Fant 10278 publikasjoner. Viser side 291 av 412:
Denne artikkelen presenter identifisering og kvantifisering av giftige forbindelser (nitrosaminer og nitraminer) som dannes som følge av den luftkjemiske degradering av to aminer (Amin-1 og Amin-2). Disse aminer blir brukt for karbonfangst. Eksperimenter ble gjenommført under forskjellige NOx blandingsforhold i det solbelyste kammer ved 'European Photochemical Reactor' EUPHORE i Valencia (Spania). Når man tar i betraktning usikkerheten i de to anvendte nitramine målemetoder, er produktutbytte av Amin-1-nitramine for lav-NOx forhold typiske for Mongstad anslått å variere fra 1.4% til 4.1%. Kandidaten for den første generasjonen nitrosamine dannet i foto-oksidasjon av Amin-1 (Amin-1-nitrosamine kandidat) ble identifisert ved analyse av Thermosorb/N prøvene i Amin-1 produktutbytte eksperimenter.
2013
2011
The report presents the results from the model simulations, performed with the air quality modelling system AirQUIS for the Khalifa Port and Industrial Zone (KPIZ). The report presents the air quality model simulation based on the existing emission and predicted emission scenarios for the KPIZ. The model simulations are also carried out for baseline scenarios in 2010 and future scenarios in 2020 and 2030.
2011
2007
2003
2004
Phthalate contamination in marine mammals off the Norwegian coast
Phthalates are used in plastics, found throughout the marine environment and have the potential to cause adverse health effects. In the present study, we quantified blubber concentrations of 11 phthalates in 16 samples from stranded and/or free-living marine mammals from the Norwegian coast: the killer whale (Orcinus orca), sperm whale (Physeter macrocephalus), long-finned pilot whale (Globicephala melas), white-beaked dolphin (Lagenorhynchus albirostris), harbour porpoise (Phocoena phocoena), and harbour seal (Phoca vitulina). Five compounds were detected across all samples: benzyl butyl phthalate (BBP; in 50 % of samples), bis(2-ethylhexyl) phthalate (DEHP; 33 %), diisononyl phthalate (DiNP; 33 %), diisobutyl phthalate (DiBP; 19 %), and dioctyl phthalate (DOP; 13 %). Overall, the most contaminated individual was the white-beaked dolphin, whilst the lowest concentrations were measured in the killer whale, sperm whale and long-finned pilot whale. We found no phthalates in the neonate killer whale. The present study is important for future monitoring and management of these toxic compounds.
2023
2007
2009
2023
2011
2012
Physical controls of dynamics of methane venting from a shallow seep area west of Svalbard
We investigate methane seepage on the shallow shelf west of Svalbard during three consecutive years, using discrete sampling of the water column, echosounder-based gas flux estimates, water mass properties, and numerical dispersion modelling. The results reveal three distinct hydrographic conditions in spring and summer, showing that the methane content in the water column is controlled by a combination of free gas seepage intensity and lateral water mass movements, which disperse and displace dissolved methane horizontally away from the seeps. Horizontal dispersion and displacement of dissolved methane are promoted by eddies originating from the West Spitsbergen Current and passing over the shallow shelf, a process that is more intense in winter and spring than in the summer season. Most of the methane injected from seafloor seeps resides in the bottom layer even when the water column is well mixed, implying that the controlling effect of water column stratification on vertical methane transport is small. Only small concentrations of methane are found in surface waters, and thus the escape of methane into the atmosphere above the site of seepage is also small. The magnitude of the sea to air methane flux is controlled by wind speed, rather than by the concentration of dissolved methane in the surface ocean.
2019
1999
2003
2006
2006
Physics-Informed Deep Learning for Wind Downscaling over Oslo
Running a numerical weather model such as WRF at kilometre or sub-kilometre grid spacing over a regional domain is computationally expensive. We present physics-informed deeplearning models that ingest a single 9km WRF wind field and simultaneously predict two finer-scale wind fields at 3 km and 1 km resolution via dual decoder heads. Four representative architectures are benchmarked-Deep Residual U-Net (DeepRU), DEVINE, a bespoke 3-D Transformer, and a Fourier Neural Operator (FNO)-each trained with divergence-free, vorticity, and Navier-Stokes residual constraints plus Charbonnier and gradient perceptual losses. We train and validate our models on the city of Oslo for the year 2018. DeepRU achieves R2=0.94 (RMSE =0.050) at 3km and R2=0.89(RMSE=0.065) at 1 km. DEVINE, Transformer 3-D, and FNO yield 3 km scores of 0.91−0.93, with 1km scores lower by 0.02−0.08, illustrating the increased difficulty of finer-scale reconstruction. Physicsinformed losses improve all models compared to MSE-only baselines, and the residual architecture (DeepRU) remains most effective for this dual-scale task.
2025
2011
2012
2015
PikMe: a flexible prioritization tool for chemicals of emerging concern
Identifying new contaminants of emerging concern remains a complex task due to the sheer number of chemical substances potentially released into the environment, the scattered sources of information, and often the lack of adequate data. Environmental screening and monitoring programs are designed to map the presence, sources, and potential environmental impacts of contaminants, yet prioritizing which chemicals to include in such efforts remains resource-intensive and technically challenging. PikMe is a modular, open-access prioritization tool that integrates information from major data bases and evaluates the concern and reliability of the data for more than one million substances. PikMe is built in a modular way so that prioritization can be done based on specific chemical properties relevant to a given scenario (i.e., drinking water contaminants or bioaccumulation in biota) rather than assigning only a global risk score. PikMe scores substances based on persistence, bioaccumulation, mobility, environmental toxicity, and human toxicity, assigning individual score per property. Additionally, PikMe is designed for flexibility by allowing the integration of external lists of chemicals and supporting optional add-ons. Different scenarios of use are described in this article, including the selection of chemicals for environmental monitoring and screening in Norway and the assessment of the implications of the new classifications according to the regulation for classification, labelling and packaging of substances and mixtures on persistent chemicals.
2025