Sustainability doi: 10.3390/su18168129

Authors: Jing Song Xiaoyu Xu Qi Li Shuowei Jia Lujia Wang

Consumer trust is critical to the sustainable development of cross-border B2C e-commerce platforms. Accurately evaluating and diagnosing trust weaknesses has become a key concern for both practitioners and researchers. To address the inherent limitations of existing trust evaluation methods, this study proposes an improved AHP-Ridge Regression hybrid model that integrates expert knowledge with actual consumer perception data. First, an improved Analytic Hierarchy Process based on stakeholder-oriented nonlinear programming is employed to optimize the evaluation weights of nine experts, reduce subjective bias, and generate expert prior weights for each dimension and indicator. Second, these prior weights are incorporated as the regularization prior mean of the Ridge Regression model to construct the improved AHP-Ridge Regression model. Based on survey data from 387 valid respondents across five major cross-border platforms (Tmall Global, JD International, Pinduoduo Global, Sam’s Club Global, and CDFG Duty-Free), the model is compared with six baseline models using a 30-times repeated five-fold nested cross-validation. The proposed model achieves the lowest RMSE (0.3179) and highest R2 (0.6510) among all compared models, with statistically significant improvements over all baselines (Nadeau–Bengio-corrected p < 0.001, large Cohen’s d effect sizes). However, the improvement over conventional Linear Regression is modest in absolute magnitude (ΔRMSE ≈ 0.0012). The primary value of the proposed model lies not in a dramatic leap in predictive accuracy but in its theoretical grounding, interpretability, and diagnostic capability. Permutation importance analysis reveals that Platform Fluidity, AI Technology Usability, Page Layout & Navigation Clarity, Content Accuracy, and Policy Assurance are the most important predictors of consumer trust. Comprehensive calibration and residual diagnostics (including MAE, normality tests, and heteroscedasticity checks) confirm the model’s predictive reliability. Furthermore, platform-specific diagnostics identify three distinct trust profiles (high-trust benchmark, trust-improvement priority, and mixed-profile platforms), providing managers with actionable insights for resource allocation. This study offers cross-border B2C e-commerce platforms a trust evaluation tool that balances predictive accuracy and interpretability, and provides implications for sustainable platform governance and ESG-oriented management by linking trust diagnostics with platform accountability frameworks.

Sustainability doi: 10.3390/su18168127

Authors: Wiley Jane Bundy Allison Rick VandeVoort Kalina M. Manoylov Samuel Mutiti

Sustainable primary producer communities depend on a diverse pool of physiologically active cells surviving transport through sediment pore spaces. However, algal transport through saturated sediments remains a major knowledge gap in surface water–groundwater (SW-GW) interactions. In this study, vertical column experiments used a conservative tracer (NaCl) to establish hydraulic baselines. Three algal groups (green algae, cyanobacteria, and diatoms) were then tested across pH 8, 7, and 6, with recovery measured through biomass quantification, morphological identification, and post-run culturing. Green algae showed the highest mobility, with recovery increasing from 14.42% at pH 8 to 38.39% at pH 6 and retardation factors (R) of 1.33–1.40. Cyanobacteria peaked at neutral pH (29.50%) with higher retardation (1.60–2.31), while diatoms were strongly retained (≤5.72%) with high retardation (1.87–2.31). These differing transport patterns are primarily driven by morphological traits. Small, unicellular green algae are less susceptible to mechanical straining, enabling higher mobility. Conversely, cyanobacteria and diatoms experience stronger retention due to physical straining of their complex morphologies (filaments and chains) and enhanced surface adhesion from extracellular polymeric substances. A permutation-based two-way ANOVA indicated that the algal group significantly affected percent recovery (p = 0.0034), whereas neither pH (p = 0.166) nor the pH × algal group interaction (p = 0.076) was significant. Post-run culturing showed approximately 68% of inoculated genera persisted after passage, suggesting that saturated sediments can function as a biological “seed bank” for algal communities. These results highlight group-specific transport patterns in controlled sand columns and may inform future studies of algal persistence in natural surface water–groundwater systems; however, field-scale transport will also depend on sediment heterogeneity, flow conditions, and changing pore-water chemistry.

Sustainability doi: 10.3390/su18168128

Authors: John Alexander Taborda Victor José Olivero Carlos Arturo Robles Javier Antonio De la Hoz Hoz Carolina Diosa Rosas Rosas

Multi-Level Governance (MLG) frameworks effectively diagnose the complexity of regional renewable energy transitions but lack operational mechanisms for institutional implementation. This study develops a hybrid evidence-based architecture that integrates the Viable System Model (VSM) with computational intelligence and objective multi-criteria decision analysis. Methodologically, a systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol of 339 peer-reviewed articles (2015–2025) feeds a Latent Dirichlet Allocation (LDA) model that extracts K = 30 strategic topics (semantic coherence Cv optimized over K = 5–40), operationalizing System 4 environmental sensing. In parallel, a 1 km2 pixel-based spatial model integrates a National Conflict Index (INC, 2019–2024) with technical feasibility layers (Global Wind Atlas v4.0, Solargis, Servicio Geológico Colombiano) and applies CRITIC (CRiteria Importance Through Intercriteria Correlation) objective weighting and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) prioritization (System 3 control). Robustness is confirmed through ±10–20% weight perturbation (Spearman >0.92). Empirically, the framework reveals a localization paradox: approximately 68% of optimal wind zones (>9 m/s at 100 m hub height) in the Colombian Caribbean overlap with the highest national conflict quartile, narrowing a theoretical capacity exceeding 100 GW (50 GW offshore wind, 30 GW onshore wind, 42 GW solar PV, 1.17 GW geothermal) to roughly 24 GW of governance-viable capacity. Scenario calibration (Accelerated 80/20, Balanced 50/50, Justice-Oriented 30/70 technical/conflict weighting) demonstrates that System 5 normative orientation materially reshapes territorial prioritization. The framework advances VSM from a qualitative diagnostic metaphor to a reproducible governance architecture for high-variety regional contexts.

Sustainability doi: 10.3390/su18168126

Authors: Abdelmalek Mimouni Youssef Chahet Aumeur El Amrani Mohamed Azeroual Mohamed El Amraoui Yassine Ayat Lahcen Bejjit

The digitalization of photovoltaic (PV) systems can support sustainable energy deployment by improving operational efficiency, system visibility, and energy extraction. However, many existing Internet of Things (IoT)-enabled solutions address monitoring and maximum power point tracking (MPPT) separately or depend on proprietary platforms, remote cloud services, and relatively costly hardware, which may restrict their accessibility and replication in small-scale and resource-constrained applications. This study presents the implementation and laboratory-scale experimental evaluation of an edge-IoT architecture that integrates real-time PV monitoring, embedded adaptive MPPT control, local data management, and visualization using low-cost hardware and open-source software. The proposed architecture combines an ESP32 microcontroller with a Raspberry Pi (RPi) local server to enable environmental and electrical sensing, edge-based control, message queuing telemetry transport (MQTT) communication, local data storage, and interactive visualization through the open-source Node-RED, InfluxDB, and Grafana platforms. An adaptive perturb-and-observe (AP&O) algorithm is implemented on the ESP32 to dynamically adjust the duty cycle of a DC–DC boost converter in response to changing operating conditions. The system is experimentally evaluated using a PV test bench equipped with a custom boost converter and sensing modules measuring eleven electrical and environmental parameters. The architecture achieved an average communication latency of 193 ± 23 ms and an average MPPT efficiency of 97.3 ± 0.54%. It also provided a power gain of 0.7 ± 0.5% compared with the conventional fixed-step perturb-and-observe method. By combining local processing, open-source software, low-cost components, and integrated monitoring and control, the proposed system reduces dependence on external cloud infrastructure while supporting responsive and accessible PV energy management. These results demonstrate its potential as a replicable technological framework for improving the operational sustainability and digital management of small-scale PV installations.

Sustainability doi: 10.3390/su18168124

Authors: Abdellatif Bouaichi Alae Azouzoute Youssef Chahet Bouchra Laarabi Houssain Zitouni Massaab El Ydrissi Zineb Bounoua Charaf Hajjaj Aumeur El Amrani Mohamed El Amraoui Najib El Ouanjli Naima Elyanboiy Pierre-Olivier Logerais

Photovoltaic (PV) technology is now one of the main options for expanding the power of low-carbon electricity generation. However, in practical operation, PV systems still face several persistent difficulties, including the variability of solar irradiance, gradual performance degradation, fault occurrence, suboptimal control, and the growing complexity of grid-connected operation. These issues explain why artificial intelligence (AI) has become increasingly relevant in PV research, not only as a prediction tool, but also to improve monitoring, control, diagnosis, and decision-making. This review investigates the applications of AI in the major stages of the PV system lifecycle: solar resource assessment, power forecasting, fault detection, condition monitoring, system sizing, maximum power point tracking (MPPT), and grid integration. Rather than treating these applications as separate research topics, the review attempts to connect them through the common factors that determine their practical value: data quality, sensing configuration, model complexity, physical operating conditions, and deployment constraints. The reviewed studies indicate that AI-based MPPT methods can achieve tracking efficiencies close to 99%, while recent forecasting models, particularly LSTM, CNN–LSTM, and transformer-based architectures, can reduce prediction errors under changing weather conditions. At the same time, PV fault detection is moving beyond electroluminescence image classification toward more practical multimodal strategies that combine infrared thermography, RGB and drone imagery, electrical measurements, and SCADA/IoT data. Nevertheless, the progress reported in the literature should be interpreted with caution. Many proposed models are still evaluated on limited or non-standardized datasets, and their performance may decrease when they are transferred to different PV technologies, climates, fault severities, or operating conditions. Other recurring limitations include class imbalance, high computational cost, weak generalization, and the limited interpretability of deep-learning models. For this reason, hybrid neural networks, explainable AI, physics-informed learning, edge-AI, federated learning, and quantum machine learning are discussed as possible directions for making AI-based PV solutions more reliable and deployable. This review aims to critically synthesize recent advances and remaining gaps in order to support the practical integration of AI into efficient, reliable, and sustainable PV systems.

Sustainability doi: 10.3390/su18168125

Authors: Al Nasrie Weli Suhaiza Zailani Abderahman Rejeb

Malaysia’s upstream poultry supply chain, comprising broiler farms, hatcheries, and breeder operations, faces persistent barriers to circular economy (CE) adoption despite growing national policy support. Existing literature has focused predominantly on quantitative assessments of CE performance, leaving a critical gap in contextual, institutional-level understanding of why CE practices remain selectively and unevenly implemented. This paper reports findings from an exploratory qualitative study involving nine semi-structured in-depth interviews with informants drawn primarily from institutional and regulatory stakeholder categories: regulatory agencies (Department of Veterinary Services Malaysia, DVS), industry associations (Federation of Livestock Farmers’ Associations of Malaysia, FLFAM), marketing and distribution agencies (Federal Agricultural Marketing Authority, FAMA), research institutions (Malaysian Agricultural Research and Development Institute, MARDI), one private sector operator, and academic informants. Thematic analysis reveals five interconnected themes that collectively explain CE implementation gaps as seen from this institutional vantage point: (1) fragmented internal coordination as the primary operational barrier, (2) policy-practice misalignment between regulatory intent and operational realities, (3) the awareness-to-action deficit in CE conceptualisation, (4) differentiated capability constraints across enterprise scales (reported mainly through an industry-association intermediary rather than smallholders directly), and (5) the digital-circular complementarity gap raised by a minority of informants (4 of 9). The study makes three contributions: it generates an institutional-level, qualitative account of CE barriers and enablers for Malaysia’s upstream poultry sector from an institutional perspective; it introduces the concept of capability-sensitive CE governance, situated relative to related constructs such as the dynamic capabilities view, absorptive capacity, and the Technology–Organisation–Environment (TOE) framework, as a novel theoretical construct grounded in empirical evidence; and it proposes a preliminary Circular Economy Implementation Readiness Model (CEIRM), offered as a basis for future validation rather than a tested framework, that outlines a staged, practical pathway for CE adoption at the enterprise level. Findings have exploratory implications for policymakers, agri-food managers, and researchers engaged in circular transitions in developing-economy food systems.

Sustainability doi: 10.3390/su18168120

Authors: Yao Xiao Shiyu Liu Wenwu Zheng

Accurate mapping of terraces is important for farmland protection, food security, and the management of terrace abandonment. However, extracting terraces from high-resolution remote sensing imagery remains challenging because of complex backgrounds, fragmented ridge structures, weak boundary contrast, and high similarity between terraces and surrounding land-cover types. This study proposes AMF-Deep, an Attention Multi-scale Fusion DeepLabv3+ model, for binary terrace extraction across representative terrace regions and morphologies. AMF-Deep was evaluated using 0.61 m high-resolution remote-sensing imagery from five representative terrace regions in China, encompassing diverse terrace morphologies and background conditions. In the proposed model, MobileNetV2 is adopted as the backbone to reduce computational cost, a modified multi-scale ASPP module is used to capture terrace morphology at different spatial scales, CBAM enhances low-level boundary and texture features, ECA refines high-level channel responses before ASPP, and NAM recalibrates semantic features after ASPP. A residual decoder is further introduced to support low-level feature transfer and boundary recovery. Experimental results show that AMF-Deep achieved the highest regional performance in Huangling, with mIoU, mPA, Accuracy, Recall, and Precision of 89.47%, 95.17%, 96.70%, 94.99%, and 93.68%, respectively. Stepwise ablation experiments further indicated that the modified ASPP module, the differentiated attention arrangement, and the residual decoder contributed to the final performance. Qualitative seasonal visualization suggests that winter images and dryland terraces in Shexian remain more challenging because of weak texture contrast and high background similarity. These results indicate that AMF-Deep has potential for terrace extraction across representative regions, although further quantitative seasonal evaluation and cross-region validation are still needed.

Sustainability doi: 10.3390/su18168122

Authors: Timur Kogabayev Elmira Mynbayeva Meruyert Bekturganova Yerbol Ismailov Rando Värnik

Business model adjustment is a critical capability for microenterprises operating in import-dependent industries within emerging markets, and is increasingly recognised in the sustainable business model literature as a mechanism through which firms build economic resilience under resource constraints and volatile operating conditions. This paper examines how a specialty coffee microenterprise in Almaty, Kazakhstan, has adjusted its business model to create, deliver and capture value in a non-producing, landlocked economy characterised by rapid demand growth, currency volatility and high import dependency. The study answers two research questions regarding this case using Osterwalder and Pigneur’s business model canvas as the main analytical framework: (1) How did the case company set up its business model to create, deliver, and capture value? (2) In the context of Kazakhstani specialty coffee roasting, what possibilities and challenges influenced this business model? The analysis combines secondary market data with qualitative evidence from a semi-structured interview conducted in autumn 2025 with the founder of a nine-employee microenterprise that has evolved from a mobile coffee bar into a hybrid B2B–B2C roaster, café operator and e-commerce subscription service. Although Kazakhstan is not a coffee-producing country, its retail coffee market expanded from USD 326.71 million in 2019 to an estimated USD 554.5 million in 2025, with the fresh-coffee share rising from approximately 30% to 37%. The interview account describes a business model centred on locally roasted, traceable specialty coffee delivered fresh to a young, urban customer base, supported by educational and community-building activities. As reported by the founder, the enterprise faces structural challenges including exposure to international green-coffee price spikes—such as the record nominal highs of 354.32 US cents/lb reached in February 2025—currency-related cost volatility, logistical complexity across Eurasian transit routes and constrained access to growth-stage financing. Because the evidence base is a single founder interview combined with secondary market data, the paper does not independently verify the firm’s resilience, viability or financial outcomes. The findings are presented in the form of analytical generalisations—that is, generalisations relating to theoretical conclusions drawn from this specific case, rather than from a broader set of companies—which illustrate, based on the founder’s own account, how this micro-enterprise pursued a targeted, phased adaptation of its business model rather than a radical overhaul; the study does not independently verify resulting sustainability or resilience outcomes. As this is a case study, the present analysis does not allow us to determine the extent to which this model is representative of other micro-enterprises involved in coffee production, or of other non-manufacturing sectors in developing economies; the contribution of this study is empirical and contextual rather than theoretical: it extends the scope of business model analysis to under-researched geographical and institutional contexts and lays the groundwork for future comparative studies.

