Search Results (229)

Airport Economic Zones (AEZs) in China are largely guided by central and local government planning, and official planning documents provide important textual signals of industrial priorities. To identify these priorities, this study examines 17 national-level Airport Economic Demonstration Zones (AEDZs) and collects official documents on industrial development issued by central authorities and relevant local governments. Using dictionary-based named entity recognition, word-frequency analysis, clustering, and association rule mining, we quantitatively analyze stated governmental preferences in AEDZ industrial planning, focusing on emphasized industries and their combinations. The results show that local governments frequently emphasize industries prioritized by the central government, including aviation equipment manufacturing and maintenance, electronic information, aviation logistics, professional exhibitions, and e-commerce. They also tend to combine high-end intelligent manufacturing, electronic information technology services, and air cargo transportation in planning narratives. These patterns indicate policy alignment across AEDZs, while high similarity in stated industrial priorities may signal potential risks of redundant construction and resource misallocation if not matched with differentiated implementation. The findings are interpreted as textual policy signals rather than evidence of actual implementation or industrial performance. Full article

Space economy involves all activities and resource allocations that generate additional economic and societal benefits through space exploitation. The development of space infrastructure enables a wider range of economic activities. Regarding economic sustainability and national security, the possession of the launch site within national territory is of utmost importance. This paper presents a methodology for selecting launch sites based on linguistic term evaluation using a Discrete Single-Valued Neutrosophic Number (DSVNN) representation. The existence of support makes the DSVNN interpretable, which is not possible in the case of Single-Valued Neutrosophic Number (SVNN) with only specific values of truth, indeterminacy, and falsity degrees. An ensemble of five widely well-known MCDM methods, namely TOPSIS, CODAS, COPRAS, EDAS, and MOORA, are used in the decision-making process. The whole procedure is then applied to the launch site selection in Thailand. All MCDM methods result in the same top priority location, U-Tapao Rayong–Pattaya International Airport, Chonburi. The weight sensitivity analysis and the method cross-validation are applied to test the robustness of the result. Full article

The rapid development of airport economic zones has significantly reshaped regional land-use structures and industrial spatial organization. Taking the Nanjing Airport Economic Zone as the study area, this study integrates multi-source geospatial data, including land-use data, enterprise registration records, Points of Interest (POIs), transportation networks, nighttime light intensity, population, topography, and ecological-environmental variables for 2013, 2018, and 2023. Land-use transition matrices, spatial autocorrelation analysis, standard deviation ellipse analysis, Geodetector, and Multiscale Geographically Weighted Regression (MGWR) models were employed to examine land-use transition, industrial spatial restructuring, and their influencing factors from 2013 to 2023. The results show that: (1) Land-use change in the study area was mainly characterized by the decline of cropland, the expansion of impervious surfaces, and the shrinkage of water bodies. From 2013 to 2023, cropland decreased from 81.07 km² to 70.12 km², impervious surfaces increased from 10.98 km² to 25.65 km², and water bodies decreased from 5.50 km² to 1.79 km². The conversion from cropland to impervious surfaces was the dominant transition pathway, covering 14.67 km². (2) Industrial space exhibited significant spatial clustering, with a Moran’s I value of 0.9639 in 2023. The standard deviation ellipse results indicate that industrial space expanded during 2013–2018 and contracted during 2018–2023, suggesting a shift from extensive outward expansion to relative agglomeration around the core area and major transport corridors. (3) Nighttime light intensity and distance to major transport access points were important explanatory factors for industrial spatial distribution, with q-values of 0.396 and 0.310, respectively. The interaction between slope and metro accessibility showed the strongest explanatory power, with a q-value of 0.6967. The MGWR results further revealed the spatial heterogeneity of the effects of transportation, economic activity, population concentration, and ecological constraints. Overall, land-use transition and industrial spatial restructuring in the Nanjing Airport Economic Zone were jointly shaped by transportation accessibility, economic vitality, population agglomeration, and ecological constraints. These findings provide a reference for land-use optimization and industrial spatial governance in airport economic zones. Full article

