Journal Description
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)
Latest Articles
Micro/Nanoplastics Alter Daphnia magna Life History by Disrupting Glucose Metabolism and Intestinal Structure
Sustainability 2025, 17(23), 10728; https://doi.org/10.3390/su172310728 (registering DOI) - 30 Nov 2025
Abstract
Microplastic pollution poses growing risks to aquatic zooplankton, yet its impact on Daphnia magna life history remains incompletely understood. This study explored the influences of micro/nanoplastics (MPs/NPs) on D. magna by exposing organisms to size- and concentration-varied microplastics, tracking microplastic distribution via fluorescence
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Microplastic pollution poses growing risks to aquatic zooplankton, yet its impact on Daphnia magna life history remains incompletely understood. This study explored the influences of micro/nanoplastics (MPs/NPs) on D. magna by exposing organisms to size- and concentration-varied microplastics, tracking microplastic distribution via fluorescence imaging. Results demonstrated significant microplastic-induced impairments in growth and reproduction. Gut microbiota analysis revealed microplastic-altered microbial communities, with functional prediction identifying disrupted glucose metabolism as a key driver of life-history changes. Intestinal structure observations further showed microplastic-accelerated aging. Collectively, our findings highlight that microplastic accumulation in D. magna disrupts gut microbiota and tissue integrity, ultimately impairing life-history traits. These alterations in growth and gut characteristics of D. magna may further propagate through the aquatic food web, potentially damaging the intestinal structure and function of plankton communities. Given the pivotal role of zooplankton in nutrient cycling and energy transfer, our findings underscore that microplastic-induced disruptions in key species like D. magna could threaten the stability and sustainability of aquatic ecosystems.
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(This article belongs to the Special Issue Sustainable Treatment of Organic Pollutants and Microbial Degradation for Environmental Sustainability)
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Open AccessArticle
Points of Entry for Enhancing Policymakers’ Capacity to Develop Green Economy Agenda-Setting
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Mahawan Karuniasa and Thoriqi Firdaus
Sustainability 2025, 17(23), 10727; https://doi.org/10.3390/su172310727 (registering DOI) - 30 Nov 2025
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Indonesia has articulated ambitious green economy objectives through frameworks such as the Low Carbon Development Initiative (LCDI). Despite this ambition, a critical research gap exists. The weak ‘green political capabilities’ of policymakers—defined as their ability to navigate political processes, build coalitions, and translate
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Indonesia has articulated ambitious green economy objectives through frameworks such as the Low Carbon Development Initiative (LCDI). Despite this ambition, a critical research gap exists. The weak ‘green political capabilities’ of policymakers—defined as their ability to navigate political processes, build coalitions, and translate technical knowledge into viable policy—hinder effective agenda-setting and implementation. This study addresses this deficit by identifying strategic points of entry for enhancing these capabilities to strengthen a more sustainable economic transition. Employing a mixed-methods approach guided by the UNDP Capacity Assessment Framework, this research gathered data from 170 stakeholders via workshops, focus group discussions, and surveys. The analysis identifies four principal entry points: (1) internal institutional development, (2) accreditation processes, (3) bureaucratic reform, and (4) external partnerships. Critically, ordinal regression reveals which actors most significantly influence capacity development priorities. Governmental/legislative institutions (Estimate = 1.855, p < 0.010) and the private sector (Estimate = 3.173, p < 0.020) exert a significant positive influence on advancing the green economy agenda. Conversely, competencies such as policy strengthening exhibit a significant negative correlation (Estimate = −3.467, p < 0.000), which indicates a concentration of need among institutions with substantial capacity gaps. The study’s key contribution is a framework for systematically integrating green competencies into national accreditation standards and bureaucratic reforms, providing a clear pathway to transform entry points into effective levers for enhancing the state’s green political capabilities.
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Open AccessArticle
Community Perceptions of Ecosystem Services from Homegarden-Based Urban Agriculture in Bandung City, Indonesia
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Aji Saputra, Oekan S. Abdoellah, Gemilang Lara Utama, Indri Wulandari, Dede Mulyanto and Yusep Suparman
Sustainability 2025, 17(23), 10726; https://doi.org/10.3390/su172310726 (registering DOI) - 30 Nov 2025
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Urban agriculture, particularly homegarden-based urban agriculture, has gained recognition as a valuable tool for promoting sustainability in rapidly urbanizing cities. This study investigates community perceptions of the ecosystem services provided by homegarden-based urban agriculture in Bandung City, Indonesia. The research aims to assess
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Urban agriculture, particularly homegarden-based urban agriculture, has gained recognition as a valuable tool for promoting sustainability in rapidly urbanizing cities. This study investigates community perceptions of the ecosystem services provided by homegarden-based urban agriculture in Bandung City, Indonesia. The research aims to assess how urban residents perceive the contributions of homegardens to food security, environmental sustainability, and social well-being. Using a mixed-methods approach, qualitative data were collected through semi-structured interviews with key informants, while quantitative data were obtained from a survey of members of the urban agriculture community. The results revealed that homegardens play a supplementary role in food production, providing fresh produce but contributing only minimally to overall food security. They were recognized for their role in biodiversity conservation, microclimate regulation, disaster risk reduction, social cohesion, and improving mental well-being. Despite these benefits, challenges such as limited space, lack of knowledge, and competing land uses hinder the full integration of homegardens into urban systems. The findings suggest that enhancing education and policy support for urban agriculture can help maximize the utilization of the potential of homegardens in urban sustainability. Future research should focus on overcoming these barriers and exploring strategies for expanding homegarden practices in urban areas.
