GeoQAIR : Quantification de l'apport d'une plateforme d'observations Géostationnaires pour la surveillance de la Qualité de l'AIR en Europe

Monitoring of air quality (AQ) and its transport at the continental scale, as well as the development of efficient forecast systems for air quality is one of the issues included in the GMES (Global Monitoring for Environment and Security) European Programme for the establishment of a European capacity for Earth Observation. The availability of satellite instruments which have the ability to monitor tropospheric ozone in the lowermost troposphere would be a step forward for this system. To monitor small scale and short term processes as involved in pollution event development, a geostationary Earth orbit (GEO) observing system is particularly well adapted. Future GEO missions dedicated to air quality monitoring using thermal infrared (TIR) instruments are planned to be operating over the USA, Japan and Korea, while existing and planned missions over Europe are not well adapted for this task. One of the objectives of the GeoQAIR project is to evaluate different satellite instrument concepts for their ability to monitor AQ and in particular quantify the possible impact for AQ forecasting. Four instruments have been considered for this study: the existing instrument IASI on MetOp-A (Low Earth Orbit - LEO - mission), the planned IASI-NG on the EPS-SG platform (LEO mission) and IRS on Sentinel4/MTG platform (GEO mission mainly dedicated to meteorology) and a new GEO mission concept, MAGEAQ, dedicated to AQ monitoring and proposed at the last Earth Explorer 8 call of ESA. Pseudo-observations for the four instruments have been generated to simulate one month of ozone observations over Europe. About 45 millions of individual measurements have been simulated using the EGI facilities. A first analysis of the performances of the different instruments to measure ozone in the lowermost troposphere demonstrates that the short time and space scale processes implied in air pollution development will not be correctly apprehended with the current existing and planned missions. Dedicated instrument with sufficient spectral resolution and signal to noise ratio, as proposed within the MAGEAQ mission concept, are necessary to correctly represent these processes

Tropospheric ozone column retrieval from OMI data by means of neural networks: a validation exercise with ozone soundings over Europe

n/

Identification of Drug Interaction Adverse Events in Patients With COVID-19: A Systematic Review

IMPORTANCE During the COVID-19 pandemic, urgent clinical management of patients has mainly included drugs currently administered for other diseases, referred to as repositioned drugs. As a result, some of these drugs have proved to be not only ineffective but also harmful because of adverse events associated with drug-drug interactions (DDIs).OBJECTIVE To identify DDIs that led to adverse clinical outcomes and/or adverse drug reactions in patients with COVID-19 by systematically reviewing the literature and assessing the value of drug interaction checkers in identifying such events.EVIDENCE REVIEW After identification of the drugs used during the COVID-19 pandemic, the drug interaction checkers Drugs.com, COVID-19 Drug Interactions, LexiComp, Medscape, and WebMD were consulted to analyze theoretical DDI-associated adverse events in patients with COVID-19 from March 1, 2020, through February 28, 2022. A systematic literature review was performed by searching the databases PubMed, Scopus, and Cochrane for articles published from March 1, 2020, through February 28, 2022, to retrieve articles describing actual adverse events associated with DDIs. The drug interaction checkers were consulted again to evaluate their potential to assess such events.FINDINGS The DDIs identified in the reviewed articles involved 46 different drugs. In total, 575 DDIs for 58 drug pairs (305 associated with at least 1 adverse drug reaction) were reported. The drugs most involved in DDIs were lopinavir and ritonavir. Of the 6917 identified studies, 20 met the inclusion criteria. These studies, which enrolled 1297 patients overall, reported 115 DDI-related adverse events: 15 (26%) were identifiable by all tools analyzed, 29 (50%) were identifiable by at least 1 of them, and 14 (24%) remained nonidentifiable.CONCLUSIONS AND RELEVANCE The main finding of this systematic review is that the use of drug interaction checkers could have identified several DDI-associated adverse drug reactions, including severe and life-threatening events. Both the interactions between the drugs used to treat COVID-19 and between the COVID-19 drugs and those already used by the patients should be evaluated

Towards IASI-New Generation (IASI-NG): impact of improved spectral resolution and radiometric noise on the retrieval of thermodynamic, chemistry and climate variables

