Search Results (412)

Repeated sowing of winter cereals represents one of the adaptive dryland approaches to make more sustainable the rainfed agriculture activities in southern Kazakhstan. This study conducted a multi-year reconstruction of crop transitions using Sentinel-2 imagery for 2018–2025, based on the combined analysis of Normalized Difference Vegetation Index (NDVI) temporal profiles and the Plowed Land Index (PLI), enabling the creation of a field-level harmonized classification set. The transition “spring crop → winter crop” was used as a formal indicator of repeated winter sowing, from which annual repeat layers and an integrated metric, the R-index, were derived. The results revealed a pronounced spatial concentration of repeated sowing in foothill landscapes, where terrain heterogeneity and locally elevated moisture availability promote the recurrent return of winter cereals. Comparison of NDVI composites for the peak spring biomass period (1–20 May) showed a systematic decline in NDVI with increasing R-index, indicating the cumulative effect of repeated soil exploitation and the sensitivity of winter crops to climatic constraints. Precipitation analysis for 2017–2024 confirmed the strong influence of autumn moisture conditions on repetition phases, particularly in years with extreme rainfall anomalies. These findings demonstrate the importance of integrating multi-year satellite observations with climatic indicators for monitoring the resilience of agricultural systems. The identified patterns highlight the necessity of implementing nature-based solutions, including contour–strip land management and the development of protective shelterbelts, to enhance soil moisture retention and improve the stability of regional agricultural landscapes. Full article

Air conditioners are a critical adaptation measure against heat- and cold-related risks under climate change. However, their electricity use and refrigerant leakage increase greenhouse gas (GHG) emissions. This study developed a data-driven life-cycle assessment (LCA) framework for residential room air conditioners in Japan by integrating large-scale field operation data with life-cycle climate performance (LCCP) modeling. We aggregated 1 min records for approximately 4100 wall-mounted split units and evaluated the 10-year LCCP across nine climate regions. Using the annual operating hours and electricity consumption, we classified the units into four behavioral quadrants and quantified the life-cycle GHG emissions and parameter sensitivities for each. The results show that the use-phase electricity dominated the total emissions, and that even under the same climate and capacity class, the 10-year per-unit emissions differed by roughly a factor of two between the high- and low-load quadrants. The sensitivity analysis identified the heating hours and the setpoint–indoor temperature difference as the most influential drivers, whereas the grid CO₂ intensity, equipment lifetime, and refrigerant assumptions were of secondary importance. By replacing a single assumed use scenario with empirical profiles and behavior-based clusters, the proposed framework improves the representativeness of the LCA for air conditioners. This enabled the design of cluster-specific mitigation strategies. Full article

Soybean is a key global crop for food and oil production, playing a vital role in ensuring food security and supplying plant-based proteins and oils. Accurate information on soybean distribution is essential for yield forecasting, agricultural management, and policymaking. In this study, we developed an Enhanced Chlorophyll Index (NRLI) to improve the separability between soybean and maize—two spectrally similar crops that often confound traditional vegetation indices. The proposed NRLI integrates red-edge, near-infrared, and green spectral information, effectively capturing variations in chlorophyll and canopy water content during key phenological stages, particularly from flowering to pod setting and maturity. Building upon this foundation, we further introduce a pixel-wise compositing strategy based on the peak phase of NRLI to enhance the temporal adaptability and spectral discriminability in crop classification. Unlike conventional approaches that rely on imagery from fixed dates, this strategy dynamically analyzes annual time-series data, enabling phenology-adaptive alignment at the pixel level. Comparative analysis reveals that NRLI consistently outperforms existing vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Greenness and Water Content Composite Index (GWCCI), across representative soybean-producing regions in multiple countries. It improves overall accuracy (OA) by approximately 10–20 percentage points, achieving accuracy rates exceeding 90% in large, contiguous cultivation areas. To further validate the robustness of the proposed index, benchmark comparisons were conducted against the Random Forest (RF) machine learning algorithm. The results demonstrated that the single-index NRLI approach achieved competitive performance, comparable to the multi-feature RF model, with accuracy differences generally within 1–2%. In some regions, NRLI even outperformed RF. This finding highlights NRLI as a computationally efficient alternative to complex machine learning models without compromising mapping precision. This study provides a robust, scalable, and transferable single-index approach for large-scale soybean mapping and monitoring using remote sensing. Full article

