Search Results (29,357)

Energy Geographies has a unique position at the intersection of geospatial and social science, and it now faces a defining methodological development with the rapid rise in Geospatial Artificial Intelligence (GeoAI). This paper examines where GeoAI has and has not been applied within energy research through two bibliometric analyses using the Dimensions database. The first establishes an updated picture of energy geographies scholarship from 2020 to 2026, mapping the field’s current priorities and geographic distribution as a baseline for evaluating GeoAI’s role. The second conducts a bibliometric analysis of GeoAI-specific energy publications from 2020 to 2026, which reveals significant GeoAI Application Gaps: a heavy concentration in energy extraction and production research and in renewable energy siting and grid optimization, while energy transition, justice, and the energy problems of underrepresented regions remain substantially underserved. GeoAI energy research is also more geographically concentrated than the broader field, dominated by a small number of countries, raising questions about the applicability of these tools to the energy challenges facing the rest of the world. We argue that this gap reflects a pattern of problem selection as much as technological limitation, and that energy geographers are well positioned to redirect the development of this new field. We outline three directions for future research: developing Explainable GeoAI to ensure transparency and accountability, expanding geographic coverage to address data biases that favor a small set of well-resourced countries, and confronting the computational energy paradox of carbon-intensive AI applied to sustainability-oriented research. Full article

Adaptive construction techniques in traditional vernacular dwellings play an important role in improving the wind–thermal microclimate of buildings. However, comparative studies on such techniques across different regions remain limited. Moving beyond a static regional perspective, this study selects six representative skywell dwellings along the historical migration route from Jiangxi to Hunan. Through field monitoring and CFD numerical simulation using PHOENICS, the wind–thermal performance of these dwellings under extreme summer high-temperature conditions is comparatively analyzed. The results reveal case-based regional differences characterized by “shared origins and regional differentiation.” The western Jiangxi dwellings tend to adopt ventilation as the main spatial logic, using open spaces to enhance convective heat dissipation. In contrast, the northern Hunan dwellings show more prominent shading and heat control characteristics, relying on optimized skywell geometry to achieve geometric shading and reduce radiative heat gain. This study clarifies that adaptive construction techniques vary significantly under regional influences, and the findings may provide quantitative data support and design references for optimizing the microenvironment of contemporary buildings. Full article

The decarbonization of maritime and inland waterway transport requires implementation pathways that go beyond fuel substitution and address energy, water, safety, infrastructure, and lifecycle constraints. This study proposes a sustainable technical pathway for hydrogen implementation in small-scale maritime and inland waterway vessels, using Colombia as a territorial case study. The methodology integrates technological surveillance, national energy-transition assessment, sectoral and territorial analysis, hydrogen pathway selection, water-resource management, safety and regulatory review, lifecycle criteria, and progressive validation under Technology Readiness Level principles. The results identify compressed gaseous hydrogen combined with Proton Exchange Membrane fuel cells and hybrid battery support as the most feasible short-term configuration for small vessels due to its modularity, operational flexibility, and compatibility with decentralized applications. The framework also shows that hydrogen production must be designed as a coupled water–energy–hydrogen system, prioritizing treated wastewater, rainwater, desalinated water, or other non-potable sources to avoid pressure on community and agricultural water demand. Laboratory and prototype validation demonstrated a progressive route from didactic hydrogen systems to small-vessel maquettes and scaled prototypes. The proposed pathway provides an implementation-oriented framework for safe, sustainable, and territorially adapted hydrogen deployment in small maritime systems. Full article

