Fant 939 publikasjoner. Viser side 1 av 40:
Classification of Radar Zones on Selected Glaciers in Ny-Ålesund, Svalbard
Glacier facies are characteristic properties of glaciers that are an observable and mappable determinant of their health. The occurrence and distribution of facies depend upon several contributing factors such as climatic shifts, sudden events, temperature, precipitation, overall deglaciation, etc. Seasonal variations of facies in one year and annual variations across several years are effective markers of seasonal and long-term glacial evolution. Synthetic aperture radar (SAR) allows for efficient generation of seasonal data within multilayer composites which can be exploited for mapping facies. In this study, we utilized Sentinel-1 data to create seasonal composites from 2016-2023 and mapped facies of selected glaciers, in Ny-Ålesund, Svalbard. We utilized unsupervised classification to obtain facies maps in a data-centric approach. This involved modulating the number of output thematic classes across sets of 3, 5, and 7, as well as changing the spatial extent from multiple glaciers to a single glacier in the classification workflow. Thematic classification revealed mixed clusters across all years and polarizations. Our analysis suggests that seasonal variability of facies leads to mixed signals within a single pixel causing misclassification. Additionally, the spatial extent of the input data drives fluxes in thematic mapping, suggesting that changes in local and global raster statistics can limit spatial scale transferability of a mapping workflow. The present results place thematic classification of glacier facies into a practical context for future applications. Our upcoming experiments will include a longer time-series, various polarizations, and advanced information extraction methods, leading to improved understanding of the operational applications of seasonal SAR data for mapping glacier facies.
2026
Urban areas face growing challenges in ensuring equitable access to essential amenities amid increasing populations and resource constraints. Active mobility modes, including walking and cycling, offer sustainable solutions to these challenges but are significantly influenced by environmental factors. This study introduces a comprehensive framework for evaluating the spatial equity of urban active mobility, defined in this study as the fair spatial distribution of segment-level walkability and bikeability along with neighborhood-level accessibility. Using Oslo, Norway, as a case study, the framework assesses pedestrian and bicycle networks. Accessibility to key amenities was evaluated using a cumulative opportunities approach. Results reveal that approximately 23.5% of Oslo’s population experience active transport inequity, with limited access to well-scored mobility routes. The analysis also showed that over 50,000 individuals reside in areas where detours do not yield a feasible improvement in the active travel experience, resulting in another form of active mobility inequity. By identifying areas where infrastructure improvements can enhance active travel and accessibility, this framework provides insights to promote equitable mobility systems.
2026
Geometrid moth outbreaks are important natural disturbances in mountain birch (Betula pubescens ssp. czerepanovii) forests of northern Fennoscandia and are expected to intensify with climate change. Impacts of these outbreaks and moth herbivory on biogenic volatile organic compound (VOC) emissions of birch remain unquantified despite the importance of VOCs in plant-herbivore interactions and atmospheric chemistry. Here, we quantify in situ VOC emission responses of mountain birch (n = 256) to naturally increasing geometrid herbivory across three consecutive growing seasons. We show that VOC emissions increased with rising herbivore pressure across the years, culminating in the outbreak, during which early-season VOC emissions were higher than at peak herbivory. At peak herbivory, birch emitted more complex VOC blends, indicating seasonal shifts in composition. Following the outbreak, a second leaf flush sustained emissions of some VOCs. Our findings demonstrate that VOC emission rates and compositions are dynamically linked to leaf phenology and herbivory intensity across multiple years.
2026
Substantial efforts and improvements in air quality across Europe lowered levels of air pollutants including particulate matter (PM) in the last decades. However, significant proportion of the European population still lives in areas exceeding WHO recommendations, especially in Northern Italy, Balkans, and Eastern Europe, including Serbia. Targeted PM mitigation strategies require extensive air quality monitoring and modelling including source apportionment (SA) studies. In the past, numerous SA studies were conducted for Belgrade city, capital of Serbia. Nevertheless, comparisons across the results are difficult, as they encompass different datasets of pollutants contained in PM fractions such as elements and/or ions and/or PAHs. Here, the aim is to offer a broader insight on PM 10 sources at an urban background site in Belgrade by including 34 species as input variables for SA (carbonaceous aerosols, elements, ions and specific organic tracers). For SA, the USEPA PMF 5.0 software was applied. The factor that dominated PM 10 mass was biomass burning (21 %), primarily during heating season, followed by ammonium sulphate (18 %) and mineral dust (17 %). A mixed traffic and industrial activity accounted for 15 % of PM 10 mass while contribution of factors from biological origin, primary biological aerosol particles and biogenic secondary organic aerosols from isoprene, was 10 % each. Mixed factor of long-range transport and road salt/local combustion contributed to the PM 10 mass 9 %. This analysis provides more detailed perspective on the composition and sources of PM 10 in Belgrade, both from anthropogenic and natural, including biological origin. These findings are valuable for defining targeted PM 10 mitigation strategies.
