Application of ultra wide вand technology

Ultra-WideBand is a high data rate, low power short-range wireless technology, considered as a highspeed alternative to existing wireless technologies

Application of ultra wide вand technology

Ultra-WideBand is a high data rate, low power short-range wireless technology, considered as a highspeed alternative to existing wireless technologies

Multipath propagation problem analysis in data transmission systems

This article deals with the problem of multipath propagation and electromagnetic wave when it is incident on a layered medium. For the selection of tangible objects on the background of the environment in practice is usually used the reflective characteristics serving tool to optimize the electrical parameters of the probing signal

Eurodelta multi-model simulated and observed particulate matter trends in Europe in the period of 1990–2010

The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990–2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000–2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty. The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) µg m−3 (or between 10 % and 30 %) across most of Europe (by 0.5–2 µg m−3 in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %–40 % over most of Europe, increasing to 50 %–60 % in the northern and eastern parts of the EDT domain. Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are −0.24 and −0.22 µg m−3 yr−1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of −0.35 and −0.40 µg m−3 yr−1 respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are −1.7 % yr−1 and −2.0 % yr−1 from the model ensemble and −2.1 % yr−1 and −2.9 % yr−1 from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries. The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located. The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of and to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appear to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties (including the implications of not accounting for forest fires and natural mineral dust by some of the models) and the effect of inter-annual meteorological variability on the trend analysis.The Ineris coordination of the EURODELTA-Trends exercise has been supported by the French Ministry in charge of Ecology in the context of the Task Force on Measurement and Modelling of the EMEP program of the LRTAP Convention. The CHIMERE simulations were performed using the TGCC supercomputers under GENCI computing allocation. The work of EMEP MSC-W has been supported by the EMEP Trust Fund under the United Nations Economic Commission for Europe (UN ECE). Funding for the MATCH participation was jointly divided between Nordforsk through the research programme Nordic Welfare (grant no. 75007), the Swedish Environmental Protection Agency through the SCAC research programme, and the 2017–2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND programme, with the funding organisations AKA (contract no. 326328), ANR (grant no. ANR-18-EBI4-007), BMBF (KFZ; grant no. 01LC1810A), FORMAS (contract nos. 2018-02434, 2018-02436, 2018-02437, and 2018-02438) and MICINN (APCIN; grant no. PCI2018-093149). Giancarlo Ciarelli has been supported by ADEME and the Swiss National Science Foundation (grant no. P2EZP2_175166). MINNI participation in this project was supported by the “Cooperation Agreement for support to international Conventions, Protocols and related negotiations on air pollution issues”, funded by the Italian Ministry for the Environment, Land and Sea. Financial support for the Institute for Advanced Sustainability Studies (IASS) has been provided by the Federal Ministry of Education and Research of Germany (BMBF) and the Ministry for Science, Research and Culture of the State of Brandenburg (MWFK). The work of CIEMAT has been supported by the Ministry for the Ecological Transition and Demographic Challenge (MITERD).Peer Reviewed"Article signat per 23 autors/es: Svetlana Tsyro, Wenche Aas, Augustin Colette, Camilla Andersson, Bertrand Bessagnet, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Kathleen Mar, Mihaela Mircea, Noelia Oter, Maria-Teresa Pay, Valentin Raffort, Yelva Roustan, Mark R. Theobald, Marta G. Vivanco, Hilde Fagerli, Peter Wind, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, and Mario Adani"Postprint (published version

Evaluation of the performance of four chemical transport models in predicting the aerosol chemical composition in Europe in 2005

© Author(s) 2016.Four regional chemistry transport models were applied to simulate the concentration and composition of particulate matter (PM) in Europe for 2005 with horizontal resolution 20 km. The modelled concentrations were compared with the measurements of PM chemical composition by the European Monitoring and Evaluation Programme (EMEP) monitoring network. All models systematically underestimated PM10 and PM2:5 by 10–60 %, depending on the model and the season of the year, when the calculated dry PM mass was compared with the measurements. The average water content at laboratory conditions was estimated between 5 and 20% for PM2:5 and between 10 and 25% for PM10. For majority of the PM chemical components, the relative underestimation was smaller than it was for total PM, exceptions being the carbonaceous particles and mineral dust. Some species, such as sea salt and NO3, were overpredicted by the models. There were notable differences between the models’ predictions of the seasonal variations of PM, mainly attributable to different treatments or omission of some source categories and aerosol processes. Benzo(a)pyrene concentrations were overestimated by all the models over the whole year. The study stresses the importance of improving the models’ skill in simulating mineral dust and carbonaceous compounds, necessity for high-quality emissions from wildland fires, as well as the need for an explicit consideration of aerosol water content in model–measurement comparison.Peer reviewedFinal Published versio

