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Low-cost sensor (LCS) networks can complement sparse regulatory monitoring, but their value depends on robust integration strategies that preserve data quality while exploiting dense spatial sampling. Here we assess the added value of incorporating validated LCS PM2.5 observations into the S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) machine learning framework (Shetty et al., 2024, 2025) to generate continental-scale, 1 km resolution surface PM2.5 fields across Central Europe. Two integration strategies are evaluated for 2021–2022 within a stacked XGBoost architecture driven by satellite aerosol optical depth, meteorological predictors, and CAMS regional forecasts: a) using LCS data as an additional training target (LCST), and b) using LCS information as a model input feature (LCSI) via an inverse-distance-weighted spatial convolution layer that encodes local sensor influence. Relative to a baseline trained only on official monitoring stations, LCSI yields consistent performance gains, with RMSE reductions of ~15–20% in urban areas, whereas LCST provides less consistent improvement. The resulting high-resolution mapping product achieves skill comparable to the CAMS regional reanalysis, often considered as a modelling “gold standard” for European air-quality assessment, and in some evaluations surpasses it, with lower annual mean absolute error (2.68 vs 3.32 µg m⁻³) (Shetty et al., 2026). This demonstrates that a data-fusion ML approach including LCS information can deliver reanalysis-level performance at 1 km resolution while requiring only modest computational resources compared with running full chemical transport model reanalyses, enabling rapid updates and scalable deployment. SHAP-based attribution further suggests that LCSI improves the model’s ability to capture localized pollution variability, while performance degrades where sensor density is low, limiting representation of inter-urban transport.Although demonstrated in Europe, the underlying methodology, namely combining globally available satellite products and meteorology with quality-controlled LCS networks in a computationally efficient ML framework, has potential to strengthen air-quality assessment also in resource-limited settings where regulatory infrastructure is scarce. A requirement for this is that appropriate sensor calibration/validation workflows are in place and equitable partnerships support sustainable sensor deployment and data stewardship. Shetty, S., Schneider, P., Stebel, K., Hamer, P. D., Kylling, A., and Koren Berntsen, T.: Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning, Remote Sens. Environ., 312, 114321, https://doi.org/10.1016/j.rse.2024.114321, 2024.Shetty, S., Hamer, P. D., Stebel, K., Kylling, A., Hassani, A., Berntsen, T. K., and Schneider, P.: Daily high-resolution surface PM2.5 estimation over Europe by ML-based downscaling of the CAMS regional forecast, Environ. Res., 264, 120363, https://doi.org/10.1016/j.envres.2024.120363, 2025.Shetty, S., Hassani, A., Hamer, P. D., Stebel, K., Salamalikis, V., Berntsen, T. K., Castell, N., and Schneider, P.: Evaluating the role of low-cost sensors in machine learning based European PM2.5 monitoring, Environ. Res., 291, 123558, https://doi.org/10.1016/j.envres.2025.123558, 2026.
2026
Global methane emission estimates from a dual-isotope inversion: new constraints from δD-CH4
Methane (CH4) is a potent greenhouse gas; however, the causes of its growth since 2006 are a subject of debate. While measurements of CH4 mole fraction and carbon isotopic composition (δ13C-CH4) have been extensively used to investigate the global CH4 budget, the hydrogen isotopic composition (δD-CH4) remains underutilised despite its unique sensitivity to source types and oxidation processes. Here, we assimilate a newly harmonised 35-year dataset of dual isotope measurements from high-latitude monitoring stations in both hemispheres within a two-box Bayesian inversion to quantify global CH4 sources and sinks. The model integrates prior emissions from five source categories based on global bottom-up inventories. Methane removal processes are represented by sink-specific kinetic isotope effects as tropospheric and stratospheric loss, and soil uptake. We find that the inclusion of δD-CH4 improves the model's ability to constrain emission apportionment between biogenic and thermogenic sources, particularly for fossil fuel emissions during the late 1990s and early 2000s, which affects CH4 lifetime estimate. CH4 increase post-2006 is driven mainly by rising wetland emissions, while fossil-fuel growth is modest, biomass burning declines, and agriculture and waste make smaller, regionalised contributions. The optimised inversion results favour a strong 13C kinetic isotope effect in total tropospheric CH4 removal and a net shortening of the NH lifetime of CH4 by 0.2 years. This study demonstrates the added value of incorporating δD-CH4 into inverse modelling frameworks and underscores the importance of long-term δD-CH4 measurements for advancing our understanding of CH4 biogeochemistry and its role in the global carbon cycle.
