Sustainability doi: 10.3390/su18115479

Authors: Angel Bayron Correa-Guamán Jorge Daniel Inga-Lafebre

Hydropower-dominated electricity systems are increasingly exposed to hydroclimatic variability, making anticipatory streamflow information essential for energy security, operational resilience, and sustainable planning. This study develops a transparent monthly early-warning framework for the Paute River basin, Ecuador, a strategically important hydrological system for national hydropower generation. Using a 42-year series of observed and compiled monthly streamflow records from 1984 to 2025 (n = 504), the framework derives seasonal low-flow thresholds (P20 warning and P10 critical) and fits a Seasonal Autoregressive Integrated Moving Average model to log-transformed flows. The resulting lognormal predictive distribution provides point forecasts, prediction intervals, and probabilities of low-flow events. Predictive skill was assessed through a 2016–2025 rolling-origin validation with 120 one-step-ahead forecasts and benchmarks against Error–Trend–Seasonal Holt–Winters and seasonal naive models. The SARIMA-log specification achieved the best point accuracy (MAE = 38.80 m3/s, RMSE = 47.62 m3/s, sMAPE = 32.63%) and modest but useful probabilistic skill (CRPSS = 0.069; Brier Skill Score = 0.169 for Q < P20 and 0.274 for Q < P10). A threshold-sensitivity analysis showed that the 0.15 and 0.30 alert thresholds represent a deliberate trade-off between early detection and false-alarm reduction. For 2026, August displayed the highest low-flow probability (P(Q < P20) = 0.303), triggering a moderate Hydropower Low-Flow Risk Traffic-Light category. The contribution is not a new forecasting algorithm but an operationally auditable integration of seasonal thresholds, probabilistic forecasting, verification, and risk communication for hydropower energy-security governance in the tropical Andes.

Sustainability doi: 10.3390/su18115478

Authors: Qing Zhang Yuqi Ji Donghui Zhang Aijun Zhu

Dryland sustainability depends on how vegetation productivity and water-use processes respond to climatic variability and human intervention. Focusing on Xinjiang, China, this study assessed eco-hydrological change from 2000 to 2023 using multi-source remote sensing and climatic datasets. We integrated vegetation productivity and water-use efficiency into a composite EcoIndex, combined anomaly-based diagnostics with eco-hydrological synchrony analysis, and used pixel-level random forest attribution to identify dominant climatic and anthropogenic controls. The results show clear regional differentiation. Northern Xinjiang remained primarily climate-driven and maintained relatively stronger vegetation–water coupling, whereas Southern Xinjiang exhibited more pronounced human-induced restructuring, especially in oasis and cultivated areas. Eastern Xinjiang functioned as a transitional zone with weak coupling and high sensitivity to multiple pressures. Across Xinjiang, 63.27% of the area was classified as climate-dominated, 22.41% as human-dominated, and 14.32% as mixed influence. The results indicate that improvements in vegetation condition do not necessarily imply improved eco-hydrological coordination, and that mixed-influence zones may represent early-warning areas of sustainability risk. This study provides a spatial diagnostic framework for supporting sustainable land and water management, regional adaptation planning, and resilience-oriented governance in arid and semi-arid regions.

Sustainability doi: 10.3390/su18115477

Authors: Styliani Konstantinidi Anna Vatsanidou Vasileios Anestis Nikolaos Katsoulas Thomas Bartzanas

Conventional hydroponic systems, although resource-efficient, face significant sustainability challenges due to the discharge of nutrient-rich effluents, resulting in severe environmental pressures. In alignment with the European Union’s “Farm to Fork” strategy, innovative circular economy approaches are required to decouple crop production from environmental degradation. This study evaluates a novel Cascade Hydroponic System (CHS), designed to maximize resource utility by recovering and reusing the drainage from a primary salt-sensitive crop (cucumber) to a secondary, more salt-tolerant cultivation (melon). A comparative Life Cycle Assessment (LCA) is performed in accordance with the Product Environmental Footprint Category Rules (PEFCRs), utilizing primary operational data and direct monitoring of nutrient concentrations in the system’s effluent. The convergence of these elements establishes the novelty of this study. The CHS is benchmarked against a conventional Separated Hydroponic System (SHS) for a functional unit (FU) defined as “the simultaneous production of 1.0 kg of cucumber and 1.0 kg of melon”. The CHS demonstrated lower characterized impacts compared to SHS across all 16 assessed Environmental Footprint categories under the examined pilot-scale conditions. The key findings include reductions of 65.7%, 41.8%, and 30% in Water Use, Climate Change, and Freshwater Eutrophication scores, respectively. Based on the normalization results, the CHS revealed a 58% lower total environmental footprint score compared to SHS. Process contribution analysis indicates that the marked decrease in the environmental burden is associated with the use of fertilizers. While these inputs represent a significant share of the conventional system’s impact scores, their contribution was substantially lower in the CHS. Although based on pilot-scale operational data from a single crop cycle, the results highlight the considerable environmental potential of cascading nutrient reuse configurations, thus enhancing resource use efficiency and mitigating the associated environmental impacts while also contributing novel empirical knowledge to a field that has been limitedly studied.

Sustainability doi: 10.3390/su18115476

Authors: Elisabetta Pigni Daniele Cespi Paola Galletti Pietro Rodolfo Natale Igor Terrarossa Chiara Samorì Serena Righi

Bio-based solvents are often claimed to make the processes in which they are used more sustainable from an environmental point of view; such claims usually come from their bio-based origin or their safety profile, which is sometimes better than that of fossil-based solvents. Herein, we intended to deepen the environmental sustainability of the synthesis of two bio-based esters (γ-valerolactone and ethyl lactate) and two bio-based ethers (2-methyl tetrahydrofuran and cyclopentyl methyl ether) from a life cycle perspective. To this purpose, a Life Cycle Assessment (LCA) was first carried out to compare the environmental impacts of the four bio-based solvent syntheses with those of six fossil-based solvents that they could potentially replace. The assessment was then extended to evaluate the potential benefits of their application in two processes: the extraction of polyethylene from multilayer plastic waste and the extraction of polyhydroxyalkanoates from bacteria. The impacts associated with the synthesis of the four bio-based solvents were substantially higher than those of fossil-based solvents. These higher impacts translate into poorer environmental performance when bio-based solvents were used in the polyethylene extraction processes but not when they were applied to the polyhydroxyalkanoate extraction. These results suggest that the feedstock renewability alone may not be sufficient to improve the sustainability of chemical processes, mainly because of the challenges associated with converting biomass into useful chemicals. Nevertheless, it should be noted that the bio-based routes were largely reconstructed from literature sources and laboratory-scale experiments, while the fossil-based references are based on mature industrial datasets.

Sustainability doi: 10.3390/su18115473

Authors: Chenting Wang Guoping Ding

This study examines the impact of supply chain finance on corporate zero-carbon transition using data from Chinese A-share listed companies from 2008 to 2023. Through text analysis, this study constructs a corporate zero-carbon transition index containing 285 keywords and a supply chain finance indicator based on a specialized dictionary. The results show that supply chain finance significantly promotes corporate zero-carbon transition, and the findings remain robust after a series of robustness and endogeneity tests. Further analysis indicates that the promoting effect is more pronounced among non-heavy-polluting firms, firms located in eastern regions, and firms with relatively weaker bargaining power within supply chains. Mechanism analysis reveals that supply chain finance mainly facilitates zero-carbon transition by alleviating financing constraints, stimulating green technological innovation, and improving green supply chain management practices. It should be noted that the text-based indicators primarily reflect firms’ strategic disclosures and may not fully capture the actual implementation of zero-carbon practices. Overall, this study provides empirical evidence on the green governance role of supply chain finance and offers policy implications for advancing coordinated decarbonization across supply chains.

Sustainability doi: 10.3390/su18115472

Authors: Zhuoran Ma Lingling Wang Xiangting Li Hebin Yun Shang Zhang

As climate governance increasingly shifts toward consumption-side intervention, digital platforms such as the Carbon Generalized System of Preferences have become important tools for promoting low-carbon behavior. However, existing studies have mainly focused on participation and engagement, paying limited attention to users’ advocacy intentions. Drawing on the perceived value perspective and Social Exchange Theory, this study examines how perceived rewards and gameful experiences influence advocacy intentions through perceived benefits and low perceived costs. A three-wave survey of Chinese respondents was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA). The results show that perceived rewards enhance perceived benefits, while gameful experiences increase perceived benefits and reduce users’ actual perceived burden. In turn, perceived benefits and lower perceived costs both promote advocacy intentions. The mediation analysis confirms the important roles of perceived benefits and low perceived costs, while the fsQCA results identify three distinct configurations leading to high advocacy intentions. This study extends CGSP research from participation to advocacy and offers practical implications for designing digital low-carbon platforms.

Sustainability doi: 10.3390/su18115475

Authors: Maksym W. Sitnicki Bożena Iwanowska Yan Kapranov Jurij Klapkiv Oleksandr Dluhopolskyi Valentyna Panasyuk Dmytro Halynskyi

The accelerating energy transition and digital transformation have increased the importance of understanding the drivers of energy-related entrepreneurship and investment across countries. This study aims to investigate how digitalisation and entrepreneurial ecosystem development influence the number and funding of energy-related start-ups, with particular attention to stage-specific effects, lagged dynamics, and non-linear relationships in a cross-country panel setting. The analysis is based on panel data from the European Commission (DESI), the International Energy Agency, and StartupBlink, covering 25 countries (2017–2022) and a global sample (2019–2023), and is estimated using Poisson pseudo-maximum likelihood models with fixed effects, lagged variables, and non-linear specifications in R. The findings show that digitalisation has a limited, selective relationship with energy-related entrepreneurship, whereas entrepreneurial ecosystem development plays a more consistent role. Digital connectivity is associated mainly with improved early-stage funding conditions, whereas broader digitalisation indicators do not systematically explain start-up formation. Stronger entrepreneurial ecosystems are linked to both higher green start-up activity and a shift in investment from early-stage ventures to more mature digital energy firms. The non-linear results further suggest diminishing returns to ecosystem development in later-stage green funding, indicating potential saturation effects in highly developed ecosystems. These findings suggest that policies aimed at accelerating sustainable energy entrepreneurship should go beyond general digitalisation strategies and focus more directly on strengthening inclusive entrepreneurial ecosystems, improving access to finance across the start-up lifecycle, and preventing excessive investment concentration in already mature ventures.

Sustainability doi: 10.3390/su18115474

Authors: Marianne Bügelmayer-Blaschek Barry Evans Romana Berg Kristofer Hasel Albert S. Chen

Compound and consecutive extreme events are increasingly understood as key contributors to climate risk, as their interactions can intensify impacts beyond those produced by individual hazards alone threatening the long-term sustainability of regional infrastructure. Compound coincident events involve multiple climate drivers or hazards that occur simultaneously or in close temporal proximity, exhibiting overlapping spatial and temporal characteristics. For assessing multi-hazards, information on critical thresholds of the events investigated (extreme precipitation and wind gusts in the presented study) is key, as is the time frame needed to determine the probability of event B after an event A. As this data is location-specific, stakeholder integration provides a potential tool for gathering this information to enable socially robust disaster risk management. The presented study displays a potential interdisciplinary approach to how multi-hazards and their occurrence can be investigated locally. Therefore, stakeholder integration is combined with climate model output and a copula-based analysis of compound coincident and consecutive extreme daily wind and precipitation events for the Salzburg region under different climate change scenarios (SSP1-2.6, SSP5-8.5). Through stakeholder integration, relevant thresholds and potential time frames were identified. Our findings indicate that the thresholds critical to the considered assets (properties, transport, energy) are well aligned between different stakeholders; however, the time frame of increased vulnerability due to a previous event differs strongly between them. Compared to the baseline scenarios, the ranges within the climate model used for rainfall and wind speed intensity under SSP1-2.6 and SSP5-8.5 scenarios are examined, and, for rainfall, have expanded to greater values for both compound coincident and consecutive events, highlighting challenges and future research needs for sustainable adaptation and regional policy.

Sustainability doi: 10.3390/su18115471

Authors: João Basso Sílvia Coelho Vera Rodrigues Bruno Augusto Hélder Relvas Daniel Graça Myriam Lopes Ana Isabel Miranda Joana Ferreira

Ambient air pollution remains a major public health concern, contributing to millions of premature deaths worldwide according to the World Health Organization. Regional air quality assessments are commonly performed using chemical-transport models that require substantial computational resources due to their detailed representation of atmospheric processes. This study explores the feasibility of applying the second-generation dispersion model URBAIR® as a computationally efficient alternative for long-term regional air quality simulations. URBAIR® was implemented for three European case studies within the DISTENDER project to simulate particulate matter (PM10) and nitrogen dioxide (NO2) concentrations for 2018 under different spatial and temporal resolutions. Model performance was assessed against background monitoring stations and compared across grid configurations. The results show that the model successfully reproduces annual mean concentration patterns, particularly in urban areas, with R2 values ranging mostly between 0.2–0.6, RMSE between 16–36 µg.m−3, and mean bias from −8 to 5 µg.m−3, indicating overall acceptable statistical performance. Within the specific configurations evaluated in this study, increasing spatial resolution was not consistently associated with improved model performance. However, because spatial resolution covaried with other factors including meteorological temporal resolution, domain characteristics, and monitoring station density, the present analysis does not allow the independent effect of spatial resolution to be isolated. Moreover, a key limitation of the modeling approach is the absence of chemical transformation processes, which may affect the representation of secondary pollutants. Overall, the dispersion-based modeling framework substantially reduces computational demand and input complexity, proving suitable for long-term exposure and climate-related applications when annual average concentrations are the primary objective. In future studies, the modeling approach should be applied to other case studies to consolidate the findings of this exploratory work so that it may contribute to sustainability-oriented decision making by facilitating regional assessments of air quality and potential health impacts related to climate change.

Sustainability doi: 10.3390/su18115470

Authors: Roksana Pawełczyk Patrycja Kabiesz Grażyna Płaza Mohammad Gheibi

This study investigates the impact of selected automation scenarios on occupational safety, ergonomics, and operational performance in a plastic crate production workstation. The research focuses on a specific case from the discrete manufacturing sector and aims to develop an integrated analytical framework combining ergonomic assessment with process simulation for the evaluation of organizational and technological improvements in manual handling operations. This study applies a simulation-based production model developed in the DBR77 discrete-event simulation environment to analyze alternative workstation configurations. The assessment framework integrates Ishikawa analysis for root-cause identification and the RULA and REBA methods for ergonomic risk evaluation. The investigated workstation was characterized by repetitive manual handling activities, awkward working postures, and increased physical workload associated with palletizing and transport operations. Several organizational and technological variants were analyzed, including additional operator support, robot-assisted palletizing, conveyor integration, and automated guided vehicle (AGV) transport. The simulation results indicated that the AGV-supported configuration achieved the shortest cycle time (1270 s per batch of 30 units), whereas the robot-assisted variant resulted in the longest cycle time (1520 s). Ergonomic assessment showed a reduction in RULA scores from 6–7 to 3–4 and REBA scores from 8–10 to 4–5 in the automated scenarios. The contribution of this study lies in the integration of ergonomic risk assessment and discrete-event simulation within a unified evaluation framework for workstation redesign in discrete manufacturing environments. The findings demonstrate how simulation-supported analysis can support decision-making regarding the balance between manual labor and automation under specific operational conditions. Due to the single-case-study design, the results should be interpreted as context-specific and exploratory rather than directly generalizable to all manufacturing systems.

Sustainability doi: 10.3390/su18115467

Authors: Santiago Alonso-del-Viejo Juan José Graña-Magariños Isabel C. Gil-García Ana Fernández-Guillamón

The increasing penetration of variable renewable energy sources requires flexible solutions to ensure system stability and economic efficiency. In this context, this study presents a comprehensive assessment of hybrid plants combining wind farms (WF) and photovoltaic (PV) systems integrated with battery energy storage systems (BESS), using the Casetona project in Spain as a real-world study. Three configurations (PV + WF + BESS, PV + BESS, and WF + BESS) are evaluated based on 2024 operational data combined with simulation tools. Under the assumptions of this study (2024 data, Spanish market), the results indicate that WF generation outperforms PV, mainly due to higher capacity factors and better alignment with high-price periods, while PV output is affected by price cannibalization. Under current Spanish market conditions and at the assumed BESS cost (236 €/kWh), energy arbitrage is not economically viable, yielding negative net present value across all configurations. In contrast, participation in automatic frequency restoration reserve services provides higher revenues under current Spanish market conditions, with the WF + BESS configuration achieving the best performance. From the perspective adopted in this study, the sustainability analysis reveals that the hybrid system enables annual greenhouse gas emissions reductions between 13,695 and 49,195 tCO2,eq, depending on the displaced generation source. Although BESS does not directly reduce emissions, it enhances renewable integration, reduces curtailment, and improves grid flexibility. The results also highlight the importance of regulatory frameworks and market design in determining the economic viability of storage systems. While the quantitative results are specific to the case study and sensitive to regulatory parameters, this study provides a comprehensive and transferable methodology for evaluating hybrid renewable systems with storage, supporting informed decision-making in the transition toward low-carbon and resilient energy systems.

Sustainability doi: 10.3390/su18115469

Authors: Usha Iyer-Raniga Janappriya Jayawardana Akvan Gajanayake

Circular economy (CE) and green building (GB) are playing increasingly prominent roles in operationalising the Sustainable Development Goals (SDGs) within the built environment, including in rapidly urbanising Global South contexts such as India. Although often assumed to be complementary, their integration remains insufficiently examined, particularly in terms of their structural alignment and divergence. This study investigates the synergies and structural divergences between CE and GB through an empirical and analytical approach grounded in the Indian built environment sector. Qualitative data were collected from a multi-stakeholder participatory workshop with built environment practitioners in India and through follow-up interviews and analysed using qualitative content analysis to identify patterns in how these approaches are interpreted and applied in a participatory setting. The findings indicate that GB predominantly engages SDGs through performance-oriented, asset-level interventions, while CE operates through system-level strategies focused on material circulation and value-chain transformation. Although areas of convergence are evident, particularly in relation to SDGs 11 and 12, important structural divergences emerge across three key dimensions: scale, temporality, and underlying mental models. These divergences influence how sustainability interventions are framed and implemented with SDG targets. The alignment of CE and GB requires systemic reforms that incorporate circularity criteria within building rating systems, align CE and GB within unified regulatory and procurement frameworks, and embed systems thinking and life cycle approaches within professional education to translate CE from a conceptual framework into an operational paradigm in the built environment.

