luc Jaffrezo, Christine Buisson, Géraldine Guillaud, Hervé Chanut, Lucie Polo-Rehn, Benjamin Golly, Aurélie Charron, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Département Aménagement, Mobilités et Environnement (IFSTTAR/AME), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon-PRES Université Nantes Angers Le Mans (UNAM)-Communauté Université Paris-Est, Laboratoire LCME / Equipe Chimie de l'Environnement (LCME_CE), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon, ATMO Auvergne-Rhône-Alpes (ATMO-AURA), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon-Communauté Université Paris-Est-PRES Université Nantes Angers Le Mans (UNAM), and Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)

Subjects
Atmospheric Science, Chassis dynamometer, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, 01 natural sciences, 7. Clean energy, lcsh:Chemistry, chemistry.chemical_compound, Diesel fuel, 11. Sustainability, [CHIM]Chemical Sciences, 0105 earth and related environmental sciences, Fluoranthene, Anthracene, Particulates, Hopanoids, lcsh:QC1-999, chemistry, lcsh:QD1-999, 13. Climate action, Environmental chemistry, [SDE]Environmental Sciences, Environmental science, Pyrene, Vehicular Emissions, lcsh:Physics
Abstract

In order to identify and quantify key species associated with non-exhaust emissions and exhaust vehicular emissions, a large comprehensive dataset of particulate species has been obtained thanks to simultaneous near-road and urban background measurements coupled with detailed traffic counts and chassis dynamometer measurements of exhaust emissions of a few in-use vehicles well-represented in the French fleet. Elemental carbon, brake-wear metals (Cu, Fe, Sb, Sn, Mn), n-alkanes (C19-C26), light-molecular-weight polycyclic aromatic hydrocarbons (PAHs; pyrene, fluoranthene, anthracene) and two hopanes (17α21βnorhopane and 17α21βhopane) are strongly associated with the road traffic. Traffic-fleet emission factors have been determined for all of them and are consistent with most recent published equivalent data. When possible, light-duty- and heavy-duty-traffic emission factors are also determined. In the absence of significant non-combustion emissions, light-duty-traffic emissions are in good agreement with emissions from chassis dynamometer measurements. Since recent measurements in Europe including those from this study are consistent, ratios involving copper (Cu∕Fe and Cu∕Sn) could be used as brake-wear emissions tracers as long as brakes with Cu remain in use. Near the Grenoble ring road, where the traffic was largely dominated by diesel vehicles in 2011 (70 %), the OC∕EC ratio estimated for traffic emissions was around 0.4. Although the use of quantitative data for source apportionment studies is not straightforward for the identified organic molecular markers, their presence seems to well-characterize fresh traffic emissions.

Published
2019

132. Sources of PM2.5 at an urban-industrial Mediterranean city, Marseille (France): application of the ME-2 solver to inorganic and organic markers

Author

A. Detournay, Nicolas Marchand, I. El Haddad, Alexandre Sylvestre, Henri Wortham, André S. H. Prévôt, Dalia Salameh, Damien Piga, A. Armengaud, Francesco Canonaco, D. Robin, Jean-Luc Jaffrezo, Jorge Pey, Carlo Bozzetti, Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), AirPACA, Institut des Géosciences de l’Environnement (IGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), and Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
Mediterranean climate, Pollution, Atmospheric Science, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, [SDE.MCG]Environmental Sciences/Global Changes, 010501 environmental sciences, Combustion, 01 natural sciences, 7. Clean energy, Atmospheric Sciences, chemistry.chemical_compound, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, 11. Sustainability, Mass concentration (chemistry), ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, media_common, Total organic carbon, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Levoglucosan, [SDE.ES]Environmental Sciences/Environmental and Society, Aerosol, Green waste, chemistry, 13. Climate action, Environmental chemistry, Environmental science
Abstract

Impacted by a complex mixture of urban, industrial, shipping and also natural emissions, Marseille, the second most populated city in France, represents a very interesting case study for the apportionment of PM2.5 sources in a Mediterranean urban environment. In this study, daily PM2.5 samples were collected over a one-year period (2011−2012) at an urban background site, and were comprehensively analyzed for the determination of organic carbon (OC), elemental carbon (EC), major ions, trace elements/metals and specific organic markers. A constrained positive matrix factorization (PMF) analysis using the ME-2 (multilinear engine-2) solver was applied to this dataset. PMF results highlighted the presence of two distinct fingerprints for biomass burning (BB1 and BB2). BB1, assigned to open green waste burning peaks in fall (33%; 7.4 μg m−3) during land clearing periods, is characterized by a higher levoglucosan/OC ratio, while BB2, assigned to residential heating, shows the highest contribution during the cold period in winter (14%; 3.3 μg m−3) and it is characterized by high proportions from lignin pyrolysis products from the combustion of hardwood. Another interesting feature lies in the separation of two fossil fuel combustion processes (FF1 and FF2): FF1 likely dominated by traffic emissions, while FF2 likely linked with the harbor/industrial activities. On annual average, the major contributors to PM2.5 mass correspond to the ammonium sulfate-rich aerosol (AS-rich, 30%) and to the biomass burning emissions (BB1 + BB2, 23%). This study also outlined that during high PM pollution episodes (PM2.5 > 25 μg m−3), the largest contributing sources to PM2.5 were biomass burning (33%) and FF1 (23%). Moreover, 28% of the ambient mass concentration of OC is apportioned by the AS-rich factor, which is representative of an aged secondary aerosol, reflecting thus the importance of the oxidative processes occurring in a Mediterranean environment.

