Sustainability

16 pages, 680 KB

Open AccessArticle

Managing Food Waste in the Restaurant Sector: Comparative Insights from Greece and Armenia

by Vardan Aleksanyan, Sargis Gevorgyan, Davit Markosyan, Felix H. Arion, Karlen Khachatryan, Firuta Camelia Oroian, Iulia Cristina Muresan, Iulia Diana Arion and Sabin Chis

Sustainability 2025, 17(24), 11386; https://doi.org/10.3390/su172411386 - 18 Dec 2025

Viewed by 692

Abstract

Efforts to reduce food waste in restaurants are crucial for business efficiency, environmental sustainability, and social responsibility. Food waste varies by restaurant type, operations, menu offerings, and customer behavior, yet research on effective reduction strategies remains limited, particularly in Greece and Armenia. This [...] Read more.

Efforts to reduce food waste in restaurants are crucial for business efficiency, environmental sustainability, and social responsibility. Food waste varies by restaurant type, operations, menu offerings, and customer behavior, yet research on effective reduction strategies remains limited, particularly in Greece and Armenia. This study aims to identify key approaches to minimizing food waste in these countries. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), a method for examining complex causal relationships, we analyzed multiple cases to determine conditions that lead to reduced food waste. Four main paths emerged: (1) digital inventory management combined with educational programs, excluding customer choice enhancement; (2) digital inventory management with flexible dining options, without customer choice enhancement; (3) educational programs with flexible dining, excluding customer choice enhancement; and (4) the combination of digital inventory management, educational programs, and flexible dining. Most cases demonstrating these paths were observed in Greece, indicating more advanced food waste management practices. Interviews highlighted recurring themes such as overordering, portion control, supplier challenges, and the importance of education and policy grounded in social responsibility. The findings provide actionable insights for restaurants and policymakers seeking effective strategies to reduce food waste and promote sustainable practices. Full article

(This article belongs to the Special Issue Consumer Behavior, Food Waste and Sustainable Food Systems)

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23 pages, 1578 KB

Open AccessArticle

Impact of Hybrid Fertilization on Winter Triticale Yield and Its Stability Based on SVD Analysis

by Alicja Lerczak, Tomasz Prałat, Maciej Spychalski, Dariusz Kayzer, Rafał Kukawka and Renata Gaj

Sustainability 2025, 17(24), 11385; https://doi.org/10.3390/su172411385 - 18 Dec 2025

Viewed by 339

Abstract

Nitrogen fertilization is extensively applied in agricultural activities to improve food production. However, the applied dose of nitrogen is often higher than that required for the desired productivity level of a given crop. Thus, research on methods that could increase the uptake of [...] Read more.

Nitrogen fertilization is extensively applied in agricultural activities to improve food production. However, the applied dose of nitrogen is often higher than that required for the desired productivity level of a given crop. Thus, research on methods that could increase the uptake of nitrogen supplied with fertilizers by plants is of high significance. One way to achieve this goal is to employ a hybrid fertilization technique (a combination of the application of solid fertilizers in the first dose with foliar application of liquid fertilizers in the second and third doses), using reduced doses of nitrogen fertilizers as well as fertilizers enriched with 10% sulfur in the form of thiosulfate. The aim of our study was to assess the productivity resulting from different fertilization treatments and the stability of the resulting yield based on interactions between the method of fertilizer application and environmental conditions. To determine interaction patterns, an additive main effects and multiplicative interaction model was employed. The key finding is that sulfur-enriched fertilizers can significantly increase yield, but at the expense of reduced stability. However, yield stability was more strongly related to meteorological conditions. Understanding of such interactions can help increase the efficiency of selection and accuracy of recommendations for new technologies of crop cultivation. Full article

(This article belongs to the Special Issue Sustainable Agriculture: Soil, Water and Environmental Practices in Climate Change)

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18 pages, 730 KB

Open AccessArticle

The Formation of Unmanned Store Customers’ Loyalty: Perspectives from Selection Attributes, Customers Perceived Value, and Their Satisfaction

by Jun Yu, Shuting Tao, Jue Wang and Hak-Seon Kim

Sustainability 2025, 17(24), 11384; https://doi.org/10.3390/su172411384 - 18 Dec 2025

Viewed by 447

Abstract

With the dramatic development of 5G technology, Internet of Things (IoT), and other technologies, the traditional offline market has been gradually altered with applying technologies to improve their efficient or cost-performance. The unmanned stores have been one of the significant and popular forms. [...] Read more.

With the dramatic development of 5G technology, Internet of Things (IoT), and other technologies, the traditional offline market has been gradually altered with applying technologies to improve their efficient or cost-performance. The unmanned stores have been one of the significant and popular forms. To maintain the sustainable development of this retail form, it is essential to know what factors to foster and the mechanism of the formation of customers’ loyalty. Thus, the present study was performed to explore what the selection attributes of unmanned stores are and examine how these attributes impact on the formation of customers’ loyalty through their perceived value and satisfaction. Structural equation modeling was applied with a valid sample of 350 respondents to testify the casual relationship among research variables. As results, it was found that practicality (β = 0.229, t = 3.164, p < 0.01) and convenience (β = 0.152, t = 2.044, p < 0.05) of unmanned stores have positive influence on their perceived value. Moreover, practicality (β = 0.164, t = 2.392, p < 0.05), cleanliness (β = 0.198, t = 3.595, p < 0.001), and pleasantness (β = 0.337, t = 4.722, p < 0.001) could positively impact on their satisfaction. Both perceived value (β = 0.151, t = 2.366, p < 0.05) and satisfaction (β = 0.123, t = 2.023, p < 0.05) could contribute to the formation of their loyalty to unmanned stores. Finally, the moderating effect of social risk has been examined. Consequently, the casual relationships confirmed among research variables could provide insights for the service improvement of unmanned stores from the perspectives of the selection attributes of unmanned stores and customers perceived value. Full article

(This article belongs to the Special Issue Sustainability and Environmental, Social, and Governance (ESG) in Hospitality and Tourism Sector—2nd Edition)

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28 pages, 6148 KB

Open AccessArticle

A Fault Diagnosis Method for Pump Station Units Based on CWT-MHA-CNN Model for Sustainable Operation of Inter-Basin Water Transfer Projects

by Hongkui Ren, Tao Zhang, Qingqing Tian, Hongyu Yang, Yu Tian, Lei Guo and Kun Ren

Sustainability 2025, 17(24), 11383; https://doi.org/10.3390/su172411383 - 18 Dec 2025

Viewed by 335

Abstract

Inter-basin water transfer projects are core infrastructure for achieving sustainable water resource allocation and addressing regional water scarcity, and pumping station units, as their critical energy-consuming and operation-controlling components, are vital to the projects’ sustainable performance. With the growing complexity and scale of [...] Read more.

