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2026
2026
Detection of ozone recovery in the Arctic from ground-based measurements
Contrary to the Antarctic, where ozone recovery has been observed for about a decade, the detection of positive ozone trends in the Arctic remains challenging due to higher natural variability of ozone in that region. Using a merging of long-term ozone data from Fourier transform infrared spectrometers, ozonesondes, and Dobson and Brewer spectrophotometers, we present regional long-term trends (2000–2024) for total, stratospheric and tropospheric ozone. First, ground-based measurements are cross-compared to two satellite data sets (MEGRIDOP and IASI-CDR). This enables the detection of drifts in ground-based data sets we further exclude from our study. We then use a representativeness study based on CAMS re-analysis data to define regions for which representative trends with reduced uncertainties are obtained by combining data sets from different instruments and stations. Annual and seasonal trends are calculated using a multiple linear regression technique involving a set of proxies that represent physical processes influencing the natural ozone variability. Annual trends indicate increasing total ozone over the Arctic, and are statistically significant over Canada and Reykjavik (+2.1 % per decade) and North-West Europe (Harestua and Lerwick, +0.7 % per decade). Ozone recovery is also observed over Canada in the mid-stratosphere (+2.0 % per decade) and over the North Pole region (Canada and Ny-Ålesund) in the upper stratosphere (+2.1 % per decade to +3.8 % per decade). By analyzing the sensitivity of the ozone trends to the proxies, we observe a slow down of the expected ozone recovery, especially in the lower stratosphere, due to stratospheric cooling (−0.6 % per decade) and to the increase of volume of polar stratospheric clouds (−0.8 % per decade).
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
Organic aerosol (OA) is a major component of atmospheric particulate matter (PM), affecting both human health and climate. However, high-resolution estimates of OA exposure needed for exposure analysis remain scarce. Here, we integrate a chemical transport model (CAMx) with a random forest (RF) machine learning approach to bias-correct and downscale daily OA concentrations across Europe. CAMx OA simulations at ∼15 km resolution show moderate agreement with observations (r = 0.55). By combining these outputs with high-resolution land-use data and training the RF model on ∼48,000 daily OA measurements from 137 sites, prediction accuracy improved (r = 0.65), with ∼l5% reduction in root mean square error. The resulting maps provide European daily OA concentrations at ∼250 m resolution for alternate years from 2011 to 2019. The model captures key spatial features, including elevated OA in the Po Valley, Southeastern, and Central Europe, as well as intracity variations due to local hotspots. Seasonal analysis reveals higher concentrations in winter, while long-term trends indicate a general decline in OA levels. Exposure estimates show that half of the European population experiences OA levels above 3 µg/m3, and ∼50 million people are exposed to more than 5 µg/m3, which is the current guideline level recommended by the world health organization for total PM2.5. These high-resolution OA maps offer vital critical support for epidemiological research and air quality policy.
2026
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2026
2026
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
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
South Asia is a major contributor to global methane (CH4) emissions, yet its emissions remain poorly constrained, limiting targeted mitigation. Current bottom-up inventories do not consistently capture the magnitude and seasonality of CH4 emissions in this region, particularly during the monsoon. Here we quantify South Asian CH4 emissions for 2020 using column observations from a satellite instrument (TROPOMI), a Lagrangian transport model (FLEXPART), and a Bayesian inversion system (FLEXINVERT+). We estimate a posteriori emission of 73.0 ± 0.7 Tg yr−1 for South Asia, including 35.6 ± 0.5 Tg yr−1 for India and 13.2 ± 0.4 Tg yr−1 for Bangladesh. Agriculture and wetlands contribute substantially to the regional budget, with the flux increments coincident with rice-growing areas and inundated lowlands. The inversion indicates pronounced monsoon-modulated seasonality in South Asia: posterior fluxes are higher than the prior by about 19.3 Tg CH4 (an increase of ∼ 70 %) during June–September and lower during January–May by ∼ 46 %. Localized enhancements seen over the lower Indus Basin align with runoff patterns, while the seasonal peaks here are absent in inventories. By resolving monsoon seasonality with satellite constraints, our results point towards key uncertainties in the South Asian CH4 budget and underscore the need for process-based, seasonally responsive inventories to inform mitigation strategies and reconcile bottom-up and top-down estimates.
