Search Results (11,997)

Food waste generated by hospitalized patients represents a significant challenge with environmental, economic, and social implications. In this context, Sustainable Development Goal 12, which promotes responsible consumption and production patterns, highlights the urgency of reducing this waste as an essential measure to mitigate climate change, optimize resource use, and improve the sustainability of health and food systems. This study presents a narrative review of the literature, complemented by a bibliometric analysis, aimed at synthesizing the available evidence on food waste in hospitals. Based on the identification of 746 records in different databases published between 2019 and 2024, studies focusing on the determining factors, quantification methods, and sustainable strategies to mitigate hospital food waste were included. The lack of menu personalization, the perceived low quality of food, operational disorganization, and reduced patient appetite are identified as relevant factors associated with waste at the hospital level, while direct weighing remains the most accurate quantification method. The sustainable strategies reviewed can reduce food waste and improve hospital sustainability; however, there remains limited assessment of their long-term impact. Our results highlight the urgent need to address food waste in hospitals through the implementation of comprehensive, evidence-based strategies. Full article

In 2023–2025, a research study named “Application of nuclear, seismic and infrasound methods for assessing climate change and mitigating the effects of climate change” was conducted in Kazakhstan under the Targeted Funding Program. The main task of the study was to create an observation network for processes occurring in the glaciers of the high Tien Shan. Seismic and infrasound methods were used for signal recording, and meteorological data was additionally used for the analysis. A network of seismic, infrasound and meteorological stations has been installed near the large glaciers of Tien Shan in Kazakhstan. This paper presents the results of the recorded data in terms of seismic and infrasound noise levels, daily variations, and the relationship between noise and changes in temperature and wind speed. The threshold of the expected minimal magnitude and energy classes of glacial earthquakes for day and night was assessed. Seismic and infrasound monitoring has proven to be a reliable all-season and all-weather tool for monitoring the dynamics of glacial processes. Among the large number of recorded glacial events, more than 4000 have been located, and a seismic bulletin that includes information on the location, magnitude, and energy class of each has been compiled. Full article

The Earth’s climate system exhibits nonlinear behavior driven by interactions among the atmosphere, oceans, cryosphere, land, and biosphere. These dynamics have given rise to relatively stable environments that shape the structure and function of the modern biosphere. This review is a primer for conservation practitioners and natural resource managers to develop a deep understanding of how the Earth System works. The key is to recognize that shifts in Earth System dynamics due to global climate change can destabilize the biosphere in unforeseen ways. The potential emergence of novel ecoregions must be a critical factor in adaptation planning for conservation and resource management. We review how thermodynamic constraints and global circulation dynamics determine the distribution of terrestrial and marine biomes. These dynamics stem from the Earth System functioning as a heat engine, transporting excess heat from low to high latitudes. We illustrate how biome climates are organized into climate regimes, with spatial and temporal characteristics linked to complex features of atmospheric and oceanic circulation. At centennial to millennial scales, these dynamics have created a stable envelope of natural variability in climate that has established a long-standing operating space for biota. However, this stability is becoming increasingly uncertain due to the growing positive energy imbalance in the Earth System primarily driven by anthropogenic greenhouse gas emissions. This forcing is leading to disruptive climatic change, putting the biosphere on a trajectory toward new transient states. Such global to regional climatic instability and biospheric restructuring introduce a high level of uncertainty in ecological futures, with major implications for natural resource management, biodiversity conservation strategies, and societal adaptation. We conclude by discussing frameworks for impact assessments and decision making under climate uncertainty. Full article

This study examines the erosion potential of earthen spillways under the growing risks posed by changing climate and extreme flood events, which threaten the stability and safety of dam infrastructure. Specifically, it employs a machine learning approach to evaluate how readily available spillway width and stream power can predict erosion potential. Site-specific erosion prediction methods are often costly and time-consuming because they rely on extensive field investigations and physical modeling. To address these challenges, this research employs multiple machine learning algorithms, including logistic regression, Support Vector Machine, and Random Forest, on existing data to classify spillways as erodible or non-erodible cases. The Random Forest model demonstrated the best predictive performance, achieving 82.7% accuracy on the test dataset. To further interpret the reliability of model predictions, a Bayesian probability analysis was performed, revealing that when the model predicts erosion, there is a 59% probability that the dam will actually experience erosion. These results highlight how integrating existing datasets with machine learning and probabilistic reasoning can enhance dam safety assessment by considering the accuracy, efficiency, and reliability of spillway erosion predictions. Full article

