Lidar Calibration Centre

This paper presents the newly established Lidar Calibration Centre, a distributed infrastructure in Europe, whose goal is to offer services for complete characterization and calibration of lidars and ceilometers. Mobile reference lidars, laboratories for testing and characterization of optics and electronics, facilities for inspection and debugging of instruments, as well as for training in good practices are open to users from the scientific community, operational services and private sector. The Lidar Calibration Centre offers support for trans-national access through the EC HORIZON2020 project ACTRIS-2

EARLINET: towards an advanced sustainable European aerosol lidar network

The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue, which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 stations in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multiwavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase in the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite community, linking the research community with the operational world, with the aim of establishing of the atmospheric part of the European component of the integrated global observing system.Peer ReviewedPostprint (published version

Antiplatelet agents for chronic kidney disease

To evaluate the benefits and harms of antiplatelet therapy in patients with any form of kidney disease, including patients with CKD not receiving renal replacement therapy (RRT), patients receiving any form of dialysis, and kidney transplant recipients

EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds

The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986, last access: 5 November 2021). The alert products developed by the EUNADICS-AV EWS, i.e. near-real-time (NRT) observations, email notifications and netCDF (Network Common Data Form) alert data products (called NCAP files), have shown significant interest in using selective detection of natural airborne hazards from polar-orbiting satellites. The combination of several sensors inside a single global system demonstrates the advantage of using a triggered approach to obtain selective detection from observations, which cannot initially discriminate the different aerosol types. Satellite products from hyperspectral ultraviolet–visible (UV–vis) and infrared (IR) sensors (e.g. TROPOMI – TROPOspheric Monitoring Instrument – and IASI – Infrared Atmospheric Sounding Interferometer) and a broadband geostationary imager (Spinning Enhanced Visible and InfraRed Imager; SEVIRI) and retrievals from ground-based networks (e.g. EARLINET – European Aerosol Research Lidar Network, E-PROFILE and the regional network from volcano observatories) are combined by our system to create tailored alert products (e.g. selective ash detection, SO2 column and plume height, dust cloud, and smoke from wildfires). A total of 23 different alert products are implemented, using 1 geostationary and 13 polar-orbiting satellite platforms, 3 external existing service, and 2 EU and 2 regional ground-based networks. This allows for the identification and the tracking of extreme events. The EUNADICS-AV EWS has also shown the need to implement a future relay of radiological data (gamma dose rate and radionuclides concentrations in ground-level air) in the case of a nuclear accident. This highlights the interest of operating early warnings with the use of a homogenised dataset. For the four types of airborne hazard, the EUNADICS-AV EWS has demonstrated its capability to provide NRT alert data products to trigger data assimilation and dispersion modelling providing forecasts and inverse modelling for source term estimate. Not all of our alert data products (NCAP files) are publicly disseminated. Access to our alert products is currently restricted to key users (i.e. Volcanic Ash Advisory Centres, national meteorological services, the World Meteorological Organization, governments, volcano observatories and research collaborators), as these are considered pre-decisional products. On the other hand, thanks to the EUNADICS-AV–SACS (Support to Aviation Control Service) web interface (https://sacs.aeronomie.be, last access: 5 November 2021), the main part of the satellite observations used by the EUNADICS-AV EWS is shown in NRT, with public email notification of volcanic emission and delivery of tailored images and NCAP files. All of the ATM stakeholders (e.g. pilots, airlines and passengers) can access these alert products through this free channel.Peer ReviewedArticle escrit per 46 autors/es: Hugues Brenot Nicolas Theys Lieven Clarisse Jeroen van Gent Daniel Hurtmans Sophie Vandenbussche Nikolaos Papagiannopoulos Lucia Mona Timo Virtanen Andreas Uppstu Mikhail Sofiev Luca Bugliaro Margarita Vázquez-Navarro Pascal Hedelt Michelle Maree Parks Sara Barsotti Mauro Coltelli William Moreland Simona Scollo Giuseppe Salerno Delia Arnold-Arias Marcus Hirtl Tuomas Peltonen Juhani Lahtinen Klaus Sievers Florian Lipok Rolf Rüfenacht Alexander Haefele Maxime Hervo Saskia Wagenaar Wim Som de Cerff Jos de Laat Arnoud Apituley Piet Stammes Quentin Laffineur Andy Delcloo Robertson Lennart Carl-Herbert Rokitansky Arturo Vargas Markus Kerschbaum Christian Resch Raimund Zopp Matthieu Plu 1 Vincent-Henri Peuch Michel van Roozendael Gerhard WotawaPostprint (author's final draft

