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1. Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate

Author

Leonardo Geronzi, Antonio Martinez, Michel Rochette, Kexin Yan, Aline Bel-Brunon, Pascal Haigron, Pierre Escrig, Jacques Tomasi, Morgan Daniel, Alain Lalande, Siyu Lin, Diana Marcela Marin-Castrillon, Olivier Bouchot, Jean Porterie, Pier Paolo Valentini, Marco Evangelos Biancolini, University of Rome Tor Vergata, Department of Enterprise Engineering Mario Lucertini, Università degli Studi di Roma Tor Vergata [Roma], ANSYS France, ANSYS, Laboratoire de Mécanique des Contacts et des Structures [Villeurbanne] (LaMCoS), 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), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Institut de Chimie Moléculaire de l'Université de Bourgogne [Dijon] (ICMUB), Université de Bourgogne (UB)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Horizon 2020 Framework Programme, H2020, H2020 Marie Skłodowska-Curie Actions, MSCA, (859836), and Horizon 2020

Subjects
Shape features, Ascending aortic aneurysm, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Health Informatics, Growth prediction, Regression, Computer Science Applications
Abstract

International audience; Objective: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to predict the ascending aortic aneurysm growth. Material and methods: 70 patients with aneurysm, for which two 3D acquisitions were available, are included. Following segmentation, three local shape features are computed: (1) the ratio between maximum diameter and length of the ascending aorta centerline, (2) the ratio between the length of external and internal lines on the ascending aorta and (3) the tortuosity of the ascending tract. By exploiting longitudinal data, the aneurysm growth rate is derived. Using radial basis function mesh morphing, iso-topological surface meshes are created. Statistical shape analysis is performed through unsupervised principal component analysis (PCA) and supervised partial least squares (PLS). Two types of global shape features are identified: three PCA-derived and three PLS-based shape modes. Three regression models are set for growth prediction: two based on gaussian support vector machine using local and PCA-derived global shape features; the third is a PLS linear regression model based on the related global shape features. The prediction results are assessed and the aortic shapes most prone to growth are identified. Results: the prediction root mean square error from leave-one-out cross-validation is: 0.112 mm/month, 0.083 mm/month and 0.066 mm/month for local, PCA-based and PLS-derived shape features, respectively. Aneurysms close to the root with a large initial diameter report faster growth. Conclusion: global shape features might provide an important contribution for predicting the aneurysm growth.

Published
2023
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2. Opposing effects of plant traits on diversification

Author

Bruce Anderson, John Pannell, Sylvain Billiard, Concetta Burgarella, Hugo de Boer, Mathilde Dufay, Andrew J. Helmstetter, Marcos Méndez, Sarah P. Otto, Denis Roze, Hervé Sauquet, Daniel Schoen, Jürg Schönenberger, Mario Vallejo-Marin, Rosana Zenil-Ferguson, Jos Käfer, Sylvain Glémin, Stellenbosch University, Université de Lausanne = University of Lausanne (UNIL), Évolution, Écologie et Paléontologie (Evo-Eco-Paleo) - UMR 8198 (Evo-Eco-Paléo (EEP)), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Uppsala University, Natural History Museum [Oslo], University of Oslo (UiO), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Centre de Synthèse et d’Analyse sur la Biodiversité (CESAB), Fondation pour la recherche sur la Biodiversité (FRB), Universidad Rey Juan Carlos [Madrid] (URJC), University of British Columbia [Vancouver], Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of New South Wales [Sydney] (UNSW), McGill University = Université McGill [Montréal, Canada], University of Vienna [Vienna], University of Kentucky (UK), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Horizon 2020 Framework Programme, H2020, H2020 Marie Skłodowska-Curie Actions, MSCA: 839643, and Horizon 2020

Subjects
Plant biology, Biological sciences, Evolutionary theories, Multidisciplinary, Plant population biology, Perspective, Evolutionary biology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

International audience; Species diversity can vary dramatically across lineages due to differences in speciation and extinction rates. Here, we explore the effects of several plant traits on diversification, finding that most traits have opposing effects on diversification. For example, outcrossing may increase the efficacy of selection and adaptation but also decrease mate availability, two processes with contrasting effects on lineage persistence. Such opposing trait effects can manifest as differences in diversification rates that depend on ecological context, spatiotemporal scale, and associations with other traits. The complexity of pathways linking traits to diversification suggests that the mechanistic underpinnings behind their correlations may be difficult to interpret with any certainty, and context dependence means that the effects of specific traits on diversification are likely to differ across multiple lineages and timescales. This calls for taxonomically and context-controlled approaches to studies that correlate traits and diversification. © 2023

