Search Results (624)

The Ordovician strata in Northern Tarim host extensively developed carbonate karst reservoirs that contain abundant hydrocarbon resources. However, owing to extreme burial depths, pronounced heterogeneity, and limited seismic resolution within the Tarim Basin, the diagenetic fluid types and their specific influences on reservoir development remain poorly understood. Consequently, this study integrates core observation, thin-section identification (TSI), cathodoluminescence (CL), scanning electron microscopy (SEM), X-ray diffraction (XRD), stable isotopes (C, O, Sr), trace and rare earth elements (REE), fluid inclusion analysis (FIA), and in situ laser U-Pb dating (U-Pb). This multifaceted petrographic and geochemical approach characterizes the macro- and microscopic geological features of these karst reservoirs. By elucidating the types, timing, and phases of diagenetic fluids, this research evaluates fluid-driven impacts on reservoir quality and establishes a comprehensive genetic model for reservoir evolution. Results identify five distinct tectonic fracturing phases. Phases 1, 2, and 4 involved calcite infilling precipitated from seawater and meteoric freshwater, with fluid inclusion homogenization temperatures of 62–87 °C, 57–91 °C, and 94–126 °C, formed during the Caledonian–Hercynian, Early Hercynian, and Indosinian–Yanshanian periods, respectively. Phase 3 featured hydrothermal dolomite infilling during the Hercynian, with fluid inclusion homogenization temperatures ranging from 128 to 163 °C, whereas Phase 5 remained unfilled during the Himalayan. Constrained by the U–Pb age interval of 445.2–436.5 Ma acquired from vug-filling calcite together with cross-cutting petrographic relationships, multi-stage meteoric freshwater dissolution mainly occurred from Middle Caledonian Episode III (447–443.7 Ma) to the Early Hercynian (460–359 Ma). Reservoirs within the Penglaiba–Lower Yingshan Formations underwent a complex evolution comprising syngenetic-to-early diagenetic pore development, Middle Caledonian–Early Hercynian weathering crust karstification and dedolomitization, and Late Hercynian hydrothermal dissolution-infilling, ultimately resulting in the formation of tectonic-karst composite reservoirs. Full article

Underground gas storage (UGS) facilities serve to balance natural gas networks within a given area. The nature of natural gas network balancing is twofold: long-term (seasonal) during periods of significant gas withdrawal (the cold half-year) and short-term (daily) during periods of peak natural gas demand throughout the day. The first type of balancing has been a standard characteristic for many years, covering increased demand during the winter season. In contrast, the importance of daily balancing is growing alongside the ongoing energy transition, where natural gas-based power generation sources flexibly replace renewable energy sources that are dependent on the time of day or weather conditions. The necessity for increased balancing of energy systems makes them more sensitive to crisis situations. This article presents the key role of UGS as a fundamental resilience factor for European energy systems, particularly in the face of energy crises triggered by geopolitical instability. Conflicts are redefining the role of UGS as a pillar of energy security. This study analyzes how strategic gas reserves mitigate the effects of sudden supply disruptions and price shocks caused by geopolitical factors. It describes impact scenarios of two conflicts: Russia’s invasion on Ukraine and the conflict in the Persian Gulf leading to the closure of the Strait of Hormuz. While UGS is essential for the short-term management of natural gas supply flows, its long-term value lies in providing a “strategic buffer” that allows energy systems to adapt to unforeseen geopolitical conflicts. Integrated storage management is indispensable for maintaining the operational integrity of the European transmission and energy system during periods of heightened instability. The paper also identifies necessary directions for the development of UGS systems. Between 2016 and Q1 2026, the share of eastern gas imports declined from over 40% to 5.2%, while LNG increased to 41.7% of total inflows, confirming the strategic importance of underground gas storage in maintaining energy system resilience. Full article

Reanalysis surface air temperatures (SATs) offer significant advantages for monitoring climate change, but their performance has not been systematically evaluated across diverse perspectives, limiting studies on surface–atmosphere interactions. In this study, observations from approximately 2400 stations across China (2013–2018) were used as a reference to assess seven types of reanalysis SATs (CMA-RA/Land, ERA-Interim, ERA5, ERA5-Land, GLDAS, JRA55, MERRA2) from different perspectives, and the main factors affecting the evaluation results were also discussed. The results indicate that (1) the overall RMSEs of the seven SATs range from 2.06 to 2.85 K, with ERA5 presenting the highest accuracy (RMSE = 2.06 K, R² = 0.97) and JRA55 performing the worst (RMSE = 2.85 K, R² = 0.95); (2) overall, their performances vary across multiple time scales, spatial scales, and weather conditions, exhibiting poor performance in western China, in winter, in high-altitude areas, over forest land, and under cloudy skies; (3) by analyzing the influencing factors, we found that terrain correction and station quality are key sources of assessment errors, while the impact of interpolation methods can be disregarded. These results provide valuable references for the development and improvement of reanalysis data and can assist researchers to select appropriate SAT products in various geographical environment and weather conditions in China. Full article

