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1. Recommendations for reporting equivalent black carbon (eBC) mass concentrations based on long-term pan-European in-situ observations

Author: Marjan Savadkoohi, Marco Pandolfi, Olivier Favez, Jean-Philippe Putaud, Konstantinos Eleftheriadis, Markus Fiebig, Philip K. Hopke, Paolo Laj, Alfred Wiedensohler, Lucas Alados-Arboledas, Susanne Bastian, Benjamin Chazeau, Álvaro Clemente María, Cristina Colombi, Francesca Costabile, David C. Green, Christoph Hueglin, Eleni Liakakou, Krista Luoma, Stefano Listrani, Nikos Mihalopoulos, Nicolas Marchand, Griša Močnik, Jarkko V. Niemi, Jakub Ondráček, Jean-Eudes Petit, Oliver V. Rattigan, Cristina Reche, Hilkka Timonen, Gloria Titos, Anja H. Tremper, Stergios Vratolis, Petr Vodička, Eduardo Yubero Funes, Naděžda Zíková, Roy M. Harrison, Tuukka Petäjä, Andrés Alastuey, and Xavier Querol
Subjects: eBC, MAC, FAPs, EC, Absorption, Site specific MAC, Environmental sciences, GE1-350
Abstract: A reliable determination of equivalent black carbon (eBC) mass concentrations derived from filter absorption photometers (FAPs) measurements depends on the appropriate quantification of the mass absorption cross-section (MAC) for converting the absorption coefficient (babs) to eBC. This study investigates the spatial–temporal variability of the MAC obtained from simultaneous elemental carbon (EC) and babs measurements performed at 22 sites. We compared different methodologies for retrieving eBC integrating different options for calculating MAC including: locally derived, median value calculated from 22 sites, and site-specific rolling MAC. The eBC concentrations that underwent correction using these methods were identified as LeBC (local MAC), MeBC (median MAC), and ReBC (Rolling MAC) respectively. Pronounced differences (up to more than 50 %) were observed between eBC as directly provided by FAPs (NeBC; Nominal instrumental MAC) and ReBC due to the differences observed between the experimental and nominal MAC values. The median MAC was 7.8 ± 3.4 m2 g-1 from 12 aethalometers at 880 nm, and 10.6 ± 4.7 m2 g-1 from 10 MAAPs at 637 nm. The experimental MAC showed significant site and seasonal dependencies, with heterogeneous patterns between summer and winter in different regions. In addition, long-term trend analysis revealed statistically significant (s.s.) decreasing trends in EC. Interestingly, we showed that the corresponding corrected eBC trends are not independent of the way eBC is calculated due to the variability of MAC. NeBC and EC decreasing trends were consistent at sites with no significant trend in experimental MAC. Conversely, where MAC showed s.s. trend, the NeBC and EC trends were not consistent while ReBC concentration followed the same pattern as EC. These results underscore the importance of accounting for MAC variations when deriving eBC measurements from FAPs and emphasize the necessity of incorporating EC observations to constrain the uncertainty associated with eBC.
Published: 2024
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2. The variability of mass concentrations and source apportionment analysis of equivalent black carbon across urban Europe

Author: Marjan Savadkoohi, Marco Pandolfi, Cristina Reche, Jarkko V. Niemi, Dennis Mooibroek, Gloria Titos, David C. Green, Anja H. Tremper, Christoph Hueglin, Eleni Liakakou, Nikos Mihalopoulos, Iasonas Stavroulas, Begoña Artiñano, Esther Coz, Lucas Alados-Arboledas, David Beddows, Véronique Riffault, Joel F. De Brito, Susanne Bastian, Alexia Baudic, Cristina Colombi, Francesca Costabile, Benjamin Chazeau, Nicolas Marchand, José Luis Gómez-Amo, Víctor Estellés, Violeta Matos, Ed van der Gaag, Grégory Gille, Krista Luoma, Hanna E. Manninen, Michael Norman, Sanna Silvergren, Jean-Eudes Petit, Jean-Philippe Putaud, Oliver V. Rattigan, Hilkka Timonen, Thomas Tuch, Maik Merkel, Kay Weinhold, Stergios Vratolis, Jeni Vasilescu, Olivier Favez, Roy M. Harrison, Paolo Laj, Alfred Wiedensohler, Philip K. Hopke, Tuukka Petäjä, Andrés Alastuey, and Xavier Querol
Subjects: Air quality, European urban environment, Filter absorption photometer, Source apportionment, eBC, Environmental sciences, GE1-350
Abstract: This study analyzed the variability of equivalent black carbon (eBC) mass concentrations and their sources in urban Europe to provide insights into the use of eBC as an advanced air quality (AQ) parameter for AQ standards. This study compiled eBC mass concentration datasets covering the period between 2006 and 2022 from 50 measurement stations, including 23 urban background (UB), 18 traffic (TR), 7 suburban (SUB), and 2 regional background (RB) sites. The results highlighted the need for the harmonization of eBC measurements to allow for direct comparisons between eBC mass concentrations measured across urban Europe. The eBC mass concentrations exhibited a decreasing trend as follows: TR > UB > SUB > RB. Furthermore, a clear decreasing trend in eBC concentrations was observed in the UB sites moving from Southern to Northern Europe. The eBC mass concentrations exhibited significant spatiotemporal heterogeneity, including marked differences in eBC mass concentration and variable contributions of pollution sources to bulk eBC between different cities. Seasonal patterns in eBC concentrations were also evident, with higher winter concentrations observed in a large proportion of cities, especially at UB and SUB sites. The contribution of eBC from fossil fuel combustion, mostly traffic (eBCT) was higher than that of residential and commercial sources (eBCRC) in all European sites studied. Nevertheless, eBCRC still had a substantial contribution to total eBC mass concentrations at a majority of the sites. eBC trend analysis revealed decreasing trends for eBCT over the last decade, while eBCRC remained relatively constant or even increased slightly in some cities.
Published: 2023
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3. Phenomenology of ultrafine particle concentrations and size distribution across urban Europe

