Search Results (3,851)

The increasing need to regenerate public housing stock highlights the importance of adopting integrated evaluation tools capable of supporting transparent, sustainable, and public value-oriented investment decisions. This study compares two alternative intervention strategies—renovation with extension and demolition followed by reconstruction—by applying a Cost–Benefit Analysis (CBA) model developed in two phases. In the first phase, the analysis focuses on social benefits, with the aim of assessing their contribution to collective well-being. The second phase incorporates potential energy-related benefits, estimated on the basis of performance improvements associated with the two design scenarios. The results demonstrate that the integrated consideration of economic, social, and energy–environmental dimensions affects the relative performance differences between the examined strategies, offering a more comprehensive evaluation framework than conventional approaches based solely on monetary costs. The proposed model, which is replicable in Mediterranean contexts, contributes to the ongoing international debate on ex ante evaluation tools and provides operational insights to support urban regeneration policies oriented towards more effective, equitable, and policy-consistent solutions, in line with the objectives of the European Green Deal and the 2030 Agenda. The two-phase structure allows decision-makers to distinguish between short-term social effects and long-term energy-related benefits, offering a transparent support tool for public investment choices under fiscal constraints. Full article

Under the background of accelerating global transitions towards low-carbon development, digital intelligence transformation (DIT) has become a critical force that helps companies overcome green technological constraints and translate external green pressures into substantive green innovation. Taking the establishment of China’s NAIIDTZs as a quasi-natural experiment, this study investigates the impact of DIT on corporate green innovation (CGI) from an internal decision-making perspective. Based on a panel dataset of 19,440 samples from Chinese A-share listed companies during 2012–2023, our findings show that DIT significantly enhances both the quantity and quality of CGI. Mechanism analyses indicate that DIT promotes CGI’s quantity through increased R&D human capital input, while improving CGI’s quality through managerial myopia reduction. Heterogeneity analyses further reveal that the positive effects of DIT on CGI are particularly pronounced in firms operating under fierce market competition, in high industrial technological intensity, and in eastern regions. Furthermore, we find that CGI exerts a lagged effect on carbon emission reduction performance, while the effect of CGI’s quality is stronger than that of CGI’s quantity. These findings extend the dynamic capacity theory to digitalization and provide practical and policy implications for promoting CGI through digital intelligence development. Full article

Accurate cropland classification within smallholder farming systems is essential for effective land management, efficient resource allocation, and informed agricultural decision-making. This study evaluates cropland classification performance using Red, Green, Blue (RGB) and multi-spectral (blue, green, red, red-edge, near-infrared) unmanned aerial vehicle (UAV) imagery. Both datasets were derived from imagery acquired using a MicaSense Altum sensor mounted on a DJI Matrice 300 UAV. Cropland classification was performed using machine learning algorithms implemented within the Google Earth Engine (GEE) platform, applying both a non-binary classification of five land cover classes and a binary classification within a probabilistic framework to distinguishing cropland from non-cropland areas. The results indicate that multi-spectral imagery achieved higher classification accuracy than RGB imagery for non-binary classification, with overall accuracies of 75% and 68%, respectively. For binary cropland classification, RGB imagery achieved an area under the receiver operating characteristic curve (AUC–ROC) of 0.75, compared to 0.77 for multi-spectral imagery. These findings suggest that, while multi-spectral data provides improved classification performance, RGB imagery can achieve comparable accuracy for fundamental cropland delineation. This study contributes baseline evidence on the relative performance of RGB and multi-spectral UAV imagery for cropland mapping in heterogeneous smallholder farming landscapes and supports further investigation of RGB-based approaches in resource-constrained agricultural contexts. Full article

