Fant 10344 publikasjoner. Viser side 10 av 414:
2025
2025
2025
2025
2025
This paper reviews results published by the International Co-operative Programme on Effects on Materials including Historic and Cultural Monuments (ICP Materials) with emphasis on those obtained after the turn of the century. Data from ICP Materials come from two main sources. The first is through exposures of materials and collection of environmental data in a network of atmospheric exposure test sites mainly distributed across Europe. Corrosion of carbon steel has continued to decrease during the period 2000–2020 but corrosion of zinc only up until 2014, and the trend in zinc corrosion is only visible when examining four-year data. Surface recession of limestone as well as soiling of modern glass show no decreasing trend during 2000–2020. The second is through case studies performed at heritage sites across Europe. Risk analysis of corrosion and soiling for twenty-six sites indicate that currently soiling is a more significant maintenance trigger than corrosion. Costs for maintaining heritage sites are substantial and costs attributable to air pollution is estimated from 40% to as much as 80% of the total cost. Future directions of the program are work on effects of particulate matter, improving the scientific basis for the work, and making the monitoring data publicly available.
2025
Construction of an enterprise-level global supply chain database
Data tracing global supply chains, commonly captured in input–output models, is a foundational resource across economic, regulatory, investment, defense, and environmental applications. Such models provide insight into interdependency and environmental burden-shifting, forming part of the empirical basis for policies such as Scope 3 embodied emissions targets, supply chain transparency, life cycle assessments, and product declarations. Current approaches, based on national statistics, remain constrained by sector-level resolution, limiting their precision and utility in certain applications. Here, we document the construction of an enterprise-level multi-regional input–output (EMRIO) table. This database merges official national input–output tables with publicly available firm-level production and transaction data, creating a globally consistent account of purchases and sales across 9,466 companies, 86,305 subsegments, and 121 countries. The finer resolution allows supply chain transactions to be represented in greater detail, providing an additional resource for analyses and policy tools requiring more disaggregated supply chain information.
2025
2025
Skogens helsetilstand i Norge. Resultater fra skogskadeovervåkingen i 2024
Skog dekker nærmere 40 % av Norges landareal. Skogene bidrar til karbonbinding både over og under bakken, forsyner oss med råvarer, spiller en viktig rolle for friluftslivet og er leveområdet for utallige arter. Skogens viktige rolle som leverandør av slike økosystemtjenester forutsetter imidlertid et intakt skogøkosystem, en god skoghelse og en langsiktig og bærekraftig forvaltning.
Skogens helsetilstand påvirkes i stor grad av klima og værforhold, enten direkte ved tørke, frost, snø og vind, eller indirekte ved at klimaet påvirker omfanget og spredningen av soppsykdommer og insektangrep.
Klimaendringene og den forventede økningen i klimarelaterte skogskader gir store utfordringer for forvaltningen av framtidas skogressurser. Det samme gjør invaderende skadegjørere, både allerede etablerte arter og nye som kan komme til Norge i nær framtid. Uansett hvilke utfordringer skogen står overfor, er det viktig med langsiktige skogovervåkingsprogrammer for å kunne oppdage endringer og iverksette tiltak mot truslene. I denne rapporten presenteres resultater fra skogskadeovervåkingen i Norge i 2024 og trender over tid for følgende temaer:
1. Landsrepresentativ skogovervåking;
2. Intensiv skogovervåking;
3. Barkbilleovervåkingen 2024: Fortsatt høye fangster i stormrammede områder;
4. Overvåking av fremmede trelevende insekter;
5. Almesyken sprer seg til nye områder;
6. Overvåking av askas naturlige foryngelse i skog angrepet av askeskuddsyke;
7. Andre spesielle skogskader i 2024.
NIBIO
2025
Impact of leakage during HFC-125 production on the increase in HCFC-123 and HCFC-124 emissions
Hydrochlorofluorocarbons (HCFCs) are ozone-depleting substances whose production and consumption have been phased out under the Montreal Protocol in non-Article 5 (mainly developed) countries and are currently being phased out in the rest of the world. Here, we focus on two HCFCs, HCFC-123 and HCFC-124, whose emissions are not decreasing globally in line with their phase-out. We present the first measurement-derived estimates of global HCFC-123 emissions (1993–2023) and updated HCFC-124 emissions for 1978–2023. Around 5 Gg yr−1 of HCFC-123 and 3 Gg yr−1 of HCFC-124 were emitted in 2023. Both HCFC-123 and HCFC-124 are intermediates in the production of HFC-125, a non-ozone-depleting hydrofluorocarbon (HFC) that has replaced ozone-depleting substances in many applications. We show that it is possible that the observed global increase in HCFC-124 emissions could be entirely due to leakage from the production of HFC-125, provided that its leakage rate is around 1 % by mass of HFC-125 production. Global emissions of HCFC-123 have not decreased despite its phase-out for production under the Montreal Protocol, and its use in HFC-125 production may be a contributing factor to this. Emissions of HCFC-124 from western Europe, the USA and East Asia have either fallen or not increased since 2015 and together cannot explain the entire increase in the derived global emissions of HCFC-124. These findings add to the growing evidence that emissions of some ozone-depleting substances are increasing due to leakage and improper destruction during fluorochemical production.
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
2025