Sustainability

29 pages, 737 KiB

Open AccessArticle

The Cost-Effectiveness of Renewable Energy Sources in the European Union’s Ecological Economic Framework

by Rafał Wyszomierski, Piotr Bórawski, Aneta Bełdycka-Bórawska, Agnieszka Brelik, Marcin Wysokiński and Magdalena Wiluk

Sustainability 2025, 17(10), 4715; https://doi.org/10.3390/su17104715 (registering DOI) - 20 May 2025

Abstract

Evaluating the competitiveness of electricity is the most important issue. The main aim of this study was to determine the cost-effectiveness of renewable energy production in the European Union (EU) using the levelized cost competitiveness of renewable energy sources. The weighted average cost [...] Read more.

Evaluating the competitiveness of electricity is the most important issue. The main aim of this study was to determine the cost-effectiveness of renewable energy production in the European Union (EU) using the levelized cost competitiveness of renewable energy sources. The weighted average cost of capital (WACC) for onshore wind was calculated for European (EU) countries. The levelized cost of electricity (LCOE) approach was used to evaluate the energy costs of renewable energy sources. Energy production costs were compared across different technologies. The capital expenditures associated with solar PV are expected to decrease from USD 810/kW in 2021 to USD 360/kW in 2050. The power factor will remain stable at 14% during the analyzed period. Fuel, CO₂, and operation and maintenance (O&M) costs will be maintained at USD 10/MWh at all three time points of the analysis (2021, 2030, and 2050), whereas the LCOE will decrease from USD 50/MWh in 2021 to USD 25/MWh in 2050. The capital expenditures associated with onshore wind energy will decrease from USD 1590/kW in 2021 to USD 1410/kW in 2050. The power factor will increase from 29% to 30%, and fuel, CO₂, and O&M costs will reach USD 15/MWh in all three years. The LCOE will decrease from USD 55/MWh in 2021 to USD 45/MWh in 2050. In offshore wind projects, capital expenditures are expected to decrease considerably from USD 3040/kW in 2021 to USD 1320/kW in 2050. Full article

22 pages, 3968 KiB

Open AccessArticle

Development of an MPE-BMA Ensemble Model for Runoff Prediction Under Future Climate Change Scenarios: A Case Study of the Xiangxi River Basin

by Wenjie Li, Huabai Liu, Pangpang Gao, Aili Yang, Yifan Fei, Yizhuo Wen, Yueyu Su and Xiaoqi Yuan

Sustainability 2025, 17(10), 4714; https://doi.org/10.3390/su17104714 - 20 May 2025

Abstract

Accurate runoff simulation and prediction are crucial for water resources management, especially under the impact of climate change. In this study, a multi-physics ensemble Bayesian model averaging (MPE-BMA) model is developed to improve runoff prediction accuracy by integrating a soil and water assessment [...] Read more.

Accurate runoff simulation and prediction are crucial for water resources management, especially under the impact of climate change. In this study, a multi-physics ensemble Bayesian model averaging (MPE-BMA) model is developed to improve runoff prediction accuracy by integrating a soil and water assessment tool (SWAT), hydrologiska byråns vattenbalansavdelning (HBV) model, and Bayesian model averaging (BMA) into a general framework. The MPE-BMA model integrates the strengths of the SWAT and HBV models. This approach enhances the robustness of simulation outputs and reduces uncertainties from single-model methods. MPE-BMA is subsequently employed to simulate and predict runoff for the upper reaches of Xiangxi River Basin (XXRB) in China, where four general circulation models (GCMs) and three shared socioeconomic pathways (SSP126, SSP245, and SSP585) are considered. Multiple statistical metrics (R², NSE, and RMSE) prove that the MPE-BMA model outperforms the single models of SWAT and HBV. Results reveal that higher-emission scenarios generally lead to significant decreases in runoff, particularly by the 2080s. Specifically, under SSP585, runoff is projected to decrease by approximately 4.61–12.68% by the 2040s and 5.96–11.28% by the 2080s compared to the historical period. From the perspective of monthly and seasonal runoff changes, the peak runoff is projected to shift from June to May by the 2080s. Additionally, under SSP585, spring and summer runoffs tend to significantly increase, while winter runoff decreases sharply, leading to wetter summers and drier winters. These findings underscore the importance of enhancing water use efficiency, upgrading hydropower stations, and implementing watershed management practices to ensure sustainable water resources management in the XXRB amidst climate change. Full article

35 pages, 3071 KiB

Open AccessArticle

Ripple Effect or Spatial Interaction? A Spatial Analysis of Green Finance and Carbon Emissions in the Yellow River Basin

by Jiayu Ru, Lu Gan and Gulinaer Yusufu

Sustainability 2025, 17(10), 4713; https://doi.org/10.3390/su17104713 (registering DOI) - 20 May 2025

Abstract

Grounded in the theory of new economic geography, this research develops a comprehensive theoretical framework to examine the spatial interaction mechanisms between the Green Finance Index and carbon emissions. Employing a range of econometric techniques—including three-dimensional kernel density estimation, spatial quantile regression, bivariate [...] Read more.

