Fant 10344 publikasjoner. Viser side 413 av 414:
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
Kan bli mer av dette – nå advarer forskere
Nye kriterier for emballasje peker på mer bruk av resirkulert plast. Men slik plast er ikke uproblematisk.
2026
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
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
Maritime sector pathways toward net-zero emissions within global energy scenarios
Abstract The maritime sector’s transition toward decarbonization cannot occur in isolation, rather it will be tied to broader transformations in energy, economic, and societal systems. Yet, most existing studies often overlook this integrated perspective, focusing primarily on sector-specific strategies without considering broader societal changes and energy availability on a global scale. To address this gap, this study integrates the MariTeam ship emission model into the MESSAGEix-GLOBIOM integrated assessment framework. Through this approach, we assess how climate scenarios may influence the maritime sector’s trajectory toward achieving net-zero emissions by 2050, in line with the International Maritime Organization (IMO) targets. Our findings indicate that action before 2030 is crucial and it can be achieved through combining four key solutions: improvements in energy efficiency, biofuels, liquefied hydrogen, and ammonia. Furthermore, the results suggest that the maritime sector could have access to enough renewables to achieve substantial emissions reductions with increase in final product costs ranging from 2 to 30% (interquartile range) with variations across products and regions. On average, cost increases are estimated at 10.2% for Global North countries and 13.3% for Global South countries. This analysis highlights the urgency and scale of transformation required for the maritime industry to meet the IMO’s net-zero ambitions and align with broader global sustainability goals.
2026
2026
Plastic pollution monitoring programs use a wide array of methods, protocols, and analytical approaches, making it difficult for researchers and practitioners to determine which techniques to apply, where, and how. This lack of harmonisation across environmental compartments and plastic size classes has led to inconsistent data and limited comparability across studies. To address this, a systematic review of monitoring methods from 1960 to 2021 was conducted, encompassing both peer-reviewed and grey literature. Techniques were categorised into Reproducible Analytical Pipelines (RAPs), each comprising six core steps: survey design, sample collection, sample preparation, analytical detection, quantification, and data reporting. Each RAP was assessed using Technological Readiness Levels (TRLs) to evaluate maturity and suitability for standardised monitoring. The review revealed that while robust and repeatable methods exist, they are inconsistently applied. At the time of this review, atmospheric plastics was underrepresented, highlighting a critical gap in monitoring efforts. The findings underscore the urgent need for a global, objective framework to guide the selection and implementation of plastic pollution monitoring methodologies. This paper lays the foundation for such a framework by presenting a methodology to identify mature, reproducible methods and prioritise areas for further development. Future work should focus on harmonising protocols across compartments and size classes, improving transparency in data reporting, and building consensus around standardised practices to enable global comparability and policy relevance.
2026
2026
New Approach Methodologies (NAMs) are gaining significant momentum globally to reduce animal testing and enhance the efficiency and human relevance of chemical safety assessment. Even with substantial EU commitment from regulatory agencies and the academic community, the full regulatory adoption of NAMs remains a distant prospect. This challenge is further complicated by the fact that the academic world, oriented toward NAMs development, and regulatory agencies, focused on practical application, frequently operate in separate spheres. Addressing this disconnect, the present paper, developed within the European Partnership for the Assessment of Risks from Chemicals (PARC), provides a clear overview of both the available non-animal tests and current evaluation practices for genotoxic and carcinogenic hazard assessment, while simultaneously highlighting existing regulatory needs, gaps, and challenges toward greater human health protection and the replacement of animal testing through NAMs adoption.
The analysis reveals a complex landscape: while the EU is deeply committed to developing and adopting NAMs, as outlined in its Chemical Strategy for Sustainability and supported by initiatives like PARC, prescriptive regulations such as Classification, Labelling and Packaging (CLP) and Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) still heavily mandate in vivo animal data for hazard classification, particularly for germ cell mutagenicity and carcinogenicity. This reliance creates a “too-short-blanket-problem,” where efforts to reduce animal testing may impact human health protection because of the current in vivo-based classification criteria. In contrast, sectors such as cosmetics and certain European Food Safety Authority (EFSA)-regulated products demonstrate greater flexibility toward progressive integration of NAMs. While the deep mechanistic understanding of genotoxicity and carcinogenicity has significantly advanced the integration of alternatives to animal tests into regulatory chemical hazard assessment, their broader and full implementation faces considerable challenges due to both scientific complexities (i.e., the development and validation of fit-for-purpose NAMs) and existing legislative provisions.