2026
Abstract Significant trends of ultraviolet radiation (UVR) have been reported at limited European sites due to changing atmospheric conditions, such as cloudiness. Whether these findings are applicable to larger areas or even the entire continent remains unclear. In a unique comparison, we analyzed measurements of erythemally weighted daily ambient radiant exposure from 40 European locations, covering the period from 2013 to 2022. At 26 locations annual means increases statistically significantly with a median of + 1.2%/yr. At 38 sites at least monthly means increases with medians between + 2%/yr and + 4%/yr. Increases were seen in satellite products of UVR, global solar radiation, and sunshine duration, too. Analysis at six stations, with data extending back to the mid-1990s, indicates that the period of statistically significant increases generally began between 2010 and 2013. Comparison of UVR data from 40 stations with a high-resolution global solar radiation trend map reveals complementary patterns, highlighting widespread but not uniform UVR changes across Europe. This combination enables figuring out the regional extent of trends. Thus, ground-based UVR measurements remain essential for quantifying changes, highlighting the need for continued monitoring with sufficiently dense measurement networks. This is also essential for understanding and mitigating the impacts of changing UVR on human health, particularly by assessing its potential for increased UVR-related skin cancer incidence and development of preventive measures. Moreover, detailed regional UVR data is essential for achieving the UN’s Sustainable Development Goals, specifically in human health, sustainable cities, climate action, and environmental conservation.
2026
Efficacy of individual and combined terrestrial and marine carbon dioxide removal
Abstract Limiting global temperature rise below 2°C requires significant reduction in greenhouse gas emissions and likely large-scale carbon dioxide removal (CDR). This study assesses the CO2 sequestration and efficacy of two CDR approaches, Bioenergy with Carbon Capture and Storage (BECCS) and Ocean Alkalinity Enhancement (OAE), applied individually and in combination. Using the Norwegian Earth System Model (NorESM2-LM), simulations were designed to ramp up deployment of BECCS and OAE, to an additional area of 5.2 million km² by 2100 for bioenergy feedstock for BECCS, and a CaO deployment rate of approximately 2.7 Gt/year for OAE within the exclusive economic zones of Europe, the United States and China. The combined land-ocean CDR simulation revealed a largely additive carbon removal effect. Over 2030-2100, OAE sequestered 7 ppm of CO 22 with an accumulated 82.3 Gt CaO, achieving a CDR effectiveness of 0.08 ppm (~ 0.17 PgC) per Gt CaO, while BECCS reduced 16 ppm of CO2, with CDR effectiveness of 3.1 ppm per million km² of bioenergy crops. Together, the carbon removal achieved by BECCS and OAE corresponds to anthropogenic CO₂ emissions of 5.4 Gt CO₂/year by 2100, slightly more than 60% of current global transport sector emissions. Notably, the efficiency of BECCS and OAE alone was unaffected by their concurrent deployment. Nevertheless, simulations revealed distinct non- linear interactions, such as declines in land and soil carbon sinks in the combined scenario. Furthermore, all simulations show negligible effects on the global annual mean temperature. These results highlight near-additive CDR responses even under net-negative emissions, but feedback on land and ocean carbon sinks must be considered when designing CDR portfolios. This study provides new insights into CDR portfolio design and Earth system feedback under an overshoot scenario, highlighting both their potential and the need for continued emissions cuts and supportive policies.