2026
Background
Tire wear particles release additives and transformation products into the environment. Among these, p-phenylenediamines (PPDs) and their quinone transformation products (PPD-Qs), including 6PPD-Q, have attracted increasing attention. However, data on tire wear contaminants (TWCs) in Central and Eastern Europe remain limited, and their hydrolytic stability is poorly characterized. This study investigated the hydrolytic stability of 16 TWCs, optimized sample pre-treatment, and assessed their occurrence and preliminary ecological risks in water and soil samples from northern Poland.
Results
Under OECD Test Guideline 111 conditions, parent PPDs generally showed lower hydrolytic stability than PPD-Qs. Ten TWCs were detected in soils, with benzothiazole (BTH) reaching 387 ng/g, whereas all target analytes were detected in water, with 6PPD-Q occurring at 1.85–297 ng/L and BTH at up to 326 ng/L. Moreover, PPD-Qs predominated over parent PPDs in water, whereas the opposite pattern occurred in soils. Additionally, sites subject to greater traffic influence generally showed more complex TWC profiles. A preliminary environmental risk assessment based on measured concentrations indicated that 6PPD-Q posed high ecological risks at all water sites.
Significance
This study provides the first dataset on TWC occurrence in surface waters and soils in Poland. The findings demonstrate the environmental relevance of PPD transformation products and support their inclusion alongside parent tire additives in environmental monitoring and risk assessment. The observed ecological risk associated with 6PPD-Q further highlights the need for continued monitoring of tire-derived contaminants in Polish aquatic environments.
2026
Revised direct radiative forcing of airborne microplastics suggests warming
Microplastics are a common airborne pollutant, capable of being transported over large distances and with potential to alter the radiative properties of the atmosphere in large enough quantities, with implications for global climate. Since the first estimates of microplastic radiative forcing were published in 2021, new constraints on many aspects of the spatial and temporal distribution of airborne plastics and their physical and optical properties have emerged. Using these updated findings concerning the size distribution of airborne microplastics, new spectral absorption data for coloured plastics, and a new microplastic emissions dataset, we investigate the sensitivity of the direct radiative effect of airborne microplastics. We find clear-sky effective radiative forcings ranging from −3.28 to +46.7 mW m−2 depending on assumptions concerning colour, size distribution, vertical profile and spatial distribution. Assuming likely real-world conditions—a mix of coloured microplastics, a power law size distribution and distributing microplastics non-uniformly through the troposphere based on a new emissions dataset—we calculate an updated estimate of +42.1 ± 4.62 mW m−2 for a global-average surface concentration of 3.99 microplastics m−3. This revised radiative forcing is at least as large in forcing magnitude as the contributions of a number of other species routinely evaluated by the Intergovernmental Panel on Climate Change. Our findings suggest that microplastics are likely contributing to atmospheric warming and, given that plastic pollution is projected to increase, should be included in climate change projections.
2026
Coarse-mode aerosol particles influence the environment, climate, and human health in diverse ways depending on their type. While mineral dust and sea spray aerosol (SSA) dominate this size range, rarer biological particles can have outsized impacts, such as initiating hydrometeor freezing at relatively warm temperatures. Accurate type-specific characterization of coarse-mode aerosol is therefore essential for investigating their roles in climate and the environment. We provide a new reference dataset for fluorescence spectra and morphology characteristics of coarse-mode aerosols from common sources, including pollen, dust, bacteria, and microplastics, measured in controlled experiments with a Multiparameter Bioaerosol Spectrometer (MBS). Comparisons with published datasets revealed consistent source-dependent fluorescence features, but also highlighted similarities between biological and non-biological particles that can bias fluorescence-based classifications.
