Found 9720 publications. Showing page 2 of 389:
Aerosol hygroscopicity influenced by seasonal chemical composition variations in the Arctic region
In this study, we quantified aerosol hygroscopicity parameter using aerosol microphysical observation data (κphy), analyzing monthly and seasonal trends in κphy by correlating it with aerosol chemical composition over 6 years from April 2007 to March 2013 at the Zeppelin Observatory in Svalbard, Arctic region. The monthly mean κphy value exhibited distinct seasonal variations, remaining high from winter to spring, reaching its minimum in summer, followed by an increase in fall, and maintaining elevated levels in winter. To verify the reliability of κphy, we employed the hygroscopicity parameter calculated from chemical composition data (κchem). The chemical composition and PM2.5 mass concentration required to calculate κchem was obtained through Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis data and the calculation of κchem assumed that Arctic aerosols comprise only five species: black carbon (BC), organic matter (OM), ammonium sulfate (AS), sea salt aerosol less than a diameter of 2.5 μm (SSA2.5), and dust aerosol less than a diameter of 2.5 μm (Dust2.5). The κchem had no distinct correlation but had a similar seasonal trend compared to κphy. The κchem value followed a trend of SSA2.5 and was much higher by a factor of 1.6 ± 0.3 than κphy on average, due to a large proportion of SSA2.5 mass concentration in MERRA-2 reanalysis data. This may be due to the overestimation of sea salt aerosols in MERRA-2 reanalysis. The relationship between monthly mean κphy and the chemical composition used to calculate κchem was also analyzed. The elevated κphy from October to February resulted from the dominant influence of SSA2.5, while the maximum κphy in March was concurrently influenced by increasing AS and Dust2.5 associated with long-range transport from mid-latitude regions during Arctic haze periods and by SSA mass concentration obtained from in-situ sampling, which remained high from the preceding winter. The relatively low κphy from April to September can be attributed to low SSA2.5 and the dominance of organic compounds in the Arctic summer. Either natural sources such as those of marine and terrestrial biogenic origin or long-range-transported aerosols may contribute to the increase in organic aerosols in summer, potentially influencing the reduction in κphy of atmospheric aerosols. To our knowledge, this is the first study to analyze the monthly and seasonal variation of aerosol hygroscopicity calculated using long-term microphysical data, and this result provides evidence that changes in monthly and seasonal hygroscopicity variation occur depending on chemical composition.
Elsevier
2025
2025
2025
Årsrapport 2024. Nasjonalt referanselaboratorium for luftkvalitetsmålinger
Denne rapporten oppsummerer oppgavene til Nasjonalt referanselaboratorium for luftkvalitetsmålinger (NRL), delkontrakt 1b, for året 2024.
NILU
2025
2025
Fungus-farming termites cultivate a Termitomyces fungus monoculture in enclosed gardens (combs) free of other fungi, except during colony declines, where Pseudoxylaria spp. stowaway fungi appear and take over combs. Here, we determined Volatile Organic Compounds (VOCs) of healthy Macrotermes bellicosus nests in nature and VOC changes associated with comb decay during Pseudoxylaria takeover. We identified 443 VOCs and unique volatilomes across samples and nest volatilomes that were mainly composed of fungus comb VOCs with termite contributions. Few comb VOCs were linked to chemical changes during decay, but longipinocarvone and longiverbenone were only emitted during comb decay. These terpenes may be involved in Termitomyces defence against antagonistic fungi or in fungus-termite signalling of comb state. Both comb and Pseudoxylaria biomass volatilomes contained many VOCs with antimicrobial activity that may serve in maintaining healthy Termitomyces monocultures or aid in the antagonistic takeover by Pseudoxylaria during colony decline. We further observed a series of oxylipins with known functions in the regulation of fungus germination, growth, and secondary metabolite production. Our volatilome map of the fungus-farming termite symbiosis provides new insights into the chemistry regulating complex interactions and serves as a valuable guide for future work on the roles of VOCs in symbioses.
John Wiley & Sons
2025
Recommendation technologies are widespread in streaming services, e-commerce, social media, news, and content management. Besides recommendation generation, its presentation is also important. Most research and development focus on the technical aspects of recommendation generation; therefore, a gap exists between recommendation generation and its effective presentation and user interaction. This study focuses on how personalized recommendations can be presented and interacted with in a music recommendation system using interactive visual interfaces. Interactive interface modeling with User-Centered Design (UCD) in a recommendation system is essential for creating a user-friendly, engaging, and personalized experience. By involving users in the recommendation process and considering their feedback, the system can deliver more relevant content, foster user trust, and improve overall user satisfaction and engagement. In this study, the visual interface design and development of a personalized music recommendation prototype (MusicReco) are presented using an iterative UCD approach, involving twenty end-users, one researcher, three academic professionals, and four experts. As the study is more inclined toward the recommendation presentation and visual modeling, we used a standard content-based filtering algorithm on the publicly available Spotify dataset for music recommendation generation. End-users helped to mature the MusicReco prototype to a basic working version through continuous feedback and design inputs on their needs, context, preferences, personalization, and effective visualization. Moreover, MusicReco captures the idea of mood-based tailored recommendations to encourage end-users. Overall, this study demonstrates how UCD can enhance the presentation and interaction of mood-based music recommendations, effectively engaging users with advancements in recommendation algorithms as a future focus.