The ash dispersion over Europe during the Eyjafjallajökull eruption e Comparison of CMAQ simulations to remote sensing and air-borne in-situ observations

The dispersion of volcanic ash over Europe after the outbreak of the Eyjafjallajökull on Iceland on 14 April 2010 has been simulated with a conventional three-dimensional Eulerian chemistry transport model system, the Community Multiscale Air Quality (CMAQ) model. Four different emission scenarios representing the lower and upper bounds of the emission height and intensity were considered. The atmospheric ash concentrations turned out to be highly variable in time and space. The model results were compared to three different kinds of observations: Aeronet aerosol optical depth (AOD) measurements, Earlinet aerosol extinction profiles and in-situ observations of the ash concentration by means of optical particle counters aboard the DLR Falcon aircraft. The model was able to reproduce observed AOD values and atmospheric ash concentrations. Best agreement was achieved for lower emission heights and a fraction of 2% transportable ash in the total volcanic emissions. The complex vertical structure of the volcanic ash layers in the free troposphere could not be simulated. Compared to the observations, the model tends to show vertically more extended, homogeneous aerosol layers. This is caused by a poor vertical resolution of the model at higher altitudes and a lack of information about the vertical distribution of the volcanic emissions. Only a combination of quickly available observations of the volcanic ash cloud and atmospheric transport models can give a comprehensive picture of ash concentrations in the atmosphere

Looking into CALIPSO climatological products: Evaluation and suggestions from EARLINET

CALIPSO (Cloud-Aerosol Lidar and Pathfinder Satellite Observations) Level 3 (CL3) data were compared against EARLINET (European Aerosol Research Lidar Network) monthly averages obtained by profiles during satellite overpasses. Data from EARLINET stations of Évora, Granada, Leipzig, Naples and Potenza, equipped with advanced multi-wavelength Raman lidars were used for this study. Owing to spatial and temporal differences, we reproduced the CL3 filtering rubric onto the CALIPSO Level 2 data. The CALIPSO monthly mean profiles following this approach are called CALIPSO Level 3*, CL3*. This offers the possibility to achieve direct comparable datasets. In respect to CL3 data, the agreement typically improved, in particular above the areas directly affected by the anthropogenic activities within the planetary boundary layer. However in most of the cases a subtle CALIPSO underestimation was observed with an average bias of 0.03 km-1. We investigated the backscatter coefficient applying the same screening criteria, where the mean relative difference in respect to the extinction comparison improved from 15.2% to 11.4%. Lastly, the typing capabilities of CALIPSO were assessed outlining the importance of the correct aerosol type (and associated lidar ratio value) assessment to the CALIPSO aerosol properties retrieval

Identification of a regulatory pathway inhibiting adipogenesis via RSPO2

Healthy adipose tissue remodeling depends on the balance between de novo adipogenesis from adipogenic progenitor cells and the hypertrophy of adipocytes. De novo adipogenesis has been shown to promote healthy adipose tissue expansion, which confers protection from obesity-associated insulin resistance. Here, we define the role and trajectory of different adipogenic precursor subpopulations and further delineate the mechanism and cellular trajectory of adipogenesis, using single-cell RNA-sequencing datasets of murine adipogenic precursors. We identify Rspo2 as a functional regulator of adipogenesis, which is secreted by a subset of CD142$^{+}$ cells to inhibit maturation of early progenitors through the receptor Lgr4. Increased circulating RSPO2 in mice leads to adipose tissue hypertrophy and insulin resistance and increased RSPO2 levels in male obese individuals correlate with impaired glucose homeostasis. Taken together, these findings identify a complex cellular crosstalk that inhibits adipogenesis and impairs adipose tissue homeostasis

An automatic aerosol classification for earlinet: application and results

Aerosol typing is essential for understanding the impact of the different aerosol sources on climate, weather system and air quality. An aerosol classification method for EARLINET (European Aerosol Research Lidar Network) measurements is introduced which makes use the Mahalanobis distance classifier. The performance of the automatic classification is tested against manually classified EARLINET data. Results of the application of the method to an extensive aerosol dataset will be presented. © The Authors, published by EDP Sciences, 2018.Peer ReviewedPostprint (published version