Inter-basin water transfer projects are core infrastructure for achieving sustainable water resource allocation and addressing regional water scarcity, and pumping station units, as their critical energy-consuming and operation-controlling components, are vital to the projects’ sustainable performance. With the growing complexity and scale of these projects, pumping station units have become more intricate, leading to a gradual rise in failure rates. However, existing fault diagnosis methods are relatively backward, failing to promptly detect potential faults—this not only threatens operational safety but also undermines sustainable development goals: equipment failures cause excessive energy consumption (violating energy efficiency requirements for sustainability), unplanned downtime disrupts stable water supply (impairing reliable water resource access), and even leads to water waste or environmental risks. To address this sustainability-oriented challenge, this paper focuses on the fault characteristics of pumping station units and proposes a comprehensive and accurate fault diagnosis model, aiming to enhance the sustainability of water transfer projects through technical optimization. The model utilizes advanced algorithms and data processing technologies to accurately identify fault types, thereby laying a technical foundation for the low-energy, reliable, and sustainable operation of pumping stations. Firstly, continuous wavelet transform (CWT) converts one-dimensional time-domain signals into two-dimensional time-frequency graphs, visually displaying dynamic signal characteristics to capture early fault features that may cause energy waste. Next, the multi-head attention mechanism (MHA) segments the time-frequency graphs and correlates feature-location information via independent self-attention layers, accurately capturing the temporal correlation of fault evolution—this enables early fault warning to avoid prolonged inefficient operation and energy loss. Finally, the improved convolutional neural network (CNN) layer integrates feature information and temporal correlation, outputting predefined fault probabilities for accurate fault determination. Experimental results show the model effectively solves the difficulty of feature extraction in pumping station fault diagnosis, considers fault evolution timeliness, and significantly improves prediction accuracy and anti-noise performance. Comparative experiments with three existing methods verify its superiority. Critically, this model strengthens sustainability in three key ways: (1) early fault detection reduces unplanned downtime, ensuring stable water supply (a core sustainable water resource goal); (2) accurate fault localization cuts unnecessary maintenance energy consumption, aligning with energy-saving requirements; (3) reduced equipment failure risks minimize water waste and environmental impacts. Thus, it not only provides a new method for pumping station fault diagnosis but also offers technical support for the sustainable operation of water conservancy infrastructure, contributing to global sustainable development goals (SDGs) related to water and energy. Full article

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18 pages, 405 KB

Open AccessArticle

A Study of Electric Vehicle Purchase Intention in Urumqi Based on a Latent Class Model

by Zhi Zuo, Lixiao Wang and Yanhai Yang

Sustainability 2025, 17(24), 11382; https://doi.org/10.3390/su172411382 - 18 Dec 2025

Viewed by 373

Abstract

To explore the mechanism of consumers’ battery electric vehicle (BEV) purchase behavior in depth and address research gaps related to insufficient consideration of psychological latent variables and neglect of consumer heterogeneity in existing studies, this study constructs a latent class model (LCM) that [...] Read more.

To explore the mechanism of consumers’ battery electric vehicle (BEV) purchase behavior in depth and address research gaps related to insufficient consideration of psychological latent variables and neglect of consumer heterogeneity in existing studies, this study constructs a latent class model (LCM) that integrates personal attributes, vehicle attributes, and six psychological latent variables: perceived usefulness, perceived ease of use, perceived risk, environmental awareness, purchase attitude, and purchase intention. Based on 1044 valid questionnaires collected from Urumqi, latent profile analysis (LPA) is used to classify consumers. The results indicate that BEV consumers can be divided into five distinct latent profiles with significant differences in purchase preferences: the risk-avoidance type, the moderate–low intention wait-and-see type, the utility-oriented and low environmental concern type, the high utility cognition and low-risk proactive type, and the all-dimensional high-intention core type. Socioeconomic and vehicle-related factors exert heterogeneous impacts on the psychological variables and purchase decisions of each profile. This study clarifies the intrinsic psychological mechanism of BEV purchase behavior, providing a theoretical basis and targeted strategy references for the government and enterprises to promote BEV adoption and advance sustainable transportation development. Full article

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30 pages, 12727 KB

Open AccessArticle

Regionalized Assessment of Urban Lake Ecosystem Health in China: A Novel Framework Integrating Hybrid Weighting and Adaptive Indicators

by Xi Weng, Dongdong Gao, Xiaogang Tian, Tianshan Zeng, Hongle Shi, Wanping Zhang, Mingkun Guo, Rong Su and Hanxiao Zeng

Sustainability 2025, 17(24), 11381; https://doi.org/10.3390/su172411381 - 18 Dec 2025

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Abstract

Urban lakes are essential for ecological balance and urban development. This study developed a comprehensive framework to evaluate the ecosystem health of urban lakes in China. Nineteen representative lakes from four lake zones were examined using three decades of remote-sensing data combined with [...] Read more.

Urban lakes are essential for ecological balance and urban development. This study developed a comprehensive framework to evaluate the ecosystem health of urban lakes in China. Nineteen representative lakes from four lake zones were examined using three decades of remote-sensing data combined with hydrological, water-quality, and aquatic–biological investigations. An extended DPSIR model guided the selection of 52 indicators, and a hierarchical weighting scheme was used: the analytic hierarchy process determined criterion-level weights, while principal component analysis with Softmax normalization was used for indicator-level weights. The established index system was applied to Xuanwu Lake and Erhai Lake, and an obstacle-degree model was used to identify key ecological constraints from 2010 to 2020. Results showed that urban lakes in the Yunnan–Guizhou Plateau and Eastern Plain zones were mainly constrained by eutrophication and intensive urbanization, with state- and impact-related indicators contributing most to the health index. The framework captured the decline of Xuanwu Lake, driven by poor water exchange and external nutrient loading, and its subsequent improvement following governance interventions, as well as the post-2014 degradation of Erhai Lake driven by climate-induced hydrological stress and non-point source pollution, providing a practical tool for diagnosing constraints and supporting adaptive, region-specific lake management. Full article

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21 pages, 662 KB

Open AccessArticle

Chemical Composition, Antimicrobial, and Repellant Properties of Lavandula stoechas and Artemisia absinthium Essential Oils Against Ephestia kuehniella

by Nawel Bouzeraa, Bilal Saoudi, Sara Grine, Hayette Bouzeraa, Mohamed Faouzi Samar, Carmine Negro, Andrea Luvisi, Luigi De Bellis, Abdelghani Djahoudi, Fouzia Benaliouche, Karim Houali, Faiza Taibi and Mahieddine Boumendjel

Sustainability 2025, 17(24), 11380; https://doi.org/10.3390/su172411380 - 18 Dec 2025

Viewed by 438

Abstract

Background: Lavandula stoechas and Artemisia absinthium essential oils (EOs) were evaluated as natural antimicrobial and repellent agents. Methods: The chemical composition was determined using gas chromatography-mass spectrometry (GC-MS). The antibacterial activity was evaluated by agar diffusion method, and the minimal inhibitory concentration [...] Read more.

Background: Lavandula stoechas and Artemisia absinthium essential oils (EOs) were evaluated as natural antimicrobial and repellent agents. Methods: The chemical composition was determined using gas chromatography-mass spectrometry (GC-MS). The antibacterial activity was evaluated by agar diffusion method, and the minimal inhibitory concentration (MIC) values were determined for antifungal activity, while the repellent effect against mill moth was tested by fumigation. Results: Camphor was the main component in both EOs, accounting for 31.83% of L. stoechas and 41.92% of A. absinthium. In antibacterial assays, both EOs showed very good activity against Gram-positive bacteria, with inhibition zone diameters (IZDs) higher than 15 mm, and average activity against Gram-negative bacteria, with IZDs ranging from 8 to 14 mm. The EOs reduced Aspergillus niger mycelial growth by 61% to 80% for LsEO and 50% to 61% for AaEO at concentrations ranging from 1 to 3 mg/mL. The oils exhibited variation in repellent and insecticidal potential, with L. stoechas showing higher activity, while both had an impact on development and fecundity of Ephestia kuehniella.Conclusions: Thus, the two EOs may be effective as biological and sustainable alternatives to conventional chemical products for food preservation. Full article

(This article belongs to the Section Sustainable Food)

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22 pages, 2682 KB

Open AccessArticle

Low-Carbon Pathways for Ski Tourism: Integrated Carbon Accounting and Driving Factors in a City Hosting the Winter Olympics

by Junjie Li, Yu Li, Bing Xia and Chang Liu

Sustainability 2025, 17(24), 11379; https://doi.org/10.3390/su172411379 - 18 Dec 2025

Viewed by 580

Abstract

As global climate change intensifies, research on low-carbon practices has become a critical component of sustainable tourism development. The carbon emission profile of ski tourism differs significantly from other tourism sectors. Ski resorts have a mountainous terrain and typically maintain relatively high levels [...] Read more.