Published
2018

133. Vertical and horizontal distribution of regional new particle formation events in Madrid

Author

Nicolas Marchand, Esther Coz, Francisco J. Gómez-Moreno, Markku Kulmala, Enrique Mantilla, Tuukka Petäjä, Xavier Querol, Elisabeth Alonso-Blanco, Andrés Alastuey, Hee-Ram Eun, Cristina Carnerero, Cristina Reche, Brice Temime-Roussel, Lubna Dada, Kang-Ho Ahn, Marina Ealo, Miguel Escudero, Noemí Pérez, Alfonso Saiz-Lopez, Veli-Matti Kerminen, David C. S. Beddows, Roy M. Harrison, Hong-Ku Lee, Gloria Titos, Yong-Hee Park, Pauli Paasonen, European Research Council, Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), University of Granada [Granada], University of Helsinki, Department of Physics [Helsinki], Falculty of Science [Helsinki], University of Helsinki-University of Helsinki, Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid] (CIEMAT), Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), National Centre for Atmospheric Science [Leeds] (NCAS), Natural Environment Research Council (NERC), Helsinki Institute of Physics (HIP), Universitat Politècnica de Catalunya. Doctorat en Enginyeria Ambiental, Department of Physics, Universidad de Granada = University of Granada (UGR), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, and Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Convection, Atmospheric Science, 010504 meteorology & atmospheric sciences, Mixed layer, LONG-TERM MEASUREMENTS, 010501 environmental sciences, Noon, Atmospheric sciences, 114 Physical sciences, 01 natural sciences, Aerosols atmosfèrics -- Madrid, lcsh:Chemistry, Ultrafine particle, 11. Sustainability, NUCLEATION EVENTS, [CHIM]Chemical Sciences, ComputingMilieux_MISCELLANEOUS, Morning, 0105 earth and related environmental sciences, CONTINENTAL BOUNDARY-LAYER, Aerosols, AEROSOL-SIZE DISTRIBUTIONS, ATMOSPHERIC AEROSOL, METROPOLITAN-AREA, Atmospheric aerosols, ORGANIC AEROSOLS, lcsh:QC1-999, Aerosol, lcsh:QD1-999, Ultrafine particles, 13. Climate action, [SDE]Environmental Sciences, SPATIOTEMPORAL VARIABILITY, Environmental science, Particle, Particle size, New particle formation, lcsh:Physics, NUMBER CONCENTRATION, Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica [Àrees temàtiques de la UPC], NPF
Abstract

The vertical profile of new particle formation (NPF) events was studied by comparing the aerosol size number distributions measured aloft and at surface level in a suburban environment in Madrid, Spain, using airborne instruments. The horizontal distribution and regional impact of the NPF events was investigated with data from three urban, urban background, and suburban stations in the Madrid metropolitan area. Intensive regional NPF episodes followed by particle growth were simultaneously recorded at three stations in and around Madrid during a field campaign in July 2016. The urban stations presented larger formation rates compared to the suburban station. Condensation and coagulation sinks followed a similar evolution at all stations, with higher values at urban stations. However, the total number concentration of particles larger than 2.5 nm was lower at the urban station and peaked around noon, when black carbon (BC) levels are at a minimum. The vertical soundings demonstrated that ultrafine particles (UFPs) are formed exclusively inside the mixed layer. As convection becomes more effective and the mixed layer grows, UFPs are detected at higher levels. The morning soundings revealed the presence of a residual layer in the upper levels in which aged particles (nucleated and grown on previous days) prevail. The particles in this layer also grow in size, with growth rates significantly smaller than those inside the mixed layer. Under conditions with strong enough convection, the soundings revealed homogeneous number size distributions and growth rates at all altitudes, which follow the same evolution at the other stations considered in this study. This indicates that UFPs are detected quasi-homogenously in an area spanning at least 17 km horizontally. The NPF events extend over the full vertical extension of the mixed layer, which can reach as high as 3000 m in the area, according to previous studies. On some days a marked decline in particle size (shrinkage) was observed in the afternoon, associated with a change in air masses. Additionally, a few nocturnal nucleation-mode bursts were observed at the urban stations, for which further research is needed to elucidate their origin. © Author(s) 2018., This work was supported by the Spanish Ministry of Agriculture, Fishing, Food and Environment; the Ministry of Economy, Industry and Competitiveness; the Madrid City Council and Regional Government; FEDER funds under the project HOUSE (CGL2016-78594-R); the CUD of Zaragoza (project CUD 2016-05); the Government of Catalonia (AGAUR 2017 SGR44); and the Korean Ministry of Environment through “The Eco-Innovation project”. The funding received by ERA-PLANET (http://www.era-planet.eu, last access: 16 November 2018), the trans-national project SMURBS (http://www.smurbs.eu, last access: 16 November 2018) (Grant agreement No. 689443), and the support of the Academy of Finland via the Center of Excellence in Atmospheric Sciences are acknowledged. These results are part of a project (ATM-GTP/ERC) that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant agreement No. 742206). The authors also acknowledge the Doctoral program of Atmospheric Sciences at the University of Helsinki (ATM-DP). Markku Kulmala acknowledges the support of the Academy of Finland via his Academy Professorship (no. 302958). We also thank the City Council of Majadahonda for logistic assistance, and the Instituto de Ciencias Agrarias, Instituto de Salud Carlos III, Alava Ingenieros, TSI, Solma Environmental Solutions, and Airmodus for their support.