Author: Pedro Trechera, Meritxell Garcia-Marlès, Xiansheng Liu, Cristina Reche, Noemí Pérez, Marjan Savadkoohi, David Beddows, Imre Salma, Máté Vörösmarty, Andrea Casans, Juan Andrés Casquero-Vera, Christoph Hueglin, Nicolas Marchand, Benjamin Chazeau, Grégory Gille, Panayiotis Kalkavouras, Nikos Mihalopoulos, Jakub Ondracek, Nadia Zikova, Jarkko V. Niemi, Hanna E. Manninen, David C. Green, Anja H. Tremper, Michael Norman, Stergios Vratolis, Konstantinos Eleftheriadis, Francisco J. Gómez-Moreno, Elisabeth Alonso-Blanco, Holger Gerwig, Alfred Wiedensohler, Kay Weinhold, Maik Merkel, Susanne Bastian, Jean-Eudes Petit, Olivier Favez, Suzanne Crumeyrolle, Nicolas Ferlay, Sebastiao Martins Dos Santos, Jean-Philippe Putaud, Hilkka Timonen, Janne Lampilahti, Christof Asbach, Carmen Wolf, Heinz Kaminski, Hicran Altug, Barbara Hoffmann, David Q. Rich, Marco Pandolfi, Roy M. Harrison, Philip K. Hopke, Tuukka Petäjä, Andrés Alastuey, and Xavier Querol
Subjects: Air quality, Aerosols, Atmospheric particulate matter, Nanoparticles, Urban environment, Particle number concentrations, Environmental sciences, GE1-350
Abstract: The 2017–2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus.The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping.Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation.PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of
Published: 2023
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4. Distributed Finite-Time Coverage Control of Multi-Quadrotor Systems with Switching Topology

Author: Hilton Tnunay, Kaouther Moussa, Ahmad Hably, and Nicolas Marchand
Subjects: coverage control, finite-time stability, distributed control, quadcopter, multiagent systems, robotic sensor network, Mathematics, QA1-939
Abstract: This paper studies the distributed coverage control problem of multi-quadcopter systems connected with fixed and switching network topologies to guarantee the finite-time convergence. The proposed method modifies the objective function originating from the locational optimization problem to accommodate the consensus constraint and solves the problem within a given time limit. The coverage problem is solved by sending angular-rate and thrust commands to the quadcopters. By exploiting the finite-time stability theory, we ensure that the rotation and translation controllers of the quadcopters are finite-time stable both in fixed and switching communication topologies, able to be implemented distributively, and able to collaboratively drive the quadcopters towards the desired position and velocity of the Voronoi centroid independent of their initial states. After carefully designing and analyzing the performance, numerical simulations using a Robot Operating System (ROS) and Gazebo simulator are presented to validate the effectiveness of the proposed control protocols.
Published: 2023
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5. European aerosol phenomenology − 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

