Search Results (211)

Global environmental changes significantly alter ecosystem services (ESs), particularly in fragile regions like the Tibetan Plateau. While methodological advances have improved spatial assessment capabilities, understanding of how multiple drivers interact to shape ecosystem service heterogeneity remains limited to regional scales, especially across complex alpine landscapes. This study aims to clarify whether multi-factor interactions produce nonlinear enhancements in ES explanatory power and how these driver–response relationships vary across heterogeneous terrains. We quantified spatiotemporal patterns of four key ecosystem services—water yield (WY), soil conservation (SC), carbon sequestration (CS), and habitat quality (HQ)—across the southeastern Tibetan Plateau from 2000 to 2020 using multi-source remote sensing data and spatial econometric modeling. Our analysis reveals that SC increased by 0.43 t·hm⁻²·yr⁻¹, CS rose by 1.67 g·m⁻²·yr⁻¹, and HQ improved by 0.09 over this period, while WY decreased by 3.70 mm·yr⁻¹. ES variations are predominantly shaped by potent synergies, where interactive explanatory power consistently surpasses individual drivers. Hydrothermal coupling (precipitation ∩ potential evapotranspiration) reached 0.52 for WY and SC, while climate–vegetation synergy (precipitation ∩ normalized difference vegetation index) achieved 0.76 for CS. Such climate–restoration synergies now fundamentally shape the region’s ESs. Geographically weighted regression (GWR) further revealed distinct spatial dependencies, with southeastern regions experiencing strong negative effects of land use type and elevation on WY, while northwestern areas showed a positive elevation associated with WY but negative effects on SC and HQ. These findings highlight the critical importance of accounting for spatial non-stationarity in driver–ecosystem service relationships when designing conservation strategies for vulnerable alpine ecosystems. Full article

This study investigates the spatial patterns and drivers of carbon emissions across China’s three major urban agglomerations—Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)—from 2011 to 2020. A sequential analytical framework was employed to examine emission inequality, spatial dependence, dynamic transitions, and multi-scale drivers. Specifically, the Gini and Theil indices were used to quantify and decompose regional disparities. Spatial clustering patterns and heterogeneity were then identified through global and local Moran’s I analysis. Following this, spatial Markov chains modeled state transitions and neighborhood spillover effects. Finally, the Spatial Durbin Model (SDM) was applied to distinguish between the direct and indirect effects of key socioeconomic drivers. The findings reveal that disparities in emissions are largely driven by factors within each region. In BTH, heavy industrial lock-in accounts for 47.1% of the within-group inequality. By contrast, the YRD and PRD show noticeable convergence, achieved through industrial synergy and technological restructuring, respectively. The mechanisms of spatial spillover also differ across regions. In the YRD, emissions exhibit strong clustering tied to geographic proximity, with Moran’s I consistently above 0.6. In BTH, policy linkages play a more central role in shaping emission patterns. Meanwhile, in the PRD, widespread technological diffusion weakens the conventional distance-decay effect. The influence of key drivers varies notably among the urban agglomerations. Economic growth has the strongest scale effect in the PRD, reflected by a coefficient of 0.556. Industrial transformation significantly lowers emissions in the YRD, with a coefficient of −0.115. Technology investment reduces emissions in BTH (−0.124) and the PRD (−0.076), but is associated with a slight rebound in the YRD (0.037). Overall, these results highlight the persistent path dependence and distinct spatial interdependencies of carbon emissions in each region. This underscores the need for tailored mitigation strategies that are coordinated across administrative boundaries. Full article

