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Sustainability

Sustainability is an international, peer-reviewed, open-access journal on environmental, cultural, economic, and social sustainability of human beings, published semimonthly online by MDPI. The Canadian Urban Transit Research & Innovation Consortium (CUTRIC), International Council for Research and Innovation in Building and Construction (CIB) and Urban Land Institute (ULI) are affiliated with Sustainability and their members receive discounts on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE and SSCI (Web of Science), GEOBASE, GeoRef, Inspec, RePEc, CAPlus / SciFinder, and other databases.
Journal Rank: JCR - Q2 (Environmental Studies) / CiteScore - Q1 (Geography, Planning and Development)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.3 days after submission; acceptance to publication is undertaken in 3.4 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Testimonials: See what our editors and authors say about Sustainability.
Companion journals for Sustainability include: World, Sustainable Chemistry, Conservation, Future Transportation, Architecture, Standards, Merits, Bioresources and Bioproducts and Accounting and Auditing.

Impact Factor: 3.3 (2024); 5-Year Impact Factor: 3.6 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2071-1050

Latest Articles

17 pages, 1413 KB

Open AccessArticle

Sustainable Urban Futures: Transportation and Development in Riyadh, Jeddah, and Neom

by Khalid Mohammed Almatar

Sustainability 2025, 17(22), 10133; https://doi.org/10.3390/su172210133 (registering DOI) - 12 Nov 2025

This study explores sustainable urbanism in the three largest Saudi Arabian cities—Riyadh, Jeddah, and NEOM—in the context of Vision 2030. Qualitative methodology was used, which incorporated environmental, social, economic, governance, and mobility aspects. The analysis of ten semi-structured interviews with planners, engineers, and [...] Read more.

This study explores sustainable urbanism in the three largest Saudi Arabian cities—Riyadh, Jeddah, and NEOM—in the context of Vision 2030. Qualitative methodology was used, which incorporated environmental, social, economic, governance, and mobility aspects. The analysis of ten semi-structured interviews with planners, engineers, and policy officials was based on Strategic Environmental Assessment (SEA), Sustainable Urbanism, and Participatory Governance models. The results indicate that Riyadh presents structural congruence and consistency of policies, Jeddah is characterized by disjointed governance and poor coordination, and NEOM is characterized by futuristic aspirations with unpredictable social inclusiveness. The paper highlights that more powerful integration of governance, participatory planning, and realistic implementation is required to create a balance between technological innovations and equity in society. It adds to the current knowledge of how the global sustainability models can be localized in the fast-changing cities of the Gulf. Full article

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28 pages, 1653 KB

Open AccessArticle

Application of Restricted Lanes Within Three Legs Roundabout at King Abdulaziz University (KAU)

by Alaa R. Sindi, Hatan S. Turkstani and Ahmed S. Alzahrani

Sustainability 2025, 17(22), 10132; https://doi.org/10.3390/su172210132 (registering DOI) - 12 Nov 2025

The three-leg 50-Years Roundabout at King Abdulaziz University (KAU) is known for its vibrance and important location as it is located at the center of several major buildings and hospitals. In recent years, the roundabout is witnessing a huge demand that influences the [...] Read more.

The three-leg 50-Years Roundabout at King Abdulaziz University (KAU) is known for its vibrance and important location as it is located at the center of several major buildings and hospitals. In recent years, the roundabout is witnessing a huge demand that influences the university road networks’ level of service, “LOS”, which in return, has negative impacts on students and faculties in terms of delay and travel time. Several treatments can be implemented along the roundabout. One of those treatments is applying restrictions during morning peak hours such as blocking and restricting specific lanes. This treatment has the advantage of reducing conflict points that cause sudden and frequent stops at the roundabout; as a result, delay and congestion occur. By reducing conflict points, traffic flow can be improved, in addition to enhancing safety and promoting sustainability. This paper examines the base condition of the 50-Years Roundabout in terms of traffic flow, LOS, delay, capacity, and toxic emissions, and proposes traffic system management (TSM) strategies through applying restricted and designated lanes to improve traffic condition. The study employs PTV Vissim, SIDRA Intersection, and Surrogate Safety Assessment Model “SSAM” to examine the base and proposed conditions. The results show a significant improvement through the reduction in conflict points, so that reflects the positive impacts on sustainability, congestion, delay, travel time, LOS, and overall toxic emissions. Full article

(This article belongs to the Special Issue Transportation Systems and Infrastructures Planning, Optimization, and Management)

14 pages, 1359 KB

Open AccessArticle

Geospatial Technology Utilization for Evaluating Land Suitability for Irrigation

by Asset Yegizbayeva, Nurgul Aitekeyeva, Kristina Konstantinova, Nurlan Bekmukhamedov, Nurdaulet Zhumabay and Nurlan Balgabayev

Sustainability 2025, 17(22), 10131; https://doi.org/10.3390/su172210131 (registering DOI) - 12 Nov 2025

Land is a limited yet vital resource, which is fundamental for food security and national stability. Ensuring its effective use requires modern tools to support informed decision making. This study evaluates land suitability for irrigation in the Kyzylorda region of Kazakhstan, with the [...] Read more.