Author: Gang Chen, Francesco Canonaco, Anna Tobler, Wenche Aas, Andres Alastuey, James Allan, Samira Atabakhsh, Minna Aurela, Urs Baltensperger, Aikaterini Bougiatioti, Joel F. De Brito, Darius Ceburnis, Benjamin Chazeau, Hasna Chebaicheb, Kaspar R. Daellenbach, Mikael Ehn, Imad El Haddad, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Anna Font, Kirsten Fossum, Evelyn Freney, Maria Gini, David C Green, Liine Heikkinen, Hartmut Herrmann, Athina-Cerise Kalogridis, Hannes Keernik, Radek Lhotka, Chunshui Lin, Chris Lunder, Marek Maasikmets, Manousos I. Manousakas, Nicolas Marchand, Cristina Marin, Luminita Marmureanu, Nikolaos Mihalopoulos, Griša Močnik, Jaroslaw Nęcki, Colin O'Dowd, Jurgita Ovadnevaite, Thomas Peter, Jean-Eudes Petit, Michael Pikridas, Stephen Matthew Platt, Petra Pokorná, Laurent Poulain, Max Priestman, Véronique Riffault, Matteo Rinaldi, Kazimierz Różański, Jaroslav Schwarz, Jean Sciare, Leïla Simon, Alicja Skiba, Jay G. Slowik, Yulia Sosedova, Iasonas Stavroulas, Katarzyna Styszko, Erik Teinemaa, Hilkka Timonen, Anja Tremper, Jeni Vasilescu, Marta Via, Petr Vodička, Alfred Wiedensohler, Olga Zografou, María Cruz Minguillón, and André S.H. Prévôt
Subjects: European Overview, Source apportionment, Harmonised Protocol, Organic Aerosol, Long-term Datasets, Rolling PMF, Environmental sciences, GE1-350
Abstract: Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models.
Published: 2022
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6. Organic aerosol source apportionment by using rolling positive matrix factorization: Application to a Mediterranean coastal city

Author: Benjamin Chazeau, Imad El Haddad, Francesco Canonaco, Brice Temime-Roussel, Barbara D'Anna, Grégory Gille, Boualem Mesbah, André S.H. Prévôt, Henri Wortham, and Nicolas Marchand
Subjects: Environmental pollution, TD172-193.5, Meteorology. Climatology, QC851-999
Abstract: We investigated the contributions and the evolution of organic aerosol (OA) sources at the Marseille-Longchamp supersite (MRS-LCP, France) based on Time-of-flight Aerosol Chemical Speciation Monitor (ToF-ACSM) measurements of non-refractory PM1 over a fourteen-month period (1 February – 3 April 2018). The OA source apportionment was performed by positive matrix factorization (PMF) using the novel “rolling window” approach implemented in the Source Finder Professional (SoFi Pro). Here, PMF is performed over a 14-days window moving over the entire OA dataset, in order to account for the temporal variability of the source profiles.Six factors were resolved, including hydrocarbon-like organic aerosol (HOA) which is related to traffic exhausts, cooking-like organic aerosol (COA), biomass burning aerosol (BBOA), less oxidized organic aerosol (LOOA), more oxidized organic aerosol (MOOA) and a new defined source related to the mix between shipping and industrial plumes (Sh-IndOA). While HOA and COA consistently contribute to the total OA with on average 11.2% (ranging between 9.2 and 12.1% over the seasons) and 11.5% (11–12.1%), respectively, BBOA (11.7% on average) shows a larger seasonal variability with 18% in winter and no contribution in summer. BBOA profiles during winter were attributed to fresh biomass burning emissions from domestic heating, and more oxygenated profiles were assigned to regional land and agricultural waste burning for spring and early autumn. Sh-IndOA fraction is estimated to 4.5% (3.7–6.1%) and contributes to the total OA mass concentrations to a minor extent. The secondary organic aerosol (SOA) fraction includes both LOOA with 21.5% (18.8–27.2%) and MOOA with 39.6% (36.8–42.6%). Based on the f44/f43 analysis these sources appeared to be more linked to biogenic influences in summer, whereas the concentrations were associated with oxidized anthropogenic sources (biomass burning and road traffic) for the rest of the year. The investigation of MOOA geographical origins suggests some influence of air masses transported from the Rhône Valley and the west basin of the Mediterranean Sea.
Published: 2022
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7. Variability of the Atmospheric PM10 Microbiome in Three Climatic Regions of France

Author: Abdoulaye Samaké, Jean M. F. Martins, Aurélie Bonin, Gaëlle Uzu, Pierre Taberlet, Sébastien Conil, Olivier Favez, Alexandre Thomasson, Benjamin Chazeau, Nicolas Marchand, and Jean-Luc Jaffrezo
Subjects: airborne microorganisms, bioaerosol, regional sources, bacteria, fungi, sugar compounds, Microbiology, QR1-502
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
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8. Bounded Attitude Control with Active Disturbance Rejection Capabilities for Multirotor UAVs

Author: José Fermi Guerrero-Castellanos, Sylvain Durand, German Ardul Munoz-Hernandez, Nicolas Marchand, Lorenzo L. González Romeo, Jesús Linares-Flores, Gerardo Mino-Aguilar, and Wuiyevaldo F. Guerrero-Sánchez
Subjects: multirotor UAV, quaternion feedback, extended state observer, ADRC, bounded input, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
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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9. Overview of the French Operational Network for In Situ Observation of PM Chemical Composition and Sources in Urban Environments (CARA Program)

