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Fant 9831 publikasjoner. Viser side 380 av 394:

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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; De Brito, Joel F.; 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.

Elsevier

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.

Royal Society of Chemistry (RSC)

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 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

ACTRIS kickoff: Use of data

Evangeliou, Nikolaos

2022

ACTRIS intercomparison experiment of volatile organic compounds in Europe. NILU F

Hoerger, C.C.; Werner, A.; Plass-Duelmer, C.; Reimann, S.; Eckart, E.; Steinbrecher, R.; 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.; Leuchner, M.; Lewis, A.C.; Maione, M.; Martin, D.; Michl, K.; Nemitz, E.; O'Doherty, S.; Sauvage, S.; Schmidbauer, N.; Spain, T.G.; Straube, E.; Vana, M.; Vollmer, M.K.; Wegener, R.; Wenger, A.

2014

ACTRIS Data Portal

Rud, Richard Olav

2023

ACTRIS Data Management Plan

Myhre, Cathrine Lund

2019

ACTRIS Data Centre.

Myhre, C. L.; Mona, L.; O'Connor, E.; Descloitres, J.; Fjæraa, A. M.; Fiebig, M.; Amato, F.; D'Amico, G.

2017

ACTRIS Data Centre: Recent implementation and future developments

Myhre, Cathrine Lund; Fiebig, Markus; Rud, Richard Olav; Mona, Lucia; Dema, Claudio; Pascal, Nicolas; Henry, Patrice; Picquet-Varrault, Bénédicte; Brissebrat, Guillaume; Boonne, Cathy; O’Connor, Ewan; Tukiainen, Simo

2023

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