Publikasjoner

Towards a reliable assessment of nanomaterial health effects using advanced biological models and assays (NanoBioReal)

Cimpan, Mihaela Roxana; Rios-Mondragon, Ivan; Camassa, Laura Maria Azzurra; Puntes, Victor Franco; Skrętna, Agnieszka Gajewicz; Busquets, Marti; Longhin, Eleonora Marta; Mariussen, Espen; Hofshagen,, Ole-Bendik; Bastus, Neus Gómez; Elje, Elisabeth; Shaposhnikov, Sergey; Dusinska, Maria; Espevik, Terje; Nilsen, Asbjørn Magne; Rundén-Pran, Elise; Zienolddiny-Narui, Shan

Eksperter: Dette bør du ikke gjenbruke

Herzke, Dorte (intervjuobjekt); Eilertsen, Stine (journalist)

Vinterlufta

Grythe, Henrik (intervjuobjekt); Leine, Jan Erlend (journalist)

Semantic Modeling of Waste Dataflow for Automating Circular Economy Systems

Motevallian, Mahsa; Alam, A M Esfar E; Taherkordi, Amirhosein; Abbasi, Golnoush

Circular Economy (CE) is a model with a concrete action plan covering the whole life cycle of a product, from production and consumption to waste management (WM). Information technologies considerably contribute to the transition towards CE, e.g., waste tracking using Internet of Things (IoT). This will cause the businesses and organizations to confront a large diversity of data (i.e. waste amount, types, locations, etc.). The generated data is often stored and processed through manual or semi-manual methods by each business or organization. However, an automated method which can also interpret and integrate the diverse data in WM fields across different organizations is still in its infancy. Often, such data is not organized and falls short of reaching its full potential in facilitating coordinated management and enabling Circular Economy initiatives. In this paper, we aim to address this need through automated interpretation and integration of municipal waste data by applying semantic data modeling. Our approach proposes to capture the semantical description of entities in the WM process and their relations, which can appear between waste producers, authorities and consumers. Then, the obtained semantic model will facilitate and automate the required interpretation and integration of waste data, both for intra- and inter-organization scenarios. We realize intelligent semantic-based searching using natural language processing and large language models.

Varsler dårlig luftkvalitet de neste dagene

Grythe, Henrik (intervjuobjekt); Stokholm, Ane Rostad (journalist)

In vitro toxicity testing of PFAS-based and PFAS-free coating materials for different industrial sectors

Longhin, Eleonora Marta

Comparison of Atmospheric Microplastic in remote and urban locations in Norway; occurence, composition and sources

Herzke, Dorte; Schmidt, Natascha; Schulze, Dorothea; Eckhardt, Sabine; Evangeliou, Nikolaos

Modelling sources and transport of airborne microplastics

Evangeliou, Nikolaos

Modelled sources of airborne microplastics collected at a remote Southern Hemisphere site

Aves, Alex; Ruffell, Helena; Evangeliou, Nikolaos; Gaw, Sally; Revell, Laura E.

Airborne microplastics have emerged in recent years as ubiquitous atmospheric pollutants. However, data from the Southern Hemisphere, and remote regions in particular, are sparse. Here, we report airborne microplastic deposition fluxes measured during a five-week sampling campaign at a remote site in the foothills of the Southern Alps of New Zealand. Samples were collected over 24-hour periods for the first week and for 7-day periods thereafter. On average, atmospheric microplastic (MP) deposition fluxes were six times larger during the 24-hour sampling periods (150 MP m−2 day−1) than during the 7-day sampling periods (26 MP m−2 day−1), highlighting the importance of sampling frequency and deposition collector design to limit particle resuspension. Previous studies, many of which used weekly sampling frequencies or longer, may have substantially underestimated atmospheric microplastic deposition fluxes, depending on the study design. To identify likely sources of deposited microplastics, we performed simulations with a global dispersion model coupled with an emissions inventory of airborne microplastics. Modelled deposition fluxes are in good agreement with observations, highlighting the potential for this method in tracing sources of deposited microplastics globally. Modelling indicates that sea-spray was the dominant source when microplastics underwent long-range atmospheric transport, with a small contribution from road dust.

Dårlig luftkvalitet

Grythe, Henrik (intervjuobjekt); Baisotti, Valentina (journalist)

Mikroplast og PFAS er giftigere sammen enn hver for seg

Schmidt, Natascha (intervjuobjekt); Bergstrøm, Ida Irene (journalist)

The Troll Observing Network (TONe): plugging observation holes in Dronning Maud Land, Antarctica

Pedersen, Christina Alsvik; Njåstad, Birgit; Aas, Wenche; Darelius, Elin Maria K.; Descamps, Sebastien; Flått, Stig; Hattermann, Tore; Hudson, Stephen; Miloch, Wojciech Jacek; Rykkje, Simen; Schweitzer, Johannes; Storvold, Rune; Tronstad, Stein

Understanding how Antarctica is changing and how these changes influence the rest of the Earth is fundamental to the future robustness of human society. Strengthening our understanding of these changes and their implications requires dedicated, sustained and coordinated observations of key Antarctic indicators. The Troll Observing Network (TONe), now under development, is Norway’s contribution to the global need for sustained, coordinated, complementary and societally relevant observations from Antarctica. When fully implemented within the coming three years, TONe will be a state-of-the-art, multi-platform, multi-disciplinary observing network in data-sparse Dronning Maud Land. A critical part of the network is a data management system that will ensure broad, free access to all TONe data to the international research community.

Roadmap for action for advancing aggregate exposure to chemicals in the EU

Lamon, L.; Doyle, J.; Paini, A.; Moeller, R.; Viegas, S.; Cubadda, F.; Hoet, P.; Nieuwenhuyse, A. van; Louro, H.; Dusinska, Maria; Galea, K. S.; Canham, R.; Martins, C.; Gama, A.; Teófilo, V.; Diniz-da-Costa, M.; Silva, M. João; Ventura, C.; Alvito, P.; Yamani, Naouale El; Ghosh, M.; Duca, R. C.; Siccardi, M.; Rundén-Pran, Elise; McNamara, C.; Price, P.

The European Food Safety Authority (EFSA) has a goal to efficiently conduct aggregate exposure assessments (AEAs) for chemicals using both exposure models and human biomonitoring (HBM) data by 2030. To achieve EFSA's vision, a roadmap for action for advancing aggregate exposure (AE) in the EU was developed. This roadmap was created by performing a series of engagement and data collection activities to map the currently available methods, data, and tools for assessing AE of chemicals, against the needs and priorities of EFSA. This allowed for the creation of a AEA framework, identification of data and knowledge gaps in our current capabilities, and identification of the challenges and blockers that would hinder efforts to fill the gaps. The roadmap identifies interdependent working areas (WAs) where additional research and development are required to achieve EFSA's goal. It also proposes future collaboration opportunities and recommends several project proposals to meet EFSA's goals. Eight proposal projects supported by SWOT analysis are presented for EFSA's consideration. The project proposals inform high-level recommendations for multi-annual and multi-partner projects. Recommendations to improve stakeholder engagement and communication of EFSA's work on AEA were gathered by surveying stakeholders on specific actions to improve EFSA's communication on AE, including webinars, virtual training, social media channels, and newsletters.