Search Results (1,310)

Hydrogen production and storage constitute a promising technology in the path towards a global energy scenario featured by renewable energy penetration, decarbonization, sustainable development and resilience. In particular, so-called green hydrogen is generated from renewable energy sources, generally produced in an electrolyzer by means of Proton Exchange Membrane (PEM) water electrolysis. To make these expectations reality, experimental and real-world facilities are required, dealing with challenging aspects such as new technologies and integration of equipment. Thus, this paper presents the implementation and operation of a pilot plant for green hydrogen generation and storage based on a commercial 30 kW PEM electrolyzer. The renewable source is a photovoltaic generator of 60.6 kW which supplies the hydrogen generator through an inverter. Furthermore, the deployment of a supervisory system entirely based on open-source technologies is reported. The equipment employed and the supervisory system developed in this work exhibit a level of complexity and scale that is uncommon in the literature. Therefore, this article is a novelty in the literature and aims to contribute to the advancement of green hydrogen production and storage by providing experimental data and descriptions of a fully functional plant operating under real-world conditions. The achieved results under real operation conditions prove the successful implementation of the pilot plant as well as the suitability of the supervisory system to effectively track the most relevant variables. Full article

This study examines whether China’s Ecological Civilization Demonstration Zones (ECDZs) promote urban green total factor productivity (GTFP). Using panel data for 282 prefecture-level cities from 2011 to 2022, when six batches of policy pilots were implemented, the paper employs a super-efficiency SBM model to estimate GTFP and a difference-in-differences (DID) model to identify the policy effects. The results indicate that ECDZs significantly improve urban GTFP. Specifically, the baseline estimates show that the implementation of ECDZs increases GTFP by approximately 6.52% relative to the sample means. Potential transmission channels further show that technological innovation and industrial structure upgrading are important channels through which ECDZs promote green productivity growth. In addition, significant regional and city-type heterogeneity is observed. The positive policy effects are more pronounced in central regions and in non-resource-based cities, whereas the effects are relatively weak in eastern regions, western regions, and resource-based cities. These findings suggest that differences in economic foundations, industrial structures, and innovation capacities may influence the effectiveness of ECDZs. Overall, this study provides empirical evidence on the green development effects of ECDZs and offers policy implications for improving differentiated environmental governance and promoting high-quality sustainable development in China. Full article

Background: This systematic review evaluates the evidence on sustainable practices in dentistry. It focuses on effective measures, innovative technologies, strategies for reducing the carbon footprint, life cycle assessments (LCA), attitudes toward “green” dentistry, and educational approaches. Methods: A systematic search was conducted in five databases (Cochrane Library, Embase, LILACS, MEDLINE via PubMed, and Scopus) without language restrictions in accordance with PRISMA. The review was registered in PROSPERO (CRD420251056821). Results: A total of 2395 records were identified; after removing 394 duplicates, 2001 remained for screening. After title and abstract screening, 154 full-text articles were evaluated, of which 51 studies were included. The included studies addressed life cycle assessments of dental materials, sustainable clinical practices, and educational measures. Environmentally friendly materials and procedures, such as reusable personal protective equipment and water-saving technologies, demonstrate significant potential for reducing environmental impact. Despite generally high acceptance among dentists and patients, implementation is often limited by financial and knowledge-related barriers. Conclusions: The implementation of sustainable materials and procedures is crucial for reducing environmental impact. Equally important are the integration of ecological content into education and appropriate financial and political frameworks to promote sustainable dentistry. Full article

This study uses data of A-share listed companies in Shanghai and Shenzhen from 2020 to 2024. We manually collect green procurement lists from official government procurement websites and match them with firm samples. Employing the two-way fixed effects model and the Bootstrap method, this paper empirically examines the impact of green public procurement on corporate carbon reduction. The results show that green public procurement significantly improves firms’ carbon reduction performance. Mechanism analysis indicates that AI adoption and government green subsidies further strengthen this effect. Heterogeneity tests reveal that the impact is more pronounced for state-owned enterprises, high-tech firms and enterprises in regions with advanced digital economies. Accordingly, we propose suggestions including strengthening the driving role of green procurement, promoting coordination between green procurement and digital technology, optimising the allocation of green funds, and implementing targeted differentiated incentives. This research helps clarify the internal mechanism of green public procurement on carbon emission reduction performance and provides references for improving relevant practices in carbon emission reduction. Full article

