Found 10544 publications. Showing page 4 of 422:
The dietary footprints and transition priorities of over 12 000 urban centers
Urban consumption plays a central role in driving global carbon emissions and is associated with a wide range of environmental pressures, including deforestation, water use, and biodiversity loss. As cities and networks of cities work to define and achieve quantitative sustainability goals, the lack of insight into their unique food footprints, shaped by each city’s specific dietary patterns and demographic composition, remains a significant obstacle. Here we combine demographic, group-specific diet, and supply-chain environmental footprint data to estimate the dietary footprints in 12 228 urban centers across 159 countries. We show that diet-related greenhouse gas emissions (GHGE) are highly concentrated in a small number of cities: The 200 urban centers with the largest footprints account for 39.8% of global urban population and 45.6% of total global urban dietary emissions. Overall, adoption of the EAT-Lancet 2.0 diet across all studied centers delivers a modest net reduction in total footprints (≈5%–16%). However, this aggregate outcome masks substantial variability: high-income centers achieve considerable reductions through lower meat and dairy consumption, while lower-income centers presently consuming below EAT-Lancet recommended levels experience footprint increases, partially offsetting global gains. Within transnational city networks (C40 Cities, Eurocities, and Milan Urban Food Policy Pact members), where member centers are predominantly high-income, EAT-Lancet 2.0 adoption delivers substantially larger reductions of 22%–50% in GHGE, underscoring the policy relevance of targeted urban-level dietary interventions. Complementary supply-side interventions, including decarbonization of agricultural production, processing, and distribution, offer additional reductions, indicating that dietary and supply-side levers must be deployed jointly. Our results highlight the need for context-specific urban dietary strategies. The resulting database, MATILDA-City, provides a globally harmonized evidence base to benchmark, rank, and monitor urban-level dietary footprints, supporting municipalities to coordinate actions toward sustainable food systems.
2026
A machine learning method for estimating atmospheric trace gas concentration baselines
Estimates of trace gas baseline mole fractions in high-frequency atmospheric measurement records are crucial for analysing long-term changes in atmospheric composition. Baseline mole fractions are those that would be observed far from emission sources (and hence are representative of background conditions). Previous methods for inferring baseline mole fractions have used statistical or meteorological approaches, or, if available, co-measured tracer species thought only to be emitted from non-baseline wind sectors. Combinations of these techniques have also been employed in some applications. Statistical methods typically fit a baseline to the observations themselves, while meteorological methods use atmospheric models of varying complexity to categorise air mass origins. In this paper, we present a novel machine learning method for estimating trace gas baseline mole fractions, which benefits from the physical basis of model-based filtering without the need for running an expensive simulator. Our approach offers the accessibility and computational cost-effectiveness of statistical models, without the associated smoothing or difficulty in identifying rapid baseline variations. By training on historical Lagrangian particle dispersion model outputs, our model learns to predict baseline mole fractions directly from meteorological fields. This advancement opens new avenues for low-latency trace gas time series data analysis, reconstruction of historical baseline trends, and improved utilisation of tracer measurement air mass classification methods.
2026
On the reliability of seasonal snow forecasts
Reliable information on seasonal snow conditions is important for long-range weather forecasting and climate modeling. The reliability of winter-mean hindcasts of snow water equivalent (SWE) produced by the ECMWF for the period 1993–2022 within the CopERnIcus climate change Service Evolution (CERISE) project is evaluated in this study. In probabilistic forecasting, reliability is defined as the consistency between forecast probabilities and observed frequencies for a binary event. Here, reliability is assessed using two independent SWE datasets (ERA5-Land and ESA Snow-CCI v4) across eight land regions in the Northern Hemisphere non-mountainous regions. The reliability assessment is performed for two tercile-based binary events representing low- and high snow accumulation winters. Reliability is quantified using a weighted linear regression applied to reliability diagrams and is grouped into five categories from perfect to dangerous. The results show that the ECMWF seasonal snow hindcasts consistently yield marginally useful to perfect reliability categories for both low- and high-snow conditions independently to the chosen benchmark. The assessment shows sensitivity to the choice of verification dataset, with ERA5-Land yielding higher reliability categories than ESA Snow-CCI, typically 1 to 2 categories higher. It is found that differences in hindcasts reliability between regions and between verification datasets may be linked to snow variability, model representation, and observational uncertainty.