To explore solutions for these confounding similarities, we developed a supervised machine learning classification algorithm integrating fluorescence and morphology information, and evaluated it using MBS and comprehensive chemical tracer observations from Zeppelin Observatory, Svalbard. This evaluation illustrates challenges for inductive methods in distinguishing biomass burning from biological particles, and dust from SSA, suggesting that important particle classes may be missing and/or laboratory-generated aerosols significantly differ from real-world counterparts. We show that domain adaptation using complementary observations can help address these difficulties. Compared to a fluorescence-only approach, the domain-adapted algorithm reproduces the previously published annual bioaerosol cycle while yielding higher summertime concentrations matching those reported from offline analyses. This open-source algorithm provides a basis for quantifying bioaerosols across diverse environments and can be refined with future field and laboratory efforts.
2026
Constraining methane (CH4) emissions at high spatial and temporal resolution is critical for accurate European greenhouse gas budgets and mitigation policy. We use the Community Inversion Framework to estimate monthly CH4 fluxes across Europe (2017–2022) at 0.2°×0.2°, coupling FLEXPART and assimilating observations from 46 in situ stations, including Integrated Carbon Observation System (ICOS) and non-ICOS sites. Prior emissions combine anthropogenic inventories, biomass burning estimates, wetland models, and climatological natural sources. The inversion substantially improves agreement with atmospheric observations (r2=0.87, RMSE=24.4 ppb, mean bias=2.1 ppb), performing best at northern European stations. For the European Union countries, together with the UK, Norway, and Switzerland, we estimate total methane emissions of 23.3±2.3 Tg CH4 yr−1, which is 6.6 % higher than the prior. For these countries, we found an average anthropogenic emissions of 17.6 Tg CH4 yr−1, with a decreasing trend of 0.3 Tg yr−1. This estimate exceeds the prior by 11 %, EDGARv8 by 4 %, and UNFCCC NGHGI (2023) by 3 %, while remaining consistent with recent studies. Country-level differences are notable, with higher emissions estimated for the Netherlands and Germany, and lower for Romania and Italy. Sectoral changes mainly reflect agricultural increases, alongside reductions in northern wetlands and southern geological sources. Sensitivity tests highlight the influence of spatial spread of emissions distribution assumptions and the importance of dense observational networks for refining regional CH4 budgets.
2026
Proton therapy is increasingly used, due to its favourable physical properties such as the Bragg peak, which enable precise dose deposition while minimizing exposure to surrounding healthy tissues. One of the main indications for proton therapy is head and neck tumours. In addition to their therapeutic relevance, protons are also a key component of space radiation spectrum, raising concerns about their biological impact on normal tissues, particularly the central nervous system. Despite this growing concern, the effects of proton irradiation on adult post-mitotic neurons in vivo remain poorly understood. In this context, we analysed the impact of proton central nervous system micro-irradiation using the MIRCOM microbeam, in young adults of Caenorhabditis elegans, with a focus on DNA damage and behaviour. Protons induce localized oxidative DNA damage, confirmed by an increase in 8-oxoG signals within both the nuclei and cytoplasm of irradiated neurons. The biological response remained strictly confined to the targeted area; no signal propagation or damage was observed in neighbouring non-irradiated tissues. Despite molecular changes, there was no observable impact on behaviours such as motor activity, foraging, habituation, or touch-avoidance. These results suggest that proton exposure in post-mitotic neurons induces complex oxidative DNA damage and activates specific BER pathways without compromising functional behaviour or triggering systemic bystander effects. These insights are important for refining clinical radiation protection and understanding risks in space exploration.
2026
2026
Assessment of the extremely low TOC at three European stations during February 2023
Exceptionally low total ozone column (TOC) values were observed over Europe in February 2023, affecting both Arctic and mid-latitude regions. This study investigates the evolution and underlying mechanisms of this low-ozone episode by integrating ground-based observations, satellite measurements, and atmospheric reanalysis data. Daily TOC data from Andøya, Oslo/Kjeller, and Hradec Králové are complemented by multi-sensor reanalysis products and vertically resolved measurements from the Microwave Limb Sounder (MLS). The lowest TOC values occurred on 14 February 2023, when all three stations recorded anomalies below the 2σ climatological threshold. This period coincided with a cold stratospheric polar vortex, which promoted the formation of polar stratospheric clouds and subsequent chemical ozone loss. MLS observations reveal pronounced decreases in HNO3 and HCl, accompanied by enhanced ClO concentrations, indicating active halogen-driven ozone loss. The strongest chemical ozone depletion was observed over Scandinavia and later extended toward Central Europe. In addition to chemical processes, dynamical factors significantly contributed to the observed TOC reduction. Elevated tropopause heights and the transport of ozone-poor air from lower latitudes further reduced TOC, particularly over Central Europe. The results demonstrate that the February 2023 low-ozone event arose from the combined effects of chemical ozone loss within cold polar vortex air and large-scale dynamical processes, emphasizing the importance of integrated chemical–dynamical analyses for understanding extreme Arctic ozone events.
