Found 10000 publications. Showing page 395 of 400:
Protein-nanomaterial interaction is a topic of great interest for nanotechnology research, particularly for advancing strategies in nanomedicine and nanosafety. This study explores the thermodynamic signatures associated with the interactions of six TiO2 nanoforms, (differing in their crystalline structure, surface properties and particle size) with bovine serum albumin as model protein. By integrating findings from electron paramagnetic resonance spectroscopy (EPR) regarding the free radical generation following interaction, together with information on the stability and conformational changes of the protein during adsorption on TiO2 nanomaterials, we aim to elucidate the binding mechanisms and identify the primary factors influencing nanomaterial's reactivity. The effect of the particle size, crystalline structure and surface properties on the binding parameters, protein structural stability and EPR data is discussed. Finally, the relevant parameters suitable for understanding molecular interactions at the bio/nano interface have been corroborated with the toxicological outcomes resulting from the measurements on the viability, proliferation and real time attachment of relevant cell lines, as well as with the detection of DNA strand breaks and oxidized DNA at the single-cell level. Thermodynamic and EPR parameters emerge as key descriptors for determining adsorption/binding processes and toxic effects of nanomaterials. The rankings with respect to cell damage and to oxidative stress inducing potential follow the same ranking seen in nanomaterial's influence on the BSA structural stability, binding affinity and enthalpic character of the interaction. Our findings highlight the intricate relationships between the parameters governing bio-nano interactions and the toxicity of the nanomaterials, and their significance in assessing nanomaterial safety and efficacy.
2025
2025
An important prerequisite for accurately characterizing economic exposure from climate change at the national scale is a spatial inventory of economic activity and value creation. Current options for such inventories are limited, being either spatially precise but economically bounded sector-specific or owner-specific datasets, or gridded gross domestic product (GDP) products with coarse spatial resolution and inadequate sectoral resolution. To address these limitations, we develop a map of national GDP with high spatial and sectoral resolution. We stress this with meter-scale flood hazard maps to characterize GDP at risk from flooding. We further couple this to a macroeconomic input–output analysis to use the new sectoral resolution to estimate the scope of indirect economic exposure to flood at a national scale.
2025
Mapping human-nature archetypes to guide global biodiversity, food security and land use policy
Reconciling biodiversity conservation, food security, and sustainable agriculture at global scale requires a clear understanding of regional social-ecological opportunities and challenges. This understanding helps untap regional contributions to better achieve global policy targets, such as those framed in the Kunming-Montreal Global Biodiversity Framework (GBF). Yet previous global syntheses of social-ecological interlinkages remain limited in thematic and spatial detail, restricting the discussion of regional contributions and targeted policy implementation. Here, we present 25 human-nature archetypes derived from clustering of global social-ecological data revealing regional opportunities and challenges for meeting global policy targets. Our results differentiate regions with large conservation opportunities from those well suited for ecological restoration or ecological intensification. They highlight the widespread need for improving governance to enhance food security and re-design agricultural systems. Overall, our analysis supports international and national decision makers in tailoring GBF targets to regional specificities in order to more effectively achieve global sustainability goals.
2025
Stress is a common human reaction to demanding circumstances, and prolonged and excessive stress can have detrimental effects on both mental and physical health. Heart rate variability (HRV) is widely used as a measure of stress due to its ability to capture variations in the time intervals between heartbeats. However, achieving high accuracy in stress detection through machine learning (ML), using a reduced set of statistical features extracted from HRV, remains a significant challenge. In this study, we aim to address these challenges by proposing lightweight ML models that can effectively detect stress using minimal HRV features and are computationally efficient enough for IoT deployment. We have developed ML models incorporating efficient feature selection techniques and hyper-parameter tuning. The publicly available SWELL-KW dataset has been utilized for evaluating the performance of our models. Our results demonstrate that lightweight models such as k-NN and Decision Tree can achieve competitive accuracy while ensuring lower computational demands, making them ideal for real-time applications. Promisingly, among the developed models, the k-nearest neighbors (k-NN) algorithm has emerged as the best-performing model, achieving an accuracy score of 99.3% using only three selected features. To confirm real-world deployability, we benchmarked the best model on an 8 GB NVIDIA Jetson Orin Nano edge device, where it retained 99.26% accuracy and completed training in 31 s. Furthermore, our study has incorporated local interpretable model-agnostic explanations to provide comprehensive insights into the predictions made by the k-NN-based architecture.
2025
2025
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
We propose operational definitions and a classification framework for air quality sensor-derived data, thereby aiding users in interpreting and selecting suitable data products for their applications. We focus on differentiating independent sensor measurements (ISM) from other data products, emphasizing transparency and traceability. Recommendations are provided for manufacturers, academia, and standardization bodies to adopt these definitions, fostering data product differentiation and incentivizing the development of more robust, reliable sensor hardware.
