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2026
Hidden Resources: The Quantity and Recovery Potential of Rare-Earth Elements in Norwegian Households
2026
2026
2026
Air Quality in Ny-Ålesund. Monitoring of Local Air Quality 2021-2024
The concentrations of the measured components are generally low and below national limit values for the protection of human health and critical levels for the protection of vegetation.
Wind from northern sectors gave the highest average concentrations of nitrogen oxides and sulfur dioxide, which indicates the power station and the harbour as possible sources. We also see single episodes of long-range transport of pollutants.
NILU
2026
Modeling soil solution electrical conductivity across Europe
Soil salinization, referring to the excessive accumulation of soluble salts in soils, adversely influences nutrient cycling, biodiversity, soil structure, crop production, soil health, and ecosystem functioning. Accurately assessing soil salinity via electrical conductivity (EC) is key to mitigating its impacts. Thus, developing predictive tools for soil EC at regional and continental scales is essential for sustainable soil management. Here, we apply machine learning models to predict soil EC in the European Union (EU) and United Kingdom (UK) soils using different environmental factors like soil, climate, topography, and satellite data as predictors. The model is trained by ≈40,000 soil EC data points from the 2015 and 2018 Land Use/Cover Area Frame Survey data (LUCAS) surveys, complemented by the EC observations from World Soil Information Services (WoSIS) dataset. To improve the model performance, a forward feature selection technique was used resulting in selection of 17 covariates out of initially 34 predictors. The final selected XGBoost model achieved R2 values of 0.68, 0.6, and 0.63 for the training, internal testing, and independent validation datasets, respectively. For the year 2018, we estimate ≈21.7 Mha of EU + UK land exceeds an EC of 0.6 dS/m (at a 1:5 soil to water ratio, the so-called EC1:5). This estimate should be interpreted as elevated predicted EC1:5, rather than a direct estimate of soils meeting protosalic diagnostic criteria. The output of the predictive model consists of a gridded dataset that illustrates the spatial distribution of EC1:5 throughout the study area for the year 2018, along with an associated uncertainty map with a spatial resolution of 1 km.
2026
Heritable mutations in male germ cells pose a critical risk to human health and future generations, however standardized methods for assessing germ cell genotoxicity remain limited. We refined the in vivo alkaline comet assay (proof-of-concept (Dirven et al. 2023); protocol (Olsen et al. 2024)) to detect DNA damage in testicular germ cells, with selective addressment of haploid spermatids and primary spermatocytes. Measurements of DNA damage (% Tail DNA) and DNA content (total fluorescence intensity) in individual comets were combined with visual comet identification to distinguish testicular comet populations based on differences in DNA content and appearance. To verify the method’s functionality and reliability, DNA damage was assessed in rats exposed to the direct-acting, well-characterized genotoxicants X-rays and ethyl methanesulfonate across distinct testicular cell populations, alongside liver and blood. To minimize experimental variation, the protocol included stringent standardization of animal handling, tissue processing, and comet assay procedures. Both X-rays and EMS induced significant DNA damage in testicular germ cells, with comparable responses across testicular cell types and similar (X-rays) or higher levels observed in somatic tissues. The low inter-animal variability observed supports the robustness of the method. Importantly, inclusion of testicular germ cells in OECD test guideline 489 would provide a valuable tool for hazard identification and mutagenicity classification of chemicals under the Globally Harmonized System of Classification and Labelling of Chemicals. This versatile, sensitive, and resource-efficient assay enhances the assessment of male-mediated genetic risks and supports regulatory efforts to protect reproductive health and safeguard the genetic integrity of future generations through the use of safer chemicals.
2026
2026
CAMS Assessment Report on European Air Quality 2025
The full report provides reference information on air quality in Europe in 2025. The purpose of the report is to present a consistent and accurate estimate of European air quality focusing on key indicators and on the origin of selected pollution episodes. It is intended to support air quality experts in their reporting under air quality legislation by providing an overview over the status of European transboundary air pollution. It contains updated information on key indicators for background air quality for the main regulatory pollutants: ozone (O3), nitrogen dioxide (NO2), particulate matter of 10 micrometres or less in diameter (PM10) and particulate matter of 2.5 micrometres or less in diameter (PM2.5).
