Previous Issue
Volume 17, October-1
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.7
3.3
Journals
Sustainability
Volume 17
Issue 20
sustainability-logo

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sustainability, Volume 17, Issue 20 (October-2 2025) – 71 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
21 pages, 7935 KB  
Article
Social and Economic Influence of Sustainable Development: The Case of Al-Mouj, Muscat, Oman
by Eman Hanye Mohamed Nasr, Aisha Mohammed Al Shehhi and Mohamed Ali Mohamed Khalil
Sustainability 2025, 17(20), 9037; https://doi.org/10.3390/su17209037 (registering DOI) - 12 Oct 2025
Abstract
The sultanate of Oman has joined other nations in promoting sustainability, guided by Oman Vision 2040 and the Oman National Spatial Strategy. Oman now focuses on developing more human-centered cities, enhancing community well-being, boosting the local economy, and increasing investments. This study addresses [...] Read more.
The sultanate of Oman has joined other nations in promoting sustainability, guided by Oman Vision 2040 and the Oman National Spatial Strategy. Oman now focuses on developing more human-centered cities, enhancing community well-being, boosting the local economy, and increasing investments. This study addresses a research gap by examining the social and economic impact of the sustainable neighborhood “Al-Mouj” on the nearby urban area “Al-Mawaleh North” to maximize sustainability benefits. It analyzes how a sustainable neighborhood influences the economy, society, quality of life, and overall well-being. The study also identifies key factors driving the growth of sustainable practices in society and the economy. It has four main objectives in terms of answering the research question, primarily through surveys of community members and business owners, and by analyzing land use development around Al-Mouj. Data collection methods include literature review, case study, questionnaires, and interviews. Data analysis employs spatial, statistical, and thematic techniques. Responses from 515 participants are examined to ensure reliable results. Ethnographic methods are used to gain insights from open-ended questionnaire responses and interviews. The results confirm that Al-Mouj’s mixed-use development and sustainability features positively influence mental and physical health and stimulate economic activity within the local community. This study provides decision-makers and urban planners valuable insights into sustainable neighborhoods’ social and economic impacts when developed as open communities. It highlights the challenges of following international NSAT standards, which do not fully address local concerns. Full article
(This article belongs to the Section Sustainable Urban and Rural Development)
►▼ Show Figures

Figure 1

21 pages, 2552 KB  
Article
Equitable Allocation of Interprovincial Industrial Carbon Footprints in China Based on Economic and Energy Flow Principles
by Jing Zhao, Yongyu Wang, Xiaoying Shi and Muhammad Umer Arshad
Sustainability 2025, 17(20), 9036; https://doi.org/10.3390/su17209036 (registering DOI) - 12 Oct 2025
Abstract
The equitable allocation of carbon emission responsibility is fundamental to advancing China’s industrial decarbonization, achieving its dual-carbon goals, and realizing regional sustainable development. However, prevailing interprovincial carbon accounting frameworks often neglect the coupled dynamics of economic benefits, energy flows, and ecological capacity, leading [...] Read more.
The equitable allocation of carbon emission responsibility is fundamental to advancing China’s industrial decarbonization, achieving its dual-carbon goals, and realizing regional sustainable development. However, prevailing interprovincial carbon accounting frameworks often neglect the coupled dynamics of economic benefits, energy flows, and ecological capacity, leading to systematic misattribution of industrial carbon footprint transfers. Here, we develop an integrated analytical framework combining multi-regional input–output (MRIO) modeling and net primary productivity (NPP) assessment to comprehensively quantify industrial carbon footprints and their transfers across 30 Chinese provinces. By embedding both the benefit principle (aligning responsibility with trade-generated economic gains) and the energy flow principle (accounting for interprovincial energy trade), we construct a dual-adjustment mechanism that rectifies spatial and sectoral imbalances in traditional accounting. Our results reveal pronounced east-to-west industrial carbon footprint transfers, with resource-rich provinces (e.g., Inner Mongolia, Xinjiang) disproportionately burdened by external consumption, impacting the balance of sustainable development in these regions. Implementing benefit and energy flow adjustments redistributes responsibility more fairly: high-benefit, energy-importing provinces (e.g., Shanghai, Jiangsu, Beijing) assume greater carbon obligations, while energy-exporting, resource-dependent regions see reduced responsibilities. This approach narrows the gap between production- and consumption-based accounting, offering a scientifically robust, policy-relevant pathway to balance regional development and environmental accountability. The proposed framework provides actionable insights for designing carbon compensation mechanisms and formulating equitable decarbonization policies in China and other economies facing similar regional disparities. Full article
►▼ Show Figures

Figure 1

22 pages, 1299 KB  
Article
From Static Congruence to Dynamic Alignment: Person–Organization Fit Practices and Their Contribution to Sustainable HRM in Poland
by Patrycja Paleń-Tondel
Sustainability 2025, 17(20), 9035; https://doi.org/10.3390/su17209035 (registering DOI) - 12 Oct 2025
Abstract
Value alignment between employees and organizations is a salient concern in sustainable human resource management (sHRM). Previous research has mainly treated person–organization (P–O) fit as a static condition assessed at entry, while little is known about its processual nature across the employee lifecycle [...] Read more.
Value alignment between employees and organizations is a salient concern in sustainable human resource management (sHRM). Previous research has mainly treated person–organization (P–O) fit as a static condition assessed at entry, while little is known about its processual nature across the employee lifecycle or about how assessments relate to organizational responses to misfit. Addressing this gap, the present study examines how organizations operationalize value alignment across stages, methods, and remedial responses using original multidimensional indices. A cross-sectional survey of 104 HR managers in Poland was conducted, introducing the Fit Stage Score (assessment points across the lifecycle), the Fit Method Score (breadth of diagnostic tools), and the Misfit Response Score (remedial actions applied when misfit occurs). Results show that foreign-owned firms rely on more diverse diagnostic methods, sectoral variation appears only in the number of assessment stages, and neither executive gender nor ownership form has systematic effects. The strongest finding is the robust association between broader assessments and broader remedial measures, confirming the existence of an integrated “assessment–response bundle.” The study advances theory by providing empirical evidence for a dynamic, multidimensional view of P–O fit. Practically, it highlights that organizations can strengthen alignment by expanding assessment methods and coupling them with concrete remedial strategies such as training, mentoring, or internal mobility. Full article
(This article belongs to the Section Sustainable Management)
►▼ Show Figures