This study synthesises evidence on whether, why, and under what conditions digital technologies improve resource efficiency across multi-tier global value chains (GVCs) and examines the theoretical adequacy of dominant explanatory lenses. Following the PRISMA 2020 protocol, we searched Web of Science, Scopus, IEEE Xplore, and ProQuest, retaining 150 articles for qualitative synthesis and 137 for bibliometric science-mapping; themes were developed via multi-cycle coding and triangulated with co-citation and keyword co-occurrence networks. Reported efficiency gains are strongest when firms deploy integrated digital stacks combining IoT sensing, AI analytics, blockchain traceability, and digital twins that jointly enable visibility, verification, and simulation-based optimisation, a pattern based predominantly on observational and cross-sectional evidence. Outcomes are contingent on cross-firm capability complementarities, data-governance arrangements, regulatory congruence, and cyber-risk maturity. A key structural finding is the digital-regionalisation paradox: stringent data-compliance demands can re-anchor sourcing within regulatory blocs, concentrating rather than extending GVC geography. Building on these findings, we propose three theoretical extensions, namely ecosystemic capability bundling, digital-sustainability spillovers, and distributed eco-innovation, that advance Transaction Cost Economics, the Resource-Based View, Dynamic Capabilities, and GVC governance theories to better account for the sustainability and platform dimensions of contemporary digitalised value chains. Full article

The rapid advancement of laboratory automation, robotics, and digital technologies has significantly transformed laboratory medicine worldwide, improving efficiency, diagnostic accuracy, and quality management. However, the adoption of these technologies in developing countries such as Indonesia remains uneven and is influenced by infrastructural, financial, regulatory, and workforce-related challenges. This structured narrative review aimed to critically examine the current landscape of laboratory automation and robotics in Indonesia, with particular emphasis on implementation challenges, workforce transformation among medical laboratory scientists (Ahli Teknologi Laboratorium Medik, ATLM), and pathways toward equitable integration. Studies published between 2015 and 2025 were identified through PubMed, Scopus, and Google Scholar, complemented by Indonesian regulatory documents, professional guidelines, and relevant grey literature. The review was informed by PRISMA principles and synthesized narratively to explore technological developments, operational impacts, policy contexts, and implementation barriers relevant to Indonesian laboratory systems. The findings indicate that automation and robotics offer substantial benefits, including improved turnaround time, enhanced quality assurance, reduced laboratory errors, and greater operational efficiency. Nevertheless, significant barriers persist, particularly disparities in digital infrastructure, financial constraints, limited workforce readiness, and the absence of comprehensive implementation frameworks. The review further highlights that automation is reshaping rather than replacing the role of ATLM, shifting professional responsibilities toward digital competency, automation oversight, data interpretation, and quality management. Achieving sustainable laboratory automation in Indonesia therefore requires an equity-centered and systems-oriented approach involving regulatory strengthening, workforce development, infrastructure investment, and multi-stakeholder collaboration. With strategic planning and policy alignment, laboratory automation and robotics hold considerable potential to modernize laboratory services and support Indonesia’s broader healthcare transformation agenda. Full article

The Sustainable Development Goals (SDGs) are widely presented as an integrated framework for social, economic, and environmental progress, yet recent assessments indicate substantial implementation shortfalls. This scoping review maps post-2015 scholarship on one of the framework’s most contested fault lines: the relationship between Goal 8 (economic growth) and the ecologically oriented goals, especially Goals 6, 12, 13, 14, and 15. Following established scoping review guidance, 32 sources published between 2015 and 2026 were identified from Scopus, Web of Science, Google Scholar, citation searching, and selected grey literature. The synthesis indicates four main patterns in the included corpus. First, a substantial share of the reviewed literature characterizes continued growth-centred development and ecological sustainability as difficult to reconcile under current technological and institutional conditions, particularly given evidence on material throughput, emissions, and planetary boundaries. Second, the corpus recurrently describes three mechanisms through which this tension is muted within the SDG architecture: the rhetorical absorption of ecological limits into “green growth” discourse, strategic vagueness in targets and indicators, and the marginalization of alternative development ontologies. Third, the review synthesizes these mechanisms under the interpretive concept of paradigmatic stacking. Fourth, the corpus identifies alternative resources for a successor framework, including relational and plural conceptions of well-being associated in the reviewed literature with Ubuntu, Buen Vivir, and Gross National Happiness. Taken together, the findings suggest that debates about SDG underperformance cannot be reduced to implementation alone but also involve questions of conceptual design. The article concludes by outlining ontological pluralism as a possible direction for post-2030 framework design. Full article

