Search Results (8,658)

This study proposes an integrated analytical framework (IAF) as a tool to simultaneously assess vulnerable social groups within their administrative context. This study hypothesizes that analyzing vulnerable groups through socio-spatial delineation reveals subnational disparities and sub-regional heterogeneity in energy poverty (EP) indicators, associated with additional context-sensitive environmental consequences of energy use. Using Hungarian deprived rural settlements (DRSs) (n = 300) as an example, mixed methods were applied to examine national–regional disparities, intra-regional variations, and the environmental implications of extreme household energy use practices. Results show that both socio-economic indicators and building energy efficiency, and energy-use profiles, fall short of national indicator performance. The sample outlined by the IAF performed homogeneously regarding socio-economic circumstances and showed mild differences in housing quality and energy access. These results indicate not structural differences but variation in underlying regional drivers, highlighting the region-specific manifestation of EP. The energy-use-related environmental assessment was performed using a parametrized building-stock model and the two most extreme energy-use scenarios for households relying on solid fuels. The results suggest that the use of substitute fuels substantially increases the combined emissions of CO₂, CO, PM, NOx, and SOx by up to 32 percentage points. Although limitations constrain the reporting of empirically representative results, findings underscore the potential policy relevance of DRSs in national climate objectives. Full article

Arid Central Asia (ACA) is a major source of atmospheric dust in the Northern Hemisphere; however, the evolutionary models and driving mechanisms of Holocene aeolian activity in this region remain debated. Based on 13 reliable AMS ¹⁴C dates from the Sayram Lake SLM2009 sediment core, this study reconstructs the Holocene sequence in aeolian activity through end-member modeling analysis (EMMA). It evaluates its relationship with regional atmospheric circulation. Four end-members were identified from base to top: EM1, with a modal grain size of 7.58 μm, represents low-energy suspension deposition; EM2 (26.30 μm) reflects lacustrine hydrodynamic processes; while EM3 (52.48 μm) and EM4 (416.86 μm) serve as proxies for regional aeolian activity. The results indicate that aeolian activity was relatively strong during the early Holocene (reaching peaks at 11.7–11.2 and 9.2–8.1 cal ka BP), significantly intensified during the mid-Holocene (7.3–5.3 cal ka BP), and gradually weakened in the late Holocene (since 4.0 cal ka BP). Comparison of the aeolian record from Lake Sayram with Greenland ice cores, North Atlantic ice-rafted debris events, and the GISP2 K⁺ record indicates that variations in aeolian activity in arid Central Asia are closely linked to the Northern Hemisphere climate system. We propose that these variations were primarily modulated by large-scale atmospheric circulation, driven by the synergistic interaction between the Siberian High and the mid-latitude westerlies. Full article

Disaster records retrieved from historical diaries are valuable for examining past seasonal variations in disaster occurrence. We extracted 154 fire and 103 flood records between 1807 and 1838 from the Zayu-Nichiroku (the Kakuson Diaries), written by KANEKO Kakuson in Kanazawa, Japan. We analyzed the seasonal probability of these events using the Poisson distribution. The probability of fire peaked between March and June, while that of floods was highest in June, July, and September. These trends align well with the current climate in Kanazawa, where low humidity and strong winds elevate fire risk, while prolonged rainfall and localized heavy precipitation during the rainy and typhoon seasons increase flood risk. However, extracting disaster records from historical diaries involves uncertainties stemming from omitted entries, the loss of archival material, ambiguous descriptions, unique local recording bias, and short-term missing records. To reduce these uncertainties, we should employ an interdisciplinary approach utilizing multiple historical sources and probabilistic analyses of disaster occurrence. Full article

