Search Results (10,499)

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

HVAC systems account for a significant portion of building energy consumption, making them a critical factor in achieving energy efficiency and sustainable development in buildings. The thermal comfort environment within kindergarten buildings has a direct impact on children’s health and learning performance while also being closely linked to building energy consumption. Natural ventilation serves as a fundamental passive technology for ensuring indoor air quality. It offers advantages such as energy savings and emissions reduction while improving thermal comfort, making it a key advancement in promoting sustainable building practices. Air change rate serves as a key indicator for measuring indoor air renewal. This study, based on the characteristics of young children being more sensitive to environmental changes and having weaker resistance, investigated the impact of different air change rates on indoor thermal comfort in kindergartens across three distinct climatic zones in China: hot summer and warm winter, hot summer and cold winter, and temperate areas. Thermal comfort was evaluated using the Temperature Humidity Index (THI) and temperature fluctuation rate. And the effects of air change rates on building energy consumption were further examined. Simulation results show that the influence of air change rates on indoor thermal comfort, temperature fluctuations, and energy consumption varies significantly across climate zones. Guided by the sustainable principles of prioritizing children’s health and low-energy operation, the findings indicate that an air change rate of 1.5 is optimal in hot summer and warm winter areas, a rate of 0.5 is most suitable in hot summer and cold winter areas, and a rate of 0.5 is most suitable in temperate areas. This study aims to provide scientific evidence for achieving energy conservation and sustainable ventilation design through natural ventilation in kindergarten buildings across different climate zones, while ensuring children’s health. Full article

The southern elderberry (Sambucus australis Cham. & Schltdl.), whose berries have highlighted functional properties, is native to temperate regions of eastern South America and is found growing spontaneously at the Reserva Ecológica Costanera Sur (RECS) in Buenos Aires, Argentina. This study aimed to describe the development of the flower bud to ripe fruit of S. australis in the agro-ecological conditions of the RECS, evaluate the different floral phases in relation to climatic factors, and identify the visiting insects that could act as potential pollinators. Flowers have all the organs to classify them as hermaphrodites; functionally, some flowers have shortly stamens without pollen and others have a non-functional ovule. Male and female flowers exhibited substantial synchronization, with the appearance of button flowers and anthesis phases occurring either simultaneously or very closely. On the other hand, it adapts to climatic changes that may occur by modifying the dates of the start of flowering and the maximum expression of the anthesis phase. Rainfall significantly influenced the opening of flower buds, the number of flowers in anthesis, and the harvest of the fruits of this species. Visiting insects which could perform pollination have been identified. Full article

Dasiops saltans is a small insect pest associated with pitahaya cultivation, whose occurrence is strongly influenced by specific environmental conditions. This study examined where this species could live in the Amazonas region by using models that identify areas with favourable conditions. With this approach, the current and future distribution of the insect was estimated, considering possible changes in climate. The results show that the places with the best conditions for the species may decrease slightly in the coming decades, while most of the region will continue to be unfavorable for its presence. The study also identified which environmental factors most influence where the insect can survive, highlighting the role of the terrain, soil characteristics and climate conditions related to temperature and moisture. These findings help us better understand the environmental limits of Dasiops saltans and provide useful information for decision-makers, farmers and local authorities, who can use this knowledge to improve management, monitoring and prevention strategies in agricultural areas. Full article

Anthropogenic activities and climate change have accelerated biological invasions, leading to profound ecological, economic, social, and health impacts. The invasive species fall webworm (Hyphantria cunea) has been reported to have outbreaks in areas with climate anomalies and human settlements in recent years, highlighting the necessity to explore the species’ suitable habitat and associated future changes. We built an ensemble species distribution model using Random Forest, MaxEnt, and Support Vector Machine, achieving excellent predictive performance (AUC = 0.996). Our results identify human settlement density as the dominant driving factor, with a contribution > 50%, far exceeding climatic and forest structure variables. Therefore, densely urbanized regions such as Beijing–Tianjin–Hebei, the Liaodong Peninsula, and the North China Plain comprise the current highly suitable areas. Future climate projections suggest a continued expansion of the suitable habitat for H. cunea, with the most pronounced growth expected under the high-emission pathway (SSP5-8.5), where human activity is greatest. Such a correlation indicates that highly urbanized regions should be given priority for corresponding monitoring and control measures. As climate warming continues, northeastern China will face escalating invasion risks. Conversely, some regions within the Yangtze River Delta may become less suitable for the habitation of H. cunea. These findings provide insightful guidance for region-specific surveillance, quarantine measures, and the precision management of H. cunea in China. Full article