The global cattle industry is experiencing significant growth, requiring advanced methods for monitoring animal health and welfare to ensure productivity and sustainability. Traditional manual monitoring techniques are labor-intensive and often impractical for large-scale operations. This review provides a comprehensive analysis of existing and emerging computer vision tools applied to the monitoring of cattle health and welfare. By systematically examining studies across major databases, this paper addresses six key research questions focusing on (1) the issues addressed by computer vision technologies, (2) data acquisition systems, (3) implemented techniques and algorithms, (4) performance outcomes, (5) challenges faced, and (6) potential applications for underexplored health and welfare aspects in cattle farming. The findings show that computer vision technologies have significantly progressed in areas such as body condition score detection, lameness detection, weight estimation, estrus detection, monitoring of feeding and drinking behavior, breathing detection, and recognition of general behaviors. Despite the progress, challenges such as variability in environmental conditions, the need for large annotated datasets, and the high cost of advanced imaging equipment persist. The review emphasizes future research opportunities to address these challenges by focusing on disease-specific monitoring. This review aims to provide veterinarians, farmers, and animal health professionals with greater insight into computer vision technologies and to promote their adoption by discussing their practical applications. Full article

This study presents a comparative evaluation of geopolymer foams incorporating either commercially available shape-stabilized phase change materials (PCMs) or laboratory-developed diatomite–paraffin PCM granules with controlled particle size fractions ranging from <1.6 mm to >2.5 mm. All PCM variants were incorporated at a constant dosage of 7.5 wt.% to isolate the influence of PCM type on the properties of the resulting composites. The commercial materials comprised PX-4, PX15, and PX20 (Rubitherm Technologies GmbH), whereas the laboratory-developed PCM consisted of paraffin immobilized within a porous diatomite matrix to produce granular shape-stabilized composites. The experimental program included the determination of bulk density, total porosity, pore size distribution, thermal conductivity (λ), thermal resistance (R), specific heat capacity (Cp), and compressive strength. The pore structure was characterized by mercury intrusion porosimetry (MIP), while the morphology and dispersion of PCM particles within the geopolymer matrix were investigated using scanning electron microscopy (SEM). All mixtures were produced using the same alkali-activated matrix and identical curing conditions, with the PCM content maintained at 7.5 wt.%. The results demonstrated that the type of PCM significantly affected the microstructure and thermophysical performance of the geopolymer foams. The laboratory-developed diatomite–paraffin PCM provided the most favorable thermal insulation performance, exhibiting the lowest thermal conductivity (0.095 W/m·K) together with the highest thermal resistance (0.278 m²·K/W). In contrast, the commercial PX15 and PX20 materials exhibited the highest specific heat capacities (1.740 and 1.778 kJ/kg·K, respectively), indicating superior thermal energy storage capability. In addition, the estimated production cost of the laboratory-developed PCM (2.5–4.0 EUR/kg) was substantially lower than that of the commercial PX materials (approximately 20 EUR/kg), highlighting its potential as a cost-effective alternative for sustainable, energy-efficient building materials. These findings demonstrate that both commercial and laboratory-developed PCM systems can effectively enhance the functionality of geopolymer foams, although they provide different balances between thermal insulation, heat storage capacity, and production cost. Full article

The study evaluated the conventional extraction (CE), microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), and pulsed electric fields-assisted extraction (PEFAE) of bioactive compounds from orange peel waste. The effect of extraction time (0–120 min), ethanol concentration (0, 50 & 80%), and temperature (25–70 °C) were investigated, while response surface methodology (RSM) was applied for each process optimization. MAE achieved the highest total phenolic content (TPC) (6.36 mg/g w.m.) under optimized conditions (50 kJ microwave energy, 50% ethanol, 60 min), representing approximately 12% higher recovery compared to CE (TPC: 5.29 mg/g w.m.; 50 °C, 55% EtOH, 80 min). UAE (90% amplitude, 66.4 W/kg) resulted in the highest flavonoid recovery (0.48 mg/g w.m.) using 50% ethanol at 50 °C for 90 min, while PEFAE (4 kV/cm, 1000 pulses) for 75 min extraction time exhibited the same TPC yield as CE and the highest antioxidant activity (1.12 mg/g w.m.) using only water at room temperature. RSM analysis confirmed that ethanol concentration and extraction time significantly affected extraction performance. These findings demonstrate the potential of green extraction technologies for sustainable valorization of citrus processing waste and recovery of high added-value compounds. Full article

