The rapid expansion of artificial intelligence has intensified the demand for high-performance data centers, leading to unprecedented pressures on energy, water, and material resources. This critical review examines the emerging challenges associated with resource management in AI-driven data centers by focusing on the interplay between computational growth and environmental constraints. The analysis integrates recent advances in energy efficiency, cooling technologies, and hardware design while highlighting the increasing water footprint of thermal management systems and the material implications linked to semiconductor manufacturing and infrastructure scaling. Particular attention is given not only to the trade-offs between performance optimization and sustainability but also to the limitations of current metrics used to assess resource efficiency. The review identifies key gaps in the literature, including the lack of integrated frameworks that simultaneously address energy, water, and material flows. Finally, this review provides insights into pathways for a more sustainable AI infrastructure by synthesizing present-day knowledge, critically evaluating existing strategies, and emphasizing the need for systemic approaches that align technological innovation with resource conservation and long-term environmental resilience.
Long utility records support renewal screening when failures, durations and exposure use consistent definitions. An audit covered 4885 water-supply failures in a major city in south-eastern Poland (2004–2025); 4859 had a valid repair duration and 4832 had a valid service-interruption status/duration. Events and annual exposure used the same diameter-based functional classification. Material was identified for 4824 events; 4806 events formed 14 material–function groups. The core CRITIC–TOPSIS model combined exposure-normalised failure rate, mean repair time and mean interruption time; 2000 event-level bootstrap replicates quantified sampling uncertainty. Network length increased by about 84.4%, while failure rate decreased (Spearman ρ = −0.911, p < 0.001). Mean repair and interruption times were 7.96 and 2.43 h; 64.2% of repairs equalled 8 h. Galvanised-steel service connections ranked first (CC = 0.819; P(rank 1) = 0.800; P(top 3) = 1.000), followed by steel and asbestos cement distribution pipes. Product-containing structures and the strict >8, >10 and >12 h threshold variants selected asbestos cement distribution pipes, whereas the inclusive ≥8 h and positive-only SIT variants retained galvanised-steel service connections. The result is a group-screening signal, not a renewal prescription; hydraulic consequence, customers affected, condition and cost remain necessary for segment decisions. Beyond the case study, the workflow provides a transferable, low-data screening approach for directing limited maintenance and renewal resources while accounting for water-service accessibility; numerical priorities should be recalculated using local exposure, operational conditions and decision thresholds.
This study investigates the transformation of energy security in distributed energy systems under growing uncertainty, geopolitical shocks, and fuel market volatility. A risk-based multi-objective optimization framework is proposed that integrates economic performance (LCOE, CAPEX, and OPEX), system reliability, and systemic risk measured by Conditional Value-at-Risk (CVaR). The empirical analysis is based on European electricity market data for 2010–2025 and combines historical analysis with stochastic scenario generation and Monte Carlo simulation to evaluate the impacts of exogenous shocks. The results reveal a structural shift in the European electricity market after 2021, characterized by increased sensitivity to fuel price fluctuations and a transition to a more volatile operating regime. Although a higher share of renewable energy improves economic and environmental performance, it does not ensure system resilience without complementary flexibility measures, including energy storage and demand-side management. The proposed framework demonstrates that integrating these measures substantially reduces systemic risk under crisis conditions. The analysis also identifies a persistent post-crisis risk pattern, reflected in elevated CVaR values after market stabilization, which is consistent with the hypothesis of risk hysteresis. Rather than proving hysteresis, the results indicate sustained risk persistence following major external shocks. The proposed framework extends existing approaches to energy security assessment by integrating economic efficiency, reliability, and risk within a unified optimization model. Its modular structure enables adaptation to different electricity markets through recalibration of local parameters, providing a practical decision-support tool for strategic planning under uncertainty.
