Found 9989 publications. Showing page 54 of 400:
2022
2022
2022
Aerosol distributions have a potentially large influence on climate-relevant cloud properties but can be difficult to observe over the Arctic given pervasive cloudiness, long polar nights, data paucity over remote regions, and periodic diamond dust events that satellites can misclassify as aerosol. We compared Arctic 2008–2015 mineral dust and combustion aerosol distributions from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis products, and the FLEXible PARTicle (FLEXPART) dispersion model. Based on coincident, seasonal Atmospheric Infrared Sounder (AIRS) Arctic satellite meteorological data, diamond dust may occur up to 60 % of the time in winter, but it hardly ever occurs in summer. In its absence, MERRA-2 and FLEXPART each predict the vertical and horizontal distribution of large-scale patterns in combustion aerosols with relatively high confidence (Kendall tau rank correlation > 0.6), although a sizable amount of variability is still unaccounted for. They do the same for dust, except in conditions conducive to diamond dust formation where CALIPSO is likely misclassifying diamond dust as mineral dust and near the surface...
2022
2022
Condensable primary organic aerosol (CPOA) emissions are a class of organic compounds that are vapour phase at stack conditions, but which can undergo both condensation and evaporation processes as the stack air is cooled and diluted upon discharge into ambient air. Emission factors may misrepresent, and even miss, the amount of particulate matter (PM) or gas that actually enters the atmosphere, depending on the emission measurement techniques used. In the current emission reporting to EMEP/CLRTAP there is no clear definition of whether condensable organics are included or not, and, if included, to what extent.
In this study, new residential combustion emission estimates have been made for the years 2005-2019 (called TNO Ref2_v2.1) in a consistent manner, with improved estimation of fuel consumption (in particular wood) and emission factors, as well as an updated split of fuel use over different appliances and technologies. For these two elements, data were taken primarily from the Eurostat fuel statistics and the IIASA GAINS model. Three scenarios have been defined: a “typical” case, which is our best estimate, an alternative “ideal” case which excludes the impact of “bad combustion”, and a “high EF” scenario in which higher emission factors are assumed than in the typical scenario. Total emissions in the typical scenario are around 40% higher than in the ideal case (in 2019), whereas resulting emissions in the “high EF” scenario are around 90% higher than in the typical scenario.
The Ref2_v2.1 inventory was used in a series of modelling studies which aimed to assess the importance of condensable organics for current air quality, for trends over time (2010–2019), and for source-receptor calculations.
Including condensables in a consistent way for all countries gave model results (concentrations, trends and bias) in better agreement with observations for OC and PM2.5 than when using the EMEP emissions which have condensables for some countries but not others. However, the model results were sensitive to the choice of Ref2_v2.1 scenario, and also to the assumptions concerning volatility of the CPOA emissions, and assumptions about extra intermediate-volatility volatile organic compounds (IVOC) associated with such emissions.
No single setup performed best for each site. There are many factors that can contribute to such mixed results (activity data, emissions factors, assumed combustion conditions, large and small scale spatial distributions issues in emissions, dispersion and CPOA/IVOC assumptions in the modelling), and much further work (and with other observational data-sets) will be needed to disentangle the reasons for model-measurement discrepancies, and to draw conclusions on how realistic the new emissions are.
Assumptions about volatility seem to be important for both the country-to-itself contribution, and for impacts of each country on others. In the few cases investigated so far, assuming inert CPOA provides results which generally lie within the range of the more complex VBS scenarios. Given the many uncertainties associated with the emissions and the modelling of POA and SOA, these results indicates that the inert CPOA assumptions provide a reasonable first approach for handling POA emissions, which can hopefully be improved once our understanding of the sources and processing of these compounds improves.
The new emission data-base, combined with increasing availability of measurements of organic and other components, should provide the best available basis for future improvements in both the emission inventories and model formulations. Much analysis and further tests remain, both with the other model setups, and ideally with alternative secondary organic aerosol schemes to get a better idea of the sensitivity of the results to the various assumptions concerning both emissions and atmospheric processing of POA.