Land is a limited yet vital resource, which is fundamental for food security and national stability. Ensuring its effective use requires modern tools to support informed decision making. This study evaluates land suitability for irrigation in the Kyzylorda region of Kazakhstan, with the objective of identifying areas appropriate for crop expansion. A multidimensional approach was employed, integrating soil properties, topography, proximity to water sources, and existing land use patterns, with suitability classes defined according to the Food and Agriculture Organization’s framework. The Analytic Hierarchy Process, based on pair-wise comparisons and Saaty’s scale, was used to assign weights to each factor. The findings reveal that 30% of highly suitable land and 80% of suitable land remain uncultivated. Conversely, 10% of the current cropland is located in marginally suitable area—likely a result of historical land use decisions or the limited availability of optimal land. This research responds to the specific challenges of arid climates and water scarcity by providing a decision-support tool that promotes sustainable land use, strengthens food security, and encourages responsible land management. Full article

(This article belongs to the Section Sustainable Agriculture)

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18 pages, 689 KB

Open AccessArticle

Sustainable Decision-Making in Higher Education: An AHP-NWA Framework for Evaluating Learning Management Systems

by Ana Veljić, Dejan Viduka, Luka Ilić, Darjan Karabasevic, Aleksandar Šijan and Miloš Papić

Sustainability 2025, 17(22), 10130; https://doi.org/10.3390/su172210130 (registering DOI) - 12 Nov 2025

This paper applies a hybrid multi-criteria decision-making (MCDM) model that integrates the Analytic Hierarchy Process (AHP) for structured weighting of evaluation criteria with the Net Worth Analysis (NWA) method for value-based aggregation of scores. The proposed framework was employed to evaluate Learning Management [...] Read more.

This paper applies a hybrid multi-criteria decision-making (MCDM) model that integrates the Analytic Hierarchy Process (AHP) for structured weighting of evaluation criteria with the Net Worth Analysis (NWA) method for value-based aggregation of scores. The proposed framework was employed to evaluate Learning Management Systems (LMS) in higher education, involving two independent expert panels representing management and IT perspectives. Results of the AHP analysis show that cost (28%), security (22%), and usability (17%) are the most influential criteria in the decision-making process, reflecting institutional priorities for financial efficiency, safety and ease of use. Based on the combined AHP-NWA model, Moodle 4.3 emerged as the most sustainable choice (0.586), followed by Atutor 2.2.1 (0.541) and Blackboard (SaaS edition) (0.490). The inclusion of sensitivity and scenario analyses confirmed the robustness of the model, demonstrating that the ranking of alternatives remains stable under variations in weighting factors and different strategic priorities. By framing LMS evaluation within the context of sustainable digital transformation, the study emphasizes how transparent and systematic decision-making supports long-term institutional resilience and aligns with the principles of Education for Sustainable Development (ESD). In addition, the framework contributes to the achievement of Sustainable Development Goal 4 (Quality Education), by guiding higher education institutions toward inclusive, resilient and cost-effective digital solutions. Full article

(This article belongs to the Special Issue E-Learning and Educational Technologies for Sustainable Transformation of Education)

28 pages, 2147 KB

Open AccessArticle

Environmentally Friendly Product Personality: The Role of Materials, Color, and Light in Car Interiors

by Franka Wehr and Martin Luccarelli

Sustainability 2025, 17(22), 10129; https://doi.org/10.3390/su172210129 (registering DOI) - 12 Nov 2025

The targeting of environmentally conscious German car drivers through product aesthetics can foster the acceptance of sustainable cars. No guidelines are currently available to designers to create product personality based on environmentally friendly design cues (EFDCs). The aim of this paper was to [...] Read more.

The targeting of environmentally conscious German car drivers through product aesthetics can foster the acceptance of sustainable cars. No guidelines are currently available to designers to create product personality based on environmentally friendly design cues (EFDCs). The aim of this paper was to explore EFDCs for car interiors through bio-based materials. To address this topic, Study 1 examined a collection of bio-based material samples and samples featuring specific colors and reactions to light to determine their potential for the creation of an environmentally friendly product personality. Study 2 built on the implications of the former to examine the contribution of blue as a color and glowing attribute on the development of EFDCs. Wood veneer, cork, and cotton fabric were perceived as sustainable, natural, and renewable by most of the subjects. Brown and white leather was also perceived as sustainable. Moreover, the perception of the naturalness of materials in direct contact with blue light was reduced. Visual texture features for EFDC design are visible fibers or a wooden look. Haptic features include soft, warm, and rough surfaces, while glare, shimmer, a shiny surface, and smoothness should be avoided. The color brown should be considered, while blue, green, and yellow should be avoided. Full article

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26 pages, 1826 KB

Open AccessArticle

Research on the Characteristics of the Global Trade Network of Antimony Products and Its Influencing Factors

by Jianguo Tang, Ligang Xu, Ying Zhang and Xiang Guo

Sustainability 2025, 17(22), 10128; https://doi.org/10.3390/su172210128 (registering DOI) - 12 Nov 2025

As a critical raw material in the semiconductor and new energy sectors, antimony is a strategic mineral resource for nations to safeguard industrial chain security. However, the scarcity of its resources and the complexity of its trade pattern underscore the urgency of antimony-related [...] Read more.

