Search Results (7,287)

Rural tourism in China is advancing rapidly, with cultural and tourism integration (CTI) becoming a vital pathway for sustainability. Mountain–water towns, given their special geographical conditions, face numerous challenges in CTI development, which need to enhance landscape resilience. This study proposes the theoretical framework of landscape resilience in mountain–water towns from the perspective of CTI. Taking Yinji Town of Wugang City as an example, it constructs a resilience evaluation system including three dimensions: cultural landscape, natural landscape, and social systems. The study uses the AHP–Entropy Weight combined method to determine indicator weights. Indicator scores are obtained through field research and GIS analysis, which are substituted into the preparedness–vulnerability resilience model to calculate resilience level, and the Jenks Natural Breaks method is used for level classification. Finally, the Obstacle Degree Model is applied to identify the primary obstacle factors affecting landscape resilience. The results indicate the following: (1) The average landscape resilience (RI) score of the 19 villages in Yinji Town is 0.84 (RI < 1), indicating a generally low level. Two villages are in the high-level range, while four villages are in the low-level range. (2) Cultural landscape resilience is the primary weakness, with the lowest average score (0.70), while natural landscape resilience is the highest (1.03). (3) Major obstacles include such as the number of cultural inheritors, the degree of susceptibility to natural disasters, and the distance to core mountain–water resources. The study contributes a CTI-based evaluation framework and methodology for assessing landscape resilience, offering enhancement strategies through increased preparedness and reduced vulnerability. Full article

The decarbonisation of the built environment has increased reliance on Environmental Life Cycle Assessment (E-LCA) to evaluate the impacts of construction materials. However, social aspects—particularly those affecting workers—remain underexplored. This study presents a regionalised approach to support socially and environmentally informed decision-making in the Italian construction sector. For this purpose, we have integrated worker health and safety indicators into the E-LCA of two representative building products assessed across key life cycle stages. These indicators are incorporated into the evaluation of Global Warming Potential (GWP), thus serving as a decision-support tool during the design phase. From a design perspective, the aim is to promote a broader understanding of sustainability—encompassing both environmental and social dimensions—within building projects. Methodologically, the contribution is twofold. First, it addresses the current gap in context-specific data on the critical indicator of worker health and safety in the construction sector, an essential requirement for robust and scientifically recognised S-LCA studies. To this end, the study develops a regionalised scoring system based on publicly available occupational health and safety data from the Italian National Accident Database (INAIL), disaggregated by sector and region. Second, we propose a framework to combine these social indicators with LCA-based environmental impact metrics, which remain central to building-scale E-LCA. It is clear that no single region performs best, while a critical need for multi-criteria decision-making in sustainable design is evident. Full article

In high-density urban areas where ecological protection constraints are increasingly stringent, transportation infrastructure layout must balance service efficiency and environmental preservation. From an ecological-prioritization perspective, this study proposes a three-stage multi-objective optimization strategy for siting underground smart parking facilities using the NSGA-III algorithm, with Haidian District, Beijing, as a case study. First, spatial identification and screening are conducted using GIS, integrating urban fringe-space extraction with POI, AOI, population, and transportation network data to determine candidate locations. Second, a multi-objective model is constructed to minimize green space occupation, walking distance, and construction cost while maximizing service coverage, and is solved with NSGA-III. Third, under the ecological-prioritization strategy, the solution with the lowest land occupation is selected, and marginal benefit analysis is applied to identify the optimal trade-off between ecological and economic objectives, forming a flexible decision-making framework. The findings show that several feasible schemes can achieve zero green-space occupation while maintaining high service coverage, and marginal benefit analysis identifies a cost-effective solution serving about 20,000 residents with an investment of 7 billion CNY. These results confirm that ecological protection and urban service efficiency can be reconciled through quantitative optimization, offering practical guidance for sustainable infrastructure planning. The proposed methodology integrates spatial analysis, multi-objective optimization, and post-Pareto analysis into a unified framework, addressing diverse infrastructure planning problems with conflicting objectives and ecological constraints. It offers both theoretical significance and practical applicability, supporting sustainable urban development under multiple scenarios. Full article

