Fant 10464 publikasjoner. Viser side 4 av 419:
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
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
Nonlinear Atmospheric Inversion with Interpretable Bias Correction via Gaussian Process Prior
Accurate quantification of atmospheric pollutant emissions is essential for evaluating the consequences of environmental incidents. Inverse modelling of such releases commonly employs a linear framework based on a source–receptor sensitivity (SRS) matrix; however, this matrix can be substantially biased or may even fail to represent the true scale of the release. We introduce a method in which the SRS matrix is corrected jointly with the inversion, resulting in a nonlinear inverse problem. The SRS discrepancies are interpreted as small shifts of observation points, leading to a deformation of the sensitivity field. The shifts are regularized through a Gaussian process prior, which imposes smoothness and sparsity while allowing inference at unobserved locations. The resulting posterior predictions of the shift field offer a practical tool for hyperparameter selection: the inferred shifts can be visualized geographically and evaluated by domain experts. This leads to a Bayesian framework that integrates inversion, SRS correction, and a tuning strategy based on L-curve-type diagnostics combined with maps of the predicted shifts. It will be demonstrated on a selected real continental-scale scenario of an atmospheric release. This research has been supported by the Czech Science Foundation (grant no. GA24-10400S). FLEXPART model simulations are cross-atmospheric research infrastructure services provided by ATMO-ACCESS (EU grant agreement No 101008004). Nikolaos Evangeliou was funded by the same EU grant. The computations were performed on resources provided by Sigma2 - the National Infrastructure for High Performance Computing and Data Storage in Norway.
2026
Inverse modelling is employed to reconcile greenhouse gas (GHG) emission inventories, based on bottom-up methods, with the observed atmospheric GHG concentrations. The Community Inversion Framework (CIF) was created to unify inverse-model developments and simplify the generation of inversions. It makes atmospheric transport models and inversion algorithms easily interchangeable and facilitates the comparison of inversion results obtained using such diverse components.After several years of development and the coupling of CIF with a wide range of transport models used by the inversion community, we present the first intercomparison study conducted with CIF. This exercise focuses on Europe and aims to refine CO₂ natural emissions for the year 2019, following a strict protocol. It involves five transport models (CHIMERE, ICON-ART, LMDz, STILT, and WRF-CHEM) and two inversion algorithms (variational and ensemble-based). Two additional transport models, TM5 and FLEXPART, will be incorporated in the near future.The results show a good agreement, both across transport models, and inversion algorithms. It paves the way towards using CIF as an operational tool for intercomparison studies. It also highlights its strong potential to support the systematic derivation of GHG budgets with multiple transport models, enable a proper and easy quantification of the modelling uncertainty, and improve the robustness of emission estimates, for any relevant atmospheric species, at any scale.
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
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
Biogenic volatile organic compound (BVOC) emissions from European vegetation are a major precursor of tropospheric ozone and remain a key uncertainty in regional air-quality modelling. We present two high-resolution (0.1° × 0.1°) European BVOC emission datasets developed within the EU SEEDS project aimed at supporting scientific development within Copernicus Atmospheric Monitoring Service (CAMS). The datasets include BVOC species consistent with the RACM chemical mechanism and are generated by coupling the SURFEX land surface model with the MEGAN3.0 emission model.Emissions based on two land surface model simulations were analysed: (i) an open-loop SURFEX simulation available for 2018–2022, and (ii) a data-assimilation simulation in which satellite leaf area index (LAI) observations are assimilated, available for 2018–2020. In both cases, SURFEX is configured to allow vegetation phenological responses to meteorological variability, enabling a realistic representation of phenology. Evaluation against independent datasets shows that both simulations capture temporal variability in LAI and root-zone soil moisture, with improved skill in the analysis configuration.Given its importance for atmospheric chemistry, we focus on isoprene emissions. Interannual and seasonal variability in isoprene emissions is shown to be primarily driven by LAI variability, with specific events (e.g. summer 2019) linked to drought-induced vegetation stress simulated by SURFEX. Daily variability in isoprene emissions is evaluated against in-situ online isoprene concentration measurements at eight western European sites, revealing moderate to strong correlations across most site-year combinations. Comparisons with other bottom-up European isoprene inventories show that SURFEX-MEGAN3.0 emissions lie between the lower CAMS-GLOB-BIOv3.1 and higher MEGAN-MACC estimates, with differences in seasonality attributable largely to the underlying LAI datasets.These results highlight the important role of vegetation phenology, particularly LAI variability, in controlling BVOC emissions on monthly to interannual timescales, and demonstrate the added value of an Earth-system approach for BVOC emission modelling in support of air-quality assessments.ReferencesHamer, . D., Markelj, M., Rojas-Munoz, O., Bonan, B., Calvet, J.-C., Marécal, V., Guenther, A., Trimmel, H., Vallejo, I., Eckhardt, S., Sousa Santos, G., Sindelarova, K., Simpson, D., Schmidbauer, N., and Tarrasón, L.: Two Biogenic Volatile Organic Compound Emission Datasets over Europe Based on Land Surface Modelling and Satellite Data Assimilation, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2025-442, in review, 2025.