Copernicus Atmosphere Monitoring Service
2026
2026
Unidentified Halon-2402 emissions in East Asia are driving the global trend
Halon-2402 (1,2‑dibromotetrafluoroethane, H-2402) is a potent ozone‑depleting substance and greenhouse gas whose global production has been banned under the Montreal Protocol since 2010, while the use of recovered or recycled stocks remains permitted for essential uses. Although these controls led to nearly two decades of declining atmospheric abundances, recent observations indicate renewed emissions. Here, we present the first observation-based regional emission estimates of H-2402 in East Asia for 2008–2023, derived using high-frequency measurements at Gosan, South Korea, and a Bayesian inversion framework. While most AGAGE stations measure background mole fractions or intermittent low-level increases, Gosan exhibits increasingly frequent and intense pollution events, revealing growing regional emissions. We find that East Asia accounted for most global H-2402 emissions in recent years, with particularly sharp increases in Japan and the Vladivostok region of Russia. Since 2015, regional emissions from East Asia have effectively driven the global emission trend, reversing the long-term decline. These emissions are spatially linked to petrochemical infrastructure, ship-repair activity, and military decommissioning sites, suggesting releases from legacy halon banks rather than new production. Cumulative emissions from East Asia between 2008 and 2023 reached ~52 Gg CFC-11-equivalent emissions. These findings imply a tangible delay in ozone layer recovery and underscore the urgent need for strengthened monitoring, transparent reporting, and verifiable management of remaining H-2402 stocks under the Montreal Protocol.
2026
Long-term trend of elemental carbon in the high Arctic and its potential drivers
The Arctic is warming at more than twice the global average rate, a phenomenon known as Arctic amplification (Rantanen et al., 2022). In addition to greenhouse gases, short-lived climate forcers play a critical role in modulating Arctic climate through their impacts on radiation, cloud properties, and the surface energy balance (e.g. AMAP, 2015, 2021). Among these forcers, elemental carbon (EC) is of particular importance due to its strong light-absorbing properties and its ability to reduce surface albedo when deposited on snow and ice. Furthermore, aged EC particles transported to the Arctic can act as cloud condensation nuclei, influencing cloud microphysical processes and thereby modifying Arctic radiative forcing and climate feedbacks.In this study, we investigate long-term trends in EC concentrations and their potential drivers in the high Arctic using 16 years of continuous EC measurements from the Villum Research Station in northeast Greenland. We combine in situ observations with Lagrangian transport modelling and back-trajectory analyses to assess the relative contributions of changes in source-region emissions, transport pathway variability, and wet scavenging processes to the observed EC trends. Robust non-parametric statistical methods are applied to assess monotonic trends over the full observational period and before 2020, enabling a systematic comparison between the declining and stagnating phases. This integrated observational–modelling framework provides new constraints on the processes controlling EC variability in the Arctic and advances our understanding of how anthropogenic emission reductions are reflected in Arctic atmospheric composition under a rapidly evolving climate.