The non-thermal plasma-driven cascade process for CO₂-to-methanol conversion shows significant potential in the field of green methanol synthesis. This process innovatively couples a plasma activation module with a catalytic synthesis module via a multi-stage pressurization device, establishing an efficient two-step pathway that converts CO₂ into methanol via a CO intermediate. Such an arrangement establishes an energy conversion system characterized by both low carbon emissions and high efficiency. This work involved an initial technical evaluation employing a custom-built, lab-scale apparatus. The optimum parameters determined through this assessment were a plasma input voltage of 40 V combined with a subsequent reaction temperature of 240 °C. Operation at these specified parameters yielded a CO₂ conversion of 48%, with the methanol selectivity and production rate reaching 40% and 502 g_MeOH·kg−1 cat·h⁻¹, respectively. Furthermore, industrial-scale process design and scale-up were performed, accompanied by process simulation using Aspen Plus and a subsequent techno-economic evaluation. The results indicate that, compared to the conventional direct CO₂ hydrogenation process, the proposed cascade route can reduce the capital investment by approximately 17%. Full article

Despite substantial growth in eco-innovation (EI) research, most studies rely on cross-sectional data, limiting understanding of the temporal dynamics of EI and its determinants under varying macroeconomic conditions. This study addresses this gap by analysing panel data from Spanish manufacturing firms across three phases of the business cycle: pre-crisis expansion (2004–2007), the global financial crisis (2008–2013), and recovery (2014–2016). We investigate the drivers of two distinct types of eco-innovation: efficiency EI (energy and material savings) and environmental EI (reducing environmental harm), focusing on the role of regulation, institutional interventions, and firm-level innovation capacities. Using a random-effects panel probit model that accounts for unobserved firm heterogeneity, we examine how these drivers operate across different macroeconomic contexts. Our findings reveal that regulation consistently fosters EI, while the influence of subsidies, R&D capacity, and collaborative networks is more context-dependent, particularly during economic downturns. The results highlight the cumulative, path-dependent, and cyclical nature of EI, providing novel insights into the conditions that enable firms to sustain green innovation over time. Drivers of eco-innovation differ systematically between efficiency- and environment-oriented strategies, and these differences remain stable over the business cycle, implying distinct underlying mechanisms and policy implications. Accordingly, policy design—particularly during economic downturns—should distinguish between reinforcing incentives for internal efficiency improvements and sustaining regulatory and financial support for environmental EI. Full article

Despite European and international regulatory frameworks promoting circular economy principles, sustainability in the furniture sector is still challenged by the limited access to reliable information about circular materials for designers, manufacturers, and waste managers in the Made-in-Italy furniture ecosystem. This research develops a digital infrastructure to address these information gaps through mixed methodology, combining desk research on regulatory frameworks and existing platforms; field research involving stakeholder mapping and interviews with designers, manufacturers, and waste managers; and the experimental development of AI-enhanced digital tools. The result integrates a web-based platform for circular materials with a CAD plugin supporting real-time sustainability assessment. As AI-assisted data entry showed a reduced form completion time while maintaining accuracy through human verification, testing also revealed how the system effectively bridges knowledge gaps between stakeholders operating in currently siloed value chains. The platform is a critical step in enabling designers to incorporate circular materials during the early design stages, while providing manufacturers access to verified punctual sustainability data compliant with mandatory Green Public Procurement criteria. Beyond the development of an innovative digital tool, the study outlines a corresponding operational model as a practical framework for strengthening the transition toward a circular economy in the Italian furniture industry. Full article

Rapid urbanization and climate change have intensified flood risk and ecological degradation along urban riverfronts. Recent literature suggests that combining green and grey infrastructure can enhance resilience while delivering ecological and social co-benefits. This study analyzes and compares five riverfront projects in China and Spain, assessing how their tactic mixes operationalize three urban flood-resilience strategies—Resist, Delay, and Store/reuse—and how these mixes translate into ecological, social, and urban impacts. A six-phase framework was applied: (1) literature review; (2) case selection; (3) categorization of resilience strategies; (4) systematization and typification of tactics into green vs. grey infrastructure; (5) percentage analysis and qualitative matrices; and (6) comparative synthesis supported by an alluvial diagram. Across cases, Delay emerges as the structural backbone—via wetlands, terraces, vegetated buffers, and floodable spaces—while Resist is used selectively where exposure and erodibility require it. Store/reuse appears in targeted settings where operational capacity and water-quality standards enable circular use. The comparison highlights hybrid, safe-to-fail configurations that integrate public space, ecological restoration, and hydraulic performance. Effective urban riverfront resilience does not replace grey infrastructure but hybridizes it with nature-based solutions. Planning should prioritize Delay with green systems, add Resist where necessary, and enable Store/reuse when governance, operation and maintenance, and water quality permit, using iterative monitoring to adapt the green–grey mix over time. Full article