Surface congestion and taxiing delays at high-density airports increasingly constrain aviation sustainability, as ground-phase fuel consumption and emissions constitute a significant share of total airport emissions. Existing studies typically decouple air traffic flow management from ground resource scheduling, hindering coordinated optimization of punctuality, environmental benefits, and resource utilization. This paper proposes a multi-objective optimization method for runway-taxiway systems oriented toward air–ground collaborative decision-making, integrating Calculated Take-Off Time (CTOT) compliance constraints. A tri-objective mixed-integer programming model is formulated to minimize CTOT deviation, total taxiing time, and runway workload imbalance. A hybrid intelligent algorithm, SSA-SCA-NSGA-II, is designed with a bidirectional elite feedback mechanism to address this NP-hard problem. Validation uses real operational data of 58 departure flights during a peak period at Beijing Daxing International Airport. The results demonstrate that the proposed method achieves effective trade-offs on the Pareto front: CTOT compliance rate increased from 77.6% to 89.7–96.6%; total taxiing time decreased from 692 min to 551–635 min; and dual-runway utilization imbalance declined from 5.2% to 1.7–3.8%. These improvements translate into quantifiable sustainability gains: fuel consumption is reduced by 1425–3525 kg and CO₂ emissions by 4503–11,139 kg per peak hour, alongside a 19-percentage point improvement in punctuality that lowers passenger delay costs and reduces controller coordination workload. By simultaneously advancing environmental sustainability (carbon footprint reduction), economic sustainability (fuel and operational cost savings), and social sustainability (service punctuality and labor efficiency), the framework provides a measurable, monitorable, and policy-relevant decision-support tool for green airport surface operations aligned with sustainable development goals (SDGs). Full article

This study examines the structural determinants of behavioral intention to use a City Airport Terminal (CAT) in Ulsan using a structural equation modeling (SEM) framework. Whereas prior literature has predominantly explained CAT adoption in terms of accessibility, this study investigates whether usage intention can be sufficiently explained by accessibility alone or whether it reflects a broader multi-factor structure involving service quality and safety, economic efficiency, infrastructure convenience, and perceived public value. To this end, five latent constructs were specified, and a survey of 500 Ulsan residents was conducted. The confirmatory factor analysis indicated an acceptable measurement structure for the five latent constructs. The structural model results show that perceived public value and regional development was the only construct with a statistically significant direct path to CAT usage intention, whereas the baseline accessibility-only model provided a statistically insufficient explanation. A nested model comparison further indicated that non-accessibility constructs collectively contributed additional explanatory value beyond what accessibility alone could provide. These findings suggest that CAT usage intention is not adequately explained by accessibility alone but is better understood through a multi-factor conceptualization of CAT adoption. This study contributes to the literature by providing structural evidence that public value—encompassing regional development expectations and community-level benefits—should be explicitly considered in sustainable airport infrastructure planning. The results highlight the importance of a multi-dimensional approach to CAT implementation policy, integrating service quality and safety, economic efficiency, infrastructure convenience, and community-level value perceptions alongside physical accessibility. From a sustainable mobility perspective, the findings offer useful implications for sustainable airport access planning and air transport management. Full article

Against the backdrop of the global aviation industry’s commitment to achieving the “Net Zero Carbon Emissions by 2050” goal, the issue of superimposed peak loads on distribution networks—arising from the large-scale transition from fossil-fueled to electric Ground Service Equipment (GSE) at civil airports—has become increasingly prominent, emerging as a critical constraint on green airport development. Focusing on the high-value airside area, this paper presents the first systematic review of how Vehicle-to-Grid (V2G) technology can transform electric Ground Service Equipment (e-GSE) from mere “charging loads” into “dispatchable energy storage resources.” The study proposes that, through bidirectional DC charging/discharging and intelligent aggregation technologies, e-GSE fleets operating on predictable schedules can be integrated as flexible regulation units within airport microgrids. To realize this pathway, the study comprehensively examines the core technological framework, encompassing wide-power-range bidirectional charging infrastructure, grid-forming power conversion topologies, standardized communication and grid interconnection interfaces, flight-schedule-based potential assessment and dispatch algorithms, and photovoltaic storage–charging hybrid system integration schemes. The review demonstrates that this technology can not only enhance grid resilience and promote renewable energy accommodation through peak shaving, valley filling, and ancillary services but also yields significant economic benefits. Finally, the study identifies the technical, standardization, and business model barriers hindering large-scale deployment, thereby providing a theoretical reference and a technology roadmap for the energy system planning and construction of future “zero-carbon smart airports”. Full article

Air transport is a key driver of economic development, tourism, and regional connectivity, yet its growth generates increasing environmental costs. Grounded in the catalytic effects framework and the sustainability trade-off perspective, this exploratory study examines the economic and sustainability dimensions of air traffic recovery and growth at Belgrade Nikola Tesla Airport during 2019–2024, a period encompassing a pandemic shock and record post-pandemic expansion. Descriptive statistical analysis and Pearson correlation analysis were applied to six annual data points, supplemented by an approximate CO₂ emission estimation. Passenger traffic increased from 6.16 to 8.37 million (+35.9%), and the destination network expanded from 99 to 135 routes. A positive co-movement was observed between passenger traffic and foreign tourist arrivals (r = 0.970; p = 0.001). No detectable association was found between passenger traffic and annual GDP growth rate (r = 0.143; p = 0.79). Estimated CO₂ emissions grew proportionally from 0.831 to 1.130 million tonnes, consistent with the proportional growth pattern generated by the fixed-factor estimation framework applied. The passengers-per-movement ratio improved from 87.5 to 97.2, indicating a proximate improvement in operational efficiency. These preliminary findings provide exploratory evidence relevant to Sustainable Development Goals 8 and 9 and may inform future research and policy discussions on the sustainability dimensions of airport development. Full article