Published
2023
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3. Exploring ultracold collisions in $^6$Li-$^{53}$Cr Fermi mixtures: Feshbach resonances and scattering properties of a novel alkali-transition metal system

Author

Ciamei, A., Finelli, S., Trenkwalder, A., Inguscio, M., Simoni, A., Zaccanti, M., Università degli Studi di Firenze = University of Florence (UniFI), Università Campus Bio-Medico di Roma / University Campus Bio-Medico of Rome ( UCBM), Institut de Physique de Rennes (IPR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), H2020 Marie Skłodowska-Curie Actions, MSCA: 894442, European Research Council, ERC: 637738, Ministero dell’Istruzione, dell’Università e della Ricerca, MIUR, Horizon 2020, and Foundation for Alcohol Research and Education, FARE

Subjects
Seismic waves, Fermionic atoms, Atomic Physics (physics.atom-ph), Scattering property, FOS: Physical sciences, S-waves, Property predictions, Resonance, Physics - Atomic Physics, Cold and ultra-cold collisions, Ultracold collisions, Physics::Atomic Physics, Quantum dynamics, Transition metal system, [PHYS]Physics [physics], Condensed Matter::Quantum Gases, Coupled-channel models, Chromium alloys, Lithium alloys, Transition metals, Binary alloys, Yield prediction, Quantum Gases (cond-mat.quant-gas), Mixtures, Atomic and molecular collisions, P waves, Condensed Matter - Quantum Gases, Molecular physics, Feshbach resonances
Abstract

We investigate ultracold collisions in a novel mixture of $^6$Li and $^{53}$Cr fermionic atoms, discovering more than 50 interspecies Feshbach resonances via loss spectroscopy. Building a full coupled-channel model, we unambiguously characterize the $^{6}$Li-$^{53}$Cr scattering properties and yield predictions for other isotopic pairs. In particular, we identify various Feshbach resonances that enable the controlled tuning of elastic $s$- and $p$-wave $^{6}$Li-$^{53}$Cr interactions. Our studies thus make lithium-chromium mixtures emerge as optimally-suited platforms for the experimental search of elusive few- and many-body regimes of highly-correlated fermionic matter, and for the realization of a new class of ultracold polar molecules possessing both electric and magnetic dipole moments., Comment: 12 pages, 4 figures, 4 tables

Published
2022
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4. Nanoscale 3D quantitative imaging of 1.88 Ga Gunflint microfossils reveals novel insights into taphonomic and biogenic characters