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Open AccessArticle
Ecological Security Assessment Based on Sensitivity, Connectivity, and Ecosystem Service Value and Pattern Construction: A Case Study of Chengmai County, China
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Yaoyao Zhao, Yuan Feng, Qing Liu, Yixian Mo, Shuhai Zhuo and Peng Zhou
Sustainability 2025, 17(23), 10724; https://doi.org/10.3390/su172310724 (registering DOI) - 30 Nov 2025
Abstract
Against the backdrop of continuous natural space loss and accelerated urbanization, considerable attention has been directed toward balancing economic development demands with the protection of fragile ecosystems within limited spatial boundaries to achieve regional sustainable development. This study therefore focuses on Chengmai County,
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Against the backdrop of continuous natural space loss and accelerated urbanization, considerable attention has been directed toward balancing economic development demands with the protection of fragile ecosystems within limited spatial boundaries to achieve regional sustainable development. This study therefore focuses on Chengmai County, a small-scale region prioritizing both green development and ecological conservation. Land-use changes and trends in ecosystem services value (ESV) from 2000 to 2020 were analyzed. An ecological security assessment model was developed, integrating ecosystem services, ecological sensitivity, and landscape connectivity, which enabled the identification of areas with high ecological security value as ecological sources. Ecological corridors and nodes were extracted using the minimum cumulative resistance model and the gravity model, culminating in the construction of Chengmai County’s ecological security pattern through overlay analysis. The main findings are summarized as follows: (1) Construction land expanded rapidly between 2000 and 2020. The ecological sensitivity of Chengmai County displayed a spatial distribution pattern of “high in the south, low in the north,” while ESV exhibited a pattern of “high in the central-south and low in the northeast,” showing an overall increasing trend. (2) The overall ecological security status was relatively favorable. A total of 10 ecological nodes and 45 ecological corridors were identified, including 16 core corridors. (3) Based on these analyses, an ecological security pattern described as “one axis, two belts, and three zones” was established for Chengmai County. This study provides a practical spatial strategy for ecological conservation and sustainable development in Chengmai County and offers a transferable methodological framework for similar coastal regions facing development pressures.
Full article
(This article belongs to the Special Issue Ecosystem Services in the Planning and Sustainable Development of Urban Green Spaces)
Open AccessArticle
Environmental Courts and Supply Chain Financing in China
by
Kandi Yang, Guangfan Sun, Xueqin Hu and Yao Wang
Sustainability 2025, 17(23), 10723; https://doi.org/10.3390/su172310723 (registering DOI) - 30 Nov 2025
Abstract
The institutionalization of environmental courts enhances regional environmental enforcement efficacy, which in turn exerts intensified regulatory pressure on local pollution intensive enterprises. Empirical evidence confirms that such judicial mechanisms significantly improve the supply chain financing capacity of regulated firms through a green governance
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The institutionalization of environmental courts enhances regional environmental enforcement efficacy, which in turn exerts intensified regulatory pressure on local pollution intensive enterprises. Empirical evidence confirms that such judicial mechanisms significantly improve the supply chain financing capacity of regulated firms through a green governance channel. This causal pathway operates via three interrelated mechanisms: increased environmental disclosure transparency, strategic recruitment of executives with environmental expertise, and systematic ESG performance upgrades. Collectively these adaptations enable polluting enterprises to achieve better supply chain financing conditions. Subgroup analysis identifies three dimensions of heterogeneous treatment effects. First, the financing enhancement effect is more pronounced among larger enterprises due to their greater resource allocation flexibility. Second, firms with gender-diverse leadership, particularly those employing female executives, demonstrate stronger responsiveness to environmental regulations. Third, enterprises operating in less technology intensive sectors benefit more substantially from compliance driven financing improvements, as their operational structures are more amenable to rapid environmental governance adjustments.