Background: Cultivated strawberry (Fragaria × ananassa) is one of the most valuable horticultural crops worldwide. Nevertheless, its productivity is increasingly constrained by high susceptibility to adverse environmental conditions, which are intensified by climate change. Drought represents a major limitation, often accompanied by water deficiency and elevated soil salinity. Plants counteract such abiotic stresses through complex molecular defense mechanisms involving transcription factors that regulate stress-responsive gene expression. Methods: In this study, we conducted a systematic bioinformatic analysis of the Tubby-like protein (TLP) transcription factor family in Fragaria × ananassa. RT-qPCR was used to analyze the expression patterns of FaTLP genes under different conditions to elucidate their potential roles in stress adaptation. Results: Eight FaTLP genes were identified in each of the four subgenomes, most of which retained the characteristic TUBBY and F-box domains. Gene expression profiling revealed that several FaTLP genes were differentially expressed in leaves under drought and salt stress, with FaTLP2 and FaTLP7 exhibiting strong induction. In addition, the expression of FaTLP2 and FaTLP7 under various oxidative and signaling-related treatments, as well as in different tissues of strawberry plants were analyzed. Promoter analysis identified multiple cis-regulatory elements associated with phytohormone signaling and abiotic stress responses, such as ABRE, MYB, and MYC motifs. Phylogenetic analysis showed that FaTLP2 and FaTLP7 share high sequence similarity with orthologous TLPs from other plant species known for enhanced stress tolerance, suggesting that these proteins may play conserved roles in the molecular mechanisms underlying drought and salinity resilience. Conclusions: This study provides valuable insights into the potential roles of FaTLPs in regulating environmental signal transduction and transcriptional control, contributing to abiotic stress tolerance in Fragaria × ananassa. Full article

Drought stress is one of the major abiotic factors limiting crop growth and yield, particularly in wheat. Water deficit leads to reduced chlorophyll content, impaired photosynthetic performance, and decreased biomass accumulation. Nitrogen fertilization may influence plant physiological responses to drought; however, its capacity to alleviate drought-induced growth reduction remains uncertain. A pot experiment was conducted to evaluate the impact of different nitrogen-based fertilizers on wheat seedlings grown under irrigation level 60% PPW (control) and 30% PPW (drought stress) conditions, with balanced levels of phosphorus and potassium maintained in all treatments. Water deficit led to substantial reductions in chlorophyll content compared to optimally irrigated plants. Similarly, the performance index (PI) decreased by 139.3% at Term 1 (1 day after foliar nitrogen application) and 27.2% at Term 2 (7 days after application). The net photosynthetic rate (Pn) declined markedly under drought conditions and was not significantly improved by nitrogen fertilization, indicating a partial and mainly short-term physiological response to nitrogen under water deficit. The application of nitrogen fertilizers, particularly urea and Nitron S, modulated the relative chlorophyll content and selected chlorophyll fluorescence (Fv/Fm, Fv/Fo, PI) and gas-exchange (E, gs, Ci) parameters under drought conditions, mainly shortly after application. However, aboveground dry biomass under drought conditions was not significantly affected by any nitrogen fertilizer. Urea induced the most consistent short-term physiological responses under both irrigation regimes, with effects more pronounced shortly after application, whereas Nitron S showed fertilizer-specific effects under drought stress. Overall, the results demonstrate that foliar nitrogen fertilization can modulate short-term physiological responses of wheat seedlings to drought but does not translate into sustained improvements in Pn or biomass accumulation. In the context of climate change and increasing water scarcity, identifying nitrogen fertilizers that support physiological functioning without overestimating growth benefits has critical implications for sustainable wheat production. Optimizing nitrogen fertilization may, therefore, contribute to improved nutrient management strategies under water-limited conditions. Full article

