Differential impact of government lockdown policies on reducing air pollution levels and related mortality in Europe

Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO2, O3, PM2.5, and PM10 levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO2 compared to PM2.5 and PM10 concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe.This research had free and open access to all data sources. The work described in this paper has received funding from European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf the European Union through commercial contract Ref. CAMS_95p. Several CAMS Regional Models of the CAMS_50 Service contributed to the present work (CHIMERE, LOTOS-EUROS, MINNI, MOCAGE, MONARCH, SILAM) under CAMS_71 coordination. CAMS_COP066 service provided the lockdown emissions information. O.J. and M.G. thankfully acknowledge the computer resources at Marenostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2020-1-0007). SILAM model runs was also funded by Finnish Academy GLORIA project (No310372). The study was supported by the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655).Peer Reviewed"Article signat per 18 autors/es: Rochelle Schneider, Pierre Masselot, Ana M. Vicedo-Cabrera, Francesco Sera, Marta Blangiardo, Chiara Forlani, John Douros, Oriol Jorba, Mario Adani, Rostislav Kouznetsov, Florian Couvidat, Joaquim Arteta, Blandine Raux, Marc Guevara, Augustin Colette, Jérôme Barré, Vincent-Henri Peuch & Antonio Gasparrini "Postprint (published version

Potential of TROPOMI for understanding spatio-temporal variations in surface NO2 and their dependencies upon land use over the Iberian Peninsula

In orbit since late 2017, the Tropospheric Monitoring Instrument (TROPOMI) is offering new outstanding opportunities for better understanding the emission and fate of nitrogen dioxide (NO2) pollution in the troposphere. In this study, we provide a comprehensive analysis of the spatio-temporal variability of TROPOMI NO2 tropospheric columns (TrC-NO2) over the Iberian Peninsula during 2018–2021, considering the recently developed Product Algorithm Laboratory (PAL) product. We complement our analysis with estimates of NOx anthropogenic and natural soil emissions. Closely related to cloud cover, the data availability of TROPOMI observations ranges from 30 %–45 % during April and November to 70 %–80 % during summertime, with strong variations between northern and southern Spain. Strongest TrC-NO2 hotspots are located over Madrid and Barcelona, while TrC-NO2 enhancements are also observed along international maritime routes close the strait of Gibraltar, and to a lesser extent along specific major highways. TROPOMI TrC-NO2 appear reasonably well correlated with collocated surface NO2 mixing ratios, with correlations around 0.7–0.8 depending on the averaging time. We investigate the changes of weekly and monthly variability of TROPOMI TrC-NO2 depending on the urban cover fraction. Weekly profiles show a reduction of TrC-NO2 during the weekend ranging from −10 % to −40 % from least to most urbanized areas, in reasonable agreement with surface NO2. In the largest agglomerations like Madrid or Barcelona, this weekend effect peaks not in the city center but in specific suburban areas/cities, suggesting a larger relative contribution of commuting to total NOx anthropogenic emissions. The TROPOMI TrC-NO2 monthly variability also strongly varies with the level of urbanization, with monthly differences relative to annual mean ranging from −40 % in summer to +60 % in winter in the most urbanized areas, and from −10 % to +20 % in the least urbanized areas. When focusing on agricultural areas, TROPOMI observations depict an enhancement in June–July that could come from natural soil NO emissions. Some specific analysis of surface NO2 observations in Madrid show that the relatively sharp NO2 minimum used to occur in August (drop of road transport during holidays) has now evolved into a much broader minimum partly de-coupled from the observed local road traffic counting; this change started in 2018, thus before the COVID-19 outbreak. Over 2019–2021, a reasonable consistency of the inter-annual variability of NO2 is also found between both datasets. Our study illustrates the strong potential of TROPOMI TrC-NO2 observations for complementing the existing surface NO2 monitoring stations, especially in the poorly covered rural and maritime areas where NOx can play a key role, notably for the production of tropospheric O3.We acknowledge the RES (AECT-2022-1- 0008, AECT-2022-2-0003) for awarding us access to the MareNostrum supercomputer in the Barcelona Supercomputing Center, and we also acknowledge the support from the Red Temática ACTRIS España (CGL2017-90884-REDT) and the H2020 ACTRIS IMP (no. 871115). SC acknowledges support from BELSPO through BRAIN-BE 2.0 project LEGO-BEL-AQ (contract B2/191/P1/LEGO-BEL-AQ). This research has received fund- ing from the Ramon y Cajal grant (RYC2021-034511-I, MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR), the MITIGATE (PID2020- 16324RA695 I00/AEI/10.13039/501100011033) and VITALISE (PID2019-108086RA-I00 MCIN/AEI/10.13039/501100011033) projects from the Agencia Estatal de Investigación (AEI), the European Union’s Horizon 2020 research and innovation program under grant agreement no. 870301 (AQ-WATCH H2020 project), and the AXA Research Fund.Peer ReviewedPostprint (published version

