910 research outputs found

    Significant spatial gradients in new particle formation frequency in Greece during summer

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    Extensive continuous particle number size distribution measurements took place during two summers (2020 and 2021) at 11 sites in Greece for the investigation of the frequency and the spatial extent of new particle formation (NPF). The study area is characterized by high solar intensity and fast photochemistry and has moderate to low fine particulate matter levels during the summer. The average PM2.5 levels were relatively uniform across the examined sites. The NPF frequency during summer varied from close to zero in the southwestern parts of Greece to more than 60 % in the northern, central, and eastern regions. The mean particle growth rate for each station varied between 3.4 and 8 nm h−1, with an average rate of 5.7 nm h−1. At most of the sites there was no statistical difference in the condensation sink between NPF event and non-event days, while lower relative humidity was observed during the events. The high-NPF-frequency sites in the north and northeast were in close proximity to both coal-fired power plants (high emissions of SO2) and agricultural areas with some of the highest ammonia emissions in the country. The southern and western parts of Greece, where NPF was infrequent, were characterized by low ammonia emissions, while moderate levels of sulfuric acid were estimated (107 molec. cm−3) in the west. Although the emissions of biogenic volatile organic compounds were higher in western and southern sectors, they did not appear to lead to enhanced frequency of NPF. The infrequent events at these sites occurred when the air masses had spent a few hours over areas with agricultural activities and thus elevated ammonia emissions. Air masses arriving at the sites directly from the sea were not connected with atmospheric NPF. These results support the hypothesis that ammonia and/or amines limit new particle formation in the study area.</p

    First results from the CAST experiment

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    The CAST Experiment commenced its first phase of solar axion-searching in 2003, and ran successfully for two years. In the transverse field of a decommissioned Large Hadron Collider (LHC) test magnet (9.26m, 9T), the CERN Axion Solar Telescope intends to transform axions -that would be produced in the sun- into X-rays with energies of a few keV. The first results from the analysis of the data taken in 2003 show no signature of axions, implying an upper limit to the axion-photon coupling gaγ ⩽ 1.16 × 10⁻¹⁰ GeV⁻¹ at 95% C.L. for ma < 0.02 eV, already a factor 100 better than previous searches. In Phase I the twin bores of the magnet were kept in vacuum. In Phase II (due to start in November 2005) the bores of the magnet will be filled with a buffer gas, which will allow CAST to explore the region of higher axion masses

    HPC+ in the medical field: overview and current examples

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    BACKGROUND: To say data is revolutionising the medical sector would be a vast understatement. The amount of medical data available today is unprecedented and has the potential to enable to date unseen forms of healthcare. To process this huge amount of data, an equally huge amount of computing power is required, which cannot be provided by regular desktop computers. These areas can be (and already are) supported by High-Performance-Computing (HPC), High-Performance Data Analytics (HPDA), and AI (together "HPC +").OBJECTIVE: This overview article aims to show state-of-the-art examples of studies supported by the National Competence Centres (NCCs) in HPC+ within the EuroCC project, employing HPC, HPDA and AI for medical applications.METHOD: The included studies on different applications of HPC in the medical sector were sourced from the National Competence Centres in HPC and compiled into an overview article. Methods include the application of HPC+ for medical image processing, high-performance medical and pharmaceutical data analytics, an application for pediatric dosimetry, and a cloud-based HPC platform to support systemic pulmonary shunting procedures.RESULTS: This article showcases state-of-the-art applications and large-scale data analytics in the medical sector employing HPC+ within surgery, medical image processing in diagnostics, nutritional support of patients in hospitals, treating congenital heart diseases in children, and within basic research.CONCLUSION: HPC + support scientific fields from research to industrial applications in the medical area, enabling researchers to run faster and more complex calculations, simulations and data analyses for the direct benefit of patients, doctors, clinicians and as an accelerator for medical research

    Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe

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    To fight against the first wave of coronavirus disease 2019 (COVID-19) in 2020, lockdown measures were implemented in most European countries. These lockdowns had well-documented effects on human mobility. We assessed the impact of the lockdown implementation and relaxation on air pollution by comparing daily particulate matter (PM), nitrogen dioxide (NO2) and ozone (O3) concentrations, as well as particle number size distributions (PNSDs) and particle light absorption coefficient in situ measurement data, with values that would have been expected if no COVID-19 epidemic had occurred at 28 sites across Europe for the period 17 February–31 May 2020. Expected PM, NO2 and O3 concentrations were calculated from the 2020 Copernicus Atmosphere Monitoring Service (CAMS) ensemble forecasts, combined with 2019 CAMS ensemble forecasts and measurement data. On average, lockdown implementations did not lead to a decrease in PM2.5 mass concentrations at urban sites, while relaxations resulted in a +26 ± 21 % rebound. The impacts of lockdown implementation and relaxation on NO2 concentrations were more consistent (−29 ± 17 and +31 ± 30 %, respectively). The implementation of the lockdown measures also induced statistically significant increases in O3 concentrations at half of all sites (+13 % on average). An enhanced oxidising capacity of the atmosphere could have boosted the production of secondary aerosol at those places. By comparison with 2017–2019 measurement data, a significant change in the relative contributions of wood and fossil fuel burning to the concentration of black carbon during the lockdown was detected at 7 out of 14 sites. The contribution of particles smaller than 70 nm to the total number of particles significantly also changed at most of the urban sites, with a mean decrease of −7 ± 5 % coinciding with the lockdown implementation. Our study shows that the response of PM2.5 and PM10 mass concentrations to lockdown measures was not systematic at various sites across Europe for multiple reasons, the relationship between road traffic intensity and particulate air pollution being more complex than expected.</p

    Phenomenology of ultrafine particle concentrations and size distribution across urban Europe

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    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 <10 nm PNC are needed for full evaluation of the health effects of this size fraction

    Annual cycle of hygroscopic properties and mixing state of the suburban aerosol in Athens, Greece

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    The hygroscopic properties of atmospheric aerosol were investigated at a suburban environment in Athens, Greece, from August 2016 to July 2017. The growth factor distribution probability density function (GF-PDF) and mixing state were determined with a hygroscopicity tandem differential mobility analyser (HTDMA). Four dry particle sizes (D0) were selected to be analysed in terms of their hygroscopic properties at 90 % relative humidity. The annual mean GFs for D0 = 30, 50, 80 and 250 nm were found to be equal to 1.28, 1.11, 1.13 and 1.22, respectively. The hygroscopic growth spectra were divided into two distinct hygroscopic ranges: a non- and/or slightly hygroscopic mode (GF &lt; 1.12) and a moderately hygroscopic mode (GF &gt; 1.12), which are representative of a suburban environment influenced by local/urban emissions and background aerosol. The standard deviation σ of the GF-PDF was employed as a measure of the mixing state of ambient aerosol. The 30 nm particles were mostly internally mixed, whereas larger particles were found to be externally mixed, either with a distinct bimodal structure or with partly overlapping modes. Cluster analysis on the hourly dry number size distributions was performed to identify the link between aerosol hygroscopicity and aerosol emission sources and formation processes. The size distributions were classified into five groups, with the “mixed urban and regional background” aerosol (67 %) and the “fresh traffic-related particles” from the neighbourhood urban area (15 %) accounting for more than 80 % of the results. The hygroscopic properties for 50 and 80 nm were found to be similar in all cases, indicating particles of similar nature and origin across these sizes. This was also confirmed through the modal analysis of the average number size distributions for each cluster; the 50 and 80 nm particles were found to belong to the same Aitken mode in most cases. The 250 nm particles (i.e. accumulation mode) were generally more hygroscopic than Aitken particles but less hygroscopic than the 30 nm particles (nuclei mode).</p

    Neutron-induced fission cross sections of <math><mmultiscripts><mi>Th</mi><mprescripts/><none/><mn>232</mn></mmultiscripts></math> and <math><mmultiscripts><mi mathvariant="normal">U</mi><mprescripts/><none/><mn>233</mn></mmultiscripts></math> up to 1 GeV using parallel plate avalanche counters at the CERN n_TOF facility