Published
2018

134. Rotorcraft with a 3DOF Rigid Manipulator: Quaternion-based Modeling and Real-time Control Tolerant to Multi-body Couplings

Author

José Juan Téllez-Guzmán, Juan Escareno, J. U. Alvarez-Munoz, Micky Rakotondrabe, Jose-Fermi Guerrero-Castellanos, Nicolas Marchand, GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut Polytechnique des Sciences Avancées (IPSA), Facultad de Ciencias de la Electrónica [Puebla] (FCE BUAP), Benemérita Universidad Autónoma de Puebla (BUAP), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Instituto de Ingeniería [Mexico], Universidad Nacional Autónoma de México (UNAM), XLIM (XLIM), Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), and Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Lyapunov function, 0209 industrial biotechnology, Quadcopter, Computer science, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], 02 engineering and technology, Workspace, Degrees of freedom (mechanics), [SPI.AUTO]Engineering Sciences [physics]/Automatic, Attitude control, symbols.namesake, 020901 industrial engineering & automation, Real-time Control System, Control theory, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, 0202 electrical engineering, electronic engineering, information engineering, Quaternion, Applied Mathematics, 020208 electrical & electronic engineering, Computer Science Applications, Control and Systems Engineering, Modeling and Simulation, symbols, Bounded-input control, Quaternion and Newton-Euler Modeling, Robotic arm, Observer-based control, Aerial Manipulator
Abstract

International audience; This paper proposes a simple solution for the stabilization of a mini-quadcopter carrying a 3DoF (degrees of freedom) ma-nipulator robot in order to enhance its achievable workspace and application profile. Since the motion of the arm induces torques which degrade the stability of the system, in the present work, we consider the stabilization of both subsystems: the quadcopter and the robot- ic arm. The mathematical model of the system is based on quaternions. Likewise, an attitude control law consisting of a bounded qua- ternion-based feedback stabilizes the quadcopter to a desired attitude while the arm is evolving. The next stage is the translational dy-namics which is simplified for control (nonlinear) design purposes. The aforementioned controllers are based on saturation functions whose stability is explicitly proved in the Lyapunov sense. Finally, experimental results and a statistical study validate the proposed control strategy.

Published
2018

135. Evidence of atmospheric nanoparticle formation from emissions of marine microorganisms

Author

David Parin, Nicolas Marchand, Karine Sellegri, A.N. Schwier, Sébastien Mas, Jorge Pey, A. Culot, Barbara D'Anna, Bruno Charrière, Clémence Rose, Alexandre Kukui, Brice Temime-Roussel, Richard Sempéré, Alfonso Saiz-Lopez, Anoop S. Mahajan, and H. L. Dewitt

Subjects
010504 meteorology & atmospheric sciences, Microorganism, Nucleation, Nanoparticle, Climate change, Pelagic zone, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Aerosol, Atmosphere, Geophysics, 13. Climate action, General Earth and Planetary Sciences, Particle, Environmental science, 14. Life underwater, 0105 earth and related environmental sciences
Abstract

Earth, as a whole, can be considered as a living organism emitting gases and particles into its atmosphere, in order to regulate its own temperature. In particular, oceans may respond to climate change by emitting particles that ultimately will influence cloud coverage. At the global scale, a large fraction of the aerosol number concentration is formed by nucleation of gas-phase species, but this process has never been directly observed above oceans. Here we present, using semicontrolled seawater-air enclosures, evidence that nucleation may occur from marine biological emissions in the atmosphere of the open ocean. We identify iodine-containing species as major precursors for new particle clusters’ formation, while questioning the role of the commonly accepted dimethyl sulfide oxidation products, in forming new particle clusters in the region investigated and within a time scale on the order of an hour. We further show that amines would sustain the new particle formation process by growing the new clusters to larger sizes. Our results suggest that iodine-containing species and amines are correlated to different biological tracers. These observations, if generalized, would call for a substantial change of modeling approaches of the sea-to-air interactions.