Author: Olivier Favez, Samuël Weber, Jean-Eudes Petit, Laurent Y. Alleman, Alexandre Albinet, Véronique Riffault, Benjamin Chazeau, Tanguy Amodeo, Dalia Salameh, Yunjiang Zhang, Deepchandra Srivastava, Abdoulaye Samaké, Robin Aujay-Plouzeau, Arnaud Papin, Nicolas Bonnaire, Carole Boullanger, Mélodie Chatain, Florie Chevrier, Anaïs Detournay, Marta Dominik-Sègue, Raphaële Falhun, Céline Garbin, Véronique Ghersi, Guillaume Grignion, Gilles Levigoureux, Sabrina Pontet, Jérôme Rangognio, Shouwen Zhang, Jean-Luc Besombes, Sébastien Conil, Gaëlle Uzu, Joël Savarino, Nicolas Marchand, Valérie Gros, Caroline Marchand, Jean-Luc Jaffrezo, and Eva Leoz-Garziandia
Subjects: France, urban air quality, aerosol chemical composition, source apportionment, monitoring strategies, Meteorology. Climatology, QC851-999
Abstract: The CARA program has been running since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks, to gain better knowledge—at a national level—on particulate matter (PM) chemistry and its diverse origins in urban environments. It results in strong collaborations with international-level academic partners for 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 throughout the year), as well as substantial contributions of mineral dust and primary biogenic particles (mostly during the warm period). Long-range transport phenomena, e.g., advection of secondary inorganic aerosols from the European continental sector and of Saharan dust into the French West Indies, are also discussed in this paper. Finally, we briefly address the use of stable isotope measurements (δ15N) and of various organic molecular markers for a better understanding of the origins of ammonium and of the different organic aerosol fractions, respectively.
Published: 2021
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10. Biomimetic-Based Output Feedback for Attitude Stabilization of Rigid Bodies: Real-Time Experimentation on a Quadrotor

Author: José Fermi Guerrero-Castellanos, Hala Rifaï, Nicolas Marchand, Rafael Cruz-José, Samer Mohammed, W. Fermín Guerrero-Sánchez, and Gerardo Mino-Aguilar
Subjects: biomimetic attitude stabilization, MEMS inertial sensors, bounded control, output feedback, flapping flyers, quadrotor unmanned aerial vehicles (UAVs), Mechanical engineering and machinery, TJ1-1570
Abstract: The present paper deals with the development of bounded feedback control laws mimicking the strategy adopted by flapping flyers to stabilize the attitude of systems falling within the framework of rigid bodies. Flapping flyers are able to orient their trajectory without any knowledge of their current attitude and without any attitude computation. They rely on the measurements of some sensitive organs: halteres, leg sensilla and magnetic sense, which give information about their angular velocity and the orientation of gravity and magnetic field vectors. Therefore, the proposed feedback laws are computed using direct inertial sensors measurements, that is vector observations with/without angular velocity measurements. Hence, the attitude is not explicitly required. This biomimetic approach is very simple, requires little computational power and is suitable for embedded applications on small control units. The boundedness of the control signal is taken into consideration through the design of the control laws by saturation of the actuators’ input. The asymptotic stability of the closed loop system is proven by Lyapunov analysis. Real-time experiments are carried out on a quadrotor using MEMS inertial sensors in order to emphasize the efficiency of this biomimetic strategy by showing the convergence of the body’s states in hovering mode, as well as the robustness with respect to external disturbances.
Published: 2015
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11. Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data

Author: Nicolas Marchand, Alain Royer, Gerhard Krinner, Alexandre Roy, Alexandre Langlois, and Céline Vargel
Subjects: soil temperature, permafrost, passive microwave, thermal infrared, snow cover, Land Surface Model, Radiative Transfer Model, Canadian arctic, Science
Abstract: High-latitude areas are very sensitive to global warming, which has significant impacts on soil temperatures and associated processes governing permafrost evolution. This study aims to improve first-layer soil temperature retrievals during winter. This key surface state variable is strongly affected by snow’s geophysical properties and their associated uncertainties (e.g., thermal conductivity) in land surface climate models. We used infrared MODIS land-surface temperatures (LST) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) brightness temperatures (Tb) at 10.7 and 18.7 GHz to constrain the Canadian Land Surface Scheme (CLASS), driven by meteorological reanalysis data and coupled with a simple radiative transfer model. The Tb polarization ratio (horizontal/vertical) at 10.7 GHz was selected to improve snowpack density, which is linked to the thermal conductivity representation in the model. Referencing meteorological station soil temperature measurements, we validated the approach at four different sites in the North American tundra over a period of up to 8 years. Results show that the proposed method improves simulations of the soil temperature under snow (Tg) by 64% when using remote sensing (RS) data to constrain the model, compared to model outputs without satellite data information. The root mean square error (RMSE) between measured and simulated Tg under the snow ranges from 1.8 to 3.5 K when using RS data. Improved temporal monitoring of the soil thermal state, along with changes in snow properties, will improve our understanding of the various processes governing soil biological, hydrological, and permafrost evolution.
Published: 2018
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12. Hovering by Gazing: A Novel Strategy for Implementing Saccadic Flight-Based Navigation in GPS-Denied Environments