Investigating vegetation dynamics and their drivers in ecologically vulnerable regions is essential for evaluating ecological restoration outcomes. This study examined the spatiotemporal evolution of the Normalized Difference Vegetation Index (NDVI) and its influencing factors in Fengning county, the Bashang region from 2001 to 2023 using land use transition matrix, trend analysis, and geographical detector methods. Key findings include the following: (1) Land use transition exhibited a clear phased pattern, shifting from cropland-to-grassland conversion (2001–2010) to grassland-to-forest conversion (2010–2023). (2) The annual mean NDVI increased significantly, showing a southeast–northwest spatial gradient consistent with landforms. The long-term trend followed a sequential “degradation–improvement–consolidation” trajectory. (3) Factor detection identified land use type as the primary driver of vegetation spatial heterogeneity (q = 0.297), highlighting the dominant influence of human activities. (4) Interaction detection demonstrated bivariate enhancement for all factor pairs, with the combination of land use type and precipitation yielding the highest explanatory power (q = 0.440). This underscores that vegetation dynamics are predominantly governed by nonlinear interactions between human-driven land use and climate. The research highlights the effectiveness of ecological restoration policies and offers valuable insights for guiding future ecosystem management in ecologically fragile areas under climate change. Full article

The Eurasian Griffon Vulture (Gyps fulvus) is the most abundant obligate scavenger in Europe. It depends on wild and domestic carcasses whose availability and location are relatively unpredictable in terms of space and time, but also on predictable sources of anthropogenic origin. In this study, satellite and accelerometer data from 10 adult individuals captured in the Basque Country (N Spain) were analysed with the aims of identifying feeding sites and determining the types of resources used. The annual cycle of the species was subdivided into three phases: pre-laying and incubation (December–March), rearing (April–July) and post-rearing (August–November). Our results showed that 64% of trophic resources were consumed in mountain pastures and on extensive or semi-extensive livestock farms, highlighting the importance of these farming systems for the species in the study area. However, 36% of the resources were exploited in more predictable anthropic environments, such as landfills and supplementary feeding stations and, to a much lesser extent, intensive farms. Individual variability was detected in terms of trophic behaviour. On semi-extensive farms, the most consumed carcasses were sheep (48%) and horses (37%), while on intensive farms, it was pigs (81%). During the pre-laying and incubation phase, feeding events detected in landfills were reduced, with vultures focusing on resources close to the colony. We observed that the population studied differed from other Spanish populations in its greater use of trophic resources from extensive and semi-extensive livestock farms, as expected from their spatial-temporal distribution and local availability. Full article

Using cover crops (CCs) following annual crops, together with sustainable nitrogen (N) management, significantly enhances soil carbon (C) storage. However, carbon accumulation in tropical soils is strongly influenced by the respective crop sequences. This study evaluated soil C stocks and fractions in a system incorporating maize–soybean rotation and successive CCs. A randomized block design with split plots was implemented, where main plots consisted of different CCs and the subplots of treatments with and without N fertilization of maize. Chemical fractions of soil organic matter (SOM) were analyzed at depths from 0 to 40 cm, and C stocks down to 100 cm. The SOM fractions responded to N topdressing of maize, varying with soil depth. Soil C stocks during the maize phase were significantly higher than during soybean cultivation (p < 0.05), likely reflecting greater residue inputs from species with elevated C:N ratios. Legume crops following maize intensified C accumulation, emphasizing the importance of N inputs for soil C dynamics. Soil C losses were lowest in the treatments with Raphanus sativus without and Crotalaria juncea with N fertilization. These findings highlight the relevance of combining CCs and N management to optimize C sequestration in tropical agroecosystems. Full article