2026
Circular Economy (CE) principles seek to eliminate hazardous substances and promote the reuse and recycling of plastic products. However, implementing these principles is challenging due to the wide variety of substances used in plastics, their potential health and environmental risks, the complexities of global supply chains, and concerns regarding reappearance of Chemicals of concern (CoCs) in post-recycled plastics (PRP). This study presents a novel approach for identifying CoCs in the waste stream by assessing the potential presence of chemicals in polymers across different industrial sectors and their hazard categories. With the objective of identifying CoCs that are most problematic regarding their reappearance in new products, selected CoCs are classified into four priority groups based on their physicochemical properties and molecular structures, for further risk and regulatory assessment. The first group includes 88 CoCs, that must be avoided in a circular economy, of which 70% are metalloids and 30% are organic additives. The second group comprises 167 CoCs, mainly additives, whose risks depend heavily on their concentration and specific use in products. The third and fourth groups consist of CoCs that are less frequently found in plastic waste and thus associated with relatively lower risks. Overall, this study offers a practical and adaptable tool to support the identification of hazardous substances in plastic waste, helping stakeholders make informed decisions by removing CoCs and promoting the development of safer alternatives for substitutions.
2026
The Filter Inlet for Gases and AEROsols coupled to a Chemical Ionization Mass Spectrometer (FIGAERO–CIMS) can be used to derive volatility of atmospheric aerosol by using the temperature at thermogram maximum signal (Tmax). For complex ambient particle matrices, Tmax of an individual compound often varies, for reasons not fully elucidated. Here, we apply machine learning to study the relation between Tmax of levoglucosan (C6H10O5), a common tracer to identify the influence of biomass burning (BB) in ambient air, and a set of atmospheric and instrumental parameters for an ambient year-long FIGAERO–CIMS data set measured in the Arctic. Using three different modeling approaches, namely, multiple linear regression (MLR), random forest (RF) regressor, and XGBoost regressor, we find that the mass loading on the FIGAERO filter has the highest relevance for variation in Tmax of levoglucosan. On the basis of these results, we suggest controlling the mass collected on the filter for continuous online measurement with the FIGAERO–CIMS if quantitative volatility information is to be gained. More generally, we demonstrate the usefulness of machine learning approaches for characterization of instrumental backgrounds in complex ambient or laboratory data.
2026
2026
Unidentified Halon-2402 emissions in East Asia are driving the global trend
Halon-2402 (1,2‑dibromotetrafluoroethane, H-2402) is a potent ozone‑depleting substance and greenhouse gas whose global production has been banned under the Montreal Protocol since 2010, while the use of recovered or recycled stocks remains permitted for essential uses. Although these controls led to nearly two decades of declining atmospheric abundances, recent observations indicate renewed emissions. Here, we present the first observation-based regional emission estimates of H-2402 in East Asia for 2008–2023, derived using high-frequency measurements at Gosan, South Korea, and a Bayesian inversion framework. While most AGAGE stations measure background mole fractions or intermittent low-level increases, Gosan exhibits increasingly frequent and intense pollution events, revealing growing regional emissions. We find that East Asia accounted for most global H-2402 emissions in recent years, with particularly sharp increases in Japan and the Vladivostok region of Russia. Since 2015, regional emissions from East Asia have effectively driven the global emission trend, reversing the long-term decline. These emissions are spatially linked to petrochemical infrastructure, ship-repair activity, and military decommissioning sites, suggesting releases from legacy halon banks rather than new production. Cumulative emissions from East Asia between 2008 and 2023 reached ~52 Gg CFC-11-equivalent emissions. These findings imply a tangible delay in ozone layer recovery and underscore the urgent need for strengthened monitoring, transparent reporting, and verifiable management of remaining H-2402 stocks under the Montreal Protocol.
2026
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
Verden er mørk. TV 2s reporter Hilde Gran spurte ChatGPT om hjelp
Svaret jeg fikk var overraskende rørende.
2026
2026
Ozone responses to the geomagnetic storms in 2024 and 2025
Solar Cycle 25 has approached its maximum phase, bringing an elevated frequency of solar eruptive events and associated geomagnetic disturbances. During 2024 and 2025, several intense geomagnetic storms have provided rare opportunities to examine the short-term coupling between space‐weather forcing and the middle atmosphere. Previous studies have shown that energetic particle precipitation (EPP) during geomagnetic storms can substantially modify the chemical composition of the mesosphere and lower thermosphere (MLT), particularly through the production of odd nitrogen (NOx) and odd hydrogen (HOx), which catalytically destroy ozone. In this presentation, we investigate the MLT ozone responses to several large geomagnetic storms occurring in 2024–2025 using MLS satellite observation. We will also estimate the particle forcing associated with these events using the observed ozone chemical responses. This analysis provides a testbed for climate model inputs.