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Environmental Contaminants in an Urban Fjord, 2025
This report presents data from the last year of a 5-year period of the Urban Fjord programme. The programme started in 2013 and has since been altered/advanced. In 2025 the programme covers sampling and analyses of sediment, polychaetes, krill, shrimps, blue mussels, herring, cod, eider, and herring gull from the Inner Oslofjord. A total of 230 single compounds/isomers were analysed, and frequent detection was found of specific PFAS compounds (e.g. PFOS) in most matrices, certain QACs in several matrices (ATAC-C22 in all
matrices), specific benzothiazoles in eider blood, LCCPs in certain matrices, certain siloxanes in most matrices, metals in all matrices and PCBs in all matrices. Biomagnification was observed for 24 PCB congeners, LCCPs and D4 (siloxane; lipid wt. basis). Furthermore, biomagnification was observed for PFOSA, ATAC-C20 and ATAC-C22, as well as for the metals As and Hg (wet wt. basis).
Norsk institutt for vannforskning (NIVA)
2026
Plastic pollution is an ever-growing concern around the globe, with current research portraying the presence of contaminants even in previously pristine regions. Especially small particles, micro- and nanoplastics, can be dispersed over long stretches by atmospheric transport, reaching even the most remote areas of the planet. This study aims to portray current levels of nanoplastic contamination (< 1 μm) by analyzing snow samples from high-altitude glaciers in the European Alps (2300–3800 m) via TD-PTR-MS. We were able to detect six common plastic pollutants, with PE and PP contributing over 60% of the total mass concentration measured across all sites. On average, nanoplastic concentrations of 85 ng mL − 1 (range: 3.6 ± 12 ng mL − 1 – 470 ± 76 ng mL − 1 ) were detected at sampled glacier surfaces. Access to these remote regions was enabled through a citizen-science initiative, involving trained mountaineers for sample collection. The results were applied to atmospheric modelling, highlighting possible point sources of contamination. While agriculture and local plastic factories were revealed as potential sources of nanoplastics, spatial and temporal limitations complicated comparison inside the sample cluster.
2026
Abstract Significant trends of ultraviolet radiation (UVR) have been reported at limited European sites due to changing atmospheric conditions, such as cloudiness. Whether these findings are applicable to larger areas or even the entire continent remains unclear. In a unique comparison, we analyzed measurements of erythemally weighted daily ambient radiant exposure from 40 European locations, covering the period from 2013 to 2022. At 26 locations annual means increases statistically significantly with a median of + 1.2%/yr. At 38 sites at least monthly means increases with medians between + 2%/yr and + 4%/yr. Increases were seen in satellite products of UVR, global solar radiation, and sunshine duration, too. Analysis at six stations, with data extending back to the mid-1990s, indicates that the period of statistically significant increases generally began between 2010 and 2013. Comparison of UVR data from 40 stations with a high-resolution global solar radiation trend map reveals complementary patterns, highlighting widespread but not uniform UVR changes across Europe. This combination enables figuring out the regional extent of trends. Thus, ground-based UVR measurements remain essential for quantifying changes, highlighting the need for continued monitoring with sufficiently dense measurement networks. This is also essential for understanding and mitigating the impacts of changing UVR on human health, particularly by assessing its potential for increased UVR-related skin cancer incidence and development of preventive measures. Moreover, detailed regional UVR data is essential for achieving the UN’s Sustainable Development Goals, specifically in human health, sustainable cities, climate action, and environmental conservation.
2026
Requirements and scientific needs for coordinated organic pollutant monitoring in both polar regions
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State of the Climate in 2025: The Arctic
Environmental conditions across the Arctic, a vast area above 60°N, look today remarkably different than one or two decades ago. Modern satellite era measurements of Arctic annual surface air temperature (1979–2025) show that the region has, on average, warmed roughly three times faster than the rest of the planet. Human emissions of heat-trapping gases are driving the change globally with additional processes in the Arctic amplifying the heating (section 5c). The impacts touch every corner of the terrestrial and marine landscape, including serious compounding hazards for people in the Arctic. This chapter delves into these long-term trends and details 2025 observations across the Arctic system, including a section on 2023/24 observations on glaciers and ice caps outside of Greenland (section 5h, which alternates yearly with a section on Arctic river discharge).
Examining surface temperature in the Arctic, 2025 was the second warmest year since the observational record began in 1900 (section 5c). The surface temperature anomaly for the year was 1.38°C above the 1991–2020 mean, a reflection of warmer-than-usual temperatures occurring across seasons. Autumn and winter continue to show the strongest increases in surface warming as compared to global trends, and 2025 marked the 12th consecutive year that Arctic temperature anomalies were higher than global surface temperature anomalies. Temperature changes also occur from the Earth’s surface up through the troposphere and stratosphere. The Arctic troposphere has warmed 0.3°C decade−1 since 1958, while the stratosphere has cooled by a similar amount, an expected pattern with human-caused climate change (section 5b). In 2025, polar tropospheric air temperatures were the second highest on record.
