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Disentangling atmospheric transport and mixing processes over mountains: overview of the preliminary field campaigns of the project DECIPHER

Rajput, Akanksha; Barbaro, Elena; Barbano, Francesco; Bracci, Alessandro; Cairns, Warren R.L.; Carpentari, Sebastiano; Cassiani, Massimo; Cozzi, Giulio; Blasi, Fabrizio de; Fabrizi, Costanza Di Felice; Girolamo, Paolo Di; Dionisi, Davide; Paolantonio, Marco Di; Sabatino, Silvana Di; Doglioni, Giorgio; Favaro, Eleonora; Finco, Angelo; Gabrieli, Jacopo; Gerosa, Giacomo; Giovannini, Lorenzo; Marzuoli, Riccardo; Nardon, Christian; Plebani, Davide; Poggi, Davide; Porcù, Federico; Rossetti, Claudia; Sankar, Mira Shivani; Summa, Donato; Vendrame, Nadia; Zardi, Dino

2026

Characterization of the atmospheric microbiome in a semi-rural area of Central Europe using flow cytometry

Abboud, Ernest; Rossi, Pierre; Crouzy, Benoit; Evangeliou, Nikolaos; Nenes, Athanasios; Violaki, Kalliopi

Characterizing bioaerosols is important for understanding their potential impacts on the environment and public health. In this study, we developed a novel flow cytometry-based approach to determine the low nucleic acid (LNA), high nucleic acid (HNA), dead, and intact bioaerosol populations in samples collected with a wet cyclone at Payerne, Switzerland, during spring and summer 2024. We found that the average bioaerosol number concentration reached (2.47 ± 3.35)×104 m−3. The HNA and intact populations were the most abundant populations, representing the largest fraction of total bioaerosols within 65% and 97% of the samples, respectively. Our results show that the LNA can be composed of dead bioaerosols, which correlated strongly with atmospheric particulate mass. Quantitative Polymerase Chain Reaction (qPCR) and metagenomic analysis reveal significant correlations and associations (Spearman, PERMANOVA, and Mantel) between the different kingdoms analyzed, reflecting complex ecological interactions in the atmosphere among the communities. Despite this complexity, LNA was mainly associated with the archaea Nitrososphaerota and bacteria Actinomycetota, whereas HNA was enriched by fungal classes such as Pichiomycetes and Ustilaginomycetes. Pollen abundance was positively correlated with temperature and negatively correlated with relative humidity and pollution (NOx and NO2), as these conditions promote the formation of sub-pollen particles (pollen fragments) through osmotic (bursting) and oxidative stress. Factor analysis indicates a seasonal dynamics transition from plant-associated bioaerosols in the spring season, to other bioaerosol types to be co-emitted during summer. Overall, the integration of flow cytometry with molecular analysis provides a framework to characterize and quantify bioaerosols and provides new insights into the ecological structure, variability, and sources of the atmospheric microbiome.

2026

HTAP3-OPNS: ozone, PM, nitrogen and sulphur deposition – multi-model experiments to support the revision of the CLRTAP Gothenburg Protocol

Butler, Tim; Ansari, Tabish; Belis, Claudio A.; Bergas-Masso, Elisa; Caspel, Willem van; Fagerli, Hilde; Flemming, Johannes; Vivanco, Marta Garcia; Griffiths, Paul; Hamilton, Douglas S.; Trujillo, Coralina Hernandez; Höglund-Isaksson, Lena; Huijnen, Vincent; Kaiser, Johannes W.; Koren, Gerbrand; Klimont, Zbigniew; Lindl, Florian; Lupascu, Aura; Mertens, Mariano; Schaap, Martijn; Turnock, Steven T.; Wild, Oliver; Weiss, Philipp; Kaminski, Jacek; Wu, Rosa; Keating, Terry

HTAP3-OPNS is a multi-model exercise designed to support the revision of the Gothenburg Protocol under the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). Using an ensemble of Chemical Transport Models (CTMs) and Chemistry-Climate Models (CCMs), this study investigates the long-range transport and impacts of ground-level ozone, particulate matter (PM), and nitrogen and sulphur deposition across different global regions. The project aims to assess the contributions of regional versus extra-regional emission sources, evaluate the suitability of current models, and project changes in air pollution under future emission scenarios and climate conditions. A series of perturbation simulations will enable the development of an ensemble emulator to explore and evaluate potential mitigation strategies efficiently. This paper outlines the scientific and policy questions motivating the study, describes the experimental design, including input datasets, model configurations, and required outputs, and discusses methodologies for data handling and analysis. The results will provide crucial insights for policy decisions aiming to improve air quality, protect human health, and protect ecosystems worldwide.