This study evaluated the anaerobic valorization of real, non-detoxified sugarcane bagasse-derived pentose liquor. Direct fermentation without nutrients, co-substrate, or buffering was limited, reaching low-to-moderate (37–54%) carbohydrate conversion efficiency at low organic loading rate (OLR < 5.6 kg COD m−3 d−1) levels. Hydrogen yield (HY) was also low (0.63–0.89 mol H2 mol−1 carbohydrateconverted) under these conditions. Increasing pentose liquor concentration up to 0.8 L L−1 and OLR of 30.2 kg COD m−3 d−1 suppressed hydrogen production, coinciding with lactate accumulation and the occurrence of homoacetogenesis. Enhanced fermentation with sucrose, nutrients, buffering, shorter hydraulic retention time (12 h) and 37 °C improved stability and carbohydrate conversion (50–61%) under higher OLR, although HY considerably decreased (0.14–0.35 mol H2 mol−1). Methanogenesis was effective in both single- and two-stage systems, with carbohydrate conversion usually above 95%, COD removal up to 83.5%, methane fractions above 60%, and methane yields reaching 299.8–301 NmL CH4 g−1 CODremoved. Furfural and 5-HMF showed phase-dependent transformation, indicating partial in situ detoxification during anaerobic conversion. Overall, pentose liquor is better valorized through integrated hydrogen–methane recovery than by fermentation alone. Future studies should focus on both applying more effective strategies to buffer the fermentative stage and adopting more conservative approaches (lower OLR) to start up the methanogenic systems.
Recovery of critical materials from industrial byproducts is often presented as a near-term United States (U.S.) supply-security strategy, yet contained inventories, pilot output, announced capacity, and commercial production are not equivalent. This study evaluates eight U.S. pathways for gallium, germanium, tellurium, lithium, magnesium, and cobalt, classified as operational, demonstration/pilot, announced target-year, or technical upper-bound cases. Facility- and stream-specific quantities were converted to qualifying domestic output and incorporated into same-stage material balances under explicit assumptions for utilization, eligibility, demand, and import displacement. Supply risk was calculated from the net import dependence and governance-adjusted production and trade concentration using a geometric index, with arithmetic formulations as robustness checks. The operational U.S. copper-refining tellurium pathway yielded the largest central reduction (49.29%). Announced 2030 Clarksville capacity reduced modeled risk by 13.87% for gallium and 8.75% for germanium, conditional on project completion, feed attribution, product qualification, utilization, and demand. All other central cases produced reductions of 4.63% or less; the current lithium demonstration, Stillwater cobalt, and aluminum-residue magnesium cases had negligible national effects. Policy support should therefore be differentiated by qualifying output, market scale, project maturity, and evidence quality rather than by contained material or nameplate capacity alone.
The construction sector relies heavily on virgin mineral resources and produces significant quantities of construction and demolition waste. This study examines crushed brick aggregate (CBA) as a volumetric substitute for natural river sand in micro-concrete at replacement levels of 0%, 25%, 50%, 75%, and 100%. Results show that increasing CBA content decreases consistency and flexural strength while increasing water absorption. However, compressive strength is maintained even at full replacement. One-way ANOVA demonstrated significant overall effects of CBA replacement level on all investigated properties. However, Tukey’s HSD comparisons indicated that not all adjacent replacement levels exhibited significant differences. Specifically, compressive strength at 25% and 50% replacement did not differ significantly from the reference mixture. A nominal resource-efficiency assessment based on the absolute-volume method and literature-derived density values indicates that, at 25% volumetric replacement, the mixture incorporates approximately 286.7 kg/m3 of CBA and saves 362.4 kg/m3 of natural sand while retaining 94.3% of the reference compressive strength. For Croatia’s estimated 8882 t of waste bricks in 2024, a maximum yield scenario suggests production of about 30,985 m3 of this mixture and natural sand savings of approximately 11,231 t. The 25% replacement level offers the most balanced outcome in terms of secondary resource utilisation, consistency, mechanical performance, and water absorption.
The world’s food industry faces significant obstacles today as it strives to meet the nutritional needs of its rapidly expanding global population while also managing an immense amount of food processing waste (FPW) generated throughout the entire food supply chain. The widespread use of traditional disposal techniques for food waste (landfilling and incineration) regularly faces challenges related to environmental sustainability and economic efficiency. This manuscript reviews the necessary transition from a linear “take-make-dispose” approach to food production to a more circular model that recycles food waste into high-value intermediate chemicals and renewable energy through the development of biorefineries. The manuscript explores the biochemical composition of food waste, with carbohydrates, lipids, proteins, and bioactive materials, making it a suitable feedstock for different multi-stage biorefinery operations. In addition, this review will evaluate a variety of existing conversion technologies for food processing waste, such as biological methods (e.g., anaerobic digestion and fermentation) and thermochemical methods (e.g., pyrolysis, gasification, and hydrothermal liquefaction), to create various platform chemicals, including organic acids, bio-alcohols and volatile fatty acids (VFAs), as well as the production of sustainable biofuels and biopolymers. The review also elucidates the three most determinative constraints on large-scale industrial implementation of food waste valorisation: feedstock variability, techno-economic feasibility, and the need for comprehensive life cycle assessments (LCAs). The alignment of food waste management strategies with the UN SDGs (in particular, SDG 12 ‘Responsible Consumption and Production’ and SDG 13 ‘Climate Action’) reflects the opportunity for food waste to serve as a foundation for a carbon-neutral, sustainable future. This review provides a strategic roadmap for academics, practitioners, and policymakers to tap into the full potential of food waste through a sustainable circular economy model.