Nordic Council of Ministers
2022
2022
2022
The Forum for Air Quality Modelling (FAIRMODE) is a European network to exchange experiences and competences on the use of air quality models in the context of the Ambient Air Quality Directives. Its purpose is to identify and promote the use of good practices for air quality modelling and to propose harmonized ways to assess the quality of model-based air quality applications by EU Member States. The recommendations in this document are part of FAIRMODE’s contribution to the on-going revision of the EU Ambient Air Quality Directives (Directives 2008/50/EC and 2004/107/EC, hereafter AAQDs) initiated by the European Commission and are an update of the previous recommendations to the Fitness check of those Directives (Thunis et al. 2019). This document builds on the existing recommendations from FAIRMODE provided in 2019 regarding modelling applications. The current document has been revised in view of the latest consensus on the maturity of modelling applications and their uses for air quality management purposes. It provides strategic and technical recommendations where there is significant level consensus within the FAIRMODE expert community. It identifies how and where these recommendations may be included in the context of the revision of the AAQDs. These recommendations would require additional work of Member States were they to be implemented and would have implications for the work of the FAIRMODE network concerning the development of relevant guidance documents to support the recommendations.
Publications Office of the European Union
2022
2022
2022
2022
Målinger av SO2 i omgivelsene til Elkem Carbon og REC Solar. Januar 2021 – desember 2021.
På oppdrag fra Elkem Carbon AS har NILU utført målinger av SO2 i omgivelsene til Elkem Carbon og REC Solar i Vågsbygd (Kristiansand kommune). Elkem Carbon har i sin tillatelse fra Miljødirektoratet krav om å gjennomføre kontinuerlig måling av SO2 i omgivelsesluft. Målingene ble utført med SO2-monitor i boligområdet på Fiskåtangen (Konsul Wilds vei). I tillegg har Elkem Carbon AS valgt å måle med passive SO2-prøvetakere ved 3 steder rundt bedriftene. Rapporten dekker målinger i perioden 1. januar – 31. desember 2021. Norske grenseverdier for luftkvalitet (SO2) ble overholdt ved Konsul Wilds vei for alle midlingsperioder krevet i forurensningsforskriften (årsmiddel, vintermiddel, døgnmiddel og timemiddel). De mest belastede stedene i måleperioden var Konsul Wilds vei nordøst og Fiskåveien rett sør for bedriftene. To døgnmidler var over 125 µg/m3 (grenseverdi, 3 tillatt), 16 døgnmidler var over øvre vurderingsterskel (75 µg/m3) og 33 døgnmidler var over nedre vurderingsterskel (50 µg/m3).
NILU
2022
Machine Learning-Based Digital Twin for Predictive Modeling in Wind Turbines
Wind turbines are one of the primary sources of renewable energy, which leads to a sustainable and efficient energy solution. It does not release any carbon emissions to pollute our planet. The wind farms monitoring and power generation prediction is a complex problem due to the unpredictability of wind speed. Consequently, it limits the decision power of the management team to plan the energy consumption in an effective way. Our proposed model solves this challenge by utilizing a 5G-Next Generation-Radio Access Network (5G-NG-RAN) assisted cloud-based digital twins’ framework to virtually monitor wind turbines and form a predictive model to forecast wind speed and predict the generated power. The developed model is based on Microsoft Azure digital twins infrastructure as a 5-dimensional digital twins platform. The predictive modeling is based on a deep learning approach, temporal convolution network (TCN) followed by a non-parametric k-nearest neighbor (kNN) regression. Predictive modeling has two components. First, it processes the univariate time series data of wind to predict its speed. Secondly, it estimates the power generation for each quarter of the year ranges from one week to a whole month (i.e., medium-term prediction) To evaluate the framework the experiments are performed on onshore wind turbines publicly available datasets. The obtained results confirm the applicability of the proposed framework. Furthermore, the comparative analysis with the existing classical prediction models shows that our designed approach obtained better results. The model can assist the management team to monitor the wind farms remotely as well as estimate the power generation in advance.
2022
Health impacts of PM
Residential wood combustion (RWC) is one of the largest sources of fine particles (PM2.5) in the Nordic cities. The current study aims to calculate the related health effects in four studied city areas in Sweden, Finland, Norway, and Denmark.