Metallurgical slags produced in the zinc–lead, copper, iron and steel metallurgical industries are characterized by a variety of technical parameters and varying chemical and mineral compositions, which depend on the type of raw material and the technological process selected and its workflow. These slags are characterized by a high content of valuable elements, including Cu, Pb, Zn, and Fe, which form complex multiphase conglomerates. In the chemical composition of Zn-Pb smelting slags, the contents of the dominant elements, i.e., Fe, Zn, and Pb, range from a few to several dozen %. These elements occur mainly in the form of polyphase oxides and silicates. The chemical composition of Cu smelting slag contains up to a few % Cu and up to several dozen % Fe, with these elements mainly forming silicates and sulphides. Iron and steel metallurgy slag contains up to several dozen % Fe, which occurs mainly in the form of silicates, oxides, and spinels. Due to their phase composition, metallurgical slags stored in landfills can have a negative impact on the environment. The phase composition of slags is one of the main factors determining their behavior in a weathering environment, i.e., their ability to release metals when exposed to atmospheric factors such as precipitation or temperature. On the other hand, such high concentrations of elements in metallurgical slags mean that they become anthropogenic deposits, and the phase composition of the slags determines how the deposited slags are processed. The aim of this article is to present the mineralogical and chemical characteristics of Zn, Pb, Cu and steel metallurgical slags deposited in landfills, along with an assessment of these materials as a source of secondary raw materials. Full article

Most studies have explored the impact of different types of local climate zones (LCZs) on energy consumption, but few have examined climate differences within intra-local climate zones (intra-LCZs) and the impact of cold waves (CW) on energy consumption. This study conducted a 150-day long-term observation of air temperature (Ta) and relative humidity (RH) in six LCZs in Shenyang, a severe cold region, to examine climate differences within intra-LCZs and the influence of CW and the urban heat island (UHI) on energy consumption. The results show that the temperatures and heating energy consumption in 5 LCZ4s exhibited a clear gradient from the urban core to the suburbs. During CW, the differences increased, and the nighttime differences were more pronounced. CW significantly increased residential heating energy consumption, whereas the urban heat island (UHI) reduced it in urban areas. Additionally, there was a clear positive correlation between UHI and the urban-suburban energy consumption difference. Under the combined effects of CW and UHI, the average daily cumulative heating energy consumption in urban areas (CW) was much higher than in suburban areas during non-cold-wave (NCW) periods, increasing by 69.2–85.9%. This study provides empirical evidence for energy conservation and strategies for responding to extreme weather events. Full article

Foundation models for time series forecasting have recently been applied to energy prediction tasks, where they can produce accurate forecasts without task-specific training. This study investigates the impact of two types of covariates, meteorological variables and calendar-based day type indicators, on the forecasting performance of Chronos-2, a state-of-the-art foundation model, in building energy consumption prediction. Using real-world monitoring data from two non-residential buildings at the ENEA Research Centre in Portici, Italy, we systematically evaluate seven configurations combining past and future covariates across multiple observation window lengths (7–28 days). Future meteorological covariates are derived from historical weather forecasts rather than observed weather data, ensuring that the evaluation reflects realistic operational forecasting conditions. The results show that incorporating day type indicators as both past and future covariates consistently delivers the highest forecasting accuracy, reducing CV-RMSE from 14.58% for the covariate-free baseline to 10.41% with a 28-day observation window. A day-stratified analysis further reveals that these improvements are concentrated on regime transition days, for which recent load history alone provides limited information about the operating conditions of the day being forecast. By contrast, meteorological variables, whether obtained from weather forecasts or historical observations, yield only marginal performance gains, suggesting that calendar-driven operational schedules are the primary determinants of energy demand in the buildings considered. These findings provide practical guidance for deploying foundation models in real-world energy building management systems and show that covariate selection is a key determinant of forecasting performance. Full article

