Found 10054 publications. Showing page 393 of 403:
Assessing the siting of air quality sampling points at industrial sites
Air quality measurements at industrial locations are intended to assess emission sources typically of the largest magnitude, many of which operate over a long time and are subject to specific permitting rules. Industrial sources represent a significant contribution to the air pollution that people and ecosystems are exposed to. Therefore, appropriately sited sampling points are essential to understanding the characteristics of these emissions, which is necessary to design meaningful monitoring network, implement effective abatement strategies, and inform supplementary assessment methods such as dispersion modelling. Existing environmental legislation establishes criteria for the reporting of industrial emissions and for the design of monitoring networks on pollutant concentrations: 1) the Industrial Emissions Directive (IED), 2) the Regulation on European Pollutant Release and Transfer Register (E-PRTR), and 3) the Ambient Air Quality Directives (AAQDs, Directives 2008/50/EC and 2004/107/EC, as well as the Revised Directive (EU) 2024/2881). The AAQDs provide rules and guidance for monitoring stations across different environments, including specific rules for those classified as industrial. In this study we have evaluated the air quality monitoring sampling points associated with industrial sources. The overarching aim is to underpin assessments by the European Commission of whether the criteria for placing industrial sampling points are applied throughout the European Union in a harmonised manner and whether the application of the criteria ensures that the highest exposure of the general population to air pollution from industrial sources is measured in all air quality zones. For this reason, we have carried out an evaluation of the 2019 monitoring network across Europe in the vicinity of industrial sources.
Publications Office of the European Union
2025
2025
Personalized approaches are required for stroke management due to the variability in symptoms, triggers, and patient characteristics. An innovative stroke recommendation system that integrates automatic predictive analysis with semantic knowledge to provide personalized recommendations for stroke management is proposed by this paper. Stroke exacerbation are predicted and the recommendations are enhanced by the system, which leverages automatic Tree-based Pipeline Optimization Tool (TPOT) and semantic knowledge represented in an OWL Ontology (StrokeOnto). Digital sovereignty is addressed by ensuring the secure and autonomous control over patient data, supporting data sovereignty and compliance with jurisdictional data privacy laws. Furthermore, classifications are explained with Local Interpretable Model-Agnostic Explanations (LIME) to identify feature importance. Tailored interventions based on individual patient profiles are provided by this conceptual model, aiming to improve stroke management. The proposed model has been verified using public stroke dataset, and the same dataset has been utilized to support ontology development and verification. In TPOT, the best Variance Threshold + DecisionTree Classifier pipeline has outperformed other supervised machine learning models with an accuracy of 95.2%, for the used datasets. The Variance Threshold method reduces feature dimensionality with variance below a specified threshold of 0.1 to enhance predictive accuracy. To implement and evaluate the proposed model in clinical settings, further development and validation with more diverse and robust datasets are required.
2025
Sb-PiPLU: A Novel Parametric Activation Function for Deep Learning
The choice of activation function—particularly non-linear ones—plays a vital role in enhancing the classification performance of deep neural networks. In recent years, a variety of non-linear activation functions have been proposed. However, many of these suffer from drawbacks that limit the effectiveness of deep learning models. Common issues include the dying neuron problem, bias shift, gradient explosion, and vanishing gradients. To address these challenges, we introduce a new activation function: Softsign-based Piecewise Parametric Linear Unit (Sb-PiPLU). This function offers improved non-linear approximation capabilities for neural networks. Its piecewise, parametric design allows for greater adaptability and flexibility, which in turn enhances overall model performance. We evaluated Sb-PiPLU through a series of image classification experiments across various Convolutional Neural Network (CNN) architectures. Additionally, we assessed its memory usage and computational cost, demonstrating that Sb-PiPLU is both stable and efficient in practical applications. Our experimental results show that Sb-PiPLU consistently outperforms conventional activation functions in both classification accuracy and computational efficiency. It achieved higher accuracy on multiple benchmark datasets, including CIFAR-10, CINIC-10, MWD, Brain Tumor, and SVHN, surpassing widely-used functions such as ReLU and Tanh. Due to its flexibility and robustness, Sb-PiPLU is particularly well-suited for complex image classification tasks.
2025
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
This report documents the EMEP VOC monitoring carried out in 2023. The levels of the measured species in 2023 are presented as well as the 2023-status and history of the VOC programme. The geographical pattern of the species in Europe is discussed as well as the long-term trend during the last 20 years.
NILU
2025
2025
Carbonaceous aerosols (CA), composed of black carbon (BC) and organic matter (OM), significantly impact the climate. Light absorption properties of CA, particularly of BC and brown carbon (BrC), are crucial due to their contribution to global and regional warming. We present the absorption properties of BC (bAbs,BC) and BrC (bAbs,BrC) inferred using Aethalometer data from 44 European sites covering different environments (traffic (TR), urban (UB), suburban (SUB), regional background (RB) and mountain (M)). Absorption coefficients showed a clear relationship with station setting decreasing as follows: TR > UB > SUB > RB > M, with exceptions. The contribution of bAbs,BrC to total absorption (bAbs), i.e. %AbsBrC, was lower at traffic sites (11–20 %), exceeding 30 % at some SUB and RB sites. Low AAE values were observed at TR sites, due to the dominance of internal combustion emissions, and at some remote RB/M sites, likely due to the lack of proximity to BrC sources, insufficient secondary processes generating BrC or the effect of photobleaching during transport. Higher bAbs and AAE were observed in Central/Eastern Europe compared to Western/Northern Europe, due to higher coal and biomass burning emissions in the east. Seasonal analysis showed increased bAbs, bAbs,BC, bAbs,BrC in winter, with stronger %AbsBrC, leading to higher AAE. Diel cycles of bAbs,BC peaked during morning and evening rush hours, whereas bAbs,BrC, %AbsBrC, AAE, and AAEBrC peaked at night when emissions from household activities accumulated. Decade-long trends analyses demonstrated a decrease in bAbs, due to reduction of BC emissions, while bAbs,BrC and AAE increased, suggesting a shift in CA composition, with a relative increase in BrC over BC. This study provides a unique dataset to assess the BrC effects on climate and confirms that BrC can contribute significantly to UV–VIS radiation presenting highly variable absorption properties in Europe.
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.
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
2025
Monitoring of long-range transported air pollutants in Norway. Annual Report 2024
This report presents results from the monitoring of atmospheric composition and deposition of air pollution in 2024, and focuses on main components in air and precipitation, particulate and gaseous phase of inorganic constituents, particulate carbonaceous matter, ground level ozone and particulate matter.
NILU
2025
2025
2025
2025