Publikasjoner

Description and evaluation of airborne microplastics in the United Kingdom Earth System Model (UKESM1.1) using GLOMAP-mode

McErlich, Cameron; Goddard, Felix; Aves, Alex; Hardacre, Catherine; Evangeliou, Nikolaos; Hewitt, Alan J.; Revell, Laura E.

Abstract. Airborne microplastics are a recently identified atmospheric aerosol species with potential air quality and climate impacts, yet they are not currently represented in global climate models. Here, we describe the addition of microplastics to the aerosol scheme of the UK Earth System Model (UKESM1.1): the Global Model of Aerosol Processes (GLOMAP). Microplastics are included as both fragments and fibres across a range of aerosol size modes, enabling interaction with existing aerosol processes such as ageing and wet and dry deposition. Simulated microplastics have higher concentrations over land, but can be transported into remote regions including Antarctica despite no assumed emissions from these regions. Lifetimes range between ∼17 d to ∼1 h, with smaller, hydrophilic microplastics having longer lifetimes. Microplastics are present throughout the troposphere, and the smallest particles are simulated to reach the lower stratosphere in small numbers. Dry deposition is the dominant microplastic removal pathway, but greater wet deposition occurs for smaller hydrophilic microplastic, due to interactions with clouds. Although microplastics currently contribute a minor fraction of the total aerosol burden, their concentration is expected to increase in future if plastic production continues to increase, and as existing plastic waste in the environment degrades to form new microplastic. Incorporating microplastics into UKESM1.1 is a key step toward quantifying their current atmospheric impact and offers a framework for simulating future emission scenarios for an assessment of their long term impacts on air quality and climate.

Plan hopes to capture carbon by tapping the ocean's power - Earth.com

Muri, Helene (journalist)

A look at how ocean carbon removal fits into climate plans and why experts say strong safeguards are needed before it can scale.

Evaluating the Combined Effect of Land and Marine CDR

Sathyanadh, Anusha; Muri, Helene

With the global annual mean temperature in 2024 exceeding 1.5°C above preindustrial levels, the world faces increasing risks from climate impacts. Achieving the long-term temperature goals of the Paris Agreement will require not only deep emission reductions but likely also large-scale deployment of carbon dioxide removal (CDR). However, major uncertainties remain regarding the Earth system’s response to CDR, its efficacy under overshoot conditions, and the potential of CDR to reverse warming beyond net-zero emissions.
Here, we use emission-driven simulations with activity-driven implementation of CDR in the Norwegian Earth System Model (NorESM2-LM) to assess the carbon sequestration efficacy and climate response of two CDR methods, Bioenergy with Carbon Capture and Storage (BECCS) and Ocean Alkalinity Enhancement (OAE), deployed individually and in combination. Our scenarios follow a high-overshoot trajectory (SSP5-3.4-OS) combined with ramped-up deployment of CDR. Additional CDR amounted to 5.2 million km² of bioenergy feedstock for BECCS in addition to the BECCS already present in the SSP5-3.4-OS and a CaO deployment rate of 2.7 Gt/year for OAE, derived from life cycle analysis. OAE is applied across the exclusive economic zones of Europe, the United States, and China. BECCS alone accounts for a 16 ppm reduction using 5.2 million km² of bioenergy crops, while OAE contributes 7 ppm reduction with a cumulative addition of 82.3 Gt of CaO, yielding a CDR effectiveness of 0.08 ppm per Gt of CaO. During the overshoot phase (2050–2060), the combined simulation shows a gross atmospheric CO₂ reduction of 2-4 ppm, increasing to a reduction of 23 ppm by 2100, indicating nearly additive contributions from the two methods.
Despite the substantial CO₂ drawdown and a net reduction of anthropogenic emissions by 5.4 GtCO₂/year by 2100 through additional CDR, the global temperature response remains modest and indistinguishable from internal variability. This highlights the importance of designing robust, scalable CDR portfolios along with ambitious emission cuts. Our results also call for better integration of CDR pathways into IAMs scenarios so that we can have them in ESMs to fully capture biogeophysical feedback and Earth system constraints in overshoot scenarios.