As a critical raw material in the semiconductor and new energy sectors, antimony is a strategic mineral resource for nations to safeguard industrial chain security. However, the scarcity of its resources and the complexity of its trade pattern underscore the urgency of antimony-related research. This study aims to reveal the structural characteristics of the global antimony trade network and explore the external factors influencing trade. Based on global antimony trade data from 2007 to 2022, the characteristics of the antimony trade network were analyzed using the complex network analysis method, and the influencing factors of antimony trade were examined via the fixed effects model. The results show that the global antimony trade network maintains a density of 0.05–0.06, with an average path length of 2.4–2.7 and a network diameter that mainly fluctuates between 5 and 6. The average clustering coefficient fluctuates within the range of 0.35–0.45. Overall, the network exhibits the characteristics of stable transmission efficiency, loose overall connectivity, and local agglomeration without a consistent upward or downward trend. Countries such as Germany, China, and the United States occupy core positions in the network. The fixed effects model indicates that GDP and LOGISTICS development are key factors promoting trade, while TARIFFS and REGULATORY policies have a significant inhibitory effect on trade. Therefore, ① Focus on the High-End Development of the Antimony Industry Chain and Promote the In-Depth Integration of Antimony Trade with the Semiconductor and New Energy Industries; ② Improve the Cross-Border Logistics and Warehousing System for Antimony Trade to Ensure the Efficient Circulation of Strategic Resources; ③ Promote; Promote Tariff Liberalization in Antimony Trade and Eliminate Market Access Barriers; ④ Strengthen the Government’s Strategic Support for the Antimony Industry to Enhance Global Discourse Power in Antimony Trade; Trade; ⑤ Maintain Macroeconomic Stability and Flexibly Manage Exchange Rates to Safeguard the Resilience of Antimony Trade. Full article

25 pages, 5581 KB

Open AccessArticle

Seasonal and Multi-Year Wind Speed Forecasting Using BP-PSO Neural Networks Across Coastal Regions in China

by Shujie Jiang, Jiayi Jin and Shu Dai

Sustainability 2025, 17(22), 10127; https://doi.org/10.3390/su172210127 (registering DOI) - 12 Nov 2025

Accurate short-term wind speed forecasting is essential for the sustainable operation and planning of coastal wind farms. This study develops an improved BP-PSO hybrid model that integrates particle-swarm optimization, time-ordered walk-forward validation, and uncertainty quantification through block-bootstrap confidence intervals and Monte-Carlo dropout prediction [...] Read more.

Accurate short-term wind speed forecasting is essential for the sustainable operation and planning of coastal wind farms. This study develops an improved BP-PSO hybrid model that integrates particle-swarm optimization, time-ordered walk-forward validation, and uncertainty quantification through block-bootstrap confidence intervals and Monte-Carlo dropout prediction intervals. Using multi-year and seasonal datasets from four coastal stations in China—from Bohai Bay (LHT, XCS, ZFD) to Zhejiang Province (SSN)—the proposed model achieves high predictive accuracy, with RMSE values between 1.09 and 1.54 m/s, MAE between 0.79 and 1.10 m/s, and R² exceeding 0.70 at most sites. The multi-year configuration provides the most stable and robust results, while autumn at ZFD yields the highest errors due to intensified turbulence. XCS and SSN exhibit the most consistent performance, confirming the model’s spatial adaptability across distinct climatic regions. Compared with the ARIMA and persistence baselines, BP-PSO reduces RMSE by over 50%, demonstrating improved efficiency and generalization. These results highlight the potential of intelligent data-driven forecasting frameworks to enhance renewable energy reliability and sustainability by enabling more accurate wind-power scheduling, grid stability, and coastal energy system resilience. Full article

(This article belongs to the Section Sustainable Engineering and Science)

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22 pages, 1636 KB

Open AccessArticle

Analysis of Spatial Changes in Urban Areas Due to Revitalization Investments Based on China and Poland

by Yingxin Wang and Adam Choryński

Sustainability 2025, 17(22), 10126; https://doi.org/10.3390/su172210126 (registering DOI) - 12 Nov 2025

In order to address the social, economic, and environmental challenges arising from urban development, some urban revitalization plans have been proposed. With the implementation of these plans, the spatial pattern of the region has also undergone corresponding changes. Some of the revitalization projects [...] Read more.