Author: Augustin Manecy, Nicolas Marchand, and Stéphane Viollet
Subjects: Electronics, TK7800-8360, Electronic computers. Computer science, QA75.5-76.95
Abstract: Hovering flies are able to stay still in place when hovering above flowers and burst into movement towards a new object of interest (a target). This suggests that sensorimotor control loops implemented onboard could be usefully mimicked for controlling Unmanned Aerial Vehicles (UAVs). In this study, the fundamental head-body movements occurring in free-flying insects was simulated in a sighted twin-engine robot with a mechanical decoupling inserted between its eye (or gaze) and its body. The robot based on this gaze control system achieved robust and accurate hovering performances, without an accelerometer, over a ground target despite a narrow eye field of view (±5°). The gaze stabilization strategy validated under Processor-In-the-Loop (PIL) and inspired by three biological Oculomotor Reflexes (ORs) enables the aerial robot to lock its gaze onto a fixed target regardless of its roll angle. In addition, the gaze control mechanism allows the robot to perform short range target to target navigation by triggering an automatic fast “target jump” behaviour based on a saccadic eye movement.
Published: 2014
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13. Privacy protection control for mobile apps users

Author: Sophie Cerf, Bogdan Robu, Nicolas Marchand, Sara Bouchenak, Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL], GIPSA - Modelling and Optimal Decision for Uncertain Systems [GIPSA-MODUS], GIPSA - COntrol, PErception, Robots, navigation and Intelligent Computing [GIPSA-COPERNIC], Institut National des Sciences Appliquées de Lyon [INSA Lyon], Laboratoire d'InfoRmatique en Image et Systèmes d'information [LIRIS], Distribution, Recherche d'Information et Mobilité [DRIM], Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), GIPSA - Modelling and Optimal Decision for Uncertain Systems (GIPSA-MODUS), 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), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), 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), Distribution, Recherche d'Information et Mobilité (DRIM), and 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)
Subjects: Control and Systems Engineering, Applied Mathematics, control of computing systems location privacy differential-privacy modeling Sampled-Data Control, [INFO]Computer Science [cs], Electrical and Electronic Engineering, Computer Science Applications, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract: International audience; Predominant in today society, mobile apps are rising as promising application systems for automatic control. An app can be viewed as a plant, processing input signals (queries, phone data, etc.) and generating outputs (such as a service or an answer). Guaranteeing that the app complies with a desired behavior is a major safety challenge. This work focuses on privacy issues for geolocated mobile apps. Many applications use the location data to provide a service (e.g., navigation, fitness) or to improve it (e.g., weather forecast, social media). This gain in service utility comes at the cost of personal data sharing. Such threat to user privacy can be leveraged by protection mechanisms, e.g., addition of noise to the location data. However, state-of-the-art techniques still lack means of ensuring both data utility and privacy in a dynamics utilization context. This paper presents the first non-linear analytical modeling followed by a control formulation for regulating the privacy level in a mobile app. The privacy is sensed using the well established notion of Point of Interest. Through modeling, we highlight the control challenges, namely the non-linearity and time-variance of the plant, its high sensibility to noise and the impact of the user's mobility pattern-seen a disturbance. A controller is designed, combining feedback with anticipation action. Evaluation is performed using mobility records from two real-world multi-users datasets. Our approach enables, with a unique and universal tuning, to robustly meet privacy objectives with preserved utility and negligible computational overhead. Control algorithm, experimental evaluation and analysis scripts are available online for reproducibility.
Published: 2023

14. Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison

Author: Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, María Cruz Minguillón, 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), and Tang, M
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmospheric Science, [SDE]Environmental Sciences, Meteorology & Atmospheric Sciences, Source apportionment (SA), 0401 Atmospheric Sciences, Organic aerosols, Particulate matter (PM)
Abstract: Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected "true"values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here, especially in periods between seasons. The results of this multi-site comparison coincide with the synthetic dataset in terms of rolling-seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the results of this study provide solid evidence of the robustness of both methods and of the overall efficiency of the recently proposed rolling PMF approach., Acknowledgements IDAEA-CSIC is a Centre of Excellence Severo Ochoa (Spanish Ministry of Science and Innovation, Project CEX2018-000794-S). The authors gratefully acknowledge the Romanian National Air Quality Monitoring Network (NAQMN, https://www.calitateaer.ro/public/home-page/?__locale=ro, last access: September 2022) for providing NOx data. Financial support This research has been supported by the Generalitat de Catalunya (grant no. AGAUR 2017 SGR41), the European Cooperation in Science and Technology (grant no. COST Action CA16109 COLOSSAL), the Ministerio de Ciencia, Innovación y Universidades (CAIAC, grant no. PID2019-108990RB-I00 and FEDER, grant no. EQC2018-004598-P.), the Horizon 2020, the Ministry of Education and Research, Romania (grant nos. PN-III-P1-1.1-TE-2019-0340 and 18PFE/30.12.2021, 18N/2019), the Agence Nationale de la Recherche (grant no. PIA, ANR-11_LABX-0005-01), the Conseil Régional Hauts-de-France (CLIMIBIO grant), the Ministère de l'Enseignement Supérieur et de la Recherche (CARA grant), the Environmental Protection Agency (AEROSOURCE, grant no. 2016-CCRP-MS-31), the Department of the Environment, Climate and Communications (AC3 network grant), and the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SAMSAM, grant nos. IZCOZ9_177063 and PZPGP2_201992). We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).
Published: 2022

15. Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

Author: André S. H. Prévôt, Jean-Eudes Petit, Stefania Gilardoni, Giulia Stefenelli, Nicolas Marchand, Francesco Canonaco, Sebnem Aksoyoglu, Jianhui Jiang, Imad El Haddad, Urs Baltensperger, Olivier Favez, Amelie Bertrand, 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), Institut National de l'Environnement Industriel et des Risques (INERIS), Institute of Polar Sciences [Venezia-Mestre] (CNR-ISP), Consiglio Nazionale delle Ricerche [Roma] (CNR), Aix Marseille Université (AMU)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), and National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)
Subjects: Box model, 010504 meteorology & atmospheric sciences, Chemical speciation, lcsh:QE1-996.5, Enthalpy of vaporization, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, CAMX, Aerosol, lcsh:Geology, 13. Climate action, [SDE]Environmental Sciences, Environmental science, Biomass burning, Volatility (chemistry), Air quality index, 0105 earth and related environmental sciences
Abstract: Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from −72.9 % (VBS_BASE) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage.
Published: 2021

16. Automatic Privacy and Utility Preservation for Mobility Data: A Nonlinear Model-Based Approach

Author: Nicolas Marchand, Antoine Boutet, Sophie Cerf, Sonia Ben Mokhtar, Vincent Primault, Lydia Y. Chen, Sara Bouchenak, 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), Privacy Models, Architectures and Tools for the Information Society (PRIVATICS), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-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), IBM Research [Zurich], 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), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Inria Lyon, and Institut National de Recherche en Informatique et en Automatique (Inria)
Subjects: Information privacy, D48b Modeling and prediction, Computer science, Distributed computing, media_common.quotation_subject, Usability, 0211 other engineering and technologies, Index Terms-D46 Security and Privacy Protection, 02 engineering and technology, Configuration control, J9a Location-dependent and sensitive, D216b Configu- ration control, Adaptability, Data modeling, [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY], Robustness (computer science), [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Privacy protection, Electrical and Electronic Engineering, media_common, Measurement, 021110 strategic, defence & security studies, business.industry, H20a Security, Adaptation models, Computational modeling, and protec- tion, Security, integrity, business, Data privacy, Personally identifiable information, Mobile device, Protection mechanism
Abstract: International audience; The widespread use of mobile devices and location-based services has generated a large number of mobility databases. While processing these data is highly valuable, privacy issues can occur if personal information is revealed. The prior art has investigated ways to protect mobility data by providing a wide range of Location Privacy Protection Mechanisms (LPPMs). However, the privacy level of the protected data significantly varies depending on the protection mechanism used, its configuration and on the characteristics of the mobility data. Meanwhile, the protected data still needs to enable some useful processing. To tackle these issues, we present PULP, a framework that finds the suitable protection mechanism and automatically configures it for each user in order to achieve user-defined objectives in terms of both privacy and utility. PULP uses nonlinear models to capture the impact of each LPPM on data privacy and utility levels. Evaluation of our framework is carried out with two protectionmechanisms from the literature and four real-world mobility datasets. Results show the efficiency of PULP, its robustness and adaptability. Comparisons between LPPMs’ configurators and the state of the art further illustrate that PULP better realizes users’ objectives, and its computation time is in orders of magnitude faster.
Published: 2021

