Found 10359 publications. Showing page 410 of 415:
Divergent impacts of climate interventions on China’s north-south water divide
Abstract Solar radiation modification-based climate interventions may cause uneven regional hydrological changes while mitigating warming. Here, we investigate the effects of climate interventions on China’s North Drought-South Flood pattern using the Norwegian Earth System Model supplemented by volcanic data. Our results indicate that equatorial stratospheric aerosol injection could mitigate the north-south water divide by reducing inter-hemispheric and equator-to-North-pole temperature gradients, thereby modifying atmospheric circulation and the East Asian monsoon to increase precipitation and surface runoff in northern China while reducing them in the south, compared to the high emissions scenario. This mechanism is supported by observed precipitation changes following the Mount Pinatubo volcanic eruption. In contrast, marine cloud brightening may intensify southern flood risks, while cirrus cloud thinning and moderate emissions reduction might exacerbate northern droughts. Our findings reveal distinct regional hydroclimatic impacts of different climate interventions, highlighting potential synergies and trade-offs between their global intervention efficacy and regional water security.
2025
Tidal Amplification in the Lower Thermosphere During the 2003 October–November Solar Storms
Abstract Using the National Center for Atmospheric Research's vertically extended version of the Whole Atmosphere Community Climate Model nudged with reanalyses, we examine the impact of the 2003 Halloween solar storms on atmospheric tides and planetary waves in the lower thermosphere (LT). One of the largest solar flares and fastest coronal mass ejections on record occurred on 30 October, resulting in significant energy transfer via Joule heating and auroral particle precipitation in the Earth's higher latitude thermosphere. In the simulation, that occurrence creates large zonally asymmetric heating perturbations, amplifying the diurnal migrating tide (DW1), semidiurnal migrating tide (SW2), as well as non‐migrating westward and eastward tides between 120 and 200 km. Large‐amplitude bursts of DW1 in the Northern Hemisphere and non‐migrating westward tides in the Southern Hemisphere lead to westward wave forcings, which strengthen the thermospheric wind. Planetary waves are also amplified, but their forcing is much weaker than the forcing exerted by tides in the LT. Non‐migrating tides are generated by nonlinear interactions between tides, or between tides and quasi‐stationary planetary waves, and in situ processes in the LT linked to Joule heating and auroral particle precipitation. The induced disruptions of the thermospheric mean meridional circulation reinforce the Spring thermospheric branch in the Southern Hemisphere at high latitudes and oppose the Fall branch in the Northern Hemisphere. Our examination could be relevant to understand the dynamical impact of recent geomagnetic storms that occurred in May 2024 and October 2024.
2025
The semi-annual oscillation (SAO) dominates seasonal variability in the equatorial stratosphere and mesosphere. However, the seasonally dependent modulation of the SAO in the stratosphere (SSAO) and mesosphere (MSAO) by sudden stratospheric warmings (SSWs) in the Arctic has not been investigated in detail. In this study, we examine the seasonal evolution of the SAO during 16 major SSW events spanning 2004 to 2024 using the Japanese Atmospheric General Circulation Model for Upper Atmosphere Research Data Assimilation System Whole Neutral Atmosphere Re-analysis (JAWARA). Basic features of the SAO are well captured by JAWARA, as evidenced by the SSAO and MSAO appearing at around 50 km and 85 km, respectively. The different responses of the SAO to early and late winter SSWs are particularly strong during the Northern Hemisphere winter of 2023/24. Early winter SSWs tend to significantly intensify the westward SSAO, while late winter SSWs tend to weaken the eastward SSAO. Similarly, the eastward MSAO is amplified during early winter SSWs, whereas the westward MSAO is slightly weakened during late winter SSWs. The weak MSAO response is probably due to its smaller climatological magnitude. Modulation of the SAO by SSWs is related to meridional temperature changes during SSWs through the thermal wind balance. Our findings contribute to the understanding of coupling between the tropics and high latitudes, as well as interhemispheric coupling.
2025
2025
Tore har 52 flyreiser på ett år: – Flaut
Tore Christian Sævold lever et dobbeltliv. I ti år har han pendlet fra Stockholm til Bergen for å holde liv i skuespillerkarrieren.