2026

Influence of Upper Tropospheric and Lower Stratospheric Conditions on the March–April Total Ozone Column at Norwegian Stations (2000–2024)

Tichopád, David; Láska, Kamil; Čížková, Klára; Svendby, Tove Marit; Fioletov, Vitali E.; Vorobeva, Ekaterina

2026

Quantifying the potential of digital innovations to advance circular economy in consumer and industrial goods

Boero, Riccardo; Hernandez, Miguel Las Heras; Guerreiro, Cristina

Non-Technical Summary
Digital Product Passports (DPPs) could help make products easier to repair, refurbish, and recycle by improving access to information about their materials and life cycle. This study examines their potential across major European product groups, including heat pumps, solar panels, printers, ICT equipment, and batteries. For the EU27, we estimate that DPP-enabled improvements could raise circularity from 14.8% to 45.0%, with substantial material and economic savings. The results provide a practical baseline for assessing how digital tools may support the European transition towards a more circular economy.

Technical Summary
DPPs are expected to support circular economy strategies by improving information availability across product value chains. Building on the CE-RISE project, we assess their potential contribution to recycling- and refurbishment-related circularity for heat pumps, photovoltaic panels, printers, ICT equipment, and batteries. The analysis combines production and trade statistics, a PRISMA 2020-compliant systematic review, and evidence-informed scenario parameterisation. We construct material-flow and circularity indicators for Europe over 2010–2023, distinguish the EU27 from non-EU Europe (Switzerland, Norway, and Türkiye), and quantify a DPP scenario with sensitivity intervals. For the EU27 in 2023, baseline circularity is estimated at 14.8%, compared with 45.0% under the DPP scenario (95% sensitivity interval: 28.6–61.4). This corresponds to potential savings of 2.5 Mt of materials and EUR 27.9 billion (bn), with sensitivity intervals of 1.1–3.8 Mt and EUR 12.7–43.1 bn. We additionally estimate refurbishment-related employment exposure using Eurostat production value per employee in NACE J. The results establish an evidence-informed baseline for evaluating DPP-enabled circularity gains and future policy impacts.

Social Media Summary
DPPs could raise EU27 circularity from 14.8% to 45.0%, with major material and economic savings.terial and economic savings. The results provide a practical baseline for assessing how digital tools may support the European transition towards a more circular economy.

2026

Classification of Radar Zones on Selected Glaciers in Ny-Ålesund, Svalbard

Wankhede, Sagar Filipe; Suresh, Athira Mankara; Balakrishna, Keshava; Jawak, Shridhar Digambar

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 active transport accessibility and equity analysis considering built environment, safety, and air pollution

Kumisbek, Aiganym; Agibayeva, Akmaral; Chung, Jaehoon; Santos, Gabriela Sousa; Weydahl, Torleif; Zhou, Tao; Lu, Chaoru

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

Insect outbreak progression over three years shapes biogenic volatile emissions in a mountain birch forest

Rieksta, Jolanta; Smart, Amy Samantha; Davie-Martin, Cleo Lisa; Engroff, Annika; García, Rosa María Picón; Wali, Reza; Gao, Yue; Jiao, Yi; Zhang, Wanying; Tang, Jing; Laursen, Simon Nyboe; Feng, Shunan; Westergaard-Nielsen, Andreas; Holst, Thomas; Seco, Roger; Li, Tao; Rinnan, Riikka

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

Chemical characterization and source apportionment of PM10 in Belgrade, Serbia : influence of local and regional anthropogenic and natural sources

Petrović, Bojana; Alastuey, Andres; Yttri, Karl Espen; Pandolfi, Marco; Jovanović, Maja; Radović, Bojan; Kovačević, Renata; Stojanović, Danka B.; Davidović, Miloš; Platt, Stephen Matthew; Bartonova, Alena; Jovašević-Stojanović, Milena

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

Occurrence and hydrolytic stability of emerging tire wear contaminants in environmental waters and soils: A case study from northern Poland

Godlewska, Klaudia; Białk-Bielińska, Anna; Rostkowski, Pawel; Paszkiewicz, Monika

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

Goddard, Felix W.; Glukhova, Stefania; Ru, Eric C. Le; Evangeliou, Nikolaos; McErlich, Cameron; Hardacre, Catherine; Frame, David; Kuma, Peter; Revell, Laura E.