Urban forests are highly valued for the multiple benefits they provide to city dwellers. The strategic provision of ecosystem services by these forests is threatened by climate change, warming conditions being responsible for heat waves and chronic droughts that inflict stress and mortality on trees. A three-year study (2011–2013) conducted at Parco Nord Milano (PNM) (Milano, Italy) assessed the impact of thinning interventions on the dynamics of fungal pathogens in declining forest plots. Symptomatic trees of the genera Alnus, Acer, Fraxinus, Platanus, Quercus and Ulmus, exhibited in thinned subplot pronounced decline/dieback, exhibiting symptoms like microphyllia, leaf yellowing, leaf shedding, sunken cankers, shoot wilting and branch dieback. Comparative analyses between the thinned and unthinned subplots revealed a significantly higher incidence of pathogens in the thinned one. Five species of Botryosphaeriaceae, namely Botryosphaeria dothidea, Diplodia corticola, Diplodia seriata, Dothiorella omnivora and Neofusicoccum parvum, were consistently isolated from tissues of declining hosts. There is evidence that thinning altered plot-level microclimate conditions and microbial equilibrium, favoring the proliferation of latent, pathogenic Botryosphaeriaceae. In fact, during the study period, the presence of N. parvum increased tenfold and that of B. dothidea fivefold in thinned subplot. Conversely, in unthinned subplot, the same pathogenic taxa maintained stable proportions. These results demonstrate that thinning altered ecological balances increasing tree susceptibility to harmful, cosmopolitan botryosphaeriaceous fungi. Our findings challenge assumptions about thinning as a universally beneficial practice, emphasizing the need for silvicultural strategies that take into account host and pathogen ecology and the microclimatic resilience of forest stands. This study emphasizes the importance of adaptive management in urban forestry to mitigate the unintended ecological consequences of climate change. Full article

Climate warming and land degradation are reshaping Mediterranean and semi-arid ecosystems, yet their combined effects remain poorly quantified in North Africa. Using four Landsat reference epochs spanning 1984–2024, and four spectral/thermal indices (NDVI, EVI, NDMI, LST), we assessed vegetation dynamics and eco-climatic resilience of Tetraclinis articulata ecosystems in Morocco. Four study sites (Stehat, Merchouch, Tamanar, and Amskroud) distributed along a latitudinal gradient from the northern to southern limits of the species’ Moroccan range were chosen and analyzed. Results reveal a generalized decline in vegetation cover, strongly coupled with increasing land surface temperatures, with threshold-like patterns emerging above 74–75 °C that lead to a rapid reduction in NDVI. The northern site (Stehat) exhibited partial recovery, likely supported by local schist aquifers, whereas the arid southern sites (Tamanar and Amskroud) experienced near-total biomass loss and reduced climate buffering. Moisture indices limited hydrological mediation and suggest that shallow soil water availability constrains T. articulata functioning, amplifying vulnerability under recurrent warming. These findings demonstrate how local edaphic and hydrological conditions modulate the impacts of global change and provide early warning indicators of heightened vulnerability and potential threshold-like behavior in drylands. The study emphasizes the urgent need for targeted management strategies to sustain ecosystem resilience under accelerating climate stress. Full article

Methane (CH₄) is one of the most important greenhouse gases, and substantially impacts climate change. Over a 20-year period, its global warming potential (GWP) is approximately 80 times higher than that of carbon dioxide (CO₂). One of the significant sources of methane emissions is the hard coal mining industry, particularly regarding the release of methane with mine ventilation air. Methane released from coal seams during mining operations and discharged into the atmosphere through exhaust shafts is referred to as VAM (Ventilation Air Methane). In the context of the European Union’s climate policy, activities aimed at reducing and utilizing VAM emissions are gaining increasing importance. One initiative supporting the development of such solutions is the research project ProVAM (Reduction of Ventilation Air Methane Emissions in the Coal Mining Transformation Process), implemented by a consortium of scientific and industrial institutions from EU member states. The project focuses on developing guidelines and selecting technologies dedicated to the utilization of VAM. This article presents a methodology for assessing parameters associated with VAM emissions and provides a characterization of the selected mine exhaust shafts analyzed within the ProVAM project. Key technical factors affecting the feasibility of using oxidation technologies to reduce methane emissions from hard coal mining are identified. Full article