The growing pressure on industrial organizations to align digital transformation with sustainability objectives has intensified the need to systematically understand the role of emerging digital technologies in sustainable industrial development. The accelerated digitalization of industrial ecosystems has positioned the Internet of Things (IoT) as a critical enabler of corporate sustainability within Industry 4.0. However, evidence on how IoT contributes to environmental, social, and economic performance remains fragmented. This study conducts a systematic literature review following PRISMA 2020 guidelines to consolidate the scientific advances linking IoT with sustainable corporate management. The search covered 2009–2025 and included publications indexed in Scopus, EBSCO Essential, and MDPI, identifying 65 empirical and conceptual studies that met the inclusion criteria. Bibliometric analyses—such as keyword co-occurrence mapping and temporal heatmaps—were performed using VOSviewer v. 2023 to detect dominant research clusters and emerging thematic trajectories. Results reveal four domains in which IoT significantly influences sustainability: (1) resource-efficient operations enabled by real-time sensing and predictive analytics; (2) energy optimization and green digital transformation initiatives; (3) circular-economy practices supported by data-driven decision-making; and (4) the integration of IoT with Green Human Resource Management to strengthen environmentally responsible organizational cultures. Despite these advances, gaps persist related to Latin American contexts, theoretical integration, and longitudinal assessment. This study proposes a conceptual model illustrating how IoT-enabled technologies enhance corporate sustainability and offers strategic insights for aligning Industry 4.0 transformations with the Sustainable Development Goals (SDGs), particularly SDGs 7, 9, and 12. Full article

Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus, is driven by a tri-component system involving the pinewood nematode, Monochamus spp. beetle vectors, and susceptible pine hosts. Chemical control remains a scenario-dependent option for emergency suppression and high-value protection, but its deployment is constrained by strong regional regulatory and practical differences. In Europe (e.g., Portugal and Spain), field chemical control is generally not practiced; post-harvest phytosanitary treatments for wood and wood packaging rely mainly on heat treatment, and among ISPMs only sulfuryl fluoride is listed for wood treatment with limited use. This review focuses on recent progress in PWD chemical control, summarizing advances in nematicide discovery and modes of action, greener formulations and delivery technologies, and evidence-based, scenario-oriented applications (standing-tree protection, vector suppression, and infested-wood/inoculum management). Recent studies highlight accelerated development of target-oriented nematicides acting on key pathways such as neural transmission and mitochondrial energy metabolism, with structure–activity relationship (SAR) efforts enabling lead optimization. Formulation innovations (water-based and low-solvent products, microemulsions and suspensions) improve stability and operational safety, while controlled-release delivery systems (e.g., micro/nanocapsules) enhance penetration and persistence. Application technologies such as trunk injection, aerial/UAV operations, and fumigation/treatment approaches further strengthen scenario compatibility and operational efficiency. Future research should prioritize robust target–mechanism evidence, resistance risk management and rotation strategies, greener formulations with smart delivery, and scenario-based exposure and compliance evaluation to support precise, green, and sustainable integrated control together with biological and other sustainable approaches. Full article