This study aims to investigate the role of artificial intelligence (AI) for strategically steering corporate environmental sustainability, which remains underexplored in the context of emerging economies. Drawing on the resource-based perspective and Dynamic Capabilities Theory, we argue that the adoption of AI also represents an aspect associated with an organizational capability on a higher rung that can enhance performance towards environmental goals. We further examine a mediating framework through which the effect of AI on environmental sustainability is transmitted through firms’ green governance structures. Using a longitudinal panel dataset of 75 publicly listed industrial firms operating in six Gulf Cooperation Council (GCC) countries from 2018 to 2025, we used fixed-effects regression analysis alongside bootstrapped mediation analysis. In fact, the empirical evidence suggests that AI adoption is positively and significantly associated with environmental sustainability. We also show that green governance partially mediates this relationship implying that AI-based strategic investment is better realized in terms of measurable environmental impacts when it is embedded within sound board-level ESG governance systems. As such, the findings provide an important empirical perspective on the AI–sustainability nexus in the GCC industrial landscape and also explain the empirical role played by green governance in implementing technology, constituting technological enablers for the transformation of technological capabilities to concrete environmental outcomes. The study will also provide policymakers and managers with actionable insights on the potential for digital transformation to act as a strategic enabler of sustainable development in resource-intensive industries. Full article

Green Supply Chain Management (GSCM) and sustainable economic development are two areas that have been studied extensively by scholars. However, there continues to exist a lack of cohesion or integration across academic fields regarding how GSCM can act as a catalyst for economic sustainability. This systematic literature review attempts to create a cohesive body of knowledge by exploring the drivers, barriers, and outcome measures associated with GSCM specifically within the context of creating sustainable economic growth in the long term. A structured literature review approach was used; this included conducting an extensive search of all relevant articles using multiple databases, followed by a thorough review and thematic analysis based upon the dimensions outlined above. The results indicate that GSCM is primarily influenced by the pressure of regulatory requirements and expectations of stakeholders. Financial constraints and technology gaps remain significant obstacles to the effective implementation of GSCM. Additionally, our analyses indicate that GSCM will enhance both environmental and economic performance when it is practiced with circular economy strategies and digital technologies such as AI and big data. The review shows that small- to medium-sized enterprises and firms in emerging economies face different practicalities than other types of organizations in terms of implementing GSCM strategically. However, SMEs and firms in emerging economies may benefit proportionally more than others from adopting GSCM strategically. Industry-specific case studies show that the success of GSCM practices varies widely depending on the sector; therefore, consideration of context is required. Additionally, the various theoretical frameworks discussed throughout the literature have developed from linear models towards more dynamic system-based models, indicating a developing discipline. In conclusion, we find that GSCM does not solely serve as an operational tool; rather, it acts as a strategic enabler of sustainable economic development, provided that it is implemented appropriately relative to organizational and regional context. Full article