The agricultural and livestock sectors of Latin America produce a large number of residues that could be converted into energy through bioenergy production processes. However, the bioenergy sector still faces several limitations across the region, including fragmented logistics systems, weak coordination among institutions, and limited integration of environmental, digital, and compliance-related performance indicators. This review systematically analyses residue-based bioenergy value chains in Latin America between 2015 and 2025 using the PRISMA methodology to evaluate selected peer-reviewed studies and regional reports indexed in Scopus, ScienceDirect, SpringerLink, and IEEE Xplore, and institutional repositories. The final synthesis included 37 studies and institutional contributions, which were further disaggregated into 208 country–residue observations for the regional and feedstock distribution analysis. The review identified three main research gap categories: the limited integration of collection and logistics systems, the insufficient treatment of uncertainty, circularity, and traceability within optimization models, and the weak incorporation of governance and institutional coordination into bioenergy value-chain design. The analysis includes biogas, biomethane and related residue-based systems, with attention to supply-chain optimization, policy alignment, methane mitigation metrics, and traceability requirements. Results indicate that although technologies such as biomass pretreatment, process intensification, and upgrading processes continue to improve conversion performance, most studies still focus mainly on technical feasibility and biomass potential. Less attention is given to governance constraints, uncertainty analysis, and monitoring systems capable of supporting regulatory compliance. This research introduced the Sustainable Bioenergy Chain Management Framework (SBCMF) to respond to these limitations and bring together different aspects of bioenergy management within one analytical structure. The framework combines supply-chain optimization under spatial and temporal constraints, circular economy valorisation, methane-related climate performance, and digital traceability, while also linking techno-economic system design with governance and monitoring requirements. In this way, it can help support the development of more transparent and low-carbon bioenergy systems across Latin America.
Sustainable pavement maintenance increasingly requires coordinated management of infrastructure condition, renewable-energy availability, carbon emissions, financial resources, and operational capacity. This study proposes a renewable-energy resource management framework for low-carbon network-level pavement maintenance using simulation-based pavement-energy modeling and multi-agent deep reinforcement learning. The proposed framework develops an AnyLogic-based pavement-energy simulation environment in which road sections, deterioration states, work zones, maintenance crews, equipment resources, photovoltaic generation, battery storage, grid support, diesel backup, carbon tracking, and budget consumption are represented within one integrated decision environment. To support adaptive maintenance control, pavement sections are modeled as interacting agents, while road connectivity, dispatch dependency, traffic interaction, and maintenance-route relationships are encoded through graph structures. A graph-based multi-agent deep reinforcement learning model, named Graph-MAPPO, is then used as the decision controller. The model integrates multi-head graph attention for spatial dependency learning, GRU-based temporal memory for deterioration-history representation, finite-element-assisted structural-risk indicators for hidden damage characterization, and constraint-aware action masking to prevent infeasible decisions under budget, carbon, energy, crew, and equipment constraints. Two calibrated datasets were generated to support the framework: a pavement network and maintenance dataset containing 4437 records and 55 features, and a renewable energy-carbon-budget dataset containing 9875 records and 38 features. The decision controller jointly selects the pavement section, treatment type, intervention timing, crew, equipment, and energy mode. Results from 20 experimental configurations show that the balanced Graph-MAPPO policy improves average PCI from 69.4 to 78.9, achieves an RSL gain of 6.8 years, reduces emissions to 58.3 tCO2e, maintains a renewable-energy share of 74.6%, and limits the constraint-violation rate to 1.8%. Under high renewable-energy availability, the framework achieves the best overall performance, with an average PCI of 80.2, renewable-energy share of 84.6%, emissions of 50.8 tCO2e, and reward of 0.90. These findings demonstrate that integrating pavement-energy simulation, renewable-energy resource allocation, carbon-aware maintenance planning, structural-risk awareness, and multi-agent decision control can support more adaptive, low-carbon, and resource-efficient pavement maintenance management.