Sustainability doi: 10.3390/su18168123

Authors: Marina Papathanasiou Evangelos Asprogerakas

Maritime Spatial Planning (MSP) is increasingly recognized as the primary governance framework for integrating multiple and often competing maritime activities within shared marine space. This paper examines how the Multi-Use (MU) concept is incorporated into formally adopted MSP frameworks across six Mediterranean EU Member States, namely France, Spain, Italy, Cyprus, Slovenia, and Malta. Drawing on content analysis and document analysis of officially approved national plans, the study develops a multi-criteria analytical framework combining conceptual and spatial dimensions to assess MU integration systematically across national contexts. Mediterranean MSP systems are dominated by soft MU forms, particularly combinations involving tourism, fisheries, underwater cultural heritage, and environmental protection, while hard MU configurations involving offshore renewable energy, aquaculture, and shared infrastructure remain largely at the strategic or pilot stage. Four distinct pathways of MU integration are identified: operational, compatibility-based, strategic coexistence, and administrative coexistence. These pathways reflect different approaches to integrating MU within MSP systems, from explicit multi-use promotion to coexistence-oriented planning. They also indicate that the institutional adaptation of marine governance has not progressed as rapidly as technological developments, particularly in relation to emerging MU configurations. Effective MU integration depends less on formal policy recognition and more on the existence of planning instruments, zoning mechanisms, and cross-sectoral governance arrangements capable of translating strategic objectives into operational practice.

Sustainability doi: 10.3390/su18168121

Authors: Muhammed Sefa Çetin Habip Sahin Muhsin Tunay Gençoğlu

This study investigates the performance, energy flow, efficiency, and environmental impact of a C-segment battery electric vehicle (BEV). As BEVs are increasingly considered a sustainable alternative to conventional internal combustion engine vehicles, a detailed understanding of their energy utilization and operational emissions is essential. A MATLAB/Simulink-based vehicle model incorporating an 88.5 kWh battery pack, a 160 kW permanent magnet synchronous motor (PMSM), regenerative braking, and longitudinal vehicle dynamics was developed. The developed model was validated by comparing the simulated vehicle performance characteristics with the publicly available specifications and performance data of the reference TOGG T10F vehicle. The vehicle was evaluated under the WLTP Class 3 driving cycle, while the effects of aggressive and high-speed driving conditions were further investigated using the US06 and Artemis Motorway 150 cycles. The results indicate a net vehicle energy consumption of 136.4 Wh/km and a driving range of 623 km under WLTP conditions. The PMSM achieved average efficiencies of 93.4% in traction mode and 92.7% in regenerative braking mode, while the cumulative battery-to-wheel drivetrain efficiency reached 81.5%. In addition, approximately 19.9% of the consumed energy was recovered through regenerative braking. Vehicle emissions were also assessed using different electricity generation mixes based on the rated energy consumption, including charging losses, yielding operational emissions between 27.7 and 116.0 gCO2e/km. The findings demonstrate that the developed model provides realistic performance predictions and confirm the potential of BEVs to achieve high efficiency and substantially lower emissions than conventional passenger vehicles.

Sustainability doi: 10.3390/su18168119

Authors: Katarzyna Turoń

Autonomous vehicles are a flagship technology of the smart city, yet smartness and sustainability are distinct goals. Automated urban mobility can be both smart and sustainable, one without the other, or neither, and which outcome a city reaches depends on how people adopt and use it. This article reports a systematic review of the human paradoxes of automated urban mobility. Drawing on a synthesis of the literature on automated mobility and the governance of sustainable mobility, it covers twenty recurring paradoxes and organises them into five families according to what generates them. Mapping the corpus shows where the evidence is dense and where it is thin, and it shows that work on the attractiveness of automated travel outweighs work on zero-occupancy running by more than an order of magnitude. It also shows that the direction of reported findings depends on how a study was conducted. Models tend to report benign outcomes for the quantity they optimise and adverse outcomes for quantities they only represent, so appraisals drawing on a single study design will be biased in a predictable direction. The paradoxes are not inherent to the technology. They hinge on human choice and governance, and automated mobility reaches the smart and sustainable quadrant only where adoption is shared, well matched to need, sequenced with care, and steered by explicit public choices. The article sets out the CalmMobility paradigm as that steering framework, maps each tension to the instruments that decide its outcome, and offers testable propositions and a research agenda for the tensions that remain thinly evidenced.

Sustainability doi: 10.3390/su18168118

Authors: Dao Huy Tuan Van Nguyen Ngoc Thanh Anh-Tuan Tran

Maintaining frequency stability in modern interconnected power systems has become increasingly challenging due to the growing penetration of renewable energy sources, energy storage systems, and hybrid AC/DC transmission networks. This study proposes an intelligent load frequency control strategy based on a Covariance Matrix Adaptation Evolution Strategy (CMA-ES)-optimized PID controller for interconnected multi-area power systems. The proposed approach is evaluated on several power system configurations, including two-area and three-area systems as well as hybrid AC/DC networks incorporating hydroelectric and thermal generating units, high-voltage direct-current transmission links, superconducting magnetic energy storage, and renewable energy integration. The controller parameters are optimized using CMA-ES and validated through extensive simulations under step load disturbances. To ensure robustness, the optimization process is repeated over 100 independent runs. The proposed method is compared with Particle Swarm Optimization, Gray Wolf Optimization, and Honey Badger Algorithm-based PID controllers using both dynamic performance measures and error-based performance indices. Simulation results demonstrate that the CMA-ES-based controller consistently achieves faster settling times, smaller frequency deviations, lower Tie-line Power oscillations, and improved damping characteristics across all investigated scenarios. In the two-area system, the proposed method reduces the Integral of Time Absolute Error by approximately 73.5% compared with the Gray Wolf Optimization approach. For more complex hybrid systems incorporating high-voltage direct-current links and energy storage units, substantial reductions in performance indices are also achieved. Furthermore, the proposed controller effectively mitigates oscillations caused by renewable power fluctuations and enhances inter-area coordination. The results confirm that CMA-ES provides an effective and robust framework for frequency regulation in modern interconnected power systems with high renewable energy penetration.

Sustainability doi: 10.3390/su18168117

Authors: Haibao Cheng Bih Ni Lee Nurulasyikin Binti Hassan

Digital transformation has become a central management agenda for higher education institutions seeking to improve teaching quality, organizational resilience, and long-term educational sustainability. However, the managerial pathways through which digital leadership contributes to sustainable teaching innovation remain insufficiently explained. Drawing on digital leadership, organizational learning, and sustainable higher education literature, this study develops and tests a conceptual path model linking digital leadership, organizational learning, faculty professional development, institutional support, and sustainable teaching innovation. A cross-sectional survey was conducted with 300 university faculty members and teaching-related personnel who had experience with digital teaching tools. Composite-score-based path analysis showed that digital leadership positively predicted organizational learning, faculty professional development, and sustainable teaching innovation. Organizational learning and faculty professional development also significantly predicted sustainable teaching innovation and served as indirect transmission mechanisms. Institutional support had a positive direct effect but did not significantly moderate the organizational learning–innovation relationship. The findings indicate that sustainable teaching innovation depends not only on digital infrastructure but also on leadership-enabled learning processes, faculty development, and institutional support. This study contributes an educational management strategy model that reframes sustainable teaching innovation as an organizational capability shaped by leadership, learning, professional development, and support mechanisms.

Sustainability doi: 10.3390/su18168116

Authors: Mengqing Wu Zihao Wu Fang Bu Junhe Liu Jiangao Deng

China’s aging population is placing growing demands on medical care, social protection, community-based provision, and everyday assistance. Using a balanced panel for 31 provincial-level regions over 2014–2023, this study evaluates whether regional digital-economy development is linked to the capacity to meet those demands and how that relationship varies across service and institutional settings. The Digital Economy Index (DEI), Aging-Service Capacity Index (ASC), Daily-Life Service Availability (DLSA), and Healthcare Resource Availability (HRA) are constructed with pooled entropy weights. The Fiscal-Technology Support Intensity Index (FTSI) averages standardized fiscal-expenditure and science-and-technology expenditure intensities. The empirical strategy combines province and year fixed effects with alternative index definitions, lag structures, Oster bounds, and two-stage least squares checks. Indirect-pathway, interaction, and panel-threshold models are then used to assess service availability and fiscal-technology conditions. The preferred estimates indicate a positive within-province DEI–ASC association. The estimated indirect associations through DLSA and HRA are both positive, suggesting that daily-life service networks and healthcare resources are relevant pathways. The association is also stronger at higher FTSI levels and above the estimated threshold, with a similar pattern under the per-capita FTSI_pc measure. Overall, digital development is more closely associated with sustainable aging where local service systems and institutional support can translate digital resources into accessible services.

Sustainability doi: 10.3390/su18168114

Authors: Jabulile Zamokuhle Manyike Yanga-Inkosi Nocezo

Smallholder farmers in South Africa face increasing climate variability, yet their agronomic decision-making depends on timely and reliable climate information. Although digital ICT platforms are expanding, limited evidence exists on how their effectiveness compares to human-based advisory systems. The study addresses this gap by examining the determinants of ICT-based climate information adoption using logistic regression and assessing its influence on agronomic decisions through propensity score matching (PSM). A cross-sectional survey and multistage sampling were used to collect data from 217 smallholder crop farmers in the Eastern Cape. The results indicate that 65% of farmers accessed climate information through ICT platforms, while 35% relied on human-based sources. The adoption of ICT-based information is driven by education, digital literacy, mobile network reliability, the perceived value of real-time updates, and smartphone ownership, whereas habitual dependence on traditional channels hinders digital uptake. PSM estimates show that ICT-based climate information is 10–15% less effective than human-based sources in shaping planting decisions, input use, and the timing of farm operations, likely due to digital literacy and infrastructure constraints. The study demonstrates that access to digital tools does not automatically translate into effective use and recommends a hybrid information model integrating digital platforms with trusted human intermediaries to strengthen climate resilience and agronomic decision-making.

Sustainability doi: 10.3390/su18168115

Authors: Irfan Syahkuala Veithzal Rivai Kasmir Farida Elmi

Public sector organizations face mounting pressure to improve employee performance while pursuing sustainable management practices, yet evidence on how sustainability-oriented leadership relates to tangible performance outcomes remains scarce, particularly in regional government settings. Grounded in Self-Determination Theory, this study examines the association of Human Capital Sustainability Leadership (HCSL) with Employee Job Performance (EJP) and the mediating role of Innovative Work Behavior (IWB) among Indonesian civil servants managing regional government assets (Barang Milik Daerah). Survey data were collected from 541 civil servants across the DKI Jakarta Provincial Government using validated multi-item scales and analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM). HCSL was positively associated with IWB (β = 0.834, p < 0.001) and EJP (β = 0.438, p < 0.001), and IWB was positively associated with EJP (β = 0.383, p < 0.001). Bootstrap analysis indicated a complementary partial mediation of the HCSL–EJP relationship through IWB (β = 0.319, 95% CI [0.194, 0.440]). The model accounted for 61.9% of the variance in EJP and 69.5% in IWB, though the cross-sectional, single-source design and very high construct reliabilities mean these estimates should be read as upper bounds. The findings suggest that sustainable leadership development may be one credible lever for supporting innovation and performance in public asset stewardship, with implications for sustainable governance and human capital development.

Sustainability doi: 10.3390/su18168113

Authors: Yaxuan Yi Youssef Haddi Haoyu Huang

As the construction industry seeks to reduce carbon emissions, timber has emerged as a key material due to its capacity for biogenic carbon storage and end-of-life (EoL) reuse. However, assessing the practical circularity potential of timber structures remains challenging. This is largely because recovered components suffer geometric and material losses at their connection points. This study evaluates the EoL reuse and recycling potential of a multi-storey timber building by combining Building Information Modelling (BIM) with Life Cycle Assessment (LCA). A digital model was used to quantify structural elements (beams, columns, and walls), explicitly accounting for material losses at connections to calculate the net recoverable timber. The recovered material (837.39 m3) was assigned to various cascading use scenarios based on material strength: structural reuse, non-structural reuse, engineered wood production, and energy recovery. To align with ISO 14044 principles, a functional equivalence factor (Q-factor) was applied to measure the environmental benefits of substituting new materials. Results indicate an overall material loss of 16.62% due to connections. Among the evaluated EoL pathways, structural reuse yielded the greatest net carbon benefit (−128.7 tCO2e), significantly outperforming lower-value alternatives such as energy recovery (−29.3 tCO2e). Additionally, a Design for Disassembly (DfD) sensitivity analysis showed that reducing connection losses by 50% could increase net global warming potential (GWP) savings by up to 19.7%. In conclusion, connection design is a critical factor in enabling timber circularity. Furthermore, combining BIM material tracking with LCA methods offers a practical approach to quantifying the long-term carbon benefits of timber reuse strategies.

Sustainability doi: 10.3390/su18168112

Authors: Teshale Tadesse Fufa Ludovic Montastruc Stéphane Negny Léa van der Werf Abubeker Yimam Brook Tesfamichael

Bioenergy development from biomass resources requires multi-criteria decision-making (MCDM) methods to rank and select suitable feedstock alternatives. Conventional TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a widely used MCDM method that assists in selecting alternatives based on their relative closeness to the ideal solution. Unlike the existing TOPSIS, which provides only an overall ranking of alternatives, this study proposes a framework that integrates TOPSIS ranking with threshold-based performance classification and mapping to enable a more comprehensive assessment and support decision-making, thereby improving the interpretability of complex multi-criteria decision problems. The proposed framework was applied to evaluate, rank, and select eight potential biomass feedstocks in Ethiopia by integrating feedstock availability, technological readiness, and economic criteria. The ranking results indicate that molasses is the most suitable, followed by non-edible oil crops (castor seed, Ethiopian mustard, and Jatropha curcas) and lignocellulosic residues (cereal, cane, and coffee residues), while water hyacinth ranked lowest. The results were mapped into a strategic implementation timeline, with molasses prioritized for the short term, non-edible oil crops for the medium term, and lignocellulosic residues for the long term in Ethiopia’s bioenergy development. The study further supports decision-makers in strategic energy planning and facilitates bioenergy development.

Sustainability doi: 10.3390/su18168111

Authors: Omar A. Baakeel

This study addresses limited evidence comparing the relative associations of three Green Human Resource Management (GHRM) practices—green recruitment and selection, green training and development, and green employee involvement—with perceived organizational sustainability in Saudi Arabia. These practices were selected because they represent workforce entry, capability development, and employee participation. A quantitative cross-sectional survey was carried out involving 394 employees from both public and private sector organizations in the Central, Western, Eastern, and Northern regions of Saudi Arabia. Data were examined through confirmatory factor analysis, correlation analysis, and multiple regression utilizing heteroscedasticity-robust standard errors. The model accounted for 53.0% of the variation in perceived organizational sustainability. Green recruitment and selection showed the largest positive association (β = 0.412, p < 0.001), followed by green training and development (β = 0.237, p < 0.001) and green employee involvement (β = 0.162, p = 0.006). These associations remained significant in adjusted and sensitivity analyses. The study contributes by comparing the relative associations of the three GHRM practices simultaneously rather than treating GHRM as a single aggregate construct, thereby providing a clearer basis for targeted HR strategies and sustainability initiatives.