Coal gangue, as a predominant solid byproduct of the global coal industry, poses severe environmental challenges because of its massive accumulation and low utilization rate. This review systematically synthesizes and analyzes published experimental and analytical studies on the dual-pathway utilization of coal gangue in concrete, including Pathway 1 (aggregate substitution) and Pathway 2 (cementitious activity activation). While the application of coal gangue aggregates is traditionally limited by their inherent high porosity and lower mechanical strength than those of natural aggregates, this review demonstrates that performance barriers can be effectively overcome. Through multiscale modification strategies—including surface densification, biological mineralization (MICP), and matrix synergy—the interfacial defects are significantly mitigated, allowing for feasible substitution in structural concrete. Conversely, for the mineral admixture pathway, controlled thermal activation is identified as a key process to optimize the phase transformation of kaolinite, thereby significantly enhancing pozzolanic reactivity and long-term durability. According to reported studies, the partial replacement of natural aggregates or cement with coal gangue can reduce CO₂ emissions by approximately tens to several hundreds of kilograms per ton of coal gangue utilized, depending on the substitution level and activation strategy, highlighting its considerable potential for carbon reduction in the construction sector. Nevertheless, challenges related to energy-intensive activation processes and variability in raw gangue composition remain. These limitations indicate the need for future research focusing on low-carbon activation technologies, standardized classification of coal gangue resources, and long-term performance validation under realistic service environments. Based on the synthesized literature, this review discusses hierarchical utilization concepts and low-carbon activation approaches as promising directions for promoting the sustainable transformation of coal gangue from an environmental liability into a carbon-reduction asset in the construction industry. Full article

Considering the challenges associated with implementing emerging technologies and bacterial-derived antimicrobial metabolites at an industrial scale in the meat industry, this comprehensive review investigates the interactions between lactic acid bacteria-producing antimicrobial metabolites and emerging food preservation technologies applied to meat systems. By integrating evidence from microbiology, food engineering, and molecular physiology, the review characterizes how metabolites-derived compounds exert inhibitory activity through pH modulation, membrane permeabilization, disruption of proton motive force, and interference with cell wall biosynthesis. These biochemical actions are evaluated in parallel with the mechanistic effects of high-pressure processing, pulsed electric fields, cold plasma, irradiation, pulsed light, ultrasound, ohmic heating and nanotechnology. Across the literature, consistent patterns of synergy emerge: many emerging technologies induce structural and metabolic vulnerabilities in microbial cells, thereby amplifying the efficacy of antimicrobial metabolites while enabling reductions in process intensity. The review consolidates these findings to elucidate multi-hurdle strategies capable of improving microbial safety, extending shelf life, and preserving the physicochemical integrity of meat products. Remaining challenges include optimizing combinational parameters, ensuring metabolite stability within complex matrices, and aligning integrated preservation strategies with regulatory and industrial constraints. Full article

Multimodal remote sensing imagery, such as visible and infrared data, offers crucial complementary information that is vital for time-sensitive emergency applications like search and rescue or disaster monitoring, where robust detection under adverse conditions is essential. However, existing methods’ object detection performance is often suboptimal due to task-independent fusion and inherent modality inconsistency. To address this issue, we propose a joint fusion and detection approach for multimodal remote sensing imagery (JFDet). First, a gradient-enhanced residual module (GERM) is introduced to combine dense feature connections with gradient residual pathways, effectively enhancing structural representation and fine-grained texture details in fused images. For robust detection, we introduce a second-order channel attention (SOCA) mechanism and design a multi-scale contextual feature-encoding (MCFE) module to capture higher-order semantic dependencies, enrich multi-scale contextual information, and thereby improve the recognition of small and variably scaled objects. Furthermore, a dual-loss feedback strategy propagates detection loss to the fusion network, enabling adaptive synergy between low-level fusion and high-level detection. Experiments on the VEDAI and FLIR-ADAS datasets demonstrate that the proposed detection-driven fusion framework significantly improves both fusion quality and detection accuracy compared with state-of-the-art methods, highlighting its effectiveness and high potential for mission-critical multimodal remote sensing and time-sensitive application. Full article