2026
2026
2026
The Arctic is warming up to 4 times faster than the global average, leading to rapid ice melting and consequently, a drastic change of the sources and processing of aerosols and their impact on clouds. Monitoring of these changes over the Arctic is extremely sparse, especially in the most remote regions where harsh conditions make it difficult to carry out even simple measurements. To address these knowledge gaps and develop better and new methods of remote sensing of aerosols and clouds, the CleanCloud project carried out the field campaign CLeancloud Arctic VIllum ExpeRiment (CLAVIER) at Villum Research Station (VRS) in northeast Greenland to study aerosol-cloud interaction (ACI) using in-situ surface and remote sensing as well as airborne measurements.CLAVIER covered two phase; spring (April) and summer (July/August) 2024, each lasting for one month. We have employed the existing in-situ surface aerosol monitoring at VRS, which includes a Scanning Mobility Particle Sizer (SMPS), a Cloud Condensation Nuclei Counter (CCNC), a High-Volume Sampler (HVS), a Nephelometer, an Aethalometer, a Neutral cluster and Air Ion Spectrometer (NAIS), a wind lidar and a ceilometer. During CLAVIER, the site was additionally equipped with a AeRosol aerosol-cloud lIdar System (ARIS lidar) and a Wideband Integrated Bioaerosol Sensor (WIBS-5/NEO) to provide realtime measurement of aerosols and fluorescent particles to infer the presence of bioaerosols and their potential contribution to Ice Nucelating Particles (INP). In addition, a W-band Cloud Doppler Radar (WProf) and a tethered balloon (Helikite) was operated during the spring phase. The helikite was equipped with aerosol and cloud instrumentation, including a Portable Optical Particle Spectrometer (POPS), a Miniaturized Scanning Electrical Mobility Sizer (mSEMS), a Single-channel tricolor absorption photometer (STAP) and a miniaturized Cloud Droplet Analyzer (miniCDA), and a filter sampler with the new nano-electromechanical membrane FTIR (NEMS-FTIR) technique. A second tethered balloon was also employed for meteorological and flux measurements. In the summer phase, a Proton-Transfer-Reaction Mass Spectrometry (PTR-MS) was used to measure VOCs online and cartridge sampling was performed for offline sampling of VOCs, as well as a WELAS (white-light aerosol spectrometer) for size distribution of larger sizes and the newest aethalometer AE36s. Finally, summertime measurements were also coordinated with the NASA ARCSIX aircraft mission for clousure experiments. In order to get a better understanding of the processes related to aerosol-cloud interactions, several modelling activities were and are being carried out for the CLAVIER period. These include the Flexible Particle Dispersion Model (FLEXPART), the WRF-SIP model to study in detail the secondary ice production in clouds, OpenIFSv48 global model to simulate the aerosol composition and forcing during the campaign, and finally, the FLEXPART-SOSAA framework and the ADCHEM model to study in detail the aerosol chemistry and impacts on CCN.This presentation will provide an overview of these activities and some preliminary results.
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
Environmental Contaminants in an Urban Fjord, 2025
This report presents data from the last year of a 5-year period of the Urban Fjord programme. The programme started in 2013 and has since been altered/advanced. In 2025 the programme covers sampling and analyses of sediment, polychaetes, krill, shrimps, blue mussels, herring, cod, eider, and herring gull from the Inner Oslofjord. A total of 230 single compounds/isomers were analysed, and frequent detection was found of specific PFAS compounds (e.g. PFOS) in most matrices, certain QACs in several matrices (ATAC-C22 in all
matrices), specific benzothiazoles in eider blood, LCCPs in certain matrices, certain siloxanes in most matrices, metals in all matrices and PCBs in all matrices. Biomagnification was observed for 24 PCB congeners, LCCPs and D4 (siloxane; lipid wt. basis). Furthermore, biomagnification was observed for PFOSA, ATAC-C20 and ATAC-C22, as well as for the metals As and Hg (wet wt. basis).
Norsk institutt for vannforskning (NIVA)
2026
Evaluating the role of low-cost sensors in machine learning based European PM2.5 monitoring
We evaluate the added value of integrating validated Low-Cost Sensor (LCS) data into a Machine Learning (ML) framework for providing surface PM2.5 estimates over Central Europe at 1 km spatial resolution. The synergistic ML-based S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) approach is extended, to incorporate LCS data through two strategies: using validated LCS data as a target variable (LCST) and as an input feature via an inverse distance weighted spatial convolution layer (LCSI). Both strategies are implemented within a stacked XGBoost model that ingests satellite-derived aerosol optical depth, meteorological variables, and CAMS (Copernicus Atmospheric Monitoring Service) regional forecasts. Model performance for 2021–2022 is evaluated against a baseline trained on air quality monitoring stations without any form of LCS integration. Our results indicate that the LCSI approach consistently outperforms both the baseline and LCST models, particularly in urban areas, with RMSE reductions of up to 15–20 %. It also exhibits higher accuracy than the CAMS regional interim reanalysis with a lower annual mean absolute error (MAE) of 2.68 μg/m3 compared to 3.32 μg/m3. SHapley Additive exPlanations based analysis indicates that LCSI information improves both spatial and temporal representativeness, with the LCSI strategy better capturing localized pollution dynamics. However, the LCSI's dependency on the spatial LCS layer limits its ability to capture inter-urban pollution transport in regions with sparse or no LCS data. These findings highlight the value of large-scale sensor networks in addressing spatial coverage gaps in official air quality monitoring stations and advancing high-resolution air quality modeling.