In order to address the social, economic, and environmental challenges arising from urban development, some urban revitalization plans have been proposed. With the implementation of these plans, the spatial pattern of the region has also undergone corresponding changes. Some of the revitalization projects have driven economic growth while accompanied by ecological degradation, while others have achieved coordinated development and protection. This study selected eight urban revitalization cases, based on remote sensing (RS) and geographic information system (GIS), and used the Random Forest (RF) machine learning method to dynamically monitor the spatial changes in the region before and after revitalization through Land Use and Land Cover (LULC) analysis. The research results show that among the eight cases, only the revitalization cases located in Beijing and Swarzędz reflected an increase in water and vegetation areas, while the built-up area decreased. The other six cases located in Nanjing, Kraków, Wągrowiec, Swarzędz, Parczew, and Mosina all reflect the result of built-up areas encroaching water and vegetation areas. Full article

(This article belongs to the Section Sustainability in Geographic Science)

30 pages, 3473 KB

Open AccessArticle

The Impact of Ecological Public Art on Public Pro-Environmental Behavior: Evidence from a Serial Multiple Mediation Model

by Suhui Zhang, Ran Tan, Yitong Shen and Dan Wu

Sustainability 2025, 17(22), 10125; https://doi.org/10.3390/su172210125 (registering DOI) - 12 Nov 2025

This study examines the mechanisms through which ecological public art influences pro-environmental behavior, addressing the urgent challenges of the global ecological crisis and sustainable urban development. Using the 5th Shanghai Urban Space Art Season (SUSAS) as a case study, a serial multiple mediation [...] Read more.

This study examines the mechanisms through which ecological public art influences pro-environmental behavior, addressing the urgent challenges of the global ecological crisis and sustainable urban development. Using the 5th Shanghai Urban Space Art Season (SUSAS) as a case study, a serial multiple mediation model was established, with ecological public art perception as the independent variable, environmental psychological ownership and ecological awareness as mediators, and pro-environmental behavior as the dependent variable. Based on 326 valid responses, structural equation modeling (SEM), which integrates confirmatory factor analysis (CFA) and path analysis, demonstrates that ecological public art perception significantly enhances pro-environmental behavior. Environmental psychological ownership and ecological awareness function not only as independent mediators but also jointly constitute a serial mediation pathway. The findings reveal a multidimensional process whereby ecological public art enhances pro-environmental behavior through “perceptual activation–emotional identification–cognitive enhancement–behavioral transformation”. Building on these insights, the study proposes intervention strategies focusing on multi-sensory integration, emotional narrative, digital technology application, and community-based practices to reinforce the role of ecological public art in urban environmental governance and sustainable development. Overall, this research advances the theoretical understanding of the social functions of public art and offers a valuable perspective for fostering ecological awareness and action. Full article

(This article belongs to the Special Issue Co-Creating Urban Public Space: Innovations in Public Space Planning Through Sustainable Ecological Planning)

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19 pages, 721 KB

Open AccessArticle

Conceptual Framework for a Machine Learning-Based Algorithmic Model for Early-Stage Business Idea Evaluation

by Karime Chahuán-Jiménez, Dominique Garrido-Araya and Carlos Escobedo Román

Sustainability 2025, 17(22), 10124; https://doi.org/10.3390/su172210124 (registering DOI) - 12 Nov 2025

This research proposes an algorithmic machine learning framework aimed at the early evaluation of business ideas. The framework integrates fifteen critical variables organized into five dimensions—innovation, sustainability, the entrepreneurial team, scalability, and initial finances—identified from a systematic review of the literature. Unlike traditional [...] Read more.

This research proposes an algorithmic machine learning framework aimed at the early evaluation of business ideas. The framework integrates fifteen critical variables organized into five dimensions—innovation, sustainability, the entrepreneurial team, scalability, and initial finances—identified from a systematic review of the literature. Unlike traditional approaches that focus on financial metrics or one-dimensional indicators, this model provides a comprehensive, multidimensional view of entrepreneurial viability in uncertain contexts. Methodologically, the study presents a structured pipeline that incorporates Random Forest, Gradient Boosting, and XGBoost ensemble algorithms, as well as SMOTE data balancing techniques. These techniques address common problems, such as class imbalance and generalization limitations. Theoretically, innovation and sustainability constructs are operationalized alongside entrepreneurial and financial factors, contributing to more consistent, integrative evaluation models. In practical terms, this proposal provides incubators, accelerators, and public policy designers with a replicable and adaptable tool for the early stages of entrepreneurship. While empirical validation is planned for the future, this work lays the methodological groundwork to bridge gaps in the literature and advance more robust predictive models for entrepreneurial evaluation. Full article

47 pages, 17541 KB

Open AccessReview

A Review of PCM Trombe Walls: Advances in Structural Optimization, Material Selection, and Operational Strategies

by Zhen Wang, Jinxuan Wang, Menghui Yu, Xinyi Zhang, Qingsong Ma, Yuling Xiao, Xindong Wei and Xin Yuan

Sustainability 2025, 17(22), 10123; https://doi.org/10.3390/su172210123 (registering DOI) - 12 Nov 2025

Given that building energy consumption accounts for a significant portion of total energy consumption, passive building technologies have demonstrated tremendous potential in addressing energy crises and the greenhouse effect. As a passive building technology, the Trombe wall (TW) can utilize solar energy to [...] Read more.