2026
2026
Abstract Potato plants are highly vulnerable to numerous diseases that can substantially affect both yield and quality. Conventional approaches for detecting these diseases are often labor-intensive, slow, and prone to inaccuracies, particularly under variable environmental conditions. This study presents a hybrid deep learning architecture, termed potato leaf diseases DenseNet (PLDNet) , which integrates a DenseNet-based convolutional neural network with a Transformer-based attention module to accurately classify potato leaf diseases. Furthermore, an adaptive parametric activation function, referred to as Adaptive Flatten p-Mish (AFpM) , is proposed to enhance the model’s learning flexibility and representational capacity. When evaluated on the PlantVillage and Mendeley datasets, PLDNet attains classification accuracies of 99.54% and 87.50%, respectively, surpassing contemporary state-of-the-art models and activation techniques. The proposed framework exhibits strong generalization performance and offers a scalable, efficient approach for automated plant disease identification. To highlight the novelty, the proposed AFpM activation function introduces a learnable parameter enabling adaptive nonlinearity, improving over Mish, Swish, and PFpM activation functions through dynamic gradient control. AFpM improves accuracy by 2.52% on Mendeley dataset, and 1.93% on PlantVillage dataset compared to PFpM, and by more than 3% compared to Swish and Mish.
2026
2026
2026
2026
Abstract Hierarchical agglomerative clustering is a useful analysis technique which allows for a level of stability, interpretability and flexibility not available in other similar techniques such as K‐means, density‐based clustering or positive matrix factorization. Previous studies using hierarchical clustering on atmospheric model output have been limited to small domain sizes (roughly 100 × 100 grid cells) by the computational expense and memory requirements of the algorithm. Here we present a scalable hierarchical clustering implementation that we apply to two year‐long, hourly atmospheric data sets: model concentration and deposition timeseries at 290,520 locations over Alberta and Saskatchewan (538 540 grid); and 366,427 multi‐pollutant observations from 51 national air pollution surveillance stations located across Canada. When combined with other information such as emissions source locations, orography, and prevailing meteorological conditions, the method yields coherent, interpretable structures. In the case of model time series, the clustering provides regions of similar air quality (airsheds) which can be used to inform air quality monitoring network placement, or regions of similar deposition which can inform critical load assessment as well as monitoring site locations. In the case of the multi‐pollutant observations, we show that a single low‐primary pollutant cluster appears the most frequently at all but one of 51 stations across Canada, accounting for 62% of all station‐hours, while elevated SO 2 appears in factor profiles at certain monitoring locations near industrial and shipping activity. Together, these results demonstrate that hierarchical clustering can efficiently summarize patterns relevant to airshed mapping and source apportionment at previously unreachable scales.
2026
The ISLAS2020 field campaign during February and March 2020 set out to obtain a unique dataset describing the Arctic water cycle using stable water isotope (SWI) observations. Our observation strategy focused on measuring evaporation, deposition, and precipitation, all of which are commonly sub-grid scale processes in numerical weather and climate models. Uncertain parameterizations for these processes can lead to compensating errors, which can go unnoticed; however, evaporation and precipitation can also be investigated with SWIs, as they are an integrated tracer for processes that atmospheric moisture has undergone. The campaign can be divided into two efforts: a localised field experiment in Ny-Ålesund focused on evaporation and deposition, and a larger precipitation collection network distributed around the Nordic Seas. The Ny-Ålesund field experiment lasted three weeks, from 23 February to 15 March 2020, with temperatures reaching below −30 °C. During these weeks, we obtained near-surface, high-resolution (approx. 20 cm) SWI profiles at two deployment sites. Using a newly developed profiling system, we measured SWI gradients in the lowermost 5 and 2 m over fjord water and snow-covered tundra, respectively. These profiles are complemented by fiber-optic distributed sensing (FODS) columns and ambient conditions from nearby meteorological stations. The FODS columns supply continuous, high-resolution (2 cm or finer) temperature profiles above both locations, whereas the meteorological stations provide information on wind speed and direction. We also made a short deployment to the Zeppelin mountain observatory (472 ma.s.l.) for measurements of the isotopic signal in the free-troposphere. Additionally, numerous water samples from the snowpack in and around Ny-Ålesund were taken, in addition to daily fjord water samples from Kongsfjorden. These samples provide the context for the surface conditions under which profiles were collected. Isotopic connections on the synoptic scale are achieved by linking Ny-Ålesund observations with precipitation sampling at locations across the European Arctic, namely Longyearbyen, Tromsø, Andenes, Ålesund, and Bergen. The resulting dataset provides comprehensive insight into the Arctic hydrological cycle and can facilitate the study of phase change processes and transport of water vapour into and out of the Svalbard region. Datasets from the field campaign are publicly available at the PANGAEA data repository (https://doi.org/10.1594/PANGAEA.971241, Seidl et al., 2024).
2026
Moss as an environmental factor
Did you know that stairstep moss can be used as a sampler for air pollution? Researchers at NILU have collected this kind of moss on several occasions and examined it for metals and other pollutants.
2026