This paper studies the impact of weather shocks on the credit risk of bank portfolios in small and rural municipalities in Colombia, which are highly vulnerable to these climate variations. It addresses the relationship between extreme temperature and precipitation events and the increase in the proportion of loans at risk, using data from 2011 to 2023. Extreme climate shocks negatively affect loan portfolio quality in Colombian rural municipalities, especially in microcredits. Credit risk decreases in municipalities with higher per capita incomes. It varies according to the type of loan and the nature of the weather shock. The results show that low temperature shocks increase risk in commercial and consumer loans. In contrast, low-precipitation shocks increase risk in microcredit. The increasing importance of climatic disturbances stresses the need for banks to develop their own models to manage these risks and to deepen analysis that incorporate borrower-specific information and banking policies to protect both financial institutions and borrowers from the impacts of climate change. The integration of sustainable practices and climate education can be key to improving financial resilience in these vulnerable areas. Full article

Forest fires are a recurring disturbance in Mediterranean ecosystems, but they also impact air quality and public health, particularly given recent trends towards increasingly widespread and extreme fires. This study analyzed six large fires that occurred in Sardinia, Italy, between 2009 and 2021, in order to evaluate their impact on ground-level PM₁₀ concentrations and to investigate the influence of fire size, fuel type, and meteorological conditions. The analysis included data on fire perimeters and land cover, meteorological conditions, smoke plume trajectory simulations using HYSPLIT, satellite imagery, and PM₁₀ concentration measurements from the regional air quality monitoring network. The six case studies differed markedly in terms of burned area, vegetation composition, duration, and weather context. The results showed that the extent of the fire is likely not the most significant factor influencing the increase in PM₁₀ observed in the days following the fires. The most pronounced increases in PM₁₀ concentrations were recorded during the Isili and Montiferru fires, which differed in burned area but were similar in terms of fuel composition, dominated by forest and shrubland vegetation. These factors, together with favorable atmospheric conditions for plume transport and particulate matter deposition, likely contributed to the observed increases in PM₁₀, including exceedances of WHO and national daily limit values. By contrast, Bonorva, Ittiri, and Borore showed limited or no clear accumulation of PM₁₀, despite large burned areas in some cases. These findings suggest that the effects of wildfires on air quality in the Mediterranean region can be influenced by several features, such as meteorological conditions, biomass burned, area burned, severity and intensity of fires. Furthermore, the observed exceedance of WHO thresholds highlights the need to integrate public health considerations into wildfire risk management in the Mediterranean basin. Full article

Artificial intelligence (AI) weather models achieve forecast skill comparable to numerical weather prediction at far lower computational cost, yet their reliability for high-impact extremes remains largely uncharacterized. We present an event-based diagnostic evaluation of Aurora, a deterministic AI model, across 16 case studies chosen for physical diversity rather than statistical representativeness, spanning tropical cyclones (TCs), freezes, heatwaves, atmospheric rivers (ARs), and extreme precipitation at lead times from 1 to 21 days. Aurora showed strong short-range (1–7 day) skill: TC track and landfall positions were accurate for well-behaved systems, temperature extremes achieved high spatial agreement, and the atmospheric river structure was reproduced faithfully. This study’s central finding is a pattern–amplitude divergence: beyond 7 days, large-scale circulation patterns remained moderately skillful even as surface amplitudes weakened toward climatological values. Event-specific failures include a severe recurvature forecast failure for Hinnamnor, TC intensity biases, and a pronounced in-sample versus out-of-sample precipitation skill gap that is substantially confounded by event-type differences (large-scale monsoon vs. mesoscale-convective/cutoff-low regimes), so the gap cannot be attributed to training-period recency alone. Across the events examined here, Aurora provides reliable deterministic guidance within 7 days. We recommend deploying Aurora as a rapid ensemble generation and regime-identification tool alongside physics-based numerical weather prediction at short-to-medium range, with its directional intensity and amplitude biases corrected through post-processing before standalone use in operational warnings. Full article