Author

Manuel Guizar-Sicairos, Felisa Berenguer, Loïc Bertrand, Plinio Jaqueto, Pierre Gueriau, Keyron Hickman-Lewis, Frances Westall, Ricardo I.F. Trindade, Douglas Galante, André L. Rossi, Mariana Verezhak, Lara Maldanis, Laboratório Nacional de Luz Sìncrotron (LNLS), Centro Nacional de Pesquisa em Energia e Materiais = Brazilian Center for Research in Energy and Materials (CNPEM), Instituto de Física de São Carlos (IFSC-USP), Universidade de São Paulo = University of São Paulo (USP), Centre de biophysique moléculaire (CBM), Université d'Orléans (UO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Paul Scherrer Institute (PSI), Institut photonique d'analyse non-destructive européen des matériaux anciens (IPANEMA), Muséum national d'Histoire naturelle (MNHN)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Ministère de la Culture (MC), Institute of Earth Sciences [Lausanne], Université de Lausanne = University of Lausanne (UNIL), Centro Brasileiro de Pesquisas Físicas (CBPF), Ministério da Ciência e Tecnologia, Synchrotron SOLEIL (SSOLEIL), Centre National de la Recherche Scientifique (CNRS), Photophysique et Photochimie Supramoléculaires et Macromoléculaires (PPSM), Institut de Chimie du CNRS (INC)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay), Conselho Nacional de Desenvolvimento Cienti­fico e Tecnologico, CNPq: 301263/2017–5, 424367/2016–5 Fundaçao de Amparo à Pesquisa do Estado de Sao Paulo, FAPESP H2020 Marie Skłodowska-Curie Actions, MSCA: 701647 Fundaçao de Amparo à Pesquisa do Estado de Sao Paulo, FAPESP: 2015/21810–6, 2016/25681–9 European Commission, EC: 654028 Coordenaçao de Aperfeiçoamento de Pessoal de Nível Superior, CAPES Instituto Serrapilheira: Serra-1709–20205 Centre National d'Etudes Spatiales, CNES Coordenaçao de Aperfeiçoamento de Pessoal de Nível Superior, CAPES Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNSF: 200021L_169753 Conselho Nacional de Desenvolvimento Cienti­fico e Tecnologico, CNPq 607297 Centre National de la Recherche Scientifique, CNRS, We acknowledge the Paul Scherrer Institut, Villigen, Switzerland for provision of synchrotron radiation beamtime at cSAXS beamline of the Swiss Light Source (SLS), Joakim Reuteler (ScopeM) for the preparation of the samples using FIB, the Centro Brasileiro de Pesquisas Físicas (CBPF) for support in sample preparation and SEM analysis, and Sylvain Janiec (ISTO, Orléans) for preparing the thin sections. LM was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 and by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grants 2015/21810–6 and 2016/25681–9), which included being hosted at the IPANEMA laboratory. DG acknowledges FAPESP (2016/06114–6), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, 424367/2016–5 and 301263/2017–5). This work was supported by the Serrapilheira Institute (grant number Serra-1709–20205). KHL and FW acknowledge the support of the French National Centre for Scientific Research (CNRS), the French Space Agency (CNES) and the MASE (Mars Analogues for Space Exploration) Project (EU-FP7 Grant no. 607297). IPANEMA and the SOLEIL synchrotron are supported by the Research Infrastructures activity IPERION CH of the Horizon2020 program of the European Commission (Grant Agreement No. 654028). LB acknowledges support from Région Île-de-France / DIM Matériaux anciens et patrimoniaux. MV is supported by European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 701647, as well as SNSF grant No 200021L_169753. We also acknowledge the constructive comments of three anonymous reviewers., European Project: 654028,H2020 Pilier Excellent Science,H2020-INFRAIA-2014-2015,IPERION CH(2015), Centro Nacional de Pesquisa em Energia e Materiais (CNPEM), Universidade de São Paulo (USP), Université d'Orléans (UO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), HAL UVSQ, Équipe, and Integrated Platform for the European Research Infrastructure ON Cultural Heritage - IPERION CH - - H2020 Pilier Excellent Science2015-05-01 - 2019-04-30 - 654028 - VALID

Subjects
[CHIM.ANAL] Chemical Sciences/Analytical chemistry, Taphonomy, Science, Geochemistry, Context (language use), 02 engineering and technology, 010502 geochemistry & geophysics, 01 natural sciences, Article, Precambrian, chemistry.chemical_compound, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, synchrotron, ptychography, Kerogen, 0105 earth and related environmental sciences, fossil, Multidisciplinary, Proterozoic, Physics, Biota, Biogeochemistry, 15. Life on land, Hematite, 021001 nanoscience & nanotechnology, [PHYS.COND.CM-MS] Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], ESPECTROSCOPIA, Diagenesis, chemistry, visual_art, [PHYS.COND.CM-MS]Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], visual_art.visual_art_medium, Medicine, [SDU.STU.PG] Sciences of the Universe [physics]/Earth Sciences/Paleontology, [SDU.STU.PG]Sciences of the Universe [physics]/Earth Sciences/Paleontology, 0210 nano-technology, paleontology, diagenesis, Geology
Abstract

Precambrian cellular remains frequently have simple morphologies, micrometric dimensions and are poorly preserved, imposing severe analytical and interpretational challenges, especially for irrefutable attestations of biogenicity. The 1.88 Ga Gunflint biota is a Precambrian microfossil assemblage with different types and qualities of preservation across its numerous geological localities and provides important insights into the Proterozoic biosphere and taphonomic processes. Here we use synchrotron-based ptychographic X-ray computed tomography to investigate well-preserved carbonaceous microfossils from the Schreiber Beach locality as well as poorly-preserved, iron-replaced fossil filaments from the Mink Mountain locality, Gunflint Formation. 3D nanoscale imaging with contrast based on electron density allowed us to assess the morphology and carbonaceous composition of different specimens and identify the minerals associated with their preservation based on retrieved mass densities. In the Mink Mountain filaments, the identification of mature kerogen and maghemite rather than the ubiquitously described hematite indicates an influence from biogenic organics on the local maturation of iron oxides through diagenesis. This non-destructive 3D approach to microfossil composition at the nanoscale within their geological context represents a powerful approach to assess the taphonomy and biogenicity of challenging or poorly preserved traces of early microbial life, and may be applied effectively to extraterrestrial samples returned from upcoming space missions.