Groundwater in Mediterranean regions is facing increasing threats from climate change and intensive agriculture, necessitating robust vulnerability assessment tools. This study evaluates nitrate pollution vulnerability of the Almyros aquifer (Thessaly, Greece) using the DRASTIC index under the high-emission scenario RCP8.5. Bias-corrected Med-CORDEX climate projections were integrated into a coupled hydrological–hydrogeological modeling framework to simulate recharge, groundwater levels, and nitrate transport. DRASTIC results for the baseline (1991–2018) showed strong agreement with observed nitrate concentrations, while future projections (2031–2060, 2071–2100) revealed shifting vulnerability patterns, particularly in low-lying agricultural areas. The findings highlight climate-driven changes in groundwater vulnerability and support targeted adaptive management strategies. Full article

Forest ecosystems provide essential ecological functions in the context of accelerating climate change. However, evaluating their conservation values and conditions remains challenging due to conceptual and methodological ambiguities. In particular, ecosystem integrity and ecosystem authenticity are often conflated in vegetation-based assessments, despite representing distinct dimensions of ecosystem condition. This study advances vegetation-based assessments by explicitly decoupling ecosystem integrity from ecosystem authenticity, while integrating spatial completeness, vegetation patterns and quality, and successional–disturbance attributes into a unified operational framework for reserve-level diagnosis and comparison. The resulting indices enable managers to distinguish boundary-driven limitations of landscape integrity from internal vegetation conditions that persist in near-natural states, thus enhancing interpretability for conservation planning in the context of climate change. Using standardized forest resource survey data and spatial analysis, we constructed two composite indices: Forest Ecosystem Integrity (FEI) and Forest Ecosystem Authenticity (FEA). These indices were applied to two adjacent cold-temperate forest nature reserves, Hanma and Huzhong, in the Greater Khingan Mountains of northeastern China, as well as to a merged spatial scenario. The results demonstrate consistently high ecosystem authenticity (>90%) across all study areas, indicating strong naturalness and successional maturity. In contrast, ecosystem integrity remains moderate (63–69%), primarily constrained by the low spatial completeness of conservation units. The spatial integration of the two reserves significantly improved ecosystem integrity without compromising authenticity, highlighting the role of boundary configuration in conservation effectiveness. By operationalizing integrity and authenticity as complementary yet distinct dimensions, this study provides a reproducible framework for evaluating forest ecosystem conditions and offers practical insights for the design of protected area networks and adaptive management in cold-temperate forest regions. Full article

In regions lacking sufficient data, remote sensing (RS) offers a reliable alternative for precipitation estimation, enabling more effective drought management. This study comprehensively evaluates four commonly used RS datasets—Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS), Tropical Applications of Meteorology using Satellite data (TAMSAT), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), and Multi-Source Weighted-Ensemble Precipitation (MSWEP) against ground-based data—with respect to their performance in detecting precipitation and drought patterns in the Great Ruaha River Basin (GRRB), Tanzania (1983–2020). Statistical metrics including the Pearson correlation coefficient (r), mean error (ME), root mean square error (RMSE), and bias were employed to assess the performance at daily, monthly, seasonal (wet/dry), and annual timescales. Most of the RS products exhibited lower correlations (r < 0.5) at daily timestep and low RMSE, bias, and ME. Monthly performance improved substantially (r > 0.8 at most stations) particularly during the wet season (r = 0.52–0.82) while annual and dry-season performance declined (r < 0.5 and r < 0.3, respectively). Performance under RMSE, bias, and ME declined at higher timescales, particularly during the wet season and annually. CHIRPS, MSWEP, and PERSIANN generally overestimated precipitation while TAMSAT consistently underestimated it. Spatially, CHIRPS and MSWEP reproduced coherent basin-scale patterns of drought persistence, with longer dry-spells concentrated in the northern, central, and western parts of the basin and shorter dry-spells in the eastern and southern regions. Trend analysis further revealed that most products captured consistent large-scale changes in dry-spell characteristics, although localized drought events were more variably detected. CHIRPS and MSWEP showed superior performance especially in capturing monthly precipitation patterns and major drought events in the basin. Most products struggled to detect extreme dry conditions with the exception of CHIRPS and MSWEP at certain stations and periods. Based on these findings, CHIRPS and MSWEP are recommended for drought monitoring and water resource planning in the GRRB. Their appropriate use can help water managers make informed decisions, promote sustainable resource use, and strengthen resilience to extreme weather events. Full article