Sustainability doi: 10.3390/su18115468

Authors: Diego Oliveira Brandão Julia Arieira J. Marion Adeney Gabriel Sperandeo Camila Duarte Ritter Pedro Aurélio Costa Lima Pequeno Lauro Euclides Soares Barata Carlos Afonso Nobre

Understanding the composition and spatial distribution of Amazonia’s bioindustry enterprises is essential for sustainable development. Based on an analysis of primary and secondary data, we offer a preliminary overview of biodiversity-based biofactories, which transform raw materials derived from Amazonian biodiversity into industrialized products, in Brazilian Amazonia. Of the 187 biofactories we identified, most operate in the food sector (74%), followed by cosmetics (14%) and organic chemicals (9%). Records identified biofactories in 72 of the study area’s 559 municipalities. Fifty percent of biofactories are in the municipalities of Manaus, Belém, Castanhal, Santarém, Benevides, and Igarapé-Miri, which together hold 18% of the study area’s population. Conversely, none were identified in the consulted sources for 487 municipalities, comprising 62% of the study area’s population—about 14 million people. Statistical modeling among municipalities with identified units revealed a positive association between municipal gross domestic product and biofactory abundance. While some units may be undetected because they operate outside formal networks, the available records suggest that these businesses are geographically unevenly distributed and mostly of low technological intensity. Moreover, a significant portion of the population may lack direct access to local industrial infrastructure for processing biodiversity resources, highlighting potential territorial inequalities in regional processing capacity.

Sustainability doi: 10.3390/su18115466

Authors: Meiyu Yang Jiping Liu Dandan Zhao

The relationship between humans and the land has always been a topic in geographical studies. Northeast China, one of the regions with the shortest history in China, is also one of the regions most representative of changes in human–land relationships. However, scholars have rarely conducted quantitative region-scale research on the dynamic changes in, and drivers of, human–land relationships in this region. This study utilizes Landsat remote sensing imagery to identify changes in the distribution of land use types in Northeast China from 1985 to 2022. By constructing a human–land coordination model, it measures the intensity of human activity and levels of human–land coordination, analyzes their spatiotemporal dynamic characteristics, and further uses the Geodetector model to explore the factors driving and interactions influencing this evolution. (1) The results show that, from 1985 to 2022, the level of human–land coordination in Northeast China generally exhibited a spatial distribution pattern decreasing from northwest to southeast. The area of imbalanced human–land relationships continuously decreased, while coordinated areas steadily increased, indicating gradual improvement in human–land relations. The predominant type of coordination was moderate imbalance, with high imbalance as a secondary level. (2) The results also demonstrate that population size, GDP, and tertiary industry output have significant explanatory power regarding levels of human–land coordination. The importance of economic development level, natural resource endowment, and natural environmental characteristics to the evolution of human–land has progressively increased.

Sustainability doi: 10.3390/su18115465

Authors: Kazım Eşber Özbaş

This study investigates the ternary co-pyrolysis of Soma lignite (SL), a low-rank Turkish coal with high ash content, with two agricultural residues: pectin-rich sugar beet pulp (SBP) and lignin-rich peanut shell (PS). The primary objective is to clarify how biomass structure and blend composition control synergistic interactions, and how co-pyrolysis can upgrade the fuel properties of a low-quality coal while valorizing agro-industrial waste. Four SL:SBP:PS blends (80:10:10, 60:20:20, 40:30:30, and 20:40:40 wt.%) were tested by non-isothermal thermogravimetric analysis at 10 ∘C min−1 under nitrogen. Differential thermogravimetric curves were deconvolved into four pseudo-components representing pectin/hemicellulose, cellulose, lignin/early coal, and main coal/mineral fractions. Mass-based deviation indices (ΔW) and rate-based deviations (Ψ) from the additive prediction were calculated in three temperature regions to detect synergy and antagonism. The results demonstrate that interactions are strongly composition-dependent. The 40:30:30 blend exhibits the most pronounced synergistic enhancement, with average ΔW values of approximately −0.94 wt.% and −1.05 wt.% in the 350–500 ∘C and 500–650 ∘C ranges, respectively, while the 60:20:20 blend shows antagonistic behavior across all regions. For the 40:30:30 blend, the calculated higher heating value increases from 11.21 to 14.74 MJ kg−1, reflecting a gradual upgrading of the feed-mixture composition by biomass loading. Overall, the findings indicate that combining a pectin-rich, fast-devolatilising biomass with a lignin-rich, slower-decomposing biomass at an intermediate coal loading can shift mass loss to lower temperatures. This combination also produces measurable non-additive behaviour within the experimental noise level. In addition, it improves several feed-mixture indicators that are relevant to sustainable energy recovery from lignite-dominated regions.

Sustainability doi: 10.3390/su18115464

Authors: Yannan Geng Dashan Liu Chunhua Cai Zixi Zhang Xuejing Huang

Environmental policies play an important role in promoting corporate green innovation, yet existing studies often treat such policies as a single exogenous shock and pay limited attention to the institutional context in which firms respond. Using the Low-Carbon City Pilot (LCCP) policy in China as a quasi-natural experiment, this study examines how environmental policies influence corporate green innovation. Based on panel data of Chinese A-share listed firms from 2007 to 2023, a staggered difference-in-differences model is employed to identify the policy effect. The results show that the LCCP policy significantly promotes corporate green innovation and stimulates both substantive and strategic green innovation. From the perspective of institutional logics, capital market time orientation plays an important moderating role: long-term institutional investors strengthen the positive policy effect, while short-term institutional investors weaken it. Mechanism tests further show that the policy promotes green innovation mainly by increasing managerial attention to environmental and low-carbon issues, while its effect on temporal attention allocation is not significant. These findings highlight the importance of institutional contexts and managerial attention in shaping firms’ strategic responses to environmental policies and provide new empirical evidence on how environmental governance policies influence corporate green innovation.

Sustainability doi: 10.3390/su18115462

Authors: Faming Li Tianming Sun Kaiting Yang Yuming Shao Yanhong Huo Yiqing Liu

Under the dual pressures of heritage conservation and tourism growth, improving inclusive access to cultural tourism opportunities in historic urban areas has become an urgent planning issue under Sustainable Development Goal 11 and the Historic Urban Landscape approach. Taking the central urban area of Suzhou, China, as a case study, this study evaluates time-budgeted walkable accessibility, spatial equity, local mismatch, and accessibility-generating conditions from a 15 min city perspective. An integrated analytical framework was developed by combining kernel density analysis, GIS-based network accessibility modelling, Lorenz–Gini equity assessment, bivariate Local Indicators of Spatial Association (LISA), and XGBoost–SHAP interpretation. The results show that cultural tourism opportunities exhibit a clear core polarisation–peripheral attenuation pattern. Within the 15 min threshold, Gusu District records SACR and AAR values of 80.18% and 95.23%, respectively, indicating a pronounced historic-core accessibility advantage. Accommodation-tier differences do not form a simple monotonic relationship with accessibility, but are shaped by the spatial embedding of different accommodation-market segments within the cultural tourism opportunity field. HL units, namely high-tier accommodation near low accessibility, emerge as priority diagnostic areas of local mismatch, while delayed accessibility beyond 30 min becomes particularly evident among elderly visitors. The SHAP interpretation further indicates that leisure-strolling attractions show a more balanced supply–accommodation structure, whereas commercial–cultural mixed and heritage-core attractions are more strongly supply-led. By linking accessibility measurement, equity assessment, local mismatch diagnosis, and mechanism-based explanation, this study provides an operational basis for zonal and typology-oriented optimisation of cultural tourism accessibility in historic urban areas.

Sustainability doi: 10.3390/su18115463

Authors: Asterios Pantokratoras

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Sustainability doi: 10.3390/su18115461

Authors: Evghenii Goncearenco Monica Scarisoreanu Iuliana P. Morjan Elena Dutu Valentin. S. Teodorescu Carmen Ioana Fort Miruna Stan

Increasing environmental pollution has intensified the focus on sustainability, encouraging the development of eco-friendly materials. This study reports the synthesis of binary (ZnO–TiO2) and ternary (SnO2–ZnO–TiO2) compounds and their loading with Au/Ag/Pt/P noble metals (NMs) to enhance photodegradation efficiency under visible light compared to pristine TiO2. The compounds were synthesized in a single step via laser pyrolysis, and then noble metal deposition through chemical impregnation and reduction was performed. Structural and morphological analyses revealed TiO2-based nanoparticles with varied morphologies decorated with noble metal nanoparticles with sizes between 2 and 6 nm (for Pt and Pd). Photocatalytic tests demonstrated a significant improvement in Methyl Orange (MO) degradation under visible light, especially for Ag-loaded samples. The degradation rate increased from 1.03 × 10−3 min−1 (TZ) to 22.65 × 10−3 min−1 (TZS_Ag), while it was 0.09 × 10−3 min−1 for the commercial P25 sample. Biocompatibility assays indicated lower cytotoxicity than Degussa P25, with Au- and Pd-loaded samples showing improved compatibility with HaCaT and HEK293 cells. Overall, these findings demonstrate that the developed TiO2-based nanocomposites, designed through a novel and sustainable strategy combining binary/ternary heterostructures with noble metal loading, are promising candidates for efficient visible light-driven photocatalytic environmental decontamination with enhanced biological compatibility.

Sustainability doi: 10.3390/su18115460

Authors: Yuming Zheng Kai-Hua Wang Nicoleta-Claudia Moldovan Lavinia Daniela Mihiț Nicolescu Ana Cristina

This study applies the rolling window Granger causality method to explore the dynamic causal nexus between China’s renewable energy consumption (REC) and climate policy uncertainty (CPU). From the perspectives of digitalization, energy development and technological innovation, empirical outcomes confirm that CPU exerts time-varying instead of static causal effects and steadily boosts REC expansion. There exists evident asymmetry in the reverse feedback of REC on CPU. Thriving renewable energy development reduces policy uncertainty by validating energy transition feasibility, while traditional energy interest-oriented policy revisions tend to heighten CPU. This study further verifies pronounced temporal heterogeneity in their causal interactions, providing fresh evidence for understanding the linkage between policy uncertainty and green growth. It finally proposes differentiated strategies involving short-term energy structure optimization and long-term climate institutional design to advance stable and resilient energy transition.

Sustainability doi: 10.3390/su18115457

Authors: Delia Stefana Donici Diana Elena Dumitras

Nature-based tourism is expanding rapidly, placing new pressures on fragile ecosystems and governance structures that were not designed for the intensity and diversity of today’s visitors. Despite this trend, protected areas face unique management constraints and rapid socio-environmental changes. While motivational segmentation of tourists can provide valuable information to policymakers, this subject remains understudied/under-researched. This study addresses the gap by examining the motivations, behaviours, and attitudes of visitors to Romania’s national and natural parks, using a structured survey (n = 509) and a two-step approach combining dimensionality reduction with visitor segmentation. Principal component analysis (PCA) reveals distinct motivational dimensions related to visitors’ desire for immersion in nature, wildlife observation and learning, active recreation, and social–cultural engagement. Based on these dimensions, three visitor segments emerge through cluster analysis, with significantly different patterns of landscape use, expectations of recreational services, and perceptions of interpretation media. This research provides practical insights for targeted communication, zoning, and adaptive governance and proposes integrating visitor typologies with park management to support sustainable rural development. The findings highlight how a nuanced understanding of tourist segments can inform more effective policy measures that balance recreational demand with the long-term protection of natural and cultural resources, offering practical value for the sustainable development of protected areas, local communities, and other stakeholders.

Sustainability doi: 10.3390/su18115456

Authors: Jakeline Baratto Paulo Miguel de Bodas Terassi Nádia Gilma Beserra de Lima Valéria Machado Emiliano Emerson Galvani

This study examines long-term mangrove vegetation dynamics in the Cananéia–Iguape Coastal System (CICS), southeastern Brazil, with emphasis on their relevance for coastal ecosystem monitoring and sustainability. Land-use and land-cover (LULC) data from MapBiomas were combined with MODIS-derived vegetation indices, namely the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), and Fractional Vegetation Cover (FVC) to assess spatial variability and temporal trends from 2003 to 2024. Spatial anomalies were calculated as deviations from long-term mean conditions, whereas temporal trajectories were evaluated using the non-parametric Mann–Kendall test and Sen’s slope estimator. The results indicate limited spatial variability, with 98.35% of the study area for the NDVI and 99.51% for the EVI showing no detectable deviations from long-term averages. Within mangrove areas, however, statistically significant positive trends were identified for the NDVI (ZMK = 2.43; p = 0.02), EVI (ZMK = 2.03; p = 0.04), and FVC (ZMK = 2.43; p = 0.02), suggesting a gradual increase in spectral greenness and FVC-derived vegetation density. The moderate correlation between mangrove extent and the NDVI (r = 0.61; p < 0.05) indicates that the mapped mangrove area is partially associated with variations in spectral greenness, although this relationship should not be interpreted as direct evidence of ecological recovery or improved ecosystem conditions. Overall, the findings point to low-magnitude but consistent vegetation index changes in a predominantly stable mangrove system. The integration of LULC information, spectral indices, and FVC provides a consistent regional-scale basis for interpreting mangrove dynamics in heterogeneous coastal environments and for guiding long-term monitoring efforts.

Sustainability doi: 10.3390/su18115459

Authors: Fahad S. Allahaim

The built environment in Saudi Arabia accounts for approximately 78% of the country’s total electricity consumption, positioning building energy performance as one of the most consequential levers available to policymakers pursuing the kingdom’s net-zero greenhouse gas emissions target for 2060 and Vision 2030’s sustainability agenda. Despite the progressive introduction of the Saudi Building Code (SBC) energy chapters SBC 601, SBC 602, and the Saudi Green Building Code (SgBC 1001), a persistent gap remains between regulatory intent and measurable outcomes across Saudi Arabia’s five distinct climatic zones. Building codes are, by design, generic policy instruments encompassing structural, fire, accessibility, and energy provisions; this paper focuses specifically on the energy and sustainability dimensions and critically examines how the SBC’s update cycle and prescriptive compliance architecture shape actual performance outcomes. This study presents three explicit research questions: (RQ1) What zone-differentiated energy savings does SBC implementation deliver across residential typologies? (RQ2) How does the Mostadam national rating system compare with international benchmarks in the Saudi context, and what caveats govern that comparison? (RQ3) What evidence-based policy interventions are needed to transition from compliance-led to performance-led building energy governance? Drawing on a systematic synthesis of 53 building energy simulation models (2018–2025), official programme data, and a structured comparative analysis of Mostadam against LEED v4.1 and BREEAM, the study finds EUI reductions of 5–25% from SBC compliance, with the largest savings in the hot–humid coastal zone. Seven prioritised policy recommendations are proposed, addressing code revision, financial incentives, digital monitoring, renewable energy thresholds, and capacity building.

Sustainability doi: 10.3390/su18115458

Authors: Felipe Sáez-Ardura Matías Parra-Salazar Arturo Vallejos-Romero Minerva Cordoves-Sánchez César Cisternas-Irarrázabal Loreto Arias-Lagos Vinicius Genaro

The regulatory conditions present regarding anthropogenic pollution of two large Chilean Northern Patagonian lakes, Llanquihue and Villarrica, are analyzed. Taking the risk-based approach (RBA) as a reference framework, the study addresses three relevant dimensions of the socio-environmental risks present in the regulatory regimes of each ecosystem: (1) the reflexive components of the institutions involved, (2) the deployment of organizational processes regarding regulatory norms, and (3) the modalities for addressing change and complexity in the regulatory field. Developing a qualitative multiple-case study with criterion-oriented maximum variation sampling, 40 individual interviews conducted with participants who perform tasks in both cases are analyzed, examining their regulatory configurations according to the investigated dimensions. The most important findings account for: (1) an institutional attenuation that bureaucratically minimizes socio-environmental risks, hindering the transition towards preventive approaches marked by a political culture that prioritizes formal compliance over territorial management; (2) a profound institutional fragmentation and centralization of regulation that dilutes responsibility, operating under logics of minimal efforts that prevent the watershed perspective from achieving normative legitimacy; and (3) a regulatory field overwhelmed by wide-ranging phenomena of difficult regulatory management, where the binary classification of saturation proves insufficient to address diffuse pollution and risks of difficult reversibility. It is concluded that strengthening the regulatory capacities of emerging nations regarding the socio-environmental protection of large lakes requires gradually integrating risk as an organizing criterion and prospecting watershed governance based on multiple regimes complementary to the regulatory effort of the already atomized and centralized normative instruments available.

Sustainability doi: 10.3390/su18115452

Authors: Stangierska-Mazurkiewicz Dagmara Kowalczuk Iwona Juszczak-Szelągowska Ksenia Olewnicki Dawid Kosicka-Gębska Małgorzata

Food waste presents a significant challenge to sustainable development, resulting in annual economic losses of more than USD 1 trillion. It contributes to 8–10% of global human-caused greenhouse gas emissions and accounts for nearly 30% of agricultural land use. Households are responsible for over half of this waste, with fruits and vegetables being the most frequently discarded items. This highlights the urgent need to promote sustainable consumption habits. This 2024 study surveyed a sample of 923 individuals who consume at least one of four categories: fresh fruits, fresh vegetables, processed fruits, or processed vegetables. It used cluster analysis to segment consumers based on the amount of food waste and fruit and vegetable losses. Three distinct segments were identified. Cluster 1 (Proactive & aware, 56%): Characterised by high environmental awareness (approximately 75%) and efficient food management skills, such as frequent shopping list preparation (48%), resulting in the lowest wastage levels. Cluster 2 (Convenient & situational, 38%): Driven by “convenience waste” mechanisms, where lack of time, poor portioning (44%), and a lack of culinary ideas lead to moderate waste levels despite mid-range awareness. Cluster 3 (Disorganised & wasteful, 6%): Reveals a significant attitude–behaviour gap; despite declaring a desire to limit waste, this group reported the highest perceived levels of waste. This is partly explained by the reverse sunk cost fallacy, where produce from own cultivation is devalued due to the absence of a market price. The findings emphasise that food waste is not a monolithic phenomenon but results from diverse behavioural deficits. The results provide a foundation for tailored behavioural interventions (nudges) and educational strategies to enhance food management skills and contribute to the achievement of sustainable development goals (SDGs).