17. Phenomenology of Ultrafine Particle Concentrations and Size Distribution Across Urban Europe

Author: Pedro Trechera, Meritxell Garcia-Marlès, Xiansheng Liu, Cristina Reche, Noemí Pérez, Marjan Savadkoohi, David Beddows, Imre Salma, Máté Vörösmarty, Andrea Casans, Juan Andrés Casquero-Vera, Christoph Hueglin, Nicolas Marchand, Benjamin Chazeau, Grégory Gille, Panayiotis Kalkavouras, Nikos Mihalopoulos, Jakub Ondracek, Nadia Zikova, Jarkko V. Niemi, Hanna E. Manninen, David C. Green, Anja H. Tremper, Michael Norman, Stergios Vratolis, Konstantinos Eleftheriadis, Francisco J. Gómez-Moreno, Elisabeth Alonso-Blanco, Holger Gerwig, Alfred Wiedensohler, Kay Weinhold, Maik Merkel, Susanne Bastian, Jean-Eudes Petit, Olivier Favez, Suzanne Crumeyrolle, Nicolas Ferlay, Sebastiao Martins Dos Santos, Jean-Philippe Putaud, Hilkka Timonen, Janne Lampilahti, Christof Asbach, Carmen Wolf, Heinz Kaminski, Hicran Altug, Barbara Hoffmann, David Q. Rich, Marco Pandolfi, Roy M. Harrison, Philip K. Hopke, Tuukka Petäjä, Andrés Alastuey, Xavier Querol, 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), and Institut National de l'Environnement Industriel et des Risques (INERIS)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Aerosols, History, Polymers and Plastics, Air quality, Atmospheric particulate matter, Nanoparticles, Urban environment, Business and International Management, Particle number concentrations, Industrial and Manufacturing Engineering, General Environmental Science
Abstract: This study is supported by the RI-URBANS project (Research Infrastructures Services Reinforcing Air Quality Monitoring Capacities in European Urban & Industrial Areas, European Union’s Horizon 2020 research and innovation programme, Green Deal, European Commission, under grant agreement No 101036245). The authors would like to thank ACTRIS (The Aerosol, Clouds and Trace Gases Research Infrastructure), especially the EBAS Data Centre, for providing datasets for the study. The authors would like to thank also the support from “Agencia Estatal de Investigación” from the Spanish Ministry of Science and Innovation, and FEDER funds under the projects CAIAC (PID2019-108990RB-I00); and the Generalitat de Catalunya (AGAUR 2021 SGR00447) and the Direcció General de Territori. This study is partly funded by the National Institute for Health Research (NIHR) Health Protection Research Unit in Environmental Exposures and Health, a partnership between UK Health Security Agency (UKHSA) and Imperial College London. The views expressed are those of the author(s) and not necessarily those of the NIHR, UKHSA, or the Department of Health and Social Care. The work in Rochester, NY was funded by the New York State Energy Research and Development Authority under contracts #59802 and 125993. This research is also partly supported by the Hungarian Research, Development and Innovation Office (grant no. K132254). We thank the Hessian Agency for Nature Conservation, Environment and Geology (HLNUG), Wiesbaden, Germany for providing concentrations of ancillary pollutants of urban background station at Darmstadt. The Stockholm traffic station (Hornsgatan) datasets were provided thanks to the nPETS project (grant agreement no. 954377) funded by the European Union (EU)., Supplementary data to this article can be found online at https://doi.org/10.1016/j.envint.2023.107744, The 2017–2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of, RI-URBANS project, ACTRIS, EBAS Data Centre, “Agencia Estatal de Investigación" Spanish Ministry of Science and Innovation, FEDER projects CAIAC (PID2019-108990RB-I00), Generalitat de Catalunya (AGAUR 2021 SGR00447) and the Direcció General de Territori, National Institute for Health Research (NIHR) Health Protection Research Unit in Environmental Exposures and Health, New York State Energy Research and Development Authority, Hungarian Research, Development and Innovation Office, CGIAR European Commission 954377
Published: 2022

18. A Cybersecurity Risk Framework for Unmanned Aircraft Systems under Specific Category

Author: Trung Duc Tran, Jean-Marc Thiriet, Nicolas Marchand, Amin El Mrabti, 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), SOGILIS company [Grenoble], GIPSA - COntrol, PErception, Robots, navigation and Intelligent Computing (GIPSA-COPERNIC), GIPSA Pôle Sciences des Données (GIPSA-PSD), and ANR-21-ESRE-0015,TIRREX,Technological Infrastructure of Robotics Research of EXcellence(2021)
Subjects: 021110 strategic, defence & security studies, Cybersecurity, Mechanical Engineering, 0211 other engineering and technologies, 020206 networking & telecommunications, 02 engineering and technology, SORA, Industrial and Manufacturing Engineering, [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], Artificial Intelligence, Control and Systems Engineering, Privacy, Specific Operation, 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], UAS, Electrical and Electronic Engineering, Software, Risk assessment
Abstract: International audience; Nowadays, safety and cybersecurity are some of the most important issues involving the development of Unmanned Aircraft System (UAS) operations. For safety, the lawmakers and aviation authorities have a lot of efforts to establish an adequate safety level for UAS operations within the current airspace system. One of them is the Specific Operation Risk Assessment (SORA) methodology developed by Joint Authorities for Rulemaking on Unmanned Aircraft System (JARUS). This methodology provides a guide to conduct risk assessments for UAS operations under the Specific Category. However, the methodology supports only some problems related to safety. In this paper, we introduce our approach to extend the SORA methodology toward cybersecurity. We illustrate this approach by extending the methodology to cover the privacy problem-an aspect related to cybersecurity. Besides that, we also introduce our supporting tool in the form of a web application that helps users conduct automatic risk assessments.
Published: 2022

