Search Results (3,034)

Against the backdrop of global climate warming and rapid urbanization, urban thermal environments exhibit strong spatiotemporal heterogeneity and diurnal contrasts. Based on the high-resolution, seamless land surface temperature dataset (GSHTD), this study systematically evaluates the evolution of extreme urban thermal environments across 107 cities in the Yangtze River Basin (YRB) from 2001 to 2020. Urban cores were delineated using high-density impervious surface area (ISA ≥ 50%), and rural background temperatures were elevation-corrected. To quantify the asynchrony between extreme heat intensification and seasonal background warming, we propose “Risk Amplification Index (Ri)”. The results reveal that: (1) The surface urban heat island intensity (SUHII) intensified across the entire basin, with daytime increases being significantly stronger and more spatially consistent than nighttime ones. (2) The intra-annual SUHII cycle exhibits a unimodal pattern peaking in August, with widening inter-city disparities during the warm season. (3) The intensification of extreme heat is often asynchronous with background warming. Combined with land-use change intensity (ΔISA), our analysis indicates that small and medium-sized cities undergoing rapid expansion (high ΔISA) exhibit a stronger heat-risk amplification effect (higher Ri), whereas mature megacities (high total ISA but low ΔISA) show relatively synchronous thermal evolution. The results suggest that an ISA density of around 70% may act as a threshold beyond which extreme-heat amplification is more likely to intensify. These findings suggest that future heat-risk governance should be time- and region-specific, shifting the focus of climate-adaptive planning from solely megacities to mitigating extreme-heat risk amplification during the rapid urbanization of small and medium-sized cities. Full article

The Tibetan Plateau (TP) atmospheric heat source crucially modulates East Asian summer monsoon precipitation, yet its synergy with upstream oceanic signals remains elusive. Using observations (1971–2020) and CMIP6 simulations, we investigate mechanisms coupling the summer TP heating and precipitation over the Middle and Lower Yangtze River (MLYR). SVD analysis reveals a robust positive coupling between them. Mechanistically, TP heating triggers a quasi-stationary Rossby wave train, inducing a “saddle-like” circulation that drives intense MLYR moisture convergence (contributing >90% to precipitation changes). Crucially, we re-examine the upstream oceanic precursor to propose a “dual-pathway superposition” framework. Contrary to the assumed linear causal chain, four-quadrant analysis reveals the spring Indian Ocean Basin Warming (IOBW) and summer TP heating are largely independent drivers (R = 0.24). While IOBW thermodynamically excites an Anomalous Anticyclone supplying abundant MLYR moisture, it lacks robust control over TP heating, which is dominated by internal atmospheric dynamics. However, our findings reveal a critical non-linear synergy: extreme MLYR rainfall strictly requires the coincidental phase overlap of these independent pathways (strong dynamic lifting coupled with oceanic moisture). CMIP6 simulations corroborate this independence, further emphasizing that extreme MLYR rainfall results from phase superposition rather than a single causal chain. Full article

Wetlands are the largest natural source of atmospheric methane (CH₄), and their emissions are projected to increase during the 21st century in response to climate change. However, how extreme climate events such as extreme heat, extreme precipitation, and their compound occurrences modulate future wetland methane emissions, remains poorly constrained. Here, we quantify the impacts of extreme temperature, precipitation, and compound hot–wet events on global wetland methane emissions (eCH₄) using simulations from the dynamic global vegetation model LPJ-wsl driven by four CMIP5 climate models under a high-emission scenario (RCP8.5) for the period 2006–2099. Our results show that extreme heat events intensify and become substantially more frequent, with global occurrence increasing by more than 303% by the end of the century. Correspondingly, their contribution to global wetland methane emissions rises from ~26–28% in 2006 to ~73–83% by 2099, making extreme heat the dominant driver of future eCH₄ increases. Extreme precipitation events exhibit relatively modest changes in frequency and mixed intensity. In contrast, compound hot–wet events, despite their low baseline frequency, increase by more than 600% and are associated with disproportionately strong methane responses, driven by the combined effects of elevated temperatures and enhanced anaerobic conditions. Across all event types, tropical wetlands account for 75–90% of global methane emissions, while contributions from mid-latitudes increase modestly and high-latitude contributions remain comparatively small. These findings highlight the emerging importance of climate extremes—particularly extreme heat and compound hot–wet events—in shaping future wetland methane emissions. Explicit consideration of extreme-event dynamics is therefore essential for improving projections of methane–climate feedback under continued global warming. Full article