Conventional Heating, Ventilation, and Air Conditioning (HVAC) control systems primarily rely on environmental and physiological parameters, largely ignoring the critical influence of psychological states on thermal comfort. Overlooking this factor often leads to suboptimal occupant satisfaction, energy inefficiency and thus carbon dioxide (CO₂) emissions. To this aim, this study introduces a novel mood-adaptive HVAC control system integrating psychological feedback to decrease CO₂ emissions in office buildings by reducing energy consumption and optimizing comfort. A total of 7000 thermal facial measurement records and high-resolution camera images were collected across seven mood state conditions using video stimuli and the Profile of Mood States (POMS) questionnaire to evaluate mood variations. A dual artificial intelligence system was developed: a Convolutional Neural Network (CNN) for analyzing facial expressions and an Artificial Neural Network (ANN) for processing facial temperatures via thermal imaging. These models collectively predict occupant mood in real-time, and a custom-designed wearable necklace interface transmits this data to dynamically adjust HVAC setpoints. To evaluate system performance, energy consumption was directly measured in real-life operations using an energy analyzer, without relying on simulations. Results indicate that this prototype personalized mood-driven system has the potential to enhance perceived thermal comfort while achieving up to a 20% reduction in carbon emissions compared to conventional systems. This human-centered approach significantly advances intelligent building management and climate change mitigation. Full article

This study investigates a typical valley city, Lanzhou, China, to reveal the nonlinear relationships and interaction mechanisms between gray–green space morphology and seasonal diurnal land surface temperature (LST) using multi-source remote sensing and land use data. A comprehensive morphological indicator system encompassing scale, complexity, connectivity, and structural integrity was constructed through landscape metric screening and the CRITIC objective weighting method, combined with the XGBoost-SHAP explainable machine learning framework. The findings highlight that: (1) Gray–green space impacts on LST exhibit significant seasonal and diurnal variations—daytime LST is predominantly governed by gray space morphology (e.g., fragmentation degree), while nighttime LST is driven by green space morphology (e.g., coverage intensity). (2) Key indicators demonstrate pronounced nonlinear and threshold characteristics: the cooling effect of green space coverage intensity (GCI) saturates beyond 0.25; gray space morphological structure factor (GRMSF) demonstrates cooling potential when exceeding 0.25, mitigating its warming effect. (3) Significant synergistic interaction effects exist between gray and green spaces. Interaction analysis reveals that “high green coverage with low structural connectivity of gray space” produces optimal synergistic cooling effects, representing the most effective spatial configuration for nighttime LST mitigation. This study deepens theoretical and methodological understanding of the complex relationships between spatial morphology and thermal environments, providing quantified, temporally differentiated spatial optimization guidance for climate-adaptive planning in valley cities. Full article

Coral reefs are biodiversity hotspots increasingly threatened by climate-induced bleaching, yet profiling the coral holobiont—the host and its associated microbiota—remains technically challenging due to high host-DNA contamination (often >95%) and the lack of comprehensive reference databases. Here, we present holo-2bRAD, a type IIB restriction site-associated DNA sequencing approach. This method, strategically integrated with a meticulously curated hologenome database (comprising 404,946 microbial genomes and 56 coral-derived metagenome-assembled genomes), effectively overcomes overwhelming host contamination (~99%). We demonstrate its exceptional species specificity (99.92%) in profiling Galaxea fascicularis (Linnaeus, 1767; Order Scleractinia, Family Euphylliidae) holobionts across bleaching severities, thereby validating its technical feasibility. Leveraging this high-resolution tool, our hologenome analysis revealed significant restructuring of coral-associated microbiota during bleaching, where microbial shifts (e.g., depletion of beneficial Thermoanaerobacterium thermosaccharolyticum and enrichment of stress-responsive bacteria) correlated more strongly with bleaching phenotypes than host genetic variation. By providing cost-effective, multi-domain hologenome profiling at unprecedented resolution, holo-2bRAD offers a practical tool for investigating holobiont dynamics and developing microbiome-informed coral conservation strategies. Full article