Grounded in the theory of new economic geography, this research develops a comprehensive theoretical framework to examine the spatial interaction mechanisms between the Green Finance Index and carbon emissions. Employing a range of econometric techniques—including three-dimensional kernel density estimation, spatial quantile regression, bivariate spatial autocorrelation analysis, and the spatial linkage equation model—the dynamic evolution, spatial pattern shifts, and mutual influences of green finance and carbon emissions in the middle and lower reaches of the Yellow River from 2003 to 2022 are systematically assessed. The findings indicate that (1) both carbon emissions and the Green Finance Index have experienced a trajectory of continuous growth, phased decline, and structural optimization, accompanied by a gradual shift in the regional center of gravity from coastal economic zones towards resource-intensive and traditional industry-concentrated areas; (2) significant spatial clustering is evident for both green finance and carbon emissions, demonstrating a strong spatial correlation and regional synergy effects; (3) a persistent negative spatial correlation exists between green finance and carbon emissions; and (4) green finance exerts a stable negative spatial spillover effect on carbon emissions, suggesting that the influence of green finance extends beyond localities to adjacent regions through spatial externalities, manifesting pronounced spatial transmission and linkage characteristics. By unveiling the bidirectional spatial association between green finance and carbon emissions, this study highlights the pivotal role of green finance in driving regional low-carbon transitions. The results provide theoretical insights for optimizing green finance policies within the Yellow River Basin and offer valuable international references for similar regional low-carbon development initiatives. Full article

(This article belongs to the Topic Sustainable and Green Finance)

27 pages, 830 KiB

Open AccessArticle

Measuring CSR with Accounting Information Systems Through a Managerial Model for Sustainable Economic Development

by Loredana Cristina Tănase, Valentin Radu, Alina Iuliana Tăbîrcă, Violeta State, Florin Radu, Laura Marcu and Cristina Maria Voinea

Sustainability 2025, 17(10), 4712; https://doi.org/10.3390/su17104712 - 20 May 2025

Abstract

In the European Union’s Corporate Sustainability Reporting Directive (CSRD) context, organizations must increasingly integrate non-financial indicators into their reporting structures. The role of accounting information in establishing a comprehensive model for measuring corporate social responsibility (CSR) is critical due to its inherent characteristics. [...] Read more.

In the European Union’s Corporate Sustainability Reporting Directive (CSRD) context, organizations must increasingly integrate non-financial indicators into their reporting structures. The role of accounting information in establishing a comprehensive model for measuring corporate social responsibility (CSR) is critical due to its inherent characteristics. This study proposes a structured model for measuring CSR performance using accounting information systems (AIS) as an analytical and operational support tool. The research investigates the extent to which financial analysts and auditors use AIS to evaluate specific CSR indicators related to employee satisfaction, environmental impact, and customer relations and how these contribute to a global CSR index. The study is based on a quantitative survey conducted among accounting professionals in Romania using a structured questionnaire, analyzed through correlation-based models. The findings reveal a statistically significant association between AIS usage and the capacity to quantify CSR performance, with clear distinctions based on professional roles and areas of expertise. This article contributes to the literature by demonstrating how AIS can operationalize sustainability reporting frameworks and support the transition toward evidence-based CSR assessments. The proposed model offers a practical tool for organizations to improve transparency, stakeholder engagement, and strategic alignment with sustainability objectives. Full article

(This article belongs to the Special Issue Advances in Economic Development and Business Management)

26 pages, 1876 KiB

Open AccessReview

Machine-Learning-Based Frameworks for Reliable and Sustainable Crop Forecasting

by Khushwant Singh, Mohit Yadav, Dheerdhwaj Barak, Shivani Bansal and Fernando Moreira

Sustainability 2025, 17(10), 4711; https://doi.org/10.3390/su17104711 - 20 May 2025

Abstract

Fueled by scientific innovations and data-driven approaches, accurate agriculture has arisen as a transformative sector in contemporary agriculture. The present investigation provides a summary of modern improvements in machine-learning (ML) strategies utilized for crop prediction, accompanied by a performance exploration of contemporary models. [...] Read more.