Rapeseed (Brassica napus L.) is a major oilseed crop worldwide, particularly valued for its high yield potential, favorable fatty acid composition, and its bioactive compounds that improve nutritional and industrial quality. However, its productivity and oil quality are increasingly compromised by climate change-induced water scarcity, particularly in semi-arid Mediterranean regions. In this study, the performance of 17 genotypes was evaluated under well-watered (irrigated) and rainfed (stressful) conditions across two contrasting locations, Douyet Experimental Station (DYT) and Ecole Nationale d’Agriculture de Meknès (ENAM), during the 2023/2024 growing season. The assessment concerned seed yield, oil traits, and nutraceutical quality. The results obtained show that drought stress significantly reduced seed yield by about 26% (from 2.29 to 1.69 t ha⁻¹) and decreased oil content by about 8.3% (from 41.1% to 37.7%). The highest reductions were observed for sensitive genotypes, particularly ‘IND23’, ‘IND82’, and ‘H2M-5’, while ‘Moufida’, ‘Nap9’, and ‘TP2’ maintained seed and oil yield above the overall average across both water regimes. Drought also impacted the accumulation of secondary metabolites, with mean total phenolic content increasing from 5.41 to 9.98 mg GAE g⁻¹ (+84.5%) and total flavonoid content rising from 25.25 to 34.93 mg QE g⁻¹ (+38.3%) under rainfed conditions, accompanied by marked increases in antioxidant activity (DPPH, ABTS), particularly for ‘Moufida’, ‘Nap9’, ‘TP2’, and ‘Marina’. Oil quality indices remained within Codex Alimentarius standards, with a slight increase in acidity values accompanied by a decrease in peroxide values, thus suggesting improved oxidative stability. Principal component analysis grouped genotypes into distinct clusters, with an elite group (‘Moufida’, ‘Nap9’, and ‘TP2’) characterized by yield stability, accumulation of phenolics, and high antioxidant activity, thus confirming their strong adaptation to the dry conditions of the Mediterranean region. These drought-tolerant lines, with high agronomic performance combined with good nutritional quality, can be recommended as valuable cultivars for sustainable and high-quality rapeseed production in dry Mediterranean regions. Full article

Growing water scarcity, climate change, and increasingly stringent environmental regulations have intensified the need for advanced wastewater treatment technologies capable of removing emerging contaminants and enabling safe water reuse. This review provides an integrated assessment of recent trends in membrane bioreactors (MBRs) and advanced oxidation processes (AOPs), including their role in hybrid treatment systems, with emphasis on contaminant removal efficiency, energy demand, operational complexity, and transformation product formation. In parallel, an exploratory statistical analysis of EUROSTAT indicators—population connected to wastewater treatment plants, Water Exploitation Index (WEI), freshwater availability, and sludge production—was conducted to examine relationships between treatment infrastructure and pressures on water resources across Europe. Correlation and principal component analyses reveal weak to moderate and predominantly indirect relationships between infrastructure expansion and water stress, highlighting that connectivity alone does not reduce resource pressure in the absence of water reuse and advanced treatment. The combined technological and statistical evidence demonstrates that reuse-oriented MBR–AOP systems are critical for improving effluent quality, mitigating emerging pollutant risks, and supporting circular, climate-resilient water management strategies under European policy frameworks. Full article