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    International audienceThe neutron-induced fission cross sections of Th232 and U233 were measured relative to U235 in a wide neutron energy range up to 1 GeV (and from fission threshold in the case of Th232, and from 0.7 eV in case of U233), using the white-spectrum neutron source at the CERN Neutron Time-of-Flight (n_TOF) facility. Parallel plate avalanche counters (PPACs) were used, installed at the Experimental Area 1 (EAR1), which is located at 185 m from the neutron spallation target. The anisotropic emission of fission fragments were taken into account in the detection efficiency by using, in the case of U233, previous results available in EXFOR, whereas in the case of Th232 these data were obtained from our measurement, using PPACs and targets tilted 45∘ with respect to the neutron beam direction. Finally, the obtained results are compared with past measurements and major evaluated nuclear data libraries. Calculations using the high-energy reaction models INCL++ and ABLA07 were performed and some of their parameters were modified to reproduce the experimental results. At high energies, where no other neutron data exist, our results are compared with experimental data on proton-induced fission. Moreover, the dependence of the fission cross section at 1 GeV with the fissility parameter of the target nucleus is studied by combining those (p,f) data with our (n,f) data on Th232 and U233 and on other isotopes studied earlier at n_TOF using the same experimental setup

    Neutron-induced fission cross sections of Th 232 and U 233 up to 1 GeV using parallel plate avalanche counters at the CERN n_TOF facility

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    The neutron-induced fission cross sections of 232^{232}Th and 233^{233}U were measured relative to 235^{235}U in a wide neutron energy range up to 1 GeV (and from fission threshold in the case of 232^{232}Th, and from 0.7 eV in case of 233^{233}U), using the white-spectrum neutron source at the CERN Neutron Time-of-Flight (n_TOF) facility. Parallel plate avalanche counters (PPACs) were used, installed at the Experimental Area 1 (EAR1), which is located at 185 m from the neutron spallation target. The anisotropic emission of fission fragments were taken into account in the detection efficiency by using, in the case of 233^{233}U, previous results available in EXFOR, whereas in the case of 232^{232}Th these data were obtained from our measurement, using PPACs and targets tilted 45∘ with respect to the neutron beam direction. Finally, the obtained results are compared with past measurements and major evaluated nuclear data libraries. Calculations using the high-energy reaction models INCL++ and ABLA07 were performed and some of their parameters were modified to reproduce the experimental results. At high energies, where no other neutron data exist, our results are compared with experimental data on proton-induced fission. Moreover, the dependence of the fission cross section at 1 GeV with the fissility parameter of the target nucleus is studied by combining those (p,f) data with our (n,f) data on 232^{232}Th and 233^{233}U and on other isotopes studied earlier at n_TOF using the same experimental setup

    Prospects for Galactic transient sources detection with the Cherenkov Telescope Array

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    Several types of Galactic sources, like magnetars, microquasars, novae or pulsar wind nebulae flares, display transient emission in the X-ray band. Some of these sources have also shown emission at MeV-GeV energies. However, none of these Galactic transients have ever been detected in the very-high-energy (VHE; E>100 GeV) regime by any Imaging Air Cherenkov Telescope (IACT). The Galactic Transient task force is a part of the Transient Working group of the Cherenkov Telescope Array (CTA) Consortium. The task force investigates the prospects of detecting the VHE counterpart of such sources, as well as their study following Target of Opportunity (ToO) observations. In this contribution, we will show some of the results of exploring the capabilities of CTA to detect and observe Galactic transients; we assume different array configurations and observing strategies

    Reconstruction of stereoscopic CTA events using deep learning with CTLearn

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    The Cherenkov Telescope Array (CTA), conceived as an array of tens of imaging atmospheric Cherenkov telescopes (IACTs), is an international project for a next-generation ground-based gamma-ray observatory, aiming to improve on the sensitivity of current-generation instruments a factor of five to ten and provide energy coverage from 20 GeV to more than 300 TeV. Arrays of IACTs probe the very-high-energy gamma-ray sky. Their working principle consists of the simultaneous observation of air showers initiated by the interaction of very-high-energy gamma rays and cosmic rays with the atmosphere. Cherenkov photons induced by a given shower are focused onto the camera plane of the telescopes in the array, producing a multi-stereoscopic record of the event. This image contains the longitudinal development of the air shower, together with its spatial, temporal, and calorimetric information. The properties of the originating very-high-energy particle (type, energy, and incoming direction) can be inferred from those images by reconstructing the full event using machine learning techniques. In this contribution, we present a purely deep-learning driven, full-event reconstruction of simulated, stereoscopic IACT events using CTLearn. CTLearn is a package that includes modules for loading and manipulating IACT data and for running deep learning models, using pixel-wise camera data as input
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