Flooding is one of the most frequent and destructive natural disasters worldwide, with intensifying socioeconomic and environmental consequences linked to rapid urbanisation and climate change. This review examines flood risk delineation and assessment in Nigeria within a broader Global South perspective, synthesising evidence from peer-reviewed studies that employ remote sensing, GIS-based techniques, and multi-criteria decision analysis. The analysis reveals persistent challenges that undermine effective flood risk management, including incompatible datasets, limited stakeholder participation, and inadequate integration with formal planning systems. To address these gaps, the study introduces the GIS-Integrated Flood Risk Management (GIFRM) Framework, a conceptual model that integrates high-resolution risk mapping, adaptive infrastructure design, sustainable urban planning, and participatory governance. GIFRM advances resilience discourse beyond hazard mapping, offering a practical bridge between science, policy, and implementation by aligning technical geospatial analysis with actionable planning solutions. Comparative case insights from flood-prone countries such as Bangladesh, India, and Kenya highlight transferable strategies, including community-led data integration, modular infrastructure approaches, and localised zoning reforms. The review concludes by critically examining the operational disconnect between advanced geospatial risk assessment and its application in resource-limited, rapidly urbanising settings. It reframes flood risk assessment as an interdisciplinary planning tool with global relevance, delivering lessons for disaster preparedness, urban sustainability, and climate resilience. In the face of escalating hydrometeorological extremes, this research offers applied strategies for embedding GIS technologies into adaptive policy frameworks, positioning flood risk management as a core driver of sustainable development. Full article

This study provides a comprehensive review of advancements in the field of train–track–subway system interaction dynamics and suggests future directions for research and development. Mathematical modeling of train–track–subway interaction system is addressed, including wheel–track contact mechanics and wear, train multibody dynamics, train–track system coupling dynamics, track slab subsystem dynamics, subway tunnel–ground interaction models, building vibration excited by ground-borne seismic waves, and noise. Advanced computing and simulation techniques used for numerical studies of the dynamics of train–track–subway system interaction in the past two decades are also addressed, including high-performance computing with efficient algorithms, multi-physics and multi-scale simulation, real-time hardware-in-the-loop simulation, and laboratory and field validation. The study extends the applications of train–track–subway interaction dynamics to subway route planning, structural and material design, subway maintenance, operations safety and reliability, and passenger comfort. Emerging technologies and future perspectives are also reviewed and discussed, including artificial intelligence, smart sensing and real-time monitoring, digital twin technology, and sustainable design integration. Full article

The Chengdu–Chongqing Economic Circle (CCEC) represents a key regional development initiative in China. University research collaboration plays a vital role in advancing its innovation ecosystem and supporting sustainable growth. This study examines inter-university collaboration among 47 public universities in the CCEC based on 53,968 co-authored publications from 2005 to 2024. Using bibliometric and visualization techniques in CiteSpace 6.4.R2, it explores the structure and evolution of collaboration from institutional, thematic, and author perspectives. The results reveal a steady expansion of collaborative activities driven by national innovation strategies. Leading institutions such as Sichuan University, UESTC, and Chongqing University act as central hubs connecting diverse research communities. Collaboration has diversified from traditional fields toward interdisciplinary areas including materials, environmental science, and applied mathematics. Author networks are becoming more cohesive, reflecting stronger knowledge integration across universities. The study highlights how policy-driven collaboration fosters regional innovation capacity and provides evidence-based insights for strengthening university networks and advancing the CCEC’s role as a science and technology innovation hub in western China. Full article

The photocatalytic reduction of carbon dioxide (CO₂) into energy-dense fuels using visible light provides a sustainable approach for solar-to-chemical energy transformation. Among the diverse metal molecular systems developed, ruthenium (II) (Ru(II)) complexes have emerged as promising catalysts due to their superior redox properties, strong visible light absorption, and customizable ligand structures. This review explores recent advances in Ru(II)-catalyzed CO₂ photoreduction, with particular attention given to catalyst design strategies, mechanistic pathways, and system integration methodologies. Key configurations, including photosensitizer/catalyst (PS/Cat) mixed systems, covalently bonded dyads, and hybrid/supramolecular frameworks, are evaluated in terms of efficiency, turnover numbers (TON), and selectivity. A critical analysis of challenges such as competing H₂ generation, inefficient charge transfer, and limited long-term stability is presented. Emerging trends toward the use of pincer ligands, transition metal integration, and self-photosensitizing frameworks are discussed as potential approaches for improving efficiency. Overall, this review offers insights into the structural and mechanistic features driving CO₂ photoreduction and provides perspectives for the rational design of next-generation Ru-based photocatalytic systems for efficient solar CO₂ conversion and the photocatalytic reduction of carbon dioxide (CO₂) into energy-dense fuels using visible light. Full article