Fueled by scientific innovations and data-driven approaches, accurate agriculture has arisen as a transformative sector in contemporary agriculture. The present investigation provides a summary of modern improvements in machine-learning (ML) strategies utilized for crop prediction, accompanied by a performance exploration of contemporary models. It examines the amalgamation of sophisticated technologies, cooperative objectives, and data-driven methodologies designed to address the obstacles in conventional agriculture. The study examines the possibilities and intricacies of precision agriculture by analyzing various models of deep learning, machine learning, ensemble learning, and reinforcement learning. Highlighting the significance of worldwide collaboration and data-sharing activities elucidates the evolving landscape of the precision farming industry and indicates prospective advancements in the sector. Full article

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26 pages, 1884 KiB

Open AccessReview

A Review of Various Advanced Oxidation Techniques for Pesticide Degradation for Practical Application in Aqueous Environments

by Mehary Dagnew, Qin Xue, Jian Zhang, Zizeng Wang, Anran Zhou, Min Li and Chun Zhao

Sustainability 2025, 17(10), 4710; https://doi.org/10.3390/su17104710 - 20 May 2025

Abstract

Pesticides are chemicals used in agriculture, industry, and households to control pests and enhance crop yields but have emerged as pollutants in soil and water due to their presence in domestic and agricultural wastewater effluents. The World Health Organization (WHO) has identified the [...] Read more.

Pesticides are chemicals used in agriculture, industry, and households to control pests and enhance crop yields but have emerged as pollutants in soil and water due to their presence in domestic and agricultural wastewater effluents. The World Health Organization (WHO) has identified the development of pesticide resistance as a significant threat to global public health. Consequently, removing pesticides in aqueous environments has gained considerable attention. Numerous methodologies, including biological, physical, and chemical methods, have been employed for their treatment. Among these methods, advanced oxidation processes (AOPs) have garnered particular interest due to their fast reaction rates and strong oxidizing abilities. This review focuses on various AOPs such as Fenton and Fenton-like oxidation, ozonation, the UV/H₂O₂process, electrochemical oxidation, photocatalytic oxidation, and the UV/O₃ process. The review analyzes and summarizes the current applications of these AOPs for treating pesticides in aqueous environments. It also compares various AOPs treatment methods and discusses the challenges, drawbacks, advantages, and strategies for addressing these issues, and provides insights into the future prospects. Finally, it propose potential strategies and areas of improvement for future research to enhance the efficiency and sustainability of AOPs in practical application. Full article

(This article belongs to the Section Sustainable Water Management)

19 pages, 17788 KiB

Open AccessArticle

The Spatio-Temporal Evolution and Influence Mechanisms of Intercity Cooperation Networks from the Perspective of Sustainable Regional Development: A Case Study of the Pearl River–Xijiang Economic Belt, China

by Ruochen Shi, Changsheng Sun, Chunying Zhang and Zhenwei Peng

Sustainability 2025, 17(10), 4709; https://doi.org/10.3390/su17104709 - 20 May 2025

Abstract

Intercity cooperation networks are critical for addressing regional imbalances and advancing sustainable regional development, yet existing studies typically focus on specific functional domains, rather than the overall intercity cooperation network. To bridge this gap, this study examines the intercity cooperation network in the [...] Read more.

Intercity cooperation networks are critical for addressing regional imbalances and advancing sustainable regional development, yet existing studies typically focus on specific functional domains, rather than the overall intercity cooperation network. To bridge this gap, this study examines the intercity cooperation network in the Pearl River–Xijiang Economic Belt (21 cities, 2014–2023), analyzing its spatio-temporal evolution and influence mechanisms through Social Network Analysis (SNA) and partial least squares structural equation modeling (PLS-SEM). The results reveal the following: (1) the network has undergone three policy-driven development stages: initial–accelerated–steady; (2) a spatial pattern of “east—dominant, west—weak” has emerged, shaped by the radiating influence of core cities; and (3) institutional proximity and cooperation investment are key drivers of network formation, while geographical and organizational proximity exhibit negative impacts. These findings underscore the need for related regional development strategies to foster a more vital and open cooperation network. Overall, this study deepens the understanding of intercity cooperation by revealing its macro-level patterns and influence mechanisms, and provides practical implications for policymakers committed to promoting sustainable regional development. Full article

(This article belongs to the Special Issue Innovation and Sustainability in Urban Planning and Governance)

17 pages, 580 KiB

Open AccessArticle

Driving Mechanism of Greening Corporate Environmental Behaviour Under the “Dual-Carbon” Goal: A Study Based on Grounded Theory Study

by Huan Wu and Jianguo Du

Sustainability 2025, 17(10), 4708; https://doi.org/10.3390/su17104708 - 20 May 2025

Abstract

In order to cope with global warming, the Chinese government is actively promoting the “dual-carbon” target policy, a green and efficient system which will become the future development direction of China’s energy system. As the main body of the carbon emissions of enterprises [...] Read more.

