Found 9746 publications. Showing page 380 of 390:
NILU performed a test campaign for measurements of CF4 and C2F6 for stack emissions at Alcoa Mosjøen Smelter. Time-integrated samples were taken with evacuated canisters combined with low-flow restrictors for continuous sampling periods as long as 4 weeks. The samples were analyzed at NILU with a Medusa preconcentration method combined with GC-MS SIM. As a main conclusion, time integrated sampling together with Medusa GC-MS methodology is a very precise alternative to the traditional attempts to quantify PFC-emission.
NILU
2024
Active vegetation fires in south-eastern (SE) Europe resulted in a notable increase in the number concentration of aerosols and cloud condensation nuclei (CCN) particles at two high latitude locations—the SMEAR IV station in Kuopio, Finland, and the Zeppelin Observatory in Svalbard, high Arctic. During the fire episode aerosol hygroscopicity κ slightly increased at SMEAR IV and at the Zeppelin Observatory κ decreased. Despite increased κ in high CCN conditions at SMEAR IV, the aerosol activation diameter increased due to the decreased supersaturation with an increase in aerosol loading. In addition, at SMEAR IV during the fire episode, in situ measured cloud droplet number concentration (CDNC) increased by a factor of ∼7 as compared to non-fire periods which was in good agreement with the satellite observations (MODIS, Terra). Results from this study show the importance of SE European fires for cloud properties and radiative forcing in high latitudes.
American Geophysical Union (AGU)
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
An AI-Enhanced Systematic Review of Climate Adaptation Costs: Approaches and Advancements, 2010–2021
This study addresses the critical global challenge of climate adaptation by assessing the inadequacies in current methodologies for estimating adaptation costs. Broad assessments reveal a significant investment shortfall in adaptation strategies, highlighting the necessity for precise cost analysis to guide effective policy-making. By employing the PRISMA 2020 protocol and enhancing it with the prismAId tool, this review systematically analyzes the recent evolution of cost assessment methodologies using state-of-the-art generative AI. The AI-enhanced approach facilitates rapid and replicable research extensions. The analysis reveals a significant geographical and sectoral disparity in research on climate adaptation costs, with notable underrepresentation of crucial areas and sectors that are most vulnerable to climate impacts. The study also highlights a predominant reliance on secondary data and a lack of comprehensive uncertainty quantification in economic assessments, suggesting an urgent need for methodological enhancements. It concludes that extending analyses beyond merely verifying that benefits exceed costs is crucial for supporting effective climate adaptation. By assessing the profitability of adaptation investments, it becomes possible to prioritize these investments not only against similar interventions but also across the broader spectrum of public spending.
MDPI
2024
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2024
Life starts with plastic: High occurrence of plastic pieces in fledglings of northern fulmars
Plastic pollution threatens many organisms around the world. In particular, the northern fulmar, Fulmarus glacialis, is known to ingest high quantities of plastics. Since data are sparse in the Eurasian Arctic, we investigated plastic burdens in the stomachs of fulmar fledglings from Kongsfjorden, Svalbard. Fifteen birds were collected and only particles larger than 1 mm were extracted, characterised and analysed with Fourier Transform InfraRed spectroscopy. All birds ingested plastic. In total, 683 plastic particles were found, with an average of 46 ± 40 SD items per bird. The most common shape, colour and polymer were hard fragment, white, and polyethylene, respectively. Microplastics ( 5 mm). This study confirms high numbers of ingested plastics in fulmar fledglings from Svalbard and suggests that fulmar fledglings may be suitable for temporal monitoring of plastic pollution, avoiding potential biases caused by age composition or breeding state.
Elsevier
2024
2024
Seabirds are often considered sentinel species of marine ecosystems, and their blood and eggs utilized to monitor local environmental contaminations. Most seabirds breeding in the Arctic are migratory and thus are exposed to geographically distinct sources of contamination throughout the year, including per- and polyfluoroalkyl substances (PFAS). Despite the abundance and high toxicity of PFAS, little is known about whether blood concentrations at breeding sites reliably reflect local contamination or exposure in distant wintering areas. We tested this by combining movement tracking data and PFAS analysis (nine compounds) from the blood of prelaying black-legged kittiwakes (Rissa tridactyla) nesting in Arctic Norway (Svalbard). PFAS burden before egg laying varied with the latitude of the wintering area and was negatively associated with time upon return of individuals at the Arctic nesting site. Kittiwakes (n = 64) wintering farther south carried lighter burdens of shorter-chain perfluoroalkyl carboxylates (PFCAs, C9–C12) and heavier burdens of longer chain PFCAs (C13–C14) and perfluorooctanesulfonic acid compared to those wintering farther north. Thus, blood concentrations prior to egg laying still reflected the uptake during the previous wintering stage, suggesting that migratory seabirds can act as biovectors of PFAS to Arctic nesting sites.
2024
Sør-Europa må forberede seg på skogbrann i sommer, mens Norge får regn
Norges forskningsråd
2024
Data fusion for enhancing urban air quality modeling using large-scale citizen science data
Rapid urbanization has led to many environmental issues, including poor air quality. With urbanization set to continue, there is an urgent need to mitigate air pollution and minimize its adverse health impacts. This study aims to advance urban air quality management by integrating a dispersion model output with large-scale citizen science data, collected over a 4-week period by 642 participants in Cork City, Ireland. The dispersion model enabled the identification of major sources of NO2 air pollution while also addressing gaps in regulatory monitoring efforts. Integrating the diffusion tube data with the dispersion model output, we developed a data fusion model that captured localized fluctuations in air quality, with increases of up to 22μg/m3 observed at major road intersections. The data fusion model provided a more accurate representation of NO2 concentrations, with estimates within 1.3μg/m3 of the regulatory monitoring measurement at an urban traffic location, an improvement of 11.7μg/m3 from the priori dispersion model. This enhanced accuracy enabled a more precise assessment of the population exposure to air pollution. The data fusion model showed a higher population exposure to NO2 compared to the dispersion model, providing valuable insights that can inform environmental health policies aimed at safeguarding public health.
Elsevier
2024
2024