On the spatio-temporal representativeness of observations

The discontinuous spatio-temporal sampling of observations has an impact when using them to construct climatologies or evaluate models. Here we provide estimates of this so-called representation error for a range of timescales and length scales (semi-annually down to sub-daily, 300 to 50 km) and show that even after substantial averaging of data significant representation errors may remain, larger than typical measurement errors. Our study considers a variety of observations: ground-site or in situ remote sensing (PM2.5, black carbon mass or number concentrations), satellite remote sensing with imagers or lidar (extinction). We show that observational coverage (a measure of how dense the spatiotemporal sampling of the observations is) is not an effective metric to limit representation errors. Different strategies to construct monthly gridded satellite L3 data are assessed and temporal averaging of spatially aggregated observations (super-observations) is found to be the best, although it still allows for significant representation errors. However, temporal collocation of data (possible when observations are compared to model data or other observations), combined with temporal averaging, can be very effective at reducing representation errors. We also show that ground-based and wideswath imager satellite remote sensing data give rise to similar representation errors, although their observational sampling is different. Finally, emission sources and orography can lead to representation errors that are very hard to reduce, even with substantial temporal averaging

Modelling of sea salt concentrations over Europe: key uncertainties and comparison with observations

Sea salt aerosol can significantly affect the air quality. Sea salt can cause enhanced concentrations of particulate matter and change particle chemical composition, in particular in coastal areas, and therefore should be accounted for in air quality modelling. We have used an EMEP Unified model to calculate sea salt concentrations and depositions over Europe, focusing on studying the effects of uncertainties in sea salt production and lifetime on calculation results. Model calculations of sea salt have been compared with EMEP observations of sodium concentrations in air and precipitation for a four year period, from 2004 to 2007, including size (fine/coarse) resolved EMEP intensive measurements in 2006 and 2007. In the presented calculations, sodium air concentrations are between 8% and 46% overestimated, whereas concentrations in precipitation are systematically underestimated by 65–70% for years 2004–2007. A series of model tests have been performed to investigate the reasons for this underestimation, but further studies are needed. The model is found to reproduce the spatial distribution of Na<sup>+</sup> in air and precipitation over Europe fairly well, and to capture most of sea salt episodes. The paper presents the main findings from a series of tests in which we compare several different sea spray source functions and also look at the effects of meteorological input and the efficiency of removal processes on calculated sea salt concentrations. Finally, sea salt calculations with the EMEP model have been compared with results from the SILAM model and observations for 2007. While the models produce quite close results for Na<sup>+</sup> at the majority of 26 measurement sites, discrepancies in terms of bias and temporal correlation are also found. Those differences are believed to occur due to differences in the representation of source function and size distribution of sea salt aerosol, different meteorology used for model runs and the different models' resolution. This study contributes to getting a better insight on uncertainties associated with sea salt calculations and thus facilitates further improvement of aerosol modelling on both regional and global scales

Good Agreement Between Modeled and Measured Sulfur and Nitrogen Deposition in Europe, in Spite of Marked Differences in Some Sites

Atmospheric nitrogen and sulfur deposition is an important effect of atmospheric pollution and may affect forest ecosystems positively, for example enhancing tree growth, or negatively, for example causing acidification, eutrophication, cation depletion in soil or nutritional imbalances in trees. To assess and design measures to reduce the negative impacts of deposition, a good estimate of the deposition amount is needed, either by direct measurement or by modeling. In order to evaluate the precision of both approaches and to identify possible improvements, we compared the deposition estimates obtained using an Eulerian model with the measurements performed by two large independent networks covering most of Europe. The results are in good agreement (bias <25%) for sulfate and nitrate open field deposition, while larger differences are more evident for ammonium deposition, likely due to the greater influence of local ammonia sources. Modeled sulfur total deposition compares well with throughfall deposition measured in forest plots, while the estimate of nitrogen deposition is affected by the tree canopy. The geographical distribution of pollutant deposition and of outlier sites where model and measurements show larger differences are discussed

Multi-model simulations of aerosol and ozone radiative forcing due to anthropogenic emission changes during the period 1990-2015

Over the past few decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and air pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing, using recently updated emission data for the period 1990-2015, as simulated by seven global atmospheric composition models. The models broadly reproduce large-scale changes in surface aerosol and ozone based on observations (e.g., -1 to -3%/yr in aerosols over 30 the US and Europe). The global mean radiative forcing due to ozone and aerosol changes over the 1990-2015 period increased by +0.17 ±0.08 Wm-2, with approximately 1/3 due to ozone. This increase is more strongly positive than that reported in IPCC AR5. The main reasons for the increased positive radiative forcing of aerosols over this period are the substantial reduction of global mean SO2 emissions, which is stronger in the new emission inventory compared to that used in the IPCC analysis, and higher black carbon emissions