2026
Climate change intensifies multi‑hazard risks that affect ecosystems, societies, and economies. Addressing these interconnected risks requires integrated systems, harmonized data, and cross‑sectoral collaboration. Research infrastructures (RIs) that observe climate‑ and nature‑related processes generate essential data and services for understanding climate risk determinants: hazard, exposure, and vulnerability, yet their potential remains underutilised by financial, banking, and insurance sectors that increasingly face nature‑dependent risks.IRISCC (Integrated Research Infrastructure Services for Climate Change Risks; www.iriscc.eu) unites leading European Research Infrastructures (Ris) to provide open, standardized climate‑risk data, tools, and services through transnational and virtual access. With nearly 80 partners across natural and social sciences, IRISCC strengthens the scientific foundations for integrated climate‑risk assessment and supports the translation of RI data and tools into risk‑management landscapeWe conducted a stakeholder analysis to map the current and emerging climate‑risk service landscape and to assess how IRISCC services connect with academic, industry and decision making sectors. Survey data from IRISCC partners combined with a preliminary mapping of climate‑risk service providers, show that while strong links exist with EU‑level organizations, direct engagement with financial, banking, and insurance sectors is still very limited. This gap is critical: recent assessments by the European Central Bank indicate that around 72% of European companies depend heavily on at least one ecosystem service, underscoring the financial sector’s exposure to nature degradation (Elderson F.2023, Network for Greening the Financial System NGFS, 2022)Our findings highlight significant opportunities to embed scientific communities more efficiently, to enhance RI usage, harmonized datasets, and analytical tools into multi‑hazard climate‑risk services. Strengthening these connections can support more robust risk detection, prevention, and early‑warning capabilities, particularly for nature‑dependent industries.This presentation outlines the key findings from stakeholder analysis, identifies gaps in the current service landscape related to climate risks, and open the potential of IRISCC’s services to contribute to the needs of financial and insurance sectors. By fostering new collaborations and co‑created solutions, IRISCC aims to advance a more holistic, interoperable, and science‑based climate‑risk ecosystem in Europe.IRISCC is funded by the European Union (project number 101131261). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. Elderson F. The economy and banks need nature to survive. European Central Bank. Published June 8, 2023. Accessed January 15, 2026. https://www.ecb.europa.eu/press/blog/date/2023/html/ecb.blog230608~5cffb7c349.en.htmlNetwork for Greening the Financial System (NGFS). Nature‑related risks. Published 2022. Accessed January 15, 2026. https://www.ngfs.net/en/what-we-do/nature-related-risks
2026
Dust in the Arctic: feedbacks and interactions between climate change, aeolian dust and ecosystems
Dust in the Arctic is an emerging topic related to climate and environmental impacts. The United Nations (UN) General Assembles and the UN Coalition to Combat Desertification (UNCCD) have reiterated that the global frequency, intensity, and duration of Sand and Dust Storms (SDS) have increased in the last decade and that SDS have natural and human causes that can be exacerbated by desertification, land degradation, drought, biodiversity loss, and climate change. UNCCD and FAO have also highlighted that emerging SDS source areas have been associated with the warming of the Arctic and high latitude regions, the seasonal or permanent drying of inland waters and river deltas, or are following large-scale deforestation and wildfires, or even the ploughing of a single field. Loss of snow cover, retreat of glaciers, and increase in drought intensity due to climate change can lead to surface conditions that increase the likelihood of creation, continuation and expansion of SDS source areas.Climatic feedback mechanisms and ecosystem impacts related to dust in the Arctic include direct radiative forcing (absorption and scattering), indirect radiative forcing (via clouds and cryosphere), semi-direct effects of dust on meteorological parameters, effects on atmospheric chemistry, as well as impacts on terrestrial, marine, freshwater, and cryosphere ecosystems. Here we give an overview of our recent understanding on dust emissions and their long-range transport routes, deposition, and ecosystem effects in the Arctic as presented in Meinander et al. (2025), part of the series of review papers of the Arctic Council Working Group AMAP (Arctic Monitoring and Assessment Program) and CAFF (Conservation of Arctic Flora and Fauna), where the target audience is the scientific community focusing on the Arctic. Additional audiences include policy advisers and other staff in environmental-related ministries.We conclude that the multiple mechanisms related to dust emissions, transport and deposition both cool and warm the climate system, with an uncertain net effect. Dust plays a significant role in terrestrial and aquatic ecosystems, e.g., by providing nutrients, and with impacts on the availability of light and water. Due to Arctic warming, HLD dust emissions can be expected to increase. The contributions of LLD and HLD complicates the interpretation of how much different sources contribute to the dust loadings and corresponding temporal and spatial deposition patterns. Another challenge is that low latitude dust source emissions of road and agricultural dust is barely characterized.Reference:Meinander O, Uppstu A, Dagsson-Waldhauserova P, Groot Zwaaftink C, Juncher Jørgensen C, Baklanov A, Kristensson A, Massling A and Sofiev M (2025). Dust in the arctic: a brief review of feedbacks and interactions between climate change, aeolian dust and ecosystems. Front. Environ. Sci. Sec. Interdisciplinary Climate Studies, Volume 13 – 2025. doi: 10.3389/fenvs.2025.1536395. CAFF-special issue.