Figure 1

17 pages, 2715 KB  
Article
Titanium Dioxide for Improved Performance of Reclaimed Asphalt Pavement Aggregates in Concrete
by Mohammad S. Al Ja’fari, Marwh M. Al-Adaileh, Ahmad K. Al-Adayleh, Mazen J. Al-Kheetan, Yazeed S. Jweihan, Amjad H. Albayati, Musab Rabi, Saad S. Alrwashdeh, Yazeed A. Al-Noaimat and Seyed Hamidreza Ghaffar
Sustainability 2025, 17(20), 9034; https://doi.org/10.3390/su17209034 (registering DOI) - 12 Oct 2025
Abstract
This work presents an innovative approach to enhancing the performance of concrete with reclaimed asphalt pavement (RAP) aggregates using titanium dioxide (TiO2) nanoparticles. Traditional limestone coarse aggregates were partially replaced with 30% and 50% RAP aggregates; a subset of mixtures containing [...] Read more.
This work presents an innovative approach to enhancing the performance of concrete with reclaimed asphalt pavement (RAP) aggregates using titanium dioxide (TiO2) nanoparticles. Traditional limestone coarse aggregates were partially replaced with 30% and 50% RAP aggregates; a subset of mixtures containing RAP aggregates was treated with TiO2 nanoparticles. The rheological, mechanical, and long-term properties of concrete, along with changes in its chemical composition following the addition of RAP and TiO2, were evaluated. Results revealed that using 30% and 50% RAP in concrete mixtures reduced their compressive strength by 18% and 27%, respectively. However, using TiO2 in those mixtures enhanced their compressive strength by 8.7% and 6.3%. Moreover, concrete with 50% RAP exhibited an 85% increase in water absorption (the highest among all mixtures) compared to the control. TiO2 treatment was most beneficial in the 30% RAP mixture, reducing its water absorption by 32.5% compared to its untreated counterpart. Additionally, the 30% RAP mixture treated with TiO2 showed the highest resistance to sulfates among modified mixtures, as its compressive strength decreased by 10.4% compared to a decrease of 23% in the strength of the untreated 30% RAP mixture. Statistical analysis using single-factor ANOVA showed that integrating RAP aggregates with or without the presence of TiO2 particles would significantly affect the concrete properties in terms of their population means. The t-test analysis, on the other hand, proved sufficient evidence that the mean values of the 30% RAP mixture treated with TiO2 would not differ significantly from the control in terms of its slump and water absorption properties. The chemical structure analysis revealed an increase in the Si-O-Si and Si-O functional groups when using TiO2 in RAP mixtures, suggesting improved hydration activity and accelerated C-S-H formation in the treated RAP mixtures. Moreover, distinct C-H peaks were witnessed in concrete with untreated RAP aggregates, resulting from the aged asphalt coating on the RAP, which weakened the bond between the RAP and the cementitious matrix. Full article
36 pages, 658 KB  
Article
Determinants of the Shadow Economy—Implications for Fiscal Sustainability and Sustainable Development in the EU
by Grzegorz Przekota, Anna Kowal-Pawul and Anna Szczepańska-Przekota
Sustainability 2025, 17(20), 9033; https://doi.org/10.3390/su17209033 (registering DOI) - 12 Oct 2025
Abstract
The shadow economy weakens fiscal sustainability, hampers the financing of public goods, and impedes the achievement of sustainable development goals. The informal sector remains a persistent challenge for policymakers, as it distorts competition, reduces transparency, and undermines the effectiveness of economic and fiscal [...] Read more.
The shadow economy weakens fiscal sustainability, hampers the financing of public goods, and impedes the achievement of sustainable development goals. The informal sector remains a persistent challenge for policymakers, as it distorts competition, reduces transparency, and undermines the effectiveness of economic and fiscal policies. The aim of this article is to identify the key factors determining the size of the shadow economy in European Union countries and to provide policy-relevant insights. The analysis covers data on the share of the informal economy in GDP and macroeconomic variables such as GDP per capita, consumer price index, average wages, household consumption, government expenditure, and unemployment, as well as indicators of digital development in society and the economy (DESI, IDT), the share of cashless transactions in GDP, and information on the implementation of digital tax administration tools and restrictions on cash payments. Five hypotheses (H1–H5) are formulated concerning the effects of income growth, labour market conditions, digitalisation, cashless payments, and tax administration tools on the shadow economy. The research question addresses which factors—macroeconomic conditions, economic and social digitalisation, payment structures, and fiscal innovations in tax administration—play the most significant role in determining the size of the shadow economy in EU countries and whether these mechanisms have broader implications for fiscal sustainability and sustainable development. The empirical strategy is based on multilevel models with countries as clusters, complemented by correlation and comparative analyses. The results indicate that the most significant factor in limiting the size of the shadow economy is the level of GDP per capita and its growth, whereas the impact of card payments appears to be superficial, reflecting overall increases in wealth. Higher wages, household consumption, and digital development as measured by the DESI also play an important role. The implementation of digital solutions in tax administration, such as SAF-T or e-PIT/pre-filled forms, along with restrictions on cash transactions, can serve as complementary measures. The findings suggest that sustainable strategies to reduce the shadow economy should combine long-term economic growth with digitalisation and improved tax administration, which may additionally foster the harmonisation of economic systems and support sustainable development. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
23 pages, 5840 KB  
Article
An Improved Method for Disassembly Depth Optimization of End-of-Life Smartphones Based on PSO-BP Neural Network Predictive Model
by Shengqiang Jiao, Lin Li, Fengfu Yin and Yang Yu
Sustainability 2025, 17(20), 9032; https://doi.org/10.3390/su17209032 (registering DOI) - 12 Oct 2025
Abstract
Disassembly is a crucial step in the remanufacturing of end-of-life (EoL) electronic products. Disassembly depth refers to the disassembly stop point determined by the disassembly sequence. For the disassembly depth optimization of EoL electronic products, a feasibility model with a fast convergence and [...] Read more.
Disassembly is a crucial step in the remanufacturing of end-of-life (EoL) electronic products. Disassembly depth refers to the disassembly stop point determined by the disassembly sequence. For the disassembly depth optimization of EoL electronic products, a feasibility model with a fast convergence and low mean squared error (MSE) is needed to improve optimization accuracy. However, the use of a backpropagation neural network (BPNN) model or mathematical model often results in a slow convergence and high MSE due to the randomness of the initial weights and biases. In this study, an improved method for the disassembly depth optimization of smartphones based on a Particle Swarm Optimization-BPNN (PSO-BPNN) predictive model is proposed. Compared with the traditional BPNN optimization method, the proposed method in this study is that the BPNN predictive model is optimized by using PSO, which shows a superior predictive performance and reduces the MSE. The case of ‘Huawei P7’ is used to verify the feasibility of the method. The results show that the method maintains disassembly profit while reducing the disassembly time and carbon emissions by 17.1% and 7.8%, respectively. Compared with the BPNN model, the PSO-BPNN model converges 18.6%, 32.8%, and 16.6% faster in predicting the disassembly time, profit, and carbon emissions, respectively, with MSE reductions of 92.95%, 96.51%, and 92.74%, respectively. Full article
►▼ Show Figures

Figure 1

15 pages, 2329 KB  
Article
Performance of Electrocoagulation Process with Copper Electrodes for Tannery Wastewater Treatment
by Radwa Hanafy, Nouran Y. Mohamed, Khaled Zaher, Md. Shahinoor Islam and Safwat M. Safwat
Sustainability 2025, 17(20), 9031; https://doi.org/10.3390/su17209031 (registering DOI) - 12 Oct 2025
Abstract
The effluents from the tanning industry pose challenges due to the complex and difficult-to-manage wastewater generation process. Usually, the main issue in tannery wastewater is the high levels of chemical oxygen demand (COD), chlorides (Cl), and chromium (Cr), which have a negative impact [...] Read more.
The effluents from the tanning industry pose challenges due to the complex and difficult-to-manage wastewater generation process. Usually, the main issue in tannery wastewater is the high levels of chemical oxygen demand (COD), chlorides (Cl), and chromium (Cr), which have a negative impact on human health and the environment. Since the conventional biological treatment methods are not effective for treating tannery wastewater, the main aim of this study was to assess the performance of the electrocoagulation process (EC) in treating tannery wastewater by copper electrodes. The study was conducted through an investigation of stirring speeds (low (60 rpm), medium (780 rpm), high (1500 rpm)), current densities (4, 8, 12, and 16 mA/cm2), and reactor volume capacities (0.5, 1, 1.5 L) over an examination period of 60 min. The EC process has proven its high efficiency in removing pollutants. The results showed the best removal efficiencies, where the removal rates of COD, Cl, and Cr reached 92.3%, 96.5%, and more than 99%, respectively, at the following optimum parameters: stirring speed of 60 rpm, current density of 4 mA/cm2, and reactor volume of 1 L. Corrosion of the Cu electrodes was observed via scanning electron microscope (SEM) imagery, and the generated sludge was analyzed via Fourier transform infrared (FTIR) spectroscopy. Full article
(This article belongs to the Special Issue Sustainable Future Prospects of Wastewater Recovery)
►▼ Show Figures