Understanding consumer perceptions of brand image is vital for the sustainable development of China Time-honored Brands, which combine cultural heritage with commercial value. This study aims to systematically analyze the brand image of Beijing’s time-honored restaurants by developing a large language model (LLM)-driven framework that advances beyond the limits of traditional text mining in semantic depth and adaptability. Using Dianping reviews from 2016 to 2022, we apply the Qwen3-32B model to map consumer feedback onto a Functional–Experiential–Symbolic (F–E–S) framework. Sentiment quantification and clustering analysis are employed to generate brand image profiles and identify common brand types, while topic modeling is used to uncover the specific consumer concerns shaping these perceptions. The results reveal a dual structure: the symbolic dimension, rooted in cultural heritage, is consistently high and stable, whereas the functional and experiential dimensions, associated with daily operations, are relatively low and highly volatile. Clustering further distinguishes two significantly different categories: comprehensive performers and heritage struggler brands. The key difference lies in whether brands can transform symbolic capital derived from historical legacy into positive consumer experiences through excellent operational performance. By integrating dynamic and structural perspectives, this study advances brand image research and provides data-driven insights to guide the targeted management and modernization of heritage brands. Full article

This scientific article examines the issue of the effectiveness of digital transformation in Kazakhstan’s industry from the perspective of how effectively enterprises are able to convert digital resources into economically measurable results in the context of the transition to a model of sustainable industrial growth. The aim of the study is to develop a comprehensive methodology for assessing the digital readiness of industrial enterprises to implement and adapt digital ecosystems based on a synthesis of conceptual and empirical approaches. The methodology developed by the authors combines a parametric diagnostic system and stochastic frontier analysis (SFA) tools, which allows for a quantitative assessment of not only the scale but also the effectiveness of digital transformations at the regional level. The empirical part of the study includes statistical data for 2023, reflecting the dynamics of the introduction of ICT, cloud technologies, big data analytics, etc., in the industrial sector. The results of the analysis showed the steady development of digitalization with the existing pronounced spatial asymmetry. The application of SFA made it possible to identify technological “frontiers” and reveal the hidden potential for increasing the effectiveness of digital investments at the regional level. The practical value of the study lies in its applicability for assessing the digital readiness of industrial enterprises for ecosystem adaptation, diagnosing regional digital disparities, and justifying targeted government policy measures aimed at strengthening the digital maturity and sustainability of the industrial sector. Full article

To enhance ecosystem services (ESs) benefits and promote ecological–economic–sociologic sustainability in highly urbanized regions such as the Beijing–Tianjin–Hebei (BTH) region, it is essential to assess the dynamic changes in ESs within these regions from a functional zoning perspective and to explore the interactions between ESs. This research delved into how ESs change over space and time, using land-use projections for 2035 based on Natural Development (ND), Ecological Protection (EP), Economic Construction (EC) scenarios. This study also took a close look at the interplay of these ESs across BTH and its five distinct functional zones: the Bashang Plateau Ecological Protection Zone (BS), the Northwestern Ecological Conservation Zone (ST), the Central Core Functional Zone (HX), the Southern Functional Expansion Zone (TZ), and the Eastern Coastal Development Zone (BH). We utilize the Multiple Ecosystem Service Landscape Index (MESLI) to assess the capacity to supply multiple ESs. Key results include the following: (1) Projected land-use changes for 2035 scenarios consistently show cropland and grassland declining, while forest and urbanland expand, though the magnitude of change varies by scenario. (2) Habitat quality, carbon storage, and soil conservation displayed a “high northwest–low southeast” gradient, opposite to water yield. The average MESLI value declined in all scenarios relative to 2020, with the highest value under the EP scenario. (3) Synergies prevailed between habitat quality, carbon storage, and soil conservation, while trade-offs occurred with water yield. These relationships varied spatially—for instance, habitat quality and soil conservation were weakly synergistic in the BS but showed weak trade-offs in the HX. These insights can inform management strategies in other rapidly urbanizing regions. Full article

In response to the dual challenge of global agricultural greening and digital transformation, it is imperative for agricultural colleges and universities in China to restructure talent cultivation models to support the development of sustainable and intelligent agriculture. This study combines literature analysis, case studies, and questionnaire surveys to identify misalignments between the current agricultural education system and industry needs. Focusing on educational objectives, curricula, practical training, and faculty expertise, the authors propose a novel four-dimensional collaborative cultivation model, “Objectives–Curriculum–Practice–Faculty”. This model centers on interdisciplinary course clusters (e.g., agricultural artificial intelligence and blockchain traceability), industry–academia-integrated training platforms (e.g., smart agriculture innovation centers), and a Dynamic Adjustment Mechanism (DCAM). To support the implementation of this model, this study advances policy recommendations from three perspectives. First, governments should accelerate reforms by providing special funding support and formulating legislation on industry–academia integration. Second, universities must establish early-warning response mechanisms. Third, enterprises must participate in developing education on ecosystems. This paper establishes both a theoretical framework and a practical pathway to transform agricultural education, offering significant referential value for global agricultural institutions adapting to technological revolutions. Full article

