Fant 10464 publikasjoner. Viser side 405 av 419:
Building-related symptoms in school environment: Predictability using machine learning approach
Building-related symptoms (BRS) are commonly experienced by students in schools and are potentially affecting academic performance and health. Even though indoor environment quality (IEQ) measurements indicated fair conditions, students still perceived discomfort that led to symptoms, highlighting the necessity of collecting user-feedback about IEQ-complaints. This study aimed to predict and understand the prevalence of BRS (headache, tiredness, cough, dry eyes-hands) experienced by students in classrooms using machine-learning (ML) approach based on measurement data, building factors, and prevalence of IEQ-complaints. We collected measurement data (from indoor and outdoor climate), building factors, and user-feedback by students via online-platform across three sampled classrooms each campaign during three consecutive school semesters. Significant input variables for ML were pre-selected using statistical tests. ML models were evaluated based on accuracy metrics and SHAP analysis for input interpretation. Models using measurement data alone performed poorly (testing R² <50 %) to predict prevalence of BRS, whereas adding building factors and prevalence of IEQ-complaints increased accuracy (R² up to 95 %) of prediction of BRS with lower RMSE. In addition, interpretation from SHAP analysis showed IEQ-complaints especially related with indoor air quality (e.g., heavy air, dust & dirt, and dry air) as significant contributors for predicting prevalence of BRS. We conclude that the framework of combining objective measurements with occupant-reported complaints can be reliable, interpretable predictions of symptom prevalence. This study is limited by single-school setting, health confounders, and symptoms verification. Future research may contribute to exploring wider set of input variables, applicability, and variation of complaints preference.
2025
Indian Land Carbon Sink Estimated from Surface and GOSAT Observations
The carbon sink over land plays a key role in the mitigation of climate change by removing carbon dioxide (CO2) from the atmosphere. Accurately assessing the land sink capacity across regions should contribute to better future climate projections and help guide the mitigation of global emissions towards the Paris Agreement. This study estimates terrestrial CO2 fluxes over India using a high-resolution global inverse model that assimilates surface observations from the global observation network and the Indian subcontinent, airborne sampling from Brazil, and data from the Greenhouse gas Observing SATellite (GOSAT) satellite. The inverse model optimizes terrestrial biosphere fluxes and ocean-atmosphere CO2 exchanges independently, and it obtains CO2 fluxes over large land and ocean regions that are comparable to a multi-model estimate from a previous model intercomparison study. The sensitivity of optimized fluxes to the weights of the GOSAT satellite data and regional surface station data in the inverse calculations is also examined. It was found that the carbon sink over the South Asian region is reduced when the weight of the GOSAT data is reduced along with a stricter data filtering. Over India, our result shows a carbon sink of 0.040 ± 0.133 PgC yr−1 using both GOSAT and global surface data, while the sink increases to 0.147 ± 0.094 PgC yr−1 by adding data from the Indian subcontinent. This demonstrates that surface observations from the Indian subcontinent provide a significant additional constraint on the flux estimates, suggesting an increased sink over the region. Thus, this study highlights the importance of Indian sub-continental measurements in estimating the terrestrial CO2 fluxes over India. Additionally, the findings suggest that obtaining robust estimates solely using the GOSAT satellite data could be challenging since the GOSAT satellite data yield significantly varies over seasons, particularly with increased rain and cloud frequency.
2025
Forurensning i Arktis kan være opptil 71 ganger høyere i løpet av sommeren sammenlignet med vinteren
2025
Havforskningsinstituttet
2025
Enniatins (ENNs) and beauvericin (BEA) are cyclic hexadepsipeptide fungal metabolites which have demonstrated antibiotic, antimycotic, and insecticidal activities. The substantial toxic potentials of these mycotoxins are associated with their ionophoric molecular properties and relatively high lipophilicities. ENNs occur extensively in grain and grain-derived products and are considered a food safety issue by the European Food Safety Authority (EFSA). The tolerable daily intake and maximum levels for ENNs in humans and animals remain unestablished due to key toxicological and toxicokinetic data gaps, preventing full risk assessment. Aiming to find critical data gaps impeding hazard characterization and risk evaluation, this review presents a comprehensive summary of the existing information from in vitro and in vivo studies on toxicokinetic characteristics and cytotoxic, genotoxic, immunotoxic, endocrine, reproductive and developmental effects of the most prevalent ENN analogues (ENN A, A1, B, B1) and BEA. The missing information identified showed that additional studies on ENNs and BEA have to be performed before sufficient data for an in-depth hazard characterisation of these mycotoxins become available.