Improving the energy efficiency of historic field stone masonry buildings often requires internal insulation, as external insulation is frequently restricted by heritage and architectural constraints. Internal insulation, however, alters the hygrothermal behavior of massive masonry walls and may increase moisture-related risks. This study assesses the hygrothermal performance of an internally insulated historic field stone masonry wall under past and projected future climatic conditions using long-term transient simulations. Coupled heat and moisture transfer simulations were performed with the DELPHIN software for an uninsulated reference wall and an internally insulated configuration. The analyses accounted for wind-driven rain, masonry heterogeneity, and variations in inner core composition. Past conditions were represented by a continuous 20-year measured climate dataset, while future conditions were evaluated using regional late-century climate projections (RCP2.6 and RCP8.5). Hygrothermal performance was evaluated based on moisture mass density, freeze–thaw exposure, and mold-relevant temperature–relative humidity conditions at predefined evaluation points within the wall. The results show that moisture accumulation develops gradually and cannot be reliably captured by short simulation periods. Internal insulation redistributes moisture-related risks within the wall rather than fundamentally altering the seasonal moisture regime. Freeze–thaw exposure occurs under all investigated climates, while mold-relevant humidity conditions persist at interior-adjacent locations. The findings demonstrate the importance of multi-year hygrothermal analyses when assessing moisture-related risks in internally insulated historic masonry walls. Full article

Soil organic carbon (SOC) stocks in cacao agroecosystems are characterized by accumulating large amounts. They depend on the balance between organic matter inputs (plant residues, roots) and losses (decomposition, erosion), being closely related to climatic conditions, soil nature, vegetation type, topography, and land management practices. The objective of this study was to quantify SOC stocks (0–30 cm) and assess key soil fertility indicators across 107 georeferenced sampling locations in cacao production systems of Guamal (Meta, Colombian Llanos Piedmont). Soil pH varies between extremely acidic and moderately acidic (3.8–6.0; mean 4.57), while available P (Bray II) and exchangeable bases showed low concentrations. Organic carbon concentration averaged 1.18% and bulk density averaged 1.17 g cm⁻³. SOC stocks averaged 41.10 Mg C ha⁻¹, ranging from 7.49 to 81.55 Mg C ha⁻¹, evidencing marked spatial contrasts in carbon storage. Spearman correlations highlighted coupled soil chemical controls, including positive associations of pH with Ca²⁺ and P availability and strong negative associations of pH and P with exchangeable Al³⁺, consistent with acidity-driven fertility constraints. Principal component analysis (PCA) further identified a dominant fertility gradient structured by pH, P availability, and Ca²⁺, and a second axis related to organic carbon and cation retention. Spatial modeling using inverse distance weighting (IDW) in ArcGIS supported the visualization of SOC stock variability across the study area. Overall, the results indicate that SOC stocks in these predominantly sandy soils are strongly influenced by acidity-related constraints and heterogeneous nutrient status, underscoring the need for site-specific management to jointly enhance soil fertility and climate-mitigation potential in cacao systems. Therefore, it would be advisable in the future to address the study of differential variations in soil C storage related to chemical fertilizer application rates, especially in the long term. Full article

Heilongjiang Province is China’s largest commercial grain-producing base, meaning that understanding the stability and climatic sensitivity of its major crops are essential for national food security. Using statistical and meteorological data from 2004 to 2023, this study systematically examines the impacts of climate change on cropping structure, yield dynamics, and production stability. The results show that over two decades the total grain crops-sown area and the yield per unit area increased by 79.4% and 38.4%, respectively. The cropping pattern shifted from a diversified structure to a maize-soybean-rice dominated pattern, while the wheat area declined by 92.2%. Additionally, mean and extreme yield fluctuations decreased by 52.3% and 42%, respectively. Rice exhibited the highest yield stability, whereas maize and soybeans experienced marked reductions in interannual variability. Spatial analysis identified Harbin and Daqing as hotspots for yield stability risk, characterized by higher yield standard deviations relative to other cities in the province. Climate elasticity analysis revealed that soybeans and rice were sensitive to warming, while wheat responded positively to increased rainfall. Overall, Heilongjiang’s grain production system has expanded and become more stable at the provincial scale, but it remains vulnerable to emerging climatic risks. Strengthening climate adaptation through crop-specific management, varietal improvement, and field water regulation is vital for enhancing system resilience and sustaining food production in cold-region agroecosystems. Full article