Sustainability doi: 10.3390/su18168110

Authors: Yan He Wanli Yang Fen Zhang

Against the backdrop of carbon peaking and carbon neutrality targets alongside the drive for high-quality urban development, the rollout of new energy vehicle pilot initiatives has become a core pathway to facilitate low-carbon transition in the transport sector. China launched the demonstration and promotion pilot policies for NEVs in 2009. Based on the externality theory, Porter Hypothesis, and financial resource allocation theory, this paper analyzes how different stakeholders respond to policy shocks and systematically elaborates on the internal mechanism through which NEV pilot policies affect urban green transition. It thoroughly clarifies the inherent transmission channels through which NEV trial policies reshape urban low-carbon development. Using a multi-period difference-in-differences (DID) framework with panel data spanning 282 cities from 2003 to 2022, the findings indicate that pilot policies have significantly enhanced the urban green transition in China. However, this positive effect is predominantly driven by improvements in green technical efficiency (GTE), while the policy’s impact on green technological progress (GTP) is notably weaker. The effects of these policies exhibit regional heterogeneity: the marginal gains generated by the trials turn out to be more substantial within central and western China, as well as in resource-growing and regenerative cities. Further tests reveal that green technological innovation and financial support positively moderate the impact of new energy vehicle pilot policies on urban green transition.

Sustainability doi: 10.3390/su18168109

Authors: Millicent A. Oyugi Troy Allen Berthold Audrey McCrary Gabriela Suchiapa Magdaleno Ambika Chandra

Because residential lawn irrigation represents a significant amount of urban water demand, homeowners play a central role in promoting sustainable and resilient communities. Understanding the motivations underlying their lawn watering decisions can help promote desirable and sustainable conservation behaviors. Using survey data from 500 Texas homeowners, this study compared attitudinal, normative, and contextual factors and lawn water conservation intentions across irrigation types. It also examined the relative contribution of these factors, alongside demographic and residential characteristics, in predicting lawn watering conservation intentions. Homeowners mainly relied on environmental and regulatory factors—rainfall, drought conditions, and water-use restrictions for lawn watering decisions. Social factors were rarely considered. Conservation intentions were strongest for routine low-effort practices (e.g., morning watering) and weakest for more technical tasks (e.g., smart irrigation controllers). Automatic irrigators reported the strongest intentions for technology-based practices; they scored significantly higher on contextual factors and social and institutional norms (p < 0.05). Hierarchical regression was significant, explaining 28% of the variance in conservation intentions (adjusted R2 = 0.26, F(12, 463) = 14.68, p < 0.001). Social and institutional norms (β = 0.20, p = 0.002), perceived behavioral control (β = 0.18, p < 0.001), and age (β = −0.23, p < 0.001) were the strongest predictors of conservation intention. Water bill rate considerations (β = 0.10, p = 0.043) and residential setting (β = −0.08, p = 0.046) were also significant. Attitudes towards lawn water preservation, aesthetics, HOA rules, environmental and regulatory norms, sex, ownership status, and HOA membership were not significant. Extension programming should combine technical assistance and norm-based strategies to encourage residential water conservation and promote sustainable urban water management in drought-prone communities.

Sustainability doi: 10.3390/su18168108

Authors: Xiangmeng Meng Lei Xi

As a new generation of general technology, artificial intelligence (AI) provides crucial technical support for addressing the dilemmas of carbon emission reduction in cities. This paper selects data from 273 prefecture-level cities in China from 2010 to 2024 to examine the impact of AI on urban carbon emission intensity (CEI) and its mechanism of action. The results show that AI is negatively associated with CEI. AI lowers the threshold for scientific research, expands the scale of patent output, and generates groundbreaking high value patents, which indicates that both the quantity and quality of innovation are key paths to facilitating urban carbon emission reduction. The results of the heterogeneity test indicate that the carbon reduction effects of AI exhibit stratified characteristics, with cities southeast of the Hu Line, northern industrial cities, and resource-based cities demonstrating more prominent emission reduction effects. Accordingly, policy recommendations such as establishing regional digital low-carbon layouts and allocating policy resources based on resource endowments are put forward. The research provides a theoretical basis for reducing carbon emissions and achieving sustainable development goals relying on AI.

Sustainability doi: 10.3390/su18168107

Authors: Dorceta E. Taylor Ivy Ortiz Kiera Quigley Destiny Treloar Haille Rae Samantha Stokes Lily Fillwalk Ashley Bell

The United Nations, in developing the Sustainable Development Goals, pays particular attention to cities, as they are crucial to achieving established benchmarks. Globally, many cities have high levels of food insecurity, and food access is a major component of the problem. Cities have increasingly complex and interdependent food environments. Yet, urban food systems are not well understood with respect to the impacts of redlining, residential segregation, and food store closures on food outlet distribution. Limited work is also being done on the relationship between urban sustainability efforts and food access. Here, we analyze 2229 open and closed food outlets in the Greater Grand Rapids area of southwest Michigan to examine their distribution and whether disparities are evident. We examined the impact of historic redlining on the distribution of food outlets. We also described sustainability efforts in the study area and the way county and city plans connect food access with sustainability. Roughly half of the food outlets are restaurants, 13.3% are small grocery and convenience stores, and 6.3% are pharmacies, dollar stores, and variety stores. Supermarkets and large grocery stores, which are the subject of most food access studies, account for 5% of food outlets. The most reliable predictors of food outlet distribution in the fully adjusted regression models are HOLC classification grade, median household income, educational attainment, and population density. The racial composition of the census tract was significant in only one model. The study leads us to urge more researchers to compare cities and adjacent municipalities, as income dynamics, neighborhood characteristics, population density, and educational attainment vary across urban, suburban, and rural areas.

Sustainability doi: 10.3390/su18168106

Authors: Daniel Filip Larisa Ivascu Livia Filip Alin Artene Aura Emanuela Domil

The transition towards the circular economy and improved environmental management is a major challenge for manufacturing SMEs under growing pressures for resource efficiency, waste reduction and industrial sustainability. Although circular economy, environmental management, digitalization and artificial intelligence are widely discussed, they are often treated separately and rarely integrated into maturity-assessment frameworks. This article proposes CEEMMI—Circular Economy and Environmental Management Maturity Index—a digital- and AI-oriented diagnostic framework with a multi-criteria structure for manufacturing SMEs. CEEMMI integrates eight dimensions covering circular strategy, eco-design, resource efficiency, life cycle management, circular supply chains, digitalization and AI, organizational capabilities and sustainable performance. In its current version, the model is operationalized as an equal-weighted additive index for preliminary self-assessment, pending future content-validity testing and expert-derived weighting. The framework supports five-level maturity classification, profile-based interpretation, compensability safeguards and illustrative sensitivity analysis, offering a reproducible basis for diagnosis, decision support and future empirical validation.

Sustainability doi: 10.3390/su18168105

Authors: Zhaokai Wang Longcang Shu Xiaolin Xia Lei Chen Xiqin Yan Huifang Wang Pengqiang Cao

Physical clogging limits managed aquifer recharge (MAR), yet the threshold-crossing time alone may not predict subsequent performance. Constant-head columns packed with borosilicate glass beads or quartz sand received a 50 mg L−1 silica suspension (0.9–2.7 μm) for 240 h. Hydraulic heads and discharge yielded relative apparent hydraulic-conductivity trajectories (Kr); X-ray computed tomography supported box-counting and block-network analyses. Sustained crossings below Kr=0.60, 0.50, and 0.40 occurred at 44/46, 61/59, and 88/78 h for the glass-bead/quartz-sand columns. Despite similar 0.60 and 0.50 crossing times, Kr values at 240 h were 0.475 and 0.043, respectively. The glass-bead trajectory rebounded after its minimum and remained above 0.40. Interface box-counting slopes depended on imaging branch and segmentation threshold, but the regional D2 and D3 ranks remained positively associated within each medium. Removing the highest-flow 5% of flow-carrying edges caused conductance-proxy losses of 0.521–0.692 across three capacity laws, greater than under random removal. For the two tested cases, threshold persistence, subsequent direction, and terminal state provided complementary evidence of hydraulic stability; broader application requires replicated tests across particle and loading conditions while retaining the distinction between obstruction probability and flow-path consequence.

Sustainability doi: 10.3390/su18168104

Authors: Evren Ülkeryıldız Ayşe Şekerci Şenoğlu Şerife İncedemir Sezen Başak Özünur Şahin

Nomadism and the tent tradition constitute foundational pillars of Anatolia’s vernacular building culture, yet the spatial continuity between nomadic dwelling practices and their urban coastal adaptations remains underexplored in the literature. This study examines how nomadic spatial strategies were reproduced in Antalya’s coastal oba settlements, evaluating them as architectural expressions of indigenous material culture and collective building knowledge rather than provisional structures. Employing a qualitative approach, the research synthesizes data from literature reviews, archival analysis, and semi-structured interviews with former residents, utilizing Lefebvre’s Rhythmanalysis as an analytic framework to examine how seasonal cycles, recurring daily rituals, and patterns of collective occupation shaped the spatial logic of these now-vanished settlements. Findings reveal three distinct oba typologies with traceable morphological continuities to the nomadic tent tradition, particularly in semi-open spatial configurations, modular organization, and the flexible adaptation of indigenous materials to coastal conditions. Interpreted through the lens of cultural landscape, the oba emerges as a site where tangible building practice and intangible cultural heritage converge. The study concludes that Antalya’s coastal obas represent a significant yet under documented chapter of vernacular architectural heritage, one whose physical erasure under post-1980 tourism-driven development has rendered its preservation in collective and embodied memory all the more urgent. By transitioning from physical fabric to intangible heritage, these settlements persist as a critical representational field for cultural and social sustainability discourse.

Sustainability doi: 10.3390/su18168103

Authors: Xiaoqian Yang Ruili Hu Kejiang Lei Minbo Zhang

Safe and resilient operation of liquefied petroleum gas (LPG) storage and distribution stations is important to the sustainability of fuel infrastructure, yet boiling liquid expanding vapor explosion (BLEVE) prevention requires time-dependent barrier analysis and a clear separation between prevention priorities and post-rupture exposure. This study develops a dynamic–spatial screening framework that integrates evidence-graded basic events, a priority-AND dynamic fault tree, a continuous-time Markov chain (CTMC), memory-efficient Monte Carlo trajectory simulation, modeled-area prevention prioritization, and tank-origin relative-exposure screening. A one-million-trajectory accelerated numerical baseline produced 112,693 BLEVE-conditioned trajectories. Weld cracking and fire-pump failure had the highest dynamic criticality because they act in later barrier-degradation stages, whereas high-wind spread had the greatest conditional involvement. Tank structure had the highest modeled-area prevention priority. Receiver rankings depended on the assumed layout: P5 ranked first under the baseline schematic coordinates, whereas P2 ranked first under the illustrative metric-coordinate scenario across the tested distance-attenuation kernels. Convergence, acceleration-factor, evidence-grade, weight, recovery, alternative-path, static-importance, coordinate, and kernel sensitivities were evaluated. Prevention-priority scores and normalized exposure indices are reported separately and are not interpreted as calibrated accident frequency, physical dose, expected loss, or quantitative risk. By supporting targeted inspection, maintenance, monitoring, and emergency-resource allocation, the framework can contribute to safer, more resilient, and more sustainable operation of LPG infrastructure.

Sustainability doi: 10.3390/su18168102

Authors: Zheng Hong Cheng Zhang

Green innovation is an important means of mitigating environmental pollution, improving production efficiency, and promoting high-quality economic development. Using prefecture-level city data and China Family Panel Studies (CFPS) data from 2010 to 2022, this study applies the Super-SBM model to measure urban green innovation efficiency and examines its effects on residents’ consumption levels and household consumption structures. The results show that (1) green innovation efficiency significantly increases consumption among urban residents and urban households, whereas its effects on rural residents and rural households are not statistically significant; (2) green innovation efficiency significantly reduces the share of subsistence-oriented consumption while increasing the shares of housing, development-oriented, and tourism consumption, thereby promoting a shift in household expenditure from basic needs toward development- and enjoyment-oriented consumption; (3) wage income and housing debt constitute two distinct transmission channels. Higher wage income facilitates development- and enjoyment-oriented consumption, whereas housing debt increases the share of housing consumption and exerts a crowding-out effect on development-oriented and tourism consumption; and (4) green innovation efficiency has a more pronounced effect on development-oriented and tourism consumption among young and high-income households. For middle-aged and older households, as well as low-income households, the effects of green innovation are reflected more strongly in an increase in the share of housing consumption. The findings provide important empirical evidence that green innovation contributes to improving residents’ quality of life.

Sustainability doi: 10.3390/su18168101

Authors: Leslie Paul Thiele Glen Billesbach

Digital twins are computer-generated replicas that simulate complex systems based on continuous, bidirectional, and potentially multimodal data flow between the virtual and physical. As digital twins enable the analysis of the full lifecycle of entities, processes, and organizations, they are increasingly employed to advance sustainable development. Digital twins can improve the monitoring and measurement of natural resources, their efficient use, and their effective protection. But there are also risks involved. They may intensify surveillance, normalize technocratic control, and narrow interpretive horizons. Employing illustrative cases of their use, we assess the benefits of digital twins for sustainable development. In turn, we expose prominent risks and place them in a theoretical framework. While the technology promises more comprehensive accountability, improved efficiency, and heightened predictive capacity, it may also imprison the analog—individuals, organizations, and the natural world—in digital dictates and conformities. The challenge that we address is how sustainable development can be advanced by digital twin technology without degrading the capacities and complexities of people and planet.

Sustainability doi: 10.3390/su18168100

Authors: Ruonan Fang Jie Chen Qiuping Yi Yunhao Ren

This study examines the structural drivers of carbon emission changes across 30 Chinese sectors from 2002 to 2023, employing a nested input–output structural decomposition analysis model grounded in both producer and consumer principles. We further construct a carbon inequality-adjusted network decoupling index to eliminate the systematic carbon transfer bias inherent to the conventional Tapio decoupling indicator. The core empirical findings are as follows: declining carbon intensity has served as the primary driver of emission reductions over the past two decades; however, its effect has been persistently offset by economic expansion. Upstream sectors, such as electricity generation, transfer substantial emissions downstream through sectoral chains, leading to a systematic overestimation of their decoupling performance, whereas the emission reductions in downstream manufacturing sectors are underestimated owing to embodied carbon imports. Inter-industry carbon inequality underwent a structural transformation following the launch of supply-side structural reforms in 2015, which substantially narrowed the arbitrage space for cross-sector carbon shifting. Cluster analysis further reveals that most industries continue to face considerable emission growth pressure. This study offers novel analytical perspectives and empirical evidence for designing carbon allowance allocation and differentiated emission reduction pathways that reconcile economic growth with environmental sustainability. This study offers a new analytical perspective and empirical evidence. It focuses on differentiated emission pathways and allowance allocations. The goal is to balance growth and sustainability. The findings also highlight a key point. Carbon markets must correct for sectoral chain carbon transfers. This study focuses on carbon emissions from 30 broadly defined sectors covering agriculture, mining, manufacturing, energy production and supply, construction, transportation, and commercial services. The accounting scope does not include direct fuel combustion emissions from residential consumption.

Sustainability doi: 10.3390/su18168098

Authors: Suchada Ukaew Noppawan Motong Kullapa Soratana Weerawun Weerachaipichasgul Prakaytham Suksatit

The global use of millions of small rodents annually in medical research creates a need for environmental enrichment that is both practical and sustainable. This study investigated the use of banana pseudostem, an agricultural residue, as a potential material for a laboratory-scale rodent enrichment prototype. A life cycle assessment (LCA) and life cycle costing (LCC) were conducted under a cradle-to-grave system boundary that included production, facility use, sterilization, freezer storage, transport, and infectious waste management. The prototype had a global warming potential (GWP) of 28.40 kg CO2 eq per functional unit. The results showed that the production phase was the dominant contributor to the environmental impacts and costs. Heat pressing was identified as the main hotspot resulting from high electricity demand, while labor was the main cost contributor, as the manual production process at the laboratory scale was time-consuming. The scenario analysis revealed that modifying the press machine to press two pieces simultaneously reduced GWP by 37.54% and total life cycle cost by 29.11%. Full substitution of grid electricity with photovoltaic electricity for heat pressing reduced GWP by about 67.47%. Extending the replacement interval from 3 to 7 days showed the largest GWP reduction of 56.35%, although this option requires confirmation of animal welfare, hygiene, and structural durability. Although banana pseudostem is a renewable agricultural residue, the environmental impacts and costs of the prototype were mainly due to energy-intensive processing at the laboratory scale rather than the raw material. Further improvement in production efficiency and electricity sourcing is required to reduce impacts and increase the feasibility of the banana pseudostem enrichment prototype.