Overall warming in the Arctic is accompanied by increases in precipitation, including the potential for bigger rain and snow events. During the period 1950–2025, there was an upward trend in annual precipitation totals, including significant upward trends in all seasons (section 5d). Examining annual records, 2025 had the third highest annual precipitation total on record, and the largest precipitation anomalies with respect to 1991–2020 were in winter (112%), spring (108%; the highest spring anomaly on record), and autumn (104%). Snow cover extent is connected to these coupled changes in precipitation and temperature, with patterns of snowpack buildup and melt shifting over the last several decades. In 2025, Arctic snow cover extent was roughly normal in Eurasia and North America in May but dropped below normal in June with early loss of snow cover, a now common occurrence (section 5i).
Arctic landscapes both respond to and influence temperature and precipitation changes. With vast areas of tundra as well as permafrost, the Arctic is home to a unique physical system that is responding rapidly to overall warming. Changes in Arctic tundra plants and productivity, such as increases in the abundance, distribution, and height of shrubs, result in Arctic “greening”, which has been detected since the late 1990s. Beginning in 2020, the Arctic has experienced a sequence of record- or near-record-high greenness values, to which 2025 is now added as the third highest value (section 5k). Local and regional variation is notable, however, with, for example, both greening and “browning” in the Eurasian Arctic. Vegetation changes in the Arctic are intrinsically connected to changes in permafrost as well. Since the 1980s, permafrost across the Arctic has seen a long-term warming trend, with the strongest trends in high-latitude, cold permafrost (section 5j). The active layer thickness, or the maximum depth of surface ground that seasonally thaws and freezes, has also increased, though at different regional rates.
Permafrost thaw is also a key player in Arctic terrestrial carbon dioxide and methane storage, though other important processes are also at play, such as wildfire, wetland development or loss, and river and lake outgassing. Examining tundra and boreal forest ecosystems in Arctic permafrost regions suggests that together carbon dioxide from these sources made the region a small net carbon dioxide source during the period 2000–20 (Sidebar 5.2). This is a serious and potentially long-term shift from Arctic permafrost regions acting as a carbon dioxide sink that dampens warming to a source that can enhance warming. Subannual records also show that the seasonal cycle of carbon storage and release is amplifying, reflecting both stronger winter emissions and stronger summer uptake (Sidebar 5.2).
Dramatic change continues for other frozen components of the Arctic system. On land, the Greenland Ice Sheet, which holds the second largest reservoir of frozen fresh water on the planet, had yet another year of overall ice loss (129±50 Gt based on gravity measurements; section 5g). Sixty percent of the planet’s glaciers and ice caps outside of Greenland and Antarctic are also found in the Arctic, and ice loss across these areas has tripled since the mid-1990s. During 2023/24, both Arctic Scandinavia and Svalbard had record years of ice loss with melt 1473% above the 1991–2020 mean in Arctic Scandinavia and 482% above in Svalbard (section 5h).
Arctic sea ice records also continue to show very low extent and predominantly first-year ice. The maximum sea ice extent in March 2025 was the lowest in the 47-year record, continuing a downward trend of −2.5% per decade, while September 2025 minimum extent was the 11th lowest on record, adding to a trend of −13.6% per decade extent loss (section 5f). Ice older than four years old is now nearly absent, with only 95,000 km2 of older ice in September 2025 as compared to 1.5 million km2 in the 1980s. Without sea ice cover, Arctic Ocean surface waters are exposed to heating from solar radiation and the atmosphere. Examined annually in August, the 2025 sea surface temperature in most Arctic Ocean regions was the highest in the 1982–2025 record and the pan-Arctic mean was the second highest on record (section 5e).
Pervasive environmental changes have direct and indirect impacts on people within and beyond the Arctic (e.g., Meng et al. 2023; Moon et al. 2019). In many instances, communities experience the combined impacts of multiple rapidly changing systems. For example, permafrost thaw and glacier retreat are increasing hazards such as glacial lake outburst floods, landslides, and the reliability of water supplies. Extreme weather hazards are also increasing. A prime example is the devastating ex-typhoon Halong that hit the Alaska west coast on 11–12 October 2025 (Sidebar 5.1). The storm traveled across anomalously warm ocean surface temperatures, and peak storm surge arrival on shore coincided with the daily high tide. Storm impacts were intense and widespread, including substantial inland and coastal flooding, ferocious winds, infrastructure loss, and loss of life.
The pace of change and the seriousness of impacts across plants, animals, and people highlight the importance of maintaining and strengthening our environmental intelligence regarding the Arctic region. Real threats to our scientific monitoring ability exist, such as the loss of a long-term Arctic vegetation monitoring dataset due to funding cuts (section 5k). This chapter’s observations show that the Arctic today is vastly different than the past, requiring close attention and increased action for hazard preparedness and response.