Sustainability doi: 10.3390/su18115455

Authors: Federico Lopez-Muñoz Luis Ricardez-Sandoval Viktor Oswaldo Cardenas-Concha Daniela S. Mainardi Arturo Gonzalez-Quiroga Angel Darío González-Delgado Jeffrey Leon-Pulido

The environmental performance of chitosan production is evaluated through a rigorous computational comparison between traditional thermochemical deacetylation and innovative green synthesis pathways utilizing Deep Eutectic Solvents (DES). Implementation of the Waste Reduction (WAR) algorithm facilitates the quantification of the Potential Environmental Impact (PEI) across eight toxicological and ecotoxicological categories, providing a systematic benchmark for process sustainability. While the conventional route, characterized by the intensive consumption of HCl and NaOH, generates a substantial environmental burden of 1.37 × 107 PEI/ton, the optimized green architecture leveraging a choline chloride:ethylene glycol (ChCl:EG) system achieves a radical reduction to 2.25 × 104 PEI/ton. This 99.8% decrease in PEI is primarily driven by the mitigation of Human Toxicity Potential (HTP) and Acidification Potential (AP) through the substitution of corrosive mineral acids and volatile organics with biodegradable, low-vapor-pressure alternatives. These findings substantiate the integration of DES-mediated biorefineries as a high-efficiency strategy for the valorization of marine waste into high-purity biopolymers, aligning with the requirements for industrial process intensification and circular bioeconomy standards.

Sustainability doi: 10.3390/su18115454

Authors: Mahnaz Babapour Maria Vittoria Corazza Guido Gentile

Understanding the gap between individuals’ intention to reduce car use and their actual willingness to adopt public transport is critical for advancing sustainable urban mobility. This case study in Rome examines how perceived public transport service quality and travel burden influence car-dependent employees’ willingness to shift to public transport. The analysis draws on survey data collected from 392 respondents, including 190 car-dependent employees, between May and July 2024. The results reveal that perceived public transport service quality has a significant positive direct effect on willingness to use public transport. In contrast, its indirect effect through intention to reduce car use is not significant. In contrast, travel burden does not show a significant total effect on willingness; however, in the combined model, it exhibits a positive direct effect on willingness, while its indirect pathway through intention is weak. Furthermore, travel burden has a marginal negative effect on intention, reflecting structural constraints associated with car dependency. Intention is a strong predictor of willingness but does not significantly mediate the effect of service quality. It also shows a significant interaction effect with travel burden in the combined model. Overall, the findings suggest that improving public transport service quality is more effective in encouraging modal shift than increasing the burden of car use. This highlights the importance of service-oriented and user-centered interventions, as well as the need to address structural barriers that limit behavioral change.

Sustainability doi: 10.3390/su18115453

Authors: Jeff S. Sharp Taylor Valentine

Preparing students to engage with sustainability challenges requires not only teaching key concepts and competencies but also supporting students in recognizing and taking ownership of their learning in ways that connect to future professional and civic roles. This study examines what reflective self-assessment reveals about sustainability competency and skill development in a large-enrollment introduction to sustainability course. Drawing on qualitative analysis of an end-of-semester reflective assignment, we examine patterns in what students emphasize, how they describe their learning, and which course learning activities and contexts they associate with competency development. The findings indicate that students frequently identify systems thinking and other sustainability competencies while also prominently emphasizing general and professional skills such as communication, teamwork, and problem-solving. Learning is most often grounded in lab-based active learning contexts and, when students are prompted to articulate their learning in professional narratives, they are integrated into accounts that identify sustainability competencies and broader skill development. Taken together, the findings suggest that reflective self-assessment can function not only as an assessment approach, but also as a pedagogical strategy that supports student sense-making, recognition, and ownership of sustainability learning relevant to future academic, civic, and professional pathways aligned with the aims of SDG 4.7.

Sustainability doi: 10.3390/su18115451

Authors: Xingmei Jia Mengting Yang Tingting Zhu

Reducing spatial inequality is central to sustainable agricultural transformation in developing regions. This study constructs a multidimensional framework to quantify regional disparities in strong agricultural development across Anhui Province, China, from 2010 to 2022. We integrated an entropy-weighted TOPSIS model with Dagum Gini decomposition and obstacle factor analysis. The analysis reveals a marked yet uneven rise in agricultural development, with growth accelerating in recent years. Central, northern, and southern Anhui exhibit a declining spatial gradient of development, while disparities—particularly between the central and southern regions—remain pronounced, though gradually narrowing. Innovation capacity, industrial competitiveness, and policy support emerge as dominant drivers of spatial differentiation, with technological innovation identified as the pivotal lever for advancing from “large” to “strong” agricultural provinces. These findings highlight the importance of innovation-led and adaptive governance strategies in narrowing development divides and guiding sustainable agricultural transformation in emerging economies.

Sustainability doi: 10.3390/su18115450

Authors: Bingyan Fan Yuan Xue Mingyue Dai Yu Ming Muchen Lin

Against the backdrop of the “dual carbon” goals, carbon emission trading prices serve as a core signal of market operational efficiency. Accurately predicting carbon prices facilitates scientific decision-making, and model optimization is key to improving prediction accuracy. This study takes five major carbon trading pilots in China—Shenzhen, Guangdong, Hubei, Beijing, and Shanghai—as the research objects. An indicator system is constructed from four dimensions: macroeconomy, energy prices, climate and environment, and international markets. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm is employed to identify the key influencing factors of carbon prices across different markets. Among them, “WTI crude oil price” and “EUA futures closing price” are consistently significant factors common to all five pilots. On this basis, four models—Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX), Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and Transformer—are constructed for multi-method prediction comparison. The results show that ARIMAX and GRU achieve the best prediction performance among the four models. To further enhance prediction accuracy, hybrid optimization models are respectively developed: Support Vector Regression (SVR) is used to optimize the nonlinear residuals of ARIMAX (SVR-ARIMAX), and Genetic Algorithm (GA) is used to optimize the key hyperparameters of GRU (GA-GRU). The hybrid models significantly reduce prediction errors in most markets. Specifically, SVR-ARIMAX shows particularly notable improvements in Beijing and Hubei, while GA-GRU outperforms standard GRU in Guangdong, Shenzhen, Shanghai, and Hubei. Based on the optimized models, 12-month-ahead forecasts indicate that the Shenzhen market exhibits high volatility and greatest uncertainty; Guangdong remains relatively stable; Hubei, Beijing, and Shanghai are characterized by narrow-range fluctuations. The findings provide empirical support for corporate emission reduction decision-making, carbon market risk management, and price mechanism improvement.

Sustainability doi: 10.3390/su18115449

Authors: Deidre D. Harmon Kendra P. Phipps Matt H. Poore Ethan Henderson Langdon J. Martin Isaac D. Fields Jan F. Stevens Wenbin Wu Vivek Fellner Broxton Ashburn Robert W. Bryant

Craft breweries generate a complex set of byproducts that exceed 2 million tons annually. Their disposal possesses material handling, financial, and environmental challenges. A mixture of these, namely trub, hops, and yeast, designated THYM®, was evaluated biochemically and in a feeding trial to enhance its valuation. THYM contained approximately 3% α plus β hop acids, 0.2% xanthohumol (XN), and 35% crude protein. It exhibited antimicrobial activity, with a minimum inhibitory concentration of 137 ± 39 μg/mL for B. subtilis, and antioxidant activity, with 90 ± 13 μmol/g of Trolox equivalents. THYM presented positive results in bovine rumen microbial in vitro fermentations, decreasing methane production and the acetate:propionate ratio at 3 mg/mL. These results led to a nine-week feedlot trial with 45 Black Angus weanling steers on either a corn silage-based diet (CON), CON with monensin (MON) at 200 mg/animal, or CON with 1% THYM (THYM). Data were analyzed by SAS 9.4 with two orthogonal contrasts of CON vs. MON and THYM and MON vs. THYM. While average daily gain (ADG) and dry matter intake (DMI) did not differ among treatments, a tendency was observed for the THYM and MON groups to have a greater gain to feed ratio (ADG:DMI) when compared to CON (p = 0.07). The XN metabolite 8-prenylnarigenin, a potent phytoestrogen, was present in the serum of the THYM group at 4.0 ± 0.9 nM by mass spectrometry. These brewing byproducts, which can be drum-dried, were well tolerated and show potential value as a cattle growth promoter.

Sustainability doi: 10.3390/su18115448

Authors: Hongpeng Guo Zihan Wu Yujie Xia Zirou Mao Wenyu Fu Yingcheng Wang

Against the backdrop of intensifying global climate change and the digital transformation of agriculture, promoting the adoption of digital technologies among new agricultural operators is a crucial pathway to enhancing agricultural climate resilience and achieving sustainable agricultural development. Based on survey data from 516 new agricultural operators in typical agricultural regions such as Northeast China, Hunan, and Hebei, this study employs Logit models, moderation effects, and heterogeneity analysis to examine the impact of digital technology cognition and climate risk on operators’ technology adoption behavior, as well as the underlying mechanisms. The findings reveal the following: First, digital technology cognition has a significant positive impact on the adoption of digital technologies, whereas climate risk perception and experiences with extreme weather significantly inhibit adoption behavior. Second, the perception of multidimensional barriers—comprising technical, economic, social, and policy obstacles—significantly moderates the positive effect of digital technology cognition on adoption behavior. Third, these effects exhibit significant heterogeneity across business scale, years in operation, and entity type. These conclusions remain valid after robustness tests and endogeneity control. This study enriches theories of agricultural technology diffusion and sustainable development from a climate resilience perspective, providing empirical evidence to promote the use of digital technologies for agricultural climate adaptation, refine differentiated extension policies, and enhance the level of agricultural sustainability.

Sustainability doi: 10.3390/su18115447

Authors: Shuzheng Wang Shengyuan Wang Zhi Wu Guyue Zhu Haode Wu

Accurate transmission-line parameters are essential for reliable, efficient, and sustainable smart grid operation, especially under increasing renewable-energy integration and data-driven grid management. However, line aging, temperature variations, and measurement outliers may cause significant deviations between actual and nominal grid models, thereby degrading the state estimation, power-flow analysis, and operational security assessment. To address these challenges, this paper proposes a robust transmission-line parameter estimation method based on a variable-projection framework. The proposed framework decomposes the original high-dimensional, strongly coupled, and non-convex joint estimation problem into two subproblems associated with line-parameter identification and operating-state calibration. An iteratively reweighted least-squares algorithm based on the Huber M-estimator is introduced to dynamically adjust measurement weights and suppress the influence of outliers. The preconditioned conjugate-gradient method is further employed to avoid the explicit inversion of large-scale normal matrices. Simulations on the IEEE 118-bus system demonstrate that the proposed method achieves a higher parameter-estimation accuracy and stronger robustness than conventional weighted least-squares and joint state-parameter estimation methods. In the base case, the proposed method reduces the RMSRE of line reactance to 0.0794%, compared with 0.1558% for WLS and 0.1126% for JSE. Under the representative 5% gross-error case, the proposed method maintains lower RMSREs of 0.9772%, 0.0875%, and 5.8536% for Rl, Xl, and Bsh, respectively. Further sensitivity tests under contamination ratios from 1% to 20%, outlier magnitude factors from 1.5 to 5.0, and different outlier-location patterns confirm that the proposed method maintains a more stable estimation accuracy than WLS, conventional JSE, and Huber-JSE without VPM under diverse bad-data conditions. In downstream operational evaluations, it reduces the branch active-power flow RMSE from 1.6842 MW to 0.7215 MW, voltage-magnitude RMSE from 0.00482 p.u. to 0.00216 p.u., and active-power-loss error from 2.4368% to 0.9327% compared with WLS. These quantitative results indicate that the proposed approach can improve the grid model accuracy under imperfect measurements, thereby supporting reliable and sustainable smart-grid operation.

Sustainability doi: 10.3390/su18115446

Authors: Riccardo Fontana Mattia Buratto Elena Smiderle Noemi Lagreca Martina Facchini Chiara Nordi Francesco Tisselli Luciano Vogli Peggy Marconi

Healthcare cleaning services are essential for infection prevention but contribute significantly to the environmental footprint of hospital operations through the intensive use of chemicals, water, and energy. This study presents an integrated assessment of a conventional cleaning protocol (TT) and a CAM-compliant environmentally oriented protocol (GREEN, TG) in a real hospital setting (Bufalini Hospital, Cesena, Italy), combining microbiological monitoring with Life Cycle Assessment (LCA). Surface contamination was evaluated across different risk areas using standardized culture-based methods, while environmental impacts were quantified using a cradle-to-grave LCA approach, focusing on Global Warming Potential (GWP100). Both protocols achieved significant reductions in microbial load, with post-cleaning values consistently below established hygienic thresholds. No pathogenic indicator organisms were detected after cleaning, and the GREEN protocol demonstrated microbiological performance equivalent to or slightly better than the traditional system across all risk categories. LCA results revealed a substantial environmental advantage for the GREEN protocol, with a 43.7% reduction in carbon footprint (−273 g CO2e m−2 year−1), corresponding to an annual saving of approximately 13.3 t CO2e at the facility scale. These reductions were primarily driven by decreased chemical consumption, optimized dosing, and lower laundering temperatures. The findings demonstrate that environmentally sustainable cleaning strategies can maintain high standards of microbiological safety while significantly reducing environmental impacts. This integrated approach supports the adoption of CAM-compliant protocols in healthcare facilities and highlights the importance of combining infection control metrics with life-cycle environmental evaluation to inform sustainable procurement and hospital management practices.

Sustainability doi: 10.3390/su18115445

Authors: Abrar Hussain Himanshu S. Maurya Dmitri Goljandin Ramin Rahmani Maris Sinka Diana Bajare

Development of sustainability systems for assessment of environmental impacts remains a paramount challenge for green and circular manufacturing of polymers. In this study, a comprehensive life cycle assessment (LCA) framework is developed for European polymeric waste by integrating OpenLCA, Ecoinvent v3.11, and Python-based machine learning (ML) algorithms. Cradle-to-gate, service-life, and cradle-to-grave assessments are performed for representative thermoplastic composite systems, including PP–PET–cotton, HDPE–glass fiber, and PEEK–carbon fiber composites, covering domestic, engineering, and high-performance polymer categories. The results demonstrate that raw material extraction and manufacturing stages dominate environmental impacts, contributing the highest shares to climate change, ecotoxicity, and non-renewable energy consumption. PP-based composite systems exhibit the lowest overall environmental burdens due to lower processing energy and simpler molecular structures, while HDPE-based systems show moderate impacts. PEEK-based composites present the highest impacts per unit mass, driven by energy-intensive synthesis and high processing temperature. Environmental impacts are evaluated using EF v3.1 and ReCiPe methodologies, supported by Monte Carlo simulations and ML-assisted uncertainty quantification. Monte Carlo simulations and ML-assisted LCA provide probabilistic ranges, uncertainty quantification, and predictive insights into impact indicators, enabling the development of a quantitative sustainability system based on probability–impact relationships. A Europe-wide assessment of 57 Mt of polymeric waste highlights that environmental burdens are concentrated in countries with high polymer production and consumption, emphasizing the importance of energy mix, recycling efficiency, and waste management strategies. Overall, this work demonstrates that digitalized LCA coupled with ML offers a powerful decision-support framework for sustainable polymer design, recycling optimization, and circular economy policy development, supporting the transition toward low-carbon and resource-efficient polymer systems in Europe.

Sustainability doi: 10.3390/su18115444

Authors: Jiawei Wen Chengxin Pang Yanxin Wang Xinhua Zeng

Emission factor matching is the most critical step in product carbon footprint (PCF) accounting based on life cycle assessment (LCA). However, this step has long been hindered by several major challenges: a lack of standardization, overreliance on expert judgment, inconsistencies in raw data, and complex processing workflows. To address these issues, this study proposes an automated emission factor matching algorithm that combines large language models (LLMs) with semantic retrieval. The algorithm proceeds in two stages: first, an LLM identifies the reference product within the LCA database; then, an embedding model retrieves the most relevant emission factors through high-precision matching. Depending on practical requirements, the algorithm can either automatically select a single best-match factor or rank multiple best-match candidates in descending order of match precision to assist LCA experts in decision-making. We evaluate the algorithm on eight industrial products—tires, cement, ammonium phosphate, wood products, textiles, electronics and electrical appliances, steel, and lithium batteries—using the Ecoinvent 3.10 LCA database. Results demonstrate that the algorithm achieves high precision and low processing latency, significantly outperforming manual expert screening. These findings confirm that the proposed algorithm enables efficient and accurate emission factor matching, thereby providing a reliable technical solution and decision-making pathway for large-scale, automated PCF accounting.