Published
2016

136. Microwave snow emission modeling uncertainties in boreal and subarctic environments

Author

Ghislain Picard, Alain Royer, Benoit Montpetit, Olivier St-Jean-Rondeau, Alexandre Langlois, Alex Mavrovic, Alexandre Roy, Nicolas Marchand, Centre d'Etudes Nordiques (CEN), Université Laval [Québec] (ULaval), Centre d'Applications et de Recherches en TELédétection [Sherbrooke] (CARTEL), Département de géomatique appliquée [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG ), 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 Grenoble Alpes [2016-2019] (UGA [2016-2019])-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 Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), 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 Grenoble Alpes [2016-2019] (UGA [2016-2019])-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])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Laval, Centre d'Applications et de Recherches en TELédétection (CARTEL), Université de Sherbrooke [Sherbrooke], 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), and Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
010504 meteorology & atmospheric sciences, 0211 other engineering and technologies, 02 engineering and technology, Atmospheric sciences, 01 natural sciences, [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology, lcsh:Environmental sciences, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, Remote sensing, lcsh:GE1-350, Taiga, lcsh:QE1-996.5, Vegetation, 15. Life on land, Snowpack, Snow, lcsh:Geology, Boreal, 13. Climate action, Brightness temperature, Environmental science, Spatial variability, Ice lens
Abstract

This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory Multi-Layer model (DMRT-ML) with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal forest and subarctic environments and a new in situ data set of measurements of snow properties (profiles of density, snow grain size and temperature, soil characterization and ice lens detection) acquired in the James Bay and Umiujaq regions of Northern Québec, Canada. A snow excavation experiment – where snow was removed from the ground to measure the microwave emission of bare frozen ground – shows that small-scale spatial variability (less than 1 km) in the emission of frozen soil is small. Hence, in our case of boreal organic soil, variability in the emission of frozen soil has a small effect on snow-covered brightness temperature (TB). Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of TB at 19 GHz to snow increases during the winter because of the snow grain growth that leads to scattering. Furthermore, the inclusion of observed ice lenses in DMRT-ML leads to significant improvements in the simulations at horizontal polarization (H-pol) for the three frequencies (up to 20 K of root mean square error). However, representation of the spatial variability of TB remains poor at 10.67 and 19 GHz at H-pol given the spatial variability of ice lens characteristics and the difficulty in simulating snowpack stratigraphy related to the snow crust. The results also show that, in our study with the given forest characteristics, forest emission reflected by the snow-covered surface can increase the TB up to 40 K. The forest contribution varies with vegetation characteristics and a relationship between the downwelling contribution of vegetation and the proportion of pixels occupied by vegetation (trees) in fisheye pictures was found. We perform a comprehensive analysis of the components that contribute to the snow-covered microwave signal, which will help to develop DMRT-ML and to improve the required field measurements. The analysis shows that a better consideration of ice lenses and snow crusts is essential to improve TB simulations in boreal forest and subarctic environments.

Published
2016

137. Event-based stabilization of linear systems of conservation laws using a dynamic triggering condition

Author

Nicolas Espitia, Nicolas Marchand, Antoine Girard, and Christophe Prieur

Subjects
0209 industrial biotechnology, Conservation law, Event (relativity), Event based, 020208 electrical & electronic engineering, Linear system, 02 engineering and technology, Filter (signal processing), Hyperbolic systems, 020901 industrial engineering & automation, Exponential stability, Control and Systems Engineering, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Mathematics
Abstract

This paper deals with a new event-based stabilization strategy for a class of linear hyperbolic systems of conservation laws. It includes an internal dynamic which serves as a filter mechanism for the event-triggered condition previously introduced in Espitia et al. (2016). The well-posedness as well as the global exponential stability of the resulting closed-loop system is studied. Some numerical simulations are performed to validate the theoretical results.

Published
2016

138. A Control-Theoretic Approach for Location Privacy in Mobile Applications

Author

Sara Bouchenak, Bogdan Robu, Nicolas Marchand, Sophie Cerf, Sonia Ben Mokhtar, GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Distribution, Recherche d'Information et Mobilité (DRIM), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Université Lumière - Lyon 2 (UL2)

Subjects
Focus (computing), Information privacy, Service (systems architecture), Computer science, media_common.quotation_subject, Distributed computing, 020206 networking & telecommunications, 02 engineering and technology, Data modeling, System dynamics, [SPI.AUTO]Engineering Sciences [physics]/Automatic, [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], [INFO.INFO-MC]Computer Science [cs]/Mobile Computing, Control theory, 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY], 020201 artificial intelligence & image processing, Relevance (information retrieval), Quality (business), media_common
Abstract

International audience; The prevalent use of mobile applications using location information to improve the quality of their service has arisen privacy issues, particularly regarding the extraction of user's points on interest. Many studies in the literature focus on presenting algorithms that allow to protect the user of such applications. However, these solutions often require a high level of expertise to be understood and tuned properly. In this paper, the first control-based approach of this problem is presented. The protection algorithm is considered as the " physical " plant and its parameters as control signals that enable to guarantee privacy despite user's mobility pattern. The following of the paper presents the first control formulation of POI-related privacy measure, as well as dynamic modeling and a simple yet efficient PI control strategy. The evaluation using simulated mobility records shows the relevance and efficiency of the presented approach.