Sustainability doi: 10.3390/su18168099

Authors: Linh Do Thuy Truong Tam Thi Do Cuong Xuan Vu Kha Xuan Nguyen

This study develops and applies a GIS-based 3D visualization model for observed flooding and subsidence conditions to support preliminary spatial screening for sustainable urban land fund development in the rapidly urbanizing Binh Chanh area, Ho Chi Minh City, during the period of 2020–2024. Field-survey records, official flood records, topographic maps, InSAR-based subsidence information, rainfall and tidal records, cadastral data, urban land-use expansion data, and planning information were integrated in a GIS environment. A DEM was generated using IDW interpolation and used as the terrain base for overlaying observed flood-prone locations with elevation, subsidence, road networks, cadastral parcels, urban land-use expansion, and planned urban land fund development areas. The overlaid datasets were then visualized in ArcScene, and an integrated map of observed flooding, subsidence, and urban land-use planning to 2030 was created to support preliminary spatial screening for sustainable urban land fund development. The observed inventory shows an increase in recorded flood-prone locations from 12 in 2020 to 34 in 2024, with maximum recorded flood depth reaching approximately 1.0 m and the largest recorded inundated area approaching 56,000 m2. Areas below 1.2 m elevation account for 80.30% of the study area, while the high and moderately high subsidence classes occupy 57.19%. The proposed approach provides a practical, parcel-linked 3D GIS visualization tool for organizing observed flood information, communicating spatial constraints, and supporting preliminary screening in data-limited urbanizing areas.

Sustainability doi: 10.3390/su18168097

Authors: Tomasz Gorzelnik Mateusz Rzeszutek Jakub Bartyzel Paweł Jagoda Tomasz Pełech-Pilichowski

Mass concentrations of particulate matter are a fundamental metric for air quality and health impact assessment; however, they are insufficient for accurately characterizing exposure. They do not capture particle size distribution or number concentration. Therefore, aerosol assessment should include particle number concentration (PNC), which better represents toxicologically relevant fractions and enables more precise source identification. The aim of this study was to conduct a comprehensive evaluation of particle number concentration (PNC) measurements in the 0.3–10 µm size range obtained using three low-cost Sensirion SPS30 particle sensors under field conditions in an urban environment. The analyses included an assessment of agreement between the SPS30 sensors, an evaluation of their measurement performance against the OPS 3330 optical particle spectrometer, and the development of calibration models. The SPS30 sensors showed high inter-device repeatability for PNC in the 0.3–1.0 µm range (CVd < 2%). However, measurement performance declined with increasing particle size, with the index of agreement (IOA) decreasing from 0.8 (0.3–0.5 µm) to −0.5 (2.5–10 µm). Sensor accuracy was influenced by meteorological conditions: relative humidity primarily affected short-term variability (precision and dynamic agreement), while temperature controlled systematic bias. Although incorporating these variables into advanced calibration models improved performance, SPS30 sensors remained unsuitable for PNC measurements in the 2.5–10 µm range, exhibiting systematic errors of ~25% even after nonlinear correction. The findings support the responsible use of low-cost particle sensors for supplementary air quality monitoring, contributing to accessible environmental data and sustainable urban air quality management.

Sustainability doi: 10.3390/su18168095

Authors: Chang Zhang Yuxiang Huang Nina Xiong Zixu Zhu Long Zhao Jia Wang Lihong Sun

Sustainable urban development increasingly depends on the efficient and equitable provision of municipal infrastructure, and waste bins, as critical end-point facilities in urban solid waste management systems, directly influence waste disposal accessibility, collection efficiency, and service equity. However, existing studies remain limited in achieving effective demand–supply matching, controlling spatial redundancy, and evaluating equity in waste facility allocation. This study developed a multi-source spatial evaluation framework integrating waste generation demand, road accessibility, and building functional characteristics, and proposed a two-stage waste bin allocation approach by coupling Adaptive Non-Maximum Suppression (ANMS) with an improved Coverage Location Problem with Overlap Control (CLPOC) model. The proposed framework first generated a theoretical candidate site pool and applied ANMS to achieve spatially balanced candidate refinement, followed by CLPOC-based optimization to improve service coverage and reduce redundant configurations. The results demonstrated that the optimized scheme substantially reduced redundant facility locations while maintaining high service coverage, thereby improving spatial allocation efficiency. Although urban areas exhibited notable improvements in service equity, the enhancement in mountainous and scenic areas was constrained by terrain conditions and spatial clustering effects. This study provides an efficiency–equity balanced framework for fine-scale waste bin planning in hilly cities, offering methodological support for sustainable urban solid waste management and contributing to the broader goal of sustainable urban development.

Sustainability doi: 10.3390/su18168096

Authors: Jiedan Guo Thian-Hee Yiew Xiao Su Dongping Fu

Agricultural subsidy policies have increasingly shifted from production-oriented support toward incentives that reward environmental stewardship and the provision of ecosystem services. Despite their rapid expansion, evidence regarding the environmental effectiveness, economic efficiency, market implications, and food-security consequences of these eco-centric agricultural subsidies remains fragmented across policy frameworks and regions. This review synthesizes current evidence on eco-centric agricultural subsidies by comparatively evaluating their environmental, economic, and policy outcomes across developed and developing economies. The review was conducted using a structured literature search following PRISMA-informed review procedures, drawing upon peer-reviewed articles, systematic reviews, policy evaluations, and international institutional reports retrieved from major scientific databases and policy sources. The evidence indicates that eco-centric subsidies generally improve biodiversity conservation, soil health, carbon sequestration, water quality, and reductions in chemical inputs when payments are appropriately targeted and supported by effective monitoring and institutional capacity. Performance-based and results-oriented payment schemes frequently demonstrate greater environmental additionality and cost-effectiveness than conventional practice-based payments; however, their broader implementation remains constrained by monitoring costs, verification requirements, administrative complexity, and regional institutional capacity. Economic outcomes are more heterogeneous, with benefits depending on program design, agroecological conditions, market structures, and farm characteristics. While these subsidies can enhance environmental returns on public investment, challenges including land-value capitalization, unequal benefit distribution, transaction costs, market distortions, and potential short-term productivity trade-offs remain important policy concerns. Evidence regarding food-security impacts is similarly context-dependent and varies across production systems and geographical regions. Overall, the review demonstrates that no single subsidy instrument is universally effective. Instead, the greatest environmental and economic benefits are achieved through integrated policy portfolios combining targeted incentives, outcome-based payments, robust monitoring systems, digital technologies, carbon-market integration, and equitable program design. The review also identifies important evidence gaps concerning developing-country experiences, long-term cost-effectiveness, and standardized evaluation frameworks, providing priorities for future research and policy development.

Sustainability doi: 10.3390/su18168090

Authors: Ignacio Faúndez Yimmy Fernando Silva Arturo Reyes-Román Héctor Hernández Gerardo Araya-Letelier

Incorporating supplementary cementitious materials (SCMs) and alternative aggregates promotes cleaner production of cement-based materials; however, optimizing their coupled effects on mechanical and environmental performance remains a key challenge. This study assesses the valorization of copper slag (CS), a massive industrial mining by-product, simultaneously as an SCM and an artificial fine aggregate (AFA) in the development of mortar mixtures with better performance and lower embodied carbon. Specifically, CS partially replaced Portland cement (PC) at 0% and 15% by volume, while natural fine aggregate (NFA) was substituted with AFA at volumetric replacement levels of 0%, 20%, 40%, and 60%. Mortar performance was systematically evaluated in the fresh state via workability and in the hardened state through water absorption, alongside short- and long-term compressive and flexural strength development. Furthermore, a cradle-to-gate life cycle assessment (LCA), expressed in terms of embodied carbon (EC) emissions, was executed to assess the environmental performance of the mixtures. The results indicate that incorporating CS as both SCM and AFA improved mortar workability by up to 30.9% compared to the reference mortar mixture (100% PC and 100% NFA). At 7 days, compressive strength decreased by 4% to 20% relative to the reference mortar. However, long-term performance improved substantially; at 330 days, mixtures with 15% CS–0% AFA and 15% CS–60% AFA achieved average compressive strengths of 42.9 MPa and 53.1 MPa, respectively, outperforming the reference mortar (42.1 MPa) by up to 26%. The cradle-to-gate embodied-carbon assessment showed that CS incorporation reduced product-stage emissions, although outcomes depended on transport distance and strength development. EC ranged from 369.8 to 438.0 kg CO2e/m3. When transport was included, EC decreased by approximately 14%, while 330-day strength-normalized EC decreased by 29.6–32.1% relative to the reference mixture. Overall, CS-based mortars improved fresh-state properties, enhanced long-term mechanical performance, and reduced product-stage embodied carbon, demonstrating their potential for cleaner production.

Sustainability doi: 10.3390/su18168089

Authors: Marialaura Giuliani Michele Pezzagno Anna Richiedei

Soil sealing is a major driver of urban transformation, generating significant environmental impacts through the loss of soil functions and Ecosystem Services (ES). In this context, economic valuation of ES has emerged as an effective tool for communicating the importance of soil within decision-making processes largely influenced by market dynamics. Despite extensive research on ES, reviews focusing on how economic valuation can support local planning remain limited. As a consequence, this study presents a semi-systematic literature review addressing two research questions: (1) how ES assessment can be integrated into local planning tools and practices, and (2) which monetary metrics can ethically and effectively represent ES values within planning frameworks. Conducted in RStudio, the review combined automated screening of 2500 records with further manual selection and an analytical framework to examine ES definitions, valuation methods, spatial assessment units, and planning applications. The findings indicate that the rigor, methods, and level of detail of ES assessments should be adapted to planning objectives, available resources, territorial context, and stakeholders involved, supporting site-specific decisions. A cross-scale approach emerges as the most suitable for integrating ecological processes with administrative planning, while robust, flexible, and participatory governance across administrative levels is essential. Finally, despite the need for a shared methodological framework, standardized approaches such as the System of Environmental Economic Accounting–Ecosystem Accounting (SEEA EA) are still rarely adopted, particularly for local-scale and monetary ES assessments. Overall, the review provides a transparent and operational approach for integrating ES into spatial planning through interdisciplinary and participatory approaches and strengthening planning systems to prevent soil sealing and promote long-term community benefits.

Sustainability doi: 10.3390/su18168094

Authors: Hao Li Yuqian Zhang

With the rapid development of digital technologies, hardware products in two-sided platforms are continuously upgraded, creating challenges for the economic and operational sustainability of platform ecosystems. Platforms must address not only consumers’ strategic waiting behavior but also horizontal seller competition when making pricing decisions. To stimulate consumption and promote product upgrading, governments have introduced subsidy programs for end consumers. This paper develops a two-period dynamic game model involving the government, a monopolistic two-sided platform, buyers, and sellers to examine the effects of three subsidy schemes—no subsidy, consumption subsidy, and trade-in subsidy—on platform pricing, market equilibrium, and social welfare. The results show that: Consumption subsidies intensify buyers’ strategic waiting behavior, reduce current demand for original products, and exacerbate seller competition; as seller competition weakens, platforms reduce product prices and increase seller commissions under all subsidy schemes; and the trade-in subsidy effectively promotes product upgrading and avoids demand cannibalization while maximizing social welfare and generating the highest platform profit and seller surplus, thereby aligning the government’s welfare objective with stakeholder participation incentives and supporting the sustainable operation of the platform. This study enriches the literature on revenue management and two-sided markets. The findings provide theoretical support for platforms’ intertemporal pricing decisions and offer policy implications for designing economically sustainable government subsidy programs for hardware products in two-sided platforms.

Sustainability doi: 10.3390/su18168088

Authors: Wen Xiang Jianzhong Gao

Based on microscopic survey data of 10,057 kiwifruit growers from the Shaanxi, Guizhou, and Sichuan provinces in China, this study takes the initial and sustained adoption of low-carbon agricultural technology by farmers as dependent variables. A comprehensive evaluation system is constructed based on the digital capability of farmers. The system covers four dimensions, namely, digital access, digital acquisition, digital processing, and digital sharing. Multiple empirical models, including Lasso regression, extreme gradient boosting, random forest, and back propagation neural network are adopted to compare the fitting and predictive performance of different approaches. The model comparison results demonstrate that the random forest model presents the optimal fitting performance among all alternative specifications. To identify the core influencing factors and explore the underlying mechanisms, this study employs the SHAP method to quantitatively evaluate the marginal contribution of each variable. The empirical findings reveal that the digital capability of farmers significantly and positively promote both initial and sustained adoption of low-carbon agricultural technology with distinct dimensional heterogeneity. Specifically, digital access and digital acquisition capability act as core driving factors for the initial adoption of technologies by farmers, while digital processing and digital sharing capability play a decisive role in facilitating sustained low-carbon technology application. In addition, farmers’ education level, health status, household income, cooperative participation, and household labour scale are crucial characteristic variables affecting the behaviours of farmers in the adoption of low-carbon technology across different stages. Accordingly, this study proposes targeted policy implications for low-carbon agricultural development. On the basis of promoting digital rural construction and improving the systems of digital skill training and digital agricultural technical services, it is essential to strengthen dynamic tracking surveys of farmers, accurately identify their technology adoption stages, and implement differentiated supporting policies. These targeted measures can effectively consolidate and assess the low-carbon production behaviours of farmers and promote the long-term and sustainable development of low-carbon agriculture.

Sustainability doi: 10.3390/su18168092

Authors: Giuliana Parisi Alessia Ursino Rosa Caponetto

In response to the growing demand for sustainable regeneration and efficient operation of urban spaces, the adoption of digitalised facility management (FM) has emerged as an effective strategy. FM facilitates data-driven planning and optimised resource use, contributing to more sustainable and resilient urban environments. This research combines Building Information Modelling (BIM) with Visual Programming Languages (VPLs) to support the regeneration and optimisation of an urban park. Autodesk Revit is employed to develop an LOD 300 semantic and geometric model, while Dynamo enables the implementation of two parametric scripts: Script A, governing on/off control of monitored systems based on environmental, temporal and contextual conditions, and Script B, providing continuous operational monitoring, fault diagnosis and color-coded visual feedback directly within the BIM environment. The framework is tested at Parco Gioeni, an 8.6-hectare historically and geologically urban park in Italy, across three management systems: irrigation, nebulization and green area monitoring. A total of 28 what-if scenarios are conducted across systems, indicating the framework’s functional consistency and contextual adaptability under the tested conditions. The proposed approach is built on accessible open software tools, making it transferable to public administration contexts, and is designed to be scalable and replicable across different urban green space typologies.

Sustainability doi: 10.3390/su18168093

Authors: Min Li Yurong Wang

The water–energy–carbon (WEC) nexus is central to sustainability, yet the role of water quality as a potential moderator within this nexus remains empirically underexplored. Using a fixed-effects panel regression model applied to provincial-level data from the Yellow River Basin over the period of 2007–2022, this study provides systematic evidence that water quality significantly moderates the WEC nexus. The empirical findings indicate that (1) water quality negatively affects the WEC nexus significantly; (2) the moderating effect presents spatial heterogeneity, showing greater carbon reduction potential in middle and lower reaches; and (3) the marginal impact of water cycle energy consumption on carbon emissions declines monotonically with improvements in water quality, with a sample-specific estimated critical point identified at a compliance rate of 88.159%—below which the marginal effect remains positive and above which it turns negative. (4) The moderating effect exhibits pronounced spatial heterogeneity, being significantly positive in the middle and lower reaches but insignificant in the upper reaches, and is significantly strengthened after the implementation of China’s strictest water resource management policy in 2013. These results suggest that water quality serves as a strategic lever for synergizing WEC governance. The findings offer theoretical and practical insights for adjusting the tightly coupled WEC nexus in the Yellow River Basin, with implications for region-specific and threshold-oriented policy design.