In order to cope with global warming, the Chinese government is actively promoting the “dual-carbon” target policy, a green and efficient system which will become the future development direction of China’s energy system. As the main body of the carbon emissions of enterprises is bound to be the focus of governance, we must accelerate green transformation. In this paper, we use procedural rooting theory, collect data from field interviews, and use open coding, principal axis coding, selective coding, and a theoretical saturation test to explore antecedent motivation mechanisms and the consequent pathway of the green change in corporate environmental behaviours under the “dual-carbon” goal. We aim to clarify the evolution of “internal and external factors—enterprise green change willingness—green change behavior” to construct a theoretical model. The results show that the influence of and interaction effects among the micro-level, macro-environmental level, and meso-industry level dimensions of enterprise will drive companies to make green changes and adopt green change behaviours in the forms of strategic change and innovation optimisation. This study enriches the theoretical framework of green change in corporate environmental behaviour under the rigid constraint of the “dual-carbon” goal and provides countermeasure suggestions for the successful achievement of the “dual-carbon” goal at the corporate body level. Full article

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16 pages, 731 KiB

Open AccessArticle

Multi-Objective Mixed-Integer Linear Programming for Dynamic Fleet Scheduling, Multi-Modal Transport Optimization, and Risk-Aware Logistics

by Nawaf Mohamed Alshabibi, Al-Hussein Matar and Mohamed H. Abdelati

Sustainability 2025, 17(10), 4707; https://doi.org/10.3390/su17104707 - 20 May 2025

Abstract

Transportation planning is a complex process that aims to achieve the maximum level of effectiveness in terms of costs, usage of transport resources, reliability of deliveries, and minimizing the negative impact on the environment. Most traditional models focus on cost minimization at the [...] Read more.

Transportation planning is a complex process that aims to achieve the maximum level of effectiveness in terms of costs, usage of transport resources, reliability of deliveries, and minimizing the negative impact on the environment. Most traditional models focus on cost minimization at the expense of risk, road dynamics, and emissions constraints. In contrast, the current paper presents a mixed-integer linear programming (MILP) model for scheduling fleets, selecting transportation modes in multiple modes of transportation, and meeting emissions regulation requirements according to dynamic transportation requirements. Risk-aware routing and taking the factor of congestion and CO₂ emission limits proposed by the government into consideration, this model can offer a more efficient and flexible optimization strategy. From the case study, we observe the significant result that the proposed model achieves, a 23% reduction in transport costs, a 25% improvement in fleet use, a 33.3% decrease in the delivery delay, and a 24.6% decrease in CO₂ emissions. The model dynamically delivers shipments utilizing both road and rail transportation and improves mode choice by minimizing idle vehicle time. This is confirmed through sensitivity analysis which addresses factors such as traffic congestion, changing fuel prices, and changing environmental standards. Full article

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34 pages, 3280 KiB

Open AccessArticle

A Systemic Approach to Sustainable Technological Extension: A Dynamic Model for Oil Palm Cultivation in Colombia

by Julián F. Becerra-Encinales, Jair D. Rodríguez-Ortega, Alexandre P. Cooman, Luis H. Reyes and Juan C. Cruz

Sustainability 2025, 17(10), 4706; https://doi.org/10.3390/su17104706 - 20 May 2025

Abstract

This study develops a systemic conceptual model to analyze the dynamics of technological extension and its impact on the sustainability of Colombia’s oil palm production sector. Using a system dynamics-based methodological approach, multiple sources of information were integrated, including the Sustainability Index (SI), [...] Read more.

This study develops a systemic conceptual model to analyze the dynamics of technological extension and its impact on the sustainability of Colombia’s oil palm production sector. Using a system dynamics-based methodological approach, multiple sources of information were integrated, including the Sustainability Index (SI), socio-economic characterizations of producers, and ethnographic insights, with the aim of identifying key actors and their interactions within the system, modeling causal relationships and feedback loops. In contrast with the traditional linear model of technology transfer, this model reveals non-linear dynamic structures, highlighting ten systemic loops (six reinforcing and four balancing) that explain how technological adoption, legal and regulatory compliance, and the SI risk level interact through dynamic feedback mechanisms. Beyond providing a structural representation of the system, the model offers concrete guidance for policy formulation and intervention strategies tailored to different producer typologies. Theoretically, this research broadens the understanding of diffusion, extension, and technology adoption processes in complex agricultural systems in developing countries. Practically, it provides a tool for analysis and planning to strengthen the sustainability of the Colombian oil palm sector, with potential applicability to other agro-industrial contexts. Future research should advance toward dynamic simulations to evaluate intervention scenarios, emphasizing the need for progressive incentive schemes, participatory extension, and integrated regulatory frameworks that promote high levels of long-term sustainability compliance. Full article