Published
2020
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5. Signature of consciousness in brain-wide synchronization patterns of monkey and human fMRI signals

Author

Dante Mantini, Helmut Laufs, Enzo Tagliazucchi, Lynn Uhrig, Morten L. Kringelbach, Béchir Jarraya, Gerald Hahn, Gorka Zamora-López, Gustavo Deco, Université de Versailles Saint-Quentin-en-Yvelines - UFR Sciences de la santé Simone Veil (UVSQ Santé), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), 661583, 720270, 785907, 945539 H2020 Marie Skłodowska-Curie Actions, MSCA Ministerio de Ciencia, Innovación y Universidades, MCIU European Research Council, ERC: 615539 Deutsche Forschungsgemeinschaft, DFG: KN 588/7 – 1 Danmarks Grundforskningsfond, DNRF: DNRF117 Bundesministerium für Bildung und Forschung, BMBF: 01 EV 0703 Agència de Gestió d'Ajuts Universitaris i de Recerca, AGAUR: 2017 SGR 1545, G.D. was supported by the Spanish Research Project AWAKENING: using whole-brain models perturbational approaches for predicting external stimulation to force transitions between different brain states, ref. PID2019-105772GB-I00 /AEI/10.13039/501100011033, financed by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI), and by the Catalan AGAUR program 2017 SGR 1545. G.D., G.H. and G.Z. received support from the European Union's Horizon 2020 research and innovation program under Grant Agreement No. 720270 (Human Brain Project SGA1), No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3). G.H. was funded by the grant CONSCBRAIN (n. 661583) of the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie action. G.D. and G.H. received funding from the German Research Council (DFG, No. KN 588/7 – 1) within the priority program Computational Connectomics (SPP 2041). E.T. and H.L. were supported by the Bundesministerium für Bildung und Forschung (grant number 01 EV 0703 ) and the LOEWE Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). M.L.K. is supported by the ERC Consolidator Grant: CAREGIVING (n. 615539 ), Center for Music in the Brain, funded by the Danish National Research Foundation ( DNRF117 ), and centre for Eudaimonia and Human Flourishing funded by the Pettit and Carlsberg Foundations., European Project: 0720270(2007), European Project: 785907,H2020,HBP SGA2(2018), European Project: 945539,HBP SGA3(2020), and European Project: 945539,H2020,H2020-SGA-FETFLAG-HBP-2019,HBP SGA3(2020)

Subjects
DYNAMICS, Computer science, [SDV]Life Sciences [q-bio], Unconsciousness, MACAQUE, INFORMATION CAPACITY, 0302 clinical medicine, CONNECTIVITY, Consciousness states, Cortical Synchronization, media_common, Brain Mapping, NEURONAL AVALANCHES, Functional connectivity, 05 social sciences, Radiology, Nuclear Medicine & Medical Imaging, Brain, Haplorhini, FLUCTUATIONS, Magnetic Resonance Imaging, NETWORKS, Neurology, symbols, medicine.symptom, Life Sciences & Biomedicine, Vigilance (psychology), GLOBAL SIGNAL, Consciousness, Cognitive Neuroscience, media_common.quotation_subject, Models, Neurological, Neuroimaging, 050105 experimental psychology, lcsh:RC321-571, 03 medical and health sciences, symbols.namesake, CEREBRAL-CORTEX, medicine, Animals, Humans, 0501 psychology and cognitive sciences, Computer Simulation, ddc:610, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Hopf bifurcation, Science & Technology, Resting state fMRI, Neurosciences, Neurophysiology, SLEEP, Neurosciences & Neurology, Sleep, Neuroscience, 030217 neurology & neurosurgery
Abstract

During the sleep-wake cycle, the brain undergoes profound dynamical changes, which manifest subjectively as transitions between conscious experience and unconsciousness. Yet, neurophysiological signatures that can objectively distinguish different consciousness states based are scarce. Here, we show that differences in the level of brain-wide signals can reliably distinguish different stages of sleep and anesthesia from the awake state in human and monkey fMRI resting state data. Moreover, a whole-brain computational model can faithfully reproduce changes in global synchronization and other metrics such as functional connectivity, structure-function relationship, integration and segregation across vigilance states. We demonstrate that the awake brain is close to a Hopf bifurcation, which naturally coincides with the emergence of globally correlated fMRI signals. Furthermore, simulating lesions of individual brain areas highlights the importance of connectivity hubs in the posterior brain and subcortical nuclei for maintaining the model in the awake state, as predicted by graph-theoretical analyses of structural data. G.D. was supported by the Spanish Research Project AWAKENING: using whole-brain models perturbational approaches for predicting external stimulation to force transitions between different brain states, ref. PID2019-105772GB-I00 /AEI/10.13039/501100011033, financed by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI), and by the Catalan AGAUR program 2017 SGR 1545. G.D., G.H. and G.Z. received support from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 720270 (Human Brain Project SGA1), No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3). G.H. was funded by the grant CONSCBRAIN (n. 661583) of the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie action. G.D. and G.H. received funding from the German Research Council (DFG, No. KN 588/7 – 1) within the priority program Computational Connectomics (SPP 2041). E.T. and H.L. were supported by the Bundesministerium für Bildung und Forschung (grant number 01 EV 0703) and the LOEWE Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). M.L.K. is supported by the ERC Consolidator Grant: CAREGIVING (n. 615539), Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117), and centre for Eudaimonia and Human Flourishing funded by the Pettit and Carlsberg Foundations.