A sustainable low-carbon transition requires policy that curbs emissions while accelerating green technological innovation. The EU Carbon Border Adjustment Mechanism (CBAM) imposes carbon costs on high-emission exports; yet, how it shapes exporters’ green innovation remains poorly understood. We develop an open-economy Environmental Dynamic Stochastic General Equilibrium (E-DSGE) model embedding three CBAM transmission channels: cost-driven (higher carbon-intensive production costs), awareness-driven (firms’ forward-looking expectations), and information-enhancement (lower green R&D financing costs). The model decomposes CBAM’s green-innovation effects by jointly endogenizing forward-looking green R&D investment and carbon disclosure quality in general equilibrium. Calibrated to Chinese data and solved in Dynare 7.0, the model is simulated over forty quarters. Under the baseline calibration, simulations suggest a CBAM shock raises green R&D investment by approximately 6.5% at its peak and the green technology level by approximately 12.5% by quarter 40, while brown emission intensity falls by approximately 10%. Within this window the policy carries a net welfare cost of approximately 0.34% of steady-state consumption, concentrated in transition-period labor disutility, with most gains accruing later. Combining CBAM with R&D subsidies modestly reduces the within-window welfare cost and raises long-run green technology. Realizing this sustainability potential requires policy credibility, carbon-information infrastructure, and coordinated innovation support. Full article

Pumped hydro storage remains one of the most established technologies for balancing supply and demand in electricity markets with high shares of renewable energy. This paper investigates the short-term economic optimization of a pumped hydro storage plant operating under real day-ahead market conditions. A Mixed-Integer Linear Programming model is used to optimize hourly dispatch decisions based on actual day-ahead electricity prices in Slovenia for the year 2024. The model accounts for technical constraints, including turbine and pump capacities, round-trip efficiency, energy storage limits, and restricted startup frequencies. The simulation results show that pumped hydro storage can achieve a positive market-based operating result by responding effectively to price volatility and frequent negative pricing events. Seasonal variations reveal higher revenues during summer months due to solar overproduction. The findings confirm the potential of pumped hydro storage to enhance grid flexibility and support the implementation of national energy transition objectives. By linking large-scale energy storage operations with renewable energy integration, grid flexibility, and market-based dispatch, the study also contributes to the technical and economic dimensions of sustainable energy system development. Full article

Artificial intelligence (AI) is increasingly viewed as a key driver of sustainable development, yet evidence on its role in corporate sustainable green innovation remains limited. Drawing on Resource Orchestration Theory and Signaling Theory, this study examines the impact of AI capability on sustainable green innovation using panel data from Chinese A-share listed companies during 2014–2023. The results show that stronger AI capability significantly promotes sustainable green innovation. AI investment serves as a mediating mechanism. However, the estimated indirect effect is negative, suggesting that the process of AI implementation may involve resource reallocation and organizational adjustment costs before innovation benefits can be fully realized. Environmental investment strengthens the positive impact of AI capability, whereas digital transformation weakens it. Robustness tests confirm the reliability of the findings. Further analyses indicate that the positive effect of AI capability is more pronounced in non-state-owned enterprises, low-technology firms, and firms in the growth stage. By revealing the mechanisms and boundary conditions through which AI capability influences sustainable green innovation, this study enriches the literature on AI-enabled sustainability and offers practical insights for firms pursuing long-term sustainable development. Full article

This study presents a critical historical, bibliometric, and technological overview of the evolution of postharvest science, emphasizing the transition from classical physiology-based approaches to emerging predictive and technology-driven systems. Scientific production related to postharvest research was analyzed using the Scopus and Web of Science databases, while bibliometric mapping and co-occurrence networks were generated using VOSviewer to identify thematic trends, emerging research areas, and structural scientific clusters. In parallel, a technological foresight analysis was conducted through the Lens.org platform to investigate the temporal evolution of patent deposits, the geographical distribution of innovation, the leading institutional applicants, and the predominant technological domains according to the Cooperative Patent Classification (CPC). The results revealed a substantial global expansion of postharvest research over recent decades. This growth was accompanied by increasing technological diversification and stronger integration between scientific knowledge and intellectual property protection. The analysis also highlighted the progressive incorporation of advanced methodologies into postharvest science, including biochemical approaches, non-destructive technologies, artificial intelligence, predictive modeling, and digital tools for quality assessment and shelf-life management. Overall, the study demonstrates that postharvest science is undergoing a paradigmatic transition toward integrated, multidisciplinary, and data-driven systems aligned with current demands for sustainability, food security, innovation, and reduction of postharvest losses. Full article

