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Fant 10464 publikasjoner. Viser side 404 av 419:

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Advances in our understanding of nanomaterial carcinogenicity.

Dusinska, M.; Gabelova, A.; El Yamani, N.; Fjellsbø, L. M.; Silva, M.J.; Rundén-Pran, E.

2016

Advances in assessing the quality of Sentinel-5P TROPOMI cloud products and their reprocessings using Cloudnet and ARM network data

Compernolle, Steven; Argyrouli, Athina; Lutz, Ronny; Sneep, Maarten; Lambert, Jean-Christopher; Fjæraa, Ann Mari; Granville, José; Hubert, Daan; Keppens, Arno; Loyola, Diego; O’Connor, Ewan; Pinardi, Gaia; Rasson, Olivier; Romahn, Fabian; Stammes, Piet; Verhoelst, Tijl; Wang, Ping

2024

Advanced Respiratory Models for Hazard Assessment of Nanomaterials—Performance of Mono-, Co- and Tricultures

Camassa, Laura Maria Azzurra; Elje, Elisabeth; Mariussen, Espen; Longhin, Eleonora Marta; Dusinska, Maria; Zienolddiny-Narui, Shanbeh; Rundén-Pran, Elise

Advanced in vitro models are needed to support next-generation risk assessment (NGRA), moving from hazard assessment based mainly on animal studies to the application of new alternative methods (NAMs). Advanced models must be tested for hazard assessment of nanomaterials (NMs). The aim of this study was to perform an interlaboratory trial across two laboratories to test the robustness of and optimize a 3D lung model of human epithelial A549 cells cultivated at the air–liquid interface (ALI). Potential change in sensitivity in hazard identification when adding complexity, going from monocultures to co- and tricultures, was tested by including human endothelial cells EA.hy926 and differentiated monocytes dTHP-1. All models were exposed to NM-300K in an aerosol exposure system (VITROCELL® cloud-chamber). Cyto- and genotoxicity were measured by AlamarBlue and comet assay. Cellular uptake was investigated with transmission electron microscopy. The models were characterized by confocal microscopy and barrier function tested. We demonstrated that this advanced lung model is applicable for hazard assessment of NMs. The results point to a change in sensitivity of the model by adding complexity and to the importance of detailed protocols for robustness and reproducibility of advanced in vitro models

2022

Advanced biological models in vitro for hazard assessment of nanomaterials on human health

Camassa, Laura Maria Azzurra; Sadeghiankaffash, Hamed; Zheng, Congying; Ervik, Torunn Kringlen; Anmarkrud, Kristine Haugen; Elje, Elisabeth; Shaposhnikov, Sergey; Rundén-Pran, Elise; Zienolddiny-Narui, Shan

2023

Addressing Urgent Questions for PFAS in the 21st Century

Ng, Carla; Cousins, Ian T.; Dewitt, Jamie C.; Glüge, Juliane; Goldenman, Gretta; Herzke, Dorte; Lohmann, Rainer; Miller, Mark; Patton, Sharyle; Scheringer, Martin; Trier, Xenia; Wang, Zhanyun

2021

Addressing the advantages and limitations of using Aethalometer data to determine the optimal absorption Ångström exponents (AAEs) values for eBC source apportionment

Savadkoohi, Marjan; Gerras, Mohamed; Favez, Olivier; Petit, Jean-Eudes; Rovira, Jordi; Chen, Gang I.; Via, Marta; Platt, Stephen Matthew; Aurela, Minna; Chazeau, Benjamin; Brito, Joel F. De; Riffault, Véronique; Eleftheriadis, Kostas; Flentje, Harald; Gysel-Beer, Martin; Hueglin, Christoph; Rigler, Martin; Gregorič, Asta; Ivančič, Matic; Keernik, Hannes; Maasikmets, Marek; Liakakou, Eleni; Stavroulas, Iasonas; Luoma, Krista; Marchand, Nicolas; Mihalopoulos, Nikos; Petäjä, Tuukka; Prévôt, André S.H.; Daellenbach, Kaspar R.; Vodička, Petr; Timonen, Hilkka; Tobler, Anna; Vasilescu, Jeni; Dandocsi, Andrei; Mbengue, Saliou; Vratolis, Stergios; Zografou, Olga; Chauvigné, Aurélien; Hopke, Philip K.; Querol, Xavier; Alastuey, Andrés; Pandolfi, Marco