Figure 1

20 pages, 1463 KB  
Article
Europe 2020 Strategy and 20/20/20 Targets: An Ex Post Assessment Across EU Member States
by Norbert Życzyński, Bożena Sowa, Tadeusz Olejarz, Alina Walenia, Wiesław Lewicki and Krzysztof Gurba
Sustainability 2025, 17(20), 9030; https://doi.org/10.3390/su17209030 (registering DOI) - 12 Oct 2025
Abstract
The 2020 Europe Strategy was designed as a comprehensive framework to promote smart, sustainable and inclusive growth in the European Union (EU), particularly emphasising the ‘20/20/20’ targets related to climate protection and energy policy. This study provides an ex post evaluation of the [...] Read more.
The 2020 Europe Strategy was designed as a comprehensive framework to promote smart, sustainable and inclusive growth in the European Union (EU), particularly emphasising the ‘20/20/20’ targets related to climate protection and energy policy. This study provides an ex post evaluation of the extent to which the strategy’s objectives were achieved in the member states of the EU in the period 2010–2020. The analysis is based on Eurostat data and uses Hellwig’s multidimensional comparative analysis to construct a synthetic indicator of progress. The results show that EU countries have made significant advances in reducing greenhouse gas emissions and increasing the share of renewable energy in gross final energy consumption, with Sweden and Finland identified as leaders, while Malta and Hungary lagged behind. Primary energy consumption overall decreased, although only a minority of the member states reached the planned thresholds. Progress was less evident in research and development (R&D) expenditure, where the average value of the EU remained below the 3% GDP target, and strong disparities persisted between innovation leaders and weaker performers. Improvements in higher education attainment were observed, contributing to the long-term goal of a knowledge-based economy, although labour market difficulties, especially among young people, remained unresolved. The findings suggest that, although the Strategy contributed to tangible progress in several areas, uneven achievements among member states limited its overall effectiveness. The study is limited by the reliance on aggregate statistical data and a single methodological approach. Future research should extend the analysis to longer time horizons, include qualitative assessments of national policies, and address implications for the implementation of the European Green Deal and subsequent EU development strategies. Full article
40 pages, 4045 KB  
Article
The Dilemma of the Sustainable Development of Agricultural Product Brands and the Construction of Trust: An Empirical Study Based on Consumer Psychological Mechanisms
by Xinwei Liu, Xiaoyang Qiao, Yongwei Chen and Maowei Chen
Sustainability 2025, 17(20), 9029; https://doi.org/10.3390/su17209029 (registering DOI) - 12 Oct 2025
Abstract
In the context of China’s increasingly competitive agricultural product branding, authenticity has become a pivotal mechanism for shaping consumer trust and willingness to pay. This study takes Perceived Brand Authenticity (PBA) as its focal construct and builds a chained mediation framework incorporating experiential [...] Read more.
In the context of China’s increasingly competitive agricultural product branding, authenticity has become a pivotal mechanism for shaping consumer trust and willingness to pay. This study takes Perceived Brand Authenticity (PBA) as its focal construct and builds a chained mediation framework incorporating experiential quality (EQ) and consumer trust. Employing a dual-evidence strategy that combines structural discovery and causal validation, the study integrates Jaccard similarity clustering and PLS-SEM to examine both behavioral patterns and psychological mechanisms. Drawing on 636 valid survey responses from across China, the results reveal clear segmentation in channel choice, certification concern, and premium acceptance by gender, age, income, and education. Younger and highly educated consumers rely more on e-commerce and digital traceability, while middle-aged, older, and higher-income groups emphasize geographical indications and organic certification. The empirical analysis confirms that PBA has a significant positive effect on EQ and consumer trust, and that the chained mediation pathway “PBA → EQ → Trust → Purchase Intention” robustly captures the transmission mechanism of authenticity. The findings demonstrate that verifiable and consistent authenticity signals not only shape cross-group consumption structures but also strengthen trust and repurchase intentions through enhanced experiential quality. The core contribution of this study lies in advancing an evidence-based framework for sustainable agricultural branding. Theoretically, it reconceptualizes authenticity as a measurable governance mechanism rather than a rhetorical construct. Methodologically, it introduces a dual-evidence approach integrating Jaccard clustering and PLS-SEM to bridge structural and causal analyses. Practically, it proposes two governance tools—“evidence density” and “experiential variance”—which translate authenticity into actionable levers for precision marketing, trust management, and policy regulation. Together, these insights offer a replicable model for authenticity governance and consumer trust building in sustainable agri-food systems. Full article
(This article belongs to the Special Issue Current Challenges in Sustainable Urban, Rural and Regional Development)
27 pages, 922 KB  
Article
The Manufacturers’ Adoption of Green Manufacturing Under the Government’s Green Subsidy
by Wu Chen, Fei Ye and Yao Qiu
Sustainability 2025, 17(20), 9028; https://doi.org/10.3390/su17209028 (registering DOI) - 12 Oct 2025
Abstract
As environmental degradation intensifies, governments increasingly subsidize green manufacturing to promote sustainability. This study develops a game-theoretic model of two competing supply chains, comprising original equipment manufacturers (OEMs) and both traditional and green contract manufacturers (CMs), to investigate the impacts of subsidies on [...] Read more.
As environmental degradation intensifies, governments increasingly subsidize green manufacturing to promote sustainability. This study develops a game-theoretic model of two competing supply chains, comprising original equipment manufacturers (OEMs) and both traditional and green contract manufacturers (CMs), to investigate the impacts of subsidies on green manufacturing adoption. Specifically, we construct a four-stage dynamic game model to examine the interactions among OEMs, CMs, and the government. The main findings are as follows: First, the government subsidy affects OEMs’ adoption decisions only if the production cost of green manufacturing or competition intensity is sufficiently high or if the market sensitivity to green products is relatively low. Second, the optimal subsidy level depends jointly on the production cost of green manufacturing, competition intensity, and market greenness sensitivity: when the production cost of green manufacturing is low (high), the subsidy should rise (fall) with market greenness sensitivity but fall (rise) with competition intensity. Third, while intensified competition reduces OEMs’ profits and overall supply chain performance, its impact on CMs and consumers depends on the production cost of green manufacturing; in contrast, greater consumer sensitivity to green products yields an all–win outcome for all stakeholders. These results yield important managerial implications. For policymakers, when the production costs of green manufacturing are relatively low, green subsidies should be scaled back as market competition intensifies. For manufacturers, it is critical to carefully evaluate the production costs of green manufacturing and the level of government subsidies and to strategically pursue first-mover advantages in advancing sustainable operations, thereby fostering an all-win outcome for stakeholders. Full article
(This article belongs to the Special Issue Sustainable Manufacturing Systems in the Context of Industry 4.0)
24 pages, 14492 KB  
Article
Inhibition Mechanism of Calcium Hydroxide on Arsenic Volatilization During Sintering of Contaminated Excavated Soils
by Xu Li, Yu Jin, Yaocheng Wang, Zhijun Dong and Weipeng Feng
Sustainability 2025, 17(20), 9027; https://doi.org/10.3390/su17209027 (registering DOI) - 12 Oct 2025
Abstract
Urbanization generates large quantities of arsenic-contaminated excavated soils that pose environmental risks due to arsenic volatilization during high-temperature sintering processes. While these soils have potential for recycling into construction materials, their reuse is hindered by arsenic release. This study demonstrated calcium hydroxide (Ca(OH) [...] Read more.
Urbanization generates large quantities of arsenic-contaminated excavated soils that pose environmental risks due to arsenic volatilization during high-temperature sintering processes. While these soils have potential for recycling into construction materials, their reuse is hindered by arsenic release. This study demonstrated calcium hydroxide (Ca(OH)2) as a highly effective additive for suppressing arsenic volatilization during soil sintering, while simultaneously improving material properties. Through comprehensive characterization using inductively coupled plasma-mass spectrometry (ICP-MS), scanning electron microscopy (SEM) and X-ray microtomography (μCT), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS), results demonstrated that Ca(OH)2 addition (0.5–2 wt.%) reduces arsenic volatilization by 57% through formation of thermally stable calcium arsenate (Ca3(AsO4)2). Ca(OH)2 acted via two mechanisms: (a) chemical immobilization through Ca-As-O compound formation, (b) physical encapsulation in a calcium-aluminosilicate matrix during liquid-phase sintering, and (c) pH buffering that maintains arsenic in less volatile forms. Optimal performance was achieved at 0.5% Ca(OH)2, yielding 9.14 MPa compressive strength (29% increase) with minimal arsenic leaching (<110 ppb). Microstructural analysis showed Ca(OH)2 promoted densification while higher doses increased porosity. This work provides a practical solution for safe reuse of arsenic-contaminated soils, addressing both environmental concerns and material performance requirements for construction applications. Full article
►▼ Show Figures