Asthma and seasonal allergic rhinitis are common conditions affecting health, wellbeing, and work place productivity. Current pollen monitoring requires experienced technicians and has a lag of at least 24 h, which limits usefulness for patient management. We evaluated agreement of daily pollen concentrations from an automated real-time sampler, the Swisens Poleno Jupiter, with a traditional Hirst-type trap using technician counting over a single monitoring season in England. We used regression models to assess the impact of weather covariates on differences. Total pollen showed a strong correlation (r = 0.74) but moderate Intraclass Correlation (ICC = 0.52) between devices, due to concentrations (total and taxa level) being higher for the manual than the automated sampler. For individual pollen taxa, strong correlation and good agreement was observed for Pinus, Alnus and Fraxinus throughout the monitoring period. Strong correlation but low/moderate agreement was observed for Poaceae (grass), Betula, Quercus and Taxus/Cupressus. No correlation or agreement was observed for Corylus and Platanus. Temperature explained most of the variability between samplers. We conclude that daily total pollen can be tracked using an automated Poleno, as can grass within its flowering season, but Poleno recognition algorithms developed for mainland Europe need further refinements for UK species. Improving agreement in quantification is of particular importance given that current allergenic thresholds are based on manual readings. Full article

Conventional generation adequacy methods rely on historical load patterns and peak demand scaling assumptions. The integration of EV and EHS introduces temporal characteristics that differ significantly from historical patterns. These new loads show strong weather dependencies, creating correlations with weather-dependent renewable energy sources (RESs) and affecting system reliability. This requires a novel approach to incorporate correlations among multiple load types and RESs into the adequacy assessment framework. This paper presents a hybrid method for developing system load models that combines past performance data for conventional loads with predictive load models for decarbonized loads. The method is assessed on the Roy Billinton Test System (RBTS) and the IEEE Reliability Test System (RTS) to evaluate the reliability impacts of various decarbonized load growth scenarios. Results reveal that load-shape characteristics and temporal correlations significantly influence system adequacy, highlighting the insufficiency of existing load modeling approaches. The integration of decarbonized loads and RES amplifies the impact of the correlation between supply and demand on reliability indices. Various flexibility strategies can be applied to decarbonized loads to enhance system reliability, depending on the temporal alignment between decarbonized loads and RES. Full article

Heat stress is a growing concern in cattle production systems due to the increasing frequency and intensity of extreme weather events driven by climate change. This review synthesizes current knowledge on the multifaceted impacts of heat stress and focuses on nutritional strategies to mitigate its effects on ruminating cattle. A comprehensive literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar. Heat stress adversely affects cattle physiology, behavior, rumen function, and overall productivity, particularly in dairy animals with high metabolic activity. During heat stress episodes, changes in the microbial population have been reported; however, there is no clear consensus, as findings vary widely among studies depending on diet, feed intake, animal type and experimental design. This variability limits the ability to draw general conclusions regarding changes in the rumen microbiome driven by heat stress. In this context, dietary nutritional intervention strategies offer a practical and scalable approach to enhance thermotolerance and maintain performance under heat stress conditions. Key nutritional strategies include modifications in diet composition to reduce metabolic heat production, with some approaches carrying potential risks to animal health, e.g., increasing dietary energy density through concentrates while minimizing forage content. Supplementation with rumen-protected nutrients like amino acids, vitamins, and minerals can be used to support immune function, antioxidant capacity, and metabolic stability. Polyphenols and betaine contribute to oxidative stress reduction and gut integrity, while probiotics may be used to improve rumen fermentation and nutrient utilization. Sensor technologies, including rumen boluses and wearable devices, offer the potential to monitor physiological responses to heat stress in real time and offer opportunities for precision feeding and early intervention. Most published studies only cover short periods of heat stress, and there is a lack of in vitro models simulating rumen hyperthermia. In parallel, future research should therefore prioritize longitudinal, in vivo trials that integrate physiological, metabolic, and microbial responses to understand the long term and systemic effect of heat stress. In addition, controlled trials in commercial settings are necessary to prove the transferability of results to commercial herds. A multidisciplinary approach combining nutritional, environmental, and technological strategies is likely to play an important role in safeguarding cattle welfare and productivity in a warming climate. Full article