Given that building energy consumption accounts for a significant portion of total energy consumption, passive building technologies have demonstrated tremendous potential in addressing energy crises and the greenhouse effect. As a passive building technology, the Trombe wall (TW) can utilize solar energy to enhance building energy efficiency. However, due to their reliance on direct solar radiation patterns and limited thermal inertia characteristics, traditional TW systems exhibit inherent efficiency limitations. By integrating phase change materials (PCMs), TW systems can achieve high thermal storage performance and temperature control flexibility within a narrow temperature gradient range. By integrating functional materials, PCM-TW systems can be made multifunctional (e.g., through thermal catalysts for air purification). This has significant engineering implications. Therefore, this paper systematically reviews the development timeline of TWs, focusing on the evolution of PCM-TW technology and its performance. Based on this, the paper particularly emphasizes the roles of three key operational parameters: structural characteristics, thermophysical material design, and operational management. Importantly, through comparative analysis of existing systems, this paper identifies the shortcomings of current PCM-TW systems and proposes future improvement directions based on the review results. Full article

22 pages, 709 KB

Open AccessArticle

Interpretable and Calibrated XGBoost Framework for Risk-Informed Probabilistic Prediction of Slope Stability

by Hani S. Alharbi

Sustainability 2025, 17(22), 10122; https://doi.org/10.3390/su172210122 (registering DOI) - 12 Nov 2025

This study develops an interpretable and calibrated XGBoost framework for probabilistic slope stability assessment using a 627-case database of circular-mode failures. Six predictors, namely, unit weight (γ), cohesion (c), friction angle (φ), slope angle (β), slope height (H), and pore-pressure ratio (rᵤ), were [...] Read more.

This study develops an interpretable and calibrated XGBoost framework for probabilistic slope stability assessment using a 627-case database of circular-mode failures. Six predictors, namely, unit weight (γ), cohesion (c), friction angle (φ), slope angle (β), slope height (H), and pore-pressure ratio (rᵤ), were used to train a gradient-boosted tree model optimized through Bayesian hyperparameter search with five-fold stratified cross-validation. Physically based monotone constraints ensured that failure probability (P_f) decreases as c and φ increase and increases with β, H, and rᵤ. The final model achieved strong performance (AUC = 0.88, Accuracy = 0.80, MCC = 0.61) and reliable calibration, confirmed by a Brier score of 0.14 and ECE/MCE of 0.10/0.19. A 1000-iteration bootstrap quantified both epistemic and aleatoric uncertainties, providing 95% confidence bands for P_f-feature curves. SHAP analysis validated physically consistent influence rankings (φ > H ≈ c > β > γ > rᵤ). Predicted probabilities were classified into Low (P_f < 0.01), Medium (0.01 ≤ P_f ≤ 0.10), and High (P_f > 0.10) risk levels according to geotechnical reliability practices. The proposed framework integrates calibration, uncertainty quantification, and interpretability into a comprehensive, auditable workflow, supporting transparent and risk-informed slope management for infrastructure, mining, and renewable energy projects. Full article

21 pages, 2379 KB

Open AccessArticle

Aligning Parental and Student Educational Expectations: Implications for Sustainable Development of Education and Social and Emotional Skills

by Zihan Wang, Haoran Cui, Kejun Zhang, Yihe Ji, Zhen Gao, Jingcheng Tian and Cixian Lv

Sustainability 2025, 17(22), 10121; https://doi.org/10.3390/su172210121 (registering DOI) - 12 Nov 2025

Parent–child discrepancies on educational expectations have a significant impact on the holistic development of children, which is crucial for building sustainable educational ecosystems. Based on 7080 samples from the 2019 OECD Survey on Social and Emotional Skills (SSES) conducted in a Chinese city, [...] Read more.

Parent–child discrepancies on educational expectations have a significant impact on the holistic development of children, which is crucial for building sustainable educational ecosystems. Based on 7080 samples from the 2019 OECD Survey on Social and Emotional Skills (SSES) conducted in a Chinese city, this study uses the ordinary least squares model and propensity score matching to estimate the causal effect of parent–child discrepancies on educational expectations on children’s social and emotional skills—core competencies for Education for Sustainable Development (ESD)—and further employs the bootstrap method to test its mechanism. The results show that parent–child discrepancies on educational expectations have a significant negative impact on children’s social and emotional skills, with stronger effects observed among boys and 15-year-olds. The parent–child relationship and test anxiety play a chain mediating role in this relationship. The results suggest that to advance the goals of sustainable education, parents should set reasonable educational expectations and pay attention to nurturing their children’s social and emotional skills to foster holistic development within supportive family microsystems. Full article

(This article belongs to the Special Issue Sustainable Development Education for the 21st Century: Teaching Method and Education System)

22 pages, 2047 KB

Open AccessArticle

Tomato Growth Monitoring and Phenological Analysis Using Deep Learning-Based Instance Segmentation and 3D Point Cloud Reconstruction

by Warut Timprae, Tatsuki Sagawa, Stefan Baar, Satoshi Kondo, Yoshifumi Okada, Kazuhiko Sato, Poltak Sandro Rumahorbo, Yan Lyu, Kyuki Shibuya, Yoshiki Gama, Yoshiki Hatanaka and Shinya Watanabe

Sustainability 2025, 17(22), 10120; https://doi.org/10.3390/su172210120 (registering DOI) - 12 Nov 2025

Accurate and nondestructive monitoring of tomato growth is essential for large-scale greenhouse production; however, it remains challenging for small-fruited cultivars such as cherry tomatoes. Traditional 2D image analysis often fails to capture precise morphological traits, limiting its usefulness in growth modeling and yield [...] Read more.