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(This article belongs to the Special Issue Sustainability Strategy, Corporate Growth and Risk Perspectives)
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Green Fund Shareholding and Corporate Carbon Performance: An Empirical Analysis Based on Chinese A-Share Listed Companies
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Qiao Chang and Hua Wang
Sustainability 2025, 17(23), 10722; https://doi.org/10.3390/su172310722 (registering DOI) - 30 Nov 2025
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Against the global low-carbon transition, China, as one of the world’s major carbon emitters, relies on green finance to drive corporate carbon reduction. However, existing research has paid limited attention to green funds, an important component of China’s green finance system, leaving their
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Against the global low-carbon transition, China, as one of the world’s major carbon emitters, relies on green finance to drive corporate carbon reduction. However, existing research has paid limited attention to green funds, an important component of China’s green finance system, leaving their role in shaping corporate carbon performance understudied. This study addresses this gap by exploring how green fund shareholding affects corporate carbon performance. Using data of Chinese A-share listed companies from 2008 to 2022, this work employed baseline regression, robustness checks, mediation analysis, and heterogeneity tests. Key findings include: green fund shareholding is associated with significant improvements in corporate carbon performance; green technology innovation plays a partial mediating role in this relationship; external supervision positively moderates the link between green fund shareholding and corporate carbon performance; and the positive effect tends to be more pronounced for firms with higher green fund ownership and net value ratios. This study helps fill the gap of ignoring investor heterogeneity in prior related research. It also suggests that regulators could optimize information disclosure and supervision for green funds, while enterprises may strengthen collaboration with green funds, providing support for China’s green finance development and corporate low-carbon transition.
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Open AccessArticle
Can Virtual Influencers Drive Online Consumer Behavior? An Applied Examination of ELM Model Investigating the Marketing Effects of Virtual Influencers
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Wei-Kuo Tseng and Chueh-Chu Ou
Sustainability 2025, 17(23), 10721; https://doi.org/10.3390/su172310721 (registering DOI) - 30 Nov 2025
Abstract
With the rapid advancement of social media and AI technologies, influencer marketing has evolved significantly. Virtual influencers have emerged as alternatives to traditional human influencers. Grounded in the Elaboration Likelihood Model (ELM), this study examines how virtual influencers’ source credibility dimensions (expertise, attractiveness,
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With the rapid advancement of social media and AI technologies, influencer marketing has evolved significantly. Virtual influencers have emerged as alternatives to traditional human influencers. Grounded in the Elaboration Likelihood Model (ELM), this study examines how virtual influencers’ source credibility dimensions (expertise, attractiveness, and trustworthiness) affect consumer attitudes and purchase intentions. Using the case of virtual influencer Imma, this study collected 344 valid online survey responses. The empirical results show that, along the central route, perceived product value has a significant and positive effect on purchase intention. Along the peripheral route, the trustworthiness, attractiveness, and expertise of the virtual influencer all exert significant positive effects on purchase intention. However, product involvement moderates these effects differently: for high-involvement consumers, the effects of trustworthiness and attractiveness on purchase intention are significantly strengthened, while the moderating effects on expertise and perceived value remain non-significant. This study contributes to the emerging literature on virtual influencer marketing by demonstrating how source credibility dimensions and perceived value interact with product involvement to shape consumer responses. Additionally, virtual influencers offer sustainability benefits by minimizing carbon emissions from travel and physical production inherent in traditional influencer campaigns. The findings offer practical implications for marketers: virtual influencers can effectively enhance brand exposure, but their persuasive impact varies by product involvement requiring tailored content strategies for high- versus low-involvement products. Furthermore, future research could extend this work by examining the effects of different product categories and cultural contexts on the effectiveness of virtual influencer marketing.
Full article
(This article belongs to the Special Issue AI-Powered Virtual Assistants in Sustainable Marketing: Enhancing Customer Experience Through Innovation Technologies)
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Decoding Climate–Soil Interactions in Kazakhstan’s Drylands: Insights from PCA and SHAP Analyses
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Raushan Ramazanova, Alexander Ulman, Vitaliy Salnikov, Konstantin Pachikin, Zhanar Raimbekova, Azamat Yershibul and Yersultan Songulov
Sustainability 2025, 17(23), 10720; https://doi.org/10.3390/su172310720 (registering DOI) - 30 Nov 2025
Abstract
Soil degradation in arid ecosystems is a major threat to sustainable development and food security, especially under accelerating climate change. Kazakhstan, where more than 70% of agricultural land suffers from salinisation, erosion, and humus loss, offers a representative case for studying climate-driven degradation.
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Soil degradation in arid ecosystems is a major threat to sustainable development and food security, especially under accelerating climate change. Kazakhstan, where more than 70% of agricultural land suffers from salinisation, erosion, and humus loss, offers a representative case for studying climate-driven degradation. This study quantitatively assessed the influence of air temperature, precipitation, aridity index, and extreme climatic events on soil properties in the arid regions of western Kazakhstan (Atyrau and Mangystau). The analysis integrated long-term meteorological time series (1941–2023) with field and laboratory data (1967–2024) into a harmonised dataset of 1330 records. Principal component analysis (PCA) identified four degradation gradients explaining 73.6% of total variance, while Random Forest and SHAP algorithms quantified variable importance. Mean annual temperature, frequency of arid years, and aridity index were the strongest predictors of humus, salinity, pH, and CO2 parameters, with climate factors accounting for up to 30% of soil variability. The findings demonstrate that climatic stressors are the main drivers of soil degradation in arid zones, with climate factors explaining up to 30% of the variability in key soil properties (humus, salinity, pH, and CO2)—a substantial proportion that underscores their dominant role relative to local geochemical and anthropogenic influences. The proposed hybrid PCA—Random Forest/SHAP framework provides a robust tool for analysing climate–soil interactions and supports the design of adaptive land-use strategies to achieve Land Degradation Neutrality (LDN) in Kazakhstan and other arid regions.
