Found 10021 publications. Showing page 396 of 401:
Cyclic volatile methyl siloxanes in the terrestrial and aquatic environment at remote Arctic sites
Cyclic volatile methyl siloxanes (cVMS) are widely used chemicals with high emissions to the atmosphere due to their volatility. They are found in the Arctic atmosphere, indicating potential for long-range transport. This study examined the potential for deposition of cVMS (D4, D5, D6) to surface media via snow in Arctic regions. Results showed low cVMS levels in vegetation, soil, sediment, and marine biota. D4 was detected above detection limits but generally below quantification limits, while D5 and D6 were generally not detected. This aligns with current research, suggesting negligible cVMS input from atmospheric deposition via snow and snow melt.
NILU
2025
2025
2025
Stochastic and deterministic processes in Asymmetric Tsetlin Machine
This paper introduces a new approach to enhance the decision-making capabilities of the Tsetlin Machine (TM) through the Stochastic Point Location (SPL) algorithm and the Asymmetric Steps technique. We incorporate stochasticity and asymmetry into the TM's process, along with a decaying normal distribution function that improves adaptability as it converges toward zero over time. We present two methods: the Asymmetric Probabilistic Tsetlin (APT) Machine, influenced by random events, and the Asymmetric Tsetlin (AT) Machine, which transitions from probabilistic to deterministic states. We evaluate these methods against traditional machine learning algorithms and classical Tsetlin (CT) machines across various benchmark datasets. Both AT and APT demonstrate competitive performance, with the AT model notably excelling, especially in complex datasets.
2025
Ensuring a healthy and comfortable indoor environment in schools is essential for student well-being and academic performance. The purpose of this study is to investigate the factors influencing students’ satisfaction with indoor air quality (IAQ) and thermal comfort in classrooms. To address this, one year-long measurements were conducted across multiple classrooms in a Norwegian secondary school, collecting data on indoor climate (CO₂, VOC levels, temperature, relative humidity, and air pressure) along with outdoor climate variables (temperature, humidity, and solar radiation). Additional room-specific data, including orientation, floor level, and ventilation system specifications, were also considered. An online feedback system was used to gather 1,473 real-time student responses on satisfaction levels. Supervised machine learning (ML) models were developed to assess the importance of these parameters in predicting perceived indoor comfort: IAQ perceptions and thermal environmental perceptions. Results showed ML models effectively predicted student dissatisfaction, achieving accuracy greater than 80% when environmental and building parameters were considered simultaneously. The findings emphasized that dissatisfaction with indoor conditions is driven by multiple interacting factors of measured variables and building parameters single independent variables. SHAP analysis provided valuable interpretability, revealing how variations in environmental conditions collectively impact students' perceived comfort. This comprehensive approach demonstrates the practical potential of ML-based IEQ monitoring systems, suggesting that schools can proactively improve indoor conditions through targeted interventions informed by real-time predictions.
2025
Ikke-spesifikk screening av støv fra norske husholdninger
Denne rapporten presenterer resultater fra en ikke-spesifikk screening av husstøv fra norske hjem. Totalt ble 203 kjemiske forbindelser identifisert, med ftalater som den mest dominerende stoffgruppen. Flere av de påviste stoffene er kjent som hormonforstyrrende, nevrotoksiske eller klassifisert som persistente, mobile og toksiske (PMT). Resultatene viser et endret stoffmønster sammenlignet med tidligere studier og understreker behovet for videre overvåkning av innemiljø, forskning på cocktail-effekter og bedre regulering av forbrukerprodukter.
NILU
2025
2025
Arctic food and energy security at the crossroads
Arctic food systems blend Traditional Ecological Knowledge with modern, often energy-intensive influences, triggered by colonization. Food systems’ future depends on alignment of tradition with innovation, facilitation of resilience and a heritage-driven interaction with the global economy – at a pace determined by local communities.
2025
This report examines the impact of air pollution from residential wood combustion on health in the Nordic countries.Residential wood combustion is a major contributor to premature deaths and health issues. The number of premature deaths is expected to decrease from 1,600 in 2019 to 1,200 by 2030, with health costs dropping from EUR 3.2 bn. to EUR 2.5 bn. This improvement is due to fewer and newer, less polluting appliances, and better energy efficiency in homes.