Accurate and nondestructive monitoring of tomato growth is essential for large-scale greenhouse production; however, it remains challenging for small-fruited cultivars such as cherry tomatoes. Traditional 2D image analysis often fails to capture precise morphological traits, limiting its usefulness in growth modeling and yield estimation. This study proposes an automated phenotyping framework that integrates deep learning-based instance segmentation with high-resolution 3D point cloud reconstruction and ellipsoid fitting to estimate fruit size and ripeness from daily video recordings. These techniques enable accurate camera pose estimation and dense geometric reconstruction (via SfM and MVS), while Nerfacto enhances surface continuity and photorealistic fidelity, resulting in highly precise and visually consistent 3D representations. The reconstructed models are followed by CIELAB color analysis and logistic curve fitting to characterize the growth dynamics. When applied to real greenhouse conditions, the method achieved an average size estimation error of 8.01% compared to manual caliper measurements. During summer, the maximum growth rate (g_max) of size and ripeness were 24.14%, and 95.24% higher than in winter, respectively. Seasonal analysis revealed that winter-grown tomatoes matured approximately 10 days later than summer-grown fruits, highlighting environmental influences on phenological development. By enabling precise, noninvasive tracking of size and ripeness progression, this approach is a novel tool for smart and sustainable agriculture. Full article

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

28 pages, 2202 KB

Open AccessArticle

Spatiotemporal Patterns and Influencing Factors of the “Three Modernizations” Integrated Development in China’s Oil and Gas Industry

by Yi Wang and Shuo Fan

Sustainability 2025, 17(22), 10119; https://doi.org/10.3390/su172210119 (registering DOI) - 12 Nov 2025

Against the backdrop of China’s “carbon peaking” and “carbon neutrality” goals, as well as the advancement of new industrialization, the oil and gas industry is undergoing a critical transformation from resource-dependent growth toward innovation-driven, low-carbon, and high-quality development. The integrated advancement of high-end, [...] Read more.

Against the backdrop of China’s “carbon peaking” and “carbon neutrality” goals, as well as the advancement of new industrialization, the oil and gas industry is undergoing a critical transformation from resource-dependent growth toward innovation-driven, low-carbon, and high-quality development. The integrated advancement of high-end, intelligent, and green transformation—collectively referred to as the “Three Modernizations”—has become a vital pathway for promoting industrial upgrading and sustainable growth. Based on panel data from 30 Chinese provinces from 2009 to 2023, this study constructs a comprehensive evaluation index system covering 19 secondary indicators across three dimensions: high-end, intelligent, and green development. Using the entropy-weighted TOPSIS method, kernel density estimation, Dagum Gini coefficient decomposition, and σ–β convergence models, the study examines the spatiotemporal evolution, regional disparities, and convergence characteristics of HIG integration, and further explores its driving mechanisms through a two-way fixed effects model and mediation effect analysis. The results show that (1) the overall HIG integration index rose from 0.34 in 2009 to 0.46 in 2023, forming a spatial pattern of “high in the east, low in the west, stable in the center, and fluctuating in the northeast”; (2) regional disparities narrowed significantly, with the Gini coefficient declining from 0.093 to 0.058 and σ decreasing from 7.114 to 6.350; and (3) oil and gas resource endowment, policy support, technological innovation, and carbon emission constraints all positively promote integration, with regression coefficients of 0.152, 0.349, 0.263, and 0.118, respectively. Heterogeneity analysis reveals an increasing integration level from upstream to downstream, with eastern regions leading in innovation-driven development. Based on these findings, the study recommends strengthening policy and institutional support, accelerating technological innovation, improving intelligent infrastructure, deepening green and low-carbon transformation, promoting regional coordination, and establishing a long-term monitoring mechanism to advance the integrated high-quality development of China’s oil and gas industry. Overall, this study deepens the understanding of the internal logic and spatial dynamics of the “Three Modernizations” integration in China’s oil and gas industry, providing empirical evidence and policy insights for accelerating the construction of a low-carbon, secure, and efficient modern energy system. Full article

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18 pages, 661 KB

Open AccessArticle

An Analysis of Farmers’ Propensity to Use Reclaimed Wastewater in Agriculture

by Antonella Tassinari and Adele Coppola

Sustainability 2025, 17(22), 10118; https://doi.org/10.3390/su172210118 (registering DOI) - 12 Nov 2025

In the Mediterranean Basin, increasing water scarcity, exacerbated by climate change, necessitates the use of alternative water resources in agriculture. This study analyses farmers’ propensity to use reclaimed wastewater for irrigation in Basilicata, a region in southern Italy. Through a survey of 167 [...] Read more.