Supramolecular oleogel lubricants construct a three-dimensional network structure within base oils through gelator-mediated non-covalent interactions, such as hydrogen bonding, van der Waals forces, and π–π stacking. These materials demonstrate unique advantages in mitigating issues inherent to traditional lubricants, including leakage, volatility, creep, and poor heat dissipation. Focusing on structural design and performance regulation, this review systematically summarizes the current development of supramolecular oleogel lubricants in the fields of green lubrication, extreme operating conditions, and nanocomposite lubrication. Specifically, it outlines the structure-property relationships between gelators and base oils in green lubrication systems, and elucidates the applications in radiation-resistant, high-load-bearing, and intelligently responsive lubrication. Strategies for utilizing nanocomposite supramolecular oleogels to resolve nanomaterial dispersion challenges are discussed, and the latest advancements in engineering applications are illustrated. By summarizing the development of supramolecular oleogel materials, this work can provide theoretical references for the future design and preparation of these lubricants. Full article

Sol–gel processing provides an unusually controllable route to nanoporous solids, making silica aerogels the leading reference systems for extremely low thermal conductivity due to their high porosity, nanoscale pore sizes, and tunable solid frameworks. Under near-ambient conditions, thermal transport is multi-scale and multiphase, arising primarily from coupled solid conduction through the skeletal network and gas conduction within the pore space. Accordingly, aerogel design has emphasized suppressing solid-phase transport by reducing network connectivity, increasing tortuosity, and enhancing boundary scattering, while also limiting gaseous conduction through the control of pore size and gas pressure. This critical review provides an integrated overview of these mechanisms and the theory-to-experiment toolbox used to quantify the separate and combined contributions of the solid and gas phases to the effective thermal conductivity. We link key structural and environmental parameters (porosity, pore size distribution, density, backbone morphology, and pressure) to dominant transport regimes and the assumptions embedded in common models. Classical approaches, including effective-medium and percolation-based models, are assessed alongside phonon-scaling descriptions that incorporate characteristic length scales. Particular attention is given to the Knudsen effect and pressure-sensitive gas-conduction models, which are central to interpreting performance at atmospheric conditions and under vacuum or low-pressure operation. This review highlights inconsistencies across datasets and modeling practices, identifies persistent knowledge gaps, and outlines practical directions toward processable structure–property guidelines for manufacturing aerogels with targeted thermal performance, with regard to conduction-dominated heat transport mechanisms. Full article

Under intensifying climate change and increasingly frequent extreme heat events, improving outdoor thermal environments has become critical for sustainable human settlements. While prior studies have mainly focused on urban contexts, systematic investigations of rural microclimates—particularly regarding the regulatory mechanisms of landscape configurations—remain limited. This study examines a mountain-adjacent village in the Loess Tableland region of China, integrating field measurements with ENVI-met simulations to analyze thermal characteristics of rural road spaces and the effects of vegetation and paving materials on human thermal comfort. The results show that village boundary areas experience the largest fluctuations in air temperature and relative humidity during midday and evening, indicating higher thermal sensitivity. Model validation demonstrates satisfactory accuracy, with RMSE values of 0.39–3.62 °C for air temperature, 1.32–3.22% for relative humidity, and 1.35–2.24 m/s for wind speed, and MAPE ranging from 0.80% to 9.05%. Furthermore, Basalt Brick and Populus alba show the best cooling performance, but when considering multiple factors such as temperature, humidity, and wind speed, Ligustrum lucidum has the most significant effects in improving thermal comfort and increasing humidity. Analysis based on Physiological Equivalent Temperature (PET) further indicates that vegetation configurations play a more substantial role in thermal comfort regulation than paving materials, and that different landscape elements exhibit synergistic and trade-off relationships in terms of cooling, humidification, and ventilation. This study provides quantitative reference for vegetation configuration and material selection in rural roads within the Loess Tableland region and similar semi-arid areas, enriches the research scope of rural microclimate studies, and offers scientific support for climate-adaptive rural planning and optimization of rural living environments. Full article