The Guizhou Plateau, with the most extensive and representative karst landforms worldwide, is characterized by severe soil erosion and a highly fragile ecological environment. However, large-scale assessments of soil conservation services in this region remain limited. A key challenge lies in identifying appropriate datasets and methodologies for regional-scale soil conservation service evaluations, particularly under conditions of data scarcity or limited data accuracy. In this study, Unmanned Aerial Vehicle imagery, runoff plot observations, ground survey data, and multi-source satellite remote sensing data were integrated to refine LS and C in the Revised Universal Soil Loss Equation (RUSLE), thereby establishing a parameterized and localized soil erosion model. This improvement provided a methodological foundation for soil conservation service research in the region. Subsequently, the spatiotemporal variations in soil conservation services in the Guizhou Plateau over the past two decades were assessed. Furthermore, the relationships between soil conservation services and other key ecosystem services, including water conservation and carbon sequestration, were quantitatively examined, and the driving factors were analyzed. Soil conservation on the Guizhou Plateau exhibited an improving trend from 2000 to 2020. In karst areas, the relationship between soil conservation and water conservation was primarily influenced by temperature, altitude, and vegetation coverage, whereas in non-karst areas, it was regulated by rainfall and slope. Ecological restoration projects have enhanced the synergy between soil conservation and carbon sequestration by promoting vegetation cover. These findings could contribute to the next stage of ecological engineering initiatives and ecological policy implementation in Guizhou. Full article

Research on the characteristics and functions of ancient Juntun (military tillage) has paid limited attention to the distribution patterns and influencing factors of Juntun in specific regions. This study employs a comprehensive approach integrating GIS technology and the multi-scale geographically weighted regression (MGWR) model to quantitatively analyze the spatial distribution characteristics and influencing factors of Ming Dynasty Juntun in Fujian. The study reveals that Juntun were primarily located in flat areas near water systems, while exhibiting a U-shaped distribution pattern away from garrison forts, reflecting a synergy between agricultural foundations and military defense. MGWR analysis further indicates that fiscal and taxation factors had a stronger influence on their distribution than arable land resources, highlighting their non-purely agriculturally driven nature. This research provides a quantitative basis for understanding the organizational logic and spatial strategy of ancient military settlements, offering valuable insights for the conservation and study of military heritage. Full article

Salinity is a key abiotic stress limiting crop growth. Accurate quantification of carbon budgets and their environmental responses is critical for sustainable cotton production, yet regional-scale assessments remain scarce. To clarify the evolutionary patterns and driving mechanisms of soil organic carbon (SOC) in saline cotton fields of arid Central Asia, this study focused on Xinjiang and modified the RothC model by integrating salinity adjustment factors and vegetation carbon decomposition indices, simulating SOC dynamics (1980–2022) with multi-source data. Results showed the improved model achieved high accuracy in capturing SOC dynamics in salinized cotton fields. Spatially, SOC exhibited high levels south of the Tianshan Mountains and low levels in southwestern Xinjiang; temporally, it showed an overall fluctuating upward trend, though both high- and low-value zones displayed localized declines. Geodetector analysis revealed fertilizer application as the primary driver of SOC spatial variation, followed by straw return, precipitation, and temperature, with most factors showing synergistic enhancement effects. Human management (fertilization and straw return) is the core regulator of SOC, and its synergy with natural factors shapes SOC spatiotemporal patterns. The salinization-adapted RothC model provides a novel framework for arid cotton field SOC simulation, offering scientific support for carbon pool optimization and sustainable agriculture in arid regions. Full article

The growing pressure to achieve carbon neutrality has exposed major limitations in current industrial processes, which often operate in isolation, rely on simplified mass-balance assumptions, and struggle to manage increasingly complex material and energy flows. Traditional industrial symbiosis and circular economy strategies have improved resource efficiency, yet they rarely capture molecular-level interactions or enable coordinated optimization across multiple facilities, restricting their ability to support large-scale decarbonization. In this context, Carbon–Hydrogen–Oxygen Symbiosis Networks (CHOSYNs) have emerged as an advanced framework that integrates atomic-level targeting with multi-scale process systems engineering to identify synergies, valorization pathways, and cross-sector exchanges that conventional approaches overlook. This review consolidates the theoretical foundations, historical development, and recent applications of CHOSYNs, illustrating how it can enhance efficiency, reduce emissions, and strengthen resilience in energy systems, chemical industries, and circular resource management. Although the literature remains limited, existing studies demonstrate the promise of CHOSYNs as a unifying methodology for designing low-carbon industrial ecosystems. Key challenges related to scalability, validation, governance, and operational robustness are examined, and a roadmap is proposed to guide the evolution and practical deployment of CHOSYNs toward 2035. Full article