Figure 1

25 pages, 1442 KB  
Article
Promoting Sustainable Life Through Global Citizenship-Oriented Educational Approaches: Comparison of Learn–Think–Act Approach-Based and Lecture-Based SDG Instructions on the Development of Students’ Sustainability Consciousness
by Aslı Koçulu
Sustainability 2025, 17(20), 9026; https://doi.org/10.3390/su17209026 (registering DOI) - 12 Oct 2025
Abstract
Promoting individuals’ sustainability consciousness (SC) is one of the important way of ensuring a sustainable world and finding ways toward a better life. Therefore, the purpose of the present study was to compare the effects of learn–think–act approach-based instruction and lecture-based instruction on [...] Read more.
Promoting individuals’ sustainability consciousness (SC) is one of the important way of ensuring a sustainable world and finding ways toward a better life. Therefore, the purpose of the present study was to compare the effects of learn–think–act approach-based instruction and lecture-based instruction on the development of sustainability consciousness in students, with the Sustainable Development Goals (SDGs) acting as the subject of the instructions. The research was conducted with 80 seventh-grade students from a state school in Istanbul, Türkiye. While 40 of them were in a class where learn–think–act approach-based SDG instruction was implemented, the other 40 participants were trained with lecture-based SDG instruction for eight weeks. A quasi-experimental research design was followed in the research. The data was collected with the Sustainability Consciousness Questionnaire and obtained before and after SDG instruction. In the data analysis, paired and independent samples t-tests were used. The findings revealed that learn–think–act approach-based SDG instruction has a significantly larger effect (d = 1.62, 95% CI) on the development of sustainability consciousness in middle school students compared to lecture-based SDG instruction. Full article
(This article belongs to the Collection Sustainable Citizenship and Education)
►▼ Show Figures

Figure 1

23 pages, 1310 KB  
Article
Thematic Coherence in Mission-Oriented EU Energy Policy: A Network-Based Analysis of Horizon Europe’s Sustainability Funding Calls
by César Palmero, Nieves Arranz and Marta F. Arroyabe
Sustainability 2025, 17(20), 9025; https://doi.org/10.3390/su17209025 (registering DOI) - 12 Oct 2025
Abstract
While Horizon Europe is expected to turn the European Union’s Mission-Oriented Innovation Policy (MOIP) into concrete actions, little is known about how coherently its funding calls translate high-level ambitions into effective guidance. To address this, we move beyond the traditional focus on funded [...] Read more.
While Horizon Europe is expected to turn the European Union’s Mission-Oriented Innovation Policy (MOIP) into concrete actions, little is known about how coherently its funding calls translate high-level ambitions into effective guidance. To address this, we move beyond the traditional focus on funded projects and offer the first systematic analysis of Horizon Europe call texts as cognitive artefacts of policy design. Using Textual Network Analysis (TNA) on 188 calls of Cluster 5 (“Climate, Energy and Mobility”) in the 2021–2022 Work Programme, we compare Scope and Expected Outcomes texts. We constructed weighted co-occurrence networks and calculated centrality, community structure, and assortativity metrics. Results reveal clear differences between layers: Scope texts show stronger clustering of technical domains (modularity 0.54, assortativity +0.206), while Outcomes present weaker clustering (modularity 0.50, assortativity −0.035), reflecting convergence around high-level impacts. Across both layers, a small set of hubs (“renewable energy”, “climate change”, “emissions”) dominates, with high-betweenness terms bridging siloed domains; peripheral concepts remain weakly linked. The study contributes a novel framework for analysing the architecture of funding calls and demonstrates the utility of centrality metrics for policymakers to identify conceptual gaps and guide future Work Programme design, as well as for applicants optimising their proposal writing. Full article
►▼ Show Figures

Figure 1

23 pages, 2205 KB  
Article
Evidence of Agroecological Performance in Production Systems Integrating Agroecology and Bioeconomy Actions Using TAPE in the Colombian Andean–Amazon Transition Zone
by Yerson D. Suárez-Córdoba, Jaime A. Barrera-García, Armando Sterling, Carlos H. Rodríguez-León and Pablo A. Tittonell
Sustainability 2025, 17(20), 9024; https://doi.org/10.3390/su17209024 (registering DOI) - 12 Oct 2025
Abstract
The expansion of conventional agricultural models in the Colombian Amazon has caused deforestation, biodiversity loss, and socio-environmental degradation. In response, agroecology and bioeconomy are emerging as key strategies to regenerate landscapes and foster sustainable production systems. We evaluated the agroecological performance of 25 [...] Read more.
The expansion of conventional agricultural models in the Colombian Amazon has caused deforestation, biodiversity loss, and socio-environmental degradation. In response, agroecology and bioeconomy are emerging as key strategies to regenerate landscapes and foster sustainable production systems. We evaluated the agroecological performance of 25 farms in the Andean–Amazon transition zone of Colombia using FAO’s Tool for Agroecology Performance Evaluation (TAPE). The analysis included land cover dynamics (2002–2024), characterization of the agroecological transition based on the 10 Elements of Agroecology, and 23 economic, environmental, and social indicators. Four farm typologies were identified; among them, Mixed Family Farms (MFF) achieved the highest transition score (CAET = 60.5%) and excelled in crop diversity (64%), soil health (SHI = 4.24), productive autonomy (VA/GVP = 0.69), and household empowerment (FMEF= 85%). Correlation analyses showed strong links between agroecological practices, economic efficiency, and social cohesion. Land cover dynamics revealed a continuous decline in forest cover (12.9% in 2002 to 7.1% in 2024) and an increase in secondary vegetation, underscoring the urgent need for restorative approaches. Overall, farms further along the agroecological transition were more productive, autonomous, and socially cohesive, strengthening territorial resilience. The application of TAPE proved robust multidimensional evidence to support agroecological monitoring and decision-making, with direct implications for land use planning, rural development strategies, and sustainability policies in the Amazon. At the same time, its sensitivity to high baseline biodiversity and to the complex socio-ecological dynamics of the Colombian Amazon underscores the need to refine the methodology in future applications. By addressing these challenges, the study contributes to the broader international debate on agroecological transitions, offering insights relevant for other tropical frontiers and biodiversity-rich regions facing similar pressures. Full article
►▼ Show Figures