2026
The Arctic is warming up to 4 times faster than the global average, leading to rapid ice melting and consequently, a drastic change of the sources and processing of aerosols and their impact on clouds. Monitoring of these changes over the Arctic is extremely sparse, especially in the most remote regions where harsh conditions make it difficult to carry out even simple measurements. To address these knowledge gaps and develop better and new methods of remote sensing of aerosols and clouds, the CleanCloud project carried out the field campaign CLeancloud Arctic VIllum ExpeRiment (CLAVIER) at Villum Research Station (VRS) in northeast Greenland to study aerosol-cloud interaction (ACI) using in-situ surface and remote sensing as well as airborne measurements.CLAVIER covered two phase; spring (April) and summer (July/August) 2024, each lasting for one month. We have employed the existing in-situ surface aerosol monitoring at VRS, which includes a Scanning Mobility Particle Sizer (SMPS), a Cloud Condensation Nuclei Counter (CCNC), a High-Volume Sampler (HVS), a Nephelometer, an Aethalometer, a Neutral cluster and Air Ion Spectrometer (NAIS), a wind lidar and a ceilometer. During CLAVIER, the site was additionally equipped with a AeRosol aerosol-cloud lIdar System (ARIS lidar) and a Wideband Integrated Bioaerosol Sensor (WIBS-5/NEO) to provide realtime measurement of aerosols and fluorescent particles to infer the presence of bioaerosols and their potential contribution to Ice Nucelating Particles (INP). In addition, a W-band Cloud Doppler Radar (WProf) and a tethered balloon (Helikite) was operated during the spring phase. The helikite was equipped with aerosol and cloud instrumentation, including a Portable Optical Particle Spectrometer (POPS), a Miniaturized Scanning Electrical Mobility Sizer (mSEMS), a Single-channel tricolor absorption photometer (STAP) and a miniaturized Cloud Droplet Analyzer (miniCDA), and a filter sampler with the new nano-electromechanical membrane FTIR (NEMS-FTIR) technique. A second tethered balloon was also employed for meteorological and flux measurements. In the summer phase, a Proton-Transfer-Reaction Mass Spectrometry (PTR-MS) was used to measure VOCs online and cartridge sampling was performed for offline sampling of VOCs, as well as a WELAS (white-light aerosol spectrometer) for size distribution of larger sizes and the newest aethalometer AE36s. Finally, summertime measurements were also coordinated with the NASA ARCSIX aircraft mission for clousure experiments. In order to get a better understanding of the processes related to aerosol-cloud interactions, several modelling activities were and are being carried out for the CLAVIER period. These include the Flexible Particle Dispersion Model (FLEXPART), the WRF-SIP model to study in detail the secondary ice production in clouds, OpenIFSv48 global model to simulate the aerosol composition and forcing during the campaign, and finally, the FLEXPART-SOSAA framework and the ADCHEM model to study in detail the aerosol chemistry and impacts on CCN.This presentation will provide an overview of these activities and some preliminary results.
2026
Quantifying European SF6 emissions (2005-2021) using a large ensemble of atmospheric inversions
Sulfur hexafluoride (SF₆) is an extremely potent (GWP100 = 24,300) and long-lived greenhouse gas whose atmospheric concentrations continue to rise due to anthropogenic emissions. Europe represents a particularly relevant test case for investigating SF₆ emissions, as successive EU F-gas regulations over the past two decades have aimed to substantially reduce emissions. A key question is whether these regulatory measures are reflected in observed emission trends and whether reported national inventories are consistent with observation-based estimates. In this study, we quantify European SF₆ emissions for the period 2005–2021 using a large ensemble of atmospheric inversions with a strong focus on uncertainty characterization. Uncertainties are assessed using an extensive set of sensitivity tests in which key inversion parameters are systematically varied, while final uncertainties are quantified via a Monte Carlo ensemble that randomly samples combinations of these parameters. This allows us to identify the main sources of uncertainty and to evaluate the robustness of inferred emission trends.Our analysis focuses on countries with relatively dense observational coverage - the United Kingdom, Germany, France, and Italy - while also examining aggregated emissions for the EU-27. The inversion results reveal declining SF₆ emissions in all studied regions except Italy, broadly consistent with the timing of EU F-gas regulations (842/2006, 517/2014). In several countries, inferred emissions exceed reported national inventories, although the agreement generally improves in more recent years. At the EU-27 scale, emissions exhibit a pronounced decline between 2017 and 2018, coinciding with a marked reduction in emissions from southwestern Germany, suggesting regional actions were taken as the 2014 regulation took effect.Our sensitivity tests highlight the crucial role of dense and sustained atmospheric monitoring networks for robust inversion-based emission estimates. In particular, expansions of the UK observing system in 2012 and 2014 lead to significant reductions in emission uncertainties, demonstrating the importance of comprehensive observational networks in refining emission estimates.
