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Airborne microplastics and nanoplastics (MNPs) are emerging contaminants of global concern due to their persistence, widespread distribution, and potential health impacts. With sizes comparable to PM2.5, they are inhalable and may penetrate deep into the respiratory tract. Their detection and quantification remain challenging because of low environmental concentrations, complex matrices, and particle sizes often below the detection limits of current micro spectroscopic techniques. Pyrolysis–gas chromatography–mass spectrometry (Py-GC-MS) offers a powerful mass-based approach, enabling identification and quantification of polymers regardless of particle size. This review critically examines current methodologies for airborne MNP analysis using Py-GC-MS, including sampling strategies, pretreatment protocols, instrumental parameters, and data modeling approaches. A technological readiness level assessment highlights limited methodological harmonization and insufficient validation, particularly for nanoplastics. Progress toward routine atmospheric monitoring requires standardized workflows, agreed polymer-specific markers, interlaboratory validation, and improved reporting practices to establish Py-GC-MS as a cornerstone technique for airborne MNP assessment.
2026
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2026
Parametric life cycle assessment of asphalt pavements with probabilistic lifetimes and traffic
This study combines established methods – parametric LCA, probabilistic pavement lifetime modelling, traffic-volume characterization, and Monte Carlo simulation – into a service-based decision-support framework for asphalt pavement assessment. The framework evaluates environmental impacts not only per unit mass, but also in relation to pavement service life and traffic exposure, expressed as impact/(yr·AADT). Results indicate that binder type, asphalt plant efficiency, and transport distances are dominant contributors to environmental impacts. Incorporating probabilistic lifetimes and traffic loads reshapes environmental rankings, revealing that longer lifetimes do not always equate to lower burdens. These findings provide data-driven insights for reducing the environmental impacts of road construction and maintenance.
2026
For the first time, we present long-term, ongoing atmospheric measurements of 1,2-dichloroethane (DCE, CH2ClCH2Cl) from the Advanced Global Atmospheric Gases Experiment (AGAGE) and National Oceanic and Atmospheric Administration (NOAA) global monitoring networks. DCE is an industrially produced, very short-lived chlorinated substance (Cl-VSLS) that has the potential to contribute chlorine to the stratosphere and cause ozone depletion. Compared to other Cl-VSLS, DCE is produced in higher volumes for its primary use as a feedstock in polyvinyl chloride (PVC) manufacture. This production has sustained annual mean mole fractions at the Earth's surface of between 5 and 10 ppt during 2017–2023, making it the third most abundant Cl-VSLS after dichloromethane and chloroform. In this study we estimate mean global emissions for 2017–2023 of 453 ± 185 Gg yr−1 using the AGAGE observations, and 525 ± 209 Gg yr−1 using the NOAA observations. We also use AGAGE measurements to estimate regional emissions for northwest Europe (2.06 [1.31, 2.65] Gg yr−1) and California (0.23 [0, 0.37] Gg yr−1), two domains with sufficient observational coverage to enable this approach. Our global emissions estimates are consistent (within uncertainties) with the only previously published estimate by Hossaini et al. (2024), whereas our regional emissions estimates are at least an order of magnitude smaller than those in that study. This suggests global total emissions may be well constrained, but their spatial distribution remains uncertain.
2026
Modeling soil solution electrical conductivity across Europe
Soil salinization, referring to the excessive accumulation of soluble salts in soils, adversely influences nutrient cycling, biodiversity, soil structure, crop production, soil health, and ecosystem functioning. Accurately assessing soil salinity via electrical conductivity (EC) is key to mitigating its impacts. Thus, developing predictive tools for soil EC at regional and continental scales is essential for sustainable soil management. Here, we apply machine learning models to predict soil EC in the European Union (EU) and United Kingdom (UK) soils using different environmental factors like soil, climate, topography, and satellite data as predictors. The model is trained by ≈40,000 soil EC data points from the 2015 and 2018 Land Use/Cover Area Frame Survey data (LUCAS) surveys, complemented by the EC observations from World Soil Information Services (WoSIS) dataset. To improve the model performance, a forward feature selection technique was used resulting in selection of 17 covariates out of initially 34 predictors. The final selected XGBoost model achieved R2 values of 0.68, 0.6, and 0.63 for the training, internal testing, and independent validation datasets, respectively. For the year 2018, we estimate ≈21.7 Mha of EU + UK land exceeds an EC of 0.6 dS/m (at a 1:5 soil to water ratio, the so-called EC1:5). This estimate should be interpreted as elevated predicted EC1:5, rather than a direct estimate of soils meeting protosalic diagnostic criteria. The output of the predictive model consists of a gridded dataset that illustrates the spatial distribution of EC1:5 throughout the study area for the year 2018, along with an associated uncertainty map with a spatial resolution of 1 km.