As global climate change intensifies, research on low-carbon practices has become a critical component of sustainable tourism development. The carbon emission profile of ski tourism differs significantly from other tourism sectors. Ski resorts have a mountainous terrain and typically maintain relatively high levels of vegetation, endowing them with inherent advantages for pioneering low-carbon and sustainable tourism practices. However, the substantial energy demands associated with artificial snowmaking systems and advanced infrastructure pose significant challenges to reducing carbon emissions in ski resort operations. This study gathers first-hand data on sustainable tourism development in the Chongli ski resort—the region that hosted the 2022 Winter Olympics—through field investigations and interviews with key industry stakeholders. It develops a comprehensive framework accounting for carbon emissions in ski resorts by integrating input–output analysis with enterprise-level data, focusing on four core operational sectors: catering, skiing, wholesale and retail, and leasing and business services. Furthermore, this study examines the coupling relationship between carbon emissions and operating revenue. Using correlation and regression analyses, this study identifies the key drivers of carbon emissions across these operational departments within the ski tourism sector. The results indicate that carbon emissions from these four sectors in the Chongli ski resort exhibit periodic fluctuations with an overall upward trend year by year. Nevertheless, progress in low-carbon development is evident, suggesting that the resort is on a trajectory toward achieving peak carbon emissions and eventual carbon neutrality. The inclusion of natural endowments, market-scale effects, festival and special events, and capital investment in ski tourism collectively serve as crucial drivers for low-carbon sustainability in Chongli. Based on these findings, this study proposes targeted recommendations to support low-carbon sustainable development, offering scientific insights for similar Winter Olympics host cities. This study integrates top-down input–output analysis with bottom-up enterprise data, taking Chongli, the host city of the Winter Olympics, as a timely case study. It constructs a four-dimensional low-carbon development model based on the identification of key natural, social, and economic driving factors, and strengthens the reliability of the conclusion by relying on first-hand field research and operator interview data. Our study provides an analysis of methodological innovation, framework integrity, and solid empirical evidence that accounts for micro-scale carbon emissions in ski resorts. Full article

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34 pages, 1675 KB

Open AccessArticle

Selection of Medical Waste Disposal Method for a University Hospital Using Hybrid Multi-Criteria Decision-Making Methods: A Case Study in Adana Province, Turkey

by Olcay Kalan, Zahide Figen Antmen and Sıla Akbaba

Sustainability 2025, 17(24), 11378; https://doi.org/10.3390/su172411378 - 18 Dec 2025

Viewed by 312

Abstract

The global expansion of healthcare services has made medical waste management an increasingly critical and complex issue. Medical wastes require specialized management due to their high infection risk, potential for environmental pollution, and adverse effects on public health. The correct collection, transportation, and [...] Read more.

The global expansion of healthcare services has made medical waste management an increasingly critical and complex issue. Medical wastes require specialized management due to their high infection risk, potential for environmental pollution, and adverse effects on public health. The correct collection, transportation, and final disposal are vital for protecting environmental health and ensuring the safety of hospital personnel and the community. Numerous disposal methods exist. Selecting the appropriate one, however, is a multi-dimensional decision-making problem, necessitating the simultaneous evaluation of various conflicting criteria. Adana, one of Turkey’s largest provinces, generates significant medical waste volumes due to its dense population and developed health infrastructure. Therefore, choosing the most suitable disposal method for hospitals in Adana is crucial for establishing an effective and sustainable waste management system. Making this decision using traditional methods is difficult. The multitude of criteria prevents any single method from being optimal across all aspects. This complexity mandates the use of Multi-Criteria Decision-Making (MCDM) methodologies. In this study, MCDM methods were applied, based on expert opinions, to select the disposal method at a university hospital in Adana. The research examined twelve criteria and four alternatives. The CRITIC (Criteria Importance Through Intercriteria Correlation) method was employed to objectively weigh the criteria. For the rigorous evaluation and ranking of the alternatives, three robust MCDM methods were utilized: PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and EDAS (Evaluation based on Distance from Average Solution). The final results conclusively identified incineration as the most appropriate disposal method for the hospital. Full article

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30 pages, 5640 KB

Open AccessArticle

Data-Driven Distributionally Robust Collaborative Optimization Operation Strategy for Multi-Integrated Energy Systems Considers Energy Trading

by Wenyuan Sun, Nan Jiang, Tianqi Wang, Shuailing Ma, Yingai Jin and Firoz Alam

Sustainability 2025, 17(24), 11377; https://doi.org/10.3390/su172411377 - 18 Dec 2025

Viewed by 335

Abstract

The strong uncertainty of renewable energy poses significant reliability and safety challenges for the coordinated operation of multi-integrated energy systems (MIES). To address this, a data-driven two-stage distributed robust collaborative optimization scheduling model for MIES is proposed, based on a spatiotemporal fusion conditional [...] Read more.

The strong uncertainty of renewable energy poses significant reliability and safety challenges for the coordinated operation of multi-integrated energy systems (MIES). To address this, a data-driven two-stage distributed robust collaborative optimization scheduling model for MIES is proposed, based on a spatiotemporal fusion conditional diffusion model (STF-CDM). First, to more accurately capture the uncertainty in renewable energy output, the model utilizes a scenario set generated by the STF-CDM model and reduced via the K-means clustering algorithm as the initial renewable energy scenarios for the distributed robust optimization set. The STF-CDM model employs a Temporal module component (TMC) unit composed of Transformer time-series modules and a Spatial module component (SMC) unit composed of CNN neural networks for feature extraction and fusion of time-series and spatial-series data. Second, a benefit allocation method based on multi-energy trading contribution rates is proposed to achieve equitable distribution of cooperative gains. Finally, to protect participant privacy and enhance computational efficiency, an alternating direction multiplier method (ADMM) coupled with parallelizable column and constraint generation (C&CG) is employed to solve the energy trading problem. The case analysis results demonstrate that the STF-CDM model proposed in this study exhibits superior performance in addressing the uncertainty of renewable energy output. Concurrently, the asymmetric Nash game mechanism and the ADMM-C&CG solution algorithm proposed in this study achieve a fair and reasonable distribution of benefits among all participants when handling energy transactions and cooperative gains. This is accomplished while ensuring system robustness, economic efficiency, and privacy. Full article

(This article belongs to the Section Energy Sustainability)

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31 pages, 3097 KB

Open AccessArticle

Office Activity Taxonomy in the Digital Transition Era: Towards Situationally Aware Buildings

by Veronica Martins Gnecco, Anja Pogladič, Agnese Chiucchiù, Ilaria Pigliautile, Sara Arko and Anna Laura Pisello

Sustainability 2025, 17(24), 11376; https://doi.org/10.3390/su172411376 - 18 Dec 2025

Viewed by 391

Abstract

In the context of the digital transition, office environments are increasingly shaped by flexibility, technological integration, and occupant-centered design. These transformations influence not only building operations but also the social dynamics and well-being of workers, thereby intersecting with the broader goals of socially [...] Read more.