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

Tracing biological, anthropogenic, and inorganic sources of coarse aerosols via single-particle fluorescence and optical morphology

Jönsson, Aiden; Fu, Jinglan; Freitas, Gabriel Pereira; Crawford, Ian; Dagsson-Waldhauserová, Pavla; Krejci, Radovan; Tobo, Yutaka; Yttri, Karl Espen; Zieger, Paul

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

High-resolution inversion of methane emissions over Europe using the Community Inversion Framework and FLEXPART

Mengistu, Anteneh Getachew; Tsuruta, Aki; Berchet, Antoine; Thompson, Rona Louise; Tenkanen, Maria; Lindqvist, Hannakaisa; Markkanen, Tiina; Leppänen, Antti; Laitinen, Antti; Martinez, Adrien; Fortems-Cheiney, Audrey; Höglund-Isaksson, Lena; Aalto, Tuula

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

Neuron irradiation of Caenorhabditis elegans by protons triggers base excision repair pathway with limited effect on behaviour

Sleiman, A.; Vianna-Legros, F.; Lalanne, K.; Cardot-Martin, M.; Gaffin, J.; Heranney, C.; Sévénié, G.; Perrot, Y.; Sengupta, Tanima; Nilsen, Hilde; Richaud, M.; Galas, S.; Adam-Guillermin, C.

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

Assessment of the extremely low TOC at three European stations during February 2023

Tichopád, David; Láska, Kamil; Čížková, Klára; Novotná, Marie; Svendby, Tove Marit; Vorobeva, Ekaterina

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 in mitigation scenarios with activity-driven simulation of carbon dioxide removal

Schwinger, Jörg; Leon, Merfort,; Nico, Bauer,; Raffaele, Bernardello,; Momme, Butenschön,; Bourgeois, Timothée; J., Gidden, Matthew; Shraddha, Gupta,; Lee, Hanna; Nadine, Mengis,; Yiannis, Moustakis,; Muri, Helene; Lars, Nieradzik,; Daniele, Peano,; Julia, Pongratz,; Pascal, Sauer,; Etienne, Tourigny,; David, Wårlind,

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

From QSAR to deep learning: an interpretable comprehensive pipeline with a read-across approach for mutagenicity prediction via the Enalos Cloud Platform

Varsou, Dimitra Danai; Tsoumanis, Andreas; Longhin, Eleonora Marta; Dusinska, Maria; Mintis, Dimitris G.; Kolokathis, Panagiotis D.; Papavasileiou, Konstantinos D.; Lynch, Iseult; Melagraki, Georgia; Afantitis, Antreas

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.

Ikingura, Andrew; Sowińska-Świerkosz, Barbara; Kociuba, Dagmara; Liu, Hai-Ying; Dace, Elina; Oliveira, Fabiano Lemes de; Kemper, Raimund; Castaldo, Anna Giulia

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

Plastic Ingestion and Plastic-Related Chemicals in Northern Fulmars (Fulmarus glacialis): Exploration of Histopathological and Endocrine Alterations

Fivelstad, Marte; Marhaug, André J.; Bourgeon, Sophie; Hallanger, Ingeborg G.; Gabrielsen, Geir W.; Jenssen, Bjørn Munro; Harju, Mikael; Herzke, Dorte; Tonning, fride; Collard, France

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

PFAS: challenges and scientific perspectives in human health risk assessment

Kowalczyk, Janine; Abraham, Klaus; August, Christina; Boeddinghaus, Runa S.; Chan, James C.Y.; Eckhardt, Alexander; Fletcher, Tony; Freeling, Finnian; Göckener, Bernd; Halldórsson, Thorhallur I.; Herzke, Dorte; Hoogenboom, Ron L.A.P.; Jakobsson, Kristina; Jung, Christian; Madia, Federica; Monien, Bernhard; Numata, Jorge; Ramhøj, Louise; Schoeters, Greet; Sommerkorn, Katharina; Trier, Xenia; Tsiros, Periklis; Unkelbach, Christian; Leeuwen, Stefan P.J. van; Buhrke, Thorsten