2026
Heritable mutations in male germ cells pose a critical risk to human health and future generations, however standardized methods for assessing germ cell genotoxicity remain limited. We refined the in vivo alkaline comet assay (proof-of-concept (Dirven et al. 2023); protocol (Olsen et al. 2024)) to detect DNA damage in testicular germ cells, with selective addressment of haploid spermatids and primary spermatocytes. Measurements of DNA damage (% Tail DNA) and DNA content (total fluorescence intensity) in individual comets were combined with visual comet identification to distinguish testicular comet populations based on differences in DNA content and appearance. To verify the method’s functionality and reliability, DNA damage was assessed in rats exposed to the direct-acting, well-characterized genotoxicants X-rays and ethyl methanesulfonate across distinct testicular cell populations, alongside liver and blood. To minimize experimental variation, the protocol included stringent standardization of animal handling, tissue processing, and comet assay procedures. Both X-rays and EMS induced significant DNA damage in testicular germ cells, with comparable responses across testicular cell types and similar (X-rays) or higher levels observed in somatic tissues. The low inter-animal variability observed supports the robustness of the method. Importantly, inclusion of testicular germ cells in OECD test guideline 489 would provide a valuable tool for hazard identification and mutagenicity classification of chemicals under the Globally Harmonized System of Classification and Labelling of Chemicals. This versatile, sensitive, and resource-efficient assay enhances the assessment of male-mediated genetic risks and supports regulatory efforts to protect reproductive health and safeguard the genetic integrity of future generations through the use of safer chemicals.
2026
Unidentified Halon-2402 emissions in East Asia are driving the global trend
Halon-2402 (1,2‑dibromotetrafluoroethane, H-2402) is a potent ozone‑depleting substance and greenhouse gas whose global production has been banned under the Montreal Protocol since 2010, while the use of recovered or recycled stocks remains permitted for essential uses. Although these controls led to nearly two decades of declining atmospheric abundances, recent observations indicate renewed emissions. Here, we present the first observation-based regional emission estimates of H-2402 in East Asia for 2008–2023, derived using high-frequency measurements at Gosan, South Korea, and a Bayesian inversion framework. While most AGAGE stations measure background mole fractions or intermittent low-level increases, Gosan exhibits increasingly frequent and intense pollution events, revealing growing regional emissions. We find that East Asia accounted for most global H-2402 emissions in recent years, with particularly sharp increases in Japan and the Vladivostok region of Russia. Since 2015, regional emissions from East Asia have effectively driven the global emission trend, reversing the long-term decline. These emissions are spatially linked to petrochemical infrastructure, ship-repair activity, and military decommissioning sites, suggesting releases from legacy halon banks rather than new production. Cumulative emissions from East Asia between 2008 and 2023 reached ~52 Gg CFC-11-equivalent emissions. These findings imply a tangible delay in ozone layer recovery and underscore the urgent need for strengthened monitoring, transparent reporting, and verifiable management of remaining H-2402 stocks under the Montreal Protocol.
2026
Promoting healthy lifestyle behaviors such as physical activity, sleep, diet quality, stress management, hydration, and healthy habits requires adaptive systems capable of responding dynamically to changing behavioral and environmental conditions. However, the development and evaluation of personalized recommendation systems are challenged by fragmented observational data, privacy constraints, delayed feedback, and ethical limitations associated with long-term human experimentation. To address these challenges, this study proposes a digital twin-driven reinforcement learning framework for generating personalized behavioral recommendations in a fully simulated and statistically validated environment. The proposed framework formulates personalized behavioral recommendation as a stochastic Markov Decision Process (MDP) incorporating adherence uncertainty, behavioral drift, environmental modulation, and engagement dynamics. Synthetic longitudinal behavioral trajectories are generated through a digital twin simulator that models demographic heterogeneity, lifestyle behaviors, contextual variables, and variability in policy adherence over time. The optimization objective is defined through an effective reward formulation that balances behavioral compliance gains against penalties associated with health and environmental constraint violations. This study implements several reinforcement learning (RL) paradigms under simulated conditions, such as multi-armed bandits, table-based Q-learning, State-Action-Reward-State-Action (SARSA), function approximation-based temporal difference (TD) learning, and deep Q-learning network (DQN). The results demonstrate that richer state representations and context-dependent action dynamics are necessary for higher-capacity reinforcement learning models to consistently outperform simpler baselines. Furthermore, this study provides a reproducible method for comparing learning dynamics, performance, and computational cost in digital twin-based recommender systems. The framework additionally supports privacy-preserving experimentation through the exclusive use of synthetic behavioral data and locally controlled simulation environments.