In the context of the digital transition, office environments are increasingly shaped by flexibility, technological integration, and occupant-centered design. These transformations influence not only building operations but also the social dynamics and well-being of workers, thereby intersecting with the broader goals of socially sustainable design. To address this complexity, Building Management Systems (BMS) and Digital Twins must evolve from static automation to adaptive frameworks that recognize and respond to diverse workplace activities and social interactions. This study proposes a standardized taxonomy of office activities as a foundation for activity recognition and environment adaptation. A systematic literature review identified key activity categories and defining attributes, which were refined and validated through direct observations, diary logs, and semi-structured interviews in small, shared offices with open-plan workspaces. The resulting taxonomy comprises four main classes—Focused Work, Meetings, Shallow Work, and Resting—each defined by contextual attributes such as plannability, social interaction, number of participants, posture, modality, location, and duration. The framework supports the development of human-centric, situationally aware BMS capable of dynamically adjusting environmental conditions to promote comfort, well-being, and energy efficiency. By integrating user agendas and feedback, this approach contributes to more inclusive and socially sustainable work environments, aligning with the emerging paradigm of adaptive, human-oriented architecture. Full article

(This article belongs to the Special Issue Socially Sustainable Urban and Architectural Design)

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34 pages, 3067 KB

Open AccessArticle

Circularity and Climate Mitigation in the EU27: An Elasticity-Based Scenario Analysis to 2050

by Olena Pavlova, Oksana Liashenko, Kostiantyn Pavlov, Maryna Nagara, Kamil Wiktor, Agata Kutyba and Olha Panivska

Sustainability 2025, 17(24), 11375; https://doi.org/10.3390/su172411375 - 18 Dec 2025

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Abstract

This study quantifies the decarbonisation potential of enhanced material circularity in the EU27 over the 2015–2022 period by integrating material flow data with elasticity-based emissions modelling. Using panel regression and logarithmic mean Divisia index (LMDI) decomposition, we evaluate the influence of recycling rate [...] Read more.

This study quantifies the decarbonisation potential of enhanced material circularity in the EU27 over the 2015–2022 period by integrating material flow data with elasticity-based emissions modelling. Using panel regression and logarithmic mean Divisia index (LMDI) decomposition, we evaluate the influence of recycling rate acceleration and material intensity decline on material-embedded emissions over the 2015–2022 period. The findings indicate that although recycling rates increased by 42% during this time, virgin materials remain responsible for over 97% of emissions. Decomposition results reveal that intensity improvements—measured as a cumulative LMDI intensity effect of −0.867 log-change units, equivalent to approximately a 58% reduction in emissions—offset most of the upward pressure from growing material demand and shifting composition. Scenario projections to 2050, based on empirically derived elasticities, show that accelerated circular economy pathways—assuming 4% annual growth in recycling rates and a 3% decline in material intensity—can reduce emissions by over 90%. In contrast, baseline policies fall short of net-zero targets. Sensitivity analysis confirms that policy ambition dominates parameter uncertainty in shaping future emissions trajectories. The study highlights the critical role of combined demand-side and supply-side measures in aligning material consumption with climate goals. The study highlights the crucial role of combined demand-side and supply-side measures in aligning material consumption with climate goals and advancing progress toward Sustainable Development Goal 12 (Responsible Consumption and Production). Full article

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23 pages, 4122 KB

Open AccessArticle

Antifungal Activity of Ag and ZnO Nanoparticles Co-Loaded in Zinc–Alginate Microparticles

by Marko Vinceković, Lana Živković Genzić, Nenad Jalšenjak, Joško Kaliterna, Iva Rezić Meštrović, Mislav Majdak, Suzana Šegota, Marijan Marciuš, Lidija Svečnjak, Ivica Kos, Ivona Švenda and Katarina Martinko

Sustainability 2025, 17(24), 11374; https://doi.org/10.3390/su172411374 - 18 Dec 2025

Viewed by 379

Abstract

Fungal infections caused by Fusarium solani demand sustainable alternatives to conventional fungicides and free nanoparticles, which often show poor stability and rapid release. This study developed zinc-crosslinked alginate microparticles containing silver (AgNPs), zinc oxide (ZnONPs), or both to improve nanoparticle stability, sustain release, [...] Read more.

Fungal infections caused by Fusarium solani demand sustainable alternatives to conventional fungicides and free nanoparticles, which often show poor stability and rapid release. This study developed zinc-crosslinked alginate microparticles containing silver (AgNPs), zinc oxide (ZnONPs), or both to improve nanoparticle stability, sustain release, and enhance antifungal efficacy. Microparticles were produced by ionic gelation and characterized by FTIR, microscopy, swelling analysis, encapsulation efficiency, and kinetic modeling. AgNPs weakened hydrogen bonding within alginate, yielding rough, porous structures, whereas ZnONPs strengthened COO⁻–Zn²⁺ interactions, forming smoother surfaces with smaller pores; co-loaded particles combined both characteristics. Encapsulation efficiencies were 77.9% (AgNPs) and 98.6% (ZnONPs), with co-loaded systems retaining 64.0% and 98.9%, respectively. Swelling was highest in AgNP-loaded microparticles (63.8%) and lowest in ZnONP and co-loaded systems (≈42%). AgNPs followed anomalous transport (n = 0.65), while ZnONPs transitioned from Fickian diffusion (n ≈ 0.36–0.38) to zero-order release (K₀ = 1.00 for ZnONPs alone; 0.80 co-loaded). Antifungal tests showed strong inhibition: 80.7% for AgNPs, 91.4% for ZnONPs, and 99.7% for co-loaded formulations. Microscopy confirmed membrane disruption, hyphal collapse, and ROS-mediated damage, with the strongest effects in co-loaded samples. These results demonstrate a tunable, synergistic, sustained-release platform that outperforms single nanoparticles and offers a promising strategy for sustainable crop protection. Full article

(This article belongs to the Special Issue Green Technology and Biological Approaches to Sustainable Agriculture)

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39 pages, 2324 KB

Open AccessArticle

The Influence of Perceived Organizational Support on Sustainable AI Adoption in Digital Transformation: An Integrated SEM–ANN–NCA Model

by Yu Feng, Yi Feng and Ziyang Liu

Sustainability 2025, 17(24), 11373; https://doi.org/10.3390/su172411373 - 18 Dec 2025

Viewed by 472

Abstract

In the era of sustainable digital transformation, organizations increasingly rely on artificial intelligence (AI) to enhance efficiency, innovation, and long-term competitiveness. However, employees’ psychological barriers, including technostress and innovation resistance, continue to constrain successful and sustainable AI adoption. Grounded in Social Exchange Theory [...] Read more.

In the era of sustainable digital transformation, organizations increasingly rely on artificial intelligence (AI) to enhance efficiency, innovation, and long-term competitiveness. However, employees’ psychological barriers, including technostress and innovation resistance, continue to constrain successful and sustainable AI adoption. Grounded in Social Exchange Theory (SET), Conservation of Resources Theory (COR), Diffusion of Innovation Theory (DOI), and the Technology Acceptance Model (TAM), this study develops an integrated model linking perceived organizational support (POS)—comprising emotional, informational, and instrumental dimensions—to employees’ sustainable AI adoption through the dual mediating roles of technostress and innovation resistance. Based on 426 valid responses collected from multiple industries, a triadic hybrid approach combining Structural Equation Modeling (SEM), Artificial Neural Networks (ANNs), and Necessary Condition Analysis (NCA) was applied to capture both linear and nonlinear mechanisms. The results reveal that Informational Support (IFS) is the most influential factor and constitutes the sole necessary condition for high-level AI adoption, while emotional and instrumental support indirectly promote sustainable adoption by mitigating employees’ stress and resistance. This study contributes to sustainable management and AI adoption research by providing insights into the potential hierarchical and threshold patterns of organizational support systems in digital transformation. It also provides managerial implications for designing transparent, empathetic, and resource-efficient support ecosystems that foster employee-driven intelligent transformation. Full article

(This article belongs to the Special Issue Digital Marketing and Sustainable Circular Economy)

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30 pages, 1870 KB

Open AccessArticle

Spatiotemporal Evolution and Spillover Effects of Tourism Industry and Inclusive Green Growth Coordination in the Yellow River Basin: Toward Sustainable Development

by Fei Lu and Sung Joon Yoon

Sustainability 2025, 17(24), 11372; https://doi.org/10.3390/su172411372 - 18 Dec 2025

Viewed by 278

Abstract

Balancing tourism industry (TI) growth and ecological protection is critical for sustainable development in the Yellow River Basin (YRB), China’s vital ecological security barrier and economic belt. However, existing research lacks a spatial perspective on the coordinated development between TI and inclusive green [...] Read more.