In recent years, green hydrogen production via water electrolysis driven by renewable energy sources has garnered increasingly significant attention. Among the various water electrolysis technologies, proton-exchange membrane water electrolysis (PEMWE) distinguishes itself owing to the unique advantages, including the compact architecture, high efficiency, rapid dynamic response, and high purity of the generated hydrogen. The membrane electrode assembly (MEA) serves as the core component of a PEM electrolyzer. And only a high-performance and stable MEA can provide a reliable platform for investigating the mass transport behavior within the porous transport layer (PTL). In this study, the MEA fabrication method was optimized by varying the ionomer-to-carbon (I/C) ratio, coating strategy, and anode Ir mass loading. As a result, the cell voltage was reduced from 1.679 V to 1.645 V at 1.0 A cm⁻², with a small degradation of 1.3% over 70 h of operation. Based on the optimized MEA, the effects of the structure and porosity of PTL on the mass transport behavior were further analyzed. After the PTL parameter optimization, the cell voltage was further reduced to 1.630 V at 1.0 A cm⁻², while a high-speed camera captured bubble dynamics in real time, showing the fast detachment of small oxygen bubbles. The integrated electrochemical and visualization results provide a useful guideline to designing both MEA and PTL for efficient PEMWE. Full article

Rapid economic growth has directly driven up energy demand, and the gradual depletion of traditional fossil fuels has severely hindered sustainable development. Developing green and efficient geothermal exploitation technologies constitutes a crucial measure for tackling this sustainable development issue. This paper presents a field test associated with a clean energy system conducted in the Guanzhong Basin, China, with the core component of a coaxial casing deep geothermal well. A distributed temperature sensing system (DTS system) with over 3000 m-depth optical fiber installed and adopted to monitor near-wellbore formation temperature changes. Combining information on the inlet/outlet water temperature and flow rate monitored by an integrated temperature–pressure monitoring system, the heat transfer patterns during the operation of the deep geothermal well are deeply investigated. The research results demonstrate that a higher operation parameter of flow rates has a significant increasing effect on the heat transfer capacity of heat exchangers for coaxial casing deep geothermal wells. Although the increase in inlet temperature has minimal effect on the outlet temperature, it leads to a continuous decline in heat transfer capacity. In addition, as heat exchange duration extends, the geothermal gradient of the near-wellbore formation progressively declines. Full article

The increasing momentum of agricultural digital transformation and green development necessitates investigations into how farmers’ digital literacy influences their engagement in green production behaviours, which is critical for achieving the high-quality development of modern agriculture. Utilising primary survey data collected from farmers in rural areas of Guizhou Province, China, this study investigated how digital literacy affects farmers’ green production behaviours. The findings are as follows: (1) Digital literacy exerts a significant positive impact on farmers’ adoption of green production behaviours. Regarding the hierarchical effect, the order of influence is as follows: digital security awareness > basic digital skills > digital application and innovation. (2) The facilitating effect of digital literacy is primarily achieved through two pathways: the peer effect and the guidance effect. (3) Farmers with higher education levels are more impacted by digital literacy than farmers with lower education levels. (4) The impact of digital literacy is more positively significant for young and older farmers than for middle-aged groups. Based on these research findings, it is recommended that future policy formulation and technology extension efforts should prioritise support for specific regions and groups, such as mountainous areas, small-scale operations, low-education backgrounds, and the elderly. Such targeted approaches are crucial for encouraging wider adoption of green production behaviours among farmers. Full article