Accurate classification of precipitation phase (liquid, mixed, or solid) is essential in high mountain environments, where rapid changes in elevation can lead to abrupt phase transitions over short distances, significantly affecting hydro-meteorological, ecological, and socio-economic activities. However, most existing classification schemes have not been evaluated over long periods using real observational data, but mainly through simulations. This study addresses this gap by introducing a new methodology based on X-band polarimetric radar and by validating it against real precipitation events over an extended time period. The machine learning model is trained and tested using a four-year dataset including X-band radar, Micro Rain Radar, disdrometer, and temperature profile data from the Grenoble region (French Alps). To improve the classification accuracy, three temperature profile sources were tested: lapse rates obtained from automatic weather stations, interpolation of the temperature profile from the freezing level detected by the Micro Rain Radar, and temperature profiles from the operational AROME model forecast. Three different phase classification schemes were tested: two existing schemes based on fuzzy-logic, and the new method based on random forest. Results show that the random forest method, trained with radar polarimetric variables, AROME temperature profiles, and target labels derived from Micro Rain Radar observations, achieves the highest accuracy. Despite the overall good classification results, limitations persist in identifying mixed-phase precipitation due to its transitional nature and vertical variability. Feature importance analysis indicates that temperature is the most influential variable in the classification scheme, followed by reflectivity factor measured in the horizontal plane (Z_e) and differential reflectivity (Z_dr). This methodology demonstrates the potential of combining machine learning techniques with multi-instrument observations to improve hydrometeor classification in complex terrain. The approach offers valuable insights for operational forecasting, water resource management, and climate impact assessments in mountainous regions. Full article

The Tibetan Plateau (TP) has experienced pronounced climate change over recent decades, yet the coupled interactions and trade-offs between vegetation dynamics and water yield (WY) remain insufficiently quantified. In this study, we employed the Lund–Potsdam–Jena (LPJ) model to simulate the spatiotemporal evolution of net primary productivity (NPP) and WY across the TP from 1981 to 2060, and applied the Geodetector method to identify the dominant drivers of vegetation dynamics. The results showed that: (1) during 1981–2020, both NPP and WY generally increased across the TP but exhibited distinct spatial patterns, with NPP showing more widespread and pronounced increases than WY; (2) sensitivity experiments revealed that a 2 °C warming substantially increased NPP (+48.79%) but suppressed WY (−17.96%), whereas a 25% increase in precipitation resulted in only a modest rise in NPP (+5.72%) but a sharp increase in WY (+46.72%); (3) the driving factor analysis showed that precipitation, temperature, and WY were the primary controls on NPP, while interaction analysis revealed that their combined effects explained NPP variability more effectively than individual factors; (4) under the Shared Socioeconomic Pathways (SSPs), vegetation–water interactions were projected to shift, with continued greening intensifying water depletion in arid regions, while humid regions were more capable of meeting increased water demand. These findings enhance understanding of vegetation–water coupling across the TP and provide a scientific basis for evaluating future ecohydrological risks under climate change. Full article