This study examines whether digital infrastructure contributes to sustainable development by improving green total factor productivity (GTFP)—a comprehensive measure that jointly evaluates economic output and environmental performance—in the Yangtze River Economic Belt. We exploit the staggered implementation of the “Broadband China” pilot policy as a quasi-natural experiment and estimate its effects using panel data for 107 prefecture-level cities from 2010 to 2022. The empirical strategy combines a staggered difference-in-differences design with an event study framework. The baseline results show that the average treatment effect for the full sample is positive but not statistically significant at conventional levels under standard TWFE estimation; however, the Sun–Abraham interaction-weighted estimator confirms a significant positive effect (ATT = 0.080, p < 0.05), and the Goodman-Bacon decomposition shows that the TWFE estimate is driven primarily by clean comparisons (91% weight, 0% negative weights). Further analysis reveals substantial regional heterogeneity. The estimated effect is significantly positive in the central region (0.171, p < 0.05), positive but not significant in the eastern region (0.097), and negligible in the western region (−0.042). A similar pattern emerges across income groups: digital infrastructure generates significant gains in GTFP in high- and middle-income cities, whereas the effect is not identifiable in low-income cities. These results remain robust to propensity score matching, placebo tests, alternative specifications, and alternative measures. Exploratory mechanism analysis provides limited evidence that technological innovation and industrial upgrading mediate the effect of digital infrastructure on GTFP within the sample period, though the causal interpretation of mediation is constrained by the sequential ignorability assumption. The findings suggest that the environmental returns to digital infrastructure depend on local complementary conditions, especially human capital, institutional capacity, and industrial foundations. These results imply that digital infrastructure policy should be differentiated across regions rather than implemented uniformly. By demonstrating that the environmental returns to digital infrastructure are conditional on local complementary conditions, this study contributes to the sustainability literature by providing a framework for quantifying and monitoring the sustainability impacts of digital infrastructure policies, with implications for sustainable development strategies in developing economies. Full article

Driven by artificial intelligence, multi-source sensing, agricultural robots and big data technologies, global agriculture is rapidly upgrading from precision agriculture and agriculture 4.0 to agriculture 5.0. Artificial intelligence has evolved from a single diagnostic tool to an intelligent system that integrates the “perception-decision-execution” process throughout. It is widely applied in crop phenotype analysis, remote sensing monitoring, yield prediction, and autonomous operation of intelligent equipment, etc. This article takes the framework of “intelligent perception-cognitive decision-autonomous execution” to systematically review the core technologies, typical applications, and frontier directions of agricultural artificial intelligence. It focuses on introducing the progress of key technologies such as three-dimensional phenotype, hyperspectral remote sensing, multimodal fusion, and causal machine learning, as well as their value in improving resource utilization efficiency, enhancing climate resilience, and supporting field precision management. At the same time, it points out that current agricultural AI still faces practical bottlenecks such as insufficient generalization ability of models, scarce data and high annotation costs, difficulties in edge deployment, barriers in multi-source data integration, and weak interpretability and engineering reliability. Future research will focus on the construction of closed-loop autonomous farms, the collaboration of agricultural large models and intelligent agents, the construction of data centers and AI and data infrastructure, and the development of green and low-cost AI research. This will provide support for the technological innovation and industrialization implementation of agricultural artificial intelligence. Full article

Waste cooking oils (WCO) are large-scale residual streams from domestic and industrial food processing. Their improper disposal poses severe environmental risks, yet their integration into the oleochemical sector offers a strategic opportunity for the green transition by substituting fossil-based feedstocks. This systematic review provides a comprehensive assessment of WCO valorization as a sustainable precursor for high-value products, specifically biopolymers, bioplasticizers, and biolubricants. The study followed the PRISMA 2020 guidelines, searching PubMed, Scopus, and MDPI databases (up to September 2025). The search strategy utilized combinations of keywords present in the title. Inclusion criteria focused on peer-reviewed chemical and biotechnological conversion pathways published in English within the last decade. Studies addressing biofuel production, patents, and review were excluded. Screening, data extraction, and qualitative risk of bias assessment, centered on experimental reproducibility and reporting transparency, were performed independently by multiple reviewers. From an initial pool of 2637 records, 87 studies met the eligibility criteria. The analysis reveals that polyhydroxyalkanoates (PHAs) represent the most extensively researched pathway, followed by WCO-derived epoxides and innovative biolubricant formulations. While several studies report high conversion yields under optimized conditions, the transition from bench-scale to industrial implementation remains hindered by the heterogeneous composition of WCO and a lack of standardized pre-treatment protocols. WCO valorization shows transformative potential for the circular economy, offering a dual benefit of waste mitigation and sustainable material synthesis. However, future research must address scalability challenges and feedstock variability. This review identifies emerging trends and provides a roadmap for the industrial adoption of WCO-based processes in the framework of clean technologies. Full article