Sustainability doi: 10.3390/su18115443

Authors: Žydrūnas Kavaliauskas Mindaugas Milieška Giedrius Blažiūnas Giedrius Gecevičius Hassan Zhairabany

This paper presents a forecasting and optimization framework for the control of a hybrid renewable energy system (HRES) integrating solar, wind, and biomass generation with lithium-ion batteries, electrolyzers, and fuel cells. A bidirectional long short-term memory (bi-LSTM) neural network model was applied for renewable generation and load forecasting, while the deep Q-network (DQN) and soft actor–critic (SAC) algorithms were used for real-time supervisory control of energy storage and hydrogen-based components. The HRES was formulated as a Markov decision process (MDP), where the agents optimize battery charging/discharging, electrolyzer activation, and fuel cell operation under dynamically changing operating conditions. Experimental results demonstrated that the SAC agent achieved more stable learning dynamics and superior operational performance compared to the DQN agent, maintaining an HRES energy imbalance below 0.5 MWh while reducing unnecessary component switching and improving overall system stability. The obtained results confirm the potential of deep reinforcement learning for adaptive and low-emission supervisory control of complex hybrid renewable energy systems.

Sustainability doi: 10.3390/su18115442

Authors: Bianca Magalhães José Pombo Willians Mendes Maria Calado Sílvio Mariano Miguel Louro

The increasing importance of photovoltaic (PV) systems in the context of the energy transition, together with the need to improve their efficiency, has driven the adoption and development of intelligent and advanced maximum power point tracking (MPPT) techniques. Among these approaches, the Particle Swarm Optimization (PSO) algorithm stands out due to its simplicity, ease of implementation, low number of control parameters, robustness, and fast convergence capability, making it widely applied in modern MPPT systems. However, the performance of PSO in MPPT applications depends on the appropriate selection of both algorithm control parameters and implementation/configurations parameters. The control parameters include the cognitive (C1) and social (C2) learning factors, as well as the inertia factor (w), which directly influence swarm dynamics and the balance between exploration and exploitation mechanisms, that is, between global and local search. On the other hand, configuration parameters such as the number of particles and the initialization strategy affect the initial population diversity, the convergence speed toward the maximum power point, and the computational cost of the algorithm, defining the trade-off between speed and accuracy. Despite the extensive research in this field, there is still no clear consensus regarding the most suitable PSO parameter configuration for MPPT applications. This paper presents a statistical analysis of PSO parameter selection in MPPT applications, identifying the most frequently adopted parameter configurations and trends reported in the literature. The findings provide useful guidelines for researchers to select the PSO parameters according to different operating conditions, particularly under partial shading and irradiance variations. From a sustainability perspective, improving MPPT performance contributes to maximizing PV energy harvesting, reducing energy losses, and enhancing the reliability of PV systems, thereby supporting the transition toward more sustainable energy generation.

Sustainability doi: 10.3390/su18115441

Authors: Sylvestre Dossa Cristian Argyelan Alexandru Rinovetz Christine Neagu Daniela Stoin Dacian Lalescu Călin Jianu Isidora Radulov Lelia Serpe Adina Brinzeu Ersilia Alexa

In this study, we investigated the possibility of partially substituting wheat flour in bread-making technology with a by-product (rapeseed meal) obtained after pressing of rapeseed seeds used to obtain edible oil. The research was conducted within the context of sustainable food systems and circular bioeconomy strategies. Experiments were conducted using substitution rates of 10%, 20%, and 30% (RMW1, RMW2, and RMW3), as well as their corresponding breads (RMWB1, RMWB2, and RMWB3). The results reveal a notable improvement in the nutritional profile, correlated with the increase in RM. Indeed, significant increases were observed in protein content (up to 16.64% in flours and 14.19% in breads), fat content (up to 8.72% and 7.89%, respectively), and ash content (up to 2.30% and 2.85%, respectively), while carbohydrates decreased (down to 63.72 g/100 g in flours and 45.76 g/100 g in breads). Furthermore, the phytochemical profile was significantly enhanced, as reflected by the increased antioxidant capacity and elevated total polyphenol concentration, highlighting the functional potential of RM-enriched products. Water absorption increased from 55% to 61%, accompanied by a decrease in dough stability, suggesting modifications in the gluten network. Mixolab analyses indicated reduced viscosity and starch retrogradation, while physical bread properties, including porosity, elasticity, and H/D ratio, decreased with increasing substitution levels. Sensory evaluation revealed that a 10% RM substitution ensured optimal acceptability, whereas higher levels (30%) resulted in significant quality deterioration. From a sustainability perspective, the incorporation of RM contributes to the valorization of agro-industrial by-products, reducing waste streams and promoting resource efficiency. Partial substitution of wheat flour also has the potential to decrease reliance on primary agricultural inputs, thereby lowering the environmental footprint associated with cereal production. Additionally, the improved antioxidant profile may enhance product stability and shelf life, contributing to food loss reduction. In conclusion, an incorporation level of up to 20% provided the most suitable compromise between improved nutritional value, functional and technological properties, consumer acceptability, and sustainability considerations, thereby supporting the formulation of novel bakery products consistent with circular bioeconomy concepts and sustainable dietary approaches.

Sustainability doi: 10.3390/su18115429

Authors: Xiaojun Yao Fengshuo Kang Gengwei Zhang He Jiang Baoguo Liu Zhuo Li Hong Wei

Mountainous cultural landscapes, characterized by fragmented heritage sites, present significant challenges for integrated conservation and regional planning. Taking the Mount Song Culture Circle in Dengfeng City, China—a World Heritage site embodying the core of Chinese ritual civilization—as a case study, this study proposes an adaptive minimum cumulative resistance (MCR) gravity model to optimize heritage corridor resilience against spatial fragmentation and development imbalances. Based on a spatial database of 294 cultural relic units, the adaptive model introduces a dynamic cultural value weight (CVIndex = 0.82) and a time decay function (λ = 0.05) to capture the interplay between cultural significance and ecological constraints—features absent in traditional static approaches. The model identifies three optimized heritage corridor networks—”Seeking Wisdom in the Mountains”, “Searching for Culture in the Landscape”, and “Exploring the City Along the River.” Compared with a traditional static MCR model (αindex = 0.42; core area node density = 0.74 nodes/km2), the adaptive approach improves network connectivity by 37% (α-index = 0.58, p < 0.01) and increases core area heritage node density to 1.12/km2. Space syntax analysis further confirms that optimized network integration values strongly correlate with cultural dissemination efficiency (R2 = 0.78, p < 0.01, n = 48). This research offers a methodological innovation for resilient conservation of complex cultural landscapes in World Heritage contexts.

Sustainability doi: 10.3390/su18115439

Authors: Tamanna Taskeen Sanket Chandrakant Patil Ravishanker Patil Ganesh Chandrakant Nikalje Suprasanna Penna

This study evaluated the phytoremediation potential of the halophytic plant Sesuvium portulacastrum (L.) L. for treating industrial wastewater (IWW) in a hydroponic system over a nine-day exposure period. After treatment, the physicochemical analysis of IWW revealed a significant decrease in chemical oxygen demand (COD), biological oxygen demand (BOD), TSs (total solids), total dissolved solids (TDSs), TSSs (total suspended solids), ammonia, phosphate, and nitrate. The COD and BOD were reduced by 90.7% and 82.9%, respectively. The metal analysis indicated a significant decrease in Fe (95%), Mn (87.4%), and Al (93.9%) and complete removal of Ni, Pd, and Zn. The plant stress responses were assessed through the estimation of photosynthetic pigments (Chlorophyll-a, Chlorophyll-b, Total chlorophyll), phenolic and flavonoid contents, and antioxidant activity. Total chlorophyll declined from 1.449 mg/g (control) to 1.20 mg/g on Day 3, followed by partial recovery to 1.25 mg/g by Day 9, indicating physiological acclimatization. Total phenolic content reached 14 mg GAE/g in leaves and 12 mg GAE/g in stems on Day 6, while Total flavonoid content increased from ~70 µg/g (control) to 115 µg/g on in leaves. The metabolic profiling using GC-MS/MS revealed distinct time- and tissue-specific metabolic responses, with 53 metabolites identified in roots and 62 metabolites in leaves. The major differentially accumulated metabolites were sucrose, pinitol, talose and psicose, with peak accumulation at Day 6. A biphasic metabolic response pattern, characterized by early stress perception followed by adaptability, was observed. Phytotoxicity assays using Vigna radiata demonstrated improved germination from 15% (untreated IWW) to 95% after treatment. Overall, the study highlights the strong phytoremediation potential of halophyte S. portulacastrum as an environmentally friendly alternative for industrial wastewater remediation.

Sustainability doi: 10.3390/su18115440

Authors: Ahsen Maqsoom

A circular economy (CE) and industrial symbiosis (IS) are increasingly recognized as key strategies for transforming construction and demolition waste (CDW) into valuable secondary resources. However, existing research remains fragmented, with limited integration across these interconnected domains. This study provides a comprehensive bibliometric review of 966 articles included in the Scopus database from 2000 to 2026 to explore the transformation, intellectual frames, and new trends within the CE–IS–CDW nexus. The results show that the field has transitioned from an early exploratory phase to rapid expansion, with research output accelerating significantly after 2018 and peaking at over 220 publications annually in recent years. The study identifies four significant thematic clusters: CE and sustainability transitions; CDW and recycling practices; life cycle and environmental assessment; and emerging IS and industrial ecology frameworks. Although this has increased, the discipline is still conceptually fragmented and has not integrated CE and IS throughout the entire building life cycle; furthermore, it still has regional differences, especially in the Global South. This is the first systematic bibliometric analysis of the CE–IS–CDW nexus that provides an overview of its conceptual evolution, thematic structure, and fragmentation. This study, in contrast to previous reviews of individual research areas, maps the linkages and gaps between CE and IS in CDW management, offering novel insights for cross-disciplinary research and policy making. Its findings can also offer useful information to policymakers and stakeholders in the industry to recover more resources, enhance industrial symbiosis, and facilitate the shift toward more circular and sustainable construction systems.

Sustainability doi: 10.3390/su18115435

Authors: Bijon Kumar Sarkar Partha Ghosh

Waste materials are abundant and often act as slow environmental contaminants, creating severe ecological challenges. With rapid industrialization, electricity demand has increased substantially, and in India, coal-based thermal power plants (TPPs) remain the dominant source of power generation. Coal combustion produces two major by-products: fly ash and bottom ash (BA). While fly ash is widely utilized in blended cements due to its pozzolanic nature, BA has received comparatively limited attention despite having similar chemical characteristics. Owing to its coarser particle size, BA shows strong potential as a substitute for natural river sand, the excessive extraction of which has led to severe resource depletion and sustainability concerns. Unlike previous studies that focused on single-source BA or limited performance evaluation, this study investigates the use of BA from multiple sources to develop resource-efficient bottom ash concrete (BAC). Concrete mixes containing 0%, 20%, 35%, and 50% BA as volumetric replacements of river sand were evaluated for their fresh, mechanical, durability, and microstructural properties. The results indicate that BA significantly influences concrete performance due to its porous structure. Among the investigated mixes, 35% river sand replacement with BA showed the most favorable performance for the specific materials and sources used in this study, achieving up to 17.46% higher compressive strength and up to 16.14% higher resistance to transport-related properties at 90 days. Microstructural analysis confirmed the formation of secondary C–S–H gel, which enhanced matrix densification. However, 50% replacement resulted in reduced performance. The findings demonstrate that BA can be effectively utilized in concrete at replacement levels of up to 35% as a sustainable substitute for river sand under the investigated material conditions.

Sustainability doi: 10.3390/su18115437

Authors: Susanna Paleari

This article investigates how EU and Member State legislation contributes to advancing circularity in the textile value chain, a priority sector due to its significant environmental impacts and economic relevance. The research aims to address the lack of comprehensive analysis of national legislation supporting textile circularity and to assess its alignment with the evolving EU framework. An inventory and critical analysis of legislative measures adopted at EU and Member State levels, covering all phases of the textile value chain, has been developed, based on review of the literature, screening of European Environment Agency and European Commission reports, and targeted web search. Results show that recent reforms of EU legislation, such as the Ecodesign for Sustainable Products Regulation and the revised Waste Framework Directive, have marked a shift toward a more systemic, lifecycle-oriented regulatory framework promoting textile circularity. Moreover, approximately 130 national policy initiatives and legislative measures exceeding EU requirements have been identified, with legislation focusing especially on the consumption and end-of-life stages and relevant innovation in countries such as France, Belgium, and the Netherlands. However, regulatory gaps remain, particularly regarding consumption, prevention of textile waste, secondary raw materials market, and recycling capacity. The findings also highlight the importance of stronger policy coherence between EU and national legislation.

Sustainability doi: 10.3390/su18115438

Authors: Fanny Rodriguez Jarama Sady García Bendezú Manuel Carrillo Zenteno Tany Burgos Herrería Henry Villón Leoro

This study assessed, in two coastal locations of Ecuador (Cerecita, Guayas; Bajada de Chanduy, Santa Elena), cadmium (Cd) occurrence in cacao cultivated soils, its transfer to plant tissues (leaves and cotyledon/beans), and its implications for producers’ economic sustainability. Twelve cacao-producing sites in Cerecita and eleven in Bajada de Chanduy were georeferenced, and thematic GIS maps were generated to identify potential Cd hotspots. Sampling comprised topsoil (0–10 cm), leaves (fourth fully expanded leaf), and dried/fermented beans, followed by laboratory Cd quantification. In addition, producer surveys were conducted to characterize productive and economic structure, the economic sustainability index (IK) was calculated using Sarandón’s methodology, and interviews with collectors and agri-export companies were performed. Soil Cd levels were comparable between locations (0.24–1.55 mg kg−1), whereas higher concentrations were detected in cotyledons/beans (0.53–5.01 mg kg−1) and leaves (1.13–11.07 mg kg−1), following the pattern leaves > cotyledon > soil. From an economic perspective, all farms exhibited IK < 2, with a marked territorial gap (≈1.6 in Cerecita vs ≈0.5 in Chanduy). Cadmium in cocoa beans poses a long-term risk to marketing; in addition, total cadmium in the soil did not consistently predict cadmium in the cotyledons, and adverse impacts are amplified in territories with limited economic capacity to respond.

Sustainability doi: 10.3390/su18115433

Authors: Li Zhang Ding

In the current era of accelerated urbanization, food security is facing unprecedented challenges. Urban agriculture, as a complex system integrating ecological, social and economic values, has become one of the effective solutions. Urban agriculture helps ensure food security, provides health benefits for the population, promotes social inclusiveness, and enhances people’s happiness. From a planning perspective, residential areas, as an important component of urban space, their integration with urban agriculture is an important way to alleviate urban food problems and enhance urban sustainability. However, existing studies mostly adopt uniform and homogeneous design methods and strategies, ignoring the differences between different types of residential areas, resulting in resource waste and insufficient implementation. Therefore, our study takes Nankai District of Tianjin as an example, uses the K-means clustering algorithm to classify residential areas, further proposes strategies for integrating spatial elements and management and operation mechanisms of different types of residential areas, and conducts a quantitative assessment of the sustainable benefits of the updated urban agriculture in residential areas. This study aims to break through the homogeneous design paradigm and provides a theoretical basis and practical references for promoting the update of urban agriculture in residential areas and sustainable urban development. The results show that differentiated urban agriculture updates in four types of residential areas can significantly improve the sustainable benefits of the residential areas.

Sustainability doi: 10.3390/su18115436

Authors: Yuhang Ma Nor Farradila Abdul Aziz

High emissions and excessive resource consumption by heavily polluting firms pose significant obstacles to sustainable development. As a strategic tool, digitalization has shown increasing potential to promote sustainable transformation. Existing studies mainly focus on the relationship between digitalization and green innovation (GI) at the regional level, while firm-level evidence remains limited, especially in heavily polluting industries. Based on information asymmetry theory and stakeholder theory, this study establishes a framework to explore how corporate digitalization (CD) affects the green innovation of heavily polluting firms (GIHPF) through external information intermediaries. Using panel data on Chinese listed heavily polluting firms from 2012 to 2023, we find that CD significantly promotes GIHPF, and the results remain robust across a series of tests. CD enhances GIHPF mainly by increasing investment analysts’ attention (IAA) and media attention (MA), thereby mitigating information asymmetry and strengthening external monitoring. Heterogeneity tests show the effect is stronger for non-state-owned firms, central-region firms, and growth and maturity-stage firms. This study contributes to the literature by providing firm-level evidence from heavily polluting industries and by uncovering the role of external information intermediaries in the relationship between CD and GIHPF. The findings also offer important implications for promoting sustainable development through digitalization.

Sustainability doi: 10.3390/su18115434

Authors: Paweł Hubar Marian Kachniarz

Depopulation constitutes a fundamental challenge for territorial governance, particularly within the framework of sustainable development; however, its representation in local strategic documents remains insufficiently explored. This study aims to identify and compare strategic responses to depopulation across two contrasting Polish regions—Dolnośląskie Voivodeship and Podlaskie Voivodeship—and three governance levels: regional, county, and municipal. An abductive mixed-methods approach was applied, combining discourse analysis with latent semantic analysis (LDA), and principal component analysis (PCA). The findings reveal a clear dominance of the pro-growth paradigm, while the adaptive approach associated with managed shrinkage remains marginal. Regional differences are primarily observed in problem framing—functional in Dolnośląskie and demographic in Podlaskie—but these distinctions do not significantly affect the types of policy responses. Structural instruments, particularly those related to consolidation, prevail, whereas functional and competency-based measures are less prominent. The results suggest the existence of a standardized model of strategic response to depopulation across regions and governance levels. This indicates limited diversification of policy approaches and highlights the need to more fully integrate adaptive strategies into territorial policy, especially in the context of long-term demographic change.

Sustainability doi: 10.3390/su18115432

Authors: Di Huang Qiaoyan Zhao

With the development of the healing economy, forest wellness tourism has emerged as a new form of healthy and high-value-added tourism, and its therapeutic attributes have become key to enhancing tourists’ health benefits. This study investigated the relationship between the therapeutic features of forest wellness tourism, restorative experiences and tourists’ health benefits. The data was obtained through the field survey of 639 forest wellness tourists in the form of questionnaires, and the research hypothesis is empirically tested using mathematical statistical analysis and a structural equation model. The results indicated that the therapeutic attributes of forest wellness tourism significantly improved tourists’ health benefits, with the natural environment, infrastructure, humane atmosphere and symbolic perception all having a positive impact. Moreover, restorative experiences play a positive mediating role between the therapeutic attributes of forest wellness tourism and tourists’ health benefits. This study enriches and expands the theoretical research system related to the therapeutic attributes of forest wellness tourism and restorative experiences, reveals how forest wellness tourism influences tourists’ health benefits, and provides a practical basis for the integrated development of the health and tourism industry.