Balancing tourism industry (TI) growth and ecological protection is critical for sustainable development in the Yellow River Basin (YRB), China’s vital ecological security barrier and economic belt. However, existing research lacks a spatial perspective on the coordinated development between TI and inclusive green growth (IGG), with limited understanding of cross-regional spillover mechanisms. Based on panel data from 75 cities in the YRB (2011–2023), this study constructs a comprehensive evaluation system encompassing the scale, structure, and potential dimensions of the TI and the economic, social, livelihood, and environmental dimensions of IGG. The study employs the coupling coordination degree (CCD) model, exploratory spatial data analysis (ESDA), and the Spatial Durbin Model (SDM) to examine spatiotemporal evolution and spillover effects. The results reveal an upward yet fluctuating coordination trend with pronounced spatial heterogeneity, characterized by a “downstream–midstream–upstream” gradient pattern, dual-core radiation centered on the Jinan–Qingdao and Xi’an–Zhengzhou agglomerations, and persistent High–High clusters in the Shandong Peninsula contrasted with Low–Low clusters in the upstream Qinghai–Gansu–Ningxia region. Critically, new-quality productive forces exert significant positive direct and spillover effects, while industrial structure and government intervention have inhibitory spatial effects on adjacent cities. Regional heterogeneity analysis confirms factor-endowment-driven differentiation across upstream, midstream, and downstream areas. These findings advance spatial spillover theory in river basin contexts and provide evidence-based pathways for balancing economic growth with ecological protection in ecologically sensitive regions worldwide, directly supporting multiple UN Sustainable Development Goals. Full article

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28 pages, 7867 KB

Open AccessArticle

Efficiency and Running Time Robustness in Real Metro Automatic Train Operation Systems: Insights from a Comprehensive Comparative Study

by María Domínguez, Adrián Fernández-Rodríguez, Asunción P. Cucala and Antonio Fernández-Cardador

Sustainability 2025, 17(24), 11371; https://doi.org/10.3390/su172411371 - 18 Dec 2025

Viewed by 311

Abstract

Automatic Train Operation (ATO) systems are widely deployed in metro networks to improve punctuality, service regularity, and ultimately the sustainability of rail operation. Although eco-driving optimisation has been extensively studied, no previous work has provided a systematic, side-by-side comparison of the two ATO [...] Read more.

Automatic Train Operation (ATO) systems are widely deployed in metro networks to improve punctuality, service regularity, and ultimately the sustainability of rail operation. Although eco-driving optimisation has been extensively studied, no previous work has provided a systematic, side-by-side comparison of the two ATO control philosophies most commonly implemented in metro systems worldwide: (i) Type 1, based on speed holding followed by a single terminal coasting at a kilometre point, and (ii) Type 2, which uses speed thresholds to apply either continuous speed holding or iterative coasting–remotoring cycles. These strategies differ fundamentally in their control logic and may lead to distinct operational and energetic behaviours. This paper presents a comprehensive comparison of these two ATO philosophies using a high-fidelity train movement simulator and Pareto-front optimisation via a multi-objective particle swarm algorithm. 40 interstations of a real metro line were evaluated under realistic comfort and operational constraints, and robustness was assessed through sensitivity to three different passenger-load variations (empty train, nominal load and full load). Results show that, once nominal profiles are implemented, Type 1 has up to 5% variability in running times, and Type 2 has up to 20% variability in energy consumption. In conclusion, a new ATO deployment combining both strategies could better balance energy efficiency and timetable robustness in metro operations. Full article

(This article belongs to the Section Sustainable Transportation)

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64 pages, 6020 KB

Open AccessArticle

Logistics Performance and the Three Pillars of ESG: A Detailed Causal and Predictive Investigation

by Nicola Magaletti, Valeria Notarnicola, Mauro Di Molfetta, Stefano Mariani and Angelo Leogrande

Sustainability 2025, 17(24), 11370; https://doi.org/10.3390/su172411370 - 18 Dec 2025

Viewed by 662

Abstract

This study investigates the complex relationship between the performance of logistics and Environmental, Social, and Governance (ESG) performance, drawing upon the multi-methodological framework of combining econometrics with state-of-the-art machine learning approaches. Employing Instrumental Variable (IV) Panel data regressions, viz., 2SLS and G2SLS, with [...] Read more.

This study investigates the complex relationship between the performance of logistics and Environmental, Social, and Governance (ESG) performance, drawing upon the multi-methodological framework of combining econometrics with state-of-the-art machine learning approaches. Employing Instrumental Variable (IV) Panel data regressions, viz., 2SLS and G2SLS, with data from a balanced panel of 163 countries covering the period from 2007 to 2023, the research thoroughly investigates how the performance of the Logistics Performance Index (LPI) is correlated with a variety of ESG indicators. To enrich the analysis, machine learning models—models based upon regression, viz., Random Forest, k-Nearest Neighbors, Support Vector Machines, Boosting Regression, Decision Tree Regression, and Linear Regressions, and clustering, viz., Density-Based, Neighborhood-Based, and Hierarchical clustering, Fuzzy c-Means, Model-Based, and Random Forest—were applied to uncover unknown structures and predict the behavior of LPI. Empirical evidence suggests that higher improvements in the performance of logistics are systematically correlated with nascent developments in all three dimensions of the environment (E), social (S), and governance (G). The evidence from econometrics suggests that higher LPI goes with environmental trade-offs such as higher emissions of greenhouse gases but cleaner air and usage of resources. On the S dimension, better performance in terms of logistics is correlated with better education performance and reducing child labor, but also demonstrates potential problems such as social imbalances. For G, better governance of logistics goes with better governance, voice and public participation, science productivity, and rule of law. Through both regression and cluster methods, each of the respective parts of ESG were analyzed in isolation, allowing us to study in-depth how the infrastructure of logistics is interacting with sustainability research goals. Overall, the study emphasizes that while modernization is facilitated by the performance of the infrastructure of logistics, this must go hand in hand with policy intervention to make it socially inclusive, environmentally friendly, and institutionally robust. Full article

(This article belongs to the Special Issue Sustainable Logistics and Supply Chain Operations: Risks, Rebuck, and Resilience)

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19 pages, 618 KB

Open AccessArticle

U.S. Monetary Policy and Capital Flows to Emerging Markets: The Role of Capital Controls in Financial Stability

by Tianyou Lin, Linxuan Liu and Xin Liang

Sustainability 2025, 17(24), 11369; https://doi.org/10.3390/su172411369 - 18 Dec 2025

Viewed by 1137

Abstract

This paper investigates the impact of U.S. monetary policy on capital flows to emerging market economies and examines the role of capital controls in moderating this effect. Using a fixed-effects model with panel data from 19 developing nations spanning 2005Q1 to 2024Q3, we [...] Read more.