Alkaline water electrolysis remains one of the leading and most mature technologies for large-scale hydrogen production. Its advantages stem from the use of inexpensive, earth-abundant materials and well-established industrial deployment, yet the technology continues to face challenges, including sluggish hydrogen evolution reaction (HER) kinetics and energy-efficiency limitations compared with acidic electrolysis systems. This review provides a comprehensive overview of the fundamental principles governing alkaline electrolysis, encompassing electrolyte chemistry, electrode materials, electrochemical mechanisms, and the roles of overpotentials, cell resistances, and surface morphology in determining system performance. Key developments in catalytic materials are discussed, highlighting both noble-metal and non-noble-metal electrocatalysts, as well as advanced approaches to surface modification and nanostructuring designed to enhance catalytic activity and long-term stability. Particular emphasis is placed on the emerging strategy of in situ ionic activation, wherein transition-metal ions and oxyanions are introduced directly into the operating electrolyte. These species dynamically interact with electrode surfaces under polarization, inducing real-time surface reconstruction, improving water dissociation kinetics, tuning hydrogen adsorption energies, and extending electrode durability. Results derived from polarization measurements, electrochemical impedance spectroscopy, and surface morphology analyses consistently demonstrate that ionic activators, such as Ni–Co–Mo systems, significantly increase the HER performance through substantial increase in surface roughness and increased intrinsic electrocatalytic activity through synergy of d-metals. By integrating both historical context and recent research findings, this review underscores the potential of ionic activation as a scalable and cost-effective way toward improving the efficiency of alkaline water electrolysis and accelerating progress toward sustainable, large-scale green hydrogen production. Full article

This paper introduces a mathematical model to assess the polluting impact of the decarbonization options for medium-sized High-Speed Crafts in the EU, and their consequences in terms of Market-Based Measure costs and Goal-Based Measure compliance under expected regulatory scenarios. This model is applied to a particular European High-Speed Craft operating in the Canary Islands. Considering slow steaming along with High Speed Craft’s retrofitting with alternative technologies for its electricity supply, we conclude that green H₂ fuel Cells provide the greatest environmental advantage by comparison with slow steaming alone, achieving a 6.96% improvement in emissions and savings under European Market-Based Measures of 39.76% by 2033. The expected regulative progression involves a 5.90% improvement in the Market-Based Measure costs’ convergence with the actual pollution impact of High-Speed Crafts. The findings warn about the pressing need to review the implementation of On-Shore Power Supply emissions into the Fuel EU fines, and about a concerning pull effect for the most polluting European High-Speed Crafts are moved towards the outermost regions of the EU due to their permanent exceptions from the application of the European Market-Based Measures. Full article

The abrupt COVID-19 lockdown in early 2020 offered a unique natural experiment to examine vegetation productivity responses to sudden declines in human activity. Although vegetation often responds to environmental changes with time lags, how such lags operate under short-term, intensive disturbances remains unclear. This study combined multi-source environmental data with an interpretable machine learning framework (XGBoost-SHAP) to analyze spatiotemporal variations in net primary productivity (NPP) across the Beijing-Tianjin-Hebei region during the strict lockdown (March–May) and recovery (June–August) periods, using 2017–2019 as a baseline. Results indicate that: (1) NPP showed a significant increase during lockdown, with 88.4% of pixels showing positive changes, especially in central urban areas. During recovery, vegetation responses weakened (65.31% positive) and became more spatially heterogeneous. (2) Integrating lagged environmental variables improved model performance (R² increased by an average of 0.071). SHAP analysis identified climatic factors (temperature, precipitation, radiation) as dominant drivers of NPP, while aerosol optical depth (AOD) and nighttime light (NTL) had minimal influence and weak lagged effects. Importantly, under lockdown, vegetation exhibited stronger immediate responses to concurrent temperature, precipitation, and radiation (SHAP contribution increased by approximately 7.05% compared to the baseline), whereas lagged effects seen in baseline conditions were substantially reduced. Compared to the lockdown period, anthropogenic disturbances during the recovery phase showed a direct weakening of their impact (decreasing by 6.01%). However, the air quality improvements resulting from the spring lockdown exhibited a significant cross-seasonal lag effect. (3) Spatially, NPP response times showed an “urban-immediate, mountainous-delayed” pattern, reflecting both the ecological memory of mountain systems and the rapid adjustment capacity of urban vegetation. These findings demonstrate that short-term removal of anthropogenic disturbances shifted vegetation responses toward greater immediacy and sensitivity to environmental conditions. This offers new insights into a “green window period” for ecological management and supports evidence-based, adaptive regional climate and ecosystem policies. Full article