Port integration reforms constitute an important institutional arrangement for promoting green development in the shipping sector and achieving China’s carbon peaking and carbon neutrality goals. Assessing their carbon-mitigation effect is crucial for improving the governance framework of port integration and promoting high-quality port development. Using panel data for 55 Chinese port cities from 2011 to 2022, this study exploits the staggered implementation of port integration strategies as a quasi-natural experiment and applies a multi-period Difference-in-Differences (DID) approach to estimate their effects on port carbon emissions. The results indicate that port integration reforms significantly reduce carbon emissions, implying that integration acts as a substantive driver for low-carbon transformation. Heterogeneity analysis shows that the emission-abatement effect is stronger for ports outside the Yangtze River Economic Belt, coastal and southern ports, large-scale and small-scale ports, regions with weaker environmental regulation, cities with more advanced industrial structures, and major national hub ports. In contrast, the policy effect is relatively muted for medium-sized ports, highly regulated regions, cities with less advanced industrial structures, and non-core hub ports, where port integration delivers merely weak marginal emission reduction effects. Further mechanism tests reveal that green technological innovation plays a certain mediating role. This study contributes to the literature by providing dynamic causal evidence on how port governance reforms shape green development outcomes. It also offers policy implications for designing differentiated port integration strategies that align with regional development conditions and national low-carbon transition objectives. Full article

This study investigates the relationship between renewable energy (RE) expansion and economic diversification in Egypt over 1990–2023 using a nonlinear autoregressive distributed lag (NARDL) framework. Egypt’s fossil fuel share stands at approximately 93% of primary energy supply, yet the country has committed to a 42% renewable electricity target by 2035. Despite quadrupling utility-scale RE capacity from 2.8 GW to 11.2 GW between 2015 and 2023, the Economic Diversification Index (EDI) has remained broadly stagnant. The bounds test confirms long-run cointegration (F = 6.760), exceeding small-sample critical values at the 1% level. Long-run estimates reveal that positive RE shocks are associated with lower diversification (θ⁺ = −0.571, p = 0.035) and negative shocks exhibit a statistically similar adverse effect (θ⁻ = −0.271, p = 0.024). Oil rents exhibit a positive long-run association (β = 0.145, p = 0.003). The error-correction term (−0.569) indicates approximately 57% annual adjustment. The Wald test provides marginal evidence against long-run symmetry (F = 2.999, p = 0.097). To complement the Granger causality analysis and address small-sample concerns, we additionally implement the Toda and Yamamoto augmented VAR procedure, which confirms robust unidirectional temporal precedence from LRE to LEDI (χ² = 23.48, p < 0.001) without reverse feedback (χ² = 2.25, p = 0.133). These patterns are interpreted through the lens of the Green Dependency Paradox—a conceptually distinct framework characterized by three mechanisms absent from classical resource curse theory: technology-mediated capital flight, procurement-induced deindustrialization, and policy-reversible lock-in operating under conditions of high import content, absent local content mandates, and fragmented industrial policy coordination. A tri-phase, evidence-grounded policy framework is proposed. All findings are explicitly conditional on Egypt’s current institutional context. Full article

This review paper presents a comprehensive synthesis of current scientific knowledge on the integration of low-emission technologies into airport operational models. Attention is also given to the role of artificial intelligence techniques in predicting environmental risks, optimizing energy system design, and enhancing operational safety. The primary objective of the study is to evaluate the synergy between renewable energy sources (solar and wind energy) and emerging propulsion technologies in aviation (hydrogen and electrification) from the perspective of safety and operational stability. The methodology is based on a systematic review of 78 scientific studies identified in the Scopus and Web of Science databases. The analysis identifies critical technical and operational barriers, including electromagnetic interference caused by wind turbines, optical hazards associated with photovoltaic systems, and stability challenges in airport microgrids under peak loads resulting from the charging of electric aircraft. Particular attention is given to the safety of hydrogen infrastructure, where findings from the literature indicate the need to revise separation distances and highlight the potential reduction of airport stand capacity by 5% to 16%. The study synthesizes these findings into a strategic framework for “Smart Green Airports”, proposing solutions such as adaptive infrastructure design, the deployment of predictive models based on artificial intelligence, and the implementation of inherently safe energy storage systems. The paper concludes that achieving airport energy self-sufficiency while maintaining the integrity of flight operations is feasible only through the holistic integration of technical measures, simulation-based planning, and strict compliance with updated safety regulations. Full article