Background: Telemedicine complements traditional healthcare delivery and may improve access, continuity of care, and patient engagement, particularly in chronic conditions requiring regular follow-up. Video consultation is a widely adopted telemedicine modality and is increasingly integrated into hybrid care models. Methods: This real-world implementation project describes scheduled video consultations embedded in a hybrid care model for children and adolescents with type 1 diabetes using continuous glucose monitoring (CGM) and integrated insulin delivery technologies as part of routine clinical care. A total of 38 families were offered video consultations as part of routine care; 18 adopted the hybrid model. Video consultations were used for routine follow-up, shared review of device data, treatment adjustment, and diabetes education. Family experience was assessed using a voluntary 5-point Likert-scale satisfaction questionnaire. Complete longitudinal CGM data were available for 13 participants, all of whom were established users of the same automated insulin delivery (AID) platform (MiniMed™ 780G (Medtronic MiniMed, Inc. Minneapolis, MN, USA) integrated with Guardian™ 4 (Medtronic MiniMed, Inc. Minneapolis, MN, USA) continuous glucose monitoring). Results: Between 2022 and 2024, 162 video consultations were conducted. Acceptability was high, with 95% (17/18) of respondents reporting high satisfaction (score ≥ 4 on the 5-point Likert scale). 89% (16/18) of families perceived the quality of care as comparable to face-to-face visits for routine follow-up. Families highlighted convenience, reduced travel burden, and flexibility, as well as the value of shared review of CGM and AID system data. Group-level CGM-derived metrics appeared descriptively similar across sequential face-to-face visits and video consultations. Individual patient trajectories showed expected variability but no consistent pattern of deterioration during periods of remote follow-up. Conclusions: Video consultation is a feasible and well-accepted complementary modality within hybrid care models for pediatric type 1 diabetes. When integrated with CGM and automated insulin delivery systems, it supports personalized, data-driven clinical decision-making and continuity of care. Structured implementation and systematic evaluation are essential for sustainable integration into routine practice. Full article

As an emerging technology-intensive industry, the low-altitude economy (hereafter LAE) has attracted growing attention for its potential contribution to sustainable development. However, little is known about whether its expansion can simultaneously promote environmental improvement and economic growth. Using panel data from 30 Chinese provinces from 2012 to 2023, this study examines the relationship between the LAE and the synergistic development of carbon reduction, pollution mitigation, green transition, and economic growth (hereafter CPGE). Green technological innovation (hereafter GT) is incorporated as a mediating variable, while artificial intelligence (hereafter AI) is introduced as both a moderating and a threshold variable to explore the underlying mechanisms and nonlinear effects. The results show that the LAE is significantly and positively associated with CPGE. GT exhibits a significant negative mediating effect, suggesting that the benefits of green innovation may not yet have been fully translated into coordinated green development outcomes during the sample period. AI not only strengthens the positive association between the LAE and CPGE but also exhibits a significant threshold effect. The contribution of the LAE becomes substantially stronger once AI development surpasses a critical level, highlighting the important role of digital intelligence in amplifying the environmental benefits of emerging industries. In addition, the impact of the LAE displays pronounced regional heterogeneity, with stronger effects observed in non-resource-based and non-central regions. This study contributes to the literature by revealing that the environmental effects of the LAE depend not only on innovation channels but also on the level of digital intelligence development. AI serves as a critical enabling condition for translating the growth potential of the LAE into coordinated green development. By revealing the mediating role of GT and the moderating and threshold effects of AI, this study provides new evidence on how emerging industries contribute to sustainable development. The findings underscore the importance of aligning LAE development with AI-driven digital transformation to advance sustainable regional development. Full article