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
This study presents results from an Intensive Measurement Period (IMP2022) conducted during the European heatwave of July 2022, focusing on ozone, volatile organic compounds (VOCs), and carbonaceous aerosols at 31 sites across Europe. The episode featured persistent high-pressure systems, record-breaking temperatures, widespread ozone exceedances and concurrent atmospheric new particle formation and growth events. Coordinated measurements and chemistry transport modelling were used to examine the spatial variability of ozone, VOC composition, and secondary organic aerosol (SOA) formation under extreme meteorological conditions. Oxygenated VOCs (O-VOCs) constituted the largest fraction of total measured VOC mixing ratios, followed by non-methane hydrocarbons (NMHCs) and aromatics, with contributions from both anthropogenic and biogenic sources. Sensitivity simulations indicate that ozone formation was predominantly NOx-limited across most regions during IMP2022. However, the highest ozone peaks occurred under conditions of elevated NOx in combination with enhanced BVOC emissions. In contrast, SOA formation was slightly enhanced under low-NOx conditions and reduced in elevated NOx. Isoprene, aliphatic NMHCs, and O-VOCs dominated the ozone formation potential, while aromatics and monoterpenes were major contributors to SOA potential. Model simulations indicated that higher NOx concentrations can reduce SOA formation by about 10 %. The campaign also highlighted observational gaps underscoring the need for broader and higher-resolution VOC monitoring across Europe. Overall, further reductions in NOx emissions, alongside targeted control of key anthropogenic VOCs, would benefit air quality under future climate extremes.
2026
An interlaboratory comparison (ILC) was conducted for levoglucosan, mannosan, and galactosan, as widely used organic tracers for assessing biomass burning aerosol in ambient air. Organized as part of the European research infrastructure ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure) activities the OrGanic Tracers and Aerosol Constituents - Calibration Centre (OGTAC-CC) distributed aliquots from three ambient PM2.5 filter samples and two prepared aqueous standard solutions to ten research laboratories across Europe, each using its own analytical protocol. Overall agreement was good for the ambient filter samples, with relative standard deviations relative to the general mean of 14% for levoglucosan, 22% for mannosan, and 33% for galactosan. Individual measurement accuracy, expressed as mean percentage error, ranged from −33% to 13% for levoglucosan, −51% to 15% for mannosan, and −54% to 42% for galactosan. Laboratory performance was also assessed using z-scores, showing that despite methodological diversity, nearly all results were classified as acceptable. This ILC provides a timely snapshot of current European laboratory capability for key biomass burning tracers. The joint intercomparison study demonstrates the readiness of European laboratories to provide harmonized levoglucosan measurements at a continental scale, meeting the comparability needs arising from the inclusion of levoglucosan in the revised EU Ambient Air Quality Directive (AAQD), and supporting requirements across European (Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP), ACTRIS) and national monitoring networks.
2026
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Hydrofluoroolefins (HFOs) are important synthetic compounds replacing other halocarbons in phase-down from usage (e.g., as refrigerants, propellants, foam blowing). Little is known about their atmospheric abundance, distribution and trends, nor about their emissons. Here, we report atmospheric observations of the widely used HFO-1234yf (2,3,3,3-tetrafluoroprop-1-ene), and HFO-1234ze(E) (E-1,3,3,3-tetrafluoroprop-1-ene), and the hydrochlorofluoroolefin (HCFO) HCFO-1233zd(E) (E-1-chloro-3,3,3-trifluoroprop-1-ene) observed as part of the Advanced Global Atmospheric Gases Experiment (AGAGE) network. Over the observational period 2011–2025, pollution events have grown in magnitude and frequency at sites which are influenced by regional emissions, while remote stations show first appearances of these substances. By 2024/2025 winter peak mole fractions in background northern hemisphere air have reached ∼ 0.25 ppt (picomol mol−1, parts-per-trillion in dry air) for HFO-1234yf and HFO-1234ze(E) and ∼ 0.45 ppt for HCFO-1233zd(E). Using European observations and the inverse modeling frameworks InTEM, ELRIS, and RHIME we determine emission trends and regional distributions. For Northwest Europe, emissions of HFO-1234yf increased steadily and rapidly from <0.1 Gg yr−1 in 2014 to 1.50 [1.23–1.74, range of 16–84 percentile] Gg yr−1 by 2023, presumably due to its introduction in mobile air conditioning and stationary refrigeration. HFO-1234ze(E) emissions were low during 2014–2017, followed by a rapid increase in 2018/2019, potentially due its introduction as an aerosol propellant, after which they increased more slowly to 0.96 [0.82–1.13] Gg yr−1 by 2023. HCFO-1233zd(E) emissions are derived from 2017 onward, showing a steady increase from 0.15 [0.07–0.23] to 1.04 [0.93–1.15] Gg yr−1 in 2023.