2025
2025
Air Quality and Healthy Ageing: Predictive Modelling of Pollutants using CNN Quantum-LSTM
The concept of healthy ageing is emerging and becoming a norm to achieve a high quality of life, reducing healthcare costs and promoting longevity. Rapid growth in global population and urbanisation requires substantial efforts to ensure healthy and supportive environments to improve the quality of life, closely aligned with the principles of healthy ageing. Access to fundamental resources which include quality healthcare services, clean air, green and blue spaces plays a pivotal role in achieving this goal. Air quality, in particular, is a critical factor in achieving healthy ageing targets. However, it necessitates a global effort to develop and implement policies aimed at reducing air pollution, which has severe implications for human health including cognitive impairment and neurodegenerative diseases, while promoting healthier environments such as high quality green and blue spaces for all age groups. Such actions inevitably depend on the current status of air pollution and better predictive models to mitigate the harmful impact of emissions on planetary health and public health. In this work, we proposed a hybrid model referred as AirVCQnet, which combines the variational mode decomposition (VMD) method with a convolutional neural network (CNN) and a quantum long short-term memory (QLSTM) network for the prediction of air pollutants. The performance of the proposed model is analysed on five key pollutants including fine Particulate Matter PM2.5, Nitrogen Dioxide (NO2), Ozone (O3), PM10, and Sulphur Dioxide (SO2), sourced from air quality monitoring station in Northern Ireland, UK. The effectiveness of the proposed model is evaluated by comparing its performance with its equivalent classical counterpart using root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2). The results demonstrate the superiority of the proposed model, achieving a performance gain of up to 14% and validating its robustness, efficiency and reliability by leveraging t.
2025
Are ingredients of personal care products likely to undergo long-range transport to remote regions?
Personal care products (PCPs) contain contaminants of emerging concern. Despite increasing reports of their presence in polar regions, the behavior of PCP ingredients under cold environmental conditions remains poorly understood. Snow collected around Villum Research Station at Station Nord, Greenland, between December 2018 and June 2019 was extracted in a stainless steel clean-room and analyzed for seven fragrance materials, four organic UV-filters and an antioxidant using gas chromatography-tandem mass spectrometry. All twelve target PCPs were detected, with elevated concentrations during two sampling events potentially tied to air mass transport from northern Europe and the northern coasts of Russia. To contextualize the presence of these PCP chemicals in high Arctic snow, we estimated their (i) partitioning properties as a function of temperature, (ii) equilibrium phase distribution and dominant deposition processes in the atmosphere at temperatures above and below freezing, and (iii) potential for long-range environmental transport (LRET). Even though most PCPs are deemed to be gas phase chemicals predominantly deposited as vapors, rapid atmospheric degradation is expected to limit their LRET. On the other hand, the less volatile octocrylene is expected to be sorbed to atmospheric particles, removed via wet and dry particle deposition, and possibly exhibit a higher potential for LRET by being protected from attack by photooxidants. The contrast between consistent detection of PCP chemicals in high Arctic snow and relatively low estimated LRET potential emphasizes the need for further research on their real-world atmospheric behavior under cold conditions.
2025
2025
Biomethanol as a Marine Fuel Within Land Use Sustainability Boundaries
Global shipping is an essential, energy-efficient enabler of trade, yet it remains a hard-to-abate sector. With shipping demand projected to continue to rise in the coming decades, identifying scalable and sustainable fuel alternatives is critical. Biofuels, and particularly biomethanol, offer a promising option due to their compatibility with existing infrastructure. However, their sustainability critically hinges on land use impacts. From this Perspective, we argue that biomethanol derived from a dedicated crop could contribute to maritime decarbonisation, with ~71–77% well-to-wake greenhouse gases (GHG) reductions under cropland-only constraints. We further point to the fact that a wider adoption faces challenges such as higher costs, limited availability, and lower energy density relative to fossil fuels. Continued research and monitoring are essential to ensure that biofuel production does not inadvertently contribute to deforestation or biodiversity loss. We underscore the need for spatially sensitive biofuel deployment strategies that align maritime decarbonisation with land-system sustainability and climate objectives.