2022
Background: Positive associations have been reported between persistent organic pollutants (POPs) and type 2 diabetes mellitus (T2DM); however, causality has not been established. Over the last decades, environmental exposure to legacy POPs has decreased, complicating epidemiological studies. In addition, physiological risk factors for T2DM may also influence POP concentrations, contributing to a complex network of factors that could impact associations with T2DM. Longitudinal studies on this topic are lacking, and few have assessed prospective and cross-sectional associations between repeated POP measurements and T2DM in the same individuals, which may shed light on causality.<p> <p>Objectives: To compare longitudinal trends in concentrations of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in T2DM cases and controls, and to examine prospective and cross-sectional associations between PCBs, OCPs and T2DM at different time-points before and after T2DM diagnosis in cases. <p>Methods: We conducted a longitudinal, nested case-control study (1986–2016) of 116 T2DM cases and 139 controls from the Tromsø Study. All participants had three blood samples collected before T2DM diagnosis in cases, and up to two samples thereafter. We used linear mixed-effect models to assess temporal changes of POPs within and between T2DM cases and controls, and logistic regression models to investigate the associations between different POPs and T2DM at different time-points. <p>Results: PCBs, trans-nonachlor, cis-nonachlor, oxychlordane, cis-heptachlor epoxide, p,p’-DDE, and p,p’-DDT declined more slowly in cases than controls, whereas β-HCH and HCB declined similarly in both groups. Most POPs showed positive associations between both pre- and post-diagnostic concentrations and T2DM, though effect estimates were imprecise. These associations were most consistent for cis-heptachlor epoxide. <p>Discussion: The observed positive associations between certain POPs and T2DM may be because of higher POP concentrations within prospective T2DM cases, due to slower temporal declines as compared to controls.
2022
2022
The aim of this project was to collect, integrate and analyse observations of climate-relevant aerosol parameters (aerosol optical depth (AOD), Ångstrøm exponent (AE), black carbon (BC)) in and around Svalbard. These observations have been performed at different places and with different instrument types, the analysis procedures of which follow different protocols. Annual merged datasets of AOD, AE and BC have been provided to the SIOS Data Management System and are now available for network-wide use in, e.g., Arctic climate and pollution studies. The analysis of the 2002-2020 data have confirmed earlier results showing a good correlation between measurements in Ny-Ålesund and Hornsund, but not a high degree of short-term agreement due to aerosol variability arising from geographical locations and local conditions. There is also a clear link between the columnar AOD/AE-measurements and in-situ aerosol measurements at Gruvebadet Observatory, while a comparison of in-situ measurements at Gruvebadet and Zeppelin Observatory shows deviations varying with season.
NILU
2022
Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models.
2022
To cope with the high number of nanomaterials manufactured, it is essential to develop high-throughput methods for in vitro toxicity screening. At the same time, the issue with interference of the nanomaterial (NM) with the read-out or the reagent of the assay needs to be addressed to avoid biased results. Thus, validated label-free methods are urgently needed for hazard identification of NMs to avoid unintended adverse effects on human health. The colony forming efficiency (CFE) assay is a label- and interference-free method for quantification of cytotoxicity by cell survival and colony forming efficiency by CFE formation. The CFE has shown to be compatible with toxicity testing of NMs. Here we present an optimized protocol for a higher-throughput set up.
2022
Grenseområdene Norge-Russland. Luft- og nedbørkvalitet 2021.
Smelteverkene i nordvest-Russland slapp tidligere ut store mengder svoveldioksid (SO2) og tungmetaller. Utslippene påvirket luft- og nedbørkvalitet i grenseområdene. Smelteverket i Nikel stengte ned 23. desember 2020 og lokal luftkvalitet ble betydelig forbedret. Dog er det fortsatt utslipp fra varmekraftverket i Nikel i den kalde årstiden. Detaljer rundt utslippene fra Zapoljarnyj er ikke kjente. Herværende rapport viser resultatene for kalenderåret 2021, det vil si året etter stengningen. Nivåene av forurensning er lave og grenseverdier og målsettingsverdier er overholdt med klar margin.
NILU
2022