Radiation Hardening of Digital Color CMOS Camera-on-a-Chip Building Blocks for Multi-MGy Total Ionizing Dose Environments

The Total Ionizing Dose (TID) hardness of digital color Camera-on-a-Chip (CoC) building blocks is explored in the Multi-MGy range using 60Co gamma-ray irradiations. The performances of the following CoC subcomponents are studied: radiation hardened (RH) pixel and photodiode designs, RH readout chain, Color Filter Arrays (CFA) and column RH Analog-to-Digital Converters (ADC). Several radiation hardness improvements are reported (on the readout chain and on dark current). CFAs and ADCs degradations appear to be very weak at the maximum TID of 6 MGy(SiO2), 600 Mrad. In the end, this study demonstrates the feasibility of a MGy rad-hard CMOS color digital camera-on-a-chip, illustrated by a color image captured after 6 MGy(SiO2) with no obvious degradation. An original dark current reduction mechanism in irradiated CMOS Image Sensors is also reported and discussed

The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016)

One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide column-integrated aerosol measurements, but observationally constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high-resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean Sea and parts of central Asia and the Atlantic and Indian oceans between 2007 and 2016. The horizontal resolution is 0.1◦ latitude × 0.1◦ longitude in a rotated grid, and the temporal resolution is 3 h. The reanalysis was produced using local ensemble transform Kalman filter (LETKF) data assimilation in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper-air variables (dust mass concentrations and the extinction coefficient), surface variables (dust deposition and solar irradiance fields among them) and total column variables (e.g. dust optical depth and load). Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20 µm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector. A set of ensemble statistics is archived for each output variable, namely the ensemble mean, standard deviation, maximum and median. The spatial and temporal distribution of the dust fields follows well-known dust cycle features controlled by seasonal changes in meteorology and vegetation cover. The analysis is statistically closer to the assimilated retrievals than the first guess, which proves the consistency of the data assimilation method. Independent evaluation using Aerosol Robotic Network (AERONET) dust-filtered optical depth retrievals indicates that the reanalysis data set is highly accurate (mean bias = −0.05, RMSE = 0.12 and r = 0.81 when compared to retrievals from the spectral de-convolution algorithm on a 3-hourly basis). Verification statistics are broadly homogeneous in space and time with regional differences that can be partly attributed to model limitations (e.g. poor representation of small-scale emission processes), the presence of aerosols other than dust in the observations used in the evaluation and differences in the number of observations among seasons. Such a reliable high-resolution historical record of atmospheric desert dust will allow a better quantification of dust impacts upon key sectors of society and economy, including health, solar energy production and transportation. The reanalysis data set (Di Tomaso et al., 2021) is distributed via Thematic Real-time Environmental Distributed Data Services (THREDDS) at BSC and is freely available at http://hdl.handle.net/21.12146/c6d4a608-5de3-47f6-a004-67cb1d498d98 (last access: 10 June 2022).This research has been supported by the DustClim project, which is part of ERA4CS, an ERA-NET programme co-funded by the European Union’s Horizon 2020 research and innovation programme (grant no. 690462); the European Research Council (FRAGMENT (grant no. 773051)); grant no. RYC-2015- 18690 funded by MCIN/AEI/10.13039/501100011033 and ESF Investing in your future; grant no. CGL2017-88911-R funded by MCIN/AEI/10.13039/501100011033 and ERDF A way of making Europe; the AXA Research Fund (AXA Chair on Sand and Dust Storms); the European Commission, Horizon 2020 Framework Programme (grant no. 792103 (SOLWARIS)); and ATMO-ACCESS (Access to Atmospheric Research