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32 pages, 813 KiB

Open AccessArticle

Integration of Artificial Intelligence Technologies into Design-Thinking Processes in the Development of Managerial Decisions as a Factor of Enterprise Sustainable Development

by Oksana Kiseleva, Anna Firsova and Alla Vavilina

Sustainability 2025, 17(10), 4705; https://doi.org/10.3390/su17104705 - 20 May 2025

Abstract

Sustainable development is one of the most significant and meaningful trends in the world. However, the process of implementing the Agenda for Sustainable Development Goals, approved on 25 September 2015, reflects the ability to achieve no more than 20% of stated goals, which [...] Read more.

Sustainable development is one of the most significant and meaningful trends in the world. However, the process of implementing the Agenda for Sustainable Development Goals, approved on 25 September 2015, reflects the ability to achieve no more than 20% of stated goals, which requires a solution that will allow for accelerating the pace of a resilient transformation. The objective of this paper is to substantiate the role of artificial intelligence technologies in ensuring effective ESG (environmental, social, governance) transformation in the process of developing managerial decisions aimed at achieving sustainable development of the enterprise by integrating into design-thinking. The research methodology is based on scientific papers on sustainable development, digital technologies, artificial intelligence, and design thinking. Analytical data from various world rankings, as well as reviews of sustainable development practices and digitalization of companies, were employed. General scientific and special methods of cognition were used to conduct the study. As a result, the role of artificial intelligence in the processes of the sustainable transformation of modern companies was identified and justified. This is reflected in the proposed algorithms and models for the development and implementation of a sustainable development strategy. Full article

18 pages, 1072 KiB

Open AccessArticle

An Evaluation of Sustainable Development in Chinese Counties Based on SDGs

by Yufei Zhao, Chaofeng Shao and Xuesong Zhan

Sustainability 2025, 17(10), 4704; https://doi.org/10.3390/su17104704 - 20 May 2025

Abstract

With the increasingly urgent demand for the localization of the United Nations’ sustainable development goals (SDGs), the construction of an evaluation system and the practice paths of counties, as important spatial units of China’s sustainable development, urgently need to be deepened. Based on [...] Read more.

With the increasingly urgent demand for the localization of the United Nations’ sustainable development goals (SDGs), the construction of an evaluation system and the practice paths of counties, as important spatial units of China’s sustainable development, urgently need to be deepened. Based on the articulation of the SDGs and China’s national conditions, this study innovatively designed an indicator delivery framework covering the United Nations level to the county level; constructed a county-level sustainable development evaluation indicator system that includes three dimensions, including economic development, social culture, and ecological environment; adopted the entropy weight method to determine the weights of indicators; and introduced a dynamic evaluation and analysis model utilizing three analytical methods, namely coupling coordination analysis, obstacle analysis, and Dagum decomposition, to evaluate the level of sustainable development of 76 counties in the 2010–2021 period considering both time and space. The results show that (1) the national county sustainable development index (CSDI) was significantly improved, regional differences were narrowed, the central region has the best overall performance, and the western region has the fastest growth rate; (2) economic development has become the main driving force, and the economic gap between regions has gradually narrowed, but the spatial heterogeneity of the environmental and social dimensions is still prominent; (3) the eastern region has generated positive spillover effects on the central and western regions through industrial transfer and technology diffusion, while the northeastern region develops relatively slowly due to the lagging industrial transformation; and (4) the degree of coupling coordination rises as a whole, but the differences in synergistic ability between regions are obvious. This study provides a scientific basis for the formulation of differentiated sustainable development policies for counties and emphasizes the key role of regional synergy mechanisms in narrowing the development gap. Full article

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31 pages, 5880 KiB

Open AccessArticle

Low-Carbon Optimal Operation Strategy of Multi-Energy Multi-Microgrid Electricity–Hydrogen Sharing Based on Asymmetric Nash Bargaining

by Hang Wang, Qunli Wu and Huiling Guo

Sustainability 2025, 17(10), 4703; https://doi.org/10.3390/su17104703 - 20 May 2025

Abstract

The cooperative interconnection of multi-microgrid systems offers significant advantages in enhancing energy utilization efficiency and economic performance, providing innovative pathways for promoting sustainable development. To establish a fair energy trading mechanism for electricity–hydrogen sharing within multi-energy multi-microgrid (MEMG) systems, this study first analyzes [...] Read more.