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(This article belongs to the Section Soil Conservation and Sustainability)
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Sustainability-Oriented Ultra-Short-Term Wind Farm Cluster Power Prediction Based on an Improved TCN–BiGRU Hybrid Model
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Ruifeng Gao, Zhanqiang Zhang, Keqilao Meng, Yingqi Gao and Wenyu Liu
Sustainability 2025, 17(23), 10719; https://doi.org/10.3390/su172310719 (registering DOI) - 30 Nov 2025
Abstract
With the large-scale integration of wind power into the grid, the accuracy of wind farm cluster power prediction has become a key factor for the sustainability of modern power systems. Reliable ultra-short-term forecasts support the secure dispatch of high-penetration renewable energy, reduce wind
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With the large-scale integration of wind power into the grid, the accuracy of wind farm cluster power prediction has become a key factor for the sustainability of modern power systems. Reliable ultra-short-term forecasts support the secure dispatch of high-penetration renewable energy, reduce wind curtailment, and improve the low-carbon and economical operation of power systems. Aiming at the problem of significant differences in wind turbine characteristics, this paper proposes a prediction method based on an improved density-based spatial clustering of applications with noise (DBSCAN) and a hybrid deep learning model. First, the wind speed signal is decomposed at multiple scales using successive variational modal decomposition (SVMD) to reduce non-stationarity. Subsequently, the DBSCAN parameters are optimized by the fruit fly optimization algorithm (FOA), and dimensionality reduction is performed by principal component analysis (PCA) to achieve efficient clustering of wind turbines. Next, the representative turbines with the highest correlation are selected in each cluster to reduce computational complexity. Finally, the SVMD-TCN-BiGRU-MSA-GJO hybrid model is constructed, and long-term dependence is extracted using a temporal convolutional network (TCN); the temporal features are captured by bidirectional gated recurrent units (BiGRUs); the feature weights are optimized by a multi-head self-attention mechanism (MSA), and the hyper-parameters are, in turn, optimized by golden jackal optimization (GJO). The experimental results show that this method reduces the MAE, RMSE, and MAPE by 14.02%, 12.9%, and 13.84%, respectively, and improves R2 by 3.9% on average compared with the traditional model, which significantly improves prediction accuracy and stability. These improvements enable more accurate scheduling of wind power, lower reserve requirements, and enhanced stability and sustainability of power system operation under high renewable penetration.
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Open AccessArticle
Comparison of Nature-Inspired Optimization Models and Robust Machine-Learning Approaches in Predicting the Sustainable Building Energy Consumption: Case of Multivariate Energy Performance Dataset
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Mümine Kaya Keleş, Abdullah Emre Keleş, Elif Kavak and Jarosław Górecki
Sustainability 2025, 17(23), 10718; https://doi.org/10.3390/su172310718 (registering DOI) - 30 Nov 2025
Abstract
Accurate prediction of building energy loads is essential for smart buildings and sustainable energy management. While machine learning (ML) approaches outperform traditional statistical models at capturing nonlinear relationships, most studies primarily optimize prediction accuracy, overlooking the importance of computational efficiency and feature compactness,
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Accurate prediction of building energy loads is essential for smart buildings and sustainable energy management. While machine learning (ML) approaches outperform traditional statistical models at capturing nonlinear relationships, most studies primarily optimize prediction accuracy, overlooking the importance of computational efficiency and feature compactness, which are critical in real-time, resource-constrained environments. This study aims to evaluate whether hybrid nature-inspired feature-selection techniques can enhance the accuracy and computational efficiency of ML-based building energy load prediction. Using the UCI Energy Efficiency dataset, eight ML models (LightGBM, CatBoost, XGBoost, Decision Tree, Random Forest, Extra Trees, Linear Regression, Support Vector Regression) were trained under feature subsets obtained from the Butterfly Optimization Algorithm (BOA), Grey Wolf Optimization Algorithm (GWO), and a hybrid BOA–GWO approach. Model performance was evaluated using three metrics (MAE, RMSE, and R2), along with training time, prediction time, and the number of selected features. The results show that gradient-boosting models consistently yield the highest accuracy, with CatBoost achieving an R2 of 0.99 or higher. The proposed hybrid BOA–GWO method achieved competitive accuracy with fewer features and reduced training time, demonstrating its suitability for efficient ML deployment in smart building environments. Rather than proposing a new metaheuristic algorithm, this study contributes by adapting a hybrid BOA–GWO feature-selection strategy to the building energy domain and evaluating its benefits under a multi-criteria performance framework. The findings support the practical adoption of hybrid feature-selection-supported ML pipelines for intelligent building systems, energy management platforms, and IoT-based real-time applications.