Facilities) funded in the frame of the programme H2020-EU.1.4.1.2 (grant no. 101008004, 1 April 2021–31 March 2025). Jerónimo Escribano and Martina Klose have received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements H2020-MSCACOFUND-2016-754433 and H2020-MSCA-IF-2017-789630, respectively. Martina Klose received further support through the Helmholtz Association’s Initiative and Networking Fund (grant no. VH-NG-1533). This work has been partially funded by the contribution agreement between AEMET and BSC to carry out development and improvement activities of the products and services supplied by the World Meteorological Organization (WMO) Barcelona Dust Regional Center (i.e. the WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) Regional Center for Northern Africa, the Middle East and Europe).Peer ReviewedArticle signat per 24 autors/es: Enza Di Tomaso (1) , Jerónimo Escribano (1) , Sara Basart (1) , Paul Ginoux (2) , Francesca Macchia (1) , Francesca Barnaba (3) , Francesco Benincasa (1), Pierre-Antoine Bretonnière (1), Arnau Buñuel (1), Miguel Castrillo (1), Emilio Cuevas (4) , Paola Formenti (5) , María Gonçalves (1,6), Oriol Jorba (1), Martina Klose (1,7), Lucia Mona (8), Gilbert Montané Pinto (1) , Michail Mytilinaios (8), Vincenzo Obiso (1,a), Miriam Olid (1), Nick Schutgens (9) , Athanasios Votsis (10,11), Ernest Werner (12), and Carlos Pérez García-Pando (1,13) // (1) Barcelona Supercomputing Center (BSC), Barcelona, Spain; (2) NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA; (3) Consiglio Nazionale delle Ricerche–Istituto di Scienze dell’Atmosfera e del Clima (CNR–ISAC), Rome, Italy; (4) Izaña Atmospheric Research Center (IARC), Agencia Estatal de Meteorología (AEMET), Santa Cruz de Tenerife, Spain; (5) Université Paris Cité and Univ Paris-Est Créteil, CNRS, LISA, 75013 Paris, France; (6) Department of Project and Construction Engineering, Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Terrassa, Spain; (7) Department Troposphere Research, Institute of Meteorology and Climate Research (IMK-TRO), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; (8) Consiglio Nazionale delle Ricerche–Istituto di Metodologie per l’Analisi Ambientale (CNR–IMAA), Tito Scalo (PZ), Italy; (9) Department of Earth Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands; (10) Section of Governance and Technology for Sustainability (BMS-CSTM), University of Twente, Enschede, the Netherlands; (11) Weather and Climate Change Impact Research, Finnish Meteorological Institute (FMI), Helsinki, Finland; (12) Agencia Estatal de Meteorología (AEMET), Barcelona, Spain; (13) ICREA, Catalan Institution for Research and Advanced Studies, Barcelona, Spain anow at: NASA Goddard Institute for Space Studies (GISS), New York, New York, USAObjectius de Desenvolupament Sostenible::13 - Acció per al Clima::13.3 - Millorar l’educació, la conscienciació i la capacitat humana i institucional en relació amb la mitigació del canvi climàtic, l’adaptació a aquest, la reducció dels efectes i l’alerta primerencaObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaPostprint (published version

Cannabinoid receptors in GtoPdb v.2023.1

Cannabinoid receptors (nomenclature as agreed by the NC-IUPHAR Subcommittee on Cannabinoid Receptors [119]) are activated by endogenous ligands that include N-arachidonoylethanolamine (anandamide), N-homo-γ-linolenoylethanolamine, N-docosatetra-7,10,13,16-enoylethanolamine and 2-arachidonoylglycerol. Potency determinations of endogenous agonists at these receptors are complicated by the possibility of differential susceptibility of endogenous ligands to enzymatic conversion [5].There are currently three licenced cannabinoid medicines each of which contains a compound that can activate CB1 and CB2 receptors [111]. Two of these medicines were developed to suppress nausea and vomiting produced by chemotherapy. These are nabilone (Cesamet®), a synthetic CB1/CB2 receptor agonist, and synthetic Δ9-tetrahydrocannabinol (Marinol®; dronabinol), which can also be used as an appetite stimulant. The third medicine, Sativex®, contains mainly Δ9-tetrahydrocannabinol and cannabidiol, both extracted from cannabis, and is used to treat multiple sclerosis and cancer pain