Besides their strong contribution to weather forecast improvement through data assimilation, thermal infrared sounders onboard polar-orbiting platforms are now playing a key role for monitoring atmospheric composition changes. The Infrared Atmospheric Sounding Interferometer (IASI) instrument developed by the French space agency (CNES) and launched by Eumetsat onboard the Metop satellite series is providing essential inputs for weather forecasting and pollution/climate monitoring owing to its smart combination of large horizontal swath, good spectral resolution and high radiometric performance. EUMETSAT is currently preparing the next polar-orbiting program (EPS-SG) with the Metop-SG satellite series that should be launched around 2020. In this framework, CNES is studying the concept of a new instrument, the IASI-New Generation (IASI-NG), characterized by an improvement of both spectral and radiometric characteristics as compared to IASI, with three objectives: (i) continuity of the IASI/Metop series; (ii) improvement of vertical resolution; (iii) improvement of the accuracy and detection threshold for atmospheric and surface components. In this paper, we show that an improvement of spectral resolution and radiometric noise fulfill these objectives by leading to (i) a better vertical coverage in the lower part of the troposphere, thanks to the increase in spectral resolution; (ii) an increase in the accuracy of the retrieval of several thermodynamic, climate and chemistry variables, thanks to the improved signal-to-noise ratio as well as less interferences between the signatures of the absorbing species in the measured radiances. The detection limit of several atmospheric species is also improved. We conclude that IASI-NG has the potential for strongly benefiting the numerical weather prediction, chemistry and climate communities now connected through the European GMES/Copernicus initiative

Towards IASI-New Generation (IASI-NG): impact of improved spectral resolution and radiometric noise on the retrieval of thermodynamic, chemistry and climate variables

Besides their strong contribution to weather forecast improvement through data assimilation, thermal infrared sounders onboard polar-orbiting platforms are now playing a key role for monitoring atmospheric composition changes. The Infrared Atmospheric Sounding Interferometer (IASI) instrument developed by the French space agency (CNES) and launched by Eumetsat onboard the Metop satellite series is providing essential inputs for weather forecasting and pollution/climate monitoring owing to its smart combination of large horizontal swath, good spectral resolution and high radiometric performance. EUMETSAT is currently preparing the next polar-orbiting program (EPS-SG) with the Metop-SG satellite series that should be launched around 2020. In this framework, CNES is studying the concept of a new instrument, the IASI-New Generation (IASI-NG), characterized by an improvement of both spectral and radiometric characteristics as compared to IASI, with three objectives: (i) continuity of the IASI/Metop series; (ii) improvement of vertical resolution; (iii) improvement of the accuracy and detection threshold for atmospheric and surface components. In this paper, we show that an improvement of spectral resolution and radiometric noise fulfill these objectives by leading to (i) a better vertical coverage in the lower part of the troposphere, thanks to the increase in spectral resolution; (ii) an increase in the accuracy of the retrieval of several thermodynamic, climate and chemistry variables, thanks to the improved signal-to-noise ratio as well as less interferences between the signatures of the absorbing species in the measured radiances. The detection limit of several atmospheric species is also improved. We conclude that IASI-NG has the potential for strongly benefiting the numerical weather prediction, chemistry and climate communities now connected through the European GMES/Copernicus initiative

Global perturbation of stratospheric water and aerosol burden by Hunga eruption

The eruption of the submarine Hunga volcano in January 2022 was associated with a powerful blast that injected volcanic material to altitudes up to 58 km. From a combination of various types of satellite and ground-based observations supported by transport modeling, we show evidence for an unprecedented increase in the global stratospheric water mass by 13% relative to climatological levels, and a 5-fold increase of stratospheric aerosol load, the highest in the last three decades. Owing to the extreme injection altitude, the volcanic plume circumnavigated the Earth in only 1 week and dispersed nearly pole-to-pole in three months. The unique nature and magnitude of the global stratospheric perturbation by the Hunga eruption ranks it among the most remarkable climatic events in the modern observation era, with a range of potential long-lasting repercussions for stratospheric composition and climate

Study of QGP signatures with the phi->K+K- signal in Pb-Pb ALICE events

The phi->K+K- decay channel in Pb-Pb collisions at LHC is studied through a full simulation of the ALICE detector. The study focuses on possible signatures in this channel of quark-gluon plasma (QGP) formation. On a basis of 10^6 collisions at high centrality some proposed QGP signatures are clearly visible both in K+K- invariant mass and transverse mass distributions. The high significance of this observation appears to reside heavily on the use of the TOF (Time Of Flight) system of ALICE in addition to its central tracking detectors.Comment: 9 pages, 7 figures, to appear in EPJ

Relationship between low Ankle-Brachial Index and rapid renal function decline in patients with atrial fibrillation: A prospective multicentre cohort study