Published
2018

139. Aerosol sources in the western Mediterranean during summertime: a model-based approach

Author

Mounir Chrit, Karine Sartelet, Jean Sciare, Jorge Pey, José B. Nicolas, Nicolas Marchand, Evelyn Freney, Karine Sellegri, Matthias Beekmann, François Dulac, 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 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), Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), 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), 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), 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), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université 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), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Laboratoire de Météorologie Physique - Clermont Auvergne (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne (UCA)-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
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 010504 meteorology & atmospheric sciences, 13. Climate action, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, ChArMEx, [SDE.MCG]Environmental Sciences/Global Changes, 14. Life underwater, 01 natural sciences, [SDE.ES]Environmental Sciences/Environmental and Society, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract

International audience; In the framework of ChArMEx (the Chemistry-Aerosol Mediterranean Experiment), the air quality model Polyphemus is used to understand the sources of inorganic and organic particles in the western Mediterranean and evaluate the uncertainties linked to the model parameters (mete-orological fields, anthropogenic and sea-salt emissions and hypotheses related to the model representation of conden-sation/evaporation). The model is evaluated by comparisons to in situ aerosol measurements performed during three consecutive summers (2012, 2013 and 2014). The model-to-measurement comparisons concern the concentrations of PM 10 , PM 1 , organic matter in PM 1 (OM 1) and inorganic aerosol concentrations monitored at a remote site (Ersa) on Corsica Island, as well as airborne measurements performed above the western Mediterranean Sea. Organic particles are mostly from biogenic origin. The model parameterization of sea-salt emissions has been shown to strongly influence the concentrations of all particulate species (PM 10 , PM 1 , OM 1 and inorganic concentrations). Although the emission of organic matter by the sea has been shown to be low, organic concentrations are influenced by sea-salt emissions; this is owing to the fact that they provide a mass onto which gaseous hydrophilic organic compounds can condense. PM 10 , PM 1 , OM 1 are also very sensitive to meteorology, which affects not only the transport of pollutants but also natural emissions (biogenic and sea salt). To avoid large and unrealistic sea-salt concentrations, a parameterization with an adequate wind speed power law is chosen. Sulfate is shown to be strongly influenced by anthropogenic (ship) emissions. PM 10 , PM 1 , OM 1 and sulfate concentrations are better described using the emission inventory with the best spatial description of ship emissions (EDGAR-HTAP). However, this is not true for nitrate, ammonium and chloride concentrations, which are very dependent on the hypotheses used in the model regarding condensation/evaporation. Model simulations show that sea-salt aerosols above the sea are not mixed with background transported aerosols. Taking the mixing state of particles with a dynamic approach to condensation/evaporation into account may be necessary to accurately represent inorganic aerosol concentrations.

Published
2018

140. Quaternion Modeling and Observer-based Torque Compensation of an Aerial Manipulator

Author

Nicolas Marchand, Thibaut Raharijaona, Micky Rakotondrabe, Jonatan Alavrez Muños, Jose Fermi Guerrero Castellanos, Juan Escareno, Institut Polytechnique des Sciences Avancées (IPSA), GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Facultad de Ciencias de la Electrónica [Puebla] (FCE BUAP), Benemérita Universidad Autónoma de Puebla (BUAP), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences du Mouvement Etienne Jules Marey (ISM), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Edited by Edgar N. Sánchez, Esteban A. Hernandez-Vargas, ANR-17-CE05-0014,CODE-Track,Méthodes de l'automatique pour la conception optimale de récupérateurs d'énergie piézoélectriques dédiés pour les systèmes de géolocalisation d'oiseaux(2017), Université de Franche-Comté (UFC), and Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Belfort-Montbeliard (UTBM)

Subjects
0209 industrial biotechnology, Quadcopter, Computer science, Aerial Manipulation, ACM: F.: Theory of Computation/F.2: ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Stochastic vs Deterministic State Estimation, 02 engineering and technology, Nonlinear control, Compensation (engineering), [SPI.AUTO]Engineering Sciences [physics]/Automatic, Attitude control, Computer Science::Robotics, 020901 industrial engineering & automation, 0203 mechanical engineering, Control theory, Position (vector), [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Torque, Manipulator, Quaternion, 020301 aerospace & aeronautics, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING, Control and Systems Engineering, Euler-Lagrange and Quaternion Modeling, Robot, Nonlinear Control
Abstract

International audience; This paper proposes a simple solution regarding the stabilization of a quadcopter unmanned aerial vehicle endowed with a manipulator arm. The manipulator robot is attached below the rotors plane and this one induces torques producing stability issues. The present study deals with the stabilization of the full system (quadcopter and arm) by means of a set of nonlinear control techniques. First, a mathematical model is proposed for the system. Then, an attitude control, consisting on a bounded quaternion-based feedback allows the quadcopter attitude stabilization while compensating adverse torques from manipulator's motion. A simple-to-implement strategy is proposed to estimate the actual torque for compensation purposes. Then, the formulation of a nonlinear control, which drives the aerial vehicle to a desired position is presented. Both controls consist on saturation functions. Simulation results validate the proposed control strategy and compare the results with different manipulator torque estimations.