2026
Source Attribution of High-Latitude Aerosols Based on Multi-Wavelength Optical Properties
Atmospheric aerosols represent one of the largest sources of uncertainty in estimates of future climate predictions. A key challenge arises from the large variety of aerosol types differing in physical properties, e.g. size and shape, and chemical composition as well as concentration. Coastal regions are particularly complex environments, where natural and anthropogenic aerosols co-exist, mix and interact, often fundamentally altering their original properties. At the same time, coastal areas are densely populated, hosting approximately 40 % of the global population. Consequently, improved knowledge of aerosol properties in coastal regions is essential not only for climate studies but also because of their relevance to human health.The aerosols’ optical properties, defined by their interactions with sunlight through scattering and absorption, provide valuable insight into both their physical and chemical properties. The wavelength-dependent light scattering signal can be predominantly related to the particles size, while the wavelength-dependent absorption signal rather more reflects the aerosol particles’ chemical composition. By combining these types of information within a so-called Ångström matrix, the aerosol sources and types can be assessed.In this work, aerosol optical properties were measured at three different coastal sites representing contrasting environments to identify dominant aerosol sources and types. Measurement campaigns were conducted in an urban environment at Aarhus Bay, Denmark, a rural environment at Askö, Sweden and a pristine Arctic environment at Villum Research Station, Northwest Greenland. Wavelength-dependent scattering coefficients were measured using a nephelometer (AURORA 3000, Ecotech) and wavelength-dependent absorption coefficients were obtained by an aethalometer (AE33 or AE36s, MAGEE). In addition, aerosol number size distributions were measured and air-mass back-trajectory analysis was performed. One intense measurement campaign of approximately five weeks was carried out at each site between spring 2023 and spring 2025. The resulting datasets were analysed regarding dominant aerosol sources, determining the importance of natural vs. anthropogenic emissions and locally emitted vs. long-range transported aerosols.
2026
Promoting healthy lifestyle behaviors such as physical activity, sleep, diet quality, stress management, hydration, and healthy habits requires adaptive systems capable of responding dynamically to changing behavioral and environmental conditions. However, the development and evaluation of personalized recommendation systems are challenged by fragmented observational data, privacy constraints, delayed feedback, and ethical limitations associated with long-term human experimentation. To address these challenges, this study proposes a digital twin-driven reinforcement learning framework for generating personalized behavioral recommendations in a fully simulated and statistically validated environment. The proposed framework formulates personalized behavioral recommendation as a stochastic Markov Decision Process (MDP) incorporating adherence uncertainty, behavioral drift, environmental modulation, and engagement dynamics. Synthetic longitudinal behavioral trajectories are generated through a digital twin simulator that models demographic heterogeneity, lifestyle behaviors, contextual variables, and variability in policy adherence over time. The optimization objective is defined through an effective reward formulation that balances behavioral compliance gains against penalties associated with health and environmental constraint violations. This study implements several reinforcement learning (RL) paradigms under simulated conditions, such as multi-armed bandits, table-based Q-learning, State-Action-Reward-State-Action (SARSA), function approximation-based temporal difference (TD) learning, and deep Q-learning network (DQN). The results demonstrate that richer state representations and context-dependent action dynamics are necessary for higher-capacity reinforcement learning models to consistently outperform simpler baselines. Furthermore, this study provides a reproducible method for comparing learning dynamics, performance, and computational cost in digital twin-based recommender systems. The framework additionally supports privacy-preserving experimentation through the exclusive use of synthetic behavioral data and locally controlled simulation environments.