Figure 1

15 pages, 576 KB  
Article
Building Resilient and Sustainable Supply Chains: A Distributed Ledger-Based Learning Feedback Loop
by Tan Gürpinar and Mehmet Akif Gulum
Sustainability 2025, 17(20), 9023; https://doi.org/10.3390/su17209023 (registering DOI) - 12 Oct 2025
Abstract
Global supply chains face increasing disruptions from cyber threats, geopolitical instability, extreme weather events, and a range of economic, social, and environmental sustainability challenges. As these disruptions intensify, enhancing Supply Chain Resilience (SCR) has become a strategic priority. This study investigates how Distributed [...] Read more.
Global supply chains face increasing disruptions from cyber threats, geopolitical instability, extreme weather events, and a range of economic, social, and environmental sustainability challenges. As these disruptions intensify, enhancing Supply Chain Resilience (SCR) has become a strategic priority. This study investigates how Distributed Ledger Technology (DLT) can contribute to SCR by mitigating vulnerabilities and strengthening key capabilities within global supply chains. A qualitative research approach is employed, utilizing expert evaluations to examine DLT’s impact on supply chain vulnerabilities and capabilities. Five workshops were conducted with 25 industry professionals from logistics, IT, procurement, and risk management. Experts examined how DLT could address disruptions stemming from supplier instability, poor traceability, and regulatory and environmental pressures, while highlighting its potential to drive ethical sourcing and environmentally responsible practices. The structured discussions were guided by theoretical frameworks and expert evaluations were synthesized into two analytical matrices illustrating DLT’s influence on SCR. The findings reveal that the contribution of DLT to SCR and sustainability is highly context-dependent, with its effectiveness hinging on how it is embedded within governance structures and aligned with the interplay of complementary technologies. Building on these insights, the study presents the DLT-LFL (Distributed Ledger Technology–Learning Feedback Loop) framework, which integrates sensing, decision-making, adaptation, and predictive learning from distributed operational data, allowing supply chains to better anticipate disruptions, adjust processes dynamically, and continuously strengthen resilience and sustainable practices. The study also develops a practical checklist to assess how effective DLT applications and their integration with predictive and AI-driven analytics reduce vulnerabilities, strengthen capabilities, mitigate risks, and support adaptive decision-making. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
►▼ Show Figures

Figure 1

14 pages, 420 KB  
Article
Does Policy Synergy Improve Ecological Resilience? Evidence from Smart City and Low-Carbon Pilots in China
by Xiandong Yang and Kemei Yu
Sustainability 2025, 17(20), 9022; https://doi.org/10.3390/su17209022 (registering DOI) - 11 Oct 2025
Abstract
Pilot policies are key determinants of urban ecological resilience, while the corresponding results are inconsistent. Moreover, existing research on the synergistic effects of policies on ecological resilience remains insufficient. Thus, this study selects low-carbon pilot policies and smart city pilot policies to explore [...] Read more.
Pilot policies are key determinants of urban ecological resilience, while the corresponding results are inconsistent. Moreover, existing research on the synergistic effects of policies on ecological resilience remains insufficient. Thus, this study selects low-carbon pilot policies and smart city pilot policies to explore the possible channels through which they affect ecological resilience. Consequently, using the sample data of China’s prefecture-level cities during the period of 2005–2022, we employ a multi-period difference-in-differences approach and two-step regression to examine the relationship between dual pilot policies and ecological resilience. We find that dual pilot policies have a significant positive impact on ecological resilience, and the conclusion is still held after a series of robustness tests. We also find that regional and population size heterogeneity effects exist. Furthermore, the sequences of pilots significantly influence ecological resilience, where the sequence of implementing low-carbon pilot programs earlier than smart city pilot programs has a greater impact on ecological resilience. Finally, the dual pilot policies enhance ecological resilience through channels of technological innovation and industrial structure upgrading. Overall, this study reveals the relationship between policies and ecological resilience, providing policy insights for building resilient cities. Full article
19 pages, 3779 KB  
Article
Spatial–Temporal Patterns of Methane Emissions from Livestock in Xinjiang During 2000–2020
by Qixiao Xu, Yumeng Li, Yongfa You, Lei Zhang, Haoyu Zhang, Zeyu Zhang, Yuanzhi Yao and Ye Huang
Sustainability 2025, 17(20), 9021; https://doi.org/10.3390/su17209021 (registering DOI) - 11 Oct 2025
Abstract
Livestock represent a significant source of methane (CH4) emissions, particularly in pastoral regions. However, in Xinjiang—a pivotal pastoral region of China—the spatiotemporal patterns of livestock CH4 emissions remain poorly characterized, constraining regional mitigation actions. Here, a detailed CH4 emissions [...] Read more.
Livestock represent a significant source of methane (CH4) emissions, particularly in pastoral regions. However, in Xinjiang—a pivotal pastoral region of China—the spatiotemporal patterns of livestock CH4 emissions remain poorly characterized, constraining regional mitigation actions. Here, a detailed CH4 emissions inventory for livestock in Xinjiang spanning the period 2000–2020 is compiled. Eight livestock categories were covered, gridded livestock maps were developed, and the dynamic emission factors were built by using the IPCC 2019 Tier 2 approaches. Results indicate that the CH4 emissions increased from ~0.7 Tg in 2000 to ~0.9 Tg in 2020, a 28.5% increase over the past twenty years. Beef cattle contributed the most to the emission increase (59.6% of total increase), followed by dairy cattle (35.7%), sheep (13.9%), and pigs (4.3%). High-emission hotspots were consistently located in the Ili River Valley, Bortala, and the northwestern margins of the Tarim Basin. Temporal trend analysis revealed increasing emission intensities in these regions, reflecting the influence of policy shifts, rangeland dynamics, and evolving livestock production systems. The high-resolution map of CH4 emissions from livestock and their temporal trends provides key insights into CH4 mitigation, with enteric fermentation showing greater potential for emission reduction. This study offers the first long-term, high-resolution CH4 emission inventory for Xinjiang, providing essential spatial insights to inform targeted mitigation strategies and enhance sustainable livestock management in arid and semi-arid ecosystems. Full article
(This article belongs to the Special Issue Geographical Information System for Sustainable Ecology)
19 pages, 4789 KB  
Article
Sustainable and Trustworthy Digital Health: Privacy-Preserving, Verifiable IoT Monitoring Aligned with SDGs
by Linshen Yang, Xinyan Wang and Yingjun Jiao
Sustainability 2025, 17(20), 9020; https://doi.org/10.3390/su17209020 (registering DOI) - 11 Oct 2025
Abstract
The integration of Internet of Things (IoT) technologies into public healthcare enables continuous monitoring and sustainable health management. However, conventional frameworks often depend on transmitting and storing raw personal data on centralized servers, posing challenges related to privacy, security, ethical compliance, and long-term [...] Read more.
The integration of Internet of Things (IoT) technologies into public healthcare enables continuous monitoring and sustainable health management. However, conventional frameworks often depend on transmitting and storing raw personal data on centralized servers, posing challenges related to privacy, security, ethical compliance, and long-term sustainability. This study proposes a privacy-preserving framework that avoids the exposure of true health-related data. Sensor nodes encrypt collected measurements and collaborate with a secure computation core to evaluate health indicators under homomorphic encryption, maintaining confidentiality. For example, the system can determine whether a patient’s heart rate within a monitoring window falls inside clinically recommended thresholds, while the framework remains general enough to support a wide range of encrypted computations. A compliance verification client generates zero-knowledge range proofs, allowing external parties to verify whether health indicators meet predefined conditions without accessing actual values. Simulation results confirm the correctness of encrypted computation, controllability of threshold-based compliance judgments, and resistance to inference attacks. The proposed framework provides a practical solution for secure, auditable, and sustainable real-time health assessment in IoT-enabled public healthcare systems. Full article
(This article belongs to the Special Issue Interdisciplinary Explorations in Health and Healthcare: Addressing Complex Challenges for Sustainable Futures)
►▼ Show Figures

