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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
Fluoropolymers are widely used across sectors, but their production is associated with emissions of perfluoroalkyl and polyfluoroalkyl substances (PFASs), which are mobile, persistent, and toxic. In this work, we compiled a global inventory of fluoropolymer production plants (FPPs) and assembled PFAS concentration measurements for various media in their vicinity. We identified 52 currently operating FPPs across 11 countries and 41 cities. For 12 FPPs, in 12 different cities, there are peer-reviewed site-specific PFAS measurements specifically attributed to the FPP. At these 12 sites, at least 236 individual PFASs have been detected across multiple environmental media, including surface water, groundwater, air, dust, soils, sediments, plants, animals, and humans, with reported detections at distances of up to approximately 150 km from FPPs. Perfluoroalkyl carboxylic acids (PFCAs) and perfluoroalkyl ether carboxylic acids (PFECAs) were most frequently measured, often at concentrations two to three orders of magnitude higher than those measured in regions without nearby FPPs. Using high-resolution population data, we estimate that approximately 14 ± 2 million people (uncertainty reflecting ± 10 km uncertainty in facility locations) live within 10 km of an FPP. These people are potentially affected by FPP-associated contamination, with the largest population shares in China (≈52%), Japan (≈24%), Europe (≈13%), and the United States (≈9%). These regional proportions largely mirror differences in population density and the number of identified production facilities. This inventory reveals the large and complex global scale of PFAS contamination from fluoropolymer production, underscoring the need for expanded systematic monitoring and risk management efforts, including regulation.
2026
2026
Bioaerosols interact with society and environment in a multi-faceted way. Information about biological aerosols in the atmosphere is at high demand for medical practitioners and allergy sufferers, climate change researchers, agriculture and forestry industries, air quality forecasters, a variety of information added-value businesses, and many other stakeholders. However, the monitoring practices established over 70 years ago and barely changed since then are country-specific, with varying data availability and usage policy. These roadblocks slow down cross-disciplinary research and development of measures to understand and, upon necessity, control societal and environmental impacts of bioaerosols.A series of technological breakthroughs during last 10 years introduced a variety of automatic particle counters capable of bioaerosol monitoring in real time. They paved the way to the volunteering consolidation of European aerobiologists to establish the EUMETNET AutoPollen Programme (www.autopollen.net), laid down the foundation for the bioaerosol monitoring infrastructure with the EU Horizon SYLVA project (A SYstem for reaL-time obserVation of Aeroallergens, https://sylva.bioaerosol.eu), initiated developments of European standards and guidelines for the automatic bioaerosol measurements with the EURAMET project BioAirMet, and started the European standardization effort with CEN WG 39.The new technologies allow to observe bioaerosol concentration in real time, analyze vertical concentration profiles via remote-sensing, perform metagenomic analysis of bioaerosols with the 3rd generation DNA sequencing technique, and combine these observations with atmospheric composition models. Newly established regional networks have been connected to regional atmospheric composition models, which assimilate the real-time regional data to improve the forecasts. It changes the existing paradigm of bioaerosol observations as the new monitoring networks involve large-scale data handling infrastructure, which also includes numerical models as an interface between the different technologies and a bridge to users of information.The new observations heavily rely on sophisticated technologies, such as high-resolution image analysis, holography, multi-band scatterometry and fluorescence spectrometry, lidar-based remote sensing, and nanotechnology for DNA sequencing. A particle recognition task, the key challenge for the new devices, is solved via machine learning approaches. Technological complexity of the new instruments and large amounts of raw data they produce have been recognized, and a European-scale solution has been proposed by AutoPollen/SYLVA. AutoPollen is being converted into a EUMETNET operational programme with the SYLVA infrastructure as its technological backbone. The programme, with support of Copernicus Atmosphere Monitoring Service (https://atmosphere.copernicus.eu), ACTRIS aerosol monitoring network, and other stakeholders, will become operational from 2027. The central processing system will be hosted by Finnish Meteorological Institute with support of MeteoSwiss, Technical University of Munich, and all SYLVA partners. The pre-operational work of AutoPollen/SYLVA started already in 2025, owing to the efforts of the SYLVA consortium, its sister projects and collaborators. The programme is open for all European (and from outside Europe) groups performing automatic bioaerosol monitoring. AutoPollen offers technological and organizational support, community-developed bioaerosol monitoring solutions, and a motivated team of experts advancing the relevant research and applications.
