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This study investigates the contamination of both ingested plastics and plasma of northern fulmars (Fulmarus glacialis) with benzotriazole UV stabilisers (BUVSs) in Kongsfjorden and Isfjorden, Svalbard. Ingested plastics were collected from fulmars in 1997, 2009, 2013, 2020 and 2021. Additionally, plasma samples were collected specifically in 2020. BUVSs, including UV-320, UV-326, UV-327, UV-328 and UV-329, were detected in both ingested plastics and plasma, suggesting a potential for transfer from plastics to the bloodstream. However, additional studies are required to confirm such a transfer mechanism. BUVSs were detected as early as 1997 in ingested plastics, highlighting the potential long-term exposure of fulmars in Svalbard. UV-326, UV-328 and total BUVS concentrations in ingested plastics increased significantly between 1997 and 2021, but likely due to outliers. In plasma, there was no significant correlation between any of BUVS concentrations and the mass of ingested plastics except for UV-327, although relying on only three values above LOD. This study represents a first step in investigating the multiple exposures of fulmars, and more generally seabirds, to plastic and plastic related chemicals and their potential ecotoxicological risks. More specifically we recommend further studies extracting microplastics from seabirds to perform additional quantification of BUVSs or other additives to provide available datasets and deeper understanding of leaching from plastics and temporal trends.
2026
Polluted air is a major global health risk factor, yet the chemical composition and toxicity of airborne gases and particles remain underexplored due to their complexity and difficulties in sampling. We recently introduced how polydimethylsiloxane (PDMS) foam─or silicone foam─can be synthesized for passive air sampling, enabling simple and cost-effective nontarget chemical profiling of indoor air. Here, we demonstrate expanded applications, indoors and outdoors, with commercial PDMS-foam, including for: (i) wide-scope target analysis of >220 priority substances by quantitative liquid- and gas chromatography-high-resolution mass spectrometry, (ii) microscopic characterization and nontarget profiling of accumulated fine particles, and (iii) effect-guided discovery of harmful substances, combining toxicological data with nontarget analysis in silico. Median method quantification limits were 0.12 ng/mL, 90% of target analytes had absolute recoveries between 70 and 130%, and hazardous substances were discovered, including ethylene glycols, insecticides, and UV filters. Microscopy revealed the accumulation of abundant fine particles, and the automated characterization of the fluorescent fraction revealed that most were <4 μm. Extracts from outdoor samples reduced human lung cell viability, and multivariate modeling flagged families of potentially toxic substances in a virtual effect-directed analysis. PDMS-foam disks require field calibration to determine their linear sampling rate(s), but current results and applications establish PDMS-foam as a multimodal passive sampler, enabling integrated chemical quantitation, toxicological analysis, and molecular discovery in air.
2026
Organic aerosol (OA) is a major component of atmospheric particulate matter (PM), affecting both human health and climate. However, high-resolution estimates of OA exposure needed for exposure analysis remain scarce. Here, we integrate a chemical transport model (CAMx) with a random forest (RF) machine learning approach to bias-correct and downscale daily OA concentrations across Europe. CAMx OA simulations at ∼15 km resolution show moderate agreement with observations (r = 0.55). By combining these outputs with high-resolution land-use data and training the RF model on ∼48,000 daily OA measurements from 137 sites, prediction accuracy improved (r = 0.65), with ∼l5% reduction in root mean square error. The resulting maps provide European daily OA concentrations at ∼250 m resolution for alternate years from 2011 to 2019. The model captures key spatial features, including elevated OA in the Po Valley, Southeastern, and Central Europe, as well as intracity variations due to local hotspots. Seasonal analysis reveals higher concentrations in winter, while long-term trends indicate a general decline in OA levels. Exposure estimates show that half of the European population experiences OA levels above 3 µg/m3, and ∼50 million people are exposed to more than 5 µg/m3, which is the current guideline level recommended by the world health organization for total PM2.5. These high-resolution OA maps offer vital critical support for epidemiological research and air quality policy.