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
Biogenic volatile organic compound (BVOC) emissions from vegetation represent a major source of volatile compounds globally and play an important role as precursors for tropospheric ozone. Understanding their emissions is therefore crucial for quantifying the impact of ozone on air quality. We present two datasets of biogenic volatile organic compound emissions that cover the European modelling domain of the Copernicus Atmospheric Monitoring Service at a resolution of 0.1° × 0.1° to support the study of European scale air quality. The compounds included in the dataset follow the VOCs included in the regional atmospheric chemistry model mechanism (RACM). The datasets were produced within the framework of the EU's SEEDS project. We produced each dataset by coupling modelling output variables from the SURFEX land surface model with the MEGAN3.0 BVOC emission model. In one instance, the SURFEX model was run in free-running mode, which we term the open-loop (OL) and in the other case we assimilated satellite observations of leaf area index (LAI), which we term the analysis. The OL and analysis land surface model outputs form the basis for each emission dataset that are called SURFEX-MEGAN3.0 OL (https://doi.org/10.7910/DVN/LAUVTU, Hamer et al., 2025a) and SURFEX-MEGAN3.0 analysis (https://doi.org/10.7910/DVN/69G1FX, Hamer et al., 2025b), respectively. The OL dataset is available over a five-year period from 2018–2022 and the analysis dataset is available over the three-year period 2018–2020. SURFEX was run for both the OL and analysis simulations in a configuration that allowed simulated vegetation to respond to variations in meteorology over time to more realistically track vegetation phenology. Evaluation of the land surface model output LAI and root-zone soil moisture (RZSM) showed that the OL and analysis simulations had good skill at tracking temporal changes in both variables, with the analysis performing better in each instance. We perform a variety of evaluations on the isoprene emissions specifically given the importance of this compound for atmospheric chemistry. We evaluated the temporal variability of isoprene emissions in both datasets and found that the majority of the interannual and monthly variability was linked to variability in LAI that in specific cases, like the summer of 2019, could be linked to drought impacts on vegetation growth simulated by SURFEX. We evaluated the daily temporal variability of the OL and analysis isoprene emission datasets against in-situ online observations of isoprene concentrations at 8 sites in western Europe and found moderate to strong correlation between the emissions and observations in almost all location-year pairings. We also evaluated the OL and analysis emission datasets against other published bottom-up isoprene emission datasets over the same European domain used in this study. We found that the SURFEX-MEGAN3.0 OL and analysis isoprene emission datasets lie between the minimum (CAMS-GLOB-BIOv3.1) and maximum (MEGAN-MACC) published emission datasets based on bottom-up approaches. Furthermore, we were able to attribute differences in seasonality between SURFEX-MEGAN3.0 and other emission inventories to differences in the temporal variability of the underlying LAI dataset used to compile them. Overall, our findings show the importance of variability in LAI in controlling isoprene emissions on monthly to annual timescales. Combining this with the demonstrated skill of the emissions in evaluation with independent data, this points towards the value of an Earth-system approach to BVOC emission modelling.