Extreme temperatures increasingly threaten public health, yet temperature–mortality relationships vary substantially across regions and are often obscured by average exposure–response models. This study investigates heat- and cold-related mortality in five climatically diverse Greek cities—Athens, Thessaloniki, Larissa, Patra, and Heraklion—during 1992–2024 using an event-based framework that integrates cumulative thermal stress with synoptic atmospheric conditions. Heat and cold events were defined using the Excess Heat Factor and Excess Cold Factor, combined with persistence criteria and Spatial Synoptic Classification air masses. Mortality responses were assessed through daily mortality ratios, regression analyses, and event severity categories. Dry Moderate air masses dominated across cities, accounting for more than 60% of all days in each city, indicating that extremes typically reflect departures from generally mild background conditions. Linear associations between cumulative thermal stress and mortality were weak overall, with correlation coefficients generally below |0.15| for cold events and below 0.20 for heat events. However, severe heat events produced substantial mortality increases, with mean mortality ratios reaching 1.69 in Larissa and exceeding 1.30 in all cities, despite relatively low event frequency. In contrast, cold-related mortality was often linked to frequent lower-severity events, particularly in Thessaloniki (more than 200 cold events) and Athens. These findings demonstrate that mortality risk concentrates in discrete high-impact episodes rather than increasing linearly with thermal stress, underscoring the value of event-based approaches for locally tailored adaptation and early-warning strategies. Full article

Climate change is an urgent global crisis requiring collaboration across sectors, including public health. In Canada, extreme heat is a leading cause of weather-related mortality, and cities play a central role in mitigating health impacts. This study examined the governance mechanisms shaping intersectoral extreme heat response in Vancouver, Toronto, and Montreal, Canada. Using a comparative case study methodology, we conducted semi-structured interviews (N = 28) and reviewed local heat response documents (N = 30) between November 2023 and December 2024. Thematic analysis informed cross-case comparisons of governance mechanisms shaping collaborative efforts. Across cases, legislative mandates, formal response plans, and coordinating structures for network engagement supported effective intersectoral collaboration. However, collaboration varied in terms of network governance leadership, intersectoral scope (i.e., the type and number of sectors involved), degree of engagement, and the roles of public health authorities. Co-leadership across sectors in Montreal seems to enable greater intersectoral engagement and integration of heat strategies. Areas for improvement include community-engaged heat response planning and enhanced capacity for conducting heat response outcome evaluations. Public health authorities may inform the strategic direction of future heat strategies by supporting the application of a population health lens and facilitating intersectoral collaboration to better address the upstream determinants of heat health inequities. Full article

Qiangduo Tibetan paper is a typical intangible cultural heritage in the Shangri-La region of Yunnan, China, mainly handmade from two local fibrous plants, Stellera chamaejasme and Wikstroemia canescens. This study focuses on the correlations among its surface properties, water absorption and dry heat durability, which are critical for heritage conservation. Four paper samples (Z1–Z4) were investigated via micromorphology, physicochemical property testing and dry heat aging (105 °C, 216 h). The results show that the two raw materials lead to distinct fiber and pore structures: Stellera chamaejasme paper has coarser fibers and loose pores, while Wikstroemia canescens paper has finer and denser fibers. All samples present a near-neutral to weakly alkaline pH (6.87–7.56) and favorable water absorption, jointly regulated by fiber structure and alkaline wood ash fillers. After dry heat aging, all samples undergo whiteness loss, tensile index decay and slight acidification, with extremely significant changes (p < 0.001). Notably, Stellera chamaejasme paper exhibits much higher aging resistance, with whiteness and tensile index retention reaching 77.97%–93.07% and 71.46%–74.77% respectively, far superior to Wikstroemia canescens paper. The mechanism lies in the high flavonoid content and low lignin level in Stellera chamaejasme fibers, which enhance antioxidant stability and reduce yellowing, whereas the opposite composition accelerates degradation in Wikstroemia canescens paper. This study provides a scientific basis for the conservation, inheritance and targeted application of Qiangduo Tibetan paper, supports the sustainable protection of handmade paper cultural relics, and enriches the application of surface science in cultural heritage conservation. Full article