Sustainability doi: 10.3390/su18168091

Authors: Łukasz Sroka Adrianna Mastalerz-Kodzis

This study examines the determinants of conditional volatility in energy-sector equity returns and their implications for sustainable energy resilience, energy security, and investment stability. Using a multi-stage econometric framework, the analysis investigates how global financial, commodity, and macroeconomic shocks are transmitted to volatility dynamics across heterogeneous energy companies. The dataset includes domestic and international firms, enabling a comparative assessment of volatility behavior and risk-transmission mechanisms under different market and institutional conditions. The empirical framework combines ARMA models for return dynamics, EGARCH/GARCH specifications for conditional volatility estimation, and OLS regressions with HAC standard errors to identify key determinants of volatility, including market indices, commodity prices, exchange rates, and major geopolitical and economic events. The findings reveal strong volatility persistence across all assets and asymmetric responses to market shocks in most cases. Global market conditions, particularly lagged MSCI World returns, significantly affect volatility, whereas commodity effects related to oil, gas, and coal remain heterogeneous across firms. Event-based regressors show that systemic shocks, including the COVID-19 pandemic and the European energy crisis, increase volatility, although geopolitical effects depend on firm-specific exposure. The results contribute to the sustainability literature by linking energy-sector financial volatility with market resilience, energy security, and stable investment conditions for the energy transition.

Sustainability doi: 10.3390/su18168087

Authors: Eman Abdraboo Hassan Shokry Takashi Asawa Marwa Elkady Hatem Mahmoud

The valorization of waste cooking oil (WCO) offers a sustainable pathway for improving building’s energy efficiency while supporting circular economy principles. This study developed a novel shape-stabilized bio-based phase change material (Bb-PCM) derived from WCO fatty acids for passive thermal regulation of building envelopes. Purified fatty acids were obtained through filtration, saponification, acidification, and solvent purification. The resulting Bb-PCM was then incorporated into a natural clay–cellulose supporting matrix containing four activated-carbon loading levels using a direct impregnation method. The composites were characterized using spectroscopic, thermal, and microstructural techniques. Differential scanning calorimetry under nitrogen at 2 °C min−1 showed melting temperatures of 34–35 °C and melting latent heats of 35.2–45.9 J g−1. Thermogravimetric analysis confirmed thermal stability below 100 °C, while microstructural characterization demonstrated differences in matrix densification and structural ordering among the composite formulations investigated. The composite containing 25 wt.% activated carbon exhibited the highest melting latent heat (45.9 J g−1) and favorable thermal conductivity (0.29 W m−1 K−1), representing the optimum composite formulation that balances thermal storage capacity, heat transfer, and structural stability. Outdoor evaluation demonstrated stable thermal performance, reducing indoor temperatures by approximately 2 °C, indicating strong potential for sustainable passive cooling applications in buildings.

Sustainability doi: 10.3390/su18168083

Authors: Chaoqun Zhang Wei Zhang Sitao Chen Yu Gu Dong Han

Demand response (DR) can improve power system flexibility and support low-carbon operation, yet the potential of Internet of Vehicles (IoV) communication infrastructures remains limited by the coupling between traffic distribution and the communication network load. Existing traffic-only or communication-only approaches do not exploit this cross-domain flexibility. This study proposes a sustainable traffic–communication–energy coordinated DR framework that uses dynamic route compensation to reshape communication loads. A Stackelberg mechanism coordinates the IoV operator and vehicle users while a large language model (LLM) generates and corrects adaptive compensation candidates under heterogeneous operating conditions. Compared with the no-guidance and static-compensation baselines, the proposed dynamic strategy redistributes traffic and communication loads, releases communication-side DR capacity, and improves both operator and user performance. Compared with the non-LLM decision baseline, LLM assistance increases the load regulation rate from 21.5% to 36.2%, raises cost savings from 16.8% to 28.5%, and increases the user response rate from 72.4% to 88.7%. The framework provides a sustainable pathway for using existing IoV communication infrastructure as a flexible demand-side resource.

Sustainability doi: 10.3390/su18168086

Authors: Sepehr Alizadehsalehi

Artificial intelligence (AI) is transforming healthcare and the built environment, yet its application to healthcare real estate (HRE) remains fragmented and poorly understood. This study systematically reviews AI applications across the HRE asset lifecycle to identify evidence gaps and evaluate their potential to improve decision-making, operational performance, and sustainable healthcare infrastructure. Following the Joanna Briggs Institute methodology and PRISMA-ScR guidelines, the search identified 2881 records, of which 87 studies met the inclusion criteria. Building on the evidence gaps identified through this mapping, this study develops conceptual contributions, including a lifecycle maturity index, the Algorithm-to-Asset-Value Translation Chain, and the AI-HREDF, that serve as theoretically grounded, testable proposals for future empirical investigation. Each study was classified by lifecycle stage, evidence directness, and evidence strength. Only 14 studies (16%) provided direct evidence linking AI to HRE decisions, while most focused on operations and facility management, leaving major gaps in site selection, planning, construction, and investment. This review identifies three evidence translation gaps that prevent AI advances from becoming measurable improvements in asset performance and financial value. To address these challenges, we propose the AI-Integrated Healthcare Real Estate Decision Framework (AI-HREDF), the Algorithm-to-Asset-Value Translation Chain, and a research agenda for future work. The findings provide a foundation for integrating AI into healthcare infrastructure planning, management, and investment while supporting more resilient, resource-efficient, and sustainable healthcare facilities.

Sustainability doi: 10.3390/su18168085

Authors: Peter Kačmáry Kristína Kleinová Norbert Lörinc

European energy markets have experienced significant instability as a result of consecutive global systemic shocks, particularly the COVID-19 pandemic and the geopolitical conflict in Ukraine. This paper analyses the development of crude oil and natural gas prices between 2019 and 2024 and discusses their implications for sustainable logistics, energy security and supply chain resilience in Europe. The study is based on secondary data from internationally recognized sources, including the International Energy Agency, OPEC, Eurostat, the European Council, the World Bank and the U.S. Energy Information Administration. An event-based comparative approach supported by descriptive price-change calculations was applied to distinguish between the pandemic-related demand shock and the geopolitical supply-side shock after 2022. The results show that crude oil prices declined from approximately 64 USD/barrel in 2019 to 41 USD/barrel in 2020, representing a decrease of about 3f5.9%, mainly in connection with reduced mobility, lower transport activity and industrial slowdown during the COVID-19 pandemic. In contrast, crude oil prices increased to approximately 100 USD/barrel in 2022, representing an increase of about 143.9% compared to 2020, coinciding with geopolitical uncertainty and supply-side pressures. The European natural gas market appeared particularly vulnerable to the 2022 crisis because of supplier dependence, pipeline infrastructure constraints and reduced Russian gas flows. EU natural gas demand declined by 55 billion m3, or 13%, in 2022, indicating the effect of high prices, energy savings and crisis adaptation. The findings suggest that crude oil shocks are mainly related to transport costs and freight rates, while natural gas shocks may influence energy-intensive production, warehousing, cold chains and broader supply chain stability. The study highlights the need for energy diversification, renewable and low-carbon energy development, energy efficiency and more resilient logistics strategies.

Sustainability doi: 10.3390/su18168084

Authors: Kinga Smolińska-Bryza Wiktoria Hoffmann Aleksandra Ostrowska Joanna Kuciel Kacper Bernacki Dawid Jabkowski

The aim of this article is to determine the significance of short supply chains for local and regional development in Poland. The supply chain in Poland is defined as a coordinated set of people, financial and material resources, and activities involved in the process of delivering goods and services from the producer to the end consumer. Short Supply Chains (SSCs) are the foundation of the green economy, aiming to minimize the number of intermediaries and build direct relationships based on trust. Although short supply chains have been widely discussed in the context of sustainable agriculture and rural development, there is still limited research examining how digitalization and local organizational models jointly influence the development of SSCs and their contribution to local and regional development in Poland. This study addresses this gap by analysing selected Polish case studies and examining the combined role of digitalization, institutional support, and local initiatives in strengthening short supply chains. The article presents the situation of short supply chains in Poland using the example of selected organizations and initiatives, such as Poznań Green Market, Sady Grójeckie, Warmiński Koszyk, and Wiejska e-skrzynka. These cases demonstrate the impact of advancing digitalization on the development of local food markets, particularly in terms of shortening distribution channels, increasing access to local products, and strengthening producer–consumer relationships. The economic basis of SSCs is based on farmers taking over market margins and diversifying their income through agricultural retail trade (RHD), marginal, local, and limited (MOL) activities, and agritourism. This development is stimulated by EU funds, including the Rural Development Program (RDP) and Local Action Group (LAG) initiatives, as well as ongoing digitization and growing demand for local food. Furthermore, the development of local markets and short supply chains in the food sector is in line with the European “Farm to Fork” Strategy, which aims to ensure better food quality, reduce waste, and decrease the environmental impact of food systems. The analysis presented in the article will highlight the potential of short supply chains in political processes and make a significant contribution to the debate on strategies for supporting local and regional food markets.

Sustainability doi: 10.3390/su18168082

Authors: Wanda Musialik Krzysztof Malik

Research on cultural heritage, regional resilience and Indigenous rights remains insufficiently integrated at the level of regional policy. This article develops a resilience-driven framework for analysing when Sámi cultural heritage in Norway, Sweden and Finland can support sustainable regional development. The study uses a conceptual research design based on a structured critical synthesis of the literature, model building and an illustrative policy application. The framework links environmental, social–cultural, economic and institutional dimensions of heritage with risk prevention, vulnerability reduction, adaptive capacity, transformative capacity and development capital security. It identifies land access, self-determination, effective participation, benefit-sharing and community control over knowledge as conditions governing heritage-to-resilience pathways. The country comparison illustrates a recurring gap between cultural recognition and influence over land and development decisions, while selected European instruments offer supportive but limited implementation pathways. The article does not claim causal proof. Its contribution is a conditional analytical and policy-screening framework that generates testable propositions and community-validated indicators for future empirical research.

Sustainability doi: 10.3390/su18168081

Authors: Ying Li Wentao Li Haihong Qin Xiaohua Zhou Yao Cui

Many coastal regions endowed with rich marine biodiversity fail to translate these resources into high-value pharmaceutical products—a “valorization gap” that obstructs progress toward SDG 14 (Life Below Water), SDG 3 (Good Health and Well-Being), and SDG 9 (Industry, Innovation and Infrastructure). This study investigates the governance barriers underlying this gap using China’s Marine Traditional Chinese Medicine (MTCM) industry as an empirical case. Guided by an integrated analytical framework synthesizing innovation systems theory, Triple Helix dynamics, global value chain analysis, and organizational ambidexterity, the study draws on semi-structured interviews with 16 stakeholders in Dalian and NVivo-based thematic analysis. Four interconnected barriers are identified: value chain lock-in at the food-product level, a fragmented innovation ecosystem with misaligned incentives, a translational “valley of death” caused by absent pilot-scale platforms and quality standardization deficits, and an underdeveloped industrial ecosystem trapped in a low-value equilibrium. Through benchmarking against Qingdao’s marine pharmaceutical model and international marine bio-pharmaceutical policies (Japan, Republic of Korea, EU), this study proposes a “Dual-Wheel Driving” sustainable governance framework that simultaneously pursues “stock upgrading” (standardization, sustainable sourcing, branding) and “increment cultivation” (strategic pharmaceutical R&D with green innovation principles), coordinated through a “one core, multiple nodes” institutional architecture. The findings offer transferable policy insights for similarly positioned coastal regions seeking to develop marine bio-pharmaceutical capabilities within a sustainable blue bioeconomy framework.

Sustainability doi: 10.3390/su18168080

Authors: Li’e Yu

The economic and social development of coal resource-exhausted cities (CRECs) depends heavily on coal resources. Measures to improve the carbon emission efficiency (CEE) of CRECs are urgently needed because this development path, characterized by high resource dependence, inevitably generates substantial carbon emissions. However, there has not been much focus on the spatial spillover effects and regional heterogeneity of CEE in these cities. To address this gap, this study selects 37 Chinese CRECs as research subjects. It comprehensively evaluates the static characteristics and dynamic changes in these cities’ CEE from 2011 to 2023 using the SBM-DDF model and the GML index. It then employs the spatial Durbin model to identify key influencing factors of CEE. According to the empirical results, the average CEE of the sample cities did not reach the production frontier, generally remaining at a moderate level and fluctuating. The main factor driving CEE growth for CRECs in all regions is technological progress. CRECs in the western region had the greatest growth in CEE (0.71%), followed by the northeastern (0.36%) and central (0.05%) regions, while the growth in CEE remained unchanged in the eastern region. The local CEE grew by 0.286 units for every unit increase in CEE in neighboring cities, demonstrating the spillover effects essential for regional sustainability. There is significant regional heterogeneity in the influencing factors of CEE in China’s CRECs, necessitating tailored sustainable development strategies.

Sustainability doi: 10.3390/su18168078

Authors: Guanhang Sui Geng Niu Tian Cheng Tianchi Duan Yu Zhang Huixiao Wang

Hydroclimatic variability and intensive human regulation have reshaped surface water dynamics in plain river network regions (PRNs), altering both water extent and stability. Unraveling the frequency structure of surface water and its nonlinear associations is critical for sustainable water resource management. Based on Landsat-derived surface water dynamics from 2015 to 2025, this study constructed water occurrence frequency (WOF) indicators for Lixiahe Plain (LP) and employed XGBoost-SHAP to identify key natural and human factors, nonlinear responses, and interaction effects. The results showed that: (1) the annual water surface ratio (WSR) exhibited a phased inverted-U pattern, increasing from 5.22% in 2015 to 6.04% in 2018, remaining high during 2018–2021, and decreasing to 4.57% in 2025; (2) WOF revealed marked stability restructuring, with low-frequency water accounting for 31.0–53.7% of annual water and becoming more dominant after 2023; (3) the XGBoost-SHAP models showed reliable performance, with R2 of 0.714–0.813 and RMSE below 0.018. Natural factors contributed more than human factors, and wind speed (WS), normalized difference vegetation index (NDVI) related features, and cropland ratio (CropR) were the influential factors, with approximate response transitions of 2.5–3.0 m s−1, 0.50–0.52, and 65–68%. These findings support refined water resource management and sustainable development in PRNs.

Sustainability doi: 10.3390/su18168079

Authors: Hao Liu Deli Wu Yufan Chen Chengsi Hou Guojie Ye Zhengwei Zhou Yue Wang

4-Chlorophenol (4-CP) is a persistent and highly toxic pollutant commonly found in groundwater. However, its efficient degradation remains challenging due to the rapid agglomeration of conventional zero-valent iron (ZVI) nanoparticles, their narrow pH operating range, and the environmental risks associated with synthetic chelating agents. To address these limitations, this study presents a rationally designed catalytic system integrating cyclodextrin polymer (CDP)-supported bimetallic Cu-Fe nanoparticles (Cu-Fe-CDP) with citric acid (CA) as a green complexing agent. The porous CDP matrix effectively mitigates nanoparticle agglomeration and provides abundant active sites, while the Fe-Cu bimetallic coupling accelerates electron transfer and iron corrosion. Critically, CA acts as a biocompatible ligand that sustains Fe(II)/Fe(III) redox cycling, expands the effective pH range, and enhances hydroxyl radical (·OH) generation. The system achieves 92.13% degradation of 4-CP within 80 min at pH 9.0 and nearly complete removal at pH values between 3.0 and 7.0. Mechanistic studies, including electron paramagnetic resonance (EPR) spectroscopy and radical quenching tests, confirm the dominance of ·OH radicals (82.67% inhibition by TBA) and the essential role of surface Fe(II)/Fe(III) cycling. The catalyst exhibits excellent reusability, broad-spectrum activity toward multiple pollutants, and sustained performance in real water matrices and long-term column tests with minimal metal leaching. This work demonstrates a chemically robust strategy for chlorophenol remediation using green citric acid and biodegradable CDP without exogenous oxidant addition, showing promise for further development toward practical applications.