Published
2018

141. Dynamic Modeling of Location Privacy Protection Mechanisms

Author

Nicolas Marchand, Sara Bouchenak, Sophie Cerf, Sonia Ben Mokhtar, Bogdan Robu, GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Distribution, Recherche d'Information et Mobilité (DRIM), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Université de Lyon-Institut National des Sciences Appliquées (INSA), Silvia Bonomi, and Etienne Rivière

Subjects
Service (systems architecture), Points of interest, Location privacy, Point of interest, Computer science, Location Based Services, Modeling, 020206 networking & telecommunications, 02 engineering and technology, Computer security, computer.software_genre, Control of computing systems, System dynamics, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Ask price, 020204 information systems, Metric (mathematics), Location-based service, 0202 electrical engineering, electronic engineering, information engineering, Relevance (information retrieval), [INFO]Computer Science [cs], Mobile device, computer
Abstract

International audience; Mobile applications tend to ask for users’ location in order to improve the service they provide. However, aside from increasing their service utility, they may also store these data, analyze them or share them with external parties. These privacy threats for users are a hot topic of research, leading to the development of so called Location Privacy Protection Mechanisms. LPPMs often are configurable algorithms that enable the tuning of the privacy protection they provide and thus the leveraging of the service utility. However, they usually do not provide ways to measure the achieved privacy in practice for all users of mobile devices, and even less clues on how a given configuration will impact privacy of the data given the specificities of everyone’s mobility. Moreover, as most Location Based Services require the user position in real time, these measures and predictions should be achieved in real time. In this paper we present a metric to evaluate privacy of obfuscated data based on users’ points of interest as well as a predictive model of the impact of a LPPM on these measure; both working in a real time fashion. The evaluation of the paper’s contributions is done using the state of the art LPPM Geo-I on synthetic mobility data generated to be representative of real-life users’ movements. Results highlight the relevance of the metric to capture privacy, the fitting of the model to experimental data, and the feasibility of the on-line mechanisms due to their low computing complexity.

Published
2018

142. Particle-bound reactive oxygen species (PB-ROS) emissions and formation pathways in residential wood smoke under different combustion and aging conditions

Author

Amelie Bertrand, Houssni Lamkaddam, André S. H. Prévôt, Jay G. Slowik, Giulia Stefenelli, Peter Zotter, Josef Dommen, Emily A. Bruns, Jun Zhou, Urs Baltensperger, Deepika Bhattu, Samuel Brown, Nicolas Marchand, Imad El-Haddad, Thomas Nussbaumer, Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), Lucerne University of Applied Sciences and Arts [Luzern], Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Swiss National Science Foundation starting grant BSSGI0_155846, and the China Scholarship Council (CSC), European Project: 730997,EUROCHAMP2020(2020), and Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Electrostatic precipitator, 010501 environmental sciences, Combustion, Mass spectrometry, 01 natural sciences, 7. Clean energy, Atmosphere, lcsh:Chemistry, Oxidation state, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, 0105 earth and related environmental sciences, chemistry.chemical_classification, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Reactive oxygen species, [SDE.ES]Environmental Sciences/Environmental and Society, lcsh:QC1-999, Aerosol, chemistry, lcsh:QD1-999, 13. Climate action, Environmental chemistry, Particle, lcsh:Physics
Abstract

Wood combustion emissions can induce oxidative stress in the human respiratory tract by reactive oxygen species (ROS) in the aerosol particles, which are emitted either directly or formed through oxidation in the atmosphere. To improve our understanding of the particle-bound ROS (PB-ROS) generation potential of wood combustion emissions, a suite of smog chamber (SC) and potential aerosol mass (PAM) chamber experiments were conducted under well-determined conditions for different combustion devices and technologies, different fuel types, operation methods, combustion regimes, combustion phases, and aging conditions. The PB-ROS content and the chemical properties of the aerosols were quantified by a novel ROS analyzer using the DCFH (2′,7′-dichlorofluorescin) assay and a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). For all eight combustion devices tested, primary PB-ROS concentrations substantially increased upon aging. The level of primary and aged PB-ROS emission factors (EFROS) were dominated by the combustion device (within different combustion technologies) and to a greater extent by the combustion regimes: the variability within one device was much higher than the variability of EFROS from different devices. Aged EFROS under bad combustion conditions were ∼ 2–80 times higher than under optimum combustion conditions. EFROS from automatically operated combustion devices were on average 1 order of magnitude lower than those from manually operated devices, which indicates that automatic combustion devices operated at optimum conditions to achieve near-complete combustion should be employed to minimize PB-ROS emissions. The use of an electrostatic precipitator decreased the primary and aged ROS emissions by a factor of ∼ 1.5 which is however still within the burn-to-burn variability. The parameters controlling the PB-ROS formation in secondary organic aerosol were investigated by employing a regression model, including the fractions of the mass-to-charge ratios m∕z 44 and 43 in secondary organic aerosol (SOA; f44 − SOA and f43 − SOA), the OH exposure, and the total organic aerosol mass. The regression model results of the SC and PAM chamber aging experiments indicate that the PB-ROS content in SOA seems to increase with the SOA oxidation state, which initially increases with OH exposure and decreases with the additional partitioning of semi-volatile components with lower PB-ROS content at higher OA concentrations, while further aging seems to result in a decay of PB-ROS. The results and the special data analysis methods deployed in this study could provide a model for PB-ROS analysis of further wood or other combustion studies investigating different combustion conditions and aging methods.