This study provides a comprehensive evaluation of the effects of environmental stressors and physical exertion on human nociceptive processing across multiple ecologically relevant conditions. Using a repeated-measures design, participants (N = 45) completed up to five controlled laboratory (thermoclimatic chamber) sessions (baseline, simulated altitude at 4200 m asl, heat at +42 °C, cold at −10 °C, and exertion). Participants were tested by using electrical stimuli. Linear mixed-effects models with participant-level random intercepts, alongside estimated marginal means and bootstrap derived effect sizes, enabled robust characterization of within-subject differences. Thermal stress emerged as the strongest modulator of nociception. Heat exposure significantly elevated sensory and pain thresholds compared with all other conditions, whereas tolerance thresholds peaked during cold exposure, yielding the largest observed effects. Altitude consistently produced the lowest thresholds across all modalities. These contrasts were confirmed statistically in the mixed-effects models, and effect-size analyses indicated substantial within-subject differences between the thermal extremes. By integrating three distinct nociceptive modalities and extreme environment simulations, this work offers novel and informative insights into how environmental stressors shape pain processing. The discovery of opposing thermal effects on sensory/pain versus tolerance thresholds—within the same cohort and design—reveals modality-specific patterns not previously documented and suggests that hypoxia may further modulate these responses. Full article

This study investigates microclimatic variation across four environmentally and socially vulnerable neighborhoods in Philadelphia, utilizing ground-based measurements to assess urban heat (UH) and heat stress (HS). HS metrics, specifically Wet-Bulb Globe Temperature (WBGT) and heat index (HI), were calculated from UH measurements, including dry bulb and globe temperature, relative humidity, and wind speed. The methodology incorporates statistical modeling to identify significant predictors of HS, with street orientation (north–south and east–west) emerging as a key determinant, while categorical shade conditions were not statistically significant. Notably, Kingsessing exhibited lower HS and a unique humidity profile, whereas temperatures in Point Breeze and Grays Ferry and Hunting Park were consistently elevated. The research demonstrates that neighborhood-scale measurements can reveal critical spatial differences in UH and HS that are helpful in customizing mitigation strategies to specific communities. The approach is adaptable for integration with public health and emergency response initiatives, supporting data-driven decision-making for local governments and community-based organizations. Although assessment of physiological metrics and sampling during peak heat periods were not possible, overall, the study provides a practical framework for addressing urban heat vulnerability and underscores the importance of context-specific, community-engaged solutions to protect at-risk populations from extreme heat impacts. Full article

Skeletal muscle development and physiological homeostasis are profoundly influenced by environmental cues. Among these factors, ambient temperature represents a critical determinant of growth performance and metabolic adaptation in mammals. However, the effects of different ambient temperature ranges on skeletal muscle characteristics and on responses across multiple visceral tissues remain poorly understood. In this study, five ambient temperature conditions (16 °C, 20 °C, 24 °C, 28 °C, and 32 °C) were established to investigate their physiological impacts in a mouse model. Our results demonstrate that ambient temperature markedly influences growth performance and skeletal muscle phenotype. Notably, mice housed at 20 °C showed relatively preserved grip strength and a shift in myofiber cross-sectional area distribution, although these findings did not consistently indicate superior skeletal muscle development across all indices. Further analysis revealed that ambient temperature significantly modulated the expression profiles of myosin heavy chain (MyHC) isoforms in skeletal muscle. Specifically, cold exposure was associated with an upregulation of the slow-twitch-related MyHC I, whereas heat stress correlated with an elevation of the fast-twitch-related MyHC IIb. Functional assessments indicated that exposure to colder or hotter conditions was associated with impaired muscle performance, as reflected by reduced grip strength at 16 °C, 28 °C, and 32 °C, and decreased endurance capacity at 28 °C and 32 °C. Histological analyses of major visceral organs revealed no obvious structural alterations in the heart, liver, spleen, lung, or kidney across temperature conditions. However, exposure to thermal extremes (16 °C and 32 °C) significantly reduced intestinal villus height, suggesting compromised intestinal integrity under temperature stress. Collectively, these findings indicate that ambient temperature is associated with multi-tissue changes in skeletal muscle characteristics, functional performance, and intestinal morphology. This study provides new insights into how environmental temperature modulates tissue adaptation and physiological homeostasis in mammals. Full article