Sustainability doi: 10.3390/su18168077

Authors: Muhammed Enes Karaoglan Yetis Sazi Murat

Accurate short-term travel time prediction is foundational for sustainable urban mobility and intelligent transportation systems on urban arterial corridors, where travel conditions are shaped by interacting traffic, weather, and public transport factors. This study proposes a multi-source machine learning framework for segment-direction-level prediction in the Denizli city center. Floating car data (FCD), Traffic Control Center (TCC) inductive loop detector measurements, historical weather, and public transport indicators were integrated into a 15 min time-segment structure. The final dataset includes 60 segment-direction targets. Performance was evaluated using Linear Regression, Random Forest, LightGBM, and LSTM under a chronological train-validation-test design. Tree-based ensemble models produced the most stable overall performance, with LightGBM and Random Forest yielding similarly low pooled test errors. Segment-level analyses revealed clear spatial and temporal heterogeneity, showing no single model is universally superior across all links. By providing reliable traffic-state information, the framework enables efficient traffic management and may indirectly reduce delay, fuel use, and emissions; these environmental effects were not quantified. SHAP-based interpretation showed that temporal and traffic-state variables dominate predictions, while weather and public transport provide complementary value.

Sustainability doi: 10.3390/su18168076

Authors: Shiwen Chen Ganxiang Huang Jiansheng Li Hongyan Wang

The digitalization and intelligent transformation of transportation have emerged as technological solutions for enhancing traffic efficiency and reducing traffic-related pollutants. However, existing studies primarily focus on traditional traffic emission reduction measures, and there is limited empirical evidence demonstrating how the digitization and intelligence of road infrastructure can reduce carbon dioxide emissions and air pollutants. To address this research gap, this study employed a difference-in-differences methodology to investigate the causal effects of the Smart Highways Pilot (SHP) policy on carbon emission intensity (i.e., CO2 emissions per unit of GDP) and air pollution (i.e., PM2.5 concentrations), using data from 272 Chinese cities spanning 2012 to 2023. Our estimation results demonstrate that the implementation of the SHP policy led to an average reduction of about 4.7% in CO2 emissions per unit of GDP and a 5.1% decrease in PM2.5 concentrations, translating to an average annual abatement of approximately 707,008 tons of CO2 and a 2.204 μg/m3 drop in PM2.5 concentrations among the sample pilot cities. Furthermore, the carbon reduction and pollution mitigation effects of the SHP policy were more pronounced in regions emphasizing pilot themes, such as infrastructure digitalization and vehicle–road collaboration, cities promoting new-energy vehicles, and eastern regions. This study provides robust causal evidence for policymakers to assess the synergistic carbon abatement and pollution reduction benefits of SHP policies, while contributing to the literature on smart transportation and sustainable development, and offering valuable insights for other countries and regions on building green, low-carbon transportation systems through the digitalization and intelligent upgrading of road infrastructure.

Sustainability doi: 10.3390/su18168075

Authors: Wei-Chih Lin Chuan Chang Kung Alvin Kuan

Effective sustainable environmental governance requires feedback between institutional risk management and lived public experience. We propose a hierarchical Topic–Aspect–Frame framework to compare pollution discourse across news and social media. Using 30,635 chunk-level Taiwanese Chinese texts collected from OpView Product Insight in May 2026, treated as an early summer one-month validation window, we analyze topic selection, aspect foregrounding, and frame-based risk construction. Category-balanced audits yielded conditional label precision among analyzable chunks of 91.3% for topics, 85.8% for aspects, and 90.1% for frames. Among 30,304 frame-eligible chunks, Governance/Regulation was more prevalent in news (gap = +4.47 pp; 95% CI = [+3.11, +5.88]), whereas Health and Lived Risk was more prevalent in social media (gap = −9.84 pp; 95% CI = [−10.68, −9.02]). Under the aspect-conditioned prototype design, sequential decomposition attributed the latter gap mainly to topic selection (−5.40 pp) and aspect foregrounding (−4.14 pp), with a smaller within-aspect component (−0.30 pp). Both core directions persisted across four fixed windows and 100 same-fraction subsamples. The framework offers a preliminary, auditable approach for identifying cross-media governance-experience mismatches, subject to seasonal, platform, denominator, and model-support constraints.

Sustainability doi: 10.3390/su18168074

Authors: Yongliang Luo Yu Han Biao Yang Xuwen Zheng Supannika Wattana Buncha Wattana

Provincial power systems must decarbonize while sustaining rapid demand growth and improving air quality; yet, few integrated assessments separate the contributions of renewable expansion and carbon capture, utilization, and storage (CCUS) for China’s less-developed regions. We apply the Low Emissions Analysis Platform (LEAP) to model Guangxi’s power system to 2060 under four scenarios—Reference (BAS), Renewable-driven (RES), CCUS-intensive (CCS), and an Integrated comprehensive-policy scenario (ICS). Under ICS, solar photovoltaic generation rises from 38 TWh in 2025 to 408 TWh in 2060 (close to half of all generations), non-fossil capacity grows by about 730%, and power-sector CO2 falls by roughly 95% relative to BAS. A counterfactual decomposition shows that CCUS provides about 75% of the CO2 reduction along the coal-retaining CCS pathway but only about 5% along the renewables-led ICS pathway and reduces neither SO2 nor NOx. The air-quality co-benefits—up to 82%, 78%, and 73% lower SO2, NOx, and PM2.5 than BAS—arise mainly from renewable substitution, which also abates carbon more cheaply (about 120–190 versus 300 CNY t−1 CO2) while sharply raising flexibility needs. Once avoided fuel and carbon-market costs are included, the renewables-led pathways become net cost-saving on a full-system basis and yield a monetized air-quality health co-benefit roughly twice that of the CCUS-intensive route. The findings give policy-relevant guidance for sustainable low-carbon transitions in Guangxi and comparable emerging regions.

Sustainability doi: 10.3390/su18168073

Authors: Imène Belabbas Zhan Su

Artificial Intelligence of Things (AIoT), which refers to the combination of Artificial Intelligence (AI) and the Internet of Things (IoT), has become an important research area in smart farming. Although the literature on AIoT has expanded rapidly, little is known about its overall development, intellectual structure, and emerging research directions. To bridge this research gap, this paper examines the AIoT literature in smart farming using a bibliometric approach based on publications indexed in the Web of Science Core Collection. Bibliometric techniques, including performance analysis, keyword co-occurrence analysis, and bibliographic coupling, were employed to examine publication trends, most relevant journals in the field, top scholars, countries, institutions, and research themes. The findings show a rapid growth of AIoT research, driven mainly by engineering and computer science disciplines. Five major research themes are identified, covering AI applications in agriculture, IoT-enabled smart farming, intelligent sensing systems, agricultural data management, and prediction models. Based on these findings, the study discusses the evolution of AIoT research, identifies current research gaps, and proposes a future research agenda focusing on artificial intelligence, interoperability, cybersecurity, data quality, technology adoption, sustainability, and responsible innovation. This study provides an extensive overview of AIoT research in smart farming and provides useful directions for researchers and practitioners interested in the future development of digital agriculture.

Sustainability doi: 10.3390/su18168072

Authors: Lulu Liu Da Gao Jinda Zhao

As climate governance and low-carbon transition continue to advance, environmental information disclosure (EID) has become an important tool for strengthening corporate environmental accountability. Based on a sample of Chinese A-share listed firms from 2008 to 2023, this study constructs a firm-level FinTech index by employing a BERT large language model and examines its relationship with EID via a two-way fixed effects model. The results show that FinTech development is positively associated with EID levels, with stronger effects observed in non-high-tech and non-manufacturing firms. In addition, mechanism tests suggest that FinTech may enhance EID by promoting internal green innovation and reducing external information asymmetry. Further analysis indicates that stronger environmental regulation and higher internal control quality may reinforce the positive relationship between FinTech and EID. These findings provide empirical evidence for understanding how FinTech supports the modernization of corporate environmental governance.

Sustainability doi: 10.3390/su18168071

Authors: Lulu Liu Xiaotian Zhou Da Gao

Against the backdrop of global low-carbon transformation, carbon finance plays an increasingly pivotal role in advancing green innovation (GI) and industrial upgrading. Drawing on data from manufacturing enterprises listed on China’s A-share market between 2009 and 2023, this study innovatively constructs an enterprise-level carbon finance (CF) index. The research indicates that: (1) CF has been found to significantly promote corporate green innovation, exhibiting a positive effect on both the quantity (Gqua) and quality (Gqli). Theoretical derivations indicate that, during the initial entry of firms into the carbon market, CF can directly incentivize firms to increase their optimal proportion of green innovation. In the market adaptation phase, CF strengthens green research and development investment by alleviating firms’ financing constraints, and this effect is amplified as the CF application increases. (2) The mediating test indicates that CF enhances both the quantity and quality of green innovation by alleviating the problem of digital knowledge-based faultlines in executives and information asymmetry. (3) The moderation analysis shows that both financing constraints and market concentration negatively moderate the relationship between CF and green innovation. (4) The heterogeneity analysis indicates that the positive effects of CF are more pronounced among highly polluting and high-technology firms. These findings provide valuable theoretical and policy insights for promoting the green transformation of the manufacturing sector.

Sustainability doi: 10.3390/su18168070

Authors: Xinyi Li Wenqi Wang Meng Zhang

Using bilateral agricultural machinery trade data for 15 RCEP member states from 2004 to 2023, this study constructs a directed weighted network and applies social network analysis and the quadratic assignment procedure (QAP) to examine structural evolution, node positions, community patterns, and factors associated with bilateral trade ties. Network density increased from 0.467 to 0.962, average path length declined from 1.533 to 1.038, and betweenness centralization fell from 0.064 to 0.021, indicating denser connections, shorter potential transmission paths, and lower dependence on intermediary nodes. After 2020, China recorded the highest centrality, while Japan, the Republic of Korea, Australia, Singapore, and major ASEAN economies retained complementary positions. QAP results show positive associations of trade ties with GDP differences, common language, contiguity, and exchange-rate differences, and negative associations with water-resource differences, trade-structure differences, and institutional distance. These findings demonstrate a close relationship between trade networks, the diffusion of sustainable technologies, and regional supply chain resilience. Policy priorities include supplier diversification, compatible sustainability standards, lifecycle governance, regional repair and remanufacturing capacity, and inclusive access to machinery services.

Sustainability doi: 10.3390/su18168069

Authors: Aleksandra Lubicz-Posochowska Dorota Benduch Borys Budka Krzysztof Zamasz Filip Nawrot

Upper Silesia, historically shaped by hard-coal mining and coal-based energy production, is undergoing a critical phase of just transition under the European Union’s 2050 climate-neutrality objective. This study examines the legal, institutional, and spatial conditions shaping this process and assesses declared social acceptance in seven mining subregions of the Silesian Voivodeship comprising 64 municipalities. The research combines structured desk research on European Union, national, and regional policy and legal instruments with a CATI survey of electricity consumers in the transformation area (N = 602). Particular attention is given to regulatory barriers affecting the revitalization and redevelopment of post-mining and post-industrial land. The document analysis reveals fragmented institutional responsibilities, weak coordination between sectoral strategies, and insufficient integration of mine-closure, revitalization, and spatial-planning regulations. The survey findings indicate that public support for the energy transition is conditional rather than unconditional. Respondents generally acknowledge the need for change; however, they expect the principal financial burden to be borne by the state budget and energy companies, while direct household financing receives only marginal support. The results also show that the survey measured self-reported familiarity with the term “energy transition” rather than objectively tested knowledge. The study contributes an integrated analytical framework linking governance, legal-regulatory constraints, post-mining land regeneration, and declared social acceptance in a coal region undergoing structural transformation.

Sustainability doi: 10.3390/su18168068

Authors: Recep Akdağ

Businesses today operate under the influence of many micro and macro factors, such as competition, digitalization, sustainability, and global and local crises. Under these conditions, it has become necessary to use resources efficiently and without waste. Therefore, the implementation of lean production principles provides significant advantages for businesses. It is of critical importance to teach lean production to both employees and university students who are prospective employees through simulation games. Within this scope, a simulation game covering eight lean production principles was implemented with undergraduate business administration students. Feedback was collected from students, who were playing a simulation game for the first time, through pre- and post-tests, as well as an evaluation questionnaire. The evaluation questionnaire was found to be reliable based on the results of the reliability analysis. According to the findings obtained from the tests and the questionnaire, an increase was observed in the students’ level of understanding of lean production. The Paired Samples t-test indicated that the observed increase was statistically significant. Positive feedback was received regarding the design of the game, while both positive and critical opinions were obtained concerning its implementation.

Sustainability doi: 10.3390/su18168064

Authors: Yarong Shi Jibo Wang Mengnan Li

As an emerging form integrating digital finance and green finance, Green Digital Finance (GDF) serves as a critical driving force for consumption structure upgrading (CSU) and coordinated regional development. Based on panel data of 30 provincial-level regions in China from 2011 to 2023, this paper systematically investigates the enabling effect of GDF on CSU from the dimensions of spatial spillover effects, transmission mechanisms, income thresholds, and urban-rural heterogeneity. The empirical results show that the local effect of GDF on CSU is 0.057 and the spatial spillover effect is 0.094, with the spillover effect exerting significant impacts only in the short run. GDF functions by raising residents’ income, advancing industrial structure upgrading and easing credit constraints. A single income threshold exists at the income level of 23,414.25 yuan; after crossing this threshold, both the local driving effect and spatial spillover effect are significantly strengthened. Furthermore, GDF generates more pronounced driving effects on developmental consumption and rural areas. This study provides empirical evidence and implications for optimizing the allocation of regional financial resources and formulating differentiated policies.

Sustainability doi: 10.3390/su18168067

Authors: Anna Gronba-Chyła Agnieszka Generowicz Paweł Kwaśnicki Katarzyna Kamińska Dariusz Karalus

The increasing generation of municipal waste and the depletion of natural mineral resources have intensified the search for sustainable alternatives for construction materials within the framework of the circular economy. While waste glass, industrial residues, and selected municipal waste fractions have been extensively investigated individually as raw materials for lightweight aggregates, their simultaneous incorporation into a single ceramic matrix remains largely unexplored. To address this research gap, the present study investigates the feasibility of producing lightweight ceramic aggregates through the simultaneous incorporation of three municipal waste streams street sweeping waste (SSW), waste glass, and bulky waste into a clay-based ceramic matrix. Three ceramic mixtures containing different proportions of these waste materials were prepared, pelletized, and fired at 1100 °C. The produced aggregates were characterized in terms of loose bulk density, water absorption, total heavy metal concentrations, and heavy metal leachability, while the bulky waste was additionally characterized by loss on ignition to determine its organic matter content. All produced aggregates satisfied the requirements of PN-EN 13055-1 for lightweight aggregates, with loose bulk densities ranging from 442.9 to 543.1 kg m−3, comparable with commercially available expanded clay lightweight aggregates. Water absorption varied between 32.93% and 56.61%, with mixture composition explaining approximately 88% of the observed variance (one-way ANOVA, p < 0.001). Loss-on-ignition analysis revealed that bulky waste contained approximately 98.8 wt.% organic matter, confirming its effectiveness as a pore-forming additive during firing. Environmental assessment of the optimum mixture indicated limited mobility for most investigated heavy metals after thermal treatment; however, chromium leachability slightly exceeded the adopted reference value, indicating the need for further optimization of the ceramic composition. Overall, the developed lightweight aggregate represents a promising alternative to conventional lightweight aggregates and contributes to resource recovery, waste valorization, and the implementation of circular economy principles in the construction sector. Future research should focus on chromium speciation, mechanical performance, long-term durability, life cycle assessment, and pilot-scale production to support future industrial application.