IEEE (Institute of Electrical and Electronics Engineers)
2025
Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer
Heart Rate Variability (HRV) serves as a vital marker of stress levels, with lower HRV indicating higher stress. It measures the variation in the time between heartbeats and offers insights into health. Artificial intelligence (AI) research aims to use HRV data for accurate stress level classification, aiding early detection and well-being approaches. This study’s objective is to create a semantic model of HRV features in a knowledge graph and develop an accurate, reliable, explainable, and ethical AI model for predictive HRV analysis. The SWELL-KW dataset, containing labeled HRV data for stress conditions, is examined. Various techniques like feature selection and dimensionality reduction are explored to improve classification accuracy while minimizing bias. Different machine learning (ML) algorithms, including traditional and ensemble methods, are employed for analyzing both imbalanced and balanced HRV datasets. To address imbalances, various data formats and oversampling techniques such as SMOTE and ADASYN are experimented with. Additionally, a Tree-Explainer, specifically SHAP, is used to interpret and explain the models’ classifications. The combination of genetic algorithm-based feature selection and classification using a Random Forest Classifier yields effective results for both imbalanced and balanced datasets, especially in analyzing non-linear HRV features. These optimized features play a crucial role in developing a stress management system within a Semantic framework. Introducing domain ontology enhances data representation and knowledge acquisition. The consistency and reliability of the Ontology model are assessed using Hermit reasoners, with reasoning time as a performance measure. HRV serves as a significant indicator of stress, offering insights into its correlation with mental well-being. While HRV is non-invasive, its interpretation must integrate other stress assessments for a holistic understanding of an individual’s stress response. Monitoring HRV can help evaluate stress management strategies and interventions, aiding individuals in maintaining well-being.
Nature Portfolio
2025
2025
Nitrous oxide (N2O) is the most important stratospheric ozone-depleting agent based on current emissions and the third largest contributor to increased net radiative forcing. Increases in atmospheric N2O have been attributed primarily to enhanced soil N2O emissions. Critically, contributions from soils in the Northern High Latitudes (NHL, >50°N) remain poorly quantified despite their exposure to rapid rates of regional warming and changing hydrology due to climate change. In this study, we used an ensemble of six process-based terrestrial biosphere models (TBMs) from the Global Nitrogen/Nitrous Oxide Model Intercomparison Project (NMIP) to quantify soil N2O emissions across the NHL during 1861–2016. Factorial simulations were conducted to disentangle the contributions of key driving factors, including climate change, nitrogen inputs, land use change, and rising atmospheric CO2 concentration, to the trends in emissions. The NMIP models suggests NHL soil N2O emissions doubled from 1861 to 2016, increasing on average by 2.0 ± 1.0 Gg N/yr (p
Elsevier
2025
2025
Atmospheric ammonia (NH3) is a key transboundary air pollutant that contributes to the impacts of nitrogen and acidity on terrestrial ecosystems. Ammonia also contributes to the atmospheric aerosol that affects air quality. Emission inventories indicate that NH3 was predominantly emitted by agriculture over the 19th and 20th centuries but, up to now, these estimates have not been compared to long-term observations. To document past atmospheric NH3 pollution in south-eastern Europe, ammonium (NH) was analysed along an ice core extracted from Mount Elbrus in the Caucasus, Russia. The NH ice-core record indicates a 3.5-fold increase in concentrations between 1750 and 1990 CE. Remaining moderate prior to 1950 CE, the increase then accelerated to reach a maximum in 1989 CE. Comparison between ice-core trends and estimated past emissions using state-of-the-art atmospheric transport modelling of submicron-scale aerosols (FLEXPART (FLEXible PARTicle dispersion) model) indicates good agreement with the course of estimated NH3 emissions from south-eastern Europe since ∼ 1750 CE, with the main contributions from south European Russia, Türkiye, Georgia, and Ukraine. Examination of ice deposited prior to 1850 CE, when agricultural activities remained limited, suggests an NH ice concentration related to natural soil emissions representing ∼ 20 % of the 1980–2009 CE NH level, a level mainly related to current agricultural emissions that almost completely outweigh biogenic emissions from natural soil. These findings on historical NH3 emission trends represent a significant contribution to the understanding of ammonia emissions in Europe over the last 250 years.