The continuous current dissipation of direct current grounding electrodes generates intense Joule heat, causing severe soil moisture loss and localized thermal runaway. Traditional static models ignore the temperature-dependent nature of soil parameters, leading to dangerous underestimations of actual temperature rises and thermal risks. To address this critical issue, this study establishes a bidirectional dynamic electro-thermal coupled model for a vertical grounding electrode using COMSOL Multiphysics. Comparative analysis demonstrates that the dynamic model accurately reproduces the late-stage accelerated temperature rise observed in experiments, proving its necessity over static methods. Simulations reveal that increased soil resistivity governs heat generation and directly causes a dramatic surge in both grounding resistance and maximum step voltage. In two-layer heterogeneous soils, current is forced into lower-resistivity regions, triggering extreme localized overheating. To mitigate this, expanding the cross-sectional radius of the coke bed effectively suppresses the thermal concentration. These findings provide quantitative evidence and non-uniform design guidelines for the safe operation and thermal protection of grounding electrodes under complex geological conditions. Full article

River water quality assessment has traditionally been conducted using univariate or threshold-based approaches; however, the exploration of extremes assessment under bivariate water quality variables has been limited by many studies. Understanding the compound extremes of low river discharge (Q) and elevated river water temperatures (RWTs) resulting from climatic variability is essential for effective water quality management and protection of the river. This study investigates the joint behaviour of RWTs and Q in six Indian rivers: Kaveri, Mahi, Sabarmati, Vardha, Bhadra, and Yamuna. The Weibull-3P and Generalised Extreme Value (GEV-3P) distributions best fit for Q and RWTs, respectively. The adequacy of eighteen different parametric copula classes was evaluated. The Gaussian copula provided the best fit for the Vardha River, the Frank copula for Bhadra, and the BB8 copula for the Yamuna River. The evaluation of joint return periods (RPs) and conditional distributions has identified notable spatial variability in compound hydrological and thermal extreme hazards. The semi-arid Vardha River showed the shortest RPs for simultaneous low Q and high RWTs, indicating a greater likelihood of combined extremes. Conversely, the monsoon-fed Bhadra River displayed moderate hazard levels, while the Himalayan-fed Yamuna River had the longest joint RPs and the lowest conditional probabilities. This suggests that simultaneous extreme drought and heat events are less likely in the Yamuna basin, although significant risks remain for less severe thresholds. Full article

Urban Heat Islands (UHIs) are widely analyzed using Land Surface Temperature (LST), yet most studies remain limited to single cities, rely on a single machine-learning model, analyze LST alone, and use inconsistent Surface Urban Heat Island Intensity (SUHII) definitions, which restrict cross-city comparability and broader generalization. This study introduces an explainable artificial intelligence (XAI) framework implemented in Google Earth Engine (GEE) to analyze census-tract summer surface heat (2018–2024) across eight climatically contrasting U.S. cities. The main novelty is a standardized tract-scale cross-city framework that jointly models LST and SUHII using a consistent SUHII definition, a common physical predictor set, city-held-out nested cross-validation, and SHAP-based interpretation, allowing absolute surface heat to be distinguished from relative within-city heat anomaly; this combination is rarely implemented within a single urban heat study. Multiple machine-learning models were evaluated, with ensemble trees performing best: Extreme Gradient Boosting (XGBoost) best predicted SUHII (R² = 0.879; RMSE = 0.213), while Extra Trees best predicted LST (R² = 0.908; RMSE = 0.745 °C). SHapley Additive exPlanations (SHAP) indicate that SUHII is driven primarily by impervious surface fraction and surface moisture availability, whereas LST is structured by latitude and mean summer air temperature. Overall, the framework provides interpretable multi-city attribution of urban surface heat drivers with demonstrated cross-city generalization. Full article