The cooperative interconnection of multi-microgrid systems offers significant advantages in enhancing energy utilization efficiency and economic performance, providing innovative pathways for promoting sustainable development. To establish a fair energy trading mechanism for electricity–hydrogen sharing within multi-energy multi-microgrid (MEMG) systems, this study first analyzes the operational architecture of MEMG energy sharing and establishes a multi-energy coordinated single-microgrid model integrating electricity, heat, natural gas, and hydrogen. To achieve low-carbon operation, carbon capture systems (CCSs) and power-to-gas (P2G) units are incorporated into conventional combined heat and power (CHP) systems. Subsequently, an asymmetric Nash bargaining-based optimization framework is proposed to coordinate the MEMG network, which decomposes the problem into two subproblems: (1) minimizing the total operational cost of MEMG networks, and (2) maximizing payment benefits through fair benefit allocation. Notably, Subproblem 2 employs the energy trading volume of individual microgrids as bargaining power to ensure equitable profit distribution. The improved alternating direction multiplier method (ADMM) is adopted for distributed problem-solving. Experimental results demonstrate that the cost of each MG decreased by 5894.14, 3672.44, and 2806.64 CNY, while the total cost of the MEMG network decreased by 12,431.22 CNY. Additionally, the carbon emission reduction ratios were 2.84%, 2.77%, and 5.51% for each MG and 11.12% for the MEMG network. Full article

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26 pages, 541 KiB

Open AccessArticle

Implementing Education for Sustainable Development in Organizations of Adult and Continuing Education: Perspectives of Leaders in China, Germany, and the USA

by Ulrich Müller, Dawson Hancock, Chuang Wang, Tobias Stricker and Qiao Liu

Sustainability 2025, 17(10), 4702; https://doi.org/10.3390/su17104702 - 20 May 2025

Abstract

Societies need to develop more sustainable ways of living, working, and doing business. Education for sustainable development (ESD) plays a pivotal role in this endeavor. The aim is to provide people with the necessary knowledge, values, and skills for the needed transformation. Therefore, [...] Read more.

Societies need to develop more sustainable ways of living, working, and doing business. Education for sustainable development (ESD) plays a pivotal role in this endeavor. The aim is to provide people with the necessary knowledge, values, and skills for the needed transformation. Therefore, organizations of adult and continuing education must address issues of climate protection and sustainability in their programs and act accordingly in the way the organization is managed. This article reports on a qualitative study that involves leaders of adult education institutions in China, Germany, and the USA. This study seeks to investigate what these leaders do and how they act to implement ESD in their organizations. It specifically looks at current challenges, management strategies, beliefs, and values of the leaders. The results of this study show that leaders of adult and continuing education organizations recognize the need to address sustainability in adult education. However, they face many challenges in implementing ESD, including a lack of resources (e.g., finances and staff), structural barriers, and difficulties in reaching new target groups. Despite these challenges, many participants strive to develop their organizations in a more sustainable way, such as through curriculum design and campus management. Some leaders take a comprehensive approach, guided by the Whole Institution Approach, by integrating ESD into their institution’s vision and mission, establishing dedicated working groups, and forming new partnerships with external stakeholders. Overall, this study highlights the crucial role of leadership in advancing sustainability efforts. Full article

(This article belongs to the Section Sustainable Education and Approaches)

33 pages, 6889 KiB

Open AccessArticle

Revitalizing Inner Areas Through Thematic Cultural Routes and Multifaceted Tourism Experiences

by Annarita Sannazzaro, Stefano Del Lungo, Maria Rosaria Potenza and Fabrizio Terenzio Gizzi

Sustainability 2025, 17(10), 4701; https://doi.org/10.3390/su17104701 - 20 May 2025

Abstract

Cultural tourism can act as a driver for inner area development, bringing about a range of socio-economic benefits through economic stimulation, quality of life improvement, and cultural heritage preservation. Inner territories, set apart by geographic marginality and low population density, hold a rich [...] Read more.

