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There are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal-to-seasonal prediction models can have significant benefits. There is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics. However, there is a lack of results providing a direct mapping between infrasound recordings and polar-cap upper stratospheric winds. The global International Monitoring System (IMS), which monitors compliance with the Comprehensive Nuclear-Test-Ban Treaty, includes ground-based stations that can be used to characterize the infrasound soundscape continuously. In this study, multi-station IMS infrasound data were utilized along with a machine-learning supported stochastic model, Delay-SDE-net, to demonstrate how a near-real-time estimate of the polar-cap averaged zonal wind at 1-hPa pressure level can be found from infrasound data. The infrasound was filtered to a temporal low-frequency regime dominated by microbaroms, which are ambient-noise infrasonic waves continuously radiated into the atmosphere from nonlinear interaction between counter-propagating ocean surface waves. Delay-SDE-net was trained on 5 years (2014–2018) of infrasound data from three stations and the ERA5 reanalysis 1-hPa polar-cap averaged zonal wind. Using infrasound in 2019–2020 for validation, we demonstrate a prediction of the polar-cap averaged zonal wind, with an error standard deviation of around 12 m·s compared with ERA5. These findings highlight the potential of using infrasound data for near-real-time measurements of upper stratospheric dynamics. A long-term goal is to improve high-top atmospheric model accuracy, which can have significant implications for weather and climate prediction.
John Wiley & Sons
2024
The extreme persistence and environmental mobility of per- and polyfluoroalkyl substances (PFAS) make their presence ubiquitous in the marine environment. Target analysis of 20 most common PFAS revealed the presence of nine perfluoroalkyl acids at low levels in surface sediments from five Norwegian marine areas covering the vast region from the eastern North Sea in the south to the Arctic Ocean north of Svalbard in the north. After correcting for sediment characteristics, no substantial difference in the sum of the nine PFAS (Σ9PFAS) between the five areas was found. Among separate compounds, PFOS, PFOA and PFNA dominate sample composition. Only two compounds, PFOS and PFUnDA, showed a statistically significant difference for one of the areas, the levels of these compounds being somewhat higher in the southernmost area than in the other areas. This may be due to local inputs in the fjords in this area. Open-sea and coastal sediments of the North-east Atlantic outside of locations with significant local sources seem to share a common, anthropogenic “PFAS background”, which may be part of a larger, global pattern.
Elsevier
2024
Background
Prioritisation of chemical pollutants is a major challenge for environmental managers and decision-makers alike, which is essential to help focus the limited resources available for monitoring and mitigation actions on the most relevant chemicals. This study extends the original NORMAN prioritisation scheme beyond target chemicals, presenting the integration of semi-quantitative data from retrospective suspect screening and expansion of existing exposure and risk indicators. The scheme utilises data retrieved automatically from the NORMAN Database System (NDS), including candidate substances for prioritisation, target and suspect screening data, ecotoxicological effect data, physico-chemical data and other properties. Two complementary workflows using target and suspect screening monitoring data are applied to first group the substances into six action categories and then rank the substances using exposure, hazard and risk indicators. The results from the ‘target’ and ‘suspect screening’ workflows can then be combined as multiple lines of evidence to support decision-making on regulatory and research actions.
Results
As a proof-of-concept, the new scheme was applied to a combined dataset of target and suspect screening data. To this end, > 65,000 substances on the NDS, of which 2579 substances supported by target wastewater monitoring data, were retrospectively screened in 84 effluent wastewater samples, totalling > 11 million data points. The final prioritisation results identified 677 substances as high priority for further actions, 7455 as medium priority and 326 with potentially lower priority for actions. Among the remaining substances, ca. 37,000 substances should be considered of medium priority with uncertainty, while it was not possible to conclude for 19,000 substances due to insufficient information from target monitoring and uncertainty in the identification from suspect screening. A high degree of agreement was observed between the categories assigned via target analysis and suspect screening-based prioritisation. Suspect screening was a valuable complementary approach to target analysis, helping to prioritise thousands of substances that are insufficiently investigated in current monitoring programmes.
Conclusions
This updated prioritisation workflow responds to the increasing use of suspect screening techniques. It can be adapted to different environmental compartments and can support regulatory obligations, including the identification of specific pollutants in river basins and the marine environments, as well as the confirmation of environmental occurrence levels predicted by modelling tools.