2026
Abstract The International Cooperative Programme on Integrated Monitoring of Air Pollution Effects on Ecosystems (ICP IM) presents a comprehensive long-term dataset of ongoing integrated ecosystem monitoring from European forested catchments. The dataset encompasses measurements from 46 monitoring stations across 14 European countries, with temporal coverage mostly extending from the early 1990s to 2020 (48 sites are currently active). The integrated monitoring approach applies over 20 monitoring subprogrammes to simultaneously measure physical, chemical, and biological properties across multiple ecosystem compartments including atmosphere, precipitation, throughfall, soil water, groundwater, runoff water, soil, vegetation, and biota. All measurements follow standardised protocols detailed in the ICP IM Manual, ensuring data quality and comparability across sites and time periods. The dataset supports research on ecosystem responses to air pollution, climate change impacts, and biogeochemical cycling. Data are available under a Creative Commons By Attribution (CC BY) licence, providing valuable long-term environmental monitoring data for the scientific community.
2026
Indoor environments have shown to be a major source of human exposure of polychlorinated alkanes (PCAs), yet information on their distribution across indoor matrices and associated exposure pathways remains limited. PCAs, the main components in chlorinated paraffin mixtures, are widely used as flame retardants and plastic additives in numerous indoor consumer products and materials. This study quantified PCAs in paired indoor dust and indoor organic films (IOFs) from homes, offices, schools and gym sports halls (n = 41) in Sweden and assess their contribution to human exposure. Mean PCA concentrations in indoor dust were 7.3, 43.2, and 14.6 μg g−1 for ∑PCAs-C10–13, ∑PCAs-C14–17, and ∑PCAs-C18–30, respectively, while corresponding concentrations in IOFs were 38.2, 312, and 123 ng m−2. PCAs-C14–17 dominated both matrices, but IOFs showed an enrichment tendency towards longer-chain, higher-KOA PCAs, reflecting the less frequent cleaning and longer-term PCA accumulation in IOFs. IOF concentrations were particularly elevated in schools, and PCA variation across sites was influenced by differences in ventilation practices and building age. Dermal uptake was the dominant exposure pathway for children, with substantially estimated doses from IOFs, while adults show comparable dust dermal and dust ingestion exposures. PCA transformation products formed through hydroxylation, hydrolysis, and sulfation were also tentatively detected in both matrices. These findings highlight the importance of jointly assessing dust and IOFs to better characterize multipathway exposure to the diverse PCA mixture in indoor environments.
2026
2026
Organic aerosol particles (OA) can absorb solar radiation with varying efficiencies depending on their chemical composition and physical properties. This light-absorbing fraction of OA, commonly referred to as brown carbon (BrC), is difficult to accurately represent in climate models due to the inherent diversity of its optical properties. This variability arises from differences in emission sources and atmospheric processing, as well as from variations in experimental design and the analytical methods used to quantify BrC absorption. As a result, the climate effect of BrC remains uncertain. Here, we studied the light absorption properties of surface ambient OA using measurements from 17 sites across Europe. Combining multi-wavelength absorption measurements from filter-based photometers with OA mass concentrations and source apportionment derived from ACSM/AMS data, we derive empirical estimates of the OA mass absorption cross section (MAC OA ), its wavelength dependence (AAE OA ), the OA density (⍴ OA ), and the MAC associated with different primary and secondary OA sources. We further develop parameterizations that relate MAC OA , AAE OA and ⍴ OA to the ambient black carbon-to-organic aerosol ratio (eBC/OA) and propose a corresponding parameterization for the imaginary refractive index (k OA ). Given the widespread availability of eBC and OA measurements in global monitoring networks, the framework presented here provides a practical approach for estimating the absorptive properties of surface OA particles under real-world conditions.
2026