Sustainability doi: 10.3390/su18115431

Authors: Dehua Shi Xu Liu Shaohua Wang Weiqi Zhou Lili Shen

To address the issues of increased energy consumption and reduced engine efficiency in plug-in hybrid electric vehicles (PHEVs) under low-temperature conditions due to cabin heating demands, this paper investigates the coupling characteristics between the powertrain system and the cabin thermal management system and proposes an adaptive energy management strategy tailored for low-temperature environments. First, a comprehensive model incorporating vehicle dynamics, the engine, and the passenger compartment thermal management system was established. The impact of different ambient temperatures and equivalent factors on the system’s energy consumption characteristics was then quantitatively analyzed under WLTC conditions. Based on this, an adaptive strategy for minimizing equivalent fuel consumption that accounts for cabin heating demand was designed. By using real-time cabin heating demand and engine waste heat power as state feedback, the equivalent factor is dynamically adjusted to coordinate the allocation of power between propulsion and heating. Simulation and hardware-in-the-loop test results indicate that the optimized strategy, by promoting early engine engagement and improving waste heat recovery efficiency, reduces PTC energy consumption by 0.47 kWh under −20 °C WLTC conditions, decreases additional fuel consumption caused by low temperatures by approximately 59%, and improves the vehicle’s equivalent fuel economy by 4.6%, while effectively maintaining passenger compartment thermal comfort. This study contributes to sustainable transportation by reducing low-temperature-induced energy waste, lowering equivalent fuel consumption, and promoting efficient use of engine waste heat, thereby supporting carbon emission reduction goals in hybrid electric vehicle operations.

Sustainability doi: 10.3390/su18115430

Authors: Magdalena Bogalecka Beata Magryta-Mut

Ensuring the sustainability and resilience of maritime transport systems under increasing climate variability is a growing challenge for ferry operations. Operational safety and economic performance are increasingly influenced by short-term weather variability, particularly in semi-enclosed seas such as the Baltic Sea. While existing studies often represent weather impacts through direct cost adjustments or disruption indicators, such approaches obscure the mechanisms through which meteorological conditions affect operational outcomes. In this context, the evolution of operational safety states can be interpreted as a proxy for system resilience, enabling a structured assessment of sustainability under dynamic environmental conditions. This study proposes a novel probabilistic framework that conceptualizes weather impacts as a process of climate-driven degradation of operational safety rather than as an exogenous cost factor. Ferry operations are modeled as a semi-Markov process with a hierarchical structure of safety states defined by nested subsets. Adverse weather conditions reduce expected lifetimes in higher safety states, increasing exposure to degraded operational regimes associated with increased cumulative costs. Costs are assigned conditionally to operational states, while safety subsets determine duration of exposure to different cost regimes, making safety dynamics the primary transmission mechanism linking weather variability to economic performance. Application to a Baltic Sea ferry route shows that moderate and severe weather conditions substantially shorten the duration of high-safety states and systematically increase expected operational costs, revealing a nonlinear relationship between climate variability, safety degradation, and cost escalation. The proposed approach provides a transparent methodological framework for assessing climate resilience and analyzing interactions between weather variability, safety degradation, and operational costs. The results should be interpreted as scenario-based outputs derived from expert-informed parameters rather than empirical forecasts, and empirical calibration would be required for practical applications. By interpreting safety-state dynamics as a proxy for operational resilience, the model supports sustainability-oriented assessment and future risk-informed planning in maritime transport systems.

Sustainability doi: 10.3390/su18115425

Authors: Kariman Kadry Walaa S. E. Ismaeel

Environmental Impact Assessment (EIA) is intended to function as a predictive, spatially grounded decision-support mechanism. Yet in many developing contexts, its operationalization remains fragmented, descriptive, and weakly standardized. Thus, this study addresses limitations in conventional EIA systems related to transparency, reproducibility, and uncertainty integration by proposing a spatially explicit, digital rule-based decision-support framework that operationalizes hierarchical receptor-based structuring, lifecycle-sensitive modelling, risk classification, and uncertainty propagation within an integrated Geographic Information Systems (GISs) architecture. The academic objective is to advance computational environmental assessment methodologies by formalizing EIA logic into a structured computational workflow that translates spatial interactions (including land use, population density, ecological sensitivity, hydrological zones) and project attributes (including project type, activities and operational conditions) into quantified risk profiles and mitigation mappings. This necessitates combining receptor proximity, overlap intensity, contextual sensitivity, operational conditions, and receptor vulnerability. The framework was applied to three airport case studies in Egypt—representing urban, peri-urban/desert expansion, and coastal–ecological environmental contexts—using standardized spatial preprocessing and normalized analytical scales. Validation was conducted using Monte Carlo uncertainty simulation, sensitivity analysis, Spearman rank correlation, and Cohen’s Kappa agreement analysis. The results demonstrated stable comparative risk classification across receptor categories, lifecycle phases, and impact mechanisms under moderate parameter perturbation (±15%). Cohen’s Kappa agreement values ranging from 0.71 to 0.79 indicated substantial consistency between model-generated exceedance zones and regulatory environmental classifications. In sum, the results demonstrate that receptor proximity, operational intensity, and lifecycle stage function as primary determinants of differentiated environmental risk configurations, and that the proposed framework can support transparent, reproducible, and spatially explicit environmental assessment.

Sustainability doi: 10.3390/su18115428

Authors: Anna Szewczyk Jolanta Dzwierzynska

The global construction sector is undergoing a major shift driven by Construction 4.0, where traditional structural design methods are increasingly complemented or replaced by advanced digital technologies. This systematic review evaluates how Artificial Intelligence (AI), Generative Design (GD), and Building Information Modeling (BIM) contribute to sustainable development in architecture and civil engineering. Using the PRISMA protocol, the study synthesizes current evidence on the role of algorithmic intelligence in supporting UN Sustainable Development Goals (SDGs), particularly Goals 9, 11, 12 and 13. Findings indicate that transitioning from deterministic engineering approaches to AI-based heuristic methods enables significant optimization of material use and structural mass, thereby reducing embodied carbon in the built environment. Performance-driven generative workflows and physics-informed neural networks (PINNs) emerge as key enablers of circularity and early-stage Life Cycle Assessment (LCA) integration. However, the review also identifies gaps, such as limited applications of genetic algorithms in sustainable steel structure design and the substantial energy consumption associated with large-scale AI models. The study concludes that while digital tools provide transformative potential for decarbonizing the construction sector, future research should focus on improving algorithm transparency, reducing black-box limitations, and standardizing performance metrics to support broader adoption in engineering practice. The review can be a framework to help researchers, engineers, and policymakers integrate emerging AI-tools into sustainable design and advancing decarbonized, resilient built environments.

Sustainability doi: 10.3390/su18115427

Authors: Hao Zeng Yongwei Liu Enqiang Yao Tianping Zhang

Transportation plays a fundamental role in tourism development, serving as the critical link between tourism demand and supply. China’s domestic demand-oriented strategy has positioned tourism as an important driver of economic recovery during the post-COVID-19 transition period, highlighting the urgent need to strengthen tourism system resilience. Tourism economic resilience is measured via the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, transportation accessibility is quantified using a composite index, and a Geographically Weighted Random Forest (GWRF) model is applied across 73 prefecture-level cities in the Yellow River Basin to map spatial patterns and examine the association between transportation accessibility and tourism economic resilience. The results reveal: (1) pronounced spatial disparities in both tourism resilience and accessibility, displaying a clear “core–periphery” pattern; (2) strong spatial coupling between high resilience and high accessibility in the east, and low–low clusters in the west (e.g., Qinghai, Gansu, Sichuan); and (3) a relatively strong association between transportation accessibility and tourism resilience, particularly in supporting recovery, adaptability, and renewal capacity. Other influential factors include tourist density, openness to external markets, and industrial structure. This study provides a quantitative foundation for understanding the spatially heterogeneous associations of transport infrastructure with tourism system resilience and offers both theoretical insights and practical guidance for formulating regionally differentiated, transport-led policy strategies to foster sustainable tourism development in river-basin economies.

Sustainability doi: 10.3390/su18115426

Authors: Hao Zheng Guoce Xu Xudong Qu Yang Lin Bin Wang

Land use and landscape patterns strongly influence water quality and are critical for ecological conservation within watersheds, as well as for effective water resource management. This study analyzed water quality data collected from 11 monitoring sites in the Minjiahe Watershed of Qinling Mountains, China. Redundancy analysis was used to analyze the impact mechanism of multi-scale landscape patterns and land use on seasonal water quality changes, while non-parametric change point analysis was used to quantify the key landscape thresholds that lead to sudden changes in water quality. The results indicated that the concentrations of ammonia nitrogen, available phosphorus, and total nitrogen in the river water were significantly higher during the rainy season than during the dry season (p < 0.05), representing increases of 18.93%, 30.33%, and 37.52%, respectively. The dissolved oxygen levels were 27.76% higher in the dry season than in the rainy season (p < 0.05). Landscape metrics at different spatial scales can strongly explain the spatiotemporal changes in water quality, with an explanatory rate exceeding 76%. The interspersion and juxtaposition index of forestland (IJIfor), largest patch index of forestland (LPIfor), landscape shape index of residential land (LSIres), and percentage of landscape of farmland (PLANDfar) are the main factors affecting seasonal changes in water quality. Small and discontinuous grasslands did not significantly affect water quality. To effectively mitigate the impact of landscape patterns on water quality, the following thresholds are suggested as effective management targets: at the sub-watershed scale, IJIfor < 80% and LPIfor > 94%; at the 150 m buffer scale, LSIres < 8 and PLANDfar < 8%. These determined thresholds can be used as indicators for landscape planning to reduce the risk of water quality degradation. The research results provide valuable insights for sustainable land use and multi-scale landscape planning, thereby informing strategies to enhance water quality.

Sustainability doi: 10.3390/su18115424

Authors: Uxue Leon-Aznar Maite M. Aldaya

Food waste is a global problem involving the loss of natural resources, human labour and money. This paper presents an educational proposal implemented as an exploratory pilot case study in a rural primary school classroom in Spain, aimed at raising awareness of food waste and promoting pupils’ involvement in its reduction. The Sustainable Development Goals and the European framework of sustainability competences (GreenComp) enabled the work to be aligned with current education legislation and global sustainability challenges. The intervention was assessed through a questionnaire administered before and after the implementation of the proposal to analyse students’ progress, adapted rubrics, and sets of questions used to review the content covered. The comparison between the initial and final questionnaires, analysed using the Wilcoxon signed-rank test, showed statistically significant differences (W = 3.0; p = 0.019), suggesting an improvement in students’ knowledge after the implementation of the teaching proposal. The results suggest that working from pupils’ initial misconceptions may support both understanding of key concepts related to food waste (such as the causes of food waste, use of resources in its production and the difference between expiry dates and best-before dates) and the development of sustainability competences, particularly critical thinking, systemic thinking and adaptability in consumption-related situations. Overall, this pilot study suggests that food waste can be meaningfully addressed in primary education not only through school-canteen practices, but also through classroom-based activities grounded in pupils’ prior ideas and supported by hands-on, competence-oriented activities.

Sustainability doi: 10.3390/su18115423

Authors: Weishuang Zhao Yang Li Xia Peng

As global energy demand continues to rise and the need for environmental conservation grows more urgent, solar energy has attracted substantial attention owing to its inherent cleanliness and sustainability. Perovskite solar cells (PSCs), an innovative photovoltaic technology, have shown significant improvements in photoelectric conversion efficiency (PCE) since their introduction. Nevertheless, significant challenges remain in enhancing efficiency and ensuring long-term stability. Naturally abundant and environmentally benign carbon materials represent a promising alternative. Incorporating carbon materials into PSCs can yield beneficial effects, such as controlling the crystallization rate of the perovskite layer, improving carrier transport properties, and realizing interface modification between various functional layers. This review systematically reviews the application of carbon materials in PSCs, including carbon nanotubes (CNT s), carbon dots (CDs), carbon nanofibers (CNFs), fullerenes, and their derivatives, thereby contributing to sustainable development by enhancing resource efficiency, device stability, and environmental compatibility of PSCs.

Sustainability doi: 10.3390/su18115422

Authors: Olayemi Kazeem Azeez Brima Sesay

The authors have made the following corrections to the published paper [...]

Sustainability doi: 10.3390/su18115419

Authors: Mohammad Ebrahimi Kateryna Fatyeyeva Wojciech Kujawski

Today, the development of ion exchange membranes has increased considerably in various applications, such as water treatment, energy conversion and storage, as well as environmental applications. In this study, several ion exchange membranes based on cellulose acetate propionate (CAP) and ionic liquids (ILs) were fabricated using the phase inversion method, aiming to develop more sustainable membrane materials for environmental and energy applications. Three different ILs with a similar cation and different anions (1-(4-sulfobutyl)-3-methylimidazolium trifluoromethanesulfonate [SMIM][TFS], 1-(4-sulfobutyl)-3-methylimidazolium hydrogen sulfate [SMIM][HS], and 1-(4-sulfobutyl)-3-methylimidazolium bis(trifluoromethanesulfonyl)imide [SMIM][TFSI]) were used in three concentrations (i.e., 9, 17, and 23 wt.%). The main objective of this work is to evaluate the influence of the anion structure on the membrane’s physical, morphological, hydrophilic, thermal, mechanical, and electrochemical properties. Water contact angle measurements demonstrated the weaker hydrophilicity of composite membranes containing [SMIM][TFS] (81–106°) and [SMIM][TFSI] (87–94°) in comparison with pure CAP (~79°) and CAP/[SMIM][HS] (79–83°) membranes. The CAP/[SMIM][HS] membrane showed higher elongation at break (~36%) compared with the pure CAP membrane (~24%), confirming the plasticization behavior of [SMIM][HS]. The CAP/[SMIM][TFS] membrane containing 23 wt.% of IL showed promising membrane potential, permselectivity, transport number and ion flux ratio values of 53.2 mV, 74.7%, 0.85, and 5.5, respectively, indicating its potential as a candidate for further evaluation in electrochemical membrane processes such as electrodialysis and fuel cells.

Sustainability doi: 10.3390/su18115417

Authors: Alfonso Ippolito Cristiana Bartolomei Davide Mezzino Martina Attenni Federico Rebecchini Caterina Morganti Vittoria Castiglione

The article illustrates the digital documentation workflow adopted to effectively use digital survey outcomes in supporting the knowledge and conservation of built heritage. This study was developed as part of the Project of Significant National Interest (PRIN), titled “KNOW.it Transition in Digital Age: KNOWing our background to refine our future”. The research focuses on the cities of Jaú and São Carlos, applying a rigorous methodology that combines archival research, photogrammetry, laser scanning, and 3D modelling. This approach is used to identify, analyse, and digitally reconstruct Italian-influenced eclectic architecture from the late 19th to early 20th century. The initiative supports both scholarly research and public dissemination through a digital platform that will host interactive maps, historical documents, 2D drawings and 3D models. By linking academic research with diasporic memory, KNOW.it highlights how digital tools can preserve and reactivate cultural legacies, fostering transnational heritage dialogue. The project’s use of social media further engages local communities in a participatory process, enriching its digital archive with crowdsourced memories and documents. The project opens up new possibilities for international cooperation, digital heritage practices, and the study of architectural migrations, showing how critically informed digital tools can recontextualise and enhance dispersed historical knowledge.

Sustainability doi: 10.3390/su18115421

Authors: Yang Zhao Ming Sun Qimeng Ren Huiru Wang

The impact of electric vehicle (EV) charging stations on sustainable urban transitions has become a crucial research topic due to the rapid growth of the new energy industry. However, the uneven distribution of EV charging infrastructure currently presents a major challenge to urban spatial equity and sustainable development. This study focuses on the central metropolitan area of Wuhan, positioning EV charging stations as a key mediating variable to explore how green infrastructure interacts with the built environment to drive sustainable economic vitality. Utilizing multi-source big data, the XGBoost-SHAP model, and Bootstrap mediation tests, this research identifies the non-linear thresholds and mediation pathways involved. The findings reveal that: (1) distinct built environment factors exhibit clear non-linear relationships with commercial vitality; (2) EV charging stations act as critical mediators that spatially reinforce or balance built environment variables, exhibiting pronounced spatial heterogeneity; and (3) EV charging stations show a significant partial mediation effect, with building density wielding the strongest direct influence. This study provides vital scientific support for low-carbon urban planning and sustainable infrastructure deployment by uncovering the threshold characteristics and mediating mechanisms necessary to harmonize commercial vitality with environmental and urban sustainability.

Sustainability doi: 10.3390/su18115420

Authors: Filip Dodigović Krešo Ivandić Anja Bek Jasmin Jug

Jet grouting (JG) is widely used for soil improvement, excavation support, and groundwater cut-off works, often under groundwater conditions and in proximity to sensitive receptors. The same high-energy erosion–mixing mechanisms that enable JG performance can also generate environmental and operational risks, including ground deformation, pore-water pressure transients, unintended hydraulic connectivity, accidental releases of grout or fluids, contaminant mobilisation, and groundwater-quality disturbance. This review synthesises field- and practice-based findings into a monitoring-oriented decision-support structure that links Source–Pathway–Receptor mechanisms with measurable early-warning indicators and predefined response actions. The study does not propose a new numerical or constitutive model; instead, it operationalises dispersed case-based evidence into a structured basis for project-specific monitoring and Trigger–Action Plan development. The analysis is organised into six recurring pathway classes: deformation response, pore-pressure and hydrogeological response, hydraulic incidents, contaminated-ground controls, barrier performance, and spoil/returns management. Across cases, escalation is rarely governed by a single absolute threshold. Instead, it is more reliably identified when an abnormal response increases with time, persists after jetting pauses, spreads beyond the expected influence zone, or is confirmed by more than one source of evidence, such as instrumentation, process behaviour, and field observations. Based on these patterns, the paper develops a generic, project-calibrated Trigger–Action Plan (TAP) structure to support risk-informed construction control, reduce environmental disturbance, protect groundwater and other sensitive receptors, and improve the environmental consistency of jet grouting practice.