The intensifying pressures of urbanization and climate change on coastal zones necessitate a holistic understanding of the interplay between human activity and ecological integrity for sustainable development. However, prevailing methods for assessing coastal vibrancy often overlook direct measures of human presence and fail to quantitatively capture its complex relationship with ecological vulnerability. To address these gaps, this study develops a novel multi-dimensional assessment framework for Coastal Landscape Vibrancy (CLV) and empirically examines its interaction with ecological vulnerability factors in Beihai, China. Moving beyond built-environment-centric approaches, our framework integrates the ‘Crowd’ dimension, directly quantified using Baidu Heat Index data, with the ‘Place’ dimension, characterized by urban features, natural attributes, and visual experience. Principal Component Analysis (PCA) was employed to objectively weight these indicators and construct a composite CLV index. We then applied multiple linear regression to analyze the influence of ecological factors constructed based on the Sensitivity-Resilience-Pressure (SRP) model. The results revealed that vibrancy was highly concentrated in urban cores and exhibited significant spatiotemporal variations. Regression analysis revealed that while ecological quality factors like green coverage (β = 0.236, p < 0.001) positively influenced vibrancy, anthropogenic stressors such as slope (β = −0.457, p < 0.001) and the impervious surface index (β = −0.092, p < 0.001) had significant negative impacts, highlighting a critical trade-off between human activity and ecological conditions. The findings provide a quantitative, evidence-based foundation for spatial planning, demonstrating that sustainable coastal vibrancy is achieved through a balanced integration of human activity and ecological conservation, rather than through unchecked development. This framework offers critical insights for formulating strategies that simultaneously enhance ecological resilience and optimize human service facilities. Full article

Wildfire activity is intensifying under climate change, particularly in temperate East Asia where human-driven ignitions interact with extreme fire-weather conditions. This study examines wildfire risk during the March 2025 large wildfire event in Korea by applying explainable machine-learning models to assess ignition-prone environments and their spatial relationship with socio-environmental features relevant to exposure and management. CatBoost and LightGBM models were used to estimate wildfire susceptibility based on climatic, topographic, vegetation, and anthropogenic predictors, with SHAP analysis employed to interpret variable contributions. Both models showed strong predictive performance (CatBoost AUC = 0.910; LightGBM AUC = 0.907). Temperature, relative humidity, and wind speed emerged as the dominant climatic drivers, with ignition probability increasing under hot (>25 °C), dry (<25%), and windy (>6 m s⁻¹) conditions. Anthropogenic factors—including proximity to graves, mountain trails, forest roads, and contiguous coniferous stands (≥30 ha)—were consistently associated with elevated ignition likelihood, reflecting the role of human accessibility within pine-dominated landscapes. The socio-environmental overlay analysis further indicated that high-susceptibility zones were spatially aligned with arboreta, private commercial forests, and campsites, highlighting areas where ignition-prone environments coincide with active human use and forest management. These results suggest that wildfire risk in Korea is shaped by the spatial concurrence of climatic extremes, fuel continuity, and socio-environmental exposure. By situating explainable susceptibility modeling within an event-conditioned risk perspective, this study provides practical insights for identifying Wildfire Priority Management Areas (WPMAs) and supporting risk-informed prevention, preparedness, and spatial decision-making under ongoing climate change. Full article

Forests face significant pressures from human activities, mainly through deforestation and land-use changes driven by agricultural expansion. This study aims to conduct a literature review to identify and analyze the primary factors that have driven farmers to engage in deforestation and agricultural expansion over the past 25 years. The review followed the methodology proposed by Arksey and O’Malley, with an initial broad search followed by article selection and exclusion. The analysis of the results revealed interacting factors with varying intensities by region, extending to different levels. At the demographic level, factors such as gender, age, household composition, and education play a significant role. At the social level, factors are mainly related to migration, population growth, and the phenomenon of “imitation”. At the economic level, poverty, unemployment, the need for supplementary income, and the growing demand for cash crops are key drivers of agricultural expansion in forests. At the political level, state licensing of deforestation, either as part of poverty reduction strategies or to meet market demand, and the inability to impose sanctions, reinforce deforestation for agricultural cultivation. Finally, at the environmental level, factors such as climate change and soil fertility decline constitute another critical area of pressure on forest ecosystems. Full article