2025
PikMe: a flexible prioritization tool for chemicals of emerging concern
Identifying new contaminants of emerging concern remains a complex task due to the sheer number of chemical substances potentially released into the environment, the scattered sources of information, and often the lack of adequate data. Environmental screening and monitoring programs are designed to map the presence, sources, and potential environmental impacts of contaminants, yet prioritizing which chemicals to include in such efforts remains resource-intensive and technically challenging. PikMe is a modular, open-access prioritization tool that integrates information from major data bases and evaluates the concern and reliability of the data for more than one million substances. PikMe is built in a modular way so that prioritization can be done based on specific chemical properties relevant to a given scenario (i.e., drinking water contaminants or bioaccumulation in biota) rather than assigning only a global risk score. PikMe scores substances based on persistence, bioaccumulation, mobility, environmental toxicity, and human toxicity, assigning individual score per property. Additionally, PikMe is designed for flexibility by allowing the integration of external lists of chemicals and supporting optional add-ons. Different scenarios of use are described in this article, including the selection of chemicals for environmental monitoring and screening in Norway and the assessment of the implications of the new classifications according to the regulation for classification, labelling and packaging of substances and mixtures on persistent chemicals.
2025
2025
Over halvparten av klimaforskerne har blitt hetset og trakassert
Klimaforskere er blant forskerne som blir mest utsatt for hets og trakassering, viser svensk rapport. Den norske klimaforskeren Helene Muri er ikke overrasket.
2025
Worldwide, edible fish are well studied for plastic occurrence. Microplastic (MP) occurrence in edible tissues raises concern for the organism’s health, but also on food safety. In the Arctic region, MP occurrence in other tissues than the digestive tract of fish has not been published yet. Plastic-related chemicals such as UV stabilisers (UVS) were also scarcely studied in Arctic biota. Our objectives were to (1) provide data on MP occurrence in Atlantic cod (Gadus morhua) fillets, (2) quantify UVS in the same fillets, and (3) provide estimations of both MP and UVS intake by Norwegian and European consumers through cod consumption. Twenty individuals were collected in the Barents Sea, south-west of Svalbard. They were dissected onboard and a piece of fillet was used for the extraction of MPs in the lab. Particles’ identification was performed by µRaman spectroscopy. MPs were found in 45 % of the fillets, with an average of 0.25 MP/g ww. Only one UV stabiliser (UV-326) was detected, in four fillets. Based on consumption data of cod, an average Norwegian man and woman would ingest 20.8 and 33.5 MPs weekly, respectively. Considering a European diet, a weekly intake of 8 MPs and a yearly intake of 403 MPs through cod consumption was calculated. The impacts of MP exposure to humans are unknown. Through this study, rather than to raise potential risks of consuming fish, we aimed to trigger further research on microplastics occurrence in seafood, i.e. in the edible tissues of aquatic animals.
2025
2025
Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components
Norwegian Meteorological Institute
2025
2025
Biomass burning emission analysis based on MODIS
We assessed the biomass burning (BB) smoke aerosol optical depth (AOD) simulations of 11 global models that participated in the AeroCom phase III BB emission experiment. By comparing multi-model simulations and satellite observations in the vicinity of fires over 13 regions globally, we (1) assess model-simulated BB AOD performance as an indication of smoke source–strength, (2) identify regions where the common emission dataset used by the models might underestimate or overestimate smoke sources, and (3) assess model diversity and identify underlying causes as much as possible. Using satellite-derived AOD snapshots to constrain source strength works best where BB smoke from active sources dominates background non-BB aerosol, such as in boreal forest regions and over South America and southern hemispheric Africa. The comparison is inconclusive where the total AOD is low, as in many agricultural burning areas, and where the background is high, such as parts of India and China. Many inter-model BB AOD differences can be traced to differences in values for the mass ratio of organic aerosol to organic carbon, the BB aerosol mass extinction efficiency, and the aerosol loss rate from each model. The results point to a need for increased numbers of available BB cases for study in some regions and especially to a need for more extensive regional-to-global-scale measurements of aerosol loss rates and of detailed particle microphysical and optical properties; this would both better constrain models and help distinguish BB from other aerosol types in satellite retrievals. More generally, there is the need for additional efforts at constraining aerosol source strength and other model attributes with multi-platform observations.
2025
Målinger av SO2 i omgivelsene til Elkem Carbon. Kalenderår 2024
På oppdrag fra Elkem Carbon AS har NILU utført målinger av SO2 i omgivelsene til Elkem Carbon i Kristiansand. Målingene ble utført med SO2-monitor i boligområdet på Fiskåtangen (Konsul Wilds vei). I tillegg ble SO2 målt med passive prøvetakere ved 3 steder rundt bedriften. Rapporten dekker målinger i perioden 1. januar – 31. desember 2024. Norske grenseverdier for luftkvalitet (SO2) ble overholdt ved Konsul Wilds vei for alle midlingsperioder (årsmiddel, vintermiddel, døgnmiddel og timemiddel). To døgnmiddelverdier var over nedre vurderingsterskel (50 µg/m3). Passive luftprøver viste at Fiskåveien, rett sør for bedriften, var det mest belastede stedet i måleperioden.
NILU
2025