2026
Assessing Earth system responses arising from carbon dioxide removal (CDR) requires developing and simulating pairs of scenarios – a mitigation scenario with deployment of CDR and a corresponding no-CDR baseline. The latter describes a world where no CDR is deployed, such that net carbon emissions are higher and a given temperature target may be missed. While over the past years a rich literature on mitigation scenarios with CDR has been emerging, no-CDR baselines have mostly been explored in stylized Earth system model (ESM) experiments. In such simulations, a no-CDR baseline simply assumes that CDR is “switched off”, while socio-economic constraints are not considered. However, the deployment of CDR in mitigation scenarios, created by integrated assessment models (IAMs), is embedded in a consistent socio-economic description of plausible futures, and disallowing CDR may affect climate drivers due to changes in the energy system and in land-use dynamics. Particularly, when moving towards an activity-driven representation of CDR in emission-driven ESMs, where the activity that draws down CO2 from the atmosphere is explicitly modelled, the creation of no-CDR baselines comes with challenges and trade-offs. Here, we conceptualize a framework for emission-driven ESM simulations of IAM scenarios that allows us to determine carbon-cycle feedbacks and biogeophysical effects of CDR deployment using no-CDR baselines. We show that different options exist for the creation of no-CDR baselines, which offer different insights and have their specific advantages and limitations. We also demonstrate that internal variability of the climate system inherently limits our ability to detect the small signals related to CDR deployment and its feedbacks. Hence, unless a sufficiently large initial conditions ensemble is employed, stylized modelling approaches may remain preferable for some applications, e.g., the quantification of regional biogeophysical effects of CDR deployment. Both, the efficiency of CDR (defined as CO2 removed per unit of resources employed) as well as related carbon-cycle feedbacks and biogeophysical effects are expected to be scenario- and model-dependent. Our simulation design of concentration- and emission-driven no-CDR baselines, together with an improved representation of CDR in the IAM – ESM modelling chain, opens an avenue towards estimating CDR efficiencies and their uncertainties under various future scenarios in upcoming model intercomparison activities.
2026
Assessing the mutagenicity of chemical compounds is essential for ensuring their safe handling and use, thereby minimizing potential health risks. New approach methodologies (NAMs), including computational approaches, provide non-animal alternatives for testing novel materials and chemicals. This study highlights the potential of in silico NAMs, which can contribute to the development of novel Safe and Sustainable by Design (SSbD) chemicals and substances by identifying potentially hazardous ones at an early stage. Emphasis is given to the mutagenicity prediction based on data from the Ames (bacterial gene mutation) test curating them to consider stereo-specific input whenever necessary. A consensus strategy integrating different chemical representations (molecular fingerprints, 2D and 3D descriptors and molecular graphs) and modelling methods, i.e., Quantitative Structure–Activity Relationship (QSAR), read-across and deep learning models, is employed to predict the mutagenic profile of chemical compounds. In this course, a XGBoost model is developed based on molecular descriptors and a graph convolutional neural networks model to classify compounds as mutagens and non-mutagens based on the Ames test data. The devised read-across methodology is based on a guided-k-Nearest Neighbours scheme (guided-kNN) where two different molecular representations (molecular fingerprints and descriptors) are considered for neighbour selection and predictions generation. The mutagenicity predictions from the three models are integrated in a majority voting scheme to enhance the overall predictive accuracy (83% in external validation) and reduce individual model biases. Interpretation of the descriptors involved in prediction is performed through explainable AI (XAI) methods to provide insight to the mutagenicity mechanism. To enhance the interpretability of the XAI-derived insights and reinforce user confidence in the models' predictions, the involved descriptors are mapped to key events leading to mutations within the Adverse Outcome Pathway (AOP) networks. Apart from the development of reliable and interpretable mutagenicity models, emphasis is given on delivering a pipeline for the generation of 3D descriptors that can be used as the basis for future cheminformatics models. To support transparency and reproducibility of the results of our work, the curated mutagenicity dataset used for modelling is disseminated through the ChemPharos database (https://db.chempharos.eu/datasets/Datasets.zul?datasetID=ds18), the modelling steps are documented following the standardized Modelling Data (MODA) guidelines and the consensus model is freely available via the Enalos Cloud platform (https://www.enaloscloud.novamechanics.com/insight/polis/), to facilitate virtual screening of novel compounds.