Published
2018

143. Modelling concentrations and properties of secondary aerosols in the Western Mediterranean

Author

Mounir Chrit, Karine Sartelet, Jean Sciare, Nicolas Marchand, Evelyne Freney, Nicolas, Jose B., Karine Sellegri, Marwa Majdi, Florian Couvidat, Matthias Beekmann, François Dulac, Jorge Pey, 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 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), Energy, Environment and Water Research Center (EEWRC), Cyprus Institute (CyI), Laboratoire Chimie de l'environnement (LCE), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institut National de l'Environnement Industriel et des Risques (INERIS), 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 National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), and Civs, Gestionnaire

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

International audience; The Mediterranean basin is among one of the areas that can be most sensitive to climate change (Giorgi et al, 2006). This fact, along with the population density around this basin, the high burden in aerosol concentration that the basin experiences throughout the year and the increasing projections for shipping emissions in the future make it an important area to explore. While the organic aerosol can have an important impact on the local and also the regional air quality presently and in the future, the simulation of this aerosol in the western part of the Mediterranean basin is a subject that has not been studied thoroughly for present conditions and has been studied even less for the future. The present work consists of two phases. The first phase explores existing climatic runs performed with CHIMERE chemistry transport model with climate inputs corresponding to RCP2.6, RCP4.5 and RCP8.5 during the French PRIMEQUAL Salut’air project; with a focus on the Mediterranean basin and the changes that these scenarios induce in the concentration of particulate matter and especially organic aerosols. The effects of boundary conditions, and anthropogenic emission changes are assessed. Major driving climate variables affecting organic and fine aerosol levels over the basin are identified. During the second phase, sensitivity runs of the RCP4.5 scenario are performed, in which three different aerosol models are used, including a VBS scheme with and without biogenic aging (Robinson et al. 2007, Lane et al. 2008), and a modified VBS scheme containing fragmentation and formation of non-volatile organic aerosols (Shrivastava et al., 2013). These schemes have been previously compared to measurements obtained during the MISTRAL / CHARMEX summer 2013 campaign (Cholakian, 2017, in preparation). 10 years of historic and years 10 future runs have been performed, and a specific method allows chosing years maximizing the temperature and organic aerosol differences between past and future runs. This allows assessing the climate sensitivity of different organic aerosol schemes. This is a new and complex topic, as organic aerosol formation depends on several parameters (temperature playing on biogenic VOC emissions and phase partition of semi-volatile compounds, winds impacting advection, and precipitation impacting aerosol removal) and their representation in a model.

Published
2018

144. Supplementary material to 'Vertical and horizontal distribution of regional new particle formation events in Madrid'

Author

Cristina Carnerero, Noemí Pérez, Cristina Reche, Marina Ealo, Gloria Titos, Hong-Ku Lee, Hee-Ram Eun, Yong-Hee Park, Lubna Dada, Pauli Paasonen, Veli-Matti Kerminen, Enrique Mantilla, Miguel Escudero, Francisco J. Gómez-Moreno, Elisabeth Alonso-Blanco, Esther Coz, Alfonso Saiz-Lopez, Brice Temime-Roussel, Nicolas Marchand, David C. S. Beddows, Roy M. Harrison, Tuukka Petäjä, Markku Kulmala, Kang-Ho Ahn, Andrés Alastuey, and Xavier Querol

Published
2018

145. Characterization of Gas-Phase Organics Using Proton Transfer Reaction Time-of-Flight Mass Spectrometry: Residential Coal Combustion

Author

Jay G. Slowik, Amelie Bertrand, Simone M. Pieber, Imad El Haddad, Junji Cao, Brice Temime-Roussel, Nicolas Marchand, André S. H. Prévôt, Felix Klein, Haiyan Ni, Veronika Pospisilova, Urs Baltensperger, Ru-Jin Huang, Dogushan Kilic, Giulia Stefenelli, Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), and Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
China, 010504 meteorology & atmospheric sciences, Air pollution, Coal combustion products, 010501 environmental sciences, medicine.disease_cause, 7. Clean energy, 01 natural sciences, complex mixtures, Mass Spectrometry, 11. Sustainability, medicine, otorhinolaryngologic diseases, Reaction Time, Environmental Chemistry, Coal, Europe, Eastern, Chemical composition, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Air Pollutants, business.industry, Anthracite, technology, industry, and agriculture, General Chemistry, Particulates, respiratory system, Aerosol, respiratory tract diseases, Europe, 13. Climate action, Environmental chemistry, Stove, Environmental science, Protons, business, [CHIM.OTHE]Chemical Sciences/Other
Abstract

International audience; Residential coal combustion is a significant contributor to particulate urban air pollution in Chinese mega cities and some regions in Europe. While the particulate emission factors and the chemical characteristics of the organic and inorganic aerosol from coal combustion is extensively studied, the chemical composition and non methane organic gas (NMOG) emission factors from residential coal combustion are mostly unknown. We conducted 23 individual burns in a traditional Chinese stove used for heating and cooking using five different coals with Chinese origins, characterizing the NMOG emissions using a proton transfer reaction time-of-fight mass spectrometer. The measured emission factors range from 1−15 g/kgcoal for bituminous coals and are below 0.1 g/kgcoal for anthracite coals. The emission factors from the bituminous coals are mostly influenced by the time until the coal is fully ignited. The emissions from the bituminous coals are dominated by aromatic and oxygenated aromatic compounds with a significant contribution of hydrocarbons. The results of this study can help to improve urban air pollution modeling in China and eastern Europe and can be used to constrain a coal burning factor in ambient gas phase positive matrix factorization studies.