The detection technology of crop diseases and pests is transitioning from single sensor monitoring to intelligent perception and multimodal fusion. This paper follows the PRISMA 2020 standard and systematically reviews the relevant core literature. This paper systematically summarizes the development history of spectral sensing technology and analyzes the physical mechanisms of hyperspectral and multispectral imaging in early identification of crop diseases. The focus is on the architectural evolution of deep learning models, including lightweight convolutional neural networks (CNNs), vision transformers (ViTs) with long-range dependency modeling capabilities, and the efficient computing state space model Mamba. In addition, the research progress of spatial spectral joint learning, heterogeneous data fusion, and vision-language models (VLMs) in improving system robustness and interpretability are introduced. By synthesizing the integrated applications of UAV remote sensing, Internet of Things (IoT) edge computing and intelligent robots in staple and cash crops, this paper summarizes the implementation of the integrated system of perception, decision-making and execution. To address the issues of insufficient cross-domain generalization ability and uneven allocation of computing resources in existing models, this paper provides perspectives on the future development of agricultural artificial intelligence (AI) towards foundation model-driven, edge-intelligent collaboration, and green sustainable direction, which can provide theoretical reference for engineering applications in the field of intelligent plant protection. Full article

Climate change has become a global challenge that cannot be ignored in the pursuit of development. The implementation of the Low-Carbon City Pilot Policy (LCCPP) represents an approach to addressing environmental issues and promoting sustainable development. Investigating the impact of this policy on urban compactness (UC) is therefore crucial for advancing sustainable development. Using a staggered DID model with panel data from 108 cities in the Yangtze River Economic Belt (YREB) over the period 2008–2023, along with robustness checks and spatial analysis, this study evaluates LCCPP’s impact on UC. The main findings are as follows: (1) The LCCPP has a significant positive effect on UC. (2) The policy enhances UC primarily through two channels: intensifying infrastructure development and promoting green technology innovation. (3) The promoting effect of the LCCPP is stronger in cities located in the upper reaches of the Yangtze River, within urban agglomerations, and in non-resource-dependent cities. (4) The policy reduces UC in neighboring non-pilot cities, leading to an overall decline in regional compactness. This study provides an important reference for exploring pathways toward sustainable development. Full article

Traditional coal mining methods have led to prominent issues of coal resource waste and large-scale solid waste emissions. The integrated “excavation–backfilling–retention” mining technology for inter-section coal pillars and gate roads is one of the key technologies to solve these problems. However, the excavation and mining process associated with this technology imposes higher requirements on the ventilation system. Aiming at addressing the ventilation challenges existing during the implementation of the “excavation–backfilling–retention” method, research on ventilation safety assurance technology for inter-section coal pillars was carried out. Using COMSOL5.5 software, a full-stage ventilation system design model was constructed, adopting a ventilation mode that combines full-air-pressure ventilation with auxiliary local ventilation. The dynamic variation characteristics of the ventilation system under the “excavation–backfilling–retention” method and its capability to prevent and control the risks of O₂ and CO gas accumulation and coal spontaneous combustion were studied. The results show that during the bypass excavation period, the air supply from the auxiliary fan is sufficient, and during the excavation period for the two gate roads, due to the increased ventilation distance, insufficient airflow occurs near the heading face, accompanied by temperature rise, O₂ concentration decrease, and local CO accumulation, posing risks of coal spontaneous combustion and toxic gas accumulation. During the inter-section coal pillar excavation period and the cyclic operation period, after the full-air-pressure ventilation system is established, the airflow becomes stable, ventilation resistance decreases, and both temperature and gas concentrations are controlled within safe limits. However, in the corner areas, auxiliary local ventilation measures are still required due to insufficient O₂ and CO accumulation. The study verifies the feasibility and safety of the integrated “excavation–backfilling–retention” ventilation system, providing a safe ventilation approach for the integrated mining method and supporting the green mining of coal mines and the synergistic development of coal-based solid waste resource utilization. Full article