The apportionment of equivalent black carbon (eBC) to combustion sources from liquid fuels (mainly fossil; eBCLF) and solid fuels (mainly non-fossil; eBCSF) is commonly performed using data from Aethalometer instruments (AE approach). This study evaluates the feasibility of using AE data to determine the absorption Ångström exponents (AAEs) for liquid fuels (AAELF) and solid fuels (AAESF), which are fundamental parameters in the AE approach. AAEs were derived from Aethalometer data as the fit in a logarithmic space of the six absorption coefficients (470–950 nm) versus the corresponding wavelengths. The findings indicate that AAELF can be robustly determined as the 1st percentile (PC1) of AAE values from fits with R2 > 0.99. This R2-filtering was necessary to remove extremely low and noisy-driven AAE values commonly observed under clean atmospheric conditions (i.e., low absorption coefficients). Conversely, AAESF can be obtained from the 99th percentile (PC99) of unfiltered AAE values. To optimize the signal from solid fuel sources, winter data should be used to calculate PC99, whereas summer data should be employed for calculating PC1 to maximize the signal from liquid fuel sources. The derived PC1 (AAELF) and PC99 (AAESF) values ranged from 0.79 to 1.08, and 1.45 to 1.84, respectively. The AAESF values were further compared with those constrained using the signal at mass-to-charge 60 (m/z 60), a tracer for fresh biomass combustion, measured using aerosol chemical speciation monitor (ACSM) and aerosol mass spectrometry (AMS) instruments deployed at 16 sites. Overall, the AAESF values obtained from the two methods showed strong agreement, with a coefficient of determination (R2) of 0.78. However, uncertainties in both approaches may vary due to site-specific sources, and in certain environments, such as traffic-dominated sites, neither approach may be fully applicable.

2025

Addressing pan-Arctic black carbon through the collective measurements of the IASOA observatories. NILU F

Burkhart, J.F.; Sharma, S.; Ogren, J.A.; Starkweather, S.; Bergin, M.H.; Eleftheriadis, K.; Lihavainen, H.; Fiebig, M.

2013

Addressing emissions of pm from wood burning using levoglucosan. NILU F

Yttri, K.E.; Dye, C.; Forster, C.

2005

Addressing black carbon driven albedo variability in the Arctic: VAUUAV. NILU F

Burkhart, J.F.; Storvold, R.; Pedersen, C.; Bogren, W.; Bates, T.; Quinn, P.

2010

Addendum to "A global assessment of precipitation chemistry and deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus".

Vet, R.; Artz, R.S.; Carou, S.; Shaw, M.; Ro, C.-U.; Aas, W.; Baker, A.; Bowersox, V.C.; Dentener, F.; Galy-Lacaux, C.; Hou, A.; Pienaar, J.J.; Gillett, R.; Forti, M.C.; Gromov, S.; Hara, H.; Khodzher, T.; Mahowald, N.M, Nickovic, S.; Rao, P.S.P.; Reid, N.W.

2014

Added value of the emissions fractions approach when assessing a chemical's potential for adverse effects as a result of long-range transport

Breivik, Knut; McLachlan, Michael S.; Wania, Frank

It is of considerable interest to identify chemicals which may represent a hazard and risk to environmental and human health in remote areas. The OECD POV and LRTP Screening Tool (“The Tool”) for assessing chemicals for persistence (P) and long-range transport potential (LRTP) has been extensively used for combined P and LRTP assessments in various regulatory contexts, including the Stockholm Convention (SC) on Persistent Organic Pollutants (POPs). The approach in The Tool plots either the Characteristic Travel Distance (CTD, in km), a transport-oriented metric, or the Transfer Efficiency (TE, in %), which calculates the transfer from the atmosphere to surface compartments in a remote region, against overall persistence (POV). For a chemical to elicit adverse effects in remote areas, it not only needs to be transported and transferred to remote environmental surface media, it also needs to accumulate in these media. The current version of The Tool does not have a metric to quantify this process. We screened a list of >12 000 high production volume chemicals (HPVs) for the potential to be dispersed, transferred, and accumulate in surface media in remote regions using the three corresponding LRTP metrics of the emission fractions approach (EFA; ϕ1, ϕ2, ϕ3), as implemented in a modified version of The Tool. Comparing the outcome of an assessment based on CTD/TE and POV with the EFA, we find that the latter classifies a larger number of HPVs as having the potential for accumulation in remote regions than is classified as POP-like by the existing approach. In particular, the EFA identifies chemicals capable of accumulating in remote regions without fulfilling the criterion for POV. The remote accumulation fraction of the EFA is the LRTP assessment metric most suited for the risk assessment stage in Annex E of the SC. Using simpler metrics (such as half-life criteria, POV, and LRTP–POV combinations) in a hazard-based assessment according to Annex D is problematic as it may prematurely screen out many of the chemicals with potential for adverse effects as a result of long-range transport.

2023

Added value of a geostationary thermal infrared and visible instrument to monitor ozone for air quality.

Hache, E.; Attié, J.-L.; Tourneur, C.; Ricaud, P.; Coret, L.; Lahoz, W.; El Amraoui, L.; Josse, B.; Hamer, P.; Warner, J.; Liu, X.; Chance, K.; Höpfner, M.; Spurr, R.; Natraj, V.; Kulawik, S.; Eldering, A.; Orphal, J.