2026

State of the Climate in 2025: The Arctic

Moon, Twila A.; Druckenmiller, Matthew L.; Thoman, Richard L.; Andreassen, Liss Marie; Askjaer, Thomas G.; Ballinger, Thomas J.; Berner, Logan T.; Bernhard, Germar H.; Bhatt, Uma S.; Bigalke, Siiri; Bjerke, Jarle W.; Bliss, Angela; Box, Jason E.; Brettschneider, Brian; Burgess, D.; Butler, Amy H.; Christiansen, Hanne H.; Crawford, Alex; Decharme, Bertrand; Derksen, Chris; Divine, Dmitry V; Elias, Chereque; Epstein, Howard E.; Farrell, Sinead; Fausto, Robert S.; Fettweis, Xavier; Fioletov, Vitali E.; Florentine, Caitlyn; Forbes, Bruce C.; Frost, Gerald V. (JJ); Gerland, Sebastian; Grooß, Jens-Uwe; Hanna, Edward; Hendricks, Stefan; Ialongo, Iolanda; Isaksen, Ketil; Jia, Gensuo; Johnsen, Bjørn; Kaleschke, Lars; Kim, Seong-Joong; Kohler, Jack; Labe, Zachary M.; Lader, Rick; Lakkala, Kaisa; Lara, Mark J.; Lee, Simon H.; Loomis, Bryant D.; Luks, B.; Luojus, Kari; López-Blanco, E.; Macander, Matthew J.; Magnússon, Rúna Í.; Mankoff, Ken D.; Medley, Brooke; Meier, Walter N.; Montesano, Paul M.; Mote, Thomas L.; Gjelten, Herdis Motrøen; Mudryk, Lawrence; Müller, Rolf; Natali, S. M.; Neigh, Christopher S. R.; Nyland, Kelsey E.; Orndahl, K. M.; Overland, James E.; Perovich, Donald K.; Petty, Alek; Phoenix, Gareth K.; Poinar, Kristin; Pálsson, F.; Ricker, Robert; Romanovsky, Vladimir E.; Sass, L.; Schuur, E. A. G.; Serreze, Mark C.; Smith, Benjamin E.; Smith, Sharon L.; Streletskiy, Dmitry A.; Svendby, Tove Marit; Thomson, L.; Thorsteinsson, T.; Tian-Kunze, Xiangshan; Timmermans, Mary-Louise; Tømmervik, Hans; Waigl, Christine F.; Walker, Donald (Skip) A.; Walsh, John E.; Wang, Muyin; Webster, Melinda; Wolken, G.; Wouters, B.; Yang, Dedi

Environmental conditions across the Arctic, a vast area above 60°N, look today remarkably different than one or two decades ago. Modern satellite era measurements of Arctic annual surface air temperature (1979–2025) show that the region has, on average, warmed roughly three times faster than the rest of the planet. Human emissions of heat-trapping gases are driving the change globally with additional processes in the Arctic amplifying the heating (section 5c). The impacts touch every corner of the terrestrial and marine landscape, including serious compounding hazards for people in the Arctic. This chapter delves into these long-term trends and details 2025 observations across the Arctic system, including a section on 2023/24 observations on glaciers and ice caps outside of Greenland (section 5h, which alternates yearly with a section on Arctic river discharge).

Examining surface temperature in the Arctic, 2025 was the second warmest year since the observational record began in 1900 (section 5c). The surface temperature anomaly for the year was 1.38°C above the 1991–2020 mean, a reflection of warmer-than-usual temperatures occurring across seasons. Autumn and winter continue to show the strongest increases in surface warming as compared to global trends, and 2025 marked the 12th consecutive year that Arctic temperature anomalies were higher than global surface temperature anomalies. Temperature changes also occur from the Earth’s surface up through the troposphere and stratosphere. The Arctic troposphere has warmed 0.3°C decade−1 since 1958, while the stratosphere has cooled by a similar amount, an expected pattern with human-caused climate change (section 5b). In 2025, polar tropospheric air temperatures were the second highest on record.

Overall warming in the Arctic is accompanied by increases in precipitation, including the potential for bigger rain and snow events. During the period 1950–2025, there was an upward trend in annual precipitation totals, including significant upward trends in all seasons (section 5d). Examining annual records, 2025 had the third highest annual precipitation total on record, and the largest precipitation anomalies with respect to 1991–2020 were in winter (112%), spring (108%; the highest spring anomaly on record), and autumn (104%). Snow cover extent is connected to these coupled changes in precipitation and temperature, with patterns of snowpack buildup and melt shifting over the last several decades. In 2025, Arctic snow cover extent was roughly normal in Eurasia and North America in May but dropped below normal in June with early loss of snow cover, a now common occurrence (section 5i).