The photocatalytic degradation of Crystal Violet (CV) using ZnO-based nanomaterials presents a promising solution for addressing water pollution caused by synthetic dyes. This review highlights the exceptional efficiency of ZnO and its modified forms—such as doped, composite, and heterostructured variants—in degrading CV under both ultraviolet (UV) and solar irradiation. Key advancements include strategic bandgap engineering through doping (e.g., Cd, Mn, Co), innovative heterojunction designs (e.g., n-ZnO/p-Cu₂O, g-C₃N₄/ZnO), and composite formations with graphene oxide, which collectively enhance visible-light absorption and minimize charge recombination. The degradation mechanism, primarily driven by hydroxyl and superoxide radicals, leads to the complete mineralization of CV into non-toxic byproducts. Furthermore, this review emphasizes the emerging role of Artificial Neural Networks (ANNs) as superior tools for optimizing degradation parameters, demonstrating higher predictive accuracy and scalability compared to traditional methods like Response Surface Methodology (RSM). Potential operational challenges and future directions—including machine learning-driven optimization, real-effluent testing potential, and the development of solar-active catalysts—are further discussed. This work not only consolidates recent breakthroughs in ZnO-based photocatalysis but also provides a forward-looking perspective on sustainable wastewater treatment strategies. Full article

High-speed rail (HSR) makes a significant contribution to green innovation (GI), thereby supporting high-quality economic development. However, prior studies have mainly focused on the impact of HSR on regional innovation, ignored the influence on GI from the micro perspective, as well as the mechanism through which HSR affect GI. Using the data from manufacturing companies listed in Shanghai and Shenzhen stock exchanges during the period of 2004 to 2023, we treat HSR as a quasi-natural experiment and employ a multi-period difference-in-difference (DID) approach to explore the effect of HSR on GI. The regression results are presented as follows. (1) HSR significantly enhances GI in enterprises, and the results still hold after several robust checks. (2) HSR has a greater impact on the improvement of GI in lightly polluting SOEs of developed cities. (3) The mechanism by which HSR can improve GI is to promote the mobility of talent and alleviate financing constraints faced by enterprises. The policy recommendation is to focus on the heterogenous effect on GI in enterprises to promote the ability of sustainable development. Full article

The coordinated scheduling of diesel generators, photovoltaic (PV) systems, and energy storage systems (ESS) is essential for improving the reliability and resilience of islanded microgrids in remote and mission-critical applications. This review systematically analyzes diesel–PV–ESSs from an “energy symbiosis” perspective, emphasizing the complementary roles of diesel power security, PV’s clean generation, and ESS’s spatiotemporal energy-shifting capability. A technology–time–performance framework is developed by screening advances over the past decade, revealing that coordinated operation can reduce the Levelized Cost of Energy (LCOE) by 12–18%, maintain voltage deviations within 5% under 30% PV fluctuations, and achieve nonlinear resilience gains. For example, when ESS compensates 120% of diesel start-up delay, the maximum disturbance tolerance time increases by 40%. To quantitatively assess symbiosis–resilience coupling, a dual-indicator framework is proposed, integrating the dynamic coordination degree (ζ ≥ 0.7) and the energy complementarity index (ECI > 0.75), supported by ten representative global cases (2010–2024). Advanced methods such as hybrid inertia emulation (200 ms response) and adaptive weight scheduling enhance the minimum time to sustain (MTTS) by over 30% and improve fault recovery rates to 94%. Key gaps are identified in dynamic weight allocation and topology-specific resilience design. To address them, this review introduces a “symbiosis–resilience threshold” co-design paradigm and derives a ζ–resilience coupling equation to guide optimal capacity ratios. Engineering validation confirms a 30% reduction in development cycles and an 8–12% decrease in lifecycle costs. Overall, this review bridges theoretical methodology and engineering practice, providing a roadmap for advancing high-renewable-penetration islanded microgrids. Full article

The construction industry is one of the largest consumers of resources and a significant contributor to environmental degradation in Europe, accounting for 50% of natural resource use, 34% of waste generation, and 5–12% of greenhouse gas emissions. In response to growing environmental pressures and regulatory demands, the sector needs to adopt sustainable material alternatives. This study examines the potential adoption of rice straw ash in the European construction sector. The research applies a PRISMA-based systematic literature review, integrated with the Multi-Level Perspective (MLP) framework, PESTLE, and SWOT analyses to provide a comprehensive assessment of the socio-technical dynamics influencing its adoption. The findings identify barriers including the absence of standards, fragmented supply chains, and inconsistent material quality. However, it highlights strategic opportunities such as the declining availability of conventional SCMs, alignment with the EU’s regulations and circular economy principles, and growing public awareness of sustainable materials. The study concludes that advancing the transition to RSA will require regulatory support, the development of standards, and coordinated collaboration among stakeholders to achieve large-scale implementation. By integrating multi-dimensional transition factors, this research contributes actionable insights for advancing sustainable material adoption. Full article