Current assessments of urban green spaces (UGS) rely largely on two-dimensional (2D) indicators, which fail to capture the three-dimensional (3D) structure necessary for evaluating ecological functions and human exposure. Among these, the Normalized Difference Vegetation Index (NDVI) describes top-down canopy greenness from a nadir perspective, whereas the Green View Index (GVI) quantifies vegetation visibility at street level from a pedestrian perspective. Because the relationship between NDVI and GVI remains unclear, multi-indicator assessments become difficult to interpret, limiting their ability to jointly characterize urban greenery. To address these gaps, we develop a synergy framework that integrates remote sensing with street-view images. First, we aligned the observation scales through street-view depth estimation and converted NDVI into fractional vegetation cover (FVC) through nonlinear mapping to unify measurement units. Correlation experiments revealed that the consistency between GVI and FVC was weak across the city (R² = 0.27) but substantially stronger along arterial roads with continuous vegetation (R² = 0.61). On this basis, we design a Green Synergy Index (GSI) that combines FVC and GVI using fractional power-law adjustments and an interaction term to capture their joint effects. Robustness tests indicate that GSI effectively handles extreme or mismatched cases, differentiates greening patterns, and integrates complementary information from nadir and street views without numerical instability. Furthermore, we assess the consistency between GSI and land surface temperature (LST), showing that the proposed index improves explanatory power compared with FVC and GVI alone (by 5.6% and 8.8%, respectively). Application to the study area yields a mean GSI value of 0.44 on a 0–1 scale, with spatial variations closely associated with road geometry and functional zoning. This enables the identification of mismatched canopy and visibility segments and supports targeted, climate-sensitive green infrastructure planning. Full article

Existing salient object detection methods for optical remote sensing images still face certain limitations due to complex background variations, significant scale discrepancies among targets, severe background interference, and diverse topological structures. On the one hand, the feature transmission process often neglects the constraints and complementary effects of high-level features on low-level features, leading to insufficient feature interaction and weakened model representation. On the other hand, decoder architectures generally rely on simple cascaded structures, which fail to adequately exploit and utilize contextual information. To address these challenges, this study proposes a Hierarchical Semantic Interaction Module to enhance salient object detection performance in optical remote sensing scenarios. The module introduces foreground content modeling and a hierarchical semantic interaction mechanism within a multi-scale feature space, reinforcing the synergy and complementarity among features at different levels. This effectively highlights multi-scale and multi-type salient regions in complex backgrounds. Extensive experiments on multiple optical remote sensing datasets demonstrate the effectiveness of the proposed method. Specifically, on the EORSSD dataset, our full model integrating both CA and PA modules improves the max F-measure from 0.8826 to 0.9100 (↑2.74%), increases maxE from 0.9603 to 0.9727 (↑1.24%), and enhances the S-measure from 0.9026 to 0.9295 (↑2.69%) compared with the baseline. These results clearly demonstrate the effectiveness of the proposed modules and verify the robustness and strong generalization capability of our method in complex remote sensing scenarios. Full article

This study investigates the synergistic influence of multi-walled carbon nanotubes (MWC-NTs), nanosilica powder (NSP), and polypropylene fiber waste (PFW) on the mechanical performance of mortar incorporating demolished concrete waste aggregates (DCWA). The replacement of natural aggregates with DCWA typically results in strength reductions and weak interfacial transition zones; therefore, the combined use of nanomaterials and microfibers is proposed as a mitigation strategy. A Taguchi Design of Experiments (DOE) approach was employed to optimize mix parameters, including MWCNT dosage, NSP content, PFW volume fraction, and DCWA replacement level. Mortar mixtures were prepared with MWCNTs (0–0.1% by binder weight), NSP (0–2% by binder weight), PFW (0–0.3% by volume), and DCWA (0–20% replacement of fine sand). Mechanical performance was assessed through compressive and flexural strength tests. A combined statistical approach using the Pareto chart and ANOVA identified the most influential parameters and their respective contributions to the response variable. The innovative aspect of this research lies in the synergistic integration of MWCNTs, NSP, demolished concrete waste, and polypropylene fiber waste within the mortar matrix, with the incorporation of nanomaterials specifically intended to compensate for the strength reduction typically induced by the use of demolition concrete waste aggregates. Although a potential nano-scale synergy between MWCNTs and NSP was initially considered, the experimental results indicated that the most relevant synergistic effects occurred among broader mix parameters rather than specifically between the two nanomaterials. Even so, when assessed individually, both nanomaterials contributed to improving the mechanical characteristics of the mortar—particularly nanosilica, which demonstrated a more pronounced effect—yet these individual enhancements did not translate into a distinct synergistic interaction between MWCNTs and NSP. The Taguchi DOE proved to be an efficient tool for multiple factor analysis, enabling reliable identification of the most influential parameters with a minimum number of tests. Its application facilitated the development of mortar mixtures that effectively integrate demolition waste while achieving enhanced mechanical performance through nano- and micro-scale reinforcement. Full article