Growing concerns regarding resource efficiency, economic uncertainty, and energy-market volatility have renewed interest in the relationship between material-use patterns and macroeconomic stability. Recent global disruptions affecting production systems and economic activity have intensified policy attention toward sustainable resource management and resilience-oriented growth strategies. Using an unbalanced panel of 30 OECD economies over the period 1995–2024, this study examines the relationship between resource productivity and economic resilience while accounting for material-use intensity and structural conditions. The empirical framework relies on second-generation panel econometric techniques that account for cross-sectional dependence and heterogeneous country dynamics. The findings indicate that resource productivity is positively associated with economic resilience, with a 1% increase in resource productivity corresponding to an approximately 0.18% increase in resilience. By contrast, domestic material consumption and material footprint display negative associations with resilience, suggesting that resource-intensive production and consumption patterns may be linked to lower adaptive capacity and macroeconomic stability. The short-run estimates additionally indicate the persistence of adjustment dynamics following economic disturbances. These findings highlight the relevance of resource-use efficiency for macroeconomic resilience and sustainable resource-management strategies in OECD economies.
Natural resources play a fundamental role in ensuring global food security, while agricultural production itself strongly influences their demand, extraction, and availability. This article discusses natural strategies for increasing crop productivity within the framework of sustainable intensification, focusing on the integrated role of plant biostimulants and micronutrients. Both groups of substances are analyzed from a resource-oriented perspective, highlighting their potential to be derived from renewable sources, particularly agro-industrial by-products and plant biomass. Plant extracts obtained from fruit, vegetable, and cereal processing residues contain numerous bioactive compounds, including phenolics, amino acids, peptides, and organic acids, which can stimulate plant growth, improve nutrient uptake, and enhance tolerance to abiotic stress. Micronutrients such as Fe, Zn, Mn, Cu, and B are also strategic resources in crop production because they regulate key metabolic processes and influence the efficiency of macronutrient utilization. Their effectiveness, however, depends strongly on chemical form and bioavailability in soil–plant systems. The novelty of this work lies in integrating perspectives from plant physiology, coordination chemistry, and resource management to propose a conceptual framework in which plant-derived extracts and micronutrient complexes act as complementary tools supporting circular and resource-efficient agricultural systems.
Although geopolymer and alkali-activated binders are promoted as low-carbon OPC alternatives, their resource-centric performance remains complex and geographically dependent. This review examines these systems from a resource-efficiency perspective and evaluates alkaline activator demand; precursor availability, including fly ash, slag, calcined clays, and mining residues; and embodied energy across mix designs and curing regimes. Recent mechanical and durability analyses, together with life cycle assessments, reveal important trade-offs in alkali-activated geopolymer systems. Customized precursors may unintentionally compromise their inherent resource efficiency, while the declining availability of industrial waste increasingly competes with alternative waste valorization processes. Developing one-part activator systems and implementing data- or machine-optimized mix designs capable of handling extremely highly variable waste streams will be necessary to achieve meaningful reductions in mineral consumption, energy demand, and emissions. The study reframes these binders as enablers of urban mining and industrial symbiosis. Policy changes toward resource-oriented governance, including performance-based standards, carbon-responsive procurement, and more transparent end-of-waste legislation, are also needed to promote a circular material economy. Strategic, large-scale deployment requires the integration of regional resource mapping with predictive performance modeling to navigate resource constraints in the construction sector.
The dumping of coal gangue poses significant risks to human health and ecosystems, necessitating ecological restoration in coal gangue mining areas. This study investigates the physical properties and water-retention characteristics of coal gangue–fly ash (CG-FA) substrates under varying coal gangue volume ratios and particle-size distributions, and evaluates their effects on alfalfa (Medicago sativa L.) growth. Six CG-FA volume ratios (5:5, 6:4, 7:3, 8:2, 9:1, 10:0) and seven particle-size distributions (1:1:1, 2:1:1, 3:1:1, 1:2:1, 1:3:1, 1:1:2, 1:1:3) were tested in 3 L pot experiments. Results showed that reducing coal gangue content significantly improved substrate structure, decreasing bulk density by 3.8–28.9% and increasing porosity by 9.8–64.4%, accompanied by enhanced water-retention capacity. The 5:5 volume ratio combined with a 1:2:1 particle-size distribution resulted in the highest alfalfa biomass, providing the best balance of substrate structure and water availability. From a resource-oriented perspective, the optimized CG–FA substrate enables the in situ utilization of coal-based solid wastes, reducing dependence on external soil resources while improving water retention and plant growth. These findings suggest potential advantages in resource utilization, economic feasibility, and environmental performance, providing a sustainable alternative for mine land restoration.