2025
CAMS Assessment Report on European Air Quality 2024
The full report provides reference information on air quality in Europe in 2024. The purpose of the report is to present a consistent and accurate estimate of European air quality focusing on key indicators and on the origin of selected pollution episodes. It is intended to support air quality experts in their reporting under air quality legislation by providing an overview over the status of European transboundary air pollution. It contains updated information on key indicators for background air quality for the main regulatory pollutants: ozone (O3), nitrogen dioxide (NO2), particulate matter of 10 micrometres or less in diameter (PM10) and particulate matter of 2.5 micrometres or less in diameter (PM2.5).
Copernicus Atmosphere Monitoring Service (CAMS)
2025
Tiltaksutredning for lokal luftkvalitet i Bærum 2025-2030
Stiftelsen NILU har, i samarbeid med Transportanalyse AS, utarbeidet trafikk- og luftkvalitetsberegninger for Oslo og Bærum kommuner. Arbeidet omfatter en kartlegging av luftkvaliteten ved trafikkberegninger og utslipps- og spredningsberegninger for relevante forurensningskomponenter (PM10, PM2,5 og NO2) for Dagens situasjon 2022, Referansesituasjonen 2030 og for 2030 med tiltak. Det er beregnet risiko for overskridelse av dagens grenseverdier i forurensningsforskriften og for grenseverdier i revidert EU-direktiv som vil innføres fullt fra 2030.
NILU
2025
Citizen-operated low-cost sensors for estimating outdoor particulate matter infiltration
Fine particulates observed indoors exhibit high variability, influenced by both indoor emission sources and the infiltration of outdoor particles through open spaces and the incomplete building insulation. This study examines the relationship between indoor and outdoor PM2.5 levels in Legionowo, Poland, using data from low-cost air quality sensors operated by citizens. The indoor PM2.5 was lower than outdoor levels (median PM2.5: 1.9–17.3 μg m–3 indoors and 6.7–27.9 μg m–3 outdoors), with occasional peaks attributed to potential indoor emission sources. Statistical analysis identified emission events—particularly during cooking and household-heating periods—occurring more frequently from October to April. During this period, nearly 17% of indoor PM2.5 measurements were attributed to indoor emission sources after 18:00 LT, representing a 7% increase compared to the May–September period. In the absence of indoor sources, outdoor particles accounted for 29% to 75% of indoor concentrations, highlighting the significance of infiltration. This research emphasizes how citizen-generated data using low-cost sensors, after post-processing, can provide decision-ready information as for example outdoor particles’ infiltration factors for each building. The knowledge of the infiltration factor enables the determination of the contribution of indoor and outdoor sources to each resident’s exposure to airborne PM. This information can help decision-makers in devising interventions such as prioritizing indoor ventilation, reducing indoor activities resulting in increased exposure, and addressing outdoor pollution sources.
2025
Unprecedented shifts in aerosol pollution sources in China under a decade of clean air actions
China is a major hotspot of black carbon (BC) emissions, contributing to climate warming and risk to public health. Here, our dual-isotope-constrained observations indicate stringent air pollution controls have drastically reduced coal-burning in North China over the past decade, marking a transition to a “post-coal” era compared to earlier 2012–2014. However, biomass-burning fraction (fbb) for north/central/east winter hazes has doubled from earlier (north/east) ~20%, with significantly higher fbb during polluted winters. Comparisons between observation and transport modelling show good alignment in BC concentrations but substantial discrepancies in source attribution (i.e., fbb). Leveraging radiocarbon measurements, advanced atmospheric modelling, and a Bayesian approach, our study identifies biases stemming from misallocated residential fuel types in emission inventories. These findings underscore the untapped potential to mitigate BC emissions by targeting rural biomass burning, while providing critical insights into BC source evolution to refine emission inventories and formulate effective air quality policies for China and other nations facing severe air pollution.
2025
The influence of aerosols on the Arctic system remains associated with significant uncertainties, particularly concerning black carbon (BC). The polar aerosol station “Island Bely” (IBS), located in the Western Siberian Arctic, was established to enhance aerosol monitoring. Continuous measurements from 2019 to 2022 revealed the long-term effects of light-absorbing carbon. During the cold period, the annual average light-absorption coefficient was 0.7 ± 0.7 Mm−1, decreasing by 2–3 times during the warm period. The interannual mean showed a peak in February (0.9 ± 0.8 Mm−1) then 10 times the lower minimum in June and exhibited high variability in August (0.7 ± 2.2 Mm−1). An increase of up to 1.5 at shorter wavelengths from April to September suggests contribution from brown carbon (BrC). The annual mean equivalent black carbon (eBC) demonstrated considerable interannual variability, with the lowest in 2020 (24 ± 29 ng m−3). Significant difference was observed between Arctic haze and Siberian wildfire periods, with record-high pollution levels in February 2022 (110 ± 70 ng m−3) and August 2021 (83 ± 249 ng m−3). Anthropogenic BC contributed 83 % to the total for the entire study period, and gas flaring, domestic combustion, transportation, and industrial emissions dominated. During the cold season, > 90 % of surface BC was attributed to anthropogenic sources, mainly gas flaring. In contrast, during the warm period, Siberian wildfires contributed to BC concentrations by 48 %. In August 2021, intense smoke from Yakutian wildfires was transported at high altitudes during the region's worst fire season in 40 years.
2025