Sustainability doi: 10.3390/su18168065

Authors: Guoxiang Hu Linjun Shi Feng Wu Chenyu Wu Keman Lin

Coordinating energy transactions with carbon allowance management is difficult in a multi-energy-coupled integrated energy system (IES) because seasonal carbon information and hourly operation are handled on different timescales. This study develops a multi-timescale low-carbon economic dispatch framework that integrates carbon–energy trading, low-carbon demand response, seasonal carbon-pressure signals, and preference-weight selection. The case study is a park-level electricity–heat–gas–cooling IES comprising two renewable generation technologies, five conversion technologies, five storage technologies, four end-use load types, and external electricity and gas interfaces. Four 24 h profiles—one for each season—are combined into a 96 h representative horizon. Historical renewable-output and load data are used to derive seasonal carbon-pressure signals, which are embedded in electricity, heat, and gas prices. Cooling demand is treated separately through a fuzzy thermal-comfort response. An outer IGA searches the economic preference weight, while CPLEX solves the hourly dispatch problem for each candidate. The selected economic and carbon-emission weights are 0.62 and 0.38, respectively. Compared with the conventional scenario, the complete framework reduces carbon emissions from 1052.92 t to 970.24 t and operating cost from CNY 1,103,420.84 to CNY 900,485.52, corresponding to reductions of 7.85% and 18.39%. In practical terms, the framework converts seasonal carbon-management information into hourly decisions without relaxing explicit comfort limits. The reported gains apply to the modeled 96 h representative horizon and should not be interpreted as annual performance.

Sustainability doi: 10.3390/su18168061

Authors: Juntao Zhong Jia Xu Bei Wang Kexin Jin Jiaqi Li Mengyue Xing Yixuan Yao Ying Gao

Accurately understanding the scale dependence of complex interactions among ecosystem services and their driving mechanisms is of great significance for regional ecosystem management. However, existing research has insufficiently addressed the scale sensitivity of ecosystem services interactions and their underlying driving mechanisms, particularly in ecologically critical mountainous regions. This study focused on the Qinling–Daba Mountains in Shaanxi Province and examined three key water-related ecosystem services. The InVEST model was employed to assess water yield, water purification, and soil conservation services across three spatial scales—5 km × 5 km grid, sub-watershed, and county—over the period 2002–2022. Pearson correlation analysis and geographically weighted regression were applied to quantify trade-off and synergies relationships at each scale, and the Geodetector method was used to systematically analyze their multi-scale driving mechanisms. The main findings were as follows: (1) All three ecosystem services exhibited significant spatiotemporal heterogeneity across scales. Water yield showed an overall increasing trend, rising from 230.25 mm in 2002 to 333.64 mm in 2022; water purification declined persistently, decreasing from 0.38 kg/ha to 0.30 kg/ha; and soil conservation increased substantially, from 78.59 t/ha to 99.85 t/ha, with the spatial patterns of each service varying markedly across scales. (2) Ecosystem services interactions demonstrated strong temporal stability but significant spatial scale dependence. The synergies between water yield and water purification weakened monotonically with increasing scale, whereas both the intensity of synergies between water yield and soil conservation and the trade-offs intensity between water purification and soil conservation strengthened progressively with coarsening scale. (3) Both the number and the explanatory power of significant driving factors and their interactions increased systematically with coarsening scale. Land use factors (FLP, CLP) were dominant at grid scale, while the importance of climatic factors (PRE) and socioeconomic factors (GDP, POP) increased progressively from the sub-watershed to the county scale. Interaction types underwent three-stage scale-dependent transitions: two-factor enhancement and nonlinear enhancement coexisted at the grid scale; nonlinear enhancement became overwhelmingly dominant at the sub-watershed scale; and enhancement and weakening types coexisted at the county scale, producing a heterogeneous interaction structure. These findings reveal that the direction, intensity, and driving mechanisms of ecosystem services interactions are inherently scale-dependent. These conclusions methodologically demonstrate the necessity of multi-scale analytical frameworks and provide important scientific foundations for developing scale-matched, spatially differentiated ecological management strategies.

Sustainability doi: 10.3390/su18168066

Authors: Saber Rahimi Meghdad Jourgholami Rachele Venanzi Rodolfo Picchio Angela Lo Monaco

Soil compaction alters soil structure and hydrology by increasing bulk density and penetration resistance, disrupting aggregates, reducing porosity and infiltration capacity, and enhancing shear strength. These changes can impede seedling establishment, particularly by restricting root development. The objective of this study was to evaluate the effects of a controlled soil penetration resistance (SPR) gradient on velvet maple (Acer velutinum Boiss.) seedling growth, morphology, and architecture under nursery conditions in northern Iran’s Hyrcanian forests. We hypothesized that increasing compaction would reduce seedling size and total biomass while altering the pattern of biomass partitioning between above- and belowground organs. Seven compaction levels were induced using a 4.736 kg hammer dropped from 45.7 cm, applying 0 (control), 1, 2, 4, 6, 8, or 10 blows per layer across 35 pots (5 replicates per level). After the 227-day growing period, seedlings were carefully excavated; root systems were gently washed, and all morphological indicators (main root length, lateral root length, and stem length) were measured manually using a ruler. Soil compaction resulted in a marked increase in soil penetration resistance (SPR), rising from 0.32 ± 0.03 MPa in the control treatment to 2.09 ± 0.08 MPa at the highest compaction level (p ≤ 0.01). Elevated SPR elicited significant polynomial responses in seedling morphological traits, including stem and root dimensions, as well as in biomass accumulation (total, shoot, and root). Notably, the main root biomass exhibited a significant decline with increasing compaction intensity, whereas lateral root length increased correspondingly, despite a reduction in lateral root biomass. These findings indicate that, in loam to clay-loam soils under optimal moisture conditions, total seedling biomass increased with moderate compaction, peaking near 1.5 MPa, whereas significant root growth reduction occurred above approximately 1.2 MPa. Above this level, compensatory lateral root elongation and a shift in biomass partitioning toward shoots were observed, but severe compaction (>1.5 MPa) ultimately suppressed whole-plant productivity. The study identifies a novel root architectural trade-off characterized by a 198% increase in specific root length and a tripling of the lateral-to-main root length ratio under severe compaction, providing species-specific thresholds and early-warning indicators for nursery soil management. These findings provide valuable insights into adaptive seedling responses to soil compaction and contribute to the development of sustainable forest nursery practices. Improving seedling quality under compacted soil conditions can enhance plantation success, soil conservation, and the long-term sustainability of forest restoration programs.

Sustainability doi: 10.3390/su18168063

Authors: Fisnik Osmani Arlinda Bresa Xhevat Berisha Betim Shabani

District heating provides efficient urban heating; however, sustainable cost allocation methods in multi-apartment buildings often require additional attention, especially in developing markets such as Prishtina, Kosovo. These systems often rely on flat-rate billing, and they fail to account for heat consumption in common areas. Consequently, not all heat entering the building is accounted for or billed. This leads to systemic cross-subsidization, penalizing energy-conscious consumers while allowing inactive or unoccupied units to benefit from unmetered heat transfer without contributing to the associated costs. To address this, this study proposes a coefficient-based economic allocation model to equitably distribute common area heating costs in mixed-metered buildings, thereby promoting sustainable energy consumption. Using Prishtina as a case study, the methodology determines an optimal common-heat coefficient (β) via constrained boundary analysis based on a physical constraint (net-to-gross area ratio of the building stock ≤ 27.5%) and an economic constraint (fixed charges ≤ 30%). The methodology was informed by a comprehensive dataset of 414 thermal substations provided by the district heating provider “Termokos” (covering 18,546 heating units during the 2024/2025 heating season), with Substation 277-UL presented as a field case study to demonstrate the practical application and validity of the model. The results show three findings: First, the optimal coefficient is established at β = 20%, satisfying both boundaries and showing that the attributed part of the heating consumption for the common area should not surpass this value. Second, the framework tackles cross-subsidization, reducing specific bills for regular, heat cost allocator-metered consumers by 21.7% compared to unmetered billing. Third, the model proposes a transparent approach to distribute common heat costs across the building community, ensuring equitable participation in shared thermal expenses of common areas. Hence, this research serves as a first step toward establishing equitable billing policies, maintaining energy balance, and fostering socio-economic and energy sustainability in the district heating industry.

Sustainability doi: 10.3390/su18168062

Authors: Jie Yang Lei Chen Lingchuan Song

Internet use has become an important channel through which citizens encounter and interpret information about social and environmental conditions. Using 2351 respondents from the Chinese General Social Survey 2021 (CGSS2021) in the baseline analyses, this study examines the association between Internet use frequency and local environmental satisfaction and explores perceived general social fairness as a possible social-evaluative correlate. Local environmental satisfaction is measured using a single six-category item concerning respondents’ satisfaction with their surrounding natural environment. Ordered Probit models are used as the primary specification, with OLS and Ordered Logit models reported as complementary specifications. The analysis additionally reports the category distributions of the principal ordinal variables, comparisons of local environmental satisfaction across Internet use frequency categories, pairwise correlations, and variance inflation factor diagnostics. More frequent Internet use is negatively associated with local environmental satisfaction. The coefficient remains negative across the reported specifications, although its model-specific magnitude and statistical precision vary with covariate and regional adjustment. An exploratory indirect-association analysis based on 2338 respondents indicates a small indirect association involving perceived general social fairness. Both component equations treat their outcomes as ordinal and are estimated using Ordered Probit models; statistical uncertainty is evaluated using 5000 nonparametric bootstrap replications with bias-corrected 95% confidence intervals. Because the data are cross-sectional, the focal constructs are measured using single survey items, and residual confounding and sample-selection bias cannot be excluded, the findings do not establish temporal ordering or causality.

Sustainability doi: 10.3390/su18168059

Authors: Miguel García Sánchez Teresa Briz de Felipe

Urban community gardens are increasingly institutionalized through public land, infrastructure, and administrative recognition, yet the mechanisms through which formalized gardens retain—or lose—civic purpose remain insufficiently understood. This article examines Madrid through a qualitative comparative case study involving 33 participants: 30 participants across 13 community gardens and three contextual actors. A layered, multi-perspectival adaptation of Interpretative Phenomenological Analysis combines idiographic interpretation with site-level and cross-case comparisons. An embedded quantitative content analysis of a transparent 12-garden transcript subsample (approximately 85,219 Spanish-language words) normalized six thematic dictionaries per 1000 words and used exploratory Mann–Whitney U tests. No thematic-rate difference reached statistical significance, suggesting that cultivation layout alone does not explain civic capacity. Cross-case analysis identifies five mediating processes: distributed roles, recurrent collective routines, knowledge translation, boundary-spanning partnerships, and accessible routes into participation and voice. Participants experienced gardens as therapeutic and relational counter-spaces, settings of agroecological learning, civic classrooms, modest forms of food autonomy, and negotiated commons. Food-security contributions were supplementary, whereas ecological literacy, practical competence, social connection, and collective agency were substantial. Adaptive Civic Commons is proposed as a framework for publicly anchored, community-led commons whose continuity depends on adaptation in governance, ecological practice, civic pedagogy, and public legitimacy.

Sustainability doi: 10.3390/su18168058

Authors: Lihong Li Mingxuan Xing Rui Zhu

Energy Management Contracting (EMC) is important for scaling energy-saving retrofits in existing buildings, yet policy incentives often fail when stakeholders perceive costs, benefits, and enforcement risks differently. This study aims to examine how subjective cognitive biases affect strategic interactions among governments, energy service companies (ESCOs), and energy-consuming units (ECUs) in China’s existing-building EMC market. Prospect theory is introduced into a tripartite evolutionary game model, and replicator dynamics with MATLAB R2024a simulations are used to analyze policy incentives, regulatory constraints, and behavioral parameters. The simulation results show that, among conventional policy parameters, moderate incentives and bilateral penalties are more effective than simply increasing subsidies or imposing unilateral punishment; when regulatory costs exceed a sustainable range, active supervision becomes unstable and cooperative implementation is weakened. Among prospect-theory parameters, higher loss aversion increases the perceived burden of fiscal and regulatory costs, while lower probability weighting reduces the perceived certainty of inspection and punishment. Reducing γ from 0.69 to 0.4 substantially weakens deterrence, and increasing λ from 1.5 to 2.25 intensifies strategic fluctuations. These findings provide a behavioral basis for designing staged EMC governance policies and offer practical implications for improving the stability and effectiveness of existing-building EMC implementation.

Sustainability doi: 10.3390/su18168035

Authors: Mohamed Ghonimy Mohamad I. Motawei

Sustainable orchard production requires precision pollination technologies that improve pollen deposition while minimizing application losses and supporting efficient biological input management. This study developed and evaluated a portable electrostatic pneumatic pollination system for date palm by integrating pneumatic conveying with corona electrostatic charging through sequential laboratory optimization and field validation. Laboratory experiments investigated the effects of airflow velocity, pollen-to-carrier mixing ratio, and electrostatic charging on material delivery rate, feeding stability, deposition efficiency, and electrostatic improvement. Airflow velocity and pollen-to-carrier mixing ratio significantly affected the material delivery rate (p < 0.001), whereas electrostatic charging did not influence pneumatic conveying performance. In contrast, deposition efficiency was significantly affected by all investigated factors and their interactions (p < 0.001), demonstrating enhanced pollen deposition while maintaining stable particle transport. The optimum operating condition consisted of an airflow velocity of 11.0 m s−1, a pollen-to-carrier mixing ratio of 1:8 (w/w), and electrostatic charging enabled, achieving a deposition efficiency of 86.4% with an electrostatic improvement of 46.94%. Field validation confirmed significantly higher fruit set than conventional pneumatic and manual pollination. The novelty of this work is the integration and experimental validation of electrostatic particles charging with pneumatic precision pollination through a laboratory-to-field optimization framework, providing a practical engineering strategy for sustainable artificial pollination in commercial date palm orchards.

Sustainability doi: 10.3390/su18168060

Authors: Huaigang Cheng Jialu Wang Wenjiao Xu Zhuohui Ma Bo Wang Xiaobing Li

Direct CO2 mineralization of carbide slag offers considerable potential for sustainable waste valorization, CO2 utilization, and high-value CaCO3 production, although associated Si-, Fe-, and Al-bearing impurities limit product quality. This study comparatively evaluated six process routes to determine how process sequence and separation-stream selection affect impurity partitioning and final product performance. The results suggest that calcination-induced phase reconstruction may improve the separability of impurity-bearing material, while hydrocyclone classification preferentially partitions impurity-rich particles toward the underflow. Relative to the calcined feed, the Si and Fe concentrations in the overflow decreased by 58.4% and 86.9%, respectively, and subsequent magnetic separation further reduced residual Fe. The preferred calcination–hydrocyclone overflow–magnetic separation–mineralization route omitted flotation and produced CaCO3 with a purity of 98.3%, a whiteness approaching 100%, and a total impurity content of 0.57%. These findings provide a process-sequence framework for balancing impurity removal, product quality, resource recovery, and environmental performance during the sustainable conversion of carbide slag into high-value CaCO3.

Sustainability doi: 10.3390/su18168057

Authors: Jang-Suk Lee Aiyun Yu

Environmental degradation is no longer a distant threat; it now permeates social media feeds, casual conversations, and daily digital content. However, whether incidental exposure to environmental news leads to meaningful behavioral change remains poorly understood. This study examines how incidental environmental news exposure (IENE) relates to pro-environmental behavior (PEB) among Chinese social media users, with particular attention to the sequential chain-mediating roles of environmental belief (EB) and perceived environmental risk (PER). A theoretical model was developed and tested using survey data from 468 respondents collected in November and December 2024, and analyzed using structural equation modeling (SEM). The results indicate that IENE is significantly and positively associated with EB, PER, and PEB. Notably, EB was not directly associated with PEB; its association operated almost entirely through PER, which accounted for 87.6% of the total EB–PEB association. PER emerged as the principal psychological pathway linking passive news exposure to behavioral engagement, and the structural model explained 42.1% of the variance in PEB. Because the design is cross-sectional, the results establish covariance patterns consistent with the proposed sequence rather than temporal or causal order. These findings indicate that cognitive risk appraisal, rather than environmental belief alone, constitutes the proximal mediating mechanism within the modelled pathway to pro-environmental action. Policymakers and media practitioners should accordingly design communication strategies that extend beyond general awareness-raising to link environmental threats explicitly to perceived personal and societal risk.