Two additional scenarios for 2030 reflecting national differences were evaluated.
Technology Scenario: Faster replacement of old appliances, reducing premature deaths by 190 and health costs by EUR 390 mil.
Zone-Based Scenario: Bans in densely populated areas, reducing premature deaths by 240 and health costs by EUR 510 mil.
Mitigation in densely populated areas offers greater health benefits than national-level efforts.
Nordic Council of Ministers
2025
2025
Satellite instruments for measuring atmospheric column mixing ratios have improved significantly over the past couple of decades, with increases in pixel resolution and accuracy. As a result, satellite observations are being increasingly used in atmospheric inversions to improve estimates of emissions of greenhouse gases (GHGs), particularly CO2 and CH4, and to constrain regional and national emission budgets. However, in order to make use of the increasing resolution in inversions, the atmospheric transport models used need to be able to represent the observations at these finer resolutions. Here, we present a new and computationally efficient methodology to model satellite column average mixing ratios with a Lagrangian particle dispersion model (LPDM) and calculate the Jacobian matrices describing the relationship between surface fluxes of GHGs and atmospheric column average mixing ratios, as needed in inversions. The development will enable a more accurate representation of satellite observations (especially high-resolution ones) via the use of LPDMs and, thus, help improve the accuracy of emission estimates obtained by atmospheric inversions. We present a case study using this methodology in the FLEXPART (FLEXible PARTicle dispersion model) LPDM and the FLEXINVERT inversion framework to estimate CH4 fluxes over Siberia using column average mixing ratios of CH4 (XCH4) from the TROPOMI (TROPOspheric Monitoring Instrument) instrument aboard the Sentinel-5P satellite. The results of the inversion using TROPOMI XCH4 are evaluated against results using ground-based observations.
2025
Unchanged PM2.5 levels over Europe during COVID-19 were buffered by ammonia
The coronavirus outbreak in 2020 had a devastating impact on human life, albeit a positive effect on the environment, reducing emissions of primary aerosols and trace gases and improving air quality. In this paper, we present inverse modelling estimates of ammonia emissions during the European lockdowns of 2020 based on satellite observations. Ammonia has a strong seasonal cycle and mainly originates from agriculture. We further show how changes in ammonia levels over Europe, in conjunction with decreases in traffic-related atmospheric constituents, modulated PM2.5. The key result of this study is a −9.8 % decrease in ammonia emissions in the period of 15 March–30 April 2020 (lockdown period) compared to the same period in 2016–2019, attributed to restrictions related to the global pandemic. We further calculate the delay in the evolution of the ammonia emissions in 2020 before, during, and after lockdowns, using a sophisticated comparison of the evolution of ammonia emissions during the same time periods for the reference years (2016–2019). Our analysis demonstrates a clear delay in the evolution of ammonia emissions of −77 kt, which was mainly observed in the countries that imposed the strictest travel, social, and working measures. Despite the general drop in emissions during the first half of 2020 and the delay in the evolution of the emissions during the lockdown period, satellite and ground-based observations showed that the European levels of ammonia increased. On one hand, this was due to the reductions in SO2 and NOx (precursors of the atmospheric acids with which ammonia reacts) that caused less binding and thus less chemical removal of ammonia (smaller loss – higher lifetime). On the other hand, the majority of the emissions persisted because ammonia mainly originates from agriculture, a primary production sector that was influenced very little by the lockdown restrictions. Despite the projected drop in various atmospheric aerosols and trace gases, PM2.5 levels stayed unchanged or even increased in Europe due to a number of reasons that were attributed to the complicated system. Higher water vapour during the European lockdowns favoured more sulfate production from SO2 and OH (gas phase) or O3 (aqueous phase). Ammonia first reacted with sulfuric acid, also producing sulfate. Then, the continuously accumulating free ammonia reacted with nitric acid, shifting the equilibrium reaction towards particulate nitrate. In high-free-ammonia atmospheric conditions such as those in Europe during the 2020 lockdowns, a small reduction in NOx levels drives faster oxidation toward nitrate and slower deposition of total inorganic nitrate, causing high secondary PM2.5 levels.
2025
2025
2025
Heavy metals and POP measurements 2023
This report presents an overview of the annual statistics and results from the monitoring programme of heavy metals and persistent organic pollutants (POPs) in EMEP in 2023.
NILU
2025