2025
2025
2025
Anthropogenic particles in surface waters from Adventfjorden (Svalbard)
The ubiquitous presence of microplastics and other anthropogenic compounds in the marine environment are unfortunately not surprising anymore. Recent publications are revealing the occurrence of those synthesized particles in even remote and/or pristine areas in different marine matrices like biota, water and sediment. Nevertheless, the knowledge about sources and transport mechanisms of those anthropogenic particles (APs) is still lacking, especially in the Arctic. In this study we investigated surface waters from Isfjorden and the branching Adventfjorden, where Longyearbyen the largest settlement of Svalbard is located. Here, untreated wastewater is released into the fjord system. At two sample sites upstream and two sample sites downstream, three replicates at each location have been collected in June 2021. APs larger than <50μm were investigated regarding size, shape, and polymer type via μFTIR spectroscopy. At each sampling station, APs were present. The highest concentration of APs was found upstream and downstream Isfjorden; whereas lower concentrations were found within Adventfjorden, closest to the wastewater outlet. Additives and polypropylene showed the highest frequencies. Besides local sources like the untreated wastewater, freshwater inputs, ship traffic or the northwards long-range transport from the south into the Arctic needs to be considered.
2025
Exposures in Indoor Air Affecting Health
Indoor air quality (IAQ) is influenced by a wide range of chemical, biological and physical agents that can negatively impact physical, immunological and mental health. Adverse health effects depend on the type and concentration of pollutants, duration of exposure, and individual susceptibility. The availability of data on IAQ is limited, as are standardized approaches for evaluating its health impact. This expert review aims to describe the most important indoor air determinants affecting health, and present the IDEAL cluster, which comprises seven EU‐funded scientific projects on the topic of IAQ and human health. Across the IDEAL projects, knowledge is generated on exposure to a wide range of indoor air pollutants, including well‐known hazards and more explorative chemical and microbiological determinants. The projects will also contribute to the implementation of low‐cost and/or real‐time sensors on IAQ, as well as advanced chemical and microbiological analyses, and evaluate various interventions to improve IAQ. Several of them focus on particularly vulnerable groups. Raising public awareness and implementing measures to reduce pollutant levels are essential for safeguarding health, particularly in urban areas with elevated pollution levels.
2026
Suspect screening helps detect chemicals in environmental samples without predefined target lists which can facilitate isolation of a larger number of substances. This study shows however that no single extraction method or analytical platform (LC-HRMS or GC-HRMS) can capture all relevant pollutants—at least half are missed. The technique works best for chemically similar families, where optimized methods can target specific classes or broader families of similar substances (e.g. PFAS). Effective grouping of similar substances is therefore essential. A broad coverage of substances can however be achieved if multiple sample extractions are performed and each extract is analysed on both LC- and GC-HRMS. Strategies where comparisons can be made over time or across locations will also help to isolate pollutant-related signals from the background. Such considerations must be integrated into programme design and budgeting for retrospective analysis. This will maximize likelihood of detection for the largest diversity of substances.
Norwegian Environment Agency, M-3038|2025
NILU
2026
2026
Franzefoss Husøya Kristiansund. Målinger av ammoniakk NH3 og flyktige organiske forbindelser VOC
NILU
2026
2026
Marine Carbon Removal Gains Momentum But Can It Scale Responsibly?
As mCDR gains global traction, we discuss the current state of this sector with leading mCDR representatives.
2026
Årsrapport 2025. Nasjonalt referanselaboratorium for luftkvalitetsmålinger
Denne rapporten oppsummerer oppgavene til Nasjonalt referanselaboratorium for luftkvalitetsmålinger (NRL), delkontrakt 1b, for året 2025.
NILU
2026
Tracing the air–sea exchange of microplastics over the Caspian Sea
The global proliferation of microplastics (MPs) is increasingly recognized as a transboundary environmental issue. At the air–ocean interface, MPs can be emitted via sea spray and transported back to land, while terrestrial MPs can likewise be advected and deposited over the oceans. However, the long-term net exchange of MPs between land and ocean via the atmosphere remains poorly constrained. Here, we investigate coastal atmospheric MPs and their near-surface landward and seaward transport over the southern Caspian Sea. Using a combination of passive air sampling (at seven heights with MWAC collectors) and active sampling (vacuum pump) over periods of 3 days and 2 months, respectively, together with coastal surface sediment samples, we quantified MP concentrations and assessed the influence of meteorological and environmental factors on their distribution. Fibrous MPs dominated all compartments, with airborne concentrations averaging 3.85 MP m−3 and sediment concentrations ranging from 507 to 1476 MP kg−1 (dry weight). Estimated near-surface horizontal fluxes were comparable in magnitude, with a landward influx of ~6566 MP m−2 h−1 and a seaward outflux of ~8039 MP m−2 h−1, indicating broadly balanced coastal transport during the 72 h campaign. To support source attribution, we evaluated co-trapped particulate proxies (sea salt and ash) and combined them with FLEXPART modelling. Trajectory modelling and proxy evidence indicate that most airborne MPs originated from inland sources (e.g., road dust and textile-related fibres), while marine sea-spray contributions were minor during the sampling period. These findings highlight the importance of long-range atmospheric transport in coastal MP pollution and demonstrate how integrating proxy observations with dispersion modelling can help constrain likely source regimes.
2026
2026
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
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