19. Smooth Visual-Coverage Path Planning for Escort Missions using UAVs

Author: Ahmad Hably, Kaouther Moussa, Nicolas Marchand, Hilton Tnunay, Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 (LAMIH), Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-INSA Institut National des Sciences Appliquées Hauts-de-France (INSA Hauts-De-France), 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), and Université Grenoble Alpes (UGA)
Subjects: Optimization, Polynomial, Optimization problem, Computer simulation, Optimization algorithm, Computer science, Escort missions, Real-time computing, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, ComputerApplications_COMPUTERSINOTHERSYSTEMS, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Computer Science::Multiagent Systems, Computer Science::Robotics, Image resolution, Computer Science::Systems and Control, Virtual leader, Surface coverage, Trajectory, Motion planning, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Path planning
Abstract: International audience; This paper investigates the trajectory generation problem for a fleet of Unmanned Aerial Vehicles (UAVs) performing escort missions with respect to a convoy with a timevarying velocity. Using camera-equipped UAVs, we propose a framework allowing to adapt the UAVs altitudes to achieve a trade-off between the size of the covered surface and the image resolution by solving an optimization problem. Furthermore, we perform polynomial refinement based on the generated planar way-points to yield a minimum-jerk time-parameterized trajectory with dynamical constraints on the virtual leader to follow. The numerical simulations presented in this paper show the effectiveness of the optimization algorithm in adapting the UAVs altitudes to satisfy a compromise between the size of the covered area and its corresponding image resolution.
Published: 2021

20. Virtual Leader based Trajectory Generation of UAV Formation for Visual Area Coverage

Author: Kaouther Moussa, Ahmad Hably, Nicolas Marchand, Hilton Tnunay, 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), Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 (LAMIH), and Centre National de la Recherche Scientifique (CNRS)-Université Polytechnique Hauts-de-France (UPHF)-INSA Institut National des Sciences Appliquées Hauts-de-France (INSA Hauts-De-France)
Subjects: Quadcopter, Virtual-leader Formation, Image quality, Computer science, Real-time computing, computer.file_format, Visual Coverage Path Planning, Network topology, Visualization, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Set (abstract data type), [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Trajectory, Motion planning, Executable, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Trajectory Generation, computer
Abstract: International audience; This paper proposes a trajectory generation strategy of quadcopter formation for area surveillance and inspection using multiple cameras. The proposed technique exploits a minimal virtual-leader based network topology to generate the executable trajectories where generating trajectories for each agent is no longer necessary. A coverage path planning algorithm is employed to generate a set of planar waypoints, which are then optimised to yield a minimum-jerk time-parametrised trajectory with dynamical constraints of the virtual leader to follow. In order to establish a formation pattern, the desired distance among the agents is then computed based on the operation mode, size of the area to cover, and the number of deployed UAVs. Numerical simulations demonstrate the effectiveness of the proposed method.
Published: 2021

21. 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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22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. Supplementary material to '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, and Jean-François Doussin
Published: 2020

29. Supplementary material to '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: Benjamin Chazeau, Brice Temime-Roussel, Grégory Gille, Boualem Mesbah, Barbara D'Anna, Henri Wortham, and Nicolas Marchand
Published: 2020

30. 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

31. Supplementary material to 'Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50'

Author: Jianhui Jiang, Imad El-Haddad, Sebnem Aksoyoglu, Giulia Stefenelli, Amelie Bertrand, Nicolas Marchand, Francesco Canonaco, Jean-Eudes Petit, Olivier Favez, Stefania Gilardoni, Urs Baltensperger, and André S. H. Prévôt
Published: 2020

32. 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

33. Supplementary material to 'Molecular Insights into New Particle Formation in Barcelona, Spain'

Author: James Brean, David C. S. Beddows, Zongbo Shi, Brice Temime-Roussel, Nicolas Marchand, Xavier Querol, Andrés Alastuey, María Cruz Minguillon, and Roy M. Harrison
Published: 2020

34. 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

35. 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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36. 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

37. 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

38. 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

39. 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

40. 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

41. 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

42. 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

43. Supplementary material to 'Secondary organic aerosol formation from smoldering and flaming combustion of biomass: a box model parametrization based on volatility basis set'

Author: Giulia Stefenelli, Jianhui Jiang, Amelie Bertrand, Emily A. Bruns, Simone M. Pieber, Urs Baltensperger, Nicolas Marchand, Sebnem Aksoyoglu, André S. H. Prévôt, Jay G. Slowik, and Imad El Haddad
Published: 2019

44. 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

45. 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

46. 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

47. 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

48. 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

49. 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

50. 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

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