Springer
2024
Monitoring of environmental contaminants in freshwater food webs (MILFERSK), 2023
Norsk institutt for vannforskning
2024
The FAIR principles as a key enabler to operationalize safe and sustainable by design approaches
Safe and sustainable development of chemicals, (advanced) materials, and products is at the heart of achieving a healthy future environment in line with the European Green Deal and the Chemicals Strategy for Sustainability. Recently, the Joint Research Center (JRC) of the European Commission (EC) developed the safe and sustainable by design (SSbD) framework for definition of criteria and evaluation procedure proposed to be established in Research and Innovation (R&I) activities. The framework aims to support the design of chemicals, materials and products that provide desirable functions (or services), while simultaneously minimizing the risk for harmful impacts to human health and the environment. While many industrial sectors already consider such aspects during R&I, the framework aims to harmonize safety and sustainability assessment across diverse sectors and innovation strategies to meet the mentioned overarching policy goals. A cornerstone to successfully implement and operationalize the SSbD framework lies in the availability of high-quality data and tools, and their interoperability, aspects which also play a key role in ensuring transparency and thereby trust in the assessment outcomes. Availability of data and tools depend on their machine-actionability in terms of findability, accessibility, interoperability, and reusability, in line with the FAIR principles. The principles were developed in order to harmonize digitalization across all data domains, supporting unanticipated data-driven “seamless” integration of information and generation of new knowledge. Here we discuss the essentiality of FAIR data and tools to operationalize SSbD providing views and examples of activities within the European Partnership for the Assessment of Risks from Chemicals (PARC). The discussion covers five areas previously brought up in relation to the SSbD framework, and which are highly dependent on implementation of the FAIR principles; (i) digitalization to leverage innovation towards a green transition; (ii) existing data sources and their interoperability; (iii) navigating SSbD with data from new scientific developments (iv) transparency and trust through automated assessment of data quality and uncertainty; and (v) “seamless” integration of SSbD tools.
Royal Society of Chemistry (RSC)
2024
Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present-day greenhouse gas (GHG) budgets. We compare bottom-up (data-driven upscaling and process-based models) and top-down (atmospheric inversion models) budgets of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom-up approaches estimate higher land-to-atmosphere fluxes for all GHGs. Both bottom-up and top-down approaches show a sink of CO2 in natural ecosystems (bottom-up: −29 (−709, 455), top-down: −587 (−862, −312) Tg CO2-C yr−1) and sources of CH4 (bottom-up: 38 (22, 53), top-down: 15 (11, 18) Tg CH4-C yr−1) and N2O (bottom-up: 0.7 (0.1, 1.3), top-down: 0.09 (−0.19, 0.37) Tg N2O-N yr−1). The combined global warming potential of all three gases (GWP-100) cannot be distinguished from neutral. Over shorter timescales (GWP-20), the region is a net GHG source because CH4 dominates the total forcing. The net CO2 sink in Boreal forests and wetlands is largely offset by fires and inland water CO2 emissions as well as CH4 emissions from wetlands and inland waters, with a smaller contribution from N2O emissions. Priorities for future research include the representation of inland waters in process-based models and the compilation of process-model ensembles for CH4 and N2O. Discrepancies between bottom-up and top-down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well-distributed in situ GHG measurements and improved resolution in upscaling techniques.
American Geophysical Union (AGU)
2024
We investigate the concentration fluctuations of passive scalar plumes emitted from small, localised (point-like) steady sources in a neutrally stratified turbulent boundary layer over a rough wall. The study utilises high-resolution large-eddy simulations for sources of varying sizes and heights. The numerical results, which show good agreement with wind-tunnel studies, are used to estimate statistical indicators of the concentration field, including spectra and moments up to the fourth order. These allow us to elucidate the mechanisms responsible for the production, transport and dissipation of concentration fluctuations, with a focus on the very near field, where the skewness is found to have negative values – an aspect not previously highlighted. The gamma probability density function is confirmed to be a robust model for the one-point concentration at sufficiently large distances from the source. However, for ground-level releases in a well-defined area around the plume centreline, the Gaussian distribution is found to be a better statistical model. As recently demonstrated by laboratory results, for elevated releases, the peak and shape of the pre-multiplied scalar spectra are confirmed to be independent of the crosswind location for a given downwind distance. Using a stochastic model and theoretical arguments, we demonstrate that this is due to the concentration spectra being directly shaped by the transverse and vertical velocity components governing the meandering of the plume. Finally, we investigate the intermittency factor, i.e. the probability of non-zero concentration, and analyse its variability depending on the thresholds adopted for its definition.
Cambridge University Press
2024
NILU og Transportøkonomisk institutt (TØI) har på oppdrag fra Miljødirektoratet videreutviklet modellen NERVE («Norwegian Emissions from Road Vehicle Exhaust») for beregning av klimagassutslipp fra veitrafikken i norske kommuner. NERVE-modellen anvender de mest detaljerte datasettene for bilpark, utslippsfaktorer, trafikk og veier for spesifikke lokale forhold. Datasettene er kombinert i en datastruktur som gjør at resultat kan aggregeres på et lite eller et stort geografisk område. NERVE kan således betegnes som en «bottom-up»-utslippsmodell, fordi den er bygget opp «nedenfra» fra detaljerte datakilder. Denne rapporten presenterer metodikken og antagelsene bak beregningene med NERVE, og sammenligner resultat aggregert på nasjonalt nivå med annen tilgjengelig nasjonal statistikk.