This paper investigates the impact of U.S. monetary policy on capital flows to emerging market economies and examines the role of capital controls in moderating this effect. Using a fixed-effects model with panel data from 19 developing nations spanning 2005Q1 to 2024Q3, we find that U.S. monetary tightening significantly reduces net capital inflows to these economies, undermining stable financing conditions necessary for long-term development. Countries with stronger capital controls are more insulated from these shocks and demonstrate greater financial resilience. This is because well-designed capital controls primarily target volatile short-term flows that are most susceptible to external policy shocks, while leaving stable, long-term productive investment largely unaffected. The study further reveals that during periods of unconventional monetary policy, the negative impact of U.S. policy shocks was more pronounced; short-term capital flows were highly responsive to policy changes, while foreign direct investment remained largely stable; and low- and middle-income nations experienced more severe disruptions than their high-income counterparts. These findings highlight the value of composition-targeted capital flow management in safeguarding financial stability and supporting sustainable development in emerging markets amid external monetary volatility. Full article

(This article belongs to the Special Issue Advancements in Entrepreneurship, Economic Analysis, and Business Strategy from a Sustainable Perspective)

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27 pages, 2484 KB

Open AccessArticle

Incorporating Life Cycle Assessment into Tunneling Technologies: Environmental Performance of TBM and ADECO–RS Methods

by Daniel Wałach, Justyna Jaskowska-Lemańska and Aleksandra Mach

Sustainability 2025, 17(24), 11368; https://doi.org/10.3390/su172411368 - 18 Dec 2025

Viewed by 307

Abstract

The article presents a quantitative analysis of the influence of selected material and structural parameters on the results of the life cycle assessment of a tunnel lining. The aim of the study was to evaluate the potential for reducing environmental impacts by decreasing [...] Read more.

The article presents a quantitative analysis of the influence of selected material and structural parameters on the results of the life cycle assessment of a tunnel lining. The aim of the study was to evaluate the potential for reducing environmental impacts by decreasing the amount of concrete and reinforcing steel or by modifying the concrete mix composition. The analysis was conducted for two tunneling technologies: TBM and ADECO–RS (14 variants in total). The results indicate that concrete is the dominant factor shaping the environmental impact of the reinforced concrete lining, while reinforcing steel plays a supplementary role, depending on the adopted material variant (4–19%). Despite structural differences, both technologies show a similar level of environmental impacts, which confirms the need for full life cycle analyses and highlights a significant optimization potential within each technology. In the ADECO–RS method, increasing the concrete class did not contribute to reducing environmental impacts, whereas in the TBM method, the use of higher-strength concrete compensated for its higher unit impact by reducing the volume of structural materials. Differences in rankings between indicators confirm the relevance of a comprehensive, multi-criteria analysis in environmental impact assessment. Full article

(This article belongs to the Special Issue Sustainable Development and Analysis of Tunnels and Underground Works)

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16 pages, 5835 KB

Open AccessArticle

Case Study of Dense Hazardous Gas Dispersion in Large Indoor Spaces: Ventilation Layout Analysis with Modeling

by Jacek Hendiger, Marta Chludzińska and Piotr Ziętek

Sustainability 2025, 17(24), 11367; https://doi.org/10.3390/su172411367 - 18 Dec 2025

Viewed by 287

Abstract

The safety of large indoor workspaces hinges on ventilation layout and airflow organization, particularly for dense contaminants that pool near the floor. This qualitative, full-scale case study evaluates chlorine (Cl₂) capture using supporting CFD and visualization experiments in a 20 × [...] Read more.

The safety of large indoor workspaces hinges on ventilation layout and airflow organization, particularly for dense contaminants that pool near the floor. This qualitative, full-scale case study evaluates chlorine (Cl₂) capture using supporting CFD and visualization experiments in a 20 × 13 × 9 m hall. Four exhaust arrangements—low, mid, high, and all levels combined—were tested under two modes: a single grille at 12,000 m³/h and three co-located grilles at 4000 m³/h each (total 12,000 m³/h), with and without an auxiliary supply (2000 m³/h). Removal performance was sensitive to exhaust elevation: low-level extraction consistently confined the plume near the floor, while distributing the same total flow across three levels achieved comparable or improved capture; mid/high extraction was less effective. A practical extraction radius of ≈5 m was identified, and the auxiliary supply improved outcomes only when steering the plume toward the low grille. CFD results showed that, regardless of the lower grille’s duty, the inlet concentration at the low grille was about twice that at the middle grille and more than four times that at the upper grille; in the three-grille configuration, the upper grille received negligible contaminant. These full-scale findings provide geometry-first guidance for dense-gas control in high-ceiling, large-volume spaces. Full article

(This article belongs to the Special Issue Healthy Indoor Environments: Air Quality in Sustainable Public and Healthcare Buildings)

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20 pages, 3069 KB

Open AccessArticle

Spatiotemporal Dynamics and Drivers of Shipping Service Industry Agglomeration and Port–City Synergy: Evidence from Jiangsu Province, China

by Tong Zhang, Linan Du, Husong Xing, Jimeng Tang and Cunrui Ma

Sustainability 2025, 17(24), 11366; https://doi.org/10.3390/su172411366 - 18 Dec 2025

Viewed by 340

Abstract

The shipping service industry plays a pivotal role in enhancing port competitiveness and fostering urban economic growth, yet limited studies systematically integrate its spatial temporal dynamics with the processes driving port–city synergy. This study constructs a three-dimensional analytical framework encompassing port operations, urban [...] Read more.

The shipping service industry plays a pivotal role in enhancing port competitiveness and fostering urban economic growth, yet limited studies systematically integrate its spatial temporal dynamics with the processes driving port–city synergy. This study constructs a three-dimensional analytical framework encompassing port operations, urban economic development, and shipping service industry agglomeration. Using data from 13 port cities in Jiangsu Province (2015–2023), we apply the entropy weight method, coupling coordination degree model, relative development model, and panel Tobit regression to evaluate interaction intensity, coordination patterns, and influencing factors. Results reveal a clear spatial gradient in coupling coordination, higher in southern Jiangsu and lower in the north, driven by disparities in economic foundations, port capacities, and service industry structures. In most cities, port operations and urban economies lag behind shipping service industry agglomeration, reflecting the predominance of low- and mid-end services. Port construction level, cargo and container throughput, economic development, openness, fixed asset investment, and population density significantly promote coordination, whereas R&D capacity shows no significant effect. The findings advance understanding of port–city service interlinkages and provide targeted policy recommendations for differentiated regional development, infrastructure enhancement, and upgrading toward high-end shipping services, with implications for maritime regions worldwide. Full article

(This article belongs to the Special Issue Advanced Studies in Sustainable Urban Planning and Urban Development)

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18 pages, 3688 KB

Open AccessArticle

Assessing Artificial Shading and Evaporative Cooling for Enhanced Outdoor Thermal Comfort at the American University of Beirut

by Zahraa Diab, Hadi Kachmar and Nesreen Ghaddar

Sustainability 2025, 17(24), 11365; https://doi.org/10.3390/su172411365 - 18 Dec 2025

Viewed by 379

Abstract

Urban environments, particularly university campuses, are increasingly exposed to thermal discomfort due to the Urban Heat Island (UHI) effect and intense solar radiation. This study evaluates the effectiveness of passive and hybrid cooling strategies, specifically sun-sail shading and mist cooling, in enhancing outdoor [...] Read more.