2026
Monitoring of long range transported air pollutants in Norway. Annual Report 2025
This report presents results from the monitoring of atmospheric composition and deposition of air pollution in 2025, and focuses on main components in air and precipitation, particulate and gaseous phase of inorganic constituents, particulate carbonaceous matter, ground level ozone and particulate matter.
NILU
2026
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
Exposures in Indoor Air Affecting Health
Indoor air quality (IAQ) is influenced by a wide range of chemical, biological and physical agents that can negatively impact physical, immunological and mental health. Adverse health effects depend on the type and concentration of pollutants, duration of exposure, and individual susceptibility. The availability of data on IAQ is limited, as are standardized approaches for evaluating its health impact. This expert review aims to describe the most important indoor air determinants affecting health, and present the IDEAL cluster, which comprises seven EU‐funded scientific projects on the topic of IAQ and human health. Across the IDEAL projects, knowledge is generated on exposure to a wide range of indoor air pollutants, including well‐known hazards and more explorative chemical and microbiological determinants. The projects will also contribute to the implementation of low‐cost and/or real‐time sensors on IAQ, as well as advanced chemical and microbiological analyses, and evaluate various interventions to improve IAQ. Several of them focus on particularly vulnerable groups. Raising public awareness and implementing measures to reduce pollutant levels are essential for safeguarding health, particularly in urban areas with elevated pollution levels.
2026
Suspect screening helps detect chemicals in environmental samples without predefined target lists which can facilitate isolation of a larger number of substances. This study shows however that no single extraction method or analytical platform (LC-HRMS or GC-HRMS) can capture all relevant pollutants—at least half are missed. The technique works best for chemically similar families, where optimized methods can target specific classes or broader families of similar substances (e.g. PFAS). Effective grouping of similar substances is therefore essential. A broad coverage of substances can however be achieved if multiple sample extractions are performed and each extract is analysed on both LC- and GC-HRMS. Strategies where comparisons can be made over time or across locations will also help to isolate pollutant-related signals from the background. Such considerations must be integrated into programme design and budgeting for retrospective analysis. This will maximize likelihood of detection for the largest diversity of substances.
Norwegian Environment Agency, M-3038|2025
NILU
2026
2026
Franzefoss Husøya Kristiansund. Målinger av ammoniakk NH3 og flyktige organiske forbindelser VOC
NILU
2026
Global Atmospheric Microplastics Emissions Estimated Using Constrained Bayesian Inverse Modeling
We present an analysis of global atmospheric microplastics (MPs) concentration and deposition measurements using constrained Bayesian inverse modeling to estimate global MPs emissions. The proposed Bayesian framework explicitly accounts for unknown ratios between size fractions inherent to MPs measurements and incorporates prior emission information to stabilize the inversion. The coupling between observations and unknown emissions is established using the atmospheric transport model FLEXPART version 11 operated in backward mode for each measurement. Model parameters are inferred using a variational Bayes approach, resulting in an iterative estimation scheme that updates both model parameters and the effective spatial structure of the computational domain. This methodology reduces the need for manual intervention during the inversion process and limits potential bias in the results. The resulting global MPs emission estimates are evaluated against previously published ones. Acknowledgment:This research has been supported by the Czech Science Foundation (grant no. GA24-10400S). N.E. was funded by the Norwegian Research Council (NFR) project MAGIC (No.: 334086). FLEXPART model simulations are cross-atmospheric research infrastructure services provided by ATMO-ACCESS (EU grant agreement No 101008004). The computations were performed on resources provided by Sigma2 - the National Infrastructure for High Performance Computing and Data Storage in Norway.
2026
2026
Marine Carbon Removal Gains Momentum But Can It Scale Responsibly?
As mCDR gains global traction, we discuss the current state of this sector with leading mCDR representatives.