2026
Uncertainties associated with Lagrangian transport in greenhouse gas flux estimates
Atmospheric Lagrangian particle dispersion models (LPDMs) are commonly combined with Bayesian inversion/optimization methods to infer emission fluxes across spatial scales from local to global. These tools are central to monitoring greenhouse gases, especially CO₂, CH₄, and N₂O. However, uncertainties in flux estimates arise from multiple sources: prior flux information, representation of the background atmospheric composition, statistical model choices (including hyperparameters and error covariance assumptions), and errors in atmospheric transport. In this presentation, we describe current uncertainty quantification activities linked to ongoing projects (e.g. EYE-CLIMA). We will discuss the use of meteorological ensemble simulations to assess transport related uncertainty and explore connections with dynamical systems tools and common assumptions such as Gaussian errors. Emphasis will be placed on high-resolution transport modelling applications.
2026
Global black carbon emissions from 2015-2022 constrained by observations and transport modelling
Black carbon (BC) is a product of incomplete combustion, is climate relevant and has negative impacts on human health. It absorbs radiation as an aerosol in the atmosphere, but also changes the albedo of snow covered surfaces and leads to earlier melting. The origins are either anthropogenic or natural, with different annual cycles. While anthropogenic sources like domestic burning peak in the winter, natural sources like wild fires and agricultural burning peak during spring and summer. Due to its short lifetime are the global atmospheric concentrations highly variable.We use ground based observational data from different global networks, and the atmospheric transport model FLEXPART driven by ERA5 meteorological analysis, emission inventories and the inversion framework FLEXINVERT. By minimizing the mismatch modelled and observed BC concentration we improve the emission inventories for natural emissions (GFAS) and anthropogenic emissions (LRTAP). For every year up to 50 stations are used and each observation is matched with a 50 day FLEXPART backward calculation.We discuss the distribution and sources of global BC aerosols over the period 2015 to 2022 and compare existing emission inventories with the improved constraints of the global BC emissions derived with the FLEXINVERT inversion framework.
2026
Arctic Amplification is not well understood. It is the result of a complicated interplay between remote and local forcing and feedback processes. Therefore, it is crucial to enhance our understanding of the transport of energy and moisture from lower latitudes. The amount of aerosol in the Arctic is also an important quantity as their role in Arctic Amplification, via direct radiative forcing and aerosol-cloud interactions, remain poorly quantified.In this work, we aim to better quantify how aerosols, energy, and moisture are transported to and distributed within the Arctic. We investigate observations at Arctic stations, including, Villum and Zeppelin, and perform backward-in-time simulations with the Lagrangian atmospheric transport model FLEXPART (Pisso et al., 2019; Bakels et al., 2024) to derive so-called emission sensitivities and use these sensitivities to better quantify source regions of aerosols, energy, and moisture.In general, we aim to better describe the spatial and temporal atmospheric transport characteristics into the Arctic and how these characteristics have changed in recent years. We focus on the transport during warm-air intrusions, since almost 30% of the total poleward transport of moisture (during winter) occurs during such events (Woods et al., 2013). Warm-air intrusions are often associated with large-scale atmospheric blocking patterns forcing a change in transport direction from east to more poleward, bringing warm, moist, and cloudy air into the Arctic. Warm-air intrusions can also be favourable for an enhanced transport of aerosols (e.g., Dada et al., 2022).Since climate models show large biases in moisture flux during these events (Woods et al., 2017), there is clearly a need to better quantify the transport of moisture, energy, and aerosols during these events. This will also help to provide better forcing for climate simulations.Bakels et al. (2024): 10.5194/gmd-17-7595-2024; Dada et al. (2022): 10.1038/s41467-022-32872-2; Lapere et al. (2024): 10.1029/2023JD039606; Pisso et al. (2019): 10.5194/gmd-12-4955-2019; Woods et al. (2013): 10.1002/grl.50912; Woods et al. (2017): 10.1175/JCLI-D-16-0710.
2026
Monitoring of long range transported air pollutants in Norway. Annual Report 2025
This report presents results from the monitoring of atmospheric composition and deposition of air pollution in 2025, and focuses on main components in air and precipitation, particulate and gaseous phase of inorganic constituents, particulate carbonaceous matter, ground level ozone and particulate matter.
NILU
2026