Arctic landscapes both respond to and influence temperature and precipitation changes. With vast areas of tundra as well as permafrost, the Arctic is home to a unique physical system that is responding rapidly to overall warming. Changes in Arctic tundra plants and productivity, such as increases in the abundance, distribution, and height of shrubs, result in Arctic “greening”, which has been detected since the late 1990s. Beginning in 2020, the Arctic has experienced a sequence of record- or near-record-high greenness values, to which 2025 is now added as the third highest value (section 5k). Local and regional variation is notable, however, with, for example, both greening and “browning” in the Eurasian Arctic. Vegetation changes in the Arctic are intrinsically connected to changes in permafrost as well. Since the 1980s, permafrost across the Arctic has seen a long-term warming trend, with the strongest trends in high-latitude, cold permafrost (section 5j). The active layer thickness, or the maximum depth of surface ground that seasonally thaws and freezes, has also increased, though at different regional rates.

Permafrost thaw is also a key player in Arctic terrestrial carbon dioxide and methane storage, though other important processes are also at play, such as wildfire, wetland development or loss, and river and lake outgassing. Examining tundra and boreal forest ecosystems in Arctic permafrost regions suggests that together carbon dioxide from these sources made the region a small net carbon dioxide source during the period 2000–20 (Sidebar 5.2). This is a serious and potentially long-term shift from Arctic permafrost regions acting as a carbon dioxide sink that dampens warming to a source that can enhance warming. Subannual records also show that the seasonal cycle of carbon storage and release is amplifying, reflecting both stronger winter emissions and stronger summer uptake (Sidebar 5.2).

Dramatic change continues for other frozen components of the Arctic system. On land, the Greenland Ice Sheet, which holds the second largest reservoir of frozen fresh water on the planet, had yet another year of overall ice loss (129±50 Gt based on gravity measurements; section 5g). Sixty percent of the planet’s glaciers and ice caps outside of Greenland and Antarctic are also found in the Arctic, and ice loss across these areas has tripled since the mid-1990s. During 2023/24, both Arctic Scandinavia and Svalbard had record years of ice loss with melt 1473% above the 1991–2020 mean in Arctic Scandinavia and 482% above in Svalbard (section 5h).

Arctic sea ice records also continue to show very low extent and predominantly first-year ice. The maximum sea ice extent in March 2025 was the lowest in the 47-year record, continuing a downward trend of −2.5% per decade, while September 2025 minimum extent was the 11th lowest on record, adding to a trend of −13.6% per decade extent loss (section 5f). Ice older than four years old is now nearly absent, with only 95,000 km2 of older ice in September 2025 as compared to 1.5 million km2 in the 1980s. Without sea ice cover, Arctic Ocean surface waters are exposed to heating from solar radiation and the atmosphere. Examined annually in August, the 2025 sea surface temperature in most Arctic Ocean regions was the highest in the 1982–2025 record and the pan-Arctic mean was the second highest on record (section 5e).

Pervasive environmental changes have direct and indirect impacts on people within and beyond the Arctic (e.g., Meng et al. 2023; Moon et al. 2019). In many instances, communities experience the combined impacts of multiple rapidly changing systems. For example, permafrost thaw and glacier retreat are increasing hazards such as glacial lake outburst floods, landslides, and the reliability of water supplies. Extreme weather hazards are also increasing. A prime example is the devastating ex-typhoon Halong that hit the Alaska west coast on 11–12 October 2025 (Sidebar 5.1). The storm traveled across anomalously warm ocean surface temperatures, and peak storm surge arrival on shore coincided with the daily high tide. Storm impacts were intense and widespread, including substantial inland and coastal flooding, ferocious winds, infrastructure loss, and loss of life.

The pace of change and the seriousness of impacts across plants, animals, and people highlight the importance of maintaining and strengthening our environmental intelligence regarding the Arctic region. Real threats to our scientific monitoring ability exist, such as the loss of a long-term Arctic vegetation monitoring dataset due to funding cuts (section 5k). This chapter’s observations show that the Arctic today is vastly different than the past, requiring close attention and increased action for hazard preparedness and response.

2026

Digital twin framework for personalized behavioral health optimization with Q-learning and graph-based planning

Chatterjee, Ayan; Avazov, Nurilla

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

Ebrahimi, Babak; Bouman, Evert

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

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