Sustainability doi: 10.3390/su18115416

Authors: Hubang Wang Zhili Qian Qiaohan Liu Yujie Liu Hongli Wang Shimin Wei

Energy poverty poses a critical threat to global sustainable development by undermining household well-being and deepening social inequality. This study draws on data from 17,778 households across six waves of the China Family Panel Studies (CFPS) from 2012 to 2022 to examine the dynamics, determinants, and predictive patterns of household energy poverty in China. Our study also enhances and optimises the four-quadrant classification framework within the Low-Income, High-Cost (LIHC) framework, which jointly evaluates income and energy expenditure using dynamic thresholds. This approach enables us to identify not only households experiencing energy poverty but also those facing heightened vulnerability. In the sample, 7.96% were classified as energy-poor, 29.10% as at risk of energy poverty, 24.14% as at risk of income poverty, and 38.81% as not at risk, indicating that the number of households facing hidden risks far exceeds that of households identified as poor using traditional binary diagnostic methods. Next, we implement a Bayesian-optimised Extreme Gradient Boosting (XGBoost) model to improve predictive accuracy. Thus, the trained model achieved a prediction accuracy of 78%. We employ Shapley Additive exPlanations (SHAP) analysis to interpret the relative importance and interaction of explanatory variables. Our findings reveal three key patterns. First, households at risk of energy insecurity substantially outnumber those already in energy poverty, indicating a large latent vulnerable population that conventional measures often overlook. Second, housing conditions and energy expenditures remain the dominant structural drivers of energy poverty; however, financial pressures related to healthcare, education, and other non-energy expenditures increasingly intensify vulnerability. Third, Bayesian optimisation significantly enhances the model’s capacity to capture nonlinear relationships and complex household heterogeneity. By integrating dynamic measurement with interpretable machine learning, this study advances methodological approaches to energy poverty assessment and provides robust empirical evidence for early-warning systems, differentiated governance strategies, and targeted policy design in the context of China’s energy transition.

Sustainability doi: 10.3390/su18115418

Authors: Sonam Aggarwal Sheifali Gupta Deepali Gupta Yonis Gulzar Sapna Juneja Ali A. Alwan Ali Nauman

The authors would like to make the following corrections to the published paper [...]

Sustainability doi: 10.3390/su18115415

Authors: Maurizio Volpe Enrico Licitra Daniele Di Trapani Manuela Russo Tiesi Antonio Messineo Gaetano Di Bella

Sediments play a crucial role in the marine ecosystem by serving as both a sink for pollutants from human activities and a medium of exchange with aquatic environments and organisms. Chemical contaminants such as heavy metals and hydrocarbons pose significant risks due to their potential for bioaccumulation. As a result, treating marine sediments is often necessary. The present study reports the results of the experimental activities aimed at evaluating the removal performance achievable with a Low-Temperature Desorption Treatment (LTDT) on contaminated marine sediments. An LTDT was simulated by means of a lab-scale plant, with the aim of optimizing recalcitrant organic pollutant removal, evaluated by the analysis of the residual concentration of total petroleum hydrocarbons (TPH) in the sediments by varying the treatment temperature (200, 350, and 500 °C) and contact time (10, 15, and 20 min). The evolved vapors were recovered by means of an off-gas condenser system that allowed mass balances to be performed and the volatile organic compound recovery efficiency to be evaluated. Two different biochars were tested as innovative adsorbent materials, achieving a contaminant removal between 97 and 99%.

Sustainability doi: 10.3390/su18115414

Authors: Mingyue Zhang Liyu Ding Ya’nan Wang Jinyin Chen

The authors would like to make the following corrections to the published paper [...]

Sustainability doi: 10.3390/su18115413

Authors: Thao Thi Phuong Nguyen Hiroki Tanikawa

Dynamic material stock–flow analysis is widely used to assess long-lived built-environment systems, but data scarcity makes its application challenging because stock, inflow, and outflow evidence often do not form a coherent accounting structure. This study develops a reconstruction framework for dynamic material stock–flow modeling under fragmented and incomplete data conditions. The framework integrates data structure diagnosis, harmonization, historical inflow reconstruction, stock anchoring through calibration, dynamic reconstruction, and credibility assessment via empirical consistency checking, uncertainty propagation, and sensitivity analysis. The study uses Vietnam’s residential metabolism case to formalize and test a reconstruction methodology with incomplete historical inflow records, intermittent benchmark stock observations, heterogeneous classifications, and limited evidence on demolition outflows. Comparative results show that omitting historical inflow reconstruction distorts cohort depth and delayed outflow behavior, while omitting stock anchoring leads to persistent underestimation of stock levels relative to benchmarks. The analysis further shows that credible interpretation depends not only on internal stock–flow consistency, but also on compatibility with benchmarks and robustness under plausible parameter variation. The study concludes that, under data scarcity, dynamic stock–flow modeling should be approached as system reconstruction, providing a transparent and reproducible methodological basis for long-lived material systems.

Sustainability doi: 10.3390/su18115408

Authors: Jean-Claude Baraka Munyaka Pablo De Roulet Jérôme Chenal Dimitri Samuel Adjanohoun Madoune Robert Seye Tatiana Dieye Pouye Mbengue Djiby Sow Cheikh Samba Wade Derguene Mbaye Moussa Diallo Mamadou Lamine Ndiaye

This study examines patterns of digital inclusion in Ziguinchor, Senegal, using household survey data combined with spatial indicators of infrastructure and access. We construct a Digital Inclusion Index (DII) capturing realized digital practices and a Composite Digital Access Score (CDAS) reflecting enabling conditions across six domains, including technological equipment, electricity, affordability, and spatial access. The results reveal substantial variation in digital inclusion across quartiers, with strong associations between inclusion outcomes and infrastructural and socioeconomic conditions, particularly electricity reliability, device quality, and mobility constraints. A key finding is the coexistence of near-universal smartphone ownership with relatively low levels of internet use, indicating a pronounced gap between access and effective engagement. This divergence suggests that device ownership alone is insufficient to ensure meaningful digital participation. A typology combining DII and CDAS further highlights mismatches between realized use and enabling conditions, identifying groups of “under-utilizers” and “over-achievers.” The findings are consistent with multidimensional digital divide frameworks and point to the importance of both structural conditions and user capabilities. Given the cross-sectional design, results should be interpreted as conditional associations rather than causal effects. The study contributes a place-based analytical framework for diagnosing digital inclusion gaps in secondary cities and provides evidence to inform targeted, context-specific policy interventions.

Sustainability doi: 10.3390/su18115412

Authors: Micael Fidalgo Francisco Dias

Despite sustained interest in sustainable tourism, the gap between environmental concern and travel behavior is still often explained as an individual failing. This article develops an integrative conceptual review and synthesis of behavioral, discursive, organizational, household decision-making, environmental ethics, and political-economic studies to reframe this gap as a multilevel condition of environmental incoherence. The proposed model explains how values, household negotiations, platform-mediated choices, institutional incentives, and mobility regimes interact to produce and stabilize misalignment between environmental commitments and travel practices. Its main contribution is a diagnostic framework that distinguishes temporary inconsistency from structurally reproduced incoherence, identifies the mechanisms through which incoherence circulates across micro-, meso-, and macro-levels, and clarifies which institutional levers may strengthen alignment between sustainability discourse and material mobility practices.

Sustainability doi: 10.3390/su18115411

Authors: Nadia Sofia Legua-Quezada Maria Cristina Miglio-Toledo Juan Gabriel Juscamaita-Morales Luis Fernando Hurtado-Díaz Paola Jorge-Montalvo Lizardo Visitación-Figueroa

The Peruvian anchoveta fishmeal industry generates wastewater (pumping water) during the transport of fish from boats to production plants. This study represents the first evaluation in Peru of Moringa oleifera (MOD) and chitosan as bio-coagulants specifically applied to the coagulation–flocculation treatment of pumping water, providing a direct comparative analysis against traditional ferric sulfate under identical experimental conditions. The effluent is characterized by an extreme turbidity of 5,683 NTU, total suspended solids (TSS) at 3359.3 mg/L, and oils and fats at 451.3 mg/L, and it was treated using optimized doses: 4.0 g/L for MOD and 0.2 g/L for chitosan. The results demonstrate that natural alternatives achieve turbidity removal exceeding 97.5%, matching the efficiency of inorganic salts. Notably, chitosan achieved 88.59% TSS removal with no significant statistical difference (p > 0.05 according to the Kruskal–Wallis test) from ferric sulfate, while MOD excelled in oil reduction (37.84%) compared with chitosan. Beyond treatment efficiency, this research fills a gap in circular economy data by identifying that the resulting sludge, containing >4% non-toxic nitrogen, is suitable for composting. These findings establish a new renewable benchmark for the Peruvian fishing industry’s transition toward sustainable, zero-waste water management.

Sustainability doi: 10.3390/su18115410

Authors: Jianhui Wu Xiangting Huang

With global supply chain restructuring and the rapid development of the digital economy, improving supply chain resilience has become a critical issue for achieving sustainable development. This study empirically investigates the impact of data asset information disclosure on supply chain resilience using a sample of Chinese A-share listed companies from 2012 to 2024. The findings reveal that data asset information disclosure significantly enhances corporate supply chain resilience. This conclusion remains robust after a series of robustness tests (excluding impression management risk, alternative measurement of the core explanatory variable, and sample exclusion of special industries and shock periods) and endogeneity treatments (lagged regression, instrumental variable approach, and propensity score matching). Mechanism analysis indicates that disclosure enhances resilience by promoting technological innovation and alleviating financing constraints. Heterogeneity analysis shows that the positive effect is more pronounced in non-state-owned enterprises, firms in core supply chain positions, enterprises with high supply chain concentration, regions with a higher degree of marketization, and industries with low competition intensity. This study contributes to the literature on sustainable supply chain governance and offers practical implications for strengthening supply chain resilience and achieving high-quality sustainable development.

Sustainability doi: 10.3390/su18115409

Authors: Longfei Ren Zhenli Wang

Biosafety laboratory construction projects are characterized by high technical complexity, strict safety requirements, and potential environmental risks, making the improvement of their green performance essential for both biosafety governance and sustainable construction. However, existing studies have paid insufficient attention to how different types of environmental regulation influence green performance in this specialized construction context. To address this gap, this study investigates the effects of command-and-control, market-incentive, and public-participation environmental regulation on three dimensions of green performance: green process innovation, green management innovation, and environmental performance. Three hypotheses were proposed to examine these relationships. Based on 372 valid questionnaire responses from professionals and enterprises involved in biosafety laboratory construction projects in China, this study used SPSS 27.0 and AMOS 26.0 to conduct reliability and validity tests, confirmatory factor analysis, structural equation modeling, and supplementary regression analysis. The results show that command-and-control environmental regulation significantly promotes green process innovation, green management innovation, and environmental performance, with standardized path coefficients of 0.316, 0.250, and 0.200, respectively. Public-participation environmental regulation has stronger positive effects on the three dimensions, with standardized path coefficients of 0.888, 0.874, and 0.808, respectively. In contrast, market-incentive environmental regulation does not significantly affect green process innovation, green management innovation, or environmental performance. These findings indicate that mandatory regulatory requirements and public-participation mechanisms are more effective than current market-based incentives in improving the green performance of biosafety laboratory construction projects. This study enriches research on environmental regulation and green performance in specialized infrastructure projects and provides practical implications for strengthening environmental governance, public participation, and incentive policy design in biosafety laboratory construction.

Sustainability doi: 10.3390/su18115407

Authors: Ana Asensio-Ciria Carmen De-Pablos-Heredero Jose Luis Montes Botella Antón García Martínez

This research mapped mentoring typologies implemented by business incubators in Spain and examined the role of these typologies in fostering sustainable entrepreneurship. Using a quantitative multivariate approach, this study identified and classified mentoring models on the basis of 28 variables related to the mentoring process. The analysis drew on data from the Funcas 2025 survey of Spanish business incubators, which provided detailed information on mentoring practices across the participating incubators (initial responses: n = 100; final analytical sample after listwise deletion of missing values: n = 93). Principal component analysis was applied to extract the main latent dimensions underlying mentoring activities, and cluster analysis was subsequently used to group incubators into homogeneous mentoring typologies. The analysis identified three distinct mentoring profiles: (i) advanced mentoring, characterized by formalized programs with systematic evaluation, rigorous mentor selection, and continuous training; (ii) moderate mentoring, defined by partial integration into incubation services and the use of basic monitoring and evaluation mechanisms; and (iii) incipient mentoring, grounded ad hoc interactions, low formalization, and the absence of structured evaluation systems. Incubators with structured, continuous, and expert-driven mentoring systems were associated with higher entrepreneurial survival rates and stronger contributions to sustainable business development. From a public policy perspective, the findings highlighted mentoring as a strategic policy instrument for advancing Sustainable Development Goals related to Decent Work and Economic Growth (SDG 8), Industry, Innovation and Infrastructure (SDG 9), and Sustainable Cities and Communities (SDG 11). The proposed mentoring typology provided an evidence-based framework to support differentiated incubation policies, improve the targeting of public resources, and design stage-specific mentoring interventions. By moving beyond uniform policy approaches, public authorities can more effectively strengthen entrepreneurial ecosystems and promote resilient, innovative, and sustainable territorial development.

Sustainability doi: 10.3390/su18115405

Authors: Mengchen Lian Yanjun Li

Traditional villages represent vital living heritage in China. We develop a multi-scale eco-coupling framework integrating GIS spatial analysis and 3D laser scanning to analyze the natural and social environment, spatial patterns, and architectural forms across macro–meso–micro levels in traditional villages of southern Shaanxi, and use partial least squares structural equation modeling (PLS-SEM) to test the hypothesized cross-scale pathways. The results show significant spatial clustering, mainly in the water-adjacent low-mountain valleys and under moderate gradients of GDP, population density, and road density. The morphology is classified as clustered, linear, or scatter shaped, while buildings are dominated by courtyard, patio, and single-row layouts with timber structures, rammed earth or stone walls, and double-pitched roofs. After reliability and validity checks, the PLS-SEM confirms significant macro–meso–micro pathways, with the meso scale as a key mediator. Overall, the study reveals that persistence depends on long-term coupling among multi-scale factors, providing theoretical and methodological support for conservation and sustainable development.

Sustainability doi: 10.3390/su18115406

Authors: Tien-Chun Ho Hsuan-Shih Lee

Smart shipping and achieving net-zero emissions have become pressing priorities in maritime transport, yet limited research has integrated sustainable shipping development with green finance decision-making. To address this gap, this study applies the AHP–RDEMATEL–TOPSIS approach to analyze the interrelationships and relative importance of key sustainability factors and to identify optimal green financing instruments. Incorporating ESG dimensions, the research conducted a survey of large international exporters in Taiwan and senior managers of shipping companies. The results reveal that green infrastructure is the most critical factor for container shipping lines, while energy efficiency and renewable energy technologies are dominant for bulk carriers and shippers. Corporate reputation and image emerge as primary factors impacted across all three groups. In financing decisions, green bonds are most suitable for container lines, whereas green equities are best suited for bulk carriers. This study bridges the theoretical gap between sustainability assessment and finance, providing practical guidance for shipping companies’ financial departments seeking to align decarbonization goals with effective green financing solutions. Ultimately, the primary contribution of this study lies in establishing an empirically validated, multi-criteria decision support framework that empowers maritime stakeholders to systematically optimize their green investment portfolios amid the global transition towards net-zero emissions.

Sustainability doi: 10.3390/su18115403

Authors: Xiaomeng Fu Pei Zhang Baokun Yang Zhijun Li

Driven by the national Rural Vitalization Strategy, regional clustered development has become an essential approach to alleviate fragmented rural construction and shift isolated village governance toward integrated regional coordination. Against the research gap that most existing rural living environment (RLE) evaluations focus merely on individual villages while neglecting synergistic interaction within village clusters, this study aims to construct a targeted RLE performance evaluation framework from the perspective of cluster synergy, and further reveal spatial differentiation characteristics and developmental bottlenecks of rural settlements in metropolitan fringe tableland areas. Taking the Tangcun area of Bailuyuan in Xi’an as a typical case, this study adopts semi-structured interviews and qualitative grounded theory to extract core evaluation dimensions and establish a multi-layered RLE performance index system. On this basis, the Analytic Hierarchy Process (AHP) is employed to determine indicator weights and conduct quantitative performance evaluation. The results indicate that RLE performance presents an obvious topographical gradient following the pattern of tableland clusters > slope clusters > gully clusters, and exhibits a typical characteristic of non-material dimension convergence versus material dimension differentiation. The core constraints of local clustered development lie in unbalanced cross-cluster resource allocation, weak functional coordination, and the absence of sound public service sharing mechanisms. Corresponding optimization paths targeting spatial planning, facility allocation, ecological and cultural coordination, and multi-stakeholder governance are finally proposed. This study provides theoretical references and practical implications for RLE improvement and coordinated revitalization of similar loess tableland and metropolitan fringe village clusters.