2014

Adapting to urban challenges in the Amazon: flood risk and infrastructure deficiencies in Belém, Brazil

Mansur, Andressa V.; Brondizio, Eduardo S.; Roy, Samapriya; Soares, Pedro Paulo de Miranda Araújo; Newton, Alice

2018

Actris, Earlinet, and Cloudnet Cal/Val Contribution to Earthcare Mission

Marinou, Eleni; Baars, Holger; Mona, Lucia; O’Connor, Ewan; Rusli, Stephanie; Koopman, Rob; Fjæraa, Ann Mari; Nicolae, Doina

2024

ACTRIS Virtual Research Environment – Examples of use and collaboration within ACTRIS-Norway and the ACTRIS Data Centre 

Murberg, Lise Eder; Myhre, Cathrine Lund; Fiebig, Markus; Evangeliou, Nikolaos; Schulz, Michael; Stjern, Camilla Weum; Dema, Claudio; Tukiainen, Simo

The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) is the European Research Infrastructure Consortium (ERIC) dedicated to short-lived atmospheric constituents and clouds, supporting fundamental research and excellence in Earth system observation. ACTRIS produces high-quality, integrated long-term datasets in the field of atmospheric sciences and provides services tailored for scientific and technological use, including access to instrumented observational platforms. To enhance the availability, usability, and scientific exploitation of these datasets across disciplines and user communities, the ACTRIS Data Centre (DC) develops a range of user-oriented services, among which the ACTRIS Virtual Research Environment (VRE) plays a central role. The ACTRIS VRE enables efficient discovery, access, and scientific analysis of long-term observational data from ACTRIS National Facilities as well as other ground based observational sites as e.g. EMEP, EARLINET, Cloudnet and GAW. It facilitates analyses such as calculation of climatologies, long-term trend assessments, and the combination of datasets within the ACTRIS domain. The VRE is developed in collaboration between the ACTRIS DC and the ACTRIS-Norway community and is designed to serve both data producers and data users, ranging from infrastructure operators to researchers and students, across a wide range of atmospheric research applications. This presentation demonstrates the use of the ACTRIS VRE through selected notebook-based examples of higher-level data analysis and highlights the collaborative scientific efforts underlying its development. Data access within the VRE is based on the ACTRIS metadata REST API. ACTRIS datasets are provided in CF-compliant NetCDF format and are accessible through both streaming services (OPeNDAP) and direct HTTPS download. This approach enables flexible, reproducible, and programmatic data use, supporting interoperability with commonly used analysis tools and workflows. In collaboration with the ACTRIS-Norway community, the VRE includes several examples combining datasets for long time series analysis, the exploration of climatologies, and the investigation of trends. Selected examples are presented and discussed, with particular focus on the combination of FLEXPART footprint products and black carbon source apportionment data, developed within the EU project ATMO-ACCESS, together with observed equivalent black carbon measurements at several ACTRIS National Facilities. Additional higher-level analysis examples include single scattering albedo (SSA), ultrafine particle number concentrations (UFPs), and PM₁ source-related metrics from wood burning and traffic. These examples highlight how ACTRIS data can be applied to both climate-relevant and air-quality-focused research questions. Beyond scientific analysis, the ACTRIS VRE also serves as a platform for education and capacity building. Introductory notebooks demonstrate programmatic access to data and metadata and illustrate best practices for scientific analysis. The VRE has been used in ACTRIS training courses, ACTRIS Week, ITINERIS training workshops, and dedicated events at NILU, including collaborations with EUMETSAT, highlighting its role as a reusable training and demonstration environment. Community contributions to the example library are encouraged through an open GitHub repository, fostering collaborative development and reuse. The ACTRIS Virtual Research Environment is openly accessible at https://data.actris.eu/vre.

2026

ACTRIS Perspectives on EOSC-NODE

Fiebig, Markus; Myhre, Cathrine Lund

2024

ACTRIS non-methane hydrocarbon intercomparison experiment in Europe to support WMO-GAW and EMEP observation networks.

Hoerger, C. C.; Claude, A.; Plass-Duelmer, C.; Reimann, S.; Eckart, E.; Steinbrecher, R.; Aalto, J.; Arduini, J.; Bonnaire, N.; Cape, J. N.; Colomb, A.; Connolly, R.; Diskova, J.; Dumitrean, P.; Ehlers, C.; Gros, V.; Hakola, H.; Hill, M.; Hopkins, J. R.; Jäger, J.; Junek, R.; Kajos, M. K.; Klemp, D.; Leuchner, M.; Lewis, A. C.; Locoge, N.; Maione, M.; Martin, D.; Michl, K.; Nemitz, E.; O'Doherty, S.; Pérez Ballesta, P.; Ruuskanen, T. M.; Sauvage, S.; Schmidbauer, N.; Spain, T. G.; Straube, E.; Vana, M.; Vollmer, M. K.; Wegener, R.; Wenger, A.

2015

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