OBJECTIVE: To investigate the relationship between Ankle-Brachial Index (ABI) and renal function progression in patients with atrial fibrillation (AF). DESIGN: Observational prospective multicentre cohort study. SETTING:Atherothrombosis Center of I Clinica Medica of 'Sapienza' University of Rome; Department of Medical and Surgical Sciences of University Magna Græcia of Catanzaro; Atrial Fibrillation Registry for Ankle-Brachial Index Prevalence Assessment-Collaborative Italian Study. PARTICIPANTS: 897 AF patients on treatment with vitamin K antagonists. MAIN OUTCOME MEASURES: The relationship between basal ABI and renal function progression, assessed by the estimated Glomerular Filtration Rate (eGFR) calculated with the CKD-EPI formula at baseline and after 2 years of follow-up. The rapid decline in eGFR, defined as a decline in eGFR >5 mL/min/1.73 m(2)/year, and incident eGFR<60 mL/min/1.73 m(2) were primary and secondary end points, respectively. RESULTS: Mean age was 71.8±9.0 years and 41.8% were women. Low ABI (ie, ≤0.90) was present in 194 (21.6%) patients. Baseline median eGFR was 72.7 mL/min/1.73 m(2), and 28.7% patients had an eGFR60 mL/min/1.73 m(2), 153 (23.9%) had a reduction of the eGFR <60 mL/min/1.73 m(2). ABI ≤0.90 was also an independent predictor for incident eGFR<60 mL/min/1.73 m(2) (HR 1.851, 95% CI 1.205 to 2.845, p=0.005). CONCLUSIONS: In patients with AF, an ABI ≤0.90 is independently associated with a rapid decline in renal function and incident eGFR<60 mL/min/1.73 m(2). ABI measurement may help identify patients with AF at risk of renal function deterioration

The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008

Neural networks algorithms for the estimation of atmospheric ozone from Envisat-SCIAMACHY and Aura-OMI measurements

Climate changes and atmospheric pollution are currently topical issues given their possible dramatic effects from the health, social and economical points of view. Assessing the causes and possible adaptation/mitigation strategies is a challenge in modern science. To understand and quantify the anthropic role in such changes is of a particular interest to depict future scenarios and to warn politicians about local and global intervention in emissions control. Ozone is one of the most important trace gases in the Earth's atmosphere. It is mainly present in the stratosphere, with only 10% in the troposphere. Despite its small amount, (2-7) 10ô 3 % in molar fraction, the solar radiation at wavelengths below 310 nm does not reach the Earth surface because of the large absorption cross sections characterizing ozone molecules at those wavelengths. Variations in the stratospheric ozone content may play a dramatic role in a possible increase of the surface UV radiation. The discovery of the Antarctic ozone hole, i.e. a considerable reduction of ozone in the polar stratosphere, was a dramatic evidence of the effects of anthropogenic emissions on the ozone layer. Human activity is likely responsible also for tropospheric ozone enhancements caused by the photochemistry associated to industrial emissions involving ozone precursors as the nitrogen dioxide. The effect of these variations at lower altitudes, with respect to background values, have been estimated to be the third largest source of the greenhouse effect. To support interpretation of the atmospheric phenomena, as well as interactions with the oceans and the ground, a constant and systematic monitoring of several atmospheric parameters, and with a good spatial coverage, is crucial. In this framework, global and systematic space-based observations of the atmospheric composition and its variations in time and space play a major role. Satellite measurements of atmospheric parameters has a proven and recognized effectiveness for such tasks. The advantage of atmospheric sounding performed from space, with respect to ground based techniques, lies in the very high number of available measurements per day and in the global coverage of the Earth, allowing for a detailed and continuous investigation of the atmospheric state. A number of different techniques are available, using different instruments, bands and viewing geometries. For all of them, a major problem is related to the intrinsically indirect nature of the measurements, as they result from the interaction between the electromagnetic radiation and the atmospheric constituents. The retrieval phase requires the solution of an inverse problem, which is never trivial and can be computationally very intensive, especially for this kind of nonlinear problems. A significant concurrent requirement is an adequate spatial resolution. Horizontal resolution is very hard to achieve by limb measurements, while it can be attained by nadir observations. Nadir measurements, however, can have poor vertical resolutions, and the inversion problem can be particularly computationally expensive. In this thesis we present novel approaches to the inversion of the nadir UV/VIS satellite Earth's radiance spectra for the retrieval of height resolved ozone information. The considered platforms are ESA EnviSat-SCIAMACHY and NASA-Aura OMI, which are particularly suited for these tasks owing to their combined high spectral and spatial resolutions. Both ozone concentration profiles and tropospheric ozone column are retrieved by means of NNs algorithms. NNs are made of interconnected elementary processing units, called neurons, and can learn from a training dataset; they were proven to be robust on systematic errors and calibration uncertainties on the input measurements vector, and they are likely to work better than OE with respect to cloudy scenarios or in presence of significant aerosols burdens. Once a net is trained it can perform retrievals in real-time