Figure 1

23 pages, 1275 KB  
Article
Roles, Risks and Responsibility: Foundations of Pro-Environmental Culture in Everyday Choices
by Olena Pavlova, Oksana Liashenko, Olena Mykhailovska, Kostiantyn Pavlov, Krzysztof Posłuszny and Antoni Korcyl
Sustainability 2025, 17(20), 9019; https://doi.org/10.3390/su17209019 (registering DOI) - 11 Oct 2025
Abstract
This study explores how contextual framings influence sustainable decision-making in everyday situations. Building on the literature about the intention–behaviour gap, we examine the combined effect of role activation and environmental risk on pro-environmental preferences. A scenario-based behavioural experiment, conducted via oTree, integrated within-subject [...] Read more.
This study explores how contextual framings influence sustainable decision-making in everyday situations. Building on the literature about the intention–behaviour gap, we examine the combined effect of role activation and environmental risk on pro-environmental preferences. A scenario-based behavioural experiment, conducted via oTree, integrated within-subject role framing (citizen, consumer, neutral) with randomised environmental risk conditions. Participants completed repeated binary choice tasks, where Eco-Preference was defined as the frequency with which they chose the sustainable option. The results indicate that activating a citizen role significantly increased Eco-Preference compared to consumer or neutral framings, while high-risk contexts did not directly boost sustainable behaviour. Instead, risk cues had an indirect effect through motivational states, highlighting the mediating role of Eco-Preference. Theoretically, this study advances Eco-Preference as a latent behavioural construct linking identity-based theories of responsibility with decision-based models of sustainability. Practically, the findings underscore the potential of role-based communication strategies to enhance ecological responsibility, suggesting that both policy and organisational interventions can benefit from fostering civic identities. Ultimately, the framework is applicable across cultures by offering a behavioural measure less prone to survey bias, supporting future comparative research on environmental decision-making. Full article
(This article belongs to the Special Issue Quality of Life in the Context of Sustainable Development)
13 pages, 451 KB  
Article
Environmental Sustainability in the Post-Soviet Republics: Cross-Country Evidence from a Composite Index
by Tommaso Filì, Enrico Ivaldi, Enrico Musso and Tiziano Pavanini
Sustainability 2025, 17(20), 9018; https://doi.org/10.3390/su17209018 (registering DOI) - 11 Oct 2025
Abstract
This study investigates the environmental dimension of sustainable development across fifteen post-Soviet republics in 2022. While sustainability is generally understood as a triadic construct—economic, social, and environmental—this paper isolates the ecological pillar to highlight cross-country differences shaped by industrial legacies, institutional capacity, and [...] Read more.
This study investigates the environmental dimension of sustainable development across fifteen post-Soviet republics in 2022. While sustainability is generally understood as a triadic construct—economic, social, and environmental—this paper isolates the ecological pillar to highlight cross-country differences shaped by industrial legacies, institutional capacity, and governance models. A composite Environmental Performance Index (EPI) is developed using the Mazziotta–Pareto Index (MPI), which captures both average performance and internal consistency across three SDG-related domains: SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land). The study adds to existing literature as it includes a non-compensatory composite index and cluster analysis, and in policy terms, it provides a benchmarking system for facilitating ecological transition in the post-Soviet context. The results reveal strong divergence across the region: Baltic countries and Moldova achieve higher scores, reflecting policy convergence with the European Union and stronger environmental institutions, while Central Asian republics lag due to resource dependence, water scarcity, and weaker governance. Geographic cluster analysis corroborates these differences, showing clear spatial patterns of environmental convergence and divergence. Correlation analysis further demonstrates that environmental sustainability is positively associated with GDP per capita, HDI, and life expectancy, while negatively linked with inequality and fertility rates. These findings stress the need for context-sensitive and evidence-based policies, intra-regional cooperation, and integrated governance mechanisms to advance ecological transition in line with the 2030 Agenda for Sustainable Development. Full article
►▼ Show Figures

Figure 1

36 pages, 1805 KB  
Article
Expert Credibility Factors and Their Impact on Digital Innovation and Sustainability Adoption in China’s Social Media Ecosystem
by Shasha Li and Chao Gao
Sustainability 2025, 17(20), 9017; https://doi.org/10.3390/su17209017 (registering DOI) - 11 Oct 2025
Abstract
The successful implementation of digital transformation initiatives depends critically on public trust in experts guiding these processes. In today’s digital media environment, expert trust faces significant challenges, potentially hindering sustainable innovation adoption. This study investigates how expert credibility dimensions and information characteristics shape [...] Read more.
The successful implementation of digital transformation initiatives depends critically on public trust in experts guiding these processes. In today’s digital media environment, expert trust faces significant challenges, potentially hindering sustainable innovation adoption. This study investigates how expert credibility dimensions and information characteristics shape trust in digital transformation experts among Chinese social media users. We employed a mixed-methods approach combining a survey of 850 Chinese social media users, a quasi-experiment testing a digital expert verification feature, and secondary data analysis. The study measured multiple dimensions of expert trust while examining relationships with expert cognition factors and media usage variables through regression, mediation, and structural equation modeling. Expert trust in digital transformation exists at moderate levels (M = 6.82/10), with higher trust in digital innovation research (M = 7.12) than specific sustainability recommendations (M = 6.59). Expert authenticity emerged as the strongest predictor of trust (β = 0.27), followed by professional competence (β = 0.21). A “digital exposure paradox” emerged whereby higher volumes of expert information negatively predicted trust (β = −0.18), while information quality positively predicted trust (β = 0.25). The digital verification feature causally enhanced trust (DID = 0.57), with institutional sources strengthening trust while user-generated content diminished it. The findings reveal that digital transformation expert trust involves multi-dimensional evaluations beyond traditional credibility assessments. The “digital exposure paradox” suggests that prioritizing information quality over quantity, demonstrating expert authenticity, and implementing verification mechanisms can enhance trust and accelerate sustainable digital transformation adoption. Full article
(This article belongs to the Special Issue Digital Transformation and Innovation for a Sustainable Future)
23 pages, 5588 KB  
Article
The Divergent Geographies of Urban Amenities: A Data Comparison Between OpenStreetMap and Google Maps
by Federico Mara, Chiara Anselmi, Federica Deri and Valerio Cutini
Sustainability 2025, 17(20), 9016; https://doi.org/10.3390/su17209016 (registering DOI) - 11 Oct 2025
Abstract
Urban models support sustainable, resilient, and equitable planning, but their validity hinges on underlying spatial data. This study examines the epistemological and technical consequences of relying on two dominant yet divergent platforms—OpenStreetMap (OSM) and Google Maps—for extracting proximity-based amenities within the 15-min city [...] Read more.
Urban models support sustainable, resilient, and equitable planning, but their validity hinges on underlying spatial data. This study examines the epistemological and technical consequences of relying on two dominant yet divergent platforms—OpenStreetMap (OSM) and Google Maps—for extracting proximity-based amenities within the 15-min city framework. Across four European contexts—Versilia, Gothenburg, Nice, and Vienna—we compare (i) data completeness and spatial coverage; (ii) semantic categories; and (iii) the effects of data heterogeneity on accessibility modelling. Findings show that OSM, while semantically consistent and openly accessible, systematically underrepresents peripheral amenities, introducing bias towards urban cores in accessibility metrics. Conversely, Google Maps provides broader coverage but is constrained by dependencies on extraction methods, opaque data structures, and ambiguous classification schemes, which hinder reproducibility, reduce interpretability, and limit its analytical robustness. These divergences yield distinct accessibility landscapes and competing readings of functionality and spatial equity. We argue that data source choice and protocol design are epistemological decisions and advocate transparent, hybrid strategies with cross-platform semantic harmonisation to strengthen robustness, equity, and policy relevance. Full article
(This article belongs to the Special Issue Spatial Analysis and Spatial Planning for Sustainability in Urban Areas)
►▼ Show Figures