The Lake Sevan basin is particularly sensitive to climate change due to its continental climate and mountainous terrain, which collectively amplify climatic impacts. This study aimed to assess the influence of climate change on the thermal dynamics of the basin by analyzing both historical and projected temperature variations. Over the past three decades, the region has experienced a marked rise in air temperatures. Seasonal variability revealed distinct contrasts between winter and summer, with winter exhibiting greater fluctuations, ranging from 1.67 to 2.41 °C, compared to the more stable summer range of 0.81 to 1.41 °C. An analysis of heat inflow and outflow patterns demonstrated a moderating effect of Lake Sevan on temperature extremes. Stations, located near the lake, recorded lower levels of heat inflow and outflow, indicating that the lake’s thermal inertia helps buffer seasonal temperature extremes. In contrast, stations situated farther from the lake exhibited more pronounced fluctuations, reflecting the absence of this stabilizing influence. These results underscore the lake’s critical role in modulating the local climate by dampening extreme thermal variations. Additionally, comparative analysis of air and water temperature trends revealed that, while both exhibit warming, air temperatures show greater interannual variability. In contrast, water temperatures remained more stable, particularly during winter, due to the lake’s thermal inertia. Future climate projections for the Lake Sevan region, based on CMIP6 (Coupled Model Intercomparison Project phase 6) ensemble outputs under four Shared Socioeconomic Pathways (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5), suggest a persistent warming trend throughout the 21st century. We project that the most significant increases are expected during summer months, with an anticipated mean annual temperature rise of up to 6 °C by the end of the century under the high-emission scenario (SSP5–8.5). Full article

This study investigates transboundary hydro-meteorological trends in the Upper Po River basin, adopting a multi-perspective framework to disentangle the joint evolution of climatic and hydrological drivers. We analyzed climatic variables from 25 weather stations (1950–2022) alongside streamflow data from 14 river sections (1911–2022). Trends were assessed using the Mann–Kendall test to detect monotonic changes and the Theil-Sen estimator to quantify magnitude, ensuring robustness against outliers. The results reveal pronounced warming, particularly in spring maximum temperatures with +0.95 ± 0.40 °C per decade, and +0.62 ± 0.35 °C per decade at the annual scale. Conversely, average and minimum daily temperatures show lower rates with, respectively, +0.50 ± 0.26 °C and +0.39 ± 0.27 °C at the annual scale. Consequently, potential evapotranspiration increased significantly (+15.1 ± 9.4 mm per decade), likely contributing to a marked decline in summer streamflow in 8 out of 14 sections. Correlation analysis confirms that snow dynamics modulate the hydrological response: precipitation drives discharge annually and in autumn, winter exhibits a weaker coupling, as winter precipitation is partially stored in the basin as snow, contributing to discharge during spring and summer. By focusing on this strategic region for European agriculture and industry, the study provides useful insights into the combined effects of warming and evapotranspiration on water availability for adaptation strategies. Full article

Growing pressures on water resources, exacerbated by climate change, resource depletion, and population growth, underline the need for sustainable and energy-efficient wastewater management. Wastewater treatment plants (WWTPs) are among the most energy-intensive elements of the Integrated Water Service, and their environmental performance depends on infrastructure design, resource availability, and treatment configuration. Improving resource efficiency while reducing energy demand and environmental impacts is therefore a priority for water utilities seeking innovative decision-support tools. Within the national project “WATERGY—Energy Efficiency of the Integrated Water Service”, this study proposes a life-cycle-based framework to assess the sustainability of technological interventions in WWTPs. A comparative gate-to-grave Life Cycle Assessment (LCA) was applied to the municipal WWTP of Potenza (Southern Italy). Three sludge End-of-Life Scenarios were assessed: the current landfill-based configuration, an enhanced oxygenation–nitrification setup, and anaerobic digestion with biogas-based cogeneration. Compared to the current scenario, anaerobic digestion with cogeneration reduces Global Warming Potential by 17% and decreases freshwater ecotoxicity by approximately 30%. Compost production shows the highest reduction in ecotoxicity (−51%) but increases fossil resource depletion and acidification due to higher energy demand. Overall, energy recovery pathways, particularly anaerobic digestion with cogeneration, provide the most balanced environmental benefits, supporting more sustainable WWTP operation within the Integrated Water Service. Full article