The complex relationship between urban torrents and riparian communities is investigated in this research, from a landscape point of view, in the aftermath of the catastrophic floods in Volos, Greece, in September 2023. The study starts with a multi-scalar approach, investigating through plural timescales and space-scales the way communities and torrents have co-existed in the Mediterranean; particularly in Volos, the way neoteric urban infrastructures have affected and underestimated torrentscapes, is observed critically. This investigation extends to the legislative spatial planning framework in Greece and the EU, concerning the torrent-beds and torrentscapes, in the framework of extreme climate events brought about by climate change. Highlighting the dual challenges of floods and droughts, the research uncovers the inadequacy of existing gray infrastructure and of top-down management approaches, in addressing flood risk. Co-vulnerability emerges as a binding agent, between riparian communities and torrent ecosystems. By the means of research-by/through-design in synergy with anthropological research tools, this approach aims at fostering “just” resilience, by presupposing social justice, towards the promotion of Integrated - Catchment- Management- Plans -(ICMPs) that combine the mitigation of flood risk and extreme drought challenges, the enhancement of torrentscape ecosystems, and the strengthening of the symbiotic relationship between the city inhabitants and its torrents. Full article

The rapid development of deep-space exploration and crewed missions makes efficient, lightweight, and low–secondary-radiation γ-ray protection in complex cosmic fields a critical materials challenge. Current studies still struggle to simultaneously balance attenuation efficiency, areal density and thickness, flexibility, and shielding against secondary γ rays. Compared with existing reviews that mainly focus on single matrices (especially polymers) or medical lead-based protection, this work targets γ-ray shielding under deep-space and mixed radiation environments, emphasizing multiscale structural designs (multilayer/gradient architectures, micro/nanofiller synergy, and fiber networks) for suppressing secondary γ-rays and outlining composition–structure–morphology–coupled strategies for flexible, wearable, lead-free shields. Recycling and sustainability remain key bottlenecks for practical deployment. Accordingly, this review also summarizes representative Monte Carlo simulation tools and their integration with experiments, and proposes directions for element selection, structural design, and green manufacturing to build design rules and a scale-up roadmap for next-generation lead-free γ-shielding wearables. Full article

Understanding the complex and evolving interactions between ecosystem services and socio-economic development is crucial for addressing ecological challenges and achieving harmony between humans and nature. However, multi-objective nexus optimization models that reveal the interdependencies of socio-ecological systems have received little attention. This study therefore aims to propose a species–carbon–water–food–economy functional nexus and explore trade-offs and synergies across China’s provinces from 2000 to 2020, using the InVEST model, correlation analysis, and redundancy analysis. The results revealed that the species protection function exhibited an “increase–decrease” trend, while the carbon sink, water conservation, food supply, and economic development functions increased. Both ecosystem functions and economic development functions exhibited spatial differences. Although synergies dominated the functional nexus, a trade-off was observed between species protection and food supply, with functional interactions showing spatial heterogeneity at the provincial scale. Complex interactions between social systems and ecosystems were observed in 2000, 2010, and 2020, with explanatory powers of 52.5%, 59.7%, and 59.1%, respectively. Functional policy goals exhibited both trade-offs and synergies. To achieve the sustainable development of the socio-ecological system, a “multi-goals driven, multi-sectoral linkage, and multi-policies synergy” framework should be implemented to balance the species–carbon–water–food–economy functional nexus. Full article