Cultural tourism can act as a driver for inner area development, bringing about a range of socio-economic benefits through economic stimulation, quality of life improvement, and cultural heritage preservation. Inner territories, set apart by geographic marginality and low population density, hold a rich cultural and environmental heritage that, however, remains off the radar and left behind. Guided by the principles of endogenous local development, this article seeks to contribute to the existing body of research by proposing potential strategies for local growth rooted in cultural tourism. From this perspective, we identified the Basilicata region (Southern Italy) as a proper test area. The region is rich in archaeological, monumental and museum evidence, but is characterized, except in a few areas, by a low rate of tourist turnout. Through a replicable, comprehensive, and flexible methodology—drawing on bibliographic research, analysis of archaeological, archival, erudite and antiquarian sources, and carrying out field surveys—the different points of interest in the region have been brought together under specific cultural themes. Results include the design of three detailed routes (Via Herculia, Frederick II’s, and St Michael’s cultural routes) useful for three different types of tourism (sustainable, emotional, and accessible). Possible scenarios for valorization and fruition are also proposed, paying particular attention to digital technologies. Thus, this research aligns with Sustainable Development Goals (SDGs) 8 and 11 promoting cultural heritage valorization and preservation, shoring up economic revitalization, stepping up community engagement, and pushing forward environmentally friendly tourism practices. Research findings can attract the interest of a wide range of stakeholders such as tourism professionals, local authorities, cultural and creative industries, local communities and entrepreneurs, as well as academics and researchers. The methodological approach can be considered for the valorization and tourist enjoyment of inner areas in other countries, with particular focus on those falling within the Mediterranean region which is rich in cultural heritage, environmental value, and socio-economic potential. Full article

(This article belongs to the Section Tourism, Culture, and Heritage)

16 pages, 766 KiB

Open AccessArticle

How Do Chinese Migrant Workers Avoid Leisure-Time Physical Inactivity?

by Zhanqiang Zhu, Jiaying Fu and Suhong Zhou

Sustainability 2025, 17(10), 4700; https://doi.org/10.3390/su17104700 - 20 May 2025

Abstract

Migrant workers, vital for urban sustainable development, often exhibit leisure-time physical inactivity (LTPI). Few studies have examined LTPI and its constraints among migrant workers. This study aimed to identify the determinants of LTPI and its constraints among migrant workers. Guangzhou was used as [...] Read more.

Migrant workers, vital for urban sustainable development, often exhibit leisure-time physical inactivity (LTPI). Few studies have examined LTPI and its constraints among migrant workers. This study aimed to identify the determinants of LTPI and its constraints among migrant workers. Guangzhou was used as a case study through a questionnaire survey of 26 communities (n = 1024). Logistic regression assessed the impact of household registration on LTPI and its interaction effects. The determinants of LTPI among migrant workers were compared with those of the other groups. The study found a link between LTPI and the living environment among residents and migrant workers. Household registration influences LTPI through interactions with factors such as the number of sports facilities and community greetings. The main barriers to leisure-time physical activity among migrant workers were insufficient education, social capital, and green open spaces. This study discusses the underlying mechanisms and proposes measures to address LTPI among migrant workers. Full article

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23 pages, 8567 KiB

Open AccessArticle

Integrating Multi-Model Coupling to Assess Habitat Quality Dynamics: Spatiotemporal Evolution and Scenario-Based Projections in the Yangtze River Basin, China

by Yuzhou Zhang, Jianxin Yang, Weilong Wu and Diwei Tang

Sustainability 2025, 17(10), 4699; https://doi.org/10.3390/su17104699 - 20 May 2025

Abstract

As a pivotal ecological–economic nexus in China, the Yangtze River Basin (YRB)’s spatiotemporal evolution of habitat quality (HQ) profoundly influences regional sustainable development. This study establishes a tripartite analytical framework integrating remote sensing big data, socioeconomic datasets, and ecological modeling. By coupling the [...] Read more.

As a pivotal ecological–economic nexus in China, the Yangtze River Basin (YRB)’s spatiotemporal evolution of habitat quality (HQ) profoundly influences regional sustainable development. This study establishes a tripartite analytical framework integrating remote sensing big data, socioeconomic datasets, and ecological modeling. By coupling the InVEST and PLUS models with Theil–Sen median trend analysis and Mann–Kendall tests, we systematically assessed HQ spatial heterogeneity across the basin during 2000–2020 and projected trends under 2030 scenarios (natural development (S1), cropland protection (S2), and ecological conservation (S3)). Key findings reveal that basin-wide HQ remained stable (0.599–0.606) but exhibited marked spatial disparities, demonstrating a “high-middle reach (0.636–0.649), low upper/lower reach” pattern. Urbanized downstream areas recorded the minimum HQ (0.478–0.515), primarily due to landscape fragmentation from peri-urban expansion and transportation infrastructure. Trend analysis showed that coefficient of variation (CV) values ranged from 0.350 to 2.72 (mean = 0.768), indicating relative stability but significant spatial variability. While 76.98% of areas showed no significant HQ changes, 15.83% experienced declines (3.56% with significant degradation, p < 0.05) concentrated in urban agglomerations (e.g., the Wuhan Metropolitan Area, the Yangtze River Delta). Only 7.18% exhibited an HQ improvement, predominantly in snowmelt-affected Qinghai–Tibet Plateau regions, with merely 0.95% showing a significant enhancement. Multi-scenario projections align with Theil–Sen trends, predicting HQ declines across all scenarios. S3 curbs decline to 0.33% (HQ = 0.597), outperforming S1 (1.07%) and S2 (1.15%). Nevertheless, downstream areas remain high-risk (S3 HQ = 0.476). This study elucidated compound drivers of urbanization, agricultural encroachment, and climate change, proposing a synergistic “zoning regulation–corridor restoration–cross-regional compensation” pathway. These findings provide scientific support for balancing ecological protection and high-quality development in the Yangtze Economic Belt, while offering systematic solutions for the sustainable governance of global mega-basins. Full article