2026
Organ-specific in vitro models for prediction of hazard assessment of nanomaterials
Organ-specific multicellular in vitro models are used to mimic the lung-blood-brain axis, and to assess the nanomaterials (NMs) safety in humans. We employed a triculture lung model, a whole-blood model, an astrocytes-neurons coculture to examine health outcomes by three cerium dioxide (CeO2) NMs and silver (Ag) nanowires. Endpoints included cytotoxicity, gene expression, genotoxicity, inflammatory markers at the air–liquid interface (ALI), complement activation, and secondary toxicity in astrocytes-neurons coculture. Post-exposure, CeO2–3.5 nm high-dose decreased cell viability, no DNA damage was detected. At epithelial-macrophages interface, CeO2–50 nm upregulated surfactant protein A (SPA), cell surface death receptor (FAS), and heme oxygenase-1 (HMOX1), whereas CeO2–3.5 nm downregulated SPA. Ag-nanowires upregulated HMOX1, macrophage inflammatory protein-1β (MIP-1β), granulocyte colony-stimulator factor (G-CSF), chemokine C-X-C-motif ligand 1 (CXCL1). At endothelial side, CeO2–50 nm and − 3.5 nm, and Ag-nanowires upregulated HMOX1. In whole-blood model, CeO2–3.5 nm high-dose reduced terminal complement complex (TCC) proteins, while CeO2–50 nm and Ag-nanowires increased them. Nanomaterials activated CD11b+ on granulocytes and monocytes. Ag-nanowires conditioned-medium (CM) on astrocytes-neurons coculture, decreased cell viability. CeO2–50 nm CM upregulated IL1β, NFκB, and HMOX1. Overall, CeO₂–3.5 nm exhibits lung toxicity; CeO₂–50 nm CM triggers inflammatory response and Ag-nanowires CM may induce cytotoxicity in brain cells.
2026
This study assesses trends in the total ozone column (TOC) and the atmospheric factors influencing ozone variability at three Antarctic stations (Marambio, Troll/Trollhaugen, and Concordia) from 2007 to 2023. Ground-based TOC measurements were used, supplemented by satellite observations from the Ozone Monitoring Instrument on NASA's Aura satellite. TOC trends were derived using a multiple linear regression model provided by the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) project. The selected LOTUS model was able to explain 94 %–97 % of the TOC variability at all three stations. The regression analysis showed that ozone variability at these stations is mainly driven by the lower stratospheric temperature, eddy heat flux, and the Quasi-Biennial Oscillation. A statistically significant increasing trend was found at the Marambio station (3.43 ± 3.22 DU per decade), while statistically insignificant trends were detected at the other two stations. Using MERRA-2 reanalyses, the LOTUS model was applied to each grid point in the 40–90° S region, which effectively illustrates the spatial distribution of the impacts of individual predictors. It was found that warmer conditions in the Antarctic stratosphere in September 2019 caused TOC to be up to 100 DU higher than normal, especially over East Antarctica. The results improve understanding of regional TOC trends and how the Antarctic ozone layer responds to changes in ozone-depleting substances.
2026
Exceptional high AOD over Svalbard in summer 2019: a multi-instrumental approach
In the summer of 2019, the Arctic region registered exceptionally high aerosol optical depth (AOD) values over Svalbard, linked to intense biomass burning (BB) and volcanic activity across the Northern Hemisphere. This study presents a comprehensive, multi-instrumental analysis of the aerosol conditions in and around Ny-Ålesund (Spitsbergen, Norway), combining data from ground-based sun-photometry, in-situ observations, active remote sensing (ground-based and on satellite), and atmospheric dispersion modelling (FLEXPART). Despite high AOD was observed during all the period, three different aerosol events are identified in the atmospheric column (6–10 July, 25–28 July, and 6–17 August). In contrast, in-situ surface stations only recorded significant aerosol load during 5–9 July, 30 August, and 12 September, suggesting that most of the aerosol particles remained above the boundary layer. Lidar and photometric observations revealed the presence of spherical, weakly absorbing Accumulation-mode particles (with effective radii between 0.1 and 0.2 µm) in both the troposphere and stratosphere, with persistent layers extending above 10 km. Simulations carried out with FLEXPART correlate well with the measurements, attributing the observed aerosol events to multiple sources, including Siberian and North American wildfires, the Raikoke (Russia) volcanic eruption, and anthropogenic pollution. While the simulations show a contribution from volcanic aerosols, the contribution from biomass-burning aerosols in the upper troposphere and lower stratosphere were likely more significant under the atmospheric conditions of summer 2019. Overall, the aerosol radiative impact during this long-lasting event was substantial, with a mean reduction in direct solar radiation of approximately −74 W m−2 during July and August. This work shows how the use of dispersion modelling together with multiple observation sources allows to achieve a more complete description of the atmospheric aerosol events and contributes to a better understanding of the overall picture.
2026
A multi-year analysis of aerosol optical depth (AOD, τ) and Ångström exponent (α) was conducted using ground-based photometer data from 15 Arctic and 11 Antarctic sites. Extending the dataset of (Tomasi et al., 2015) through December 2024, the study incorporates stellar and lunar photometric observations to fill data gaps during the polar night. Daily mean values of τ at 0.500 µm and α (0.440–0.870 µm) were used to derive monthly means and seasonal histograms. In the Arctic, persistent haze events in winter and early spring lead to peak τ values. A decreasing trend in Arctic τ suggests the impact of European emission regulations, while biomass-burning aerosols are becoming more significant. In Antarctica, τ increases from the plateau to the coast. Fine-mode aerosols dominate in summer-autumn, while coarse-mode particles are more prevalent in winter-spring. Shipborne photometer data align well with ground-based measurements, confirming the reliability of mobile observations. Trend analyses using the Mann-Kendall test and Theil-Sen regression indicate a significant negative trend in τ at Andenes (−2.43 % per year), likely driven by reduced anthropogenic emissions. Antarctic stations such as Syowa and South Pole show positive trends (+3.84 % and +3.54 % per year), though these are subject to uncertainties from data limitations and instrument changes. This work contributes to the Polar-AOD network (https://polaraod.net/, last access: 15 May 2025), enhancing the understanding of aerosol variability and long-term trends in polar regions while promoting open data access for the scientific community.