This study investigates the energy performance of anaerobic digesters in a municipal wastewater treatment plant by integrating empirical data from two tanks located at different distances from the heat source with simulation results. The analysis of measurements enabled the determination of heat transferred to the raw sludge, total heat losses of both systems, and provided input data for an hourly simulation of the thermal balance of the digester envelope. An analytical model was developed, including separate equations for the sludge and biogas phases, considering heat losses caused by mass transfer, conduction, convection, and radiation, as well as solar heat gains. The results show that the temperature difference between sludge and biogas exhibits seasonal variation, with a maximum value of 10.5 K, while the desired operational temperature of sludge fermentation is maintained at 38 °C. The total annual heat balance of the anaerobic digester in 2024 was estimated at 202.8 MWh, with the following structure: aboveground walls 46%, ground-contact partitions 30%, and dome 24%. Model validation using data from one of the digesters indicated a total system energy demand of 1812.0 MWh, distributed as follows: heat transferred to raw sludge 88.6%, heat transfer losses 0.2%, and digester envelope balance 11.2%. Replacing the thermal insulation of the aboveground section could reduce heat losses by 70.7 MWh, decreasing the total energy demand of the system by 3.9%. Comparison with the second digester revealed an energy gap of 166.3 MWh, which may be attributed to higher transmission losses or degradation of the insulation layer. Full article

Ti-6Al-4Zr-3Nb-1.1Mo-1Sn-1V (Ti90) alloy is widely used in marine engineering and oil and gas extraction due to its excellent strength, impact toughness, and corrosion resistance. The corrosion behavior of Ti90 alloy after solution treatment at 750 °C, 900 °C, 940 °C, and 960 °C in 5 M hydrochloric acid (HCl) solution was investigated using open-circuit potential (OCP), potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), static immersion tests, and surface characterization. The results of electrochemical tests indicate that the corrosion resistance of Ti90 alloy increases with rising solid solution temperature. The static immersion tests show that the variation trend of the annual corrosion rate at different solid solution temperatures in 5 M HCl solution is consistent with the electrochemical test results. The corrosion morphology of Ti90 alloy reveals that the α phase is more prone to decomposition than the β phase. The corrosion behavior of Ti90 alloy in 5 M HCl solution is mainly influenced by the volume fraction of the β phase and the size of the α phase. Full article

Seasonality has traditionally shaped the U.S. housing market, with activity peaking in spring-summer and declining in autumn-winter. However, recent disruptions, particularly those following COVID-19, raise questions about shifts in these patterns. This study analyzes housing market data (1991–2024) to examine evolving seasonality and regional heterogeneity. Using Housing Price Index (HPI) data, inventory, and sales data from the Federal Housing Finance Agency and U.S. Census Bureau, seasonal components are extracted via the X-13-ARIMA procedure, and statistical tests assess variations across regions. The results confirm seasonal fluctuations in prices and volumes, with recent shifts toward earlier annual peak (March–April) and amplified seasonal effects. Regional variations align with differences in climate and market structure, while prices and sales volumes exhibit in-phase movement, suggesting thick-market momentum behaviour. These findings highlight key implications for policymakers, realtors and investors navigating post-pandemic market dynamics, offering insights into the timing and interpretation of housing market activities. Full article

Buildings consume energy and are responsible for a significant portion of greenhouse gas emissions in Australia. Increased standards are being set for building thermal performance. Given the rising demand for energy-efficient housing solutions, this work explores the potential application of innovative technologies to enhance the thermal performance. Since modular construction is attracting popularity owing to numerous advantages, including its efficiency and cost-effectiveness, optimising the thermal performance is a way to further improve its popularity, particularly in diverse Australian climates. Smart materials are unique and have desirable properties when subjected to a change in the external environment. Integration of smart insulation materials in prefabricated buildings forecasts a potential to expand the horizon of thermal performance of prefabricated buildings and subsequently lead towards an enhanced energy performance. This work investigates the effects of aerogel, phase change materials (PCMs), and electrochromic glazing. To assess their potential to improve the thermal performance of a modular house, building energy performance simulations were conducted for three different climatic conditions in Australia. Individual implementation of innovative technologies and their combined effects were also quantified. The combination of the three innovative technologies has yielded total annual energy savings of 15.6%, 11.2%, and 6.1% for Melbourne, Perth, and Brisbane, respectively. Full article