2026
The Fire Modeling Intercomparison Project (FireMIP) for CMIP7
Fire is a global phenomenon and a key Earth system process. Extreme fire events have increased in recent years, and fire frequency and intensity are projected to rise across most regions and biomes, posing substantial challenges for ecosystems, the carbon cycle, and society. The Fire Model Intercomparison Project (FireMIP), launched in 2014, has advanced global fire modeling in Dynamic Global Vegetation Models (DGVMs) and improved understanding of fire's local and direct drivers and its local impacts on vegetation and land carbon budgets through land offline simulations (i.e., uncoupled from the atmosphere). We now bring FireMIP into Coupled Model Intercomparison Project Phase 7 (CMIP7) to: (1) evaluate fire simulations in state-of-the-art fully coupled Earth system models (ESMs); (2) assess fire regime changes in the past, present, and future, and identify their primary natural and anthropogenic forcings and causal pathways within the Earth system, including the associated uncertainties; and (3) quantify the impacts of fires and fire changes on climate, ecosystems, and society across Earth system components, regions, and timescales, and elucidate the underlying mechanisms. FireMIP in CMIP7 will advance the fire and fire-related modeling in fully coupled ESMs, and provide a quantitative, comprehensive, and process-based understanding of fire's role in the Earth system by using models that incorporate critical climate feedbacks and CMIP7 multi-model, multi-initial-condition, and multi-scenario ensemble. This protocol paper presents the motivation, scientific questions, experimental design and rationale, model inputs and outputs, and recommended analysis framework for FireMIP in CMIP7, providing guidance to Earth system modeling teams conducting simulations and informing communities studying fire, climate change, and climate solutions.
2026
2026
This study provides a short-term, dry-weather multi-compartment assessment of microplastic (MP) contamination in the Choghakhor Wetland, a vital freshwater ecosystem in western Iran. We quantified MPs in air, subsurface water, the surface water microlayer (SML), and sediments and developed a first-order mass-balance framework to clarify transport and fate. The SML showed much higher MP concentrations than the subsurface water when converted to volumetric units, while method-specific SML estimates varied among approaches (4.4–13.8 MP m⁻² using a glass tube; 196–982 MP m⁻² using a sieve; and 130–1754 MP m⁻² using filter paper). Subsurface water contained 0.083–1.5 MP L⁻¹, and the two sediment samples contained 60–400 MP kg⁻¹. Atmospheric deposition during the monitored intervals reached 2363 MP m⁻² h⁻¹. Flux analysis indicated that dry-weather influx exceeded observed outflux by more than three orders of magnitude. Using the conservative combined-outlet scenario, the wetland residence time was at least 168 days, whereas a water-only outlet scenario yielded ∼344 days. FLEXPART suggested that road dust dominated modeled source contributions, with smaller agricultural and soil-related contributions, although site-specific attribution remains model-based. These findings identify wetlands as important sinks and reservoirs of MPs, while emphasizing that the present results represent a dry-weather baseline rather than seasonal or annual conditions.
2026
Global mapping of city-level economic growth decoupling from fossil fuels
Cities seek to generate economic prosperity while reducing their dependence on fossil fuel combustion, yet tracking such progress at the city level remains challenging because of the limited and inconsistent emissions and economic data. Here we introduce an objective, globally consistent framework to measure decoupling between fossil fuel use and economic growth, either through reduced fuel use or shifts toward cleaner/more efficient combustion, proxied by tropospheric nitrogen dioxide columns combined with second-level administrative gross domestic product per capita based on purchasing power parity data. Analysing 5,435 cities globally over 2019–2024, we identify significant trends for 2,475 cities and classify them into 4 decoupling states. We find that 80% of these cities, mainly located in China, Europe and North America, enjoy relative decoupling, whereas 16%, mainly located in India and the Middle East, experience fossil fuel-dependent growth. Beyond these patterns, the described scalable satellite-based methodology can be revisited regularly to monitor city-level green growth and support urban policy effectiveness.
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
Understanding new particle formation (NPF) and the fate of nanoparticles is crucial because of their close links to air quality, cloud formation, and climate. These effects vary spatially and temporally owing to diverse aerosol sources and their relatively short atmospheric lifetime. Here, we present a comprehensive analysis of long-term trends in NPF-associated nucleation-mode particles and cloud condensation nuclei (CCN) concentrations across diverse observation environments using quality-controlled particle number size distribution (PNSD) and CCN data from 37 sites, primarily from Global Atmosphere Watch (GAW) stations. We identify declining decadal trends in both NPF occurrences and nucleated particle concentrations across most site types, with the strongest declines in urban areas. We observe simultaneous reductions in both CCN concentrations and nucleation-mode particles, suggesting that newly formed particles are a potential source of CCN. This, in turn, suggests that cloud microphysical properties and radiative effects can be indirectly influenced through aerosol–cloud interactions that modify cloud droplet formation. These findings indicate that decreasing anthropogenic emissions could influence the climate forcing potential of aerosol–cloud interactions, with important implications for future climate projections.
2026