In the Mediterranean Basin, increasing water scarcity, exacerbated by climate change, necessitates the use of alternative water resources in agriculture. This study analyses farmers’ propensity to use reclaimed wastewater for irrigation in Basilicata, a region in southern Italy. Through a survey of 167 farms and the application of a logit model, this work quantifies the role of the main factors influencing farmers’ propensity to use this new resource. The results identify several key drivers and barriers. A higher level of education and participation in Producers’ Organisations make wastewater use approximately ten times (odds ratio equal to 9.84) and five times (odds ratio equal 4.96) more likely, respectively. Furthermore, an adequate knowledge of the relevant legislation nearly quadruples (odds ratio equal to 3.57) the likelihood of adoption. In contrast, concerns related to worker health and groundwater pollution are strong deterrents, reducing the odds of adoption by 90% and 87%, respectively. Concerns about product quality also significantly decrease the propensity to adopt (odds ratio equal to 0.25). The findings underscore the need for integrated interventions that enhance farmers’ awareness and knowledge of the characteristics and impacts of new practices, thereby fostering the innovative and sustainable management of water resources. Full article

(This article belongs to the Section Resources and Sustainable Utilization)

36 pages, 1326 KB

Open AccessReview

Artificial Intelligence for Enhancing Indoor Air Quality in Educational Environments: A Review and Future Perspectives

by Alexandros Romaios, Petros Sfikas, Athanasios Giannadakis, Thrassos Panidis, John A. Paravantis, Eugene D. Skouras and Giouli Mihalakakou

Sustainability 2025, 17(22), 10117; https://doi.org/10.3390/su172210117 (registering DOI) - 12 Nov 2025

Indoor Air Quality (IAQ) in educational environments is a critical determinant of students’ health, well-being, and learning performance, with inadequate ventilation and pollutant accumulation consistently associated with respiratory symptoms, fatigue, and impaired cognitive outcomes. Conventional monitoring approaches—based on periodic inspections or subjective perception—provide [...] Read more.

Indoor Air Quality (IAQ) in educational environments is a critical determinant of students’ health, well-being, and learning performance, with inadequate ventilation and pollutant accumulation consistently associated with respiratory symptoms, fatigue, and impaired cognitive outcomes. Conventional monitoring approaches—based on periodic inspections or subjective perception—provide only fragmented insights and often underestimate exposure risks. Artificial intelligence (AI) offers a transformative framework to overcome these limitations through sensor calibration, anomaly detection, pollutant forecasting, and the adaptive control of ventilation systems. This review critically synthesizes the state of AI applications for IAQ management in educational environments, drawing on twenty real-world case studies from North America, Europe, Asia, and Oceania. The evidence highlights methodological innovations ranging from decision tree models integrated into large-scale sensor networks in Boston to hybrid deep learning architectures in New Zealand, and regression-based calibration techniques applied in Greece. Collectively, these studies demonstrate that AI can substantially improve predictive accuracy, reduce pollutant exposure, and enable proactive, data-driven ventilation management. At the same time, cross-case comparisons reveal systemic challenges—including sensor reliability and calibration drift, high installation and maintenance costs, limited interoperability with legacy building management systems, and enduring concerns over privacy and trust. Addressing these barriers will be essential for moving beyond localized pilots. The review concludes that AI holds transformative potential to shift school IAQ management from reactive practices toward continuous, adaptive, and health-oriented strategies. Realizing this potential will require transparent, equitable, and cost-effective deployment, positioning AI not only as a technological solution but also as a public health and educational priority. Full article

25 pages, 5472 KB

Open AccessArticle

Multi-Scenario Emission Reduction Potential Assessment and Cost–Benefit Analysis of Motor Vehicles at the Provincial Level in China Based on the LEAP Model: Implication for Sustainable Transportation Transitions

by Jiarong Li, Yijing Wang and Rong Wang

Sustainability 2025, 17(22), 10116; https://doi.org/10.3390/su172210116 (registering DOI) - 12 Nov 2025

With the continuous expansion in China’s vehicle fleet, emissions of CO₂ and air pollutants from the on-road transportation sector are widely projected to be rising, posing a challenge to realizing China’s targets of carbon peaking in 2030 and carbon neutrality in 2060, [...] Read more.