Extreme climates pose increasing threats to ecosystems, particularly in ecologically fragile regions such as the Yellow River Basin (YRB). Leaf area index (LAI) reflects vegetation response to climatic stressors, yet spatiotemporal dynamics of such responses under future climate scenarios remain poorly understood. This study examined LAI responses to extreme climatic factors across the YRB from 2025 to 2065, utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs under three Shared Socioeconomic Pathways (SSP) scenarios. Partial least squares regression was performed using historical consistency-validated and future scenario LAI data alongside 26 extreme climate indices to identify extreme climate impacts on vegetation dynamics. Time-lag and cumulative effect analyses using Pearson correlation further quantified the potential impacts of extreme climate on future vegetation dynamics. Results indicate that the regionally averaged LAI in the YRB exhibits a consistent increasing trend under all three SSP scenarios, with linear rates of 0.0016–0.0020 yr⁻¹ and the highest values under SSP5-8.5, accompanied by clear scenario-dependent spatial differences in LAI distribution and vegetation response to extreme climates, particularly in the lag and cumulative effects that depend on local hydro-climatic conditions. Partial least squares regression results identified annual total wet-day precipitation, frost days, growing season length, summer days, and ice days as the dominant extreme climate indices regulating LAI variability. In the arid and semiarid Loess Plateau regions, relatively long lag and cumulative effects imply vegetation vulnerability to delayed or prolonged climatic stress, necessitating enhanced soil and water conservation practices. These findings support region-specific ecological conservation and climate mitigation strategies for the YRB and other ecologically vulnerable watersheds. Full article

The paper discusses the economic and infrastructural challenges preventing the adoption of Electric Vehicles (EVs) in Pakistan. It focuses on key factors such as affordability, consumer preferences, and the overall readiness of the market. Based on a segment-wise comparison, the analysis reveals that four-wheeler EVs carry an initial price premium of 20 to 64 percent over internal combustion engine (ICE) vehicles, with payback periods ranging from 11 to 25 years, placing them out of reach for most middle-income consumers. In contrast, electric two- and three-wheelers—comprising more than 90 percent of registered vehicles—offer a significantly more practical and affordable pathway for mass adoption. These vehicles exhibit minimal upfront cost differences, annual operational savings exceeding PKR 62,000, and short payback periods of just 4 to 6 months, making them highly feasible in the local context. The study adopts a mixed-methods approach using national price data, vehicle registration records, and international case studies from India, Kenya, and Norway. It evaluates financing innovations such as battery leasing, concessional green loans, and carbon-credit-linked microfinance, and outlines a consumer-focused policy framework that emphasizes financial inclusion, decentralized infrastructure development, and phased implementation strategies. By aligning global lessons with Pakistan’s socioeconomic and infrastructural realities, the paper offers a scalable and inclusive roadmap for accelerating EV adoption through targeted, consumer-driven solutions. Full article

Westerlies Asia, which includes arid Central Asia (ACA) and arid West Asia (AWA), is characterized by water vapor transport primarily controlled by the westerlies. Recent studies have identified a dipole pattern in hydroclimate variability between ACA and AWA during both the Holocene and modern period. However, it remains unclear whether such a dipole pattern persisted over the past millennium. Our findings demonstrate that the PMIP4 multi-model simulations reveal a dipole precipitation pattern between arid Central Asia and arid West Asia over the past millennium. During the Little Ice Age (LIA), annual precipitation increased in ACA but decreased in AWA, while the opposite pattern occurred during the Medieval Climate Anomaly (MCA). This dipole precipitation pattern is attributed to seasonal differences: increased spring precipitation in ACA together with decreased summer precipitation in AWA shaped the annual precipitation anomaly during the Little Ice Age, with a reversed regime during the Medieval Climate Anomaly. Mechanistically, a negative North Atlantic Oscillation (NAO) phase during LIA springs shifted the westerly moisture transport southward, enhancing moisture supply to ACA and increasing the precipitation there. In contrast, during LIA summers, a positive NAO phase displaced the westerly northward, reducing moisture advection to AWA, while a strengthened Azores High promoted moisture outflow and descending motion, suppressing precipitation. These findings offer a paleo-hydroclimatic basis for anticipating alternating dry-wet regimes between subregions, which can inform adaptive water allocation strategies, drought and flood preparedness, and long-term infrastructure planning across Westerlies Asia in a warming world. Full article