Sustainability doi: 10.3390/su18115390

Authors: Midori Kato Hisashi Kato-Noguchi

Water hyacinth (Pontederia crassipes Mart.) is native to the Amazon basin. It has spread to freshwater ecosystems in over 80 countries in tropical, subtropical, and warm temperate regions. Due to its invasive nature, water hyacinth is listed among the world’s 100 worst invasive alien species. Infestations of water hyacinth affect the abiotic components of these ecosystems, including water evaporation, flow, and quality; oxygen and nitrogen levels; sunlight transmission; and greenhouse gases. These changes reduce the abundance and diversity of primary producers in the food web, including phytoplankton and aquatic plants. Consequently, these alterations affect consumers in the food web, including zooplankton, invertebrates, fish, and birds. A negative correlation has often been observed between water hyacinth infestations and the abundance and diversity of these organisms, particularly native species. However, the abundance of some introduced species among these consumers has increased due to water hyacinth infestations. These changes alter the structure and function of natural ecosystems compared to what they were before infestations occurred. Infestations also negatively impact daily human activities and livelihoods, harming local communities and increasing disease transmission. Global warming and the eutrophication of freshwater ecosystems allow water hyacinth to spread into additional non-native areas in high latitudes, thereby increasing the threat it poses. Water hyacinth also contributes to global warming by increasing methane emissions. Over the past century, management strategies have shifted toward restoring the structure and function of ecosystems by progressively integrating various sectors. The infestation of water hyacinth is a complicated, site-specific process influenced by time, climate, existing biotic and abiotic factors, and ecosystem resilience. Therefore, long-term monitoring of environmental outcomes is essential for developing sustainable, site-specific strategies. Robust evaluation systems are necessary to track the efficacy of interventions and to understand the broader ecological ramifications of management strategies. Water hyacinth is still sold in some local markets for ornamental purposes. Raising public awareness of its invasive characteristics is necessary.

Sustainability doi: 10.3390/su18115404

Authors: Răzvan-Andrei Polcovnicu Sebastian-Valeriu Hudișteanu Nicolae Țăranu Dragoș Ungureanu Marius Alexa Iuliana Hudișteanu Nelu-Cristian Cherecheș Florin-Emilian Țurcanu Cătălin Onuțu Alexandru-Florin Mustiață

This study presents an experimental investigation on the electrical performance, durability, and sustainability of different types of photovoltaic panels subjected to controlled climatic conditions and simulated solar radiation. Four photovoltaic technologies were analyzed, including monocrystalline, polycrystalline, and two semi-flexible panels, to evaluate their behavior under thermal stress. The experimental methodology consisted of repeated freeze–thaw cycles conducted in a double climatic chamber, with temperatures varying between −18 °C and +5 °C. Each panel was subjected to up to 500 cycles designed to reproduce repeated freeze–thaw environmental conditions representative of moderate cold-climate operation. At predefined intervals, the electrical characteristics of the panels were assessed using a solar radiation simulator based on high-pressure mercury vapor lamps, ensuring controlled and repeatable irradiation conditions. The results indicate that all tested panels exhibited relatively stable open-circuit voltage and output current values throughout the investigated thermal cycling interval, with only minor fluctuations observed during the experimental measurements. No visible macroscopic structural degradation and no major variations in the monitored electrical parameters were identified during the investigated testing conditions. Semi-flexible panels demonstrated comparable behavior to rigid panels, highlighting their potential for applications requiring mechanical adaptability. From a sustainability perspective, the observed durability and performance stability contribute to extending the operational lifetime of photovoltaic systems, reducing maintenance needs and material replacement rates. The findings provide comparative experimental observations regarding the evolution of selected electrical parameters under repeated moderate freeze–thaw exposure conditions.

Sustainability doi: 10.3390/su18115402

Authors: Xiangman Chen Xuezhou Liu

To resolve severe urban‒rural contradictions and promote urban‒rural integration (URI), China successively implements two national strategies: new urbanisation (NU) and rural revitalisation (RR). In Economic Geography, the URI system is one type in the human‒earth interaction system, composed of urban and rural areal subsystems, and RR and NU are its two strategic driving elements. This study aims to reveal the intrinsic logic behind how RR and NU synergistically optimise the URI system’s operation and drive its evolution towards high-quality development. Combining analysis methods and synthesis methods in systems theory, this study clarifies the connotations of RR, NU, and their five complementary sub-dimensions in industry, ecology, society, space, and economy, and fully elucidates the coupling mechanisms of RR and NU, using specific cases of URI worldwide as illustrative examples. The coupling mechanisms of RR and NU include two parts: the coupling mechanisms in the above five aspects, respectively, and the cross-fusion relationships among these aspects. The coupling mechanisms reflect the dynamic process of RR and NU mobilising various other elements to optimise the URI system’s operation and evolution. Holding the systematic concept that city and village are originally a unity, three paths of dissolving the main obstacles to URI and promoting high-quality URI are proposed: reforming institutions that hinder the free flow of urban‒rural factors, achieving broader and deeper urban‒rural industry integration, and improving rural public service supply levels. This study constructs a theoretical framework for understanding the URI system’s driving mechanisms and evolution logic, enriching the content of URI system theory and providing implications and a reference for evaluating URI quality and formulating policies for improving URI quality.

Sustainability doi: 10.3390/su18115401

Authors: Ieva Mockeviciene Danute Karcauskiene Alvyra Slepetiene Monika Vilkiene Regina Repsiene Zilvinas Kryzevicius Sandra Gabrilaviciene

Soil pH is a key regulator of soil chemical processes, organic matter transformation, and ecosystem functioning in acid soils. This study examines how pH gradients induced by long-term liming affect soil chemical properties, aluminum dynamics, and soil organic carbon (SOC) stabilization in Retisols under plant-derived organic inputs. The study was conducted at six soil pH levels (pHKCl from 3.9–4.0 to 6.5–6.7), which reflect a gradient of acidity conditions. Soil chemical parameters, SOC content and fractions, humic substance composition, aluminum forms, and soil respiration (CO2 release under laboratory conditions) were analysed. Increasing soil pH significantly reduced aluminum concentrations (by up to 59%) and improved nitrogen and phosphorus availability, indicating a gradual reduction in chemical limitations associated with soil acidity. Soil pH strongly controlled both SOC content and quality. The highest SOC content was observed at pH 6.0–6.1, and strongly acidic conditions favored the accumulation of more labile carbon forms. As the pH increased, there was a clear shift towards more stable organic matter, as indicated by higher humic acid content, an increased HA/FA ratio, and a threefold increase in the organic carbon stability index. At the same time, the reduced water-extractable organic carbon content indicated reduced carbon mobility and improved physicochemical stabilization. Microbial activity increased with increasing pH, but showed a nonlinear response, reflecting a balance between increased mineralization and carbon stabilization processes. These data indicate that soil pH primarily determines SOC stabilization pathways, rather than just total carbon accumulation. These results suggest that soil pH may influence SOC stabilization through changes in aluminum dynamics, organo-mineral interactions, and microbial processes, supporting previously reported mechanisms of carbon stabilization in acid soils. The optimal pH range of 5.5–6.1 promotes favorable interactions between nutrient availability, microbial processes, and organic–mineral associations, supporting long-term soil functionality. This study highlights liming as a key strategy for regulating soil biogeochemical processes and improving the sustainability of acid soil management.

Sustainability doi: 10.3390/su18115400

Authors: Ashish Tripathi Mohd Tauseef Khan Anurag Tripathi

The Balanced Whale Optimization Algorithm (BWOA) is proposed to address the optimal power flow (OPF) problem in grids incorporating flexible AC transmission systems (FACTS) and renewable energy sources. The standard Whale Optimization Algorithm (WOA) is enhanced through the integration of Lévy Flight (LF) dynamics for global exploration and Chaotic Local Search (CLS) for refined exploitation, producing a balanced search that mitigates premature convergence and local-optima stagnation typical of metaheuristic OPF solvers. The BWOA is benchmarked on the modified IEEE 30-bus system under both fixed and dynamic loading conditions and against five state-of-the-art metaheuristics (ALCPSO, CLPSO, MFO, SaDE, and the standard WOA) across eight study cases. Across the full set of cases, the BWOA delivers, on average, lower gross cost (mean reduction of approximately 1.3–6.8% relative to the comparators), lower active power loss (mean reduction of 6–22%), and lower expected gross cost under load and renewable uncertainty (mean reduction of 0.5–4.9%). The BWOA additionally attains the leading or co-leading position in the Friedman rank test (FRT) in the majority of cases, while incurring only a marginal runtime overhead (≤1% over the next-fastest comparator). The algorithm shows slightly higher voltage deviations in some scenarios, which is discussed as a controllable trade-off. The results indicate that the BWOA is a robust and cost-effective solver for OPF in grids with FACTS devices and stochastic renewable generation.

Sustainability doi: 10.3390/su18115398

Authors: Abdul Waheed Muhammad Fazil Michele Biasutti

Developing countries often face challenges in the effective implementation of the Sustainable Development Goals (SDGs). Within diverse sustainability discourses, a context-specific understanding of the SDGs contributes to the development of sustainability awareness (SA), reflecting individuals’ recognition of the importance of sustainability and its dimensions. Empirical evidence highlights the need for reliable and valid measures of sustainability awareness (SA) among learners in educational contexts. In response, this study reports the development and psychometric validation of the Sustainability Awareness Scale (SAS), a self-report instrument designed to assess pre-service teachers’ awareness across three dimensions: economic, environmental, and social. The scale was administered to undergraduate pre-service teachers in Bachelor of Science (Honours) in Education programs at Pakistani universities. The sample was split into two independent subsamples for exploratory factor analysis (EFA; n = 144) and confirmatory factor analysis (CFA; n = 145). EFA supported a three-factor structure, and CFA confirmed a refined 12-item model with acceptable model fit (χ2/df = 1.68, RMSEA = 0.068, SRMR = 0.056, CFI = 0.93, TLI = 0.91). Construct validity was supported by acceptable composite reliability (CR = 0.715–0.780), average variance extracted (AVE = 0.489–0.569), and heterotrait–monotrait ratio (HTMT = 0.78–0.83) values. Internal consistency was satisfactory for the full scale (α = 0.872; ω = 0.875) and acceptable for all subscales. The findings indicate that the SAS is a reliable and contextually relevant instrument for assessing SA among pre-service teachers in Pakistan. The scale offers a practical tool for evaluating and strengthening Education for Sustainable Development (ESD) initiatives and supports the design of sustainability-focused educational programs.

Sustainability doi: 10.3390/su18115399

Authors: Kecun Chen Hong Chen Zhaoqi Li

Perceived overqualification has attracted widespread scholarly attention; however, its impact on employees’ innovative behavior remains inconclusive, particularly from a sustainability perspective. Drawing on person–job fit theory, self-determination theory, and social identity theory, this study develops an integrated framework to examine the mechanisms and conditions under which perceived overqualification inhibits innovative behavior, with a focus on the sustainable utilization of human capital. This study proposes that perceived overqualification undermines employees’ sense of job meaningfulness, thereby reducing intrinsic motivation and limiting sustained engagement in innovative activities. Professional identity is introduced as a key boundary condition that buffers this negative process. Based on a three-wave time-lagged dataset collected from employees in high-tech and knowledge-intensive organizations, the findings reveal that perceived overqualification is negatively associated with innovative behavior. Job meaningfulness mediates this relationship, while professional identity weakens the negative effect of overqualification on job meaningfulness and further attenuates its indirect negative impact on innovative behavior. Overall, the findings suggest that the consequences of perceived overqualification depend on employees’ ability to maintain meaning and professional identity under conditions of misfit. This study highlights the importance of activating underutilized human capital and provides important implications, from a sustainable human resource management perspective, for enhancing resource utilization efficiency and fostering sustainable innovation.

Sustainability doi: 10.3390/su18115395

Authors: Hua Cui Yunyan Li

Understanding the synergistic effects of pollution reduction (PR) and carbon mitigation (CM) and their driving factors is essential for achieving environmental improvement and dual-carbon targets. On the basis of panel data from 13 cities in the Beijing–Tianjin–Hebei (BTH) urban agglomeration from 2010 to 2023, this study analyzed the spatiotemporal evolution of air pollutant and carbon emissions. The synergistic effects of PR and CM were quantified using the co-control effect coordinate system and vector angle analysis, and their underlying driving mechanisms were examined using a geographically and temporally weighted regression model. Results showed that air pollutant emissions in the BTH region declined substantially over the study period, whereas carbon emissions increased in all cities, except Beijing. The spatial patterns of air pollutant and carbon emissions were largely consistent, with Tangshan being a high-emission hotspot and northern Hebei cities being low-emission areas. Most cities were in a “pollution reduction but carbon increase” stage, but the overall synergistic degree gradually improved. The synergistic effects were positively driven by green travel and technological R&D and negatively influenced by economic development, energy utilization, and transportation structure. The positive effect of industrial structure on PR and CM weakened, and spatial heterogeneity was evident. Economic development and technological R&D exerted strong influences in southern Hebei. Energy utilization and transportation structure had pronounced effects in northern Hebei. Industrial structure had remarkable effects in cities surrounding Beijing and Tianjin. Moreover, green travel demonstrated spatial heterogeneity, exerting a facilitative effect on emissions in southern Hebei cities. These findings provide policy implications for promoting the synergistic effects of PR and CM in the BTH urban agglomeration.

Sustainability doi: 10.3390/su18115397

Authors: Lujun Lin Qifeng Ding Xinzhan Li Haoji Hu Qun Wang Houkui Zhou

With the rapid increase in urban waste, efficient and accurate garbage classification has become pivotal for sustainable development. However, existing methods often grapple with high computational complexity, limited adaptability to diverse waste types, and challenges in deploying on resource-constrained devices. To address these issues, this study proposes GMamba, a lightweight garbage classification model based on the Mamba architecture. GMamba employs a hierarchical structure, integrating two modules, the GML Block for efficient local–global feature fusion and the GMC Block for fine-grained spatial dependency modeling, achieving robust feature aggregation while minimizing computational redundancy. Evaluations on the Huawei Cloud Garbage Classification dataset and the custom MixTrash dataset demonstrate that GMamba, with only 17.18 M parameters, achieves Top-1 accuracies of 92.75% and 92.58%, respectively. While scaling evaluations indicate that VMamba maintains a marginal lead in absolute Top-1 accuracy, the proposed GMamba delivers a substantially superior balance between accuracy and computational efficiency, reducing parameter count by 45% and FLOPs by 47.3%, thus demonstrating promising deployment potential for resource-constrained edge systems.

Sustainability doi: 10.3390/su18115396

Authors: Bo Yuan Baoxing Sun Weibing Du Hui Wang Wei Ge Zongkun Li Yadong Zhang

Ecological water supply has been integrated into the water supply scope of numerous water diversion projects, yet ecosystem complexity makes ecological benefit assessment difficult. Traditional quantitative methods for water supply benefits mainly focus on economic benefits from productive and domestic water use, ignoring the ecological benefits and real-time benefit changes over the project service period. This study categorizes ecological water supply separately in benefit calculation and considers enhanced ecosystem service value brought by ecological water replenishment. Based on emergy analysis, the water resource values of domestic, productive, and ecological water supply are calculated individually, and a water supply benefits evaluation model is established in combination with corresponding water supply volumes. A dynamic evaluation method for the project service period is further proposed using a Grey Model (1,1). Verified via the Yangtze-to-Huaihe Water Diversion Project (Henan section), results indicate that from 2021 to 2070, comprehensive water supply benefits increase yearly from 5.19 billion yuan to 16.18 billion yuan. Productive water supply provides the largest benefits (67–74%), followed by urban domestic (19–25%), rural domestic (5–7%), and ecological water supply (1–2%). This study constructs a comprehensive, systematic, and dynamic evaluation system, supporting the holistic assessment of the long-term economic and environmental impacts of water diversion projects.

Sustainability doi: 10.3390/su18115394

Authors: Yuefeng Zhang Bo Zhang Wen Huang Yushen Wang Jialei Xu Zhenbei Zhang

Rapid urban expansion has intensified interactions between human disturbance and urban ecological processes, creating an urgent need for robust and urban-sensitive assessment tools. To improve the applicability of conventional remote sensing ecological evaluation in cities, this study develops an Urban Remote Sensing Ecological Index (URSEI) by incorporating an Urbanization Index (UI) into the RSEI-based PCA framework. Multi-temporal Landsat observations acquired during the peak vegetation season were used to construct annual ecological indicators, thereby improving the temporal representativeness of ecological assessment. Taking Hangzhou, China, as a case study, URSEI was applied to examine ecological quality dynamics inside and outside the Ecological Conservation Redline (ECR) from 2010 to 2024, together with temporal trend characteristics, indicative persistence patterns, and meteorological associations. The results show that URSEI generally achieved higher first principal component contribution rates than RSEI, suggesting stronger integration of ecological information within the PCA framework. UI exhibited the strongest negative correlation with URSEI among the stress-related indicators, highlighting the importance of explicitly representing urbanization-related disturbance in urban ecological assessment. Citywide ecological quality displayed a fluctuating but weakly improving tendency over the study period, while the ECR consistently maintained higher URSEI values than the overall urban area. However, most detected temporal changes were statistically non-significant, indicating that ecological conditions remained broadly stable rather than showing pronounced improvement or degradation. Temperature-related thermal conditions were predominantly negatively associated with URSEI, whereas precipitation showed mainly positive relationships and a stronger association with URSEI among the climatic variables examined. Overall, URSEI provides an urbanization-aware framework for long-term ecological monitoring and offers a useful basis for ecological management and sustainable planning in rapidly urbanizing regions.

Sustainability doi: 10.3390/su18115393

Authors: Percy Antonio Vilchez Olivares Brandelt Jesús Astorga De La Cruz

Expanding ESG disclosure mandates under the Corporate Sustainability Reporting Directive (CSRD) and the International Sustainability Standards Board (ISSB) have driven rising demand for artificial intelligence (AI) and data analytics capable of supporting sustainability reporting and verification at scale. Nevertheless, the scholarly literature remains dispersed across discrete disciplinary fields—natural language processing, machine learning, auditing, and regulatory compliance—with limited integrative synthesis. To address this gap, the present study conducts a PRISMA 2020-compliant systematic review of 45 peer-reviewed articles indexed in Scopus and published between 2020 and 2025. The methodology combines bibliometric mapping through VOSviewer with qualitative thematic content analysis. Findings document a rapidly expanding field exhibiting a compound annual growth rate of 91.9%. Four principal thematic dimensions emerge: (i) NLP and text mining for ESG disclosure analysis; (ii) machine learning for ESG scoring and corporate performance; (iii) AI-enabled ESG assurance, auditing, and governance; and (iv) regulatory frameworks and the digital transformation of sustainability reporting. The evidence indicates that AI is progressively reshaping ESG disclosure from a largely narrative and self-reported practice into a data-driven, independently verifiable transparency system. These developments carry substantive implications for regulators, corporate practitioners, assurance providers, and investors seeking to strengthen the reliability and comparability of sustainability disclosures.