Urban environments, particularly university campuses, are increasingly exposed to thermal discomfort due to the Urban Heat Island (UHI) effect and intense solar radiation. This study evaluates the effectiveness of passive and hybrid cooling strategies, specifically sun-sail shading and mist cooling, in enhancing outdoor thermal comfort (OTC) in a university courtyard. The Van Dyck courtyard at the American University of Beirut, located on the East Mediterranean coast, was selected due to its heavy use between 10 am and 2 pm during summer, when ambient temperatures ranged between 32 and 36 °C and relative humidity between 21 and 33%. Thermal variations across four seating areas were analyzed using ENVI-met, a high-resolution microscale model validated against on-site data, achieving Mean Absolute Percentage Errors of 4% for air temperature and 5.2% for relative humidity. Under baseline conditions, Physiological Equivalent Temperature (PET) exceeded 58 °C, indicating severe thermal stress. Several mitigation strategies were evaluated, including three shading configurations, two mist-cooling setups, and a combined system. Results showed that double-layer shading reduced PET by 17.1 °C, mist cooling by 1.2 °C, and the combined system by 20.7 °C. Shading minimized radiant heat gain, while mist cooling enhanced evaporative cooling, jointly bringing thermal sensations closer to slightly warm–comfortable conditions. These cooling interventions also have sustainability value by reducing dependence on mechanically cooled indoor spaces and lowering campus air-conditioning demand. As passive or low-energy measures, shading and mist cooling support climate-adaptive outdoor design in heat-stressed Mediterranean environments. Full article

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28 pages, 3077 KB

Open AccessReview

Sustainable Maritime Decarbonization: A Review of Hydrogen and Ammonia as Future Clean Marine Energies

by Chungkuk Jin, JungHwan Choi, Changhee Lee and MooHyun Kim

Sustainability 2025, 17(24), 11364; https://doi.org/10.3390/su172411364 - 18 Dec 2025

Viewed by 766

Abstract

Maritime transport accounts for approximately 80–90% of global trade and nearly 3% of global greenhouse gas (GHG) emissions. In response, the International Maritime Organization (IMO) adopted an ambitious strategy for net-zero emissions by 2050, critically mandating a Well-to-Wake (WtW) life-cycle assessment for fuels. [...] Read more.

Maritime transport accounts for approximately 80–90% of global trade and nearly 3% of global greenhouse gas (GHG) emissions. In response, the International Maritime Organization (IMO) adopted an ambitious strategy for net-zero emissions by 2050, critically mandating a Well-to-Wake (WtW) life-cycle assessment for fuels. This framework invalidates fuels produced with high carbon intensity, regardless of their emissions at the point of use, thereby compelling the industry to focus on truly clean and sustainable alternatives. This push positions green hydrogen and ammonia as leading solutions, though they present a distinct trade-off. Hydrogen is an ideal fuel with zero-carbon emission in fuel cells but faces significant storage challenges due to its extremely low volumetric energy density and cryogenic requirements. In contrast, ammonia offers superior energy density and easier handling but contends with issues of toxicity and potentially harmful emissions like nitrous oxide. This paper provides a comprehensive review of this complex landscape, analyzing the production, utilization, and associated techno-economic and geopolitical challenges of using hydrogen and ammonia as future marine fuels, with environmental aspects briefly considered. Full article

(This article belongs to the Topic Maritime Transportation in the Blue Economy and Green Shipping Technology)

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18 pages, 4195 KB

Open AccessArticle

Sustainable Cold Region Urban Expansion Assessment Through Impervious Surface Classification and GDP Spatial Simulation

by Guanghong Ren and Luhe Wan

Sustainability 2025, 17(24), 11363; https://doi.org/10.3390/su172411363 - 18 Dec 2025

Viewed by 289

Abstract

In the context of accelerating global urbanization and sustainable development challenges, impervious surfaces, as a key component of urban land cover, are significantly associated with regional economic development. This study takes Harbin, a typical cold region city, as a research object and constructs [...] Read more.

In the context of accelerating global urbanization and sustainable development challenges, impervious surfaces, as a key component of urban land cover, are significantly associated with regional economic development. This study takes Harbin, a typical cold region city, as a research object and constructs a three-level analytical framework of “land surface classification-economic simulation-mechanism analysis.” By innovatively integrating multi-source remote sensing, demographic, and economic data, the research addresses gaps in understanding urban sustainability in cold environments. An enhanced XGBoost algorithm was employed to achieve high-precision classification of ten land surface materials, resulting in a high overall accuracy. Furthermore, a gridded GDP spatialization model developed using high-resolution population data demonstrated superior performance compared to traditional methods. Machine learning-assisted analysis revealed that asphalt and metal surfaces are the most significant impervious materials driving economic output, reflecting the respective influences of transportation infrastructure and industrial agglomeration. Spatial pattern analysis indicates that Harbin’s impervious surfaces exhibit a lower fractal dimension and a distinct grid-like morphology compared to the typical subtropical city of Guangzhou, underscoring urban form adaptations to cold climatic constraints. The strong spatial coupling between gradients of GDP intensity and the attenuation of impervious surface density is quantitatively confirmed. This study provides a quantitative basis and a transferable technical framework for optimizing land use intensity and infrastructure planning in cold cities, thereby offering a scientific foundation for sustainable, intensive land utilization in climate-vulnerable urban systems. Full article

(This article belongs to the Special Issue Geographical Information System for Sustainable Ecology)

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27 pages, 697 KB

Open AccessArticle

Research on the Synergistic Development Path of Enterprise Data Asset Trading and New Quality Productive Forces Under the TOE Framework—Empirical Evidence from China

by Yan Lai, Juan Zhang and Minggui Zheng

Sustainability 2025, 17(24), 11362; https://doi.org/10.3390/su172411362 - 18 Dec 2025

Viewed by 369

Abstract

In the digital economy, promoting enterprise data asset trading and cultivating enterprises’ new quality productive forces are systemic issues. The present paper employs a combined method of QCA and regression analysis to construct a complex mediation model, based on the TOE framework theory [...] Read more.

In the digital economy, promoting enterprise data asset trading and cultivating enterprises’ new quality productive forces are systemic issues. The present paper employs a combined method of QCA and regression analysis to construct a complex mediation model, based on the TOE framework theory and from a configurational perspective. This study examines the driving mechanisms behind corporate data asset transactions and the development of new-quality productive forces among Chinese A-share listed companies from 2020 to 2024, focusing on the interplay of technological, organizational, and environmental factors. The study finds that there are three configurations for achieving high-level enterprise data asset trading: the “technology–organization–environment” synergistic-driven type, the “environmental constraint–technological compensation” driven type, and the “organizational operation–environmental ecology” driven type. Among them, the level of enterprise data elements, the structure of enterprise human capital, and urban data governance are key factors in achieving high disclosure of enterprise data asset trading and a leap in new quality productive forces. The research conclusions provide valuable insights for enterprises considering a development strategy that combines data asset trading with new quality productive forces. Full article

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37 pages, 2427 KB

Open AccessArticle

Distances from Efficiency: A Territorial Assessment of the Performance of the Circular Economy in Italy

by Roberta Arbolino, Luisa De Simone and Antonio Lopes

Sustainability 2025, 17(24), 11361; https://doi.org/10.3390/su172411361 - 18 Dec 2025

Viewed by 298

Abstract

This study investigates territorial disparities in transition toward circular economy within Italy, introducing an innovative methodological approach aimed at measuring regional efficiency and inequality. The research develops two complementary analytical tools: the Regional Circular Economy Index (ReCEI), a composite indicator designed for comparative [...] Read more.

This study investigates territorial disparities in transition toward circular economy within Italy, introducing an innovative methodological approach aimed at measuring regional efficiency and inequality. The research develops two complementary analytical tools: the Regional Circular Economy Index (ReCEI), a composite indicator designed for comparative evaluation of circular economy performance across regions, and the Regional Circular Economy Disparity Index (ReCED), inspired by the model of Sen which quantifies both the magnitude and spatial distribution of territorial inequalities. Applying this integrated framework to the 20 Italian regions reveals a pronounced heterogeneity: a select group of regions achieves or approaches efficiency benchmarks, whereas others exhibit persistent structural delays linked to infrastructural, institutional and innovative deficits. These findings, thus, confirm the persistence of a territorial dualism in the circular transition, only partially mitigated by instances of advanced governance and coordinated policies. Full article

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20 pages, 1475 KB

Open AccessArticle

The Impact of Energy Transition on Residents’ Health: Evidence from a Quasi-Natural Experiment of China’s New Energy Demonstration City Pilot Program

by Peisen Hu, Aijun Yang and Chongjia Luo

Sustainability 2025, 17(24), 11360; https://doi.org/10.3390/su172411360 - 18 Dec 2025

Viewed by 287

Abstract

Promoting the green transition of the energy structure is crucial for achieving climate mitigation and safeguarding public health. Using data from the China Family Panel Studies, this paper takes the New Energy Demonstration City pilot (NEDCP) program as a quasi-natural experiment to empirically [...] Read more.