Soil organic carbon (SOC) is essential for ecosystem stability and long-term carbon storage in alpine grasslands, yet the relative importance and interactions of hydrothermal and biotic controls remain poorly understood at regional scales. In this study, we quantified surface SOC (0–20 cm) across the Yellow River Source Region (YRSR) on the northeastern Tibetan Plateau, a climate-sensitive alpine headwater system characterized by strong hydrothermal gradients and freeze–thaw dynamics. Field-based SOC measurements were integrated with multi-source remote sensing and reanalysis data that describe thermal conditions, moisture processes, vegetation productivity, soil properties, topography, and human influence. A two-step screening approach was applied using Boruta and variance inflation factor filtering, followed by modeling with random forest. The model outputs were interpreted using Shapley Additive Explanations (SHAP). SOC displayed significant spatial heterogeneity across the region. Vegetation productivity, moisture availability, and thermal conditions were identified as the dominant nonlinear drivers of SOC variation. Moisture availability emerged as a central regulator of SOC, affecting it both directly and indirectly through vegetation productivity and thermal conditions. These findings underscore the importance of hydrothermal stability in sustaining soil carbon stocks and provide a quantitative basis for adaptive grassland management under a warming climate. Full article

Since the start of the U.S. Conservation Reserve Program (CRP) in 1985, producers have enrolled environmentally sensitive land in exchange for annual rental payments, supporting multiple dimensions of sustainability through reduced soil loss, improved water quality, enhanced habitat provision, and strengthened climate resilience through land stewardship. Recent declines in enrollment raise concerns about whether participation remains spatially aligned with local environmental need and economic incentives. This study examines regional variation in CRP participation and its sustainability implications by identifying spatial patterns in participation and key drivers using exploratory spatial data analysis (ESDA). We analyze county-level CRP participation rates alongside three key drivers (CRP rental rates, soil erosion risk on cultivated cropland, and farm income) and assess spatial dependence using Global Moran’s I, univariate Local Indicators of Spatial Association (LISA), and bivariate LISA (BiLISA). Framed as an assessment of agri-environmental policy effectiveness for sustainable land management, the framework is applied to counties in the U.S. Midwest, a region with historically substantial CRP enrollment. Global Moran’s I statistics indicate significant positive spatial autocorrelation for CRP participation (I = 0.491), CRP rental rates (I = 0.892), and soil erosion (I = 0.503), confirming pronounced regional clustering across Midwestern counties. LISA results further show that more than 60% of counties fall into high–high (HH) or low–low (LL) clusters for CRP rental rates, while BiLISA results indicate that 22.9% of counties form HH clusters between CRP participation and soil erosion, suggesting only partial alignment between CRP participation and the environmental need. These findings indicate that the environmental benefits of CRP may vary across the region depending on where participation occurs. Overall, the findings support a shift toward a data-driven, spatially explicit CRP strategy that integrates environmental risk, economic incentives, and regional context to strengthen sustainability outcomes and enhance environmental effectiveness, economic efficiency, and the spatial equity of conservation benefits in the United States. Full article

Forest soil conservation is pivotal for controlling soil erosion and ensuring ecological security. Taking the Qilian Mountains Area in China as the research region, this study used ArcMap 10.8 software to process data for six prefecture-level cities in the area from 2008 to 2023. The Revised Universal Soil Loss Equation (RUSLE) model was applied to quantify the forest soil conservation amount and evaluate its ecosystem service value (ESV). Their spatiotemporal variations and dynamic evolution patterns were analyzed, alongside the influence of soil organic matter (OM) and nitrogen (N), phosphorus (P), and potassium (K) contents. The results showed that the average contents of OM, N, P and K in the forest soils of the Qilian Mountains Area were 24.22 g·kg⁻¹, 1.54 g·kg⁻¹, 0.70 g·kg⁻¹, and 19.96 g·kg⁻¹, respectively, with significant regional heterogeneity. Haibei Tibetan Autonomous Prefecture (HBTAP) had the highest while Jinchang City (JC) had the lowest. From 2008 to 2023, the average annual forest soil conservation amount and its ESV of the region were 1.749 × 10⁹ tons and 2.0444 × 10¹⁰ yuan, respectively, both showing a fluctuating trend of initial increase followed by a decrease. Spatially, HBTAP ranked first in average annual forest soil conservation amount per unit area and ESV. Jiuquan City (JQ) had the lowest forest soil conservation amount per unit area, and JC the lowest ESV. Forest soil conservation and its ESV in the region were affected by the contents of soil nutrients (OM and N, P, K elements), vegetation types and quality, topography, climate, and human activities (including ecological governance), which collectively intensified the spatiotemporal heterogeneity. These findings provide a theoretical basis for precise regional ecological protection and differentiated restoration strategies in arid regions. Full article

