Found 10166 publications. Showing page 405 of 407:
2025
2025
Statusrapport 2025. Nasjonalt referanselaboratorium for luftkvalitetsmålinger
Denne rapporten oppsummerer oppgavene til Nasjonalt referanselaboratorium for luftkvalitetsmålinger (NRL), delkontrakt 1b, for første halvår 2025.
NILU
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
Global greenhouse gas reconciliation 2022
n this study, we provide an update on the methodology and data used by Deng et al. (2022) to compare the national greenhouse gas inventories (NGHGIs) and atmospheric inversion model ensembles contributed by international research teams coordinated by the Global Carbon Project. The comparison framework uses transparent processing of the net ecosystem exchange fluxes of carbon dioxide (CO2) from inversions to provide estimates of terrestrial carbon stock changes over managed land that can be used to evaluate NGHGIs. For methane (CH4), and nitrous oxide (N2O), we separate anthropogenic emissions from natural sources based directly on the inversion results to make them compatible with NGHGIs. Our global harmonized NGHGI database was updated with inventory data until February 2023 by compiling data from periodical United Nations Framework Convention on Climate Change (UNFCCC) inventories by Annex I countries and sporadic and less detailed emissions reports by non-Annex I countries given by national communications and biennial update reports. For the inversion data, we used an ensemble of 22 global inversions produced for the most recent assessments of the global budgets of CO2, CH4, and N2O coordinated by the Global Carbon Project with ancillary data. The CO2 inversion ensemble in this study goes through 2021, building on our previous report from 1990 to 2019, and includes three new satellite inversions compared to the previous study and an improved managed-land mask. As a result, although significant differences exist between the CO2 inversion estimates, both satellite and in situ inversions over managed lands indicate that Russia and Canada had a larger land carbon sink in recent years than reported in their NGHGIs, while the NGHGIs reported a significant upward trend of carbon sink in Russia but a downward trend in Canada. For CH4 and N2O, the results of the new inversion ensembles are extended to 2020. Rapid increases in anthropogenic CH4 emissions were observed in developing countries, with varying levels of agreement between NGHGIs and inversion results, while developed countries showed a slowly declining or stable trend in emissions. Much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites, coordinated into a global constellation, is expected in the coming years. The methodology proposed here to compare inversion results with NGHGIs can be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objectives of their pledges. The dataset constructed for this study is publicly available at https://doi.org/10.5281/zenodo.13887128 (Deng et al., 2024).
2025
2025
2025
2025
2025
Machine learning for mapping glacier surface facies in Svalbard
Glaciers are dynamic and highly sensitive indicators of climate change, necessitating frequent and precise monitoring. As Earth observation technology evolves with advanced sensors and mapping methods, the need for accurate and efficient approaches to monitor glacier changes becomes increasingly important. Glacier Surface Facies (GSF), formed through snow accumulation and ablation, serve as valuable indicators of glacial health. Mapping GSF provides insights into a glacier's annual adaptations. However, satellite-based GSF mapping presents significant challenges in terms of data preprocessing and algorithm selection for accurate feature extraction. This study presents an experiment using very high-resolution (VHR) WorldView-3 satellite data to map GSF on the Midtre Lovénbreen glacier in Svalbard. We applied three machine learning (ML) algorithms—Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Machine (SVM)—to explore the impact of different image preprocessing techniques, including atmospheric corrections, pan sharpening methods, and spectral band combinations. Our results demonstrate that RF outperformed both ANN and SVM, achieving an overall accuracy of 85.02 %. However, nuanced variations were found for specific processing conditions and can be explored for specific applications. This study represents the first clear delineation of ML algorithm performance for GSF mapping under varying preprocessing conditions. The data and findings from this experiment will inform future ML-based studies aimed at understanding glaciological adaptations in a rapidly changing cryosphere, with potential applications in long-term spatiotemporal monitoring of glacier health.
2025
Geoengineering skulle kunna skapa ett mer orättvist klimat
Världens klimatsystem hänger ihop, så geoengineering för bättre klimat i en region kan påverka andra regioner negativt. Men vem styr och tar beslut om ...
2025
2025
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
This study examines how southern wintering areas may contribute to organochlorine (OCs) loads in arctic seabirds during breeding. Light-sensitive geolocators (GLS loggers) were deployed on Arctic skuas (Stercorarius parasiticus) in one high arctic and two subarctic colonies. Hexcahlorobenzene (HCB), chlordanes, mirex, p,p′-dichlorodiphenyldichloro-ethylene (p,p′-DDE), and polychlorinated biphenyls (PCBs) were measured in the blood of breeding adults at the nest (58 individuals, a total of 128 samples) in northern Norway and Svalbard between 2009 and 2015. We compared OC concentrations and OC profiles among nesting skuas wintering in five Atlantic regions, determined by the GLS loggers: the coast of Argentina, the Caribbean, off West Africa, off the coast of southern Africa, and the Mediterranean Sea. As predicted, HCB, which is semi-volatile and has high long-range transport potential, showed high prevalence in birds wintering in all regions except the Mediterranean. Mirex showed the highest prevalence in birds wintering off the coasts of Argentina and southern Africa, in accordance with high background levels previously documented in the Southern Ocean. Chlordanes were particularly prevalent in skuas wintering off southern Africa, whereas p,p′-DDE seemed relatively evenly distributed among wintering areas. As predicted, the prevalence of PCBs was much higher in birds wintering in the Mediterranean Sea than in birds from other regions. This study thus suggests that the Mediterranean Sea and the mid- and southern Atlantic are essential sources of different OCs in the blood of Arctic skuas breeding in the European Arctic.
2025
This study critically examines the workflow for untargeted analysis of volatile organic compounds (VOCs) in ambient air, from sampling strategies to data interpretation by using GC-HRMS. While untargeted approaches are well-established in liquid chromatography (LC) due to advanced-deconvolution tools and extensive metabolomic libraries, their application in gas chromatography (GC) remains less developed, particularly for VOCs. The high structural isomerism of VOCs and the relative novelty of GC-based untargeted methodologies present unique challenges, including limited software tools and reference libraries. Air samples from suburban and rural sites in central Italy were analyzed to explore chemical diversity and address methodological gaps. This study evaluates critical decisions, such as sampling strategies, extraction techniques, and data-processing workflows, highlighting the limitations of automated deconvolution tools and the need for manual validation. Results revealed distinct source contributions, with suburban areas showing higher levels of anthropogenic compounds and rural areas dominated by biogenic emissions. This work underscores the potential of GC-HRMS untargeted analysis to advance environmental chemistry, while addressing key pitfalls and providing practical recommendations for reliable application. By bridging methodological gaps, it offers a roadmap for future studies aiming to integrate untargeted and targeted approaches in air quality research.
2025
This document provides technical details and support for the implementation of air quality monitoring under the Directive (EU) 2024/2881 of the European Parliament and of the Council of 23 October 2024 on ambient air quality and cleaner air for Europe (recast) (AAQD, Directive (EU) 2024/2881). It presents an overview of current knowledge and best practices, signposting to existing technical guidance on air quality monitoring and to sources of ongoing technical guidance development. This document does not formulate any legal provisions and as such, it does not have a legally binding value.
Publications Office of the European Union/European Commission. Directorate-General for Environment
2025