Delays are among air transport’s main operational challenges, with significant economic, societal and environmental consequences, and many methodological alternatives have been used in their study. Here we explore the use of symbolic regression, a data-driven technique that searches a space of analytic expressions to identify compact and interpretable models explaining a given set of data. We specifically use symbolic regression to characterise delays at the busiest European airports, how they evolve in time and depend on their own past, up to how they propagate across airports. This is done with the aim of evaluating the feasibility of using this approach, and the added value when compared to standard statistical and causal models. Results of this proof of concept point to a nuanced picture: while symbolic regression demonstrates clear potential for uncovering interpretable functional relationships in delay dynamics, its applicability is hindered by the significant computational cost and its stochastic nature. Full article

Airports face persistent capacity constraints and increasing delays. This study introduces a behavioural framework for demand management that integrates airport and airline preferences with principles from Prospect Theory. By incorporating concepts from behavioural economics—such as loss aversion, reference dependence, and non-linear probability weighting—into choice architectures, we explore how adaptive decision environments can influence airline scheduling and demand distribution. A practical example illustrates the applicability of the proposed methodology. Results suggest that behavioural interventions can sustain economically viable schedules while maximising total prospect value. This approach provides policymakers and operators with innovative tools to address complex capacity challenges in air transport systems. Full article

Freeze–thaw damage significantly reduces the performance and durability of airport pavements in cold regions. Traditional assessment methods, such as the F300 freeze–thaw test, are time-consuming and hinder rapid optimisation of mix design. In addition, previous studies have mostly relied on long-term laboratory testing and have evaluated phase-change concrete (PCC) independently, without considering synergistic effects. These approaches lack fast, synergy-aware predictive capability and interpretable tools for mix proportion design, resulting in a gap between laboratory research and practical engineering applications. To address this issue, this study proposes an intelligent and explainable framework for predicting freeze–thaw damage and guiding mix design of steel fibre-reinforced phase-change concrete (SF–PCC). A boundary-controlled experimental programme was first conducted, varying steel fibre (SF) content from 0 to 1.2% and phase-change material (PCM) content from 0 to 12% under fixed mixture conditions. The freeze–thaw test results were recorded sequentially and used to construct a supervised learning dataset. Then, an XGBoost model was developed to predict two key durability indicators: relative dynamic modulus of elasticity (RDEM) and mass loss. SHAP (SHapley Additive exPlanations) analysis was further applied to quantify feature importance and interaction effects. The model achieved high predictive accuracy (R² = 0.9938 for mass loss and R² = 0.9935 for RDEM) under controlled experimental conditions. After 300 freeze–thaw cycles, the reference mix exhibited an RDEM of 61.2%, while optimised configurations showed improved performance. The economical design (9% PCM + 0.9% SF) achieved an RDEM of 66.8%, and the high-performance design (12% PCM + 1.2% SF) reached 72.6%. These results demonstrate that the proposed framework can effectively enhance durability and support rapid preliminary decision-making. The framework significantly accelerates freeze–thaw performance evaluation by enabling near-instant prediction and serves as an efficient supplementary tool for mix design optimisation alongside conventional laboratory testing. It also provides interpretable, data-driven insights for the design of freeze–thaw-resistant airport pavement concrete in cold regions. Full article

Municipal solid waste (MSW) generation is a global problem affecting the environment and public health. The current landfill’s useful life is reaching its end, making new site selection a priority to guarantee proper MSW management. This research evaluated the suitability of the metropolitan area of the municipalities of Chihuahua, Aldama, and Aquiles Serdan, using Spatial Decision Support Systems (SDSS) integrated with Multi-criteria Decision-making (MCDM) and hierarchical analysis, and Geographic Information Systems (GIS) to determine potential sites for new Metropolitan landfill development in a semi-arid region. Results showed that 44.7% of the areas studied present a high suitability level, while 29.52% corresponds to a very high suitability level. These areas are located mainly in the north and center zones of the Chihuahua and Aldama municipalities, with some isolated areas in Aquiles Serdan. The key selection criteria were airport distance, land slope, and proximity to the intermunicipal boundary, which enabled the identification of sites with lower environmental impact and greater technical and economic feasibility. This study demonstrates that SDSS and GIS are efficient tools for identifying potential landfill sites. The results highlight the importance of integrating technical, environmental, and social criteria into MSW management planning to achieve sustainable, efficient management in the region. Full article