Phosphorus Versus Arsenic: Role of the Photodiode Doping Element in CMOS Image Sensor Radiation-Induced Dark Current and Random Telegraph Signal

This work the role of the phosphorus doping element in the radiation-induced dark current in a CMOS image sensor (CIS) photodiode. The neutron and proton irradiations on shallow arsenic-based photodiode CISs and deep phosphorus-based photodiodes CISs have been performed. The results highlight the applicability of the same dark current increase and random telegraph signal (RTS) models. Already verified on other photodiode structures, these results further extend the universality of these analytic tools. Moreover, it emphasizes that the phosphorus element does not play a significant role either in the radiation-induced dark current increase or in the dark current RTS. The results on RTS after annealing reveal the same recovery dynamic than those already observed in irradiated image sensors, suggesting that the phosphorus element does not play a significant role after annealing. Therefore, this work is a piece of experimental evidence supporting the idea that RTS induced by displacement damage is principally due to defect clusters mainly constituted of intrinsic silicon defects such as clusters of vacancies and interstitials

Multi-MGy total ionizing dose induced MOSFET variability effects on radiation hardened CMOS image sensor performances

MOSFETs variability in irradiated CIS up to 10 MGy (SiO2) is statistically investigated on about 65000 devices. Different variability sources are identified and the role played by the transistors composing the readout chain is clarified

Radiation Hardening of Digital Color CMOS Camera-on-a-Chip Building Blocks for Grad Total Ionizing Dose Environments

Radiation Hardening of Digital Color CMOS Camera-on-a-Chip Building Blocks for Grad Total Ionizing Dose Environments

Vulnerability and Hardening Studies of Optical and Illumination Systems at MGy Dose Levels

In the framework of the fusion for energy radiation hard imaging system project, the main radiation effects affecting the image quality of a miniaturized complementary metal-oxide-semiconductor-based camera exposed to radiation doses up to 1 MGy(SiO 2 ) are investigated for ITER applications. The radiation effects related to two of the three subcomponents of the camera are investigated: the optical system (OS) and the illumination system (IS). Subsystem demonstrators have been manufactured selecting radiation tolerant or hardened materials and components to demonstrate the feasibility to withstand such high dose levels while fulfilling the ITER remote handling needs in terms of optical performances and miniaturization. Regarding the OS, the observed degradation of the radiation-hardened optical glasses used for the OS lenses is characterized in terms of both radiation-induced attenuation and radiation-induced refractive-index change. At the system level, impact of these phenomena on the OS demonstrator performances is discussed in terms of image contrast. Radiation test results highlight the high radiation tolerance of manufactured monochrome and color OS to both degradation mechanisms. Regarding the IS, the selected architecture consists in a ring of 20 commercially available light-emitting diodes (LEDs) with monochrome (amber) or white emissions. An appropriate choice for the LEDs allows designing an IS with the requested performances and slight degradation of its output power at the MGy dose levels. From the obtained results, developing miniaturized IS and OS subcomponents for MGy dose operation levels appears realistic using commercially available technologies and appropriate hardening procedures

Trail formation based on directed pheromone deposition

We propose an Individual-Based Model of ant-trail formation. The ants are modeled as self-propelled particles which deposit directed pheromones and interact with them through alignment interaction. The directed pheromones intend to model pieces of trails, while the alignment interaction translates the tendency for an ant to follow a trail when it meets it. Thanks to adequate quantitative descriptors of the trail patterns, the existence of a phase transition as the ant-pheromone interaction frequency is increased can be evidenced. Finally, we propose both kinetic and fluid descriptions of this model and analyze the capabilities of the fluid model to develop trail patterns. We observe that the development of patterns by fluid models require extra trail amplification mechanisms that are not needed at the Individual-Based Model level