Somatic embryogenesis (SE) represents the most efficient and scalable technology for the mass clonal propagation and genetic improvement of superior conifer genotypes, which is crucial for meeting global wood demand and supporting forest adaptation to climate change. Despite its immense potential, SE in the genus Pinus still faces major limitations, including low initiation frequencies, restricted explant availability, and pronounced genotype dependence. This review synthesizes current knowledge on the factors influencing SE in Pinus species, with a specific focus on two ecologically vital Tertiary relicts endemic to the Balkan Peninsula: Pinus peuce (Macedonian pine) and Pinus heldreichii (Bosnian pine). For these species, traditional vegetative propagation methods are difficult or ineffective, making SE the priority approach for clonal propagation. Detailed studies on these species revealed that SE induction is highly dependent on the explant type and developmental stage. Successful embryogenic tissue formation was achieved only from whole megagametophytes containing immature zygotic embryos, within a narrow developmental window spanning 4–10 weeks post-fertilization. Furthermore, medium composition, particularly reduced ammonium concentration, proved critical for P. heldreichii success. These findings underscore the need for continued, species-specific optimization to overcome current bottlenecks and realize the full potential of SE for the conservation and sustainable clonal forestry of these high-value pines. Full article

Against the backdrop of China’s “Dual Carbon” strategy (peak carbon emissions and carbon neutrality), timber forests serve the dual function of wood supply and carbon sink enhancement. In this study, we employed the Kuenm package in R to optimize Maximum Entropy model (MaxEnt) parameters. Based on the distribution data of six timber tree species in Sichuan Province and 43 environmental factors, we utilized the MaxEnt outputs and ArcGIS 10.8 software to map the geographic distribution of the suitable habitats for these species from the present day into the future (2061–2080) under different climate scenarios (SSP126 and SSP585). Furthermore, we analyzed the migration trend of their future distribution centers. The model optimization significantly improved both fit and predictive performance, with AUC values ranging from 0.8552 to 0.9637 and TSS values ranging from 0.6289 to 0.84, indicating high predictive capability and stability of the model. Analysis of environmental factors, including altitude, precipitation, and temperature, revealed that altitude plays a dominant role in species distribution. Future climate scenario simulations indicated that climate change will significantly alter the distribution of suitable habitats for these timber tree species. The suitable areas for some species contracted, with changes being particularly pronounced under the SSP585 scenario, in which the high-suitability area for Phoebe zhennan is projected to increase from 12,788 km² to 20,004 km², whereas the high-suitability area for Eucalyptus robusta is expected to contract from 8706 km² to 7715 km². The migration distances of suitable habitats for timber tree species in Sichuan range from 5 km to 101 km southwestward under different climate scenarios, and these shifts are statistically significant (p < 0.01), with shifts in elevation and precipitation patterns, reflecting species-specific responses to climate change. This study aims to predict future suitable habitats of timber tree species in Sichuan, providing scientific support for forestry planning, forest quality improvement, and climate risk mitigation. Full article

Temperature and related thermal comfort metrics at a representative 9-member ensemble of airports in Europe are presented using a combination of historical (1985–2014) and future projection (2035–2064) timescales under a variety of forcing scenarios. Data are shown for summer (June–July–August) and the nine sites are further grouped into `oceanic’, `continentally influenced’, and `Mediterranean coastal’ climate types, which ameliorates visualisation and provides more generalised policy-relevant results. Using the Humidex metric, it is shown that some airports in southern Europe may enter a `dangerous’ (>45 C) regime of human discomfort. This would be accompanied by economic impacts related to longer mandated rest periods for ground workers, as well as increased water intake and changes to health and safety training. The coincidence of the 38 C flash point of kerosene jet fuel with perturbed daily maximum temperature occurrence thresholds at some sites will likely also have knock-on effects on safety practices since some sites may experience 70% of future summer days with temperatures exceeding this value. Using an 18 C threshold for defining cooling and heating `degree days’, increases in cooling requirements are projected to be larger than reductions in heating for continental and Mediterranean sites, and heatwave occurrence (3 or more days at or above the 95th historical percentile) may increase by a factor of 10. From a building and infrastructure services perspective, increased temperature variability around larger average values has the potential to reduce safe runway lifetimes and increase structural fatigue in large-span steel terminal buildings. Full article