Full article
(This article belongs to the Special Issue Energy Efficiency and Innovative Material Application in Sustainable Buildings)
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Digital Economy’s Impact on Tourism Eco-Efficiency: An Empirical Analysis of Chinese Cities
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Hong Shi, Caiqing Chen, Lu Gan, Taohong Li and Yijun Liu
Sustainability 2025, 17(23), 10717; https://doi.org/10.3390/su172310717 (registering DOI) - 30 Nov 2025
Abstract
The tourism industry’s strong integration with the digital economy has recognized as a development trend. Tourism eco-efficiency is a useful indicator of the industry’s capacity for sustainable development. More thorough research is required to determine how the degree of digital economy development affects
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The tourism industry’s strong integration with the digital economy has recognized as a development trend. Tourism eco-efficiency is a useful indicator of the industry’s capacity for sustainable development. More thorough research is required to determine how the degree of digital economy development affects tourism eco-efficiency in the backdrop of the sustainable tourism development. In order to evaluate the tourism eco-efficiency of 275 Chinese prefecture-level cities, this study builds a super-SBM model with unexpected output. We empirically determine the impact of the comprehensive development of the digital economy on eco-efficiency with a panel model (2011–2017). The analysis findings show the following: (1) Eco-efficiency in China is consistently maintained at the level of 0.5, with a gradient that puts the east ahead of the central, northeastern, and western regions. (2) Urban eco-efficiency is significantly inhibited by China’s digital economy, with notable regional variation. (3) The inhibiting effect of the degree of digital economic development on TEE can be mitigated by environmental quality. Strategic policy ideas for improving urban tourism eco-efficiency are included in the paper’s conclusion.
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(This article belongs to the Section Tourism, Culture, and Heritage)
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Open AccessFeature PaperReview
Global Innovations in Sustainable Pharmaceutical Packaging in the Last 25 Years: A Scoping Review
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Sophie Jackman, Peter Mc Guinness, Lia Brennan, Ruby Pereira, Anne Tyrrell, Anna Maria Barry, Cait Brennan and Bernard D. Naughton
Sustainability 2025, 17(23), 10716; https://doi.org/10.3390/su172310716 (registering DOI) - 29 Nov 2025
Abstract
Pharmaceutical packaging is integral to the efficacy, safety, quality and regulatory compliance of medicinal products. However, traditional pharmaceutical packaging can cause harmful environmental effects due to a lack of eco-design methods, excessive use of synthetic materials, and a lack of effective recycling techniques.
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Pharmaceutical packaging is integral to the efficacy, safety, quality and regulatory compliance of medicinal products. However, traditional pharmaceutical packaging can cause harmful environmental effects due to a lack of eco-design methods, excessive use of synthetic materials, and a lack of effective recycling techniques. In response, a range of innovations in sustainable pharmaceutical packaging have emerged to mitigate these environmental effects. This scoping review aims to identify and map global innovations in sustainable pharmaceutical packaging developed within the last 25 years, examine implementation challenges, identify gaps in the literature, and suggest a framework to guide the pharmaceutical industry in adopting these eco-innovations. Following the PRISMA-ScR guidelines, this review analysed 100 studies from grey and academic literature published between the years 2000 and 2025. Data extraction and thematic analysis was performed and revealed four main areas of innovation: biodegradable materials, design, smart technology, and waste management. Key barriers to their adoption include regulatory, safety, and economic challenges. One gap identified in the literaturewas the lack of a framework to aid the implementation of innovations in sustainable pharmaceutical packaging. Therefore, this review also proposes a responsible packaging innovation framework.
