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Arctic smoke - record high air pollution levels in the European Arctic due to agricultural fires in Eastern Europe.

Stohl, A.; Berg, T.; Burkhart, J.F.; Fjæraa, A.M.; Forster, C.; Herber, A.; Hov, Ø.; Lunder, C.; McMillan, W.W.; Oltmans, S.; Shiobara, M.; Simpson, D.; Solberg, S.; Stebel, K.; Ström, J.; Tørseth, K.; Treffeisen, R.; Virkkunen, K.; Yttri, K.E.

2007

Arctic springtime depletion of mercury as observed in the European Arctic.

Berg, T.; Sekkesæter, S.; Steinnes, E.; Vandal, A.; Wibetoe, G.

2001

Arctic springtime depletion of mercury increases the input of mercury to the ecosystems.

Berg, T.; Sekkeseter, S.; Steinnes, E.; Valdal, A.; Wibetoe, G.

2002

Arctic transport climatologies for the International Arctic System for Observing the Atmosphere (IASOA) and POLARCAT.

Burkhart, J.F.; John, B.F.; Stohl, A.; Eckhardt, S.; Uttal, T.; Ocko, I.; Tørseth, K.

2007

Arctic Tropospheric Ozone Trends

Law, Kathy S.; Hjorth, Jens Liengaard; Pernov, Jakob B.; Whaley, Cynthia; Skov, Henrik; Coen, Martine Collaud; Langner, Joakim; Arnold, Stephen R.; Tarasick, David; Christensen, Jesper; Deushi, Makoto; Effertz, Peter; Faluvegi, Greg; Gauss, Michael; Im, Ulas; Oshima, Naga; Petropavlovskikh, Irina; Plummer, David; Tsigaridis, Kostas; Tsyro, Svetlana; Solberg, Sverre; Turnock, Stephen

Observed trends in tropospheric ozone, an important air pollutant and short-lived climate forcer (SLCF), are estimated using available surface and ozonesonde profile data for 1993–2019, using a coherent methodology, and compared to modeled trends (1995–2015) from the Arctic Monitoring Assessment Program SLCF 2021 assessment. Increases in observed surface ozone at Arctic coastal sites, notably during winter, and concurrent decreasing trends in surface carbon monoxide, are generally captured by multi-model median trends. Wintertime increases are also estimated in the free troposphere at most Arctic sites, with decreases during spring months. Winter trends tend to be overestimated by the multi-model medians. Springtime surface ozone increases in northern coastal Alaska are not simulated while negative springtime trends in northern Scandinavia are not always reproduced. Possible reasons for observed changes and model performance are discussed including decreasing precursor emissions, changing ozone dry deposition, and variability in large-scale meteorology.

American Geophysical Union (AGU)

2023

Arctic tropospheric ozone: assessment of current knowledge and model performance

Whaley, Cynthia; Law, Kathy S.; Hjorth, Jens Liengaard; Skov, Henrik; Arnold, Stephen R.; Langner, Joakim; Pernov, Jakob Boyd; Bergeron, Garance; Bourgeois, Ilann; Christensen, Jesper H.; Chien, Rong-You; Deushi, Makoto; Dong, Xinyi; Effertz, Peter; Faluvegi, Gregory; Flanner, Mark G.; Fu, Joshua S.; Gauss, Michael; Huey, Greg L.; Im, Ulas; Kivi, Rigel; Marelle, Louis; Onishi, Tatsuo; Oshima, Naga; Petropavlovskikh, Irina; Peischl, Jeff; Plummer, David A.; Pozzoli, Luca; Raut, Jean-Christophe; Ryerson, Tom; Skeie, Ragnhild Bieltvedt; Solberg, Sverre; Thomas, Manu Anna; Thompson, Chelsea R.; Tsigaridis, Kostas; Tsyro, Svetlana; Turnock, Steven T.; von Salzen, Knut; Tarasick, David

As the third most important greenhouse gas (GHG) after carbon dioxide (CO2) and methane (CH4), tropospheric ozone (O3) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O3 depletion in the springtime; however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been previously reported, and we show that there continues to be no convergence among models or improved accuracy in simulating tropospheric O3 and its precursor species. The MMM underestimates Arctic surface O3 by 5 % to 15 % depending on the location. The vertical distribution of tropospheric O3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O3 within a range of ±50 % depending on the model and the altitude. The MMM performs best, within ±8 % for most locations and seasons. However, nearly all models overestimate O3 near the tropopause (∼300 hPa or ∼8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O3 at high latitudes. For example, the MMM is biased high by about 20 % at Eureka. Observed and simulated O3 precursors (CO, NOx, and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NOx but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O3 matches the observed O3 reasonably well. Our findings suggest that despite model updates over the last decade, model results are as highly variable as ever and have not increased in accuracy for representing Arctic tropospheric O3.

2023

Arctic winter 2005: Implications for stratospheric ozone loss and climate change.

Rex, M.; Salawitch, R.J.; Deckelmann, H.; von der Gathen, P.; Harris, N.R.P.; Chipperfield, M.P.; Naujokat, B.; Reimer, E.; Allaart, M.; Andersen, S.B.; Bevilacqua, R.; Braathen, G.O.; Claude, H.; Davis, J.; De Backer, H.; Dier, H.; Dorokhov, V.; Fast, H.; Gerding, M.; Godin-Beekmann, S.; Hoppel, K.; Johnson, B.; Kyrö, E.; Litynska, Z.; Moore, D.; Nakane, H.; Parrondo, M.C.; Risley, A.D.; Skrivankova, P.; Stübi, R.; Viatte, P.; Yushkov, V.; Zerefos, C.