2026
Quantifying the Spatio-Ecological Context of Urban Nature-Based Solutions Across European Cities.
Nature-Based Solutions (NBS) are increasingly implemented to address urban environmental challenges, yet the surrounding spatial context in which they are embedded may influence the conditions supporting their ecological functioning. This study applied an integrated remote sensing-based spatial diagnostic framework combining Sentinel-2 spectral indices and land-cover composition metrics to characterize and compare the surrounding environments of five NBS sites in Oslo, Riga, Milan, St. Gallen, and Lublin. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), and Normalized Difference Built-Up Index (NDBI) were analyzed within 100 m, 300 m, and 500 m buffer zones alongside land-cover composition assessments. The analysis revealed substantial variation in vegetation greenness, moisture conditions, built-up intensity, and landscape composition. Three spatial-context profiles were identified: low-density/peri-urban settings, exemplified by the Riga NBS site with consistently high NDVI (0.483–0.374), positive NDMI (0.230–0.171), and strongly negative NDBI (−0.230 to −0.171); mixed urban settings, represented by the Oslo, Lublin, and St. Gallen NBS sites; and dense urban settings, represented by the Milan NBS site, which exhibited the lowest NDVI (0.197–0.124), declining NDMI (0.054 to −0.014), and positive NDBI beyond 300 m (0.001–0.014). These findings demonstrate that surrounding landscape characteristics provide a meaningful basis for distinguishing urban NBS settings. The proposed replicable framework can support context-sensitive planning by identifying areas where complementary landscape-scale measures, including de-paving, strategic greening, and improved landscape connectivity, may be considered to strengthen the broader environmental conditions surrounding NBS.
2026
Northern fulmars (Fulmarus glacialis) are pelagic seabirds prone to ingesting plastics. Ingestion of plastic particles can have both physical and chemical impacts, although these effects are poorly understood. This study investigated scar tissue formation and thyroid disruption in relation to plastic ingestion. Abundance of ingested plastic types and polymers, and liver concentrations of plastic-related chemicals (PRCs; including plastic additives, production aids and adsorbed environmental contaminants) were determined. A total of 14 (N = 15, 93.3%) of the fledglings exceeded the EcoQO threshold (containing more than 0.1g of plastic). None of the quantified PRCs appeared to be reliable proxies for plastic ingestion. Only the plastic type “Industrial” (i.e., pellets/“nurdles”, distinct from plastic derived from industry-specific activities, such as fisheries) showed a significant positive correlation with per-/poly-fluoroalkyl substances (PFAS) in liver. Regardless of plastic exposure, some PFAS compounds showed significant negative correlations with the ratio between total and free thyroxine (TT4:FT4), while other PFAS and some polybrominated diphenyl ethers (PBDEs) showed significant positive correlations with total 3-triiodothyronine (TT3) and the ratio between total and free T3 (TT3:FT3). Most histological observations of scar tissue were classified as “moderate” and no correlation was observed between collagen prevalence (or scar tissue severity) and plastic ingestion. However, some PBDEs and PFAS showed positive correlations with collagen prevalence. Finally, thyroid hormones tended to be negatively correlated with collagen prevalence. Together with uptake from prey as an important exposure pathway for PRCs, uptake from plastic is a probable additional route. In conclusion, we hypothesise that the presence of PRCs, potentially originating from industrial plastic, may induce a thyroid-disrupting effect. However, as total plastic mass was not correlated with PRCs, other exposure routes, are likely important for the contaminant burden in the majority of the fulmar fledglings. The impact of plastic ingestion on collagen prevalence remains unclear.
2026
2026
Promoting healthy lifestyle behaviors, including physical activity, sleep, diet, stress management, and healthy habits, requires adaptive systems capable of responding to dynamic changes in human behavior. Sustained behavioral change improves individual wellbeing, reduces disease risk, and contributes to healthier societies. However, developing personalized behavioral intervention systems is challenged by demographic heterogeneity, limited and fragmented datasets, reporting inconsistencies, and scarce high-quality labeled data. Ethical, privacy, and cost constraints further restrict the collection of large-scale longitudinal behavioral data. Consequently, there is a need for robust simulation and synthetic data generation frameworks that enable the development and evaluation of adaptive decision-making systems capable of optimizing personalized behavioral interventions over time. This study presents a digital twin framework integrated with tabular Q-learning for personalized behavioral recommendation under World Health Organization (WHO) lifestyle constraints. The framework combines synthetic behavioral data generation, reinforcement learning, and a TSP-inspired planning mechanism to investigate long-term behavioral adaptation in privacy-preserving simulated environments. The digital twin environment models user adherence variability, misreporting, dropout, and behavioral drift, enabling the evaluation of intervention strategies under realistic conditions. Experimental evaluation on synthetic populations demonstrates that Q-learning achieves competitive reward performance while maintaining favorable computational efficiency and stability compared with heuristic and reinforcement learning baselines. Statistical analysis indicates that reward differences among the evaluated methods are not significant; however, the proposed framework provides a flexible platform for adaptive behavioral recommendation and simulation-based experimentation. Furthermore, a real-time recommendation interface illustrates how simulation knowledge can be translated into actionable behavioral guidance. The proposed framework offers a scalable foundation for future digital health systems, particularly in scenarios where data scarcity, privacy constraints, and personalization requirements limit the use of real-world datasets.