2026
This study investigates atmospheric microplastic (MP) exchange between marine and terrestrial compartments and associated deposition patterns at Bushehr Port, Persian Gulf. We combined field sampling of the sea-surface microlayer (SML), bulk seawater, sea foam, deposited particles, and suspended airborne particles with FLEXPART Lagrangian dispersion modelling and exploratory Elastic Net regression to evaluate MP sources, transport pathways, and meteorological controls. The simulations indicate a pronounced seasonal contrast in atmospheric MP transport and suggest that land-based sources collectively represented the largest modelled contribution to the atmospheric MP burden. Within the FLEXPART inventory, textile-related microfibres were the largest modelled source category for suspended MPs (∼61%); for deposited MPs, the estimated microfibre contribution (∼32%) was comparable to bare-soil resuspension (∼31%), while sea spray contributed ∼11% to both fractions. Elastic Net regression repeatedly retained air pressure as a positive predictor and the Lifted Index as a negative predictor; however, these associations are interpreted as exploratory because of the limited number of independent sampling intervals. Sea foam and SML samples were enriched in MPs relative to bulk seawater, although the enrichment pattern varied with wave period and tidal-current conditions. The large difference between field-derived net deposition velocities (Vd) and theoretical terminal velocities (Vt) indicates that turbulence, resuspension, environmental mixing, and particle-shape assumptions substantially affect the apparent removal of atmospheric MPs. Overall, the results suggest that MP cycling at this semi-enclosed coastal margin is influenced by coupled land-based emissions, marine surface processes, and atmospheric dynamics, highlighting the need for mitigation strategies that consider both local terrestrial inputs and air-sea exchange.
2026
Climate change impacts on designing the power system of Kenya in 2050
Africa’s economic growth in the coming decades will hinge on the strategic planning of national power systems to meet growing demand and ensure rural energy access. Renewable energy sources, particularly wind and solar, will be pivotal in the expansion and transition to a low-carbon energy system. However, the vulnerability of these renewable sources to climate change could introduce imponderability in the design of the energy mix. In this regard, this paper explores a climate-informed energy system pathway by integrating the future climate projections directly into the capacity expansion of Kenya’s power system within three scenarios towards 2050, to formulate future energy profiles under climate change. The PyPSA-Earth model is applied to calculate capacity expansion decisions of the Kenyan power system. The EC-Earth3-Veg Earth System Model projects future climate variables such as wind speed. The cooling demands with global warming are estimated based on Cooling Degree Days (CDDs) projected by the Multi-Climate Model ensemble. The capacity expansion optimization results reveal that temperature increase leads to a rise in cooling demand, resulting in capacity expansion by 12% to 52% larger than the cooling demand without global warming. The projected change in wind speed is complex, with the onshore wind speed declining and the offshore wind speed rising, which causes a jump in the share of offshore wind power, taking 9% to 19% of the total capacity. Life cycle assessment indicates that large-scale deployment of wind and solar has less 5% climate change mitigation potential, but has 35% more total system cost compared to the baseline. In Kenya, geothermal is expected to continue playing a critical role in the energy strategy. Besides solar power, offshore wind is forecasted to become an important renewable energy source for Kenya. However, climate models’ resolutions and accuracy need to be further improved for effective integration into energy system modelling.
2026
Promoting healthy lifestyle behaviors, including physical activity, sleep, diet, stress management, and healthy habits, requires adaptive systems capable of responding to dynamic changes in human behavior. Sustained behavioral change improves individual wellbeing, reduces disease risk, and contributes to healthier societies. However, developing personalized behavioral intervention systems is challenged by demographic heterogeneity, limited and fragmented datasets, reporting inconsistencies, and scarce high-quality labeled data. Ethical, privacy, and cost constraints further restrict the collection of large-scale longitudinal behavioral data. Consequently, there is a need for robust simulation and synthetic data generation frameworks that enable the development and evaluation of adaptive decision-making systems capable of optimizing personalized behavioral interventions over time. This study presents a digital twin framework integrated with tabular Q-learning for personalized behavioral recommendation under World Health Organization (WHO) lifestyle constraints. The framework combines synthetic behavioral data generation, reinforcement learning, and a TSP-inspired planning mechanism to investigate long-term behavioral adaptation in privacy-preserving simulated environments. The digital twin environment models user adherence variability, misreporting, dropout, and behavioral drift, enabling the evaluation of intervention strategies under realistic conditions. Experimental evaluation on synthetic populations demonstrates that Q-learning achieves competitive reward performance while maintaining favorable computational efficiency and stability compared with heuristic and reinforcement learning baselines. Statistical analysis indicates that reward differences among the evaluated methods are not significant; however, the proposed framework provides a flexible platform for adaptive behavioral recommendation and simulation-based experimentation. Furthermore, a real-time recommendation interface illustrates how simulation knowledge can be translated into actionable behavioral guidance. The proposed framework offers a scalable foundation for future digital health systems, particularly in scenarios where data scarcity, privacy constraints, and personalization requirements limit the use of real-world datasets.
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