Wetlands are vital ecosystems that provide critical provisioning, regulating, cultural, and supporting services that underpin biodiversity conservation and local livelihoods. Despite their importance, ecosystem service valuation is often overlooked in coastal wetland restoration, limiting recognition of their contributions to the United Nations Sustainable Development Goals (SDGs). To address this gap and overcome methodological fragmentation in wetland assessments, this study develops the Integrated Ecosystem Valuation and Management of Wetlands (IEVMW) framework, which integrates the Millennium Ecosystem Assessment (MEA), Drivers–Pressures–State–Impact–Response (DPSIR) framework, IPCC climate risk assessment, and Total Economic Value (TEV) approaches into a unified methodology. The framework was applied to the Kol Wetlands in India to identify ecosystem services, assess climate-related risks, estimate economic values, and develop management recommendations. Results indicate that provisioning services contribute the highest economic value, followed by regulating and cultural services. Climate change was estimated to place approximately 11.7% and 13.0% of ecosystem service value at risk in North Kol and South Kol, respectively, corresponding to a combined economic value at risk of ₹42.9 crore, with provisioning services being the most vulnerable. The IEVMW framework provides a practical and scalable approach for linking ecosystem service valuation, climate risk assessment, and governance, thereby supporting climate-resilient wetland management and biodiversity conservation across diverse socio-environmental contexts.
Environmental implications of resource dependence remain a central concern for hydrocarbon-based economies undergoing energy transition. Using panel data for GCC countries over 1990-2024 and second-generation econometric techniques that account for cross-sectional dependence and heterogeneity, this study identifies a stable long-run relationship between natural resource rents, renewable energy, and CO2 emissions. The results show that a 1% increase in natural resource rents is linked to a 0.21% rise in CO2 emissions, highlighting the persistence of carbon-intensive economic structures. By contrast, renewable energy is associated with a 0.15% reduction in emissions, although its environmental contribution remains modest. The interaction effect is negative (-0.048) but only partially robust, indicating that renewable energy weakens, but does not fully offset, the environmental pressure associated with resource dependence. These findings suggest that energy transition in GCC economies remains gradual and structurally constrained, requiring not only renewable expansion but also deeper transformation of hydrocarbon-based growth models.
Coal resource exploitation may alter hydrogeological conditions and influence the occurrence and migration of coal-derived organic contaminants in mining regions. Among these contaminants, naphthenic acids (NAs) have received increasing attention, whereas their occurrence and environmental behavior in coal mining areas remain insufficiently understood. For the first time in an open-pit coal mining setting, this study systematically investigated the concentrations and molecular compositions of NAs in surface water, groundwater, and source-related water samples from the Shenfu Coalfield, a representative mining area in China. NAs were detected in all samples, with concentrations exhibiting clear spatial variability. Groundwater consistently contained substantially higher NA levels than surface water, and elevated concentrations in downstream river reaches coincided spatially with groundwater discharge zones, identifying groundwater as a key reservoir and transport pathway for NAs in the mining-affected watershed. Principal component analysis further revealed compositional similarities among groundwater, coal-washing wastewater, and certain surface-water samples, indicating contributions from both coal-bearing strata and coal-processing activities. These findings highlight the necessity of incorporating NAs into routine mine-water monitoring and groundwater protection programs in open-pit coal mining regions.