2026
2026
Abstract Trifluoroacetic acid (TFA) is a persistent pollutant with potential long‐term effects on the environment and on health. Recent studies using ice core records report large increases (up to tenfold) in Arctic TFA deposition since the 1970s, and trends suggest long‐lived chlorofluorocarbon (CFC) replacements may be a major source. Here, we use a chemical transport model to examine the global TFA budget arising from CFC replacements–hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs)–and inhalation anesthetics. Global TFA deposition from these sources increased ∼3.5‐fold from 6.8 (5.9–7.6) Gg/yr in 2000 to 21.8 (18.6–25.0) Gg/yr in 2022, with cumulative deposition reaching 335.5 Gg. We find HCFC‐123, HCFC‐124, and HFC‐134a account for most modeled TFA production and that long‐lived CFC replacements account for virtually all of the observed Arctic deposition trend. At lower latitudes, our analysis supports the recent emergence of hydrofluoroolefins (HFOs) as a TFA source. We conclude that increased TFA monitoring is required.
2026
Safeguarding drinking water in north-western europe by modelling the fate of amines from CO2capture
The European Union (EU) net-zero emission target for 2050 requires large-scale deployment of carbon capture and storage (CCS). Amine-based CO2 capture (CC) is the most mature CC technology but may lead to the spread of nitrosamines (NSAs) and nitramines (NAs) in the nearby surroundings. These are carcinogenic compounds that can persist in water resources. Hence, EU's ambition towards carbon neutrality might pose risk of drinking water contamination as well as ecosystem and agricultural crops pollution. We compiled a dataset of planned CCS projects in the Franco-Danish corridor, Europe's future CCS hub, where most capacity will be located by 2030, with at least 40% based on amine technology. Spatial analysis indicates that up to 10.2 million inhabitants, large Natura 2000 reserves, and extensive crop areas may be impacted by NA and NSA deposition, often in regions already under severe water stress. Biogeochemical modelling shows that surface waters with short residence times are highly sensitive to deposition rates, whereas groundwater concentrations depend strongly on the interplay between NA and NSA half-lives and travel times, creating greater uncertainty in aquifers, especially small systems with limited dilution. In both cases, MEA is the most environmentally friendly when emission abatement measures are limited to water wash, compared to piperazine and other emerging solvents. Main findings highlight the need for regional-scale modelling and harmonized regulation to safeguard drinking water, ecosystems, and food security as CCS deployment expands.
2026
Plastic pellet spills are a major source of microplastic pollution, and pellets are found on beaches worldwide. However, the potential environmental impacts of these spills remain poorly understood. In December 2023, approximately 25,000 kg of polyethylene pellets containing high concentrations of the additive Tinuvin UV-622 were spilled during a shipping accident off the northern coast of Portugal. Pellets collected from an affected beach located in Galicia, Spain, along with solvent extracts and aqueous leachates, were subjected to both target and nontarget chemical analyses and tested in a battery of toxicity assays including a green microalga (Raphidocelis subcapitata), a marine copepod (Apocyclops royi), a fish model (Danio rerio), and a human cell line. Chemical screening identified on the order of 50 chemical substances in addition to Tinuvin UV-622, including a range of known plastic additives and nonintentionally added substances (NIAS). Toxicity assays revealed significant growth inhibition and stress-induced cell aggregation in R. subcapitata and acute toxicity causing immobilization in copepods, which could have potential implications in the environment via the disruption of primary producers and food web dynamics. In contrast, zebrafish embryos showed no significant developmental effects, while human cells exhibited modest, time-dependent reductions in viability. Our findings underscore the complex chemical burden associated with pellet spills and stress the need for policies and regulations to prevent them, reinforcing the importance of applying the precautionary principle in managing the environmental risks linked to plastic pellet production, transport, and accidental release.