20 pages, 3716 KiB

Open AccessArticle

Antimicrobial Action of Ginger and Ornamental Rock Wastes for Cement Mortar

by Romário Moreira Siqueira, Bruna Sthefanie Paz de Souza, Jonas Alexandre, Aline Chaves Intorne, Edmilson José Maria, Sergio Neves Monteiro and Afonso Rangel Garcez de Azevedo

Sustainability 2025, 17(10), 4698; https://doi.org/10.3390/su17104698 - 20 May 2025

Abstract

This study investigated the technical feasibility and antimicrobial potential of incorporating ornamental rock, limestone, and ginger waste into coating mortars with the aim of developing an innovative and sustainable solution for civil construction. This study evaluated the synergistic action of these materials on [...] Read more.

This study investigated the technical feasibility and antimicrobial potential of incorporating ornamental rock, limestone, and ginger waste into coating mortars with the aim of developing an innovative and sustainable solution for civil construction. This study evaluated the synergistic action of these materials on the microbiological and mechanical resistance of mortar, contributing to the greater durability and efficiency of the coatings. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD) analyses were performed to characterize the morphology, chemical composition, and crystalline structure of the added materials, confirming their suitability for the cement matrix. Tests in the fresh state evaluated parameters such as density, consistency index, and entrained air content, demonstrating the viability of the formulations, whereas flexural and compressive strength tests indicated significant improvements in the mechanical performance of the modified mortar. Microbiological tests demonstrated a significant reduction in microbial colonization, indicating the action of ginger’s bioactive compounds, such as gingerol and shogaol, which have antimicrobial properties and are effective in inhibiting the growth of pathogenic microorganisms, as confirmed by the reduction in the bacterial colony count from 4 × 10² to 1 × 10² CFU mL⁻¹. Comparisons with conventional compositions indicate that the proposed approach outperformed traditional formulations in terms of both mechanical resistance and microbiological control. Thus, the results validate this research as a promising strategy for improving the durability and performance of coating mortars, reducing maintenance costs, and promoting the sustainable use of alternative materials in civil construction. Full article

(This article belongs to the Special Issue Sustainable Advancements in Construction Materials)

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17 pages, 1116 KiB

Open AccessArticle

Integrating DEA and AHP for Optimizing Rural Road Network Planning Under the Common Prosperity Framework: A Case Study of Yueqing City

by Yesen Lu, Hualong Huang, Zhihua Zhang, Qiugang Tao, Jinrui Gong and Zhenyu Mei

Sustainability 2025, 17(10), 4697; https://doi.org/10.3390/su17104697 - 20 May 2025

Abstract

Transportation infrastructure serves a pivotal role in driving regional development. This study proposes a decision-making framework for rural road network planning within the context of China’s common prosperity initiative. An integrated model combining Data Envelopment Analysis (DEA) and the Analytic Hierarchy Process (AHP) [...] Read more.

Transportation infrastructure serves a pivotal role in driving regional development. This study proposes a decision-making framework for rural road network planning within the context of China’s common prosperity initiative. An integrated model combining Data Envelopment Analysis (DEA) and the Analytic Hierarchy Process (AHP) is developed, where DEA is employed to identify technically efficient planning alternatives and AHP is used to rank these alternatives based on social and environmental benefits. Applying the model to the case of Yueqing City, Zhejiang Province, the findings reveal that common prosperity-oriented schemes, particularly the Scheme, which emphasizes full industrial coverage and balanced equity, achieve a superior balance among construction costs, industrial coverage, regional equity, and carbon emissions. Theoretically, this research advances transportation planning by incorporating equity-focused metrics, such as the Gini coefficient, into efficiency analyses, thus promoting a socially sustainable approach to infrastructure development. Practically, the proposed method offers a systematic and actionable tool for local governments to optimize rural transportation networks in support of common prosperity and balanced regional growth. The resulting framework not only identifies technically efficient and equitable layouts but also offers planners a transparent tool for balancing cost, social equity, and environmental impact in future rural infrastructure projects. Full article

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