Advancing FAIRness in the Atmospheric Subdomain:​ Implementing FAIR Principles in the ACTRIS Data Centre

Myhre, Cathrine Lund; Fiebig, Markus

Cyclic volatile methyl siloxanes in the terrestrial and aquatic environment at remote Arctic sites

Nipen, Maja; Hartz, William Frederik; Schulze, Dorothea; Christensen, Guttorm; Løge, Oda Siebke; Nikiforov, Vladimir; Bohlin-Nizzetto, Pernilla

Cyclic volatile methyl siloxanes (cVMS) are widely used chemicals with high emissions to the atmosphere due to their volatility. They are found in the Arctic atmosphere, indicating potential for long-range transport. This study examined the potential for deposition of cVMS (D4, D5, D6) to surface media via snow in Arctic regions. Results showed low cVMS levels in vegetation, soil, sediment, and marine biota. D4 was detected above detection limits but generally below quantification limits, while D5 and D6 were generally not detected. This aligns with current research, suggesting negligible cVMS input from atmospheric deposition via snow and snow melt.

NILU

Cross-Cutting Studies of Per- and Polyfluorinated Alkyl Substances (PFAS) in Arctic Wildlife and Humans

Abass, Khaled; Bonefeld-Jørgensen, Eva Cecilie; Bossi, Rossana; Dietz, Rune; Ferguson, Steve; Fernie, Kim J.; Grandjean, Philippe; Herzke, Dorte; Houde, Magali; Lemiere, Melanie; Letcher, Robert J; Muir, Derek C.G.; Silva, Amila O. De; Ostertag, Sonja; Rand, Amy A.; Søndergaard, Jens; Sonne, Christian; Sunderland, Elsie M.; Vorkamp, Katrin; Wilson, Simon; Weihe, Pal

Stochastic and deterministic processes in Asymmetric Tsetlin Machine

Elmisadr, Negar; Belaid, Mohamed-Bachir; Yazidi, Anis

This paper introduces a new approach to enhance the decision-making capabilities of the Tsetlin Machine (TM) through the Stochastic Point Location (SPL) algorithm and the Asymmetric Steps technique. We incorporate stochasticity and asymmetry into the TM's process, along with a decaying normal distribution function that improves adaptability as it converges toward zero over time. We present two methods: the Asymmetric Probabilistic Tsetlin (APT) Machine, influenced by random events, and the Asymmetric Tsetlin (AT) Machine, which transitions from probabilistic to deterministic states. We evaluate these methods against traditional machine learning algorithms and classical Tsetlin (CT) machines across various benchmark datasets. Both AT and APT demonstrate competitive performance, with the AT model notably excelling, especially in complex datasets.

Machine Learning Prediction of Student Satisfaction on Indoor Air Quality and Thermal Environment in a Norwegian Secondary School

Alam, Azimil Gani; Mathisen, Hans Martin; Cao, Guangyu; Bartonova, Alena; Høiskar, Britt Ann Kåstad; Fredriksen, Mirjam

Ensuring a healthy and comfortable indoor environment in schools is essential for student well-being and academic performance. The purpose of this study is to investigate the factors influencing students’ satisfaction with indoor air quality (IAQ) and thermal comfort in classrooms. To address this, one year-long measurements were conducted across multiple classrooms in a Norwegian secondary school, collecting data on indoor climate (CO₂, VOC levels, temperature, relative humidity, and air pressure) along with outdoor climate variables (temperature, humidity, and solar radiation). Additional room-specific data, including orientation, floor level, and ventilation system specifications, were also considered. An online feedback system was used to gather 1,473 real-time student responses on satisfaction levels. Supervised machine learning (ML) models were developed to assess the importance of these parameters in predicting perceived indoor comfort: IAQ perceptions and thermal environmental perceptions. Results showed ML models effectively predicted student dissatisfaction, achieving accuracy greater than 80% when environmental and building parameters were considered simultaneously. The findings emphasized that dissatisfaction with indoor conditions is driven by multiple interacting factors of measured variables and building parameters single independent variables. SHAP analysis provided valuable interpretability, revealing how variations in environmental conditions collectively impact students' perceived comfort. This comprehensive approach demonstrates the practical potential of ML-based IEQ monitoring systems, suggesting that schools can proactively improve indoor conditions through targeted interventions informed by real-time predictions.