With the continuous expansion in China’s vehicle fleet, emissions of CO₂ and air pollutants from the on-road transportation sector are widely projected to be rising, posing a challenge to realizing China’s targets of carbon peaking in 2030 and carbon neutrality in 2060, as well as the national target for air quality improvement. Therefore, vehicle electrification in the on-road transportation sector is urgently needed to reduce emissions of CO₂ and air pollutants, as it serves as a key pathway to align transportation development with sustainability goals. While vehicle electrification is supposed to be the primary solution, there is a research gap in quantifying the provincial, environmental, and economic impacts of implementing such a policy in China. To bridge this gap, we projected the provincial-level ownership of different types of vehicles based on historical trends, assessed the emission reduction potential for CO₂ and air pollutants using the LEAP model from 2021 to 2060, and predicted the provincial marginal abatement costs at different mitigation stages under various scenarios with different strategies of vehicle electrification and development patterns of electricity structure. Our results show that the implementation of vehicle electrification lowers the national carbon peak by 0.2–0.6 Gt yr⁻¹ and advances its achievement by 1–3 years ahead of 2030. The marginal abatement cost ranges from $532 to $3466 per ton CO₂ (tCO₂⁻¹) in 2025 and from -$180 to -$113 tCO₂⁻¹ in 2060 across scenarios. The provincial marginal abatement cost curves further indicate that China’s vehicle electrification should be prioritized in cost-effective regions (e.g., Shanghai and Guangdong), while concurrently advancing nationwide grid decarbonization to guarantee the supply of low-carbon electricity across the country. This optimized pathway ensures that transportation decarbonization aligns with both environmental and economic requirements, providing actionable support for China’s sustainable development strategy. Full article

(This article belongs to the Section Sustainable Transportation)

22 pages, 1158 KB

Open AccessArticle

Location Criteria for E-Commerce Logistics Facilities: A Scale-Sensitive Analysis

by Büşra Güven Güney and Mehmet Ali Yüzer

Sustainability 2025, 17(22), 10115; https://doi.org/10.3390/su172210115 (registering DOI) - 12 Nov 2025

The rapid proliferation of e-commerce has reshaped the spatial logic and facility typologies of urban logistics. While the literature on logistics facility location selection is extensive, there is limited understanding of how the relative importance of location criteria varies across facility types shaped [...] Read more.

The rapid proliferation of e-commerce has reshaped the spatial logic and facility typologies of urban logistics. While the literature on logistics facility location selection is extensive, there is limited understanding of how the relative importance of location criteria varies across facility types shaped by e-commerce. This study addresses this gap by analyzing the location criteria of logistics facilities of different sizes using a multi-criteria decision-making (MCDM) approach. Twenty-five criteria, identified through a literature review and feedback from seven experts in the Istanbul e-commerce logistics sector, were analyzed using the Fuzzy Simple Additive Weighting (SAW) method. The relative weights of criteria were calculated for three facility scales, macro-, meso-, and micro-scales, to reveal how location priorities vary across scales. Proximity to main arteries ranks first across all scales (macro: 0.317, meso: 0.431, micro: 0.409). Land rental values are highly prioritized at both the macro- and meso-scale, while population density ranks prominently at the macro- and micro-scale. At the meso-scale, shopping mall proximity gains notable weight, whereas intermediate arteries stand out as a key factor at the micro scale. These findings advance the understanding of scale-sensitive dynamics in urban logistics and provide a framework for more adaptable and sustainable logistics planning. Full article

39 pages, 37467 KB

Open AccessArticle

Symbiosis and Synergy of Smart Urban Places: The Case of Zwycięstwa Street in Gliwice, Poland

by Marek Gachowski, Łukasz Walusiak, Marcin Budziński, Tomasz Szulc and Lidia Wanik

Sustainability 2025, 17(22), 10114; https://doi.org/10.3390/su172210114 (registering DOI) - 12 Nov 2025

Symbiosis and synergy among urban uses are key determinants of spatial quality, liveability, and resilience. While symbiosis denotes the coexistence of users and functions within specific places, synergy refers to the collective benefits emerging from their interaction. These dynamics are especially relevant in [...] Read more.

Symbiosis and synergy among urban uses are key determinants of spatial quality, liveability, and resilience. While symbiosis denotes the coexistence of users and functions within specific places, synergy refers to the collective benefits emerging from their interaction. These dynamics are especially relevant in city centres and main streets, which serve as structural and social backbones of urban life. This article applies the SyM_SyN Method to Zwycięstwa Street in Gliwice, Poland, to assess the intensity and distribution of symbiotic and synergistic relations. The analysis identified significant spatial deficiencies that weaken the coherence and attractiveness of the street. The results demonstrate how a systematic, data-driven evaluation can expose hidden weaknesses in urban structures. Importantly, from the perspective of the smart city paradigm, liveability and responsiveness of urban spaces cannot be reduced to technology-driven systems of sensors and devices. They must also be understood in terms of human-scale interactions and the ability of urban form to support them. Beyond its methodological contribution, the study emphasises the practical implications for urban renewal: reinforcing positive interactions between adjacent uses enhances street vitality, improves social inclusiveness, and supports more sustainable development strategies. The SyM_SyN Method thus provides both an analytical framework and a decision-support tool for designing user-oriented, high-quality urban spaces within the broader smart and sustainable city paradigm. Full article

(This article belongs to the Special Issue Sustainable Urban Planning and Regional Development)

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