Advanced Air Mobility (AAM) includes innovative aviation technologies and services that could alter how people and goods are transported. However, future AAM growth and potential regional integration are uncertain and influenced by a range of factors. In this paper, we report findings from expert interviews (n = 35) and a scenario planning workshop (n = 32 stakeholders), conducted between August 2024 and July 2025, to explore potential alternative futures for AAM at the San Francisco International Airport (SFO) and the greater San Francisco Bay Area. We applied a two-axis framework: regulatory environment (supportive vs. restrictive) and economic conditions (vibrant vs. stagnant). Building on this, we developed four plausible scenarios for the 2025 to 2030 and post-2030 time horizons. We apply the SPELT (social, political, economic, legal, technological) framework to assess cross-cutting drivers, tensions, and indicators across the four scenarios based on two timeframes, i.e., 2025 to 2030 and post-2030. Our analysis of the scenarios reveals that regulatory clarity and macroeconomic conditions are key influencers that define the pace and scale of AAM growth, while community impacts (e.g., noise), public acceptance, and infrastructure availability are constraints. These factors largely determine whether technical readiness can translate into scaled deployment. Cross-cutting themes across all of the scenarios consistently shape the outcomes: (1) equity and community acceptance strongly influence political feasibility; (2) SFO and other airports can serve dual roles as conveners and practical enablers but face risks of stranded assets; and (3) flexible, modular infrastructure and incremental investment strategies reduce uncertainty for SFO and other Bay Area airports and public agencies. Together, the findings suggest that while the future of AAM is uncertain, policy and planning responses can assist airports, local governments, and other public agencies in preparing for potential developments. Full article

Eigenvector-based centrality captures recursive notions of importance in networks. While the direct problem computes centrality from given edge weights, the inverse eigenvector centrality problem seeks edge weights that reproduce a prescribed centrality profile; for directed multigraphs, this inverse task is typically non-unique and depends on the admissible arc structure. We study the direct and inverse problems on directed multigraphs and derive an explicit linear characterization of the set of admissible edge-weight vectors that are compatible with a given centrality target. On this feasible set, we formulate a generalized Nash equilibrium problem with shared centrality constraints, in which multiple agents select edge weights to maximize economically interpretable payoffs that incorporate arc-level competition effects. We provide conditions under which the induced game admits a concave potential function, yielding equilibrium existence and, under standard strict concavity assumptions, uniqueness. Finally, we illustrate the model on an airport network where nodes represent airports and parallel arcs represent airline-specific routes, showing that equilibrium selection produces a feasible and interpretable weight configuration that preserves the prescribed centrality. Full article

Climate change (CC) is widely recognized as a major human concern, affecting society across all aspects and activities. Among various economic sectors, aviation is one of the most affected due to its exposure to adverse weather events. Consequently, adaptation and mitigation actions are becoming increasingly important to reduce the negative effects of CC-driven extreme weather events on aviation operations. In this study, we analyzed 30 years of historical aerodrome meteorological routine reports (METARs) from several major Italian airports to assess multi-decadal changes in aviation weather-related hazards, based on observational evidence such as convection, visibility, and snow and freezing precipitation. Furthermore, we examined the ERA5 reanalysis dataset to assess potential anomalies in the synoptic circulation over the Euro-Mediterranean region that may drive fluctuations in local airport climatology. Our results reveal relevant trends for the considered aviation-related weather hazards, while also indicating meaningful links to variations in local and synoptic patterns. The observed increases in 500 hPa geopotential height, 850 hPa temperature, and convective available potential energy (CAPE) lead to changes in the climatology of the airports considered, including a general enhancement of thermoconvective phenomena, a reduction in events associated with synoptic-scale disturbances, an overall decrease in snowfall, and contrasting trends in fog occurrence depending on local factors. Full article

A regenerative economy refers to an economic system that regenerates various forms of capital, including natural resources and social systems, for long-term use. Regenerating these forms of capital enables the sustained improvement of social well-being. This concept differs from a traditional consumption-based economy or a sustainable economy, which primarily aims to secure the satisfaction of future needs. Traditional capitalism has regenerated capital in production but has often consumed natural capital and sometimes degraded social capital. The concept of a regenerative economy provides principles for restoring these forms of capital. This paper discusses how digital transformation (DX) technologies can help realize a regenerative economy, using development projects for DX technologies as case studies. Airport-adjacent districts in three countries—Japan, the Philippines, and Thailand—representing different industrial sectors are examined, and the impacts of these technologies are analyzed based on Fullerton’s concept of a regenerative economy. Based on qualitative assessment, we found that these technologies are expected to contribute to improving some principles of a regenerative economy, but challenges remain in others. As a result, the concept of a regenerative economy can be useful for a conceptual yet holistic assessment of the regeneration of natural and social capital. Full article