Ranked 30th globally in dryness, South Africa faces severe challenges in ensuring fodder security, which is worsened by climate change impacts on agriculture. However, there is still limited knowledge about optimising fodder radish cultivation under shifting climatic conditions. This study investigated the effects of planting dates (December to March), cultivars (Nooitgedacht, Line 2 and Endurance) and seasons (2020/21 and 2021/22) on growth, yield, and crude protein (CP) and mineral concentrations under rainfed conditions. Seasonal variation significantly (p < 0.05) influenced emergence, relative growth, and flowering across planting dates. Fresh tuber yield was highest when Nooitgedacht was planted in December (2052 and 2102 kg ha⁻¹). In contrast, January planting enhanced aboveground biomass and crude protein (CP) yield, with Endurance recording the highest biomass (1260 and 1157.95 kg ha⁻¹ DM) and tuber CP yield (19.2 and 18 kg ha⁻¹). December planting favoured tuber production, whereas January planting optimised biomass, CP yield, and persistence. Planting date and cultivar significantly affected leaf and tuber mineral concentrations. December–January plantings generally enhanced leaf P, K, and Zn concentrations. Endurance and Nooitgedacht accumulated higher micronutrients than Line 2, particularly under early planting. The late flowering of Endurance extended the grazing period, aligning with late-winter forage demand under rainfed conditions. Overall, this study offers practical guidance for improving the quantity and quality of fodder radish in diverse agricultural settings. Future work should evaluate these cultivars across more sites to confirm performance stability under variable rainfall patterns. Full article

Harsh environments and climate change hamper industrial hemp productivity. Under stress conditions, uniform germination and vigorous seedlings are key to sustaining crop establishment and performance. Trichoderma spp. are beneficial micromycetes, able to colonize plant roots and promote plant development even under abiotic stress conditions. Thus, the seed treatment with specifically selected Trichoderma isolates could be a useful strategy to enhance hemp seed germination and plantlet growth. In this view, a preliminary screening was performed with ‘Eletta campana’ cv. Nine out of 20 Trichoderma isolates enhanced the radicle growth (+66–111%); most of them resulted in good root colonization, but only four isolates significantly enhanced the shoot DW (+18–22%). Three isolates were selected for a pot experiment, compared to T. afroharzianum T22, to evaluate the effect on plant growth, root architecture, accumulation of photosynthetic pigments and stress-related compounds, and variation in antioxidant activity in 20-day-old plantlets. T. afroharzianum OR4 significantly promoted plantlet growth (+9% shoot DW and +11% leaf DW). The seed treatment had a low impact on the other variables studied, except in the case of foliar proline content, a marker of stress tolerance, that was greatly increased with T. afroharzianum T22 and T. atrobrunneum X44 (+32% and +17% DW). Full article

Due to the influence of multiple factors such as the physical and chemical properties of the atmosphere, the limitations of data sources, and the assumptions of inversion methods, there are many difficulties in inverting the concentration distribution with high temporal and spatial resolution over a large area near the ground. In this study, the GEOS-Chem chemical transport model was adopted. Through dynamic constraints of emission sources, meteorological fields, and chemical mechanisms, combined with the optimization output of radial basis functions, a 1 km × 1 km hourly near-surface nitrogen dioxide concentration distribution dataset in China from 2015 to 2024 was generated. Based on the analysis of spatial differences and temporal fluctuations, the concentration changes of nitrogen dioxide are closely related to human activities, climate change, and seasonal variations. Thanks to China’s implementation of a large number of proactive pollution control measures, the average annual concentration of nitrogen dioxide has dropped from 19.7 μg/m³ in 2015 to 14.1 μg/m³ in 2024, with a cumulative reduction of 28.43%. The phenomenon of the one-hour average concentration exceeding the limit of 200 μg/m³ has been basically eliminated across the country. Full article