Figure 1

32 pages, 5864 KB  
Article
Monitoring Temperate Typical Steppe Degradation in Inner Mongolia: Integrating Ecosystem Structure and Function
by Xinru Yan, Dandan Wei, Jinzhong Yang, Weiling Yao and Shufang Tian
Sustainability 2025, 17(20), 9015; https://doi.org/10.3390/su17209015 (registering DOI) - 11 Oct 2025
Abstract
Under the combined effects of climate change, overexploitation, and intense grazing, temperate steppe in northern China is experiencing increasing deterioration, which is typified by a shift from structural degradation to functional disruption. Accurately tracking steppe degradation using remote sensing technology has emerged as [...] Read more.
Under the combined effects of climate change, overexploitation, and intense grazing, temperate steppe in northern China is experiencing increasing deterioration, which is typified by a shift from structural degradation to functional disruption. Accurately tracking steppe degradation using remote sensing technology has emerged as a crucial scientific concern. Prior research failed to integrate ecosystem structure and function and lacked reference baselines, relying only on individual indicators to quantify degradation. To resolve these gaps, this study established a novel degradation evaluation index system integrating ecosystem structure and function, incorporating vegetation community distribution and proportions of degradation-indicator species to define reference states and quantify degradation severity. Analyzed spatiotemporal evolution and drivers across the temperate typical steppe (2013–2022). Key findings reveal (1) non-degraded and slightly degraded areas dominated (75.57% mean coverage), showing an overall fluctuating improvement trend; (2) minimal transitions between degradation levels, with stable conditions prevailing (59.52% unchanged area), indicating progressive degradation reversal; and (3) natural factors predominated as degradation drivers. The integrated structural–functional framework enables more sensitive detection of early degradation signals, thereby informing more effective steppe restoration management. Full article
(This article belongs to the Section Resources and Sustainable Utilization)
►▼ Show Figures

Figure 1

27 pages, 2973 KB  
Review
Innovative Approaches to Mitigating Microplastic Pollution in Effluents and Soils
by Solange Magalhães, Luís Alves, Bruno Medronho, Ida Svanedal, Magnus Norgren and Maria Graça Rasteiro
Sustainability 2025, 17(20), 9014; https://doi.org/10.3390/su17209014 (registering DOI) - 11 Oct 2025
Abstract
Microplastic pollution represents a significant environmental challenge, as microplastics accumulate in effluents and soils, causing serious risks to ecosystems and human health. Efficient removal of these contaminants is essential to mitigate their potential adverse effects. This review summarizes and critically analyses current methods [...] Read more.
Microplastic pollution represents a significant environmental challenge, as microplastics accumulate in effluents and soils, causing serious risks to ecosystems and human health. Efficient removal of these contaminants is essential to mitigate their potential adverse effects. This review summarizes and critically analyses current methods for the removal of microplastics from effluents and soils, focusing on their effectiveness, advantages, and limitations. Conventional techniques—including filtration, flotation, chemical coagulation, flocculation, and adsorption—are discussed in the context of wastewater treatment and soil remediation. Emerging approaches, such as flocculation processes with special focus on the application of bio-based flocculants, are also highlighted as promising solutions. Key challenges in microplastic removal, including the diversity of microplastic types, their small size, and the complexity of environmental matrices, are addressed. This work intends to contribute to the urgent need for further research to develop more efficient and sustainable strategies for microplastic removal from environmental systems. Full article
(This article belongs to the Special Issue Microplastic Research and Environmental Sustainability)
►▼ Show Figures

Figure 1

26 pages, 764 KB  
Article
A Multidimensional Impact Study of Heterogeneous Market-Based Environmental Regulations on Carbon Emissions
by Zizhuo Li, Yiniu Cui and Mengyao Guo
Sustainability 2025, 17(20), 9013; https://doi.org/10.3390/su17209013 (registering DOI) - 11 Oct 2025
Abstract
Within the context of global climate change and China’s commitment to the “Dual Carbon” goals (carbon peak and carbon neutrality), this study proposes a novel taxonomy of market-based environmental regulations, dividing them into investment-driven and tax-based supervisory mechanisms. Using panel data from 30 [...] Read more.
Within the context of global climate change and China’s commitment to the “Dual Carbon” goals (carbon peak and carbon neutrality), this study proposes a novel taxonomy of market-based environmental regulations, dividing them into investment-driven and tax-based supervisory mechanisms. Using panel data from 30 Chinese provinces between 2010 and 2023, we empirically investigate their differential effects on carbon emissions. Results indicate that both regulatory approaches significantly curb carbon emissions, each exhibiting distinct nonlinear patterns: an inverted-U curve for investment-oriented measures and a U-shaped trajectory for tax-oriented policies, implying that excessively stringent tax supervision may lead to a rebound in emissions due to effects such as the “resource curse” and “innovation crowding-out.” Industrial structure transformation functions as a common mediating channel, while green innovation efficiency exerts a distinct moderating influence. Both policy types demonstrate adverse spatial spillover effects, with no support found for the “pollution haven” or “race to the bottom” hypotheses. This study offers new empirical insights into how environmental regulations facilitate green and low-carbon transition through market mechanisms, providing valuable implications for designing ecological policy systems that harmonize emission reduction efficiency with sustainability in China and other emerging economies. Full article
(This article belongs to the Topic Climate Change and Environmental Sustainability, 4th Edition)
►▼ Show Figures

Figure 1

21 pages, 43153 KB  
Article
Surface Temperature Prediction of Grain Piles: VMD-SampEn-vLSTM-E Prediction Method Based on Decomposition and Reconstruction
by Peiru Li, Bangyu Li, Jin Qian and Liang Qi
Sustainability 2025, 17(20), 9012; https://doi.org/10.3390/su17209012 (registering DOI) - 11 Oct 2025
Abstract
The surface temperature of grain piles is sensitive to environmental fluctuations and exhibits nonlinear, multi-scale temporal patterns, making accurate prediction crucial for grain storage risk early warning. This paper proposes a decomposition–reconstruction prediction method integrating Sample Entropy (SampEn), variational mode decomposition (VMD), and [...] Read more.
The surface temperature of grain piles is sensitive to environmental fluctuations and exhibits nonlinear, multi-scale temporal patterns, making accurate prediction crucial for grain storage risk early warning. This paper proposes a decomposition–reconstruction prediction method integrating Sample Entropy (SampEn), variational mode decomposition (VMD), and a variant Long Short-Term Memory network (vLSTM). SampEn determines the optimal decomposition parameters, VMD extracts intrinsic mode functions (IMFs), and vLSTM, with peephole connections and coupled gates, conducts synchronous multi-IMF prediction. To explicitly account for environmental influences, a support vector regression (SVR) model driven by dew point temperature and vapor pressure deficit is employed to estimate the surface temperature variation ΔT. This component enhances the adaptability of the framework to dynamic storage conditions. The environment-derived ΔT is then integrated with the VMD-SampEn-vLSTM output to obtain the final forecast. Experiments on real-granary data from Liaoning, China demonstrate that the proposed method reduces mean absolute error (MAE) and root mean square error (RMSE) by 25% and 14%, respectively, compared with baseline models, thus achieving a significant improvement in prediction performance. This integration of data-driven prediction with environmental adjustment significantly improves forecasting accuracy and robustness. Full article
23 pages, 7574 KB  
Article
30-Year Dynamics of Vegetation Loss in China’s Surface Coal Mines: A Comparative Evaluation of CCDC and LandTrendr Algorithms
by Wanxi Liu, Yaling Xu, Huizhen Xie, Han Zhang, Li Guo, Jun Li and Chengye Zhang
Sustainability 2025, 17(20), 9011; https://doi.org/10.3390/su17209011 (registering DOI) - 11 Oct 2025
Abstract
Large-scale vegetation loss induced by surface coal mining constitutes a critical driver of regional ecological degradation. However, the applicability of existing change detection methodologies based on remote sensing within complex mining areas under diverse climatic conditions remains systematically unverified. To address this gap [...] Read more.
Large-scale vegetation loss induced by surface coal mining constitutes a critical driver of regional ecological degradation. However, the applicability of existing change detection methodologies based on remote sensing within complex mining areas under diverse climatic conditions remains systematically unverified. To address this gap and reveal nationwide disturbance patterns, this study systematically evaluates the performance of two algorithms—Continuous Change Detection and Classification (CCDC) and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr)—in identifying vegetation loss across three major climatic zones of China (the humid, semi-humid, and semi-arid zones). Based on the optimal algorithm, the vegetation loss year and loss magnitude across all of China’s surface coal mining areas from 1990 to 2020 were accurately identified, enabling the reconstruction of the comprehensive, nationwide spatio-temporal pattern of mining-induced vegetation loss over the past 30 years. The results show that: (1) CCDC demonstrated superior stability and significantly higher accuracy (OA = 0.82) than LandTrendr (OA = 0.31) in identifying loss years across all zones. (2) The cumulative vegetation loss area reached 1429.68 km2, with semi-arid zones accounting for 86.76%. Temporal analysis revealed a continuous expansion of the loss area from 2003 to 2013, followed by a distinct inflection point and decline during 2014–2016 attributable to policy-driven regulations. (3) Further analysis revealed significant variations in the average magnitude of loss across different climatic zones, namely semi-arid (0.11), semi-humid (0.21), and humid (0.25). These findings underscore the imperative for region-specific restoration strategies to ensure effective conservation outcomes. This study provides a systematic quantification and analysis of long-term, nationwide evolution patterns and regional differentiation characteristics of vegetation loss induced by surface coal mining in China, offering critical support for sustainable development decision-making in balancing energy development and ecological conservation. Full article
(This article belongs to the Special Issue Application of Remote Sensing and GIS in Environmental Monitoring)
►▼ Show Figures