Promoting the green transition of the energy structure is crucial for achieving climate mitigation and safeguarding public health. Using data from the China Family Panel Studies, this paper takes the New Energy Demonstration City pilot (NEDCP) program as a quasi-natural experiment to empirically examine energy transition’s impact on residents’ health. The results show that the NEDCP program significantly improves residents’ health, with benefits that are almost equal to those of regular physical exercise. This finding remains robust after a series of robustness and endogeneity checks. Mechanism analyses indicate that the NEDCP program promotes the substitution of traditional fossil energy with new energy, improving environmental quality, and thereby enhancing residents’ health. Moreover, rising carbon prices and stricter urban environmental regulation further amplify these health benefits. Heterogeneity analyses reveal that the impact of the NEDCP program on residents’ health is more pronounced among vulnerable populations, including smokers and older adults, as well as in resource-dependent, economically underdeveloped, and environmentally underregulated cities, highlighting the NEDCP program’s positive role in advancing health equity across different demographic groups and regions. This study offers valuable insights into how the NEDCP program promotes public health and advances health equity. Full article

(This article belongs to the Section Energy Sustainability)

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21 pages, 2122 KB

Open AccessArticle

A Case Study on Advanced Detection and Management of Fugitive Methane Emissions in the Romanian Oil and Gas Sector

by Silvian Suditu, Liviu Dumitrache, Gheorghe Branoiu, Stefan Dragut, Cristian Nicolae Eparu, Ioana Gabriela Stan and Alina Petronela Prundurel

Sustainability 2025, 17(24), 11359; https://doi.org/10.3390/su172411359 - 18 Dec 2025

Viewed by 366

Abstract

In the context of intensifying global efforts to mitigate climate change, methane emissions from the oil and gas sector have emerged as a critical environmental and regulatory challenge, given methane’s high global warming potential over short timeframes. This study investigates methane emissions from [...] Read more.

In the context of intensifying global efforts to mitigate climate change, methane emissions from the oil and gas sector have emerged as a critical environmental and regulatory challenge, given methane’s high global warming potential over short timeframes. This study investigates methane emissions from representative extraction and production of oil and gas facilities in Romania, focusing on fugitive emissions from wells and associated processing infrastructure. The research is grounded in the implementation of a comprehensive Leak Detection and Repair (LDAR) program, aligned with OGMP 2.0 standards, and utilizes advanced detection technologies such as Flame Ionization Detectors (FID), Optical Gas Imaging (OGI), and Quantitative Optical Gas Imaging (QOGI). A systematic inventory and screening of thousands of components enabled the precise identification and quantification of methane leaks, providing actionable data for maintenance and emissions management. The findings highlight that, although the proportion of leaking components is relatively low, cumulative emissions are significant, with block valves, connectors, and compressor shaft seals identified as the most frequent sources of major leaks. The study underscores the importance of rigorous preventive and corrective maintenance, rapid leak remediation, and the adoption of modern detection and continuous monitoring technologies. The approach developed offers a robust framework for regulatory compliance and supports the transition from inventory-based to measurement-based emissions reporting, in line with recent European regulations. Ultimately, effective methane management not only fulfills environmental obligations but also delivers economic benefits by reducing product losses and enhancing operational efficiency, contributing to the decarbonization and sustainability objectives of the energy sector. Full article

(This article belongs to the Section Air, Climate Change and Sustainability)

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21 pages, 538 KB

Open AccessReview

Literature Review on Measuring Sustainable Performance in the Retail Sector: A Review of Energy Efficiency Strategies and Their Key Performance Indicators in Supermarkets

by Marios Terzis and Katerina Gotzamani

Sustainability 2025, 17(24), 11358; https://doi.org/10.3390/su172411358 - 18 Dec 2025

Viewed by 603

Abstract

The concept of sustainability in the supermarket sector has emerged as a strategic priority, as companies are required to reduce their environmental footprint and enhance their social and economic performance. The aim of this literature review is to identify, document, and analyze the [...] Read more.

The concept of sustainability in the supermarket sector has emerged as a strategic priority, as companies are required to reduce their environmental footprint and enhance their social and economic performance. The aim of this literature review is to identify, document, and analyze the key performance indicators (KPIs) applied in the sector, with emphasis on environmental, social, and economic dimensions, and to investigate the extent to which technical energy interventions are linked to business and consumer benefits. The methodology was inspired by the general logic of organized search and selection procedures, and for this reason, elements of the PRISMA framework were used, with a search conducted across multiple international scientific databases and selection criteria ensuring the validity and relevance of the sources. The analysis classified the indicators into the following three categories: environmental (e.g., CO₂ emissions, energy consumption), social (e.g., customer satisfaction, corporate image), and economic (e.g., ESG score, return on investment). The study revealed substantial progress made by supermarket chains globally in adopting energy-efficiency technologies, such as LED lighting and renewable energy with proven benefits in reducing consumption and consequently, improving environmental performance. However, a lack of holistic integration between technical interventions and social-economic indicators was identified, limiting the use of KPIs as a strategic tool for guiding specific sustainability strategies. This research concludes that there is a need to develop unified, sector-specific measurement frameworks that integrate environmental, social, and economic parameters, as well as empirical research that quantitatively connects energy strategies with business and consumer performance through comparable indicators in the context of supermarket operations, thereby opening ground for further exploration of the field. Full article

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25 pages, 2515 KB

Open AccessSystematic Review

Systematic Review of Smart Elderly Care in Digital Environments: Toward Sustainable Wellbeing for Older Adults

by Jiaqi Liu and Bo Wang

Sustainability 2025, 17(24), 11357; https://doi.org/10.3390/su172411357 - 18 Dec 2025

Viewed by 859

Abstract

The growing proportion of older adults has created significant societal pressure for sustainable, inclusive solutions that enhance health, autonomy, and well-being in old age. Smart elderly care has therefore emerged as a multidisciplinary research frontier at the intersection of technology, health, and social [...] Read more.

The growing proportion of older adults has created significant societal pressure for sustainable, inclusive solutions that enhance health, autonomy, and well-being in old age. Smart elderly care has therefore emerged as a multidisciplinary research frontier at the intersection of technology, health, and social sustainability. This study provides a comprehensive systematic review to map and conceptualize its evolving landscape in the digital era. Following the PRISMA guidelines, 55 peer-reviewed articles published in the Web of Science database were analyzed using document co-citation analysis and natural language processing-based content analysis, utilizing CiteSpace and Leximancer for implementation. The findings reveal that existing studies have predominantly focused on technology acceptance and adoption among older adults, with quantitative approaches such as Structural Equation Modeling within the Technology Acceptance Model framework being most frequently used. Building on these insights, the review identifies five key directions for advancing sustainable wellbeing: (1) conceptual clarification and operationalization of smart elderly care, (2) theoretical integration across disciplines, (3) examination of influencing factors shaping user engagement, (4) evaluation of social and well-being outcomes, and (5) methodological and disciplinary diversification. By synthesizing fragmented knowledge into a coherent framework, this study contributes to the understanding of smart elderly care as a critical component of sustainable aging societies and lays the groundwork for future academic inquiry and policy innovation. Full article

(This article belongs to the Special Issue Engineering Psychology: Human-Orientated Design and Sustainable Wellbeing)

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