2026
2026
The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) is the European Research Infrastructure Consortium (ERIC) dedicated to short-lived atmospheric constituents and clouds, supporting fundamental research and excellence in Earth system observation. ACTRIS produces high-quality, integrated long-term datasets in the field of atmospheric sciences and provides services tailored for scientific and technological use, including access to instrumented observational platforms. To enhance the availability, usability, and scientific exploitation of these datasets across disciplines and user communities, the ACTRIS Data Centre (DC) develops a range of user-oriented services, among which the ACTRIS Virtual Research Environment (VRE) plays a central role. The ACTRIS VRE enables efficient discovery, access, and scientific analysis of long-term observational data from ACTRIS National Facilities as well as other ground based observational sites as e.g. EMEP, EARLINET, Cloudnet and GAW. It facilitates analyses such as calculation of climatologies, long-term trend assessments, and the combination of datasets within the ACTRIS domain. The VRE is developed in collaboration between the ACTRIS DC and the ACTRIS-Norway community and is designed to serve both data producers and data users, ranging from infrastructure operators to researchers and students, across a wide range of atmospheric research applications. This presentation demonstrates the use of the ACTRIS VRE through selected notebook-based examples of higher-level data analysis and highlights the collaborative scientific efforts underlying its development. Data access within the VRE is based on the ACTRIS metadata REST API. ACTRIS datasets are provided in CF-compliant NetCDF format and are accessible through both streaming services (OPeNDAP) and direct HTTPS download. This approach enables flexible, reproducible, and programmatic data use, supporting interoperability with commonly used analysis tools and workflows. In collaboration with the ACTRIS-Norway community, the VRE includes several examples combining datasets for long time series analysis, the exploration of climatologies, and the investigation of trends. Selected examples are presented and discussed, with particular focus on the combination of FLEXPART footprint products and black carbon source apportionment data, developed within the EU project ATMO-ACCESS, together with observed equivalent black carbon measurements at several ACTRIS National Facilities. Additional higher-level analysis examples include single scattering albedo (SSA), ultrafine particle number concentrations (UFPs), and PM₁ source-related metrics from wood burning and traffic. These examples highlight how ACTRIS data can be applied to both climate-relevant and air-quality-focused research questions. Beyond scientific analysis, the ACTRIS VRE also serves as a platform for education and capacity building. Introductory notebooks demonstrate programmatic access to data and metadata and illustrate best practices for scientific analysis. The VRE has been used in ACTRIS training courses, ACTRIS Week, ITINERIS training workshops, and dedicated events at NILU, including collaborations with EUMETSAT, highlighting its role as a reusable training and demonstration environment. Community contributions to the example library are encouraged through an open GitHub repository, fostering collaborative development and reuse. The ACTRIS Virtual Research Environment is openly accessible at https://data.actris.eu/vre.
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
Måling av svevestøv i Fiskåveien (Kristiansand). Kalenderår 2025
Kristiansand kommune, Agder Fylkeskommune og Elkem Carbon Fiskå etablerte et måleprogram for PM10 og PM2.5 på Fiskå. Formålet er å kartlegge svevestøvnivået sørvest for Fiskå Teknologipark. Mulige svevestøvkilder er industri, veitrafikk og vedfyring. I 2025 ble alle grenseverdiene og vurderingstersklene for svevestøv overholdt. Lokale meteorologiske målinger og kombinasjon med andre svevestøvmålinger i Kristiansand peker på regionale forurensningsepisoder, bidrag fra nær industri og ukjente kilder som forklaringer for de høyeste målte PM konsentrasjonene.
NILU
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
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
2026
2026
2026