Based on a cloud water resources (CWR) diagnostic dataset with a 1° × 1° resolution over China from 2000 to 2019, this study systematically analyzes the spatiotemporal patterns of CWR in the complex terrain of the North China Region. The results indicate the following: (1) CWR-related physical quantities exhibit significant seasonal differences, with most being highest in summer and lowest in winter; water vapor convergence is strongest in summer and weakest in autumn, while hydrometeor convergence is smallest in summer and largest in winter; and the water surplus (precipitation minus evaporation) is minimal and negative in spring, indicating severe spring drought. (2) At the annual scale, precipitation is highly correlated with cloud condensation (r > 0.99), and CWR variation is primarily controlled by hydrometeor influx (r > 0.99). (3) The regional annual CWR and precipitation increase at rates of 34.8 mm/10 years and 49.2 mm/10 years, respectively, but exhibit seasonal asynchrony—CWR increases in all four seasons, while precipitation shows a slight decreasing trend in winter. (4) Spatially, CWR show a pattern of “more in the south and north, less in the central region; more in the east, less in the west,” with significant increases in the central–southern parts (southern Shanxi and Hebei, Beijing, and Tianjin). (5) Empirical orthogonal function (EOF) analysis reveals two dominant modes of CWR anomalies: a “region-wide consistent pattern” and a “north–south out-of-phase dipole pattern,” the latter being related to terrain-induced differences in water vapor transport and uplift condensation. The results statistically elucidate the distribution patterns of CWR under the influence of complex topography in NCR, providing a scientific reference for the development and utilization of regional CWR. Full article

Background/Objectives: The medial longitudinal arch (MLA) is initially masked by a fat pad that makes the foot appear flat. In preschool age, this fat pad resorbs, and the arch becomes more defined. The exact age at which the arch attains its final form remains uncertain due to high inter-individual variability and differing assessment methods, which complicates the distinction between physiological development and potential abnormalities. Moreover, commonly used classification terms such as “flat” or “normal” do not adequately reflect the developmental progression and may be misleading in young children. This study aimed to describe the MLA developmental patterns and propose an adjusted classification terminology to improve clinical differentiation between feet undergoing normal developmental changes and cases requiring intervention. Methods: The present study employs both cross-sectional (285 children aged 4.00–8.99 years) and longitudinal (50 children measured annually between ages 4–6) designs. Foot dimensions were assessed using standard anthropometry, and the MLA was assessed via podograms using the Chippaux–Smirak index (CSI). To better reflect the developmental nature of the MLA, the arch was categorized as “formed” and “unformed”. Cross-sectional data were analyzed with ANOVA and visualized using LOESS regression, longitudinal data with linear mixed models, and relationships between CSI and foot dimensions with Spearman’s correlation. Results: MLA development showed significant changes up to age 6, with the most pronounced changes occurring between ages 4 and 5 and slowing thereafter. Children with an unformed arch at age 4 exhibited a steeper developmental trajectory than those with an already advanced arch form. Correlations between arch shape and foot dimensions were statistically significant but weak. No significant between-sex differences were observed. Conclusions: The timing of the most pronounced phase of medial longitudinal arch (MLA) development varies between individuals and is typically completed by 6 years of age, with no sex-dependent differences. Age 6 therefore represents a practical milestone for reliable clinical assessment, since earlier classifications risk misinterpreting normal developmental variation as pathology. Full article