Sustainability doi: 10.3390/su18115391

Authors: Chao Yuan Shizhen Guo Weilin Xu Qiong Liu

Building a sustainable workplace necessitates a fundamental commitment to employee safety and psychological well-being, particularly in high-risk sectors like construction. While individual unsafe behavior is a primary cause of accidents, the psychological mechanisms linking organizational practices to safety outcomes remain underexplored from an industrial-organizational psychology perspective. This study examines the relationship between safety ritual sense (a psychological outcome of socio-affective organizational practices) and the safety behavior of construction workers, with safety psychological capital (a positive psychological resource) tested as a mediator. Data were collected via questionnaire surveys from 444 construction employees in China and analyzed using structural equation modeling. The results confirm a significant positive correlation between safety ritual sense and safety behavior. Furthermore, safety psychological capital significantly partially mediates this relationship, with its four dimensions—confidence, optimism, hope, and resilience—each playing distinct mediating roles. This research elucidates a critical psychological pathway through which ritualized organizational practices enhance safety performance. It provides empirical evidence that fostering safety rituals to cultivate employees’ psychological capital is an effective industrial-organizational psychology intervention, contributing directly to the development of safer, healthier, and more sustainable modern workplaces.

Sustainability doi: 10.3390/su18115392

Authors: Yufei Zhang Yong Zeng Biqi Mao Yuanyuan Xie Jiaxin Liu

Recycling residual plastic film is an important measure to prevent plastic pollution and achieve farmland sustainability, with farmers’ participation being the key. To understand the determinants of farmers’ participation in the recycling of residual plastic film, this study developed an extended TPB framework by introducing moral norm and responsibility attribution as additional explanatory constructs. Based on questionnaire responses from 429 cotton farmers in southern Xinjiang, China, the proposed relationships were examined through structural equation modeling. The empirical results indicated that recycling intentions were mainly determined by attitudes and perceived behavioral control, and responsibility attribution had a positive effect on subjective norm. Furthermore, the influence of moral norm served as a minor mediating factor in the connection between subjective norms and intentions to recycle. These findings not only deepen the understanding of the behavioral mechanisms underlying residual film recovery, but also provide policy-relevant insights for strengthening government efforts to address plastic film pollution.

Sustainability doi: 10.3390/su18115388

Authors: Yuzeng Xin Xihao Zeng Jingru Gao Guilin Xu

In the context of extreme climate events and increasingly stringent environmental regulation, insufficient corporate green resilience has become a micro-level bottleneck to achieving China’s “dual-carbon” targets. Using panel data on Chinese A-share listed firms from 2015 to 2023, this study treats the approval of the National Pilot Zone for Artificial Intelligence Innovation Applications as a quasi-natural experiment and employs a double machine learning (DML)–augmented difference-in-differences framework to estimate the causal impact of the policy on firms’ green resilience. We find that the pilot-zone policy significantly increases corporate green resilience by about 32%, with stronger effects among high-tech firms, non-heavily polluting industries, regulated sectors, and large enterprises. Mechanism analyses show that the policy improves green resilience through four channels—accelerating green innovation, enhancing supply-chain efficiency, alleviating financing constraints, and reducing operating costs—with innovation and supply-chain efficiency playing dominant roles. These findings provide firm-level causal evidence that AI-oriented place-based policies can strengthen firms’ capability to sustain green development under disturbances and inform the coordination of the “Digital China” and “Dual Carbon” agendas.

Sustainability doi: 10.3390/su18115389

Authors: Yi Ge Honggang Xue

Common prosperity is an important feature of Chinese modernization, and human–environment interaction is the underlying geographical foundation of regional development. So, the level of coupling coordination of human–environment interaction directly affects the advancement process and regional balance of multidimensional common prosperity. This study took Guangdong Province as the study area, selected long-term municipal panel data, LandScan data, and construction land data from 2010 to 2025, and used the coupling coordination model, random forest, and other methods to systematically carry out an empirical study on the relationship between human–environment interaction and multidimensional common prosperity. The results showed that the coupling coordination degree of human–environment interaction and the level of multidimensional common prosperity in Guangdong Province both showed an overall upward trend, and both exhibited the spatial characteristics of core polarization and peripheral lag. At the same time, the effect of the coupling coordination of human–environment interaction on common prosperity showed significant dimensional heterogeneity. Specifically, the coupling coordination of human–environment interaction could stably promote prosperity development, but it showed a threshold effect of first promoting and then inhibiting in the dimension of shared equity, while its driving effect on the dimension of ecological sustainability was relatively weak. This study not only enriched the relevant explanation of the driving mechanism of common prosperity from a geographical perspective but also provided scientific decision reference for optimizing the allocation of human–environment elements, promoting coordinated regional development, and realizing sustainable development practices in which prosperity and equity improved at the same time.

Sustainability doi: 10.3390/su18115386

Authors: Ali Mardani Hatice Gizem Şahin Öznur Biricik Murat Tuyan

This study investigates the influence of fly ash (FA) content and aggregate type on the mechanical performance and environmental efficiency of concrete. Twelve concrete mixtures were prepared using limestone and basalt aggregates, with FA replacement levels of 0%, 15%, and 35% and water-to-binder (w/b) ratios of 0.4 and 0.7. Compressive strength (CS), the modulus of elasticity (MoE), water absorption, and freeze–thaw resistance were measured. Basalt aggregates enhanced the CS and MoE while reducing water absorption and freeze–thaw deterioration compared to limestone. Although a higher FA content lowered early-age strength and stiffness, it contributed to long-term improvements and greater eco-efficiency. A new MoE prediction model incorporating CS, unit weight, aggregate type, and FA content demonstrated better accuracy than current standards. Assessment of binder usage and CO2 intensity confirmed that all mixtures remained below the average literature values. The optimal combination was achieved with basalt aggregates, a high FA content, a low w/b ratio, and extended curing, highlighting strategies for sustainable concrete production.

Sustainability doi: 10.3390/su18115385

Authors: Weixiang Sun Jiayi Zheng Peilin Lan Haoran Lu Kun Xing

Against the backdrop of global warming and the ‘warming and wetting’ trend in north-western China, changes in seasonal snowpack and glacial ice in high-altitude cold regions directly impact water security in inland river basins. At present, there is a paucity of systematic research concerning the long-term evolution of snow and ice cover, multi-scale climate responses and future trends in the source region of the Keriya River on the northern slope of the Kunlun Mountains. To address this, this study utilised Landsat remote sensing imagery and meteorological station data from 2005 to 2024. Employing a multi-model fusion framework that integrates various machine learning and time-series models—including random forests, gradient boosting trees and ARIMA—the research incorporated trend factors, climate cycle identification and probabilistic modelling of extreme events to systematically analyse the spatiotemporal variability of snow/ice coverage and its multiscale coupling relationships with air temperature and precipitation. Given the inherent limitations of optical remote sensing methods in distinguishing between seasonal snow and glacial ice, this study defines the extracted coverage type as snow/ice coverage. Given the inherent limitations of optical remote sensing methods in distinguishing between seasonal snow and glacial ice, this study defines the extracted coverage type as snow/ice coverage. The results indicate that: (1) the annual average snow/ice cover percentage in the study area shows a non-significant decreasing trend (−0.69%/year, p > 0.1); within the year, it exhibits a pattern of accumulation in winter and melting in summer, with a peak in January (average 63.2%) and a trough in August (average 11.6%); (2) snow/ice cover percentage increases significantly with altitude; the annual average SICP in the <2000 m elevation zone is 5.2%; in the 2000–3000 m and 3000–4000 m altitude ranges, this rises to 5.7% and 8.3%, respectively, representing the primary seasonal snow/ice distribution zones; in areas above 6000 m, the annual average reaches 70.3%, constituting a zone of perennial stable snow/ice cover; (3) the relationship between snow/ice and temperature and precipitation exhibits significant time-scale dependence: correlations are weak on an annual scale (temperature R = −0.25, precipitation R = −0.14), but significantly strengthen on a monthly scale and exhibit seasonal differentiation; during the melting season, temperature exerts a dominant negative influence (August R = −0.35), whilst during the accumulation season, solid precipitation provides a positive supplement (February R = 0.34), with the strongest correlation with temperature occurring in September (R = −0.50); (4) it is projected that between 2025 and 2044, snow and ice cover will follow a fluctuating downward trend (averaging an annual decrease of roughly −0.12%), falling to approximately 29% by 2044; at the same time, temperatures are expected to continue rising (+0.035 °C per year), whilst precipitation will increase slightly (+0.4% per year). The results of this study provide a sound scientific basis for formulating sustainable water resource management strategies for the northern flank of the Kunlun Mountains and optimising measures to regulate snowmelt runoff. They are of great importance for safeguarding the stability of the oasis ecological systems in the Keriya River basin and ensuring the sustainable development and utilisation of water resources.

Sustainability doi: 10.3390/su18115384

Authors: Jorge Vareda Gomes Catarina Moreira

Agri-food systems account for a substantial share of global greenhouse gas (GHG) emissions, with a significant proportion arising from upstream supply-chain activities beyond direct operational control. In this context, effective decarbonization requires systematic assessment of emissions across all life-cycle stages. This study applies an ISO 14040/44-compliant cradle-to-grave Life Cycle Assessment (LCA) to CERELAC® infant cereal, a processed dairy-based product, to quantify Scope 1, Scope 2, and Scope 3 emissions and identify mitigation pathways across the full product life cycle. Results indicate that Scope 3 emissions account for 94.3% of total product emissions, with product use (44.7%) and purchased goods and services (36.9%) as the primary contributors. Upstream agricultural inputs—particularly milk powder—emerge as the dominant hotspot due to methane emissions and energy-intensive processing. Scenario-based evaluation suggests that regenerative sourcing, ingredient optimization, packaging redesign, logistics improvements, and consumer-phase engagement could significantly reduce life cycle emissions. The findings demonstrate how product-level LCA can operationalize Scope 3 decarbonization strategies in processed food systems, bridging corporate net-zero ambitions with actionable supply chain interventions. These results provide transferable insights for cleaner production transitions within the agri-food sector.

Sustainability doi: 10.3390/su18115387

Authors: Soumya Basu Takaya Ogawa

This study evaluates the scalability and sustainability impacts of integrating Napier grass cultivation with biofertilizer production and dairy systems in rural West Bengal. Field-level evidence indicates that biofertilizer application and irrigation optimization significantly enhance soil organic carbon (SOC), improving nutrient availability and enabling Napier yields of up to 500 tons/acre on fallow land. A technoeconomic model shows strong economies of scale, with production costs decreasing by 40% when area under cultivation is simulated from 1 acre to 100 acres. Statewide scaling scenarios demonstrate significant development potential. Under 10% adoption of fallow land by 2040, approximately 75 million tons of biomass can be grown annually, benefiting 3.75 million households, doubling under a 20% adoption scenario by 2050. The system enables a 2.5–4× increase in household income while delivering substantial climate co-benefits. Avoided emissions from manure management are estimated at ~40 Mt CO2 annually by 2040, increasing to ~80 Mt CO2 by 2050, alongside additional gains from soil carbon sequestration and reduced high-emission urea-use. Overall, the proposed circular model offers a scalable pathway for achieving multiple Sustainable Development Goals through integrated agricultural transformation.

Sustainability doi: 10.3390/su18115380

Authors: Shahrin Shahab Sorowar Chowdhury Md Rafique Ahasan Chawdhery

Exposure to wildfire smoke has been a growing public health issue with the increasing effects of climate change. The increasing frequency and severity of wildfires fueled by higher global temperatures and shifting climate change patterns have left more people exposed to smoke for longer periods. This exposure is primarily driven by fine particulate matter (PM2.5) and carbon monoxide (CO) and other toxic gases, causing harmful health impacts, particularly to the respiratory system and cardiovascular system. The potential to reduce health effects is dependent on the adaptive capacity of individuals, households, and communities in anticipating, responding to, and recovering from smoke events. Social vulnerability factors, including socioeconomic status, race/ethnicity, housing quality, and healthcare access, greatly influence how well individuals or communities can prepare for and respond to the effects of wildfire smoke exposure. Although simple protective steps are often possible, more expensive solutions are usually out of reach for the most marginalized groups, showing that the ability to adapt depends on the resources people have. This review aims to analyze the convergence of wildfire smoke exposure, social vulnerability, and adaptive capacity in vulnerable communities with specific reference to approaches to building community resilience. This study adopts a narrative integrative review approach to synthesize current interdisciplinary evidence on the health impacts of wildfire smoke, associated social inequities, and adaptive capacity strategies, while introducing an integrated conceptual framework linking social vulnerability, adaptive capacity, and community resilience. The findings of this review substantiate the necessity of integrated, equity-oriented adaptation responses, such as enhanced risk communication, sustainable climate change mitigation strategies, and improved access to healthcare and infrastructure. In conclusion, strengthening community resilience to wildfire smoke requires confronting structural social inequities while simultaneously enhancing the adaptive capacity of resource-constrained communities.

Sustainability doi: 10.3390/su18115383

Authors: Zhinuo Zhang Ziqiang Liu

As a strategic infrastructure supporting high-quality economic and social development, computing infrastructure plays a pivotal role in enabling green transitions. Using panel data from Chinese prefecture-level cities spanning 2007 to 2023 and leveraging the staggered commissioning of 12 National Supercomputing Centers as a quasi-natural experiment, this paper employs a time-varying difference-in-differences (DID) approach to estimate the effect of computing infrastructure on urban green total factor productivity (GTFP). The results indicate that the operation of supercomputing centers has a statistically significant positive effect on urban GTFP, with a magnitude equivalent to approximately 0.83 times the sample standard deviation of GTFP, a finding that remains robust to alternative dependent variable specifications, the exclusion of other policy shocks, and placebo tests. Mechanism analysis reveals that computing infrastructure facilitates green development through three channels: fostering green technological innovation, optimizing energy efficiency, and strengthening environmental regulation. Heterogeneity analysis shows that the positive effect is more pronounced in coastal cities, small-to-medium-sized cities, and regions with weaker digital infrastructure. Spatial analysis further uncovers a distance-decay pattern, with a siphoning effect within a 50 km radius and a spillover effect between 50 km and 200 km from the supercomputing center. This study provides empirical evidence on the environmental consequences of the computing economy and offers policy implications for optimizing computing infrastructure deployment to facilitate green transitions.

Sustainability doi: 10.3390/su18115379

Authors: Guanjun Lu Wenxiao Gao Zhihui Chai

Grassland ecological governance is a systematic project integrating natural and social attributes, involving pastoral social structure adjustment and herders’ livelihood transformation. Pastoral households are the basic production units and direct ecological responsibility bearers in Inner Mongolia. Based on 2001–2023 statistical data and 2014–2023 field surveys, this study adopts an integrated mixed-methods approach: quantitative trend analysis is used to identify long-term changes in household number and size, while qualitative thematic coding of interviews and participatory observation is applied to interpret behavioral logic and governance mechanisms, so as to achieve mutual verification and complementarity between the two data types. We find that pastoral household numbers grew rapidly after 2010 and remained high. By 2023, the number reached 641,500, with average household size dropping to 2.89 people. Driven by ecological subsidy policies, grassland tenure confirmation, and livestock market returns, household scale shrank and grassland was fragmented. The three spontaneously formed ecological governance functions—population regulation, grass-livestock balance, and human-land adjustment—have weakened and shifted from “spontaneous governance” to “passive response.” Herder differentiation in this paper refers to the stratification of pastoral households into distinct groups in terms of livestock scale, grassland area, livelihood structure, and governance capacity, forming heterogeneous behavioral patterns and policy responses. Future governance should abandon the one-sided label of herders as “ecological destroyers,” improve differentiated subsidy policies, and support joint household governance to revitalize endogenous governance capacity.

Sustainability doi: 10.3390/su18115381

Authors: Anna M. Kaczmarek

The extant body of evidence pertaining to the acceptance of cultured meat in Sub-Saharan Africa remains limited. The present study examined the determinants of intention to adopt cultured meat among a sample of young, urban, meat-eating adults in Chad (n = 290, from a recruited sample of 304). This was achieved using a cross-sectional online survey. Hierarchical OLS with HC3-robust inference was estimated across five hypothesis blocks, complemented by dominance analysis, binary outcome sensitivity, and exploratory triangulation (Bayesian, elastic net, conditional random forest). Approximately half of the respondents expressed a willingness to try cultured meat (52.4%). The final model accounted for 30.6% of the intention variance (adjusted R2 = 0.188). Following Holm’s correction for multiple comparisons, the conventional-meat and knowledge blocks did not demonstrate a significant difference. The product beliefs (ΔR2 = 0.056, p = 0.022), affective risk barriers (ΔR2 = 0.086, p = 0.004), and value fit (ΔR2 = 0.039, p = 0.048) were found to be significant, with affective risk ranking first in dominance analysis (22.8%). Binary sensitivity analysis demonstrated acceptable discrimination (AUC = 0.744), although no block remained significant after correction. Exploratory analyses yielded convergent results, including notably robust Bayesian support for excluding the conventional-meat block (BF01 = 1.66 × 1012). Sensitivity power analysis confirmed adequate power (≥0.80) for the significant blocks, but indicated that the conventional-meat non-significance may partly reflect limited power (estimated power = 0.47). Cultured meat adoption intention was more strongly associated with affective risk and value fit appraisals than with conventional meat purchase priorities. This suggests that acceptance strategies should prioritise risk reduction, trust-building, and perceived value. The findings should be interpreted as applying to a digitally connected, young, urban, meat-eating, predominantly tertiary-educated early-adopter-like segment (90.5% with university-level education; 72.7% residing in cities of more than 500,000 inhabitants), rather than to the general Chadian population.