2006

Are Fluoropolymers Really of Low Concern for Human and Environmental Health and Separate from Other PFAS?

Lohmann, Rainer; Cousins, Ian T.; DeWitt, Jamie; Glüge, Juliane; Goldenman, Gretta; Herzke, Dorte; Lindstrom, Andrew B.; Miller, Mark F.; Ng, Carla A.; Patton, Sharyle; Scheringer, Martin; Trier, Xenia; Wang, Zhanyun

2020

Are Ingredients of Personal Care Products Likely to Undergo Long Range Transport to Remote Regions?

D'Amico, Marianna; Frank, Wania; Breivik, Knut; Gambaro, Andrea; Vecchiato, Marco

2023

Are ingredients of personal care products likely to undergo long-range transport to remote regions?

D'Amico, Marianna; Wania, Frank; Breivik, Knut; Skov, Henrik; Spolaor, Andrea; Sørensen, Lise Lotte; Gambaro, Andrea; Vecchiato, Marco

Personal care products (PCPs) contain contaminants of emerging concern. Despite increasing reports of their presence in polar regions, the behavior of PCP ingredients under cold environmental conditions remains poorly understood. Snow collected around Villum Research Station at Station Nord, Greenland, between December 2018 and June 2019 was extracted in a stainless steel clean-room and analyzed for seven fragrance materials, four organic UV-filters and an antioxidant using gas chromatography-tandem mass spectrometry. All twelve target PCPs were detected, with elevated concentrations during two sampling events potentially tied to air mass transport from northern Europe and the northern coasts of Russia. To contextualize the presence of these PCP chemicals in high Arctic snow, we estimated their (i) partitioning properties as a function of temperature, (ii) equilibrium phase distribution and dominant deposition processes in the atmosphere at temperatures above and below freezing, and (iii) potential for long-range environmental transport (LRET). Even though most PCPs are deemed to be gas phase chemicals predominantly deposited as vapors, rapid atmospheric degradation is expected to limit their LRET. On the other hand, the less volatile octocrylene is expected to be sorbed to atmospheric particles, removed via wet and dry particle deposition, and possibly exhibit a higher potential for LRET by being protected from attack by photooxidants. The contrast between consistent detection of PCP chemicals in high Arctic snow and relatively low estimated LRET potential emphasizes the need for further research on their real-world atmospheric behavior under cold conditions.

Royal Society of Chemistry (RSC)

2025

Are parents driving air pollution at schools?

Grythe, Henrik; Sousa Santos, Gabriela; Castell, Nuria

2024

Are poly(anhydride) nanoparticles really safe?

Alonso, T. I.; El Yamani, N.; Dusinska, M.; Salsamendi, A. L.; Oscoz, A. A.

2016

Are poly(anhydride) nanoparticles really safe?

Alonso, T.I.; El Yamani, N.; Dusinska, M.; Salsamendi, A.L.; Oscoz, A.A.

2016

Are Sterols Useful for the Identification of Sources of Faecal Contamination in Shellfish? A Case Study.

Florini, Styliano; Shahsavari, Esmaeil; Aburto-Medina, Arturo; Khudur, Leadin S.; Mudge, Stephen Michael; Smith, David J.; Ball, Andrew S.

This work aimed to identify the major source(s) of faecal pollution impacting Salcott Creek oyster fisheries in the UK through the examination of the sterol profiles. The concentration of the major sewage biomarker, coprostanol, in water overlying the oysters varied between 0.01 µg L−1 and 1.20 µg L−1. The coprostanol/epicoprostanol ratio ranged from 1.32 (September) to 33.25 (February), suggesting that human sewage represents the key input of faecal material into the estuary. However, a correlation between the sterol profile of water above the oysters with that of water that enters from Tiptree Sewage Treatment Works (r = 0.82), and a sample from a site (Quinces Corner) observed to have a high population of Brent geese (r = 0.82), suggests that both sources contribute to the faecal pollution affecting the oysters. In identifying these key faecal inputs, sterol profiling has allowed targeted management practices to be employed to ensure that oyster quality is optimised.

MDPI

2020

Arealutslipp for Oslo. NILU OR

Sundvor, I.

Arelautslippene som benyttes for spredningsberegninger for Oslo er gjennomgått og endret utifra trender og ny tilgjengelig informasjon. Som resultat ble det flere kildekategorier enn tidligere og totalutslippet har økt.

2014

Arktis brenner! Hvordan kanadiske skogbranner påvirker oss alle.

Stebel, Kerstin; Eckhardt, Sabine; Evangeliou, Nikolaos; Schneider, Philipp

2023

Artificial cloud test confirms volcanic ash detection using infrared spectral imaging.

Prata, A.J.; Dezitter, F.; Davies, I.; Weber, K.; Birnfeld, M.; Moriano, D.; Bernardo, C.; Vogel, A.; Prata, G.S.; Mather, T.A.; Thomas, H.E.; Cammas, J.; Weber, M.

2016

Artificial intelligence models for calibration of low-cost electrochemical sensors in high-density air pollution monitoring networks.

Topalovic, D.B.; Ristovski, Z.; Bartonova, A.; Castell, N.; Davidovic, M.; Jovaševic-Stojanovic, M.

2016

Artificial intelligence models with multivariate inputs for calibration of low cost PM sensors.

Topalovic, D. B.; Davidovic, M.; Bartonova, A.; Jovaševic-Stojanovic, M.

2017

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