Published
2020
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6. The Red Sea Deep Water is a potent source of atmospheric ethane and propane

Author

Ivan Tadic, Sergey Osipov, Horst Fischer, Jean-Daniel Paris, Tobias Könemann, Achim Edtbauer, Eva Y. Pfannerstill, Jonathan Williams, T. Sattler, Nijing Wang, David Walter, Andrea Pozzer, Christof Stönner, Lisa Ernle, Jos Lelieveld, V.N. Matthaios, Efstratios Bourtsoukidis, Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, School of Geography, Earth and Environmental Sciences [Birmingham], University of Birmingham [Birmingham], Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-RAMCES (ICOS-RAMCES), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Max Planck Institute for Biogeochemistry (MPI-BGC), The Cyprus Institute, Energy, Environment and Water Research Center, H2020 Marie Skłodowska-Curie Actions, MSCA: 674911 King Abdullah University of Science and Technology, KAUST Kuwait Institute for Scientific Research, KISR Horizon 2020 Framework Programme, H2020: 856612, We acknowledge the fruitful collaborations with the Cyprus Institute (CyI), the King Abdullah University of Science and Technology (KAUST), and the Kuwait Institute for Scientific Research (KISR). We are grateful to Hays Ships Ltd, the ship’s captain Pavel Kirzner, and the ship crew for providing the best possible working conditions onboard Kommandor Iona. We thank all the participants of the AQABA ship campaign and in particular Hartwig Harder for the fruitful discussions and day-to-day organization of the campaign, and Marcel Dorf, Claus Koeppel, Thomas Klüpfel, and Rolf Hofmann for logistics organization and assistance during the setup phase. Uwe Parchatka is acknowledged for his contribution to the NOx data set. Marc Delmotte, Laurence Vialettes, and Olivier Laurent are acknowledged for helping with setting up the methane measurements. NW acknowledges funding by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 674911. We acknowledge the EMME-CARE project from the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement No. 856612), as well as matching co-funding by the Government of the Republic of Cyprus., European Project: 674911,H2020,H2020-MSCA-ITN-2015,IMPACT(2016), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

Subjects
Atmospheric chemistry, 010504 meteorology & atmospheric sciences, Atmospheric circulation, Science, [SDV]Life Sciences [q-bio], General Physics and Astronomy, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, Article, Environmental impact, chemistry.chemical_compound, Propane, Hotspot (geology), 14. Life underwater, Tropospheric ozone, Underwater, lcsh:Science, 0105 earth and related environmental sciences, chemistry.chemical_classification, Pollutant, Multidisciplinary, Environmental monitoring, General Chemistry, 6. Clean water, Hydrocarbon, chemistry, Marine chemistry, 13. Climate action, lcsh:Q
Abstract

Non-methane hydrocarbons (NMHCs) such as ethane and propane are significant atmospheric pollutants and precursors of tropospheric ozone, while the Middle East is a global emission hotspot due to extensive oil and gas production. Here we compare in situ hydrocarbon measurements, performed around the Arabian Peninsula, with global model simulations that include current emission inventories (EDGAR) and state-of-the-art atmospheric circulation and chemistry mechanisms (EMAC model). While measurements of high mixing ratios over the Arabian Gulf are adequately simulated, strong underprediction by the model was found over the northern Red Sea. By examining the individual sources in the model and by utilizing air mass back-trajectory investigations and Positive Matrix Factorization (PMF) analysis, we deduce that Red Sea Deep Water (RSDW) is an unexpected, potent source of atmospheric NMHCs. This overlooked underwater source is comparable with total anthropogenic emissions from entire Middle Eastern countries, and significantly impacts the regional atmospheric chemistry., The Middle East is known to emit large amounts of non-methane hydrocarbon pollutants to the atmosphere, but the sources are poorly characterized. Here the authors discover a new source—deep water in the Red Sea—and calculate that its emissions exceed rates of several high gas-production countries.

Published
2020
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