2026
Parametric life cycle assessment of asphalt pavements with probabilistic lifetimes and traffic
This study combines established methods – parametric LCA, probabilistic pavement lifetime modelling, traffic-volume characterization, and Monte Carlo simulation – into a service-based decision-support framework for asphalt pavement assessment. The framework evaluates environmental impacts not only per unit mass, but also in relation to pavement service life and traffic exposure, expressed as impact/(yr·AADT). Results indicate that binder type, asphalt plant efficiency, and transport distances are dominant contributors to environmental impacts. Incorporating probabilistic lifetimes and traffic loads reshapes environmental rankings, revealing that longer lifetimes do not always equate to lower burdens. These findings provide data-driven insights for reducing the environmental impacts of road construction and maintenance.
2026
For the first time, we present long-term, ongoing atmospheric measurements of 1,2-dichloroethane (DCE, CH2ClCH2Cl) from the Advanced Global Atmospheric Gases Experiment (AGAGE) and National Oceanic and Atmospheric Administration (NOAA) global monitoring networks. DCE is an industrially produced, very short-lived chlorinated substance (Cl-VSLS) that has the potential to contribute chlorine to the stratosphere and cause ozone depletion. Compared to other Cl-VSLS, DCE is produced in higher volumes for its primary use as a feedstock in polyvinyl chloride (PVC) manufacture. This production has sustained annual mean mole fractions at the Earth's surface of between 5 and 10 ppt during 2017–2023, making it the third most abundant Cl-VSLS after dichloromethane and chloroform. In this study we estimate mean global emissions for 2017–2023 of 453 ± 185 Gg yr−1 using the AGAGE observations, and 525 ± 209 Gg yr−1 using the NOAA observations. We also use AGAGE measurements to estimate regional emissions for northwest Europe (2.06 [1.31, 2.65] Gg yr−1) and California (0.23 [0, 0.37] Gg yr−1), two domains with sufficient observational coverage to enable this approach. Our global emissions estimates are consistent (within uncertainties) with the only previously published estimate by Hossaini et al. (2024), whereas our regional emissions estimates are at least an order of magnitude smaller than those in that study. This suggests global total emissions may be well constrained, but their spatial distribution remains uncertain.
2026
First evidence of nanoplastics in Antarctica soil
Plastic contamination has become a global concern, with evidence even in remote regions like Antarctica. While macro- and microplastics have been documented in Antarctic marine ecosystems, their presence in soils - particularly submicro- and nanoplastics - remains poorly studied. This study analyses soil samples from the McMurdo Dry Valleys collected on January 8th to 28th, 2023, and reports the first detection of nanoplastics - including polypropylene, polyethylene, polyethylene terephthalate, polystyrene, polyvinyl chloride, and tyre wear particles - using thermal desorption proton transfer reaction mass spectrometry. These plastics were detected at multiple topsoil sampling sites (n = 13), with concentrations reaching up to 295 ng g⁻¹ with nanoplastics detected above polymer-specific method detection limits at 54% of sites (median: 26.6 ng g⁻¹). They were also detected at lower concentrations in deeper soil layers (> 20 cm; n = 4), where nanoplastics were present at 50% of the sampled sites (median: 1.95 ng g⁻¹). Lagrangian particle dispersion model FLEXPART suggested seasonal deposition patterns, with inputs from both local sources and long-range atmospheric transport. This evidence shows that soils in one of Earth’s most pristine environments are not exempt from plastic contamination, with the reported concentrations providing a crucial baseline for global pollution assessments. These findings also highlight the urgent need to study plastic fate, transport, and ecological impacts in polar regions.
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
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