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Open AccessArticle
How Events Empower the Countryside: A Study of Rural Household Livelihoods in Traditional Villages of Ethnic Mountainous Areas Influenced by Guizhou’s “Village Super League”
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Keru Luo, Fangqin Yang, Jianwei Sun, Jing Luo, Jiaxing Cui, Xuesong Kong, Xiaojian Chen, Ya Wang and Shuyang Huang
Sustainability 2025, 17(23), 10715; https://doi.org/10.3390/su172310715 (registering DOI) - 29 Nov 2025
Abstract
As an emerging sports tourism event, Guizhou’s “Village Super League” injects new vitality into the optimization of human–land relationships and the development of household livelihoods in traditional villages of ethnic mountainous regions. Studying five affected traditional tourism villages from an “event–actor–capital” perspective using
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As an emerging sports tourism event, Guizhou’s “Village Super League” injects new vitality into the optimization of human–land relationships and the development of household livelihoods in traditional villages of ethnic mountainous regions. Studying five affected traditional tourism villages from an “event–actor–capital” perspective using mixed methods, this research finds the following: (1) The composite average score of household livelihood capital is 0.3177, indicating a medium–low level, which suggests that households’ livelihood structure still requires significant enhancement despite the tourism boost from the “Village Super League”. (2) There is an imbalance in development among the villages. The livelihoods of households under the influence of the “Village Super League” exhibit distinct characteristics, being “driven by external flows, led by social capital, supported by the material foundation, and coordinated with other forms of capital.” (3) The evolution of household livelihoods follows a pathway of “event-driven supplementation, endogenous renewal of actors, capital integration and synergy.” By constructing shared event memory markers, the livelihoods of villages at different stages of tourism development demonstrate differentiated dynamic mechanisms. The findings deepen the theoretical understanding of livelihoods in traditional villages under event-driven development. Consequently, this study recommends that policymakers and community stewards channel transient social capital and external flows into durable physical and financial assets to ensure livelihood sustainability beyond the initial event boom.
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Open AccessArticle
The Link Between ESG Factors and Corporate Profitability: Evidence from Resource-Intensive Industries in Europe and the USA
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Aurelija Burinskienė, Virginija Grybaitė and Giedrė Lapinskienė
Sustainability 2025, 17(23), 10714; https://doi.org/10.3390/su172310714 (registering DOI) - 29 Nov 2025
Abstract
Recently, the role of businesses in advancing sustainable development has drawn growing attention from governments, investors, and a wide range of stakeholders. This increased focus has led enterprises to incorporate environmental, social, and governance (ESG) considerations into their strategic and operational decisions, driven
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Recently, the role of businesses in advancing sustainable development has drawn growing attention from governments, investors, and a wide range of stakeholders. This increased focus has led enterprises to incorporate environmental, social, and governance (ESG) considerations into their strategic and operational decisions, driven by evolving regulatory frameworks, increasing investor scrutiny, and rising consumer expectations. Despite this shift toward sustainability-oriented practices, the relationship between ESG performance and financial results remains a subject of considerable debate and empirical uncertainty. The research examines the links between separate ESG pillars and the financial performance of enterprises operating within resource-intensive industries, such as energy, industrials, materials, and utilities across Europe and the USA, based on a sample of 384 companies, using data from 2015 to 2024. The study focuses on differences between regions and further examines whether differences in the influence of individual ESG dimensions on the financial results of enterprises are evident within specific industries. The research findings present identified positive and statistically significant relationships with the environmental pillar of ESG for both Europe and the US regions. There are differences between the social and governance pillars of ESG and the financial performance of the resource-intensive industries of Europe and the USA. In Europe, there is a positive influence of social-related factors on financial performance, while in the USA, there is a negative impact. However, the governance-related factor shows that a statistically significant relationship exists with financial performance in the USA, and a negative one in Europe. These findings show the different focus directions of Europe and the USA regions.
Full article
(This article belongs to the Special Issue Corporate Social Responsibility and Sustainable Economic Development)
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Open AccessArticle
Dynamic Regulation and Renewable Integration for Low-Carbon District Heating Networks
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Frantisek Vranay, Daniela Kaposztasova and Zuzana Vranayova
Sustainability 2025, 17(23), 10713; https://doi.org/10.3390/su172310713 (registering DOI) - 29 Nov 2025
Abstract
Integration of renewable energy sources into existing residential and communal district heating systems requires technical adjustments and corrections. Measures aimed at reducing heat consumption at the points of delivery have a similar impact. This study aims, through simplified partial models (in heating mode),
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Integration of renewable energy sources into existing residential and communal district heating systems requires technical adjustments and corrections. Measures aimed at reducing heat consumption at the points of delivery have a similar impact. This study aims, through simplified partial models (in heating mode), to present the relationships between these modifications and their potential effects on operational problems and deficiencies. The main parameters assessed in the design and correction of systems are temperature differentials, derived flow rates, pumping work, and control methods. Within the chain of heat source–primary distribution–secondary distribution–consumers, the analysis focuses on secondary circuits with consumers. A simplified multi-building network model was used to compare static and dynamic control strategies under temperature regimes of 70/50 °C, 60/40 °C, and 40/30 °C. The results show that dynamic control based on variable-frequency pumps, weather-compensated supply regulation, and optimized temperature differences between supply and return lines (ΔT) reduces pumping energy by 30–40% and increases heat delivery efficiency by up to 10%. A significant reduction in CO2 emissions is also observed due to decreased pumping work, reduced heat losses in the distribution network, and the integration of renewable energy sources. The savings depend on the type and extent of RES utilization. The implementation of dynamic control in these systems significantly improves exergy efficiency, operational stability, and the potential for low-temperature operation, thus providing a practical framework for the modernization of district heating networks.