NILU
2024
2024
2024
Design of multi-luminescent silica-based nanoparticles for the detection of liquid organic compounds
Tracer testing in reservoir formations is utilised to determine residual oil saturation as part of optimum hydrocarbon production. Here, we present a novel detection method of liquid organic compounds by monodisperse SiO2 nanoparticles (NPs) containing two luminophores, a EuIII:EDTA complex and a newly synthesised fluorophore based on the organic boron-dipyrromethene (BODIPY)-moiety. The particles exhibited stable EuIII PL emission intensity with a long lifetime in aqueous dispersion. The fluorescence of the BODIPY was also preserved in the aqueous environment. The ratiometric PL detection technique was demonstrated by using toluene and 1-octanol as model compounds of crude oil. The optimal synthesis conditions were found to give NPs with a diameter of ~100 nm, which is suitable for transport through porous oil reservoir structures. The cytotoxicity of the NPs was confirmed to be very low for human lung cell and fish cell lines. These findings demonstrate the potential of the NPs to replace the hazardous chemicals used to estimate the residual oil saturation. Moreover, the ratiometric PL detection technique is anticipated to be of benefit in other fields, such as biotechnology, medical diagnostics, and environmental monitoring, where a reliable and safe detection of a liquid organic phase is needed.
Wiley-VCH
2024
2024
2024
The Chinese Loess Plateau (CLP) in northern China is home to one of the most prominent loess records in the world, reflecting past eolian dust activity in East Asia. However, their interpretation is hampered by ambiguity in the origin of loess-forming dust and an incomplete understanding of the circulation forcing dust accumulation. In this study, we used a novel modeling approach combining a dust emission model FLEXDUST with simulated back trajectories from FLEXPART to trace the dust back to where it was emitted. Over 21 years (1999–2019), we modeled back trajectories for fine (∼2 μm) and super-coarse (∼20 μm) dust particles at six CLP sites during the peak dust storm season from March to May. FLEXPART source-receptor relationships are combined with the dust emission inventory from FLEXDUST to create site-dependent high-resolution maps of the source contribution of deposited dust. The nearby dust emission areas were found to be the main source of dust to the CLP. Dust deposition across the CLP was found to predominantly occur via wet removal, with also some super-coarse dust from distant emission regions being wet deposited following high-level tropospheric transport. The high topography located on the downwind side of the emission area plays an essential role in forcing the emitted super-coarse dust upward. On an interannual scale, the phase of the Arctic Oscillation in the preceding winter was found to have a strong association with the spring deposition rate on the CLP, while the strength of the East Asian Winter Monsoon was less influential.
American Geophysical Union (AGU)
2024
Miljøforskernes nye reklamedingser var fulle av miljøgifter
Norges forskningsråd
2024
NILU har på oppdrag fra Multiconsult AS gjort spredningsberegninger av utslipp til luft fra fremtidig renseanlegg i Nordbykollen i Drammen, samt pumpestasjon ved Solumstrand. Det er gjort beregninger for tre utslippspunkter ved Nordbykollen, 15 moh., 45 moh. og 85 moh. og det er beregnet grad av fortynning ved ulike naboer. Vurderingen er at ved normale driftsforhold vil plasseringen 15 moh. være tilstrekkelig for å minimere risiko for lukt. Men ved spesielle værforhold som inversjon kan det oppstå situasjoner med stabil luft og dårlig fortynning med økt risiko for følbar lukt hos nærmeste naboer. For pumpestasjonen ved Solumstrand bør det velges en løsning med minimum 10-12 m skorstein og vertikal utgangshastighet 5-6 m/s for å sikre god spredning og fortynning av utslippet.
NILU
2024
Monitoring of microplastics in the Norwegian environment (MIKRONOR) 2023
The MIKRONOR monitoring program aims to establish baseline levels of microplastics in the Norwegian environment and to identify potential sources and sinks. This third MIKRONOR report focuses mainly on results from air samples, including data on tyre wear particles (TWP), as well as river and fjord surface water samples, and their correlation to rainfall and river discharge levels. Additionally, it presents data from sand samples taken from an OSPAR beach in the outer Oslofjord. The results for 2023 provide evidence of the omnipresence of microplastics in the environment. However, levels were higher near cities and populated areas, with decreasing levels further from human activities. This trend was observed in both air and surface water samples. Sand samples from the OSPAR beach in the Oslofjord showed levels of microplastics comparable to, or slightly higher than studied eabches at Svalbard. Since no other beach studies have been conducted in the MIKRONOR program, it is difficult to determine typical microplastic levels on a beach in the outer Oslofjord. Determined levels of microplastics in the beach samples were comparable to levels in marine bottom sediment at remote areas along the coast and lower than levels in sediments from the Oslofjord. Main conclusions of this report highlight the need for further research into the processes that control the levels and variations of microplastics and TWPs, such as weather conditions, river discharge, and air mass movement. Sampling of different matrices should, where possible, be conducted using similar strategies and equipment to improve the comparability of results. Additionally, the high spatial and temporal variability between samples must be considered to determine the appropriate number of analyses needed to obtain reliable results.
Norsk institutt for vannforskning og Miljødirektoratet
2024
2024