Figure 1

15 pages, 2964 KB  
Article
Optimizing Amendment Ratios for Sustainable Recovery of Aeolian Sandy Soils in Coal Mining Subsidence Areas: An Orthogonal Experiment on Medicago sativa
by Lijun Hao, Zhenqi Hu, Qi Bian, Xuyang Jiang, Yingjia Cao, Changjiang Li and Ruihao Cui
Sustainability 2025, 17(20), 9010; https://doi.org/10.3390/su17209010 (registering DOI) - 11 Oct 2025
Abstract
Coal mining in the aeolian sandy regions of western China has caused extensive land degradation. Traditional single-component soil amendments have proven inadequate for ecological restoration, underscoring the need for integrated and sustainable strategies to restore soil fertility and vegetation. A pot experiment using [...] Read more.
Coal mining in the aeolian sandy regions of western China has caused extensive land degradation. Traditional single-component soil amendments have proven inadequate for ecological restoration, underscoring the need for integrated and sustainable strategies to restore soil fertility and vegetation. A pot experiment using alfalfa (Medicago sativa L.) evaluated the effects of weathered coal, cow manure, and potassium polyacrylate combined in a three-factor three-level orthogonal design on plant growth, nutrient uptake, and soil properties. Results showed that compared with the control (C0O0P0), amendment treatments significantly increased alfalfa fresh weight (+47.57~107.38%), dry weight (+43.46~104.93%), plant height (+43.46~104.93%), and stem diameter (+12.62~31.52%), along with improved plant phosphorus and potassium concentrations (+15.41~46.65%). Soil fertility was also notably enhanced, with increases in soil organic matter, total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) ranging from 4.25% to 777.78%. In contrast, soil pH and bulk density were significantly reduced. The optimal amendment combination was identified as 10 g·kg−1 weathered coal, 5 g·kg−1 cow manure, and 0.6 g·kg−1 potassium polyacrylate. Structural equation modeling revealed that the amendments promoted plant growth both directly by improving soil conditions and indirectly by enhancing nutrient uptake. However, high doses (30 g·kg−1) of weathered coal may inhibit plant growth, and the co-application of high-dose weathered coal or manure with potassium polyacrylate may lead to antagonistic effects. This study provides fundamental insights into soil–plant interactions and proposes a sustainable amendment strategy for improving aeolian sandy soils, which could support future ecological reclamation efforts in coal mining area. Full article
26 pages, 4838 KB  
Article
Optimizing Spatial Scales for Evaluating High-Resolution CO2 Fossil Fuel Emissions: Multi-Source Data and Machine Learning Approach
by Yujun Fang, Rong Li and Jun Cao
Sustainability 2025, 17(20), 9009; https://doi.org/10.3390/su17209009 (registering DOI) - 11 Oct 2025
Abstract
High-resolution CO2 fossil fuel emission data are critical for developing targeted mitigation policies. As a key approach for estimating spatial distributions of CO2 emissions, top–down methods typically rely upon spatial proxies to disaggregate administrative-level emission to finer spatial scales. However, conventional [...] Read more.
High-resolution CO2 fossil fuel emission data are critical for developing targeted mitigation policies. As a key approach for estimating spatial distributions of CO2 emissions, top–down methods typically rely upon spatial proxies to disaggregate administrative-level emission to finer spatial scales. However, conventional linear regression models may fail to capture complex non-linear relationships between proxies and emissions. Furthermore, methods relying on nighttime light data are mostly inadequate in representing emissions for both industrial and rural zones. To address these limitations, this study developed a multiple proxy framework integrating nighttime light, points of interest (POIs), population, road networks, and impervious surface area data. Seven machine learning algorithms—Extra-Trees, Random Forest, XGBoost, CatBoost, Gradient Boosting Decision Trees, LightGBM, and Support Vector Regression—were comprehensively incorporated to estimate high-resolution CO2 fossil fuel emissions. Comprehensive evaluation revealed that the multiple proxy Extra-Trees model significantly outperformed the single-proxy nighttime light linear regression model at the county scale, achieving R2 = 0.96 (RMSE = 0.52 MtCO2) in cross-validation and R2 = 0.92 (RMSE = 0.54 MtCO2) on the independent test set. Feature importance analysis identified brightness of nighttime light (40.70%) and heavy industrial density (21.11%) as the most critical spatial proxies. The proposed approach also showed strong spatial consistency with the Multi-resolution Emission Inventory for China, exhibiting correlation coefficients of 0.82–0.84. This study demonstrates that integrating local multiple proxy data with machine learning corrects spatial biases inherent in traditional top–down approaches, establishing a transferable framework for high-resolution emissions mapping. Full article
26 pages, 627 KB  
Article
Sustainable Marketing: Can Retailers’ Profit-Motivated Consumer Education Enhance Green R&D and Production?
by Zixi He, Junqiang Zhang and Wei Yan
Sustainability 2025, 17(20), 9008; https://doi.org/10.3390/su17209008 (registering DOI) - 11 Oct 2025
Abstract
Drawing from practices at Walmart, we model a supply chain where the manufacturer conducts product R&D while the retailer distributes products to two distinct consumer segments: green-conscious consumers who translate environmental principles into purchasing decisions, and non-green-conscious consumers who are deterred by perceived [...] Read more.
Drawing from practices at Walmart, we model a supply chain where the manufacturer conducts product R&D while the retailer distributes products to two distinct consumer segments: green-conscious consumers who translate environmental principles into purchasing decisions, and non-green-conscious consumers who are deterred by perceived high costs and information deficits. The retailer engages in green education targeted at non-green-conscious consumers, providing clear product explanations to improve their willingness to pay for sustainable products, though this education is motivated by profit maximization rather than altruistic environmental responsibility. Our analysis reveals that while retailer green education can boost product R&D and adoption under certain conditions, this creates a ‘consumer education paradox’—a situation where green education could further enhance product R&D and adoption, but the retailer forgoes it because doing so does not contribute to profit. This occurs because profit-driven retailers limit education to self-beneficial ranges, creating tension between individual profit maximization and overall environmental performance. We then propose two government subsidy solutions—green product quantity subsidies and product R&D subsidies—to resolve this paradox. Both effectively alleviate the tension, but green innovation subsidies, despite requiring greater government investment, consistently outperform in fostering innovation and adoption, offering superior environmental outcomes. Full article
(This article belongs to the Special Issue Sustainable Marketing and Consumer Management)
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-71
Previous Issue
Back to TopTop