Full article
(This article belongs to the Special Issue Sustainable Building: Renewable and Green Energy Efficiency)
Open AccessArticle
Optimization of Start-Extraction Time for Coalbed Methane Well in Mining Area Using Fluid–Solid Coupling Numerical Simulation
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Peiming Zhou, Ang Xu, Xueting Sun, Xiaozhi Zhou, Sijie Han, Jihang Dong, Jie Chen, Wei Gao and Yunfei Feng
Sustainability 2025, 17(23), 10712; https://doi.org/10.3390/su172310712 (registering DOI) - 29 Nov 2025
Abstract
Optimizing the start-extraction time for coalbed methane (CBM) wells in mining areas remains challenging. This is due to the limited understanding of mining-induced mechanical changes and fluid migration in protected seams, which restricts the development of clean fossil energy. To address this, a
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Optimizing the start-extraction time for coalbed methane (CBM) wells in mining areas remains challenging. This is due to the limited understanding of mining-induced mechanical changes and fluid migration in protected seams, which restricts the development of clean fossil energy. To address this, a geological-engineering model is constructed to investigate the mining-induced zonal evolution of stress, strain, permeability, and gas migration in protected seams, with the goal of optimizing the start-extraction time. The results show that gas production is controlled by the mechanical properties and gas pressure of protected seams near the well. Initially, these seams experience prolonged elastic strain. Plastic compressive strain develops at close-distance protected seams only when the coalface advances to within 5 m of them. Subsequently, rapid stress relief and complex stress directions lead to continuous plastic shear and expansion strains. As the distance from the mining seam increases, the plastic strains delay and diminish, reverting to elastic strain. These transitions collectively characterize the dynamic development of five distinct permeability regimes. Within permeability-reduced zones, an enhanced gas pressure gradient mitigates production declines. As the start-extraction time is progressively delayed, post-initiation gas production manifests in four phases: gradual decline, slow rebound, rapid increase, and surge. The optimal start-extraction time aligns with the rapid increase phase, when the coalface reaches the well, shortening extraction by at least 5.75 days and reducing electricity consumption by more than 2.07 × 104 kWh in the study area. This research provides practical solutions for methane emission reduction and sustainable CBM development in mining areas.
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(This article belongs to the Section Resources and Sustainable Utilization)
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Proposal for a New Indicator of the Economic Dimension of Sustainable Development: The Unproductive Employment Rate (UER)
by
Włodzimierz Kołodziejczak
Sustainability 2025, 17(23), 10711; https://doi.org/10.3390/su172310711 (registering DOI) - 29 Nov 2025
Abstract
The disparity in labour productivity between agriculture and non-agricultural sectors is a widespread and persistent phenomenon, and its effects are detrimental to all three pillars of sustainable development. Efforts to reduce this disparity require the establishment of a benchmark. Therefore, the paper proposes
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The disparity in labour productivity between agriculture and non-agricultural sectors is a widespread and persistent phenomenon, and its effects are detrimental to all three pillars of sustainable development. Efforts to reduce this disparity require the establishment of a benchmark. Therefore, the paper proposes a new measure of the economic dimension of sustainable development—the unproductive employment rate (UER)—which could be included in Sustainable Development Goal 8 (SDG 8). ‘Decent work and economic growth’, under target 8.5 ‘Full and productive employment and decent work with equal pay’, as SDG indicator 8.5.3. Based on cross-sectoral differences in labour productivity, this indicator measures the percentage of employment in agriculture that would need to be transferred out of the agricultural sector to achieve a balance between value added per employee in agriculture and value added per employee in the industrial and service sectors. The examples presented use World Bank data from 1995 and 2019 and show that higher levels of development and prosperity help to reduce the share of employment in agriculture and lower the UER indicator. A widening labour productivity gap has been observed between rich, developed groups of countries and groups of poor and least developed countries.
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(This article belongs to the Special Issue Agricultural Economics, Policies, and Rural Development for Sustainability)
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Human Capital and the Sustainable Energy Transition: A Socio-Economic Perspective
by
Maria Klonowska-Matynia
Sustainability 2025, 17(23), 10710; https://doi.org/10.3390/su172310710 (registering DOI) - 29 Nov 2025
Abstract
This article addresses the role of human capital in socio-economic development processes during Europe’s energy transition. The main empirical objectives are firstly to diagnose the overall level of human capital in the energy transition economy based on the original synthetic measure, HCIe, and
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This article addresses the role of human capital in socio-economic development processes during Europe’s energy transition. The main empirical objectives are firstly to diagnose the overall level of human capital in the energy transition economy based on the original synthetic measure, HCIe, and secondly to analyse and assess the variation in its spatial distribution across the European socio-economic landscape, which serves as a foundation for developing a targeted policy typology directly linked to the identified cluster profiles and their specific weaknesses. The general research question is: what is the level and degree of variation in the internal structure of human capital across the European socio-economic landscape? What actions should individual European countries take to support the development of human capital in the context of the energy transition? The research concept adopted also raises additional questions. Firstly, how can the importance of human capital be captured in an economy undergoing an energy transition? Secondly, are there appropriate indicators for measuring this based on the adopted research approach? European countries were selected as the subjects of the study. In the empirical section, taxonomic methods were employed to develop a proprietary synthetic measure of human capital in a transforming energy economy (HCIe), which was then used for the hierarchical classification of entities. The internal structure of human capital was explored using multi-criteria cluster analysis with the k-means algorithm. This approach resulted in a non-hierarchical classification of entities (typologisation). The main data sources used to construct the synthetic measures were international databases: IRENA, OECD, EUROSTAT, and the World Bank. Analysis of the HCIe measure and the clustering of European countries revealed that the key risk factor for transformation is the absence of integrated human capital within individual groups of countries. This highlights the urgent need for targeted investment in health and the development of systemic and green competencies.