Published
2018

148. Evolution of the chemical fingerprint of biomass burning organic aerosol during aging

Author

Amelie Bertrand, Giulia Stefenelli, Coty N. Jen, Simone M. Pieber, Emily A. Bruns, Brice Temime-Roussel, Jay G. Slowik, Allen H. Goldstein, Imad El Haddad, Urs Baltensperger, André S. H. Prévôt, Henri Wortham, and Nicolas Marchand

Abstract

A Thermal Desorption Aerosol Gas Chromatograph coupled to a High Resolution – Time of Flight – Aerosol Mass Spectrometer (TAG-AMS) was connected to an atmospheric chamber for the molecular characterization of the evolution organic aerosol (OA) emitted by woodstoves appliances for residential heating. Two logwood stoves (old and modern) and one pellet stove were operated under typical conditions. Emissions were aged during a time equivalent to 5 hours of atmospheric aging. 5 to 7 samples were collected and analyzed with TAG-AMS during each experiment. We detect and quantify over 70 compounds, including levoglucosan and nitrocatechols. We calculate the emission emissions factor (EF) of these tracers in the primary emissions and highlight the influence of the combustion efficiency on these emissions. Smoldering combustion contribute to higher EF and a more complex composition. We also demonstrate the effect of the atmospheric aging on the chemical fingerprint. The tracers are sorted into 3 categories according to the evolution of their concentration: primary compounds, non-conventional primary compounds, and secondary compounds. For each we provide a quantitative overview of their contribution to the OA mass at different times of the photo-oxidative process.

Published
2018

149. Influence of the vapor wall loss on the degradation rate constants in chamber experiments of levoglucosan and other biomass burning markers

Author

Amelie Bertrand, Giulia Stefenelli, Simone M. Pieber, Emily A. Bruns, Brice Temime-Roussel, Jay G. Slowik, Henri Wortham, André S. H. Prévôt, Imad El Haddad, Nicolas Marchand, Laboratoire Chimie de l'environnement (LCE), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC), Laboratory of Atmospheric Chemistry [Paul Scherrer Institute] (LAC), Paul Scherrer Institute (PSI), ADEME project VULCAIN (grant no. 1562C0019), and Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], 010504 meteorology & atmospheric sciences, 13. Climate action, [CHIM.OTHE]Chemical Sciences/Other, 01 natural sciences, 0105 earth and related environmental sciences
Abstract

Vapor wall loss has only recently been shown a potentially significant bias in atmospheric chamber studies. Yet, previous works aimed at the determination of the degradation rate of semi-volatile organic compounds (SVOCs) often did not account for this process. Here we evaluate the influence of vapor wall loss on the determination of the gas phase reaction rate kOH of several biomass burning markers (levoglucosan, mannosan, coniferyl aldehyde, 3-guaiacyl propanol, and acetosyringone) with hydroxyl radicals (OH). Emissions from the combustion of beech wood were injected into a 5.5 m3 Teflon atmospheric chamber, and aged for 4 hours (equivalent to 5–8 hours in the atmosphere). The particle phase compound concentrations were monitored using a Thermal Desorption Aerosol Gas Chromatograph coupled to a High-Resolution – Time of Flight – Mass Spectrometer (TAG-AMS). The observed depletion of the concentration was later modeled using two different approaches: the previously published approach which does not take into consideration partitioning and vapor wall loss, and an approach with a more complex theoretical framework which integrates all the processes likely influencing the particle phase concentration. We find that with the first approach one fails to predict the measured markers concentration time evolution. With the second approach, we determine that partitioning and vapor wall loss play a predominant role in the particle phase concentration depletion of all the compounds, while the reactivity with OH has a non-significative effect. Furthermore we show that kOH cannot be determined precisely without a strong constraint of the whole set of physical parameters necessary to formally describe the various processes involved. It was found that the knowledge of the saturation mass concentration C* is especially crucial. Therefore previously published rate constants of levoglucosan and more generally SVOCs with hydroxyl radicals inferred from atmospheric chamber experiments must be, at least, considered with caution.

Published
2018

150. Distributed Reconfigurable Formation Generator for Mini Aerial Vehicles

Author

Nicolas Marchand, Lara Brifion-Arranz, Jonathan Dumon, Matthieu Muschinowski, Marchand, Nicolas, Réseau national de plateformes robotiques d'excellence - - ROBOTEX2010 - ANR-10-EQPX-0044 - EQPX - VALID, GIPSA - Systèmes non linéaires et complexité (GIPSA-SYSCO), Département Automatique (GIPSA-DA), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), GIPSA-Services (GIPSA-Services), CAP2018, and ANR-10-EQPX-0044,ROBOTEX,Réseau national de plateformes robotiques d'excellence(2010)

Subjects
Computer Science::Robotics, Generator (computer programming), [SPI.AUTO] Engineering Sciences [physics]/Automatic, Control theory, Computer science, Position (vector), Distributed algorithm, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Trajectory, Robot, [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering, ComputingMilieux_MISCELLANEOUS, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

This video presents a distributed trajectory generator for formation control of multi-robot systems. The desired formation is defined by its geometric parameters but the position of each robot in the formation is not predefined a priori. The contribution is the design of a distributed algorithm to compute the robots' positions with respect to a given target while maintaining a particular formation which can be reconfigured on-line. A tracking controller ensures the convergence of the robots to their desired positions.

Published
2018

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