This study examines the economics of blue and green hydrogen as feedstock for large industrial facilities in Southeast Asia. To understand how industries can adopt low-emission and renewable hydrogen, the levelised costs of blue and green hydrogen are calculated. Four pathways are examined, including a large-scale carbon capture and sequestration facility located a distance away from an existing steam methane reforming hydrogen plant, a gigawatt-scale electrolysis facility adjacent to a large industrial site fed by an adjacent solar photovoltaic electricity source, as well as two pathways with either remote electrolyser and solar photovoltaic, necessitating hydrogen transport and storage, or a remote solar photovoltaic source with a dedicated power transmission line. The region's transition to green hydrogen must overcome the challenges of high renewable electricity costs, the need for large land banks for solar photovoltaic farms and efficient long-distance hydrogen transport solutions or power transmission lines. Moreover, the region must improve its inconsistent track record in implementing billion-dollar public-private projects within budget and on time.
The rapid growth of battery energy storage and electric vehicles has increased lithium demand and intensified the attention given to the environmental performance of alternative extraction pathways. Conventional life cycle assessments (LCA) of lithium production typically report midpoint indicators in physical units, which limits cross-category comparison and reduces their usefulness for economic and policy analysis. This study presents a comparative monetized LCA of lithium carbonate equivalent (LCE) production from three pathways: solar brine evaporation, hard-rock spodumene mining, and geothermal brine recovery. Using the TRACI 2.1 midpoint results reported in a prior LCA, six impact categories—global warming, smog formation, acidification, respiratory effects, carcinogenic toxicity, and non-carcinogenic toxicity—are converted into monetary values through a benefit-transfer, damage-cost approach. Total environmental external costs are estimated at USD 11.85/kg LCE for solar brine evaporation, USD 9.45/kg LCE for spodumene mining, and USD 4.11/kg LCE for geothermal brine recovery (all USD amounts are expressed in $2025 unless otherwise mentioned). Smog formation contributes more than 80% of the total monetized damages across all pathways, while toxicity-related impacts account for a smaller share than implied by the normalized midpoint results. Monetization changes the relative ranking of the solar brine and spodumene pathways, while indicating that geothermal brine recovery has the lowest monetized external cost among the impact categories evaluated. These findings show that monetized LCA can complement conventional midpoint assessment and provide more decision-relevant insights for policy and economic evaluation.
Sustainable fertilization strategies are required to reduce dependence on synthetic inputs, enhance waste recycling, and improve agricultural resilience under climate change. This study evaluates the effects of wastewater-derived sludge, particularly when modified with Fe-montmorillonite, on phosphorus availability and early development of Zea mays. Methods: Germination and early growth of Zea mays were assessed under four treatments: (i) untreated soil (Control); (ii) soil amended with sludge from the Cardeal Wastewater Treatment Plant (SC); (iii) soil amended with Fe-montmorillonite-modified sludge (TechPhos, ST); and (iv) soil amended with a commercial phosphorus salt (PS). Soil characterization was conducted using XRF, XRD, and FTIR. Plant responses were evaluated through laboratory (5 days) and pot (22 days) experiments. Results: ST showed the highest performance, with a germination index of 171.7 and improved biomass, leaf development, and chlorophyll content compared to Control and SC. ST also performed similarly to or better than the commercial fertilizer (PS), indicating high phosphorus efficiency. Conclusions: The integration of nanostructured modified montmorillonite with wastewater-derived sludge represents a promising alternative phosphorus source for early maize development. Its application supports waste valorization and circular economy approaches while contributing to improved soil fertility and more sustainable nutrient management under climate change scenarios.
This study examines the dynamic interlinkages among energy, food, and metal commodity markets under geopolitical tensions using daily data from January 2022 to July 2025. The empirical framework integrates correlation analysis, Granger causality tests, and a Vector Error Correction Model (VECM) to capture both short- and long-run transmission mechanisms, with robustness assessed through impulse response functions, forecast error variance decomposition, and a Diebold-Yilmaz connectedness analysis across three structurally distinct geopolitical event windows. The results reveal asymmetric and sector-specific transmission patterns in which geopolitical risk significantly influences key commodity prices-particularly WTI crude oil, wheat, copper, and aluminium-confirming its role as a primary external shock driver. WTI emerges as the dominant transmitter of shocks, while industrial metals exhibit strong internal connectedness. Critically, gold's role proves to be conditional and context-dependent: within an integrated energy-food-metal network under geopolitical stress, it functions primarily as a net receiver and passive absorber of macroeconomic uncertainty rather than as a systemic transmitter, a finding that complements, rather than contradicts, its established safe-haven role in financial asset pricing frameworks. These findings are subject to limitations, including reliance on futures price data and a linear VECM framework that may not fully capture nonlinear or regime-dependent dynamics.