The carried-out microfield model research was aimed at identifying patterns in the dynamics of soil CO₂ effluxes depending on the locally occurring hydrothermal regimes of regenerated lawn ecosystems on peat–sand substrates with different peat contents. Monitoring was carried out every ten days from 21 April 2019 to 30 October 2019 and included measurements of soil and air temperature, soil moisture, and CO₂ efflux every 3 h during the day. The weather conditions of the 2019 growing season in Moscow, with air temperature close to the annual average and increased precipitation, made it possible to clarify quantitative patterns of the temperature influence on CO₂ efflux from lawn soils in case of their pronounced dynamics without real soil moisture deficit. To study relationships between CO₂ efflux and soil and air temperatures, three empirical CO₂ efflux models (Exponential, Raich–Hashimoto and Lloyd–Taylor) were used with comparative assessment of their results. The conducted investigation showed that both peat content, local hydrothermal regime, and type of vegetation cover play a significant role in efflux modulation, with the temperature factor dominating on both seasonal (72% impact) and intraday (51–94% impact) scales. The lawn substrate factor accounts for up to 10% of CO₂ efflux variability on the intraday scale. The lawn vegetation cover (with the lower and higher diversity) significantly affects the soil hydrothermal regime depending on the peat content (a higher impact with a lower peat content due to the soil pH difference). The denser vegetation reduces the soil temperature, providing better protection, and at the same time reduces soil moisture by transpiration, which provides the combined effect on the CO₂ efflux reduction (up to 1 g CO₂ m⁻² day⁻¹ reduction for the lower-pH soils). Full article

A significant low-level wind shear event that occurred at Xining Caojiabu Airport on 10 April 2019 was comprehensively analyzed. The analysis utilized data from the airport’s ground automatic weather observation system (AWOS), lidar detection data, ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), and ETOPO2v2 topographic data from the National Oceanic and Atmospheric Administration (NOAA). The analysis focused on the evolution of meteorological elements during the wind shear, lidar characteristics, large-scale environmental features, and the main influencing systems. The results indicate that this was a typical “easterly backflow” low-level wind shear event, representing a special type of cold-frontal low-level wind shear, with the wind shear occurring in the prefrontal area as the cold front approached the airport. During the passage of the wind shear, the AWOS stations at Runways 29 and 11 sequentially recorded pressure increases and temperature decreases, reflecting the gradual intrusion of cold air from east to west into the airport. Lidar Plan Position Indicator (PPI), Range-Height Indicator (RHI), and Doppler Beam Swinging (DBS) modes revealed that the wind shear appeared as convergence between southeast and northwest winds, with an impact on the airport that moved from east to west and from bottom to top, belonging to a meso-γ-scale system. The evolution of the sea-level pressure field, pressure-change field, frontogenesis function, and temperature advection indicated that cold air first moved eastward along the Hexi Corridor and then poured back into the Huangshui River Valley through the topographic gap at the eastern end of the Qilian Mountains. The easterly wind converged with the westerly wind, and the topographic funneling effect strengthened the easterly backflow and promoted its westward advance, leading to the occurrence of low-level wind shear. The large-scale influencing systems of this event included a transverse trough over Mongolia at 500 hPa, an upper-level frontal zone, an upper-level jet stream, and a surface cold front. The favorable conditions for the formation of this “easterly backflow” low-level wind shear were the strengthening of baroclinicity in the upper-level frontal zone, intensified cold advection, momentum downward transport induced by the upper-level jet and ageostrophic secondary circulation, and the easterly backflow and wind speed enhancement caused by the special topography. Full article

Groundwater serves as a vital source of domestic and agricultural water in rural areas of the Songnen Plain. Its chemical composition and water quality directly impact public health and regional sustainable development, making them subjects of significant concern. This study employed a comprehensive analytical framework, integrating Piper trilinear diagrams, ionic ratio analysis, the Water Quality Index (WQI), and the Human Health Risk Assessment (HHRA) model, to preliminarily evaluate groundwater conditions in a rural township of the Songnen Plain. The multi-method approach was designed to provide scientific insights for groundwater pollution prevention and remediation strategies in the region. Results indicate that the predominant groundwater chemical type in the study area is HCO₃-Ca. The hydrochemical process is primarily controlled by weathering and dissolution of silicate and carbonate minerals, accompanied by cation exchange. The WQI ranged from 84.78 to 192.82, with an average of 132.68, indicating overall moderate water quality. Fe and Mn are significant factors affecting water quality. The potential non-carcinogenic risks posed by groundwater to children, females, and males (0.988, 0.701, 0.534) and carcinogenic risks (1.77 × 10⁻⁵, 6.27 × 10⁻⁵, 4.81 × 10⁻⁵) are both below the USEPA recommended threshold (1.0, 1 × 10⁻⁴), indicating that the health risks were generally acceptable, though the HI for children approached the threshold. The results underscore the need for targeted mitigation of elevated Fe/Mn concentration (e.g., via aeration biofilters) while highlighting the region’s low health risks under current conditions. This work provides a template for integrating geochemical and health risk paradigms in groundwater management. Full article