2026
Abstract Potato plants are highly vulnerable to numerous diseases that can substantially affect both yield and quality. Conventional approaches for detecting these diseases are often labor-intensive, slow, and prone to inaccuracies, particularly under variable environmental conditions. This study presents a hybrid deep learning architecture, termed potato leaf diseases DenseNet (PLDNet) , which integrates a DenseNet-based convolutional neural network with a Transformer-based attention module to accurately classify potato leaf diseases. Furthermore, an adaptive parametric activation function, referred to as Adaptive Flatten p-Mish (AFpM) , is proposed to enhance the model’s learning flexibility and representational capacity. When evaluated on the PlantVillage and Mendeley datasets, PLDNet attains classification accuracies of 99.54% and 87.50%, respectively, surpassing contemporary state-of-the-art models and activation techniques. The proposed framework exhibits strong generalization performance and offers a scalable, efficient approach for automated plant disease identification. To highlight the novelty, the proposed AFpM activation function introduces a learnable parameter enabling adaptive nonlinearity, improving over Mish, Swish, and PFpM activation functions through dynamic gradient control. AFpM improves accuracy by 2.52% on Mendeley dataset, and 1.93% on PlantVillage dataset compared to PFpM, and by more than 3% compared to Swish and Mish.
2026
City-produced and transported black carbon: Synergy of in-situ optical measurements and modeling
The implementation of air pollution mitigation strategies requires not only high-quality continuous measurements of pollutants but also proper definitions of ways to differentiate between transported and locally produced contributions, as only the latter can be effectively reduced by authorities. To address this issue, we propose a new approach for partitioning monitored black carbon (BC) concentrations into city-produced (urban) and transported fractions using a combination of measured and modeled data. Two simultaneous measurement campaigns (warm season 2022 and cold season 2022/23) were conducted in two urban environments: Vilnius (Lithuania) and Warsaw (Poland). In the cold season in Warsaw, BC mass concentration was 90% higher than in the warm season, while in Vilnius, an increase of 44% was observed, as compared to the warm season. Aerosol optical properties showed more complex aerosol mixtures of dust, BC and brown carbon (BrC) during the cold season, forming larger particles. Single scattering albedo (SSA) anti-correlated with BCFF, proving that fossil fuel (FF) combustion contributes to the warming effect in both cities. A positive correlation between the population density of the emission areas of transported BC and the BC mass concentrations in Vilnius and Warsaw was found. The impact of transported BC on the local BC levels in the cities was of % and % in the cold season and of % and % in the warm season for Warsaw and Vilnius, respectively. Thus, the approach of BC partitioning showed that in the cold season, the two cities suffered from worse air quality, in part due to more transported BC.
2026
Boreal forests at risk: Absence of climate perspectives in current management policies
Boreal forests influence climate both biogeochemically through carbon uptake and biogeophysically through evapotranspiration, turbulent fluxes and albedo, and are in turn impacted by climate through biotic and abiotic damages. This systematic literature review and qualitative narrative policy review and analysis aims to get a better insight into the discrepancy between policy and science on forestry action to mitigate climate warming in high latitude jurisdictions. We identify climate effects on and from forests with corresponding management options in a systematic review of scientific literature following PRISMA guidelines. These results were combined with a qualitative policy review and analysis to identify the climate and forestry policies from all boreal-to-Arctic jurisdictions and determine how (many of) these climate effects ended up in forest and climate policy. There is mounting evidence that in boreal regions, albedo-driven warming can partially offset, and in some contexts be comparable to, carbon-driven cooling; the balance varies by season, forest type and disturbance history. However, although all analysed jurisdictions (Alaska, Canada, European Union, Sweden, Finland, Iceland, Norway and Russia) recognise the forests' role in carbon uptake, none recognise the albedo effect, and none translate these climate effect into binding regulatory measures. Nor do most of the jurisdictions take into account possible risk of climate-related damages. This might lead to ineffective and even adverse forest and climate measures. Our study emphasises a need for more evidence-based and comprehensive climate and forestry policies and regulations, along with a proactive approach to adopting these measures swiftly.
2026