2026
The growing adoption of low-cost sensors (LCSs) has significantly enhanced environmental monitoring by enabling widespread, community-driven data collection, particularly in regions requiring dense monitoring, and in regions with limited or no reference instrumentation. Increased public awareness and demand for dense environmental monitoring have resulted in extensive air quality and meteorological datasets from diverse sources. However, the integration of such datasets into regulatory frameworks and large-scale environmental monitoring remains challenging due to persistent issues related to data quality, standardization, and interoperability. To address these challenges, the FILTER (Framework for Improving Low-cost Technology Effectiveness and Reliability) approach developed by Hassani et al. (2025) provides a suite of algorithms to harmonize, quality-check, flag, and perform in-situ corrections on crowdsourced PM2.5 LCS datasets. While FILTER was initially designed and validated for static PM2.5 sensors, it has since been extended to address data quality challenges associated with the dynamics of mobile and wearable sensing. Across both static and mobile LCS platforms, FILTER employs a unified processing pipeline that generates measurement-level quality flags based on multiple statistical tests, to quantify the reliability of each observation. Quality control (QC) includes statistical tests to: (a) assess physical measurement consistency (range validity test), (b) detect flatline behavior (constant value test), and (c) identify abnormal patterns (spatiotemporal outlier detection test) using both historical trends and spatial comparisons with neighboring LCSs. Beyond these mandatory QC steps, more advanced statistical procedures incorporate relative (spatial correlation test) and absolute (spatial similarity test) comparisons with nearby LCSs, higher-quality instruments, and reference monitoring stations. For mobile and wearable sensing, FILTER has been specifically adapted to support pairwise comparisons between mobile sensors and comparisons with higher-accuracy nodes, accounting for operation under dynamic environmental and operational conditions. In this context, statistical comparisons are evaluated during rendezvous events, that is, periods in which the mobile sensor and a higher-accuracy node provide temporally coincident measurements. The modified framework retains the core principles of transparency, scalability, and sensor independence, while introducing additional steps to address motion-related artifacts, intermittent time series, and location-specific uncertainties. FILTER is developed in the open-source R environment. Its modular and hierarchical design allows flexible adaptation of quality control and correction workflows based on data availability, the spatiotemporal characteristics of LCS networks, and application-specific requirements. By improving data reliability and usability, FILTER enables crowdsourced LCS datasets to serve as a reliable complement to official monitoring networks for air quality management, urban- and regional-scale modeling, and policymaking. References Hassani, A., Salamalikis, V., Schneider, P., Stebel, K., and Castell, N.: A scalable framework for harmonizing, standardization, and correcting crowd-sourced low-cost sensor PM2. 5 data across Europe, J. Environ. Manage., 380, 125100, 2025.
2026
Benzotriazole UV stabilizers (BUVs) are widely used plastic additives and are increasingly recognized as contaminants of emerging concern due to their persistence and potential for long-range environmental transport. In this study, bird feathers collected from polar regions and China were analyzed to investigate the occurrence and profiles of BUVs. BUVs were detected in all studied regions, with detection frequencies varying among compounds (up to 89.2%) and concentration levels ranging from 9.64 to 52.68 ng/g ww for ΣBUVs. Among individual compounds, UV-329 exhibited the highest median concentration (up to 26.0 ng/g ww), followed by UV-326 and UV-327. BUVs were identified in Antarctic bird feathers, whereas previous biomonitoring studies based on other biological matrices reported non-detectable levels in Antarctic samples. This work also represents the first application of bird feathers to investigate BUV contamination across the Arctic, the Antarctic, and China. Differences in BUV profiles were observed across regions and species, but these patterns should be interpreted cautiously because sampling year, species ecology, and feather-specific processes may all influence feather concentrations. The results also support the use of bird feathers as a non-destructive biomonitoring matrix for monitoring BUV contamination in both remote and populated regions. These findings highlight the need for further investigation into the sources, transport pathways, and ecological risks of BUVs.
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
Coastal aerosols are formed through the complex mixing between marine air masses and continental emissions, which originate from both natural and anthropogenic sources. The properties of coastal aerosols are decisive for their interaction with sunlight and their influence on clouds, as well as the potential health implications for the population in these areas. In this study, the aerosol properties and sources at Aarhus Bay, Denmark, were investigated by combining in situ aerosol light scattering and absorption with size distribution measurements and footprint analysis by FLEXPART. Our analysis demonstrates a considerable contribution of anthropogenic aerosols from both fossil fuel combustion and biomass burning, as well as periods with highly scattering aerosols. Furthermore, good agreement was found between in situ and modelled black-carbon data. Combining in situ measurements and FLEXPART analysis further evidenced a major impact of local emissions, as well as a few long-range transport intrusions.
2026