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(This article belongs to the Special Issue Human Behavior, Psychology and Sustainable Well-Being: 2nd Edition)
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Urinary Creatinine as an Indicator of Water Intake in Sheep and Goats Sustainably Farmed in Tropical Climates
by
Emanoela Souza-Conde, Manuela Tosto, Raiane Mendes, Maria Leonor Araújo, José Herailton Gama Junior, Beatriz Santana, Henry Alba, Stefanie Santos, Evandro Pereira Neto, José Augusto Azevêdo, Robério Silva, Douglas Pina and Gleidson Giordano Carvalho
Sustainability 2025, 17(23), 10709; https://doi.org/10.3390/su172310709 (registering DOI) - 29 Nov 2025
Abstract
Mathematical models are valuable tools for predicting water intake in small ruminants, enhancing water use efficiency, reducing environmental pollution, alleviating competition for water with human consumption, and improving productive performance, ultimately leading to increased revenues and promoting sustainability. This study aims to evaluate
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Mathematical models are valuable tools for predicting water intake in small ruminants, enhancing water use efficiency, reducing environmental pollution, alleviating competition for water with human consumption, and improving productive performance, ultimately leading to increased revenues and promoting sustainability. This study aims to evaluate creatinine as a metabolic marker for estimating water intake in sheep and goats and to develop predictive models for tropical conditions. Five Santa Inês crossbred sheep and five Boer crossbred goats were used in a replicated 5 × 5 Latin square design. Treatments consisted of titanium dioxide supplementation at 1.0, 1.75, 2.5, 3.25, and 4.0 g/day. A species effect was observed on dry matter intake. Significant correlations were identified between water intake, urinary volume, body weight, metabolic weight, and creatinine concentration. Negative correlations were observed between water intake and both dry matter intake and metabolic measures. Five mathematical models were developed to predict water intake, all of which demonstrated good predictive capacity. Among them, the equation ŶH2Og/kgBW = 164.72 − 6.60 × MBW + 0.025 × Creat (mg/L) proved most reliable. This model enables accurate estimation of water intake in sheep and goats, supporting more efficient water management and sustainability in tropical regions where water resources are limited.
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(This article belongs to the Special Issue Sustainability of the Agricultural System and Agro-Ecological Environment)
Open AccessArticle
An Explicit Model for Optimal Siting and Sizing of Electric Truck Charging Stations
by
Yang Xu, Xia Shang, Yeying Wang and Lihui Zhang
Sustainability 2025, 17(23), 10708; https://doi.org/10.3390/su172310708 (registering DOI) - 29 Nov 2025
Abstract
The deployment of electric trucks is recognized as a crucial tool for reducing dependence on traditional fossil fuels and mitigating pollution from transportation systems. However, insufficient and unbalanced distribution of charging stations may hinder the use of electric trucks. This study develops an
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The deployment of electric trucks is recognized as a crucial tool for reducing dependence on traditional fossil fuels and mitigating pollution from transportation systems. However, insufficient and unbalanced distribution of charging stations may hinder the use of electric trucks. This study develops an explicit mixed-integer linear program to optimize the siting and sizing of charging stations for electric trucks in general transport networks. The model incorporates the queuing dynamics of electric trucks at charging stations through a formulated set of first-come-first-served constraints, enabling the direct computation of the charging waiting time for each truck. The objective function minimizes the total system cost, comprising the charging station construction cost, the electric truck procurement cost, the electricity consumption cost, and the operational cost, consisting of travel times, queuing times, and the delay penalties of the trucks. To address the computational challenges in solving large-scale network problems, we propose a hybrid solution strategy combining a rolling horizon framework with a genetic algorithm, which enhances computational efficiency through problem decomposition and iterative optimization. Finally, numerical experiments are conducted on three road networks, including the Sioux Falls network and the Chicago network, to validate the effectiveness of the proposed model and algorithm.
Full article
(This article belongs to the Section Sustainable Transportation)
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