2026
2026
Large aerosol particles within the coarse mode affect the environment, climate, and human health in ways that strongly depend on particle type. Although this size range is dominated by mineral dust and sea spray aerosol (SSA), less abundant biological particles can exert disproportionate effects, such as triggering ice formation at comparatively warm temperatures. Accurate, type-resolved characterization of coarse-mode aerosols is therefore critical for understanding their environmental and climatic roles. Here, we present a new laboratory-based reference dataset for common coarse-mode aerosol sources, including pollen, dust, bacteria, and microplastics, based on laboratory measurements of single-particle ultraviolet light-induced fluorescence (UV-LIF) spectroscopy and particle morphology. Comparison with existing datasets reveals source-specific fluorescence signatures, but also demonstrates substantial overlap between biological and non-biological particles, which can lead to misclassification when fluorescence information is used alone.Building on this dataset, we introduce a new machine-learning classification framework that combines fluorescence and morphological features. The algorithm is trained using laboratory data and evaluated with field observations from Zeppelin Observatory, Svalbard. To improve discrimination of combustion-related particles and to better separate dust from SSA, we apply domain adaptation using in situ measurements. The updated classifier successfully reproduces the previously reported annual bioaerosol cycle, yields higher bioaerosol concentrations than a fluorescence-only method, and maintains similar correlations with established biological and combustion tracers. Our open-source code enables more robust quantification of bioaerosols across a range of environments, allows reassessment of prior observations, and can be further improved as new particle characterization data become available.
2026
Heritable mutations in male germ cells pose a critical risk to human health and future generations, however standardized methods for assessing germ cell genotoxicity remain limited. We refined the in vivo alkaline comet assay (proof-of-concept (Dirven et al. 2023); protocol (Olsen et al. 2024)) to detect DNA damage in testicular germ cells, with selective addressment of haploid spermatids and primary spermatocytes. Measurements of DNA damage (% Tail DNA) and DNA content (total fluorescence intensity) in individual comets were combined with visual comet identification to distinguish testicular comet populations based on differences in DNA content and appearance. To verify the method’s functionality and reliability, DNA damage was assessed in rats exposed to the direct-acting, well-characterized genotoxicants X-rays and ethyl methanesulfonate across distinct testicular cell populations, alongside liver and blood. To minimize experimental variation, the protocol included stringent standardization of animal handling, tissue processing, and comet assay procedures. Both X-rays and EMS induced significant DNA damage in testicular germ cells, with comparable responses across testicular cell types and similar (X-rays) or higher levels observed in somatic tissues. The low inter-animal variability observed supports the robustness of the method. Importantly, inclusion of testicular germ cells in OECD test guideline 489 would provide a valuable tool for hazard identification and mutagenicity classification of chemicals under the Globally Harmonized System of Classification and Labelling of Chemicals. This versatile, sensitive, and resource-efficient assay enhances the assessment of male-mediated genetic risks and supports regulatory efforts to protect reproductive health and safeguard the genetic integrity of future generations through the use of safer chemicals.
2026
2026
Årsrapport 2025. Nasjonalt referanselaboratorium for luftkvalitetsmålinger
Denne rapporten oppsummerer oppgavene til Nasjonalt referanselaboratorium for luftkvalitetsmålinger (NRL), delkontrakt 1b, for året 2025.
NILU
2026
Tracing the air–sea exchange of microplastics over the Caspian Sea
The global proliferation of microplastics (MPs) is increasingly recognized as a transboundary environmental issue. At the air–ocean interface, MPs can be emitted via sea spray and transported back to land, while terrestrial MPs can likewise be advected and deposited over the oceans. However, the long-term net exchange of MPs between land and ocean via the atmosphere remains poorly constrained. Here, we investigate coastal atmospheric MPs and their near-surface landward and seaward transport over the southern Caspian Sea. Using a combination of passive air sampling (at seven heights with MWAC collectors) and active sampling (vacuum pump) over periods of 3 days and 2 months, respectively, together with coastal surface sediment samples, we quantified MP concentrations and assessed the influence of meteorological and environmental factors on their distribution. Fibrous MPs dominated all compartments, with airborne concentrations averaging 3.85 MP m−3 and sediment concentrations ranging from 507 to 1476 MP kg−1 (dry weight). Estimated near-surface horizontal fluxes were comparable in magnitude, with a landward influx of ~6566 MP m−2 h−1 and a seaward outflux of ~8039 MP m−2 h−1, indicating broadly balanced coastal transport during the 72 h campaign. To support source attribution, we evaluated co-trapped particulate proxies (sea salt and ash) and combined them with FLEXPART modelling. Trajectory modelling and proxy evidence indicate that most airborne MPs originated from inland sources (e.g., road dust and textile-related fibres), while marine sea-spray contributions were minor during the sampling period. These findings highlight the importance of long-range atmospheric transport in coastal MP pollution and demonstrate how integrating proxy observations with dispersion modelling can help constrain likely source regimes.
2026
2026