Ikke-spesifikk screening av støv fra norske husholdninger

Froment, Jean Francois; Skaar, Jøran Solnes; Gundersen, Hans; Rostkowski, Pawel

Denne rapporten presenterer resultater fra en ikke-spesifikk screening av husstøv fra norske hjem. Totalt ble 203 kjemiske forbindelser identifisert, med ftalater som den mest dominerende stoffgruppen. Flere av de påviste stoffene er kjent som hormonforstyrrende, nevrotoksiske eller klassifisert som persistente, mobile og toksiske (PMT). Resultatene viser et endret stoffmønster sammenlignet med tidligere studier og understreker behovet for videre overvåkning av innemiljø, forskning på cocktail-effekter og bedre regulering av forbrukerprodukter.

NILU

SHORT- AND MEDIUM-CHAIN CHLORINATED PARAFFINS IN AN ARCTIC MARINE FOOD CHAIN

Giebichenstein, Julia; Warner, Nicholas Alexander; Harju, Mikael; Routti, Heli Anna Irmeli; Varpe, Øystein; Gabrielsen, Geir W.; Borgå, Katrine

National E-waste Monitor 2025 - Norway

D'Angelo, Elena; Schubert, Maximillian; Balde, Cornelis Peter; Yamamoto, Tales; Bourgé, Émilien; Abbasi, Golnoush

The National E-waste Monitor 2025 – Norway provides a detailed assessment of the current situation of e-waste statistics and legislation, and an outlook on e-waste statistics up to 2050.

Norway is the world’s leading nation in Waste Electrical and Electronic Equipment (WEEE) generation per capita, producing 27.5 kg per person in 2022, equivalent to 149 kt.

However, the country has established an efficient collection system, successfully gathering 72% of generated e-waste, with 107 kt tons collected in 2022 (approximately 19.5 kg per capita).

The country’s WEEE stock has seen significant growth over the past decade, expanding from 14 million tons in 2010 to nearly 20 million tons in 2022. However, based on the monitor’s results, the implementation of robust Circular Economy measures could help EEE Put on the Market in Norway reaching, by 2050, half of the to 2010 levels (67 kt). The big drop is explained by more repairability and improved durability of EEE products; by contrast, the projection in a Business as Usual scenario would be 5 times higher (294 kt) than in the Circular Economy scenario.

In terms of international trade, Norway reported 20 kt of used EEE exports for reuse, primarily within the European Union. Legal WEEE exports saw an increase from 27 kt in 2022 to 38 kt in 2023. Authorities intercepted 15.5 t of illegal exports due to inadequate documentation and functionality testing.

Upcoming country investments may go in the direction of recycling technologies for rare earth metals and precious materials recovery, improved small electronics collection systems, stricter labelling requirements for recyclable components and hazardous substances.

While Norway’s e-waste management system is already considered exemplary, the monitor’s results emphasize the need for more ambitious targets aligned with the WEEE Directive to create a truly sustainable and circular electronics management system. The focus is now shifting toward public awareness campaigns to encourage repair over replacement and the development of more efficient collection methods for small electronic devices.

Citation: E. D’Angelo, M. Schubert, T. Yamamoto, C.P. Baldé, E. Bourgé and G. Abbasi, United Nations Institute for Training and Research, NILU, “National E-waste monitor 2025 - Norway”, 2025, Bonn/Oslo, Germany and Norway.

NILU

Arctic food and energy security at the crossroads

Unc, Adrian; Najm, Majdi R. Abou; Aspholm, Paul Eric; Bolisetti, Tirupati; Charles, Colleen; Datta, Ranjan; Eggen, Trine; Flem, Belinda Eline; Hailu, Getu; Heimstad, Eldbjørg Sofie; Hurlbert, Margot; Karlsson, Meriam; Korsnes, Marius Støylen; Nash, Arthur; Parsons, David; Sajeevan, Radha Sivarajan; Shurpali, Narasinha J.; Valkenburg, Govert; Wilde, Danielle; Wu, Bing; Yanni, Sandra F.; Misra, Debasmita

Arctic food systems blend Traditional Ecological Knowledge with modern, often energy-intensive influences, triggered by colonization. Food systems’ future depends on alignment of tradition with innovation, facilitation of resilience and a heritage-driven interaction with the global economy – at a pace determined by local communities.