2025
Methane in Svalbard (SvalGaSess)
Methane is a powerful greenhouse gas whose emission into the atmosphere from Arctic environments is increasing in response to climate change. At present, the increase in atmospheric methane concentrations recorded at Ny-Ålesund and globally threatens the Paris Agreement goal of limiting warming to 2 degrees, preferably 1.5 degrees, by increasing the need for abatements. However, our understanding of the physical, chemical and biological processes that control methane in the Arctic are strongly biased towards just a few lowland sites that are not at all like Svalbard and other similar mountainous, ice-covered regions. Svalbard can therefore be used to better understand these locations. Svalbard’s methane stocks include vast reserves of ancient, geogenic methane trapped beneath glaciers and permafrost. This methane supplements the younger, microbial methane mostly produced in waterlogged soils and wetlands during the summer and early winter. Knowledge about the production, removal and migration of these two methane sources in Svalbard’s complex landscapes and coastal environments has grown rapidly in recent years. However, the need to exploit this knowledge to produce reliable estimates of present-day and future emissions of methane from across the Svalbard landscape is now paramount. This is because understanding these quantities is absolutely necessary when we seek to define how society must adjust in order to better manage greenhouse gases in Earth’s atmosphere
2025
På oppdrag fra Alcoa Norway AS dept. Mosjøen har NILU utført målinger i omgivelses-luft rundt smelteverket i Mosjøen. Målingene ble utført med aktiv prøvetaking (fluor, SO2, metaller, PAH, PM10) og passiv prøvetaking (SO2, støvnedfall). Måleprosjektet ble utført i perioden 22. mai – 19. august 2024. Alle målte komponenter var godt under de individuelle grenseverdier, målsettingsverdier og luftkvalitetskriterier i måleperioden. Siden Mosjøen er mest utsatt for utslipp fra aluminiumsverket i sommermånedene, pga. hovedvindretning fra fjorden, over smelteverket mot byen, blir måleresultatene et øvre anslag for bidraget fra smelteverket til konsentrasjonene i Mosjøen over hele året.
NILU
2025
This study examines the environmental impacts of urban growth in Warsaw since 2006 and models the implications of future urban development for traffic pollutant emissions and pollution levels. Our findings demonstrate that, over the past two decades, urban sprawl has resulted in decreases in accessibility to public transport, social services, and natural areas. We analyse CO2 traffic emissions, NO2 concentrations, and population exposure across urban areas in future scenarios of further sprawling or alternative compacting land-use development. Results indicate that a compact future scenario reduces transport CO2 emissions and urban NO2 levels, though increases in population density raise exposure to air pollution. A sprawl future scenario increases CO2 and NOx emissions due to longer commutes and congestion, and NO2 levels increase up to 25% in parts of the city. Several traffic abatement strategies were simulated, and in all simulations a compact city consistently yields the largest reductions in CO2 emissions and NO2 levels, implying that the best abatement strategy for combating negative consequences of sprawl is to reduce sprawling. In both city layouts, network-wide improvements of public transport travel times gave significantly reduced emissions. Combined, our findings highlight the importance of co-beneficial urban planning strategies to balance CO2 emissions reduction, and air pollution exposure in expanding cities.
Elsevier
2025
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
2025
2025
2025
The complex and dynamic nature of airborne fine particulate matter (PM2.5) has hindered understanding of its chemical composition, sources, and toxic effects. In the first steps of a larger study, here, we aimed to elucidate relationships between source regions, ambient conditions, and the chemical composition in water extracts of PM2.5 samples (n = 85) collected over 16 months at an observatory in the Yellow Sea. In each extract, we quantified elements and major ions and profiled the complex mixtures of organic compounds by nontarget mass spectrometry. More than 50,000 nontarget features were detected, and by consensus of in silico tools, we assigned a molecular formula to 13,907 features. Oxygenated compounds were most prominent, followed by mixed nitrogenated/oxygenated compounds, organic sulfates, and sulfonates. Spectral matching enabled identification or structural annotation of 43 substances, and a workflow involving SIRIUS and MS-DIAL software enabled annotation of 74 unknown per- and polyfluoroalkyl substances with primary source regions in China and the Korean Peninsula. Multivariate modeling revealed seasonal variations in chemistry, attributable to the combination of warmer temperatures and maritime source regions in summer and to cooler temperatures and source regions of China in winter.
2025
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.
MDPI
2025
American Chemical Society (ACS)
2025
This study evaluated galvanostatic three-dimensional electrolysis using ceramic carbon foam anodes for the removal of emerging pollutants from wastewater and assessed transformation product formation. Five pollutants (paracetamol, triclosan, bisphenol A, caffeine, and diclofenac) were selected based on their detection in wastewater treatment plant effluents. Electrochemical oxidation was carried out on artificial wastewater spiked with these compounds under galvanostatic conditions (50, 125, and 250 mA) using a stainless steel tube electrolyzer with three ceramic carbon foam anodes and a stainless steel cathode. Decreasing pollutant concentrations were observed in all of the experiments. Nontarget chemical analysis using liquid chromatography coupled to a high-resolution mass spectrometer detected 338 features with increasing intensity including 12 confirmed transformation products (TPs). Real wastewater effluent spiked with the pollutants was then electrolyzed, again showing pollutant removal, with 9 of the 12 previously identified TPs present and increasing. Two TPs (benzamide and 2,4-dichlorophenol) are known toxicants, indicating the formation of a potential toxic by-product during electrolysis. Furthermore, electrolysis of unspiked real wastewater revealed the removal of five pharmaceuticals and a drug metabolite. While demonstrating electrolysis’ ability to degrade pollutants in wastewater, the study underscores the need to investigate transformation product formation and toxicity implications of the electrolysis process.
American Chemical Society (ACS)
2025