Sustainability doi: 10.3390/su18168056

Authors: Shun-Yao Hou Tian-Yow Chern

Publicly funded rural-regeneration programs often deliver facilities, yet post-completion continuity depends on whether the outputs remain usable, active, and maintainable. This study examines Hsinchu City, Taiwan, through a five-year documentary trajectory (2020–2024) comprising five annual reports, one citywide achievement booklet, and four case evidence bundles. It asks how project delivery may support—or fail to support—everyday landscape stewardship. Using an abductive documentary case-study design and maximum-variation comparison of Haishan, Gangbei, Qiedong, and Xiangcun, the analysis develops conditional landscape stewardship around three interdependent conditions: material–spatial usability, functional continuity, and social-organizational maintenance. It identifies four indicative interruption modes: completed but underused space, event-dependent activation, responsibility and resource gaps, and livelihood value disconnected from shared maintenance. The weakest-link heuristic treats a pronounced weakness as a review trigger rather than proof of project failure. The study contributes a document-supported diagnostic framework and a proposed ex ante/ex post governance checklist. It identifies governance conditions and vulnerabilities; it does not directly measure long-term use, environmental performance, or sustainability outcomes.

Sustainability doi: 10.3390/su18168055

Authors: Amina Chandad Mohamed Amine Benchekroun Mostafa Abakouy

The Industry 5.0 paradigm reframes sustainable operations management around human-centric, resilient and responsible production, yet the conditions under which digital and AI-enabled manufacturing translate into genuine worker well-being—particularly for women—remain under-investigated. This study analyses the determinants of women’s well-being at work in the Moroccan automotive industry, a sector that has become the country’s largest industrial exporter and a strategic laboratory for Industry 4.0-to-5.0 transitions. A systematic review was first conducted in Scopus (2015–2025) following PRISMA 2020 guidelines, yielding 54 eligible studies, of which 18 explicitly addressed automotive or Industry 4.0–5.0 contexts. Building on Job Demands–Resources theory and the human-centric tenets of Industry 5.0, a conceptual model articulated five antecedents—perceived supervisor support, job autonomy, work–life balance, technology-inclusive AI environment, and organisational justice—and a moderator, Industry 5.0 maturity. The model was tested via PLS-SEM (SmartPLS 4) on survey data from 412 women working in supplier and OEM plants across Tangier, Kénitra and Casablanca. Measurement quality was satisfactory (Cronbach’s α: 0.92–0.94; CR: 0.94–0.96; AVE: 0.81–0.85; HTMT < 0.63). All five antecedents significantly predicted well-being (β = 0.09–0.29; p ≤ 0.01), explaining 62% of its variance (Q2 = 0.571). Industry 5.0 maturity amplified the effect of a technology-inclusive AI environment on well-being (β interaction = 0.120; p < 0.001). The findings support a contingent, human-centric view of smart manufacturing and provide actionable levers for sustainable, gender-inclusive operations management.

Sustainability doi: 10.3390/su18168052

Authors: Stavroula Klempetsani Clea Pavlakou Nafsika Angeliki Zafeiri Foteini Mentzou Jelica Novakovic Simos Malamis Katherine-Joanne Haralambous

Food waste (FW) valorization through resource recovery is central to circular economy strategies that reduce environmental burden while generating sustainable, bio-based chemicals. This work investigated the effect of anaerobic sludge inoculum and the process control parameters of temperature (35 °C and 55 °C), pH value (4–10), and total solids content (2.5%, 5%, 7.5% and 10%) on the recovery of volatile fatty acids (VFAs)—chemicals used in bioplastics and bioenergy production—during acidogenic fermentation of food waste in batch reactors. While FW is well studied for biogas production, its potential for VFA recovery, a strategy that adds economic value to waste streams and supports the circular bioeconomy, remains comparatively underexplored. Mesophilic conditions favored fermentation over thermophilic conditions, and pH was the most influential factor affecting VFA accumulation, although temperature, inoculum presence, and total solids content also had statistically significant, large effects. Basic pH values provided maximum VFA yields from 2% to 25%, roughly double the acidic pH yields, while the highest solids content (10%) minimized VFA production at both temperatures. The highest yield (25%) occurred at T = 35 °C, pH 9, and TS = 5%, without sludge, while the highest yield under thermophilic conditions (T = 55 °C) reached 22.4% at TS = 2.5% and pH 9. By systematically evaluating these parameters together, this study offers a more comprehensive understanding of FW acidogenic fermentation than prior single-parameter works, guiding bioprocess design for sustainable waste management and resource efficiency.

Sustainability doi: 10.3390/su18168054

Authors: Iasmina Iosim Cornelia Diana Marin Dana Rad Gavril Rad

The dominant discourse on tourism resilience has traditionally emphasized physical infrastructure, environmental management, and technological solutions as key mechanisms for adapting destinations to climate change and socio-economic disruptions. While these dimensions remain essential, growing evidence suggests that the long-term sustainability of tourism destinations, particularly in remote and vulnerable regions, depends equally on less visible but equally essential community capacities. This paper introduces the concept of human infrastructure as a complementary perspective for understanding resilience in tourism development. Human infrastructure encompasses social relationships, local leadership, collective efficacy, cultural identity, community participation, intergenerational knowledge transfer, and educational capacity, which enable communities to adapt, recover, and innovate under conditions of uncertainty. Drawing upon an integrative conceptual review of the literature on tourism studies, community psychology, rural development, resilience theory, and sustainable development, this conceptual paper proposes a human-centered framework explaining how communities themselves function as adaptive infrastructures. The article argues that resilient tourism destinations emerge not only from investments in roads, visitor centers, and digital technologies, but also from investments in social cohesion, local knowledge systems, community empowerment, and cultural continuity. The paper concludes by discussing policy implications for sustainable tourism planning and proposing future research directions for operationalizing and measuring human infrastructure in tourism contexts.

Sustainability doi: 10.3390/su18168049

Authors: Anastasiia Fugaeva Elena Vialkova

A modern approach to the organization of wastewater disposal systems ensures the sustainable development of resort areas. Warm mineral springs (WMSs) located in suburban areas are not only recreational facilities for the population, but also sources of used mineral and communal wastewater. Preventing or reducing the discharge of pollutants in this type of liquid waste can reduce the anthropogenic impact on the environment. The article proposes a method for the chemical precipitation of ammonium ions in a mixture of mineral and domestic wastewater, and the production of struvite, a complex agricultural fertilizer. Three series of experiments were conducted: (1) on a model solution of ammonium ions; (2) on a mixture of a model solution and real mineral water; and (3) on real wastewater and spent mineral water taken from a thermal resort. As a result of an experiment with water samples at an initial concentration of no more than 85 mg/L, optimal doses of reagents were identified: 5.67 g/L of sodium hydrophosphate and 3.21 g/L of magnesium chloride to achieve a residual concentration of ammonium ions in purified water of no more than 1.5 mg/L at pH = 9–10. In the case of mixing of domestic wastewater and used mineral water, it was possible to reduce the use of magnesium chloride by 80%. At the same time it was possible to obtain the amount of sediment containing struvite, which is a valuable agricultural fertilizer. With the introduction of this technology, it is possible to reduce the expenses of reagents and reduce the damage caused by the discharge of liquid waste from a thermal resort, while the profit earned through the sale of fertilizer can partially offset the cost of wastewater disposal.

Sustainability doi: 10.3390/su18168051

Authors: Erhan Oruç Muhammet Rıdvan Ince Yavuz Kılınç Ali Rıza Solmaz Özgür Bayram Soylu

Over the past seven decades, rapid economic growth has been accompanied by a substantial increase in environmental degradation worldwide. Given the magnitude and transboundary nature of environmental externalities, country-specific policies may be insufficient, and regionally coordinated environmental strategies are likely to be more effective. For such frameworks to succeed, convergence in levels of environmental pressure among member countries is essential. In this study, convergence is examined using the ecological footprint (EFP), a comprehensive indicator of environmental pressure. The analysis covers the six member states of the Gulf Cooperation Council (GCC)—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates—over 1971–2024 and tests for the stochastic convergence of per-capita footprints relative to the year-t regional average. Conventional ADF tests indicate convergence for Kuwait and Qatar—with Saudi Arabia at the 10% level—and Phillips–Perron results point in the same direction. Quantile ADF and Fourier quantile KSS tests with bootstrap inference show that adjustment is regime-dependent and country-specific: mean reversion is confined to below-average states in Bahrain, to above-average states in Kuwait and Saudi Arabia, and to both extremes in Qatar, while the United Arab Emirates and Oman revert to almost no quantile. The Phillips–Sul log-t procedure does not reject full-panel convergence: all six countries form a single convergence club, the result survives leave-one-country-out and cross-sectional-dependence checks, and subsample estimates date the convergence process mainly to the post-1990 period. Component-level analysis shows that aggregate convergence is carried by the carbon component (84–99% of the GCC footprint), whereas cropland, grazing, forest, and built-up components diverge. The findings support regionally coordinated energy–carbon policy combined with nationally tailored land-use policy.

Sustainability doi: 10.3390/su18168053

Authors: Jiacheng Liu

The integration of green finance and digital technology exhibits considerable methodological diversity; however, existing scholarship lacks a systematic account of how empirical evidence is generated in this field. This scoping (PRISMA-ScR) review develops a literature classification framework centered on methodological approaches and applies it to 423 English-language articles on the green finance–digital technology nexus from the Web of Science Core Collection (2018 to April 2026). Research practices are organized along a two-dimensional framework spanning the epistemological objectives (explanatory vs. predictive) and the technical toolkit (traditional econometrics vs. machine learning), with causal machine learning integrating both paradigms. Each study is assigned a primary methodological label via a lexicon-based multi-label classification engine employing a 2 × 2 weight matrix. Weight sensitivity analysis confirms that classification outcomes are robust to parameter perturbation. Inter-coder reliability was near-perfect (Cohen’s κ = 0.93); algorithm–gold standard agreement was substantial (κ = 0.76, F1 = 0.79). The classification reveals that traditional econometrics remains the most prevalent method (26.95%), followed by predictive machine learning (17.26%) and technology application (16.31%), while causal machine learning (9.69%) remains underutilized and behavioral research is virtually absent (0.95%). Over a quarter of studies (26.24%) employ multiple methodologies. These findings provide a methodological map for researchers and policymakers navigating the green finance–digital technology landscape.

Sustainability doi: 10.3390/su18168050

Authors: Jung-Sup Bae Kyoung-Min Ko Hye-Jin Park

Artificial intelligence (AI) literacy has emerged as a foundational competency for sustainable higher education aligned with Sustainable Development Goal 4 (Quality Education). Although AI literacy coursework is expanding rapidly, classroom instruction alone is insufficient for cultivating the applied, ethical, and reflective dimensions of AI competency, and systematic research on the components of curriculum-linked AI/data extracurricular programs remains scarce. This study employed a sequential mixed-methods design integrating the Delphi technique and the Analytic Hierarchy Process (AHP) to identify and prioritize the key components of such programs. Ten experts spanning AI education, curriculum development, extracurricular administration, and industry participated in two Delphi rounds, followed by AHP pairwise comparisons and content validity ratio (CVR). The Delphi rounds yielded a consensus framework of 24 components across seven domains; six domains served as AHP Level 1 evaluation criteria and the seventh (program type) as Level 2 alternatives. AI practice integration and curricular linkage jointly accounted for 57.2% of the criterion weight, and three program types—AI tool workshops, AI-based problem-solving challenges, and data analytics projects—exhibited distinct strategic priorities. The final framework achieved a content validity index of 0.84, providing an empirically validated design framework for sustainable AI literacy education, with potential applicability to resource-constrained settings.

Sustainability doi: 10.3390/su18168045

Authors: Jae-Young Huh Han-Seon Park

Green ODA supports renewable energy and low-carbon structural transformation. Limited studies have explicitly evaluated whether Green ODA reduces emissions or examined the structural conditions that enable climate-oriented aid to produce meaningful decarbonisation outcomes. In this study, we examined the relationship between Green ODA and carbon dioxide emissions and investigated whether this relationship differs across the stages of renewable energy transition. Using annual panel data for 63 developing countries selected from the OECD Development Assistance Committee (DAC) List of ODA Recipients, including low-income, lower-middle-income, and eligible upper-middle-income economies, between 2010 and 2021, a dynamic panel threshold regression model was employed, with renewable energy consumption as the threshold variable. Renewable energy consumption was significantly associated with lower carbon emissions. However, the effects of Green ODA varied depending on the level of renewable energy development. The estimated threshold value for renewable energy consumption was 78.2%. When renewable energy consumption remained below this threshold, Green ODA was associated with increased carbon emissions. Following threshold exceedance, the effect became negative, although it remained statistically insignificant. These findings suggest that the relationship between Green ODA and carbon emissions differs across the stages of renewable energy transition in recipient countries.

Sustainability doi: 10.3390/su18168048

Authors: Sorin Mihăilescu Daniela Tinca Andrei-Alexandru Boroiu

Mobility is an essential condition for ensuring the functionality of urban areas. This study analyses the transportation preferences of the inhabitants of Petroșani, a small city integrated into a conurbation with former mining functions (the Petroșani Basin). Data were collected based on household surveys and interviews regarding mobility behaviour. To evaluate travel patterns, the study applies three statistical methods: descriptive analysis, the χ2 (Chi-square) test and Multiple Correspondence Analysis (MCA). The results indicate significant variations according to gender and the demographic segments analysed (children, adolescents, students, active population, retirees). The MCA model explains 39.3% of the total inertia (Dim1 = 20.9%, Dim2 = 18.4%). The results indicate that the active population occupies a central position, characterized by a diversified mix of transport modes, while other segments present polarized modal behaviours. At a general level, the analysis highlights a clear prevalence of personal car use and pedestrian travel in Petroșani, underlining the need for local mobility policies adapted to the characteristics of the conurbation.

Sustainability doi: 10.3390/su18168047

Authors: Daisy Odunze Helena McMahon

The transition to a circular bioeconomy is increasingly recognised as a critical pathway for achieving climate neutrality and resource use efficiency in Ireland. However, this transition is highly dependent on the availability of a skilled workforce capable of operating across interconnected bio-based sectors. Ireland’s National Bioeconomy Action Plan recognises the critical role that skills and knowledge will play in this transition. This study develops a comprehensive taxonomy of skills required to support the transition to a circular bioeconomy, with a specific focus on key Irish primary bioeconomy sectors (agriculture, forestry, fishery and aquaculture) and traditional industries (food processing, wood, textiles, and construction). A qualitative systematic literature review was conducted following the PRISMA 2020 guidelines. Peer-reviewed articles were retrieved from the Web of Science and Scopus databases and complemented with relevant Irish and European grey literature. A total of 96 publications were analysed using thematic analysis to identify and synthesise sector-specific and cross-sectoral competencies. The taxonomy organises circular bioeconomy skills into five overarching competence domains (systems-thinking, sustainability, circularity and bioeconomy/biotechnology, and digital skills). Findings reveal that while each sector has unique skills, a set of shared skills is consistently critical across all sectors. The identified competencies were subsequently organised into a structured taxonomy and mapped to Ireland’s National Framework of Qualifications (NFQ), establishing progressive proficiency levels from awareness (NFQ 5–6) through practitioner (NFQ 7–8) to expert (NFQ 9–10). This competency progression framework represents the principal contribution of the study, translating the taxonomy into a practical tool for curriculum development, workforce planning, professional development, and policy implementation.

Sustainability doi: 10.3390/su18168046

Authors: Huabing Zhu Yajing Bu Ping Li Yangjie Huang

The rapid development of artificial intelligence has intensified the need for higher education institutions to cultivate students’ capacity to engage with complex and changing innovation problems. Existing research has largely examined the net effects of individual educational resources, leaving less understood how heterogeneous institutional and student resources combine across universities. Drawing on Resource Orchestration Theory, this study examines configurations associated with students’ perceived and self-reported innovation capacity. Survey responses from 14,034 students were aggregated to 126 Chinese universities after tests of aggregation reliability, and the university-level data were analyzed using fuzzy-set qualitative comparative analysis (fsQCA). No single antecedent met the conventional necessity threshold. The analysis identified five configurations associated with high self-reported innovation capacity and three configurations associated with low self-reported innovation capacity, which were summarized into three overarching high-outcome patterns. Additional checks varying consistency, frequency, and calibration choices indicated substantial, although not complete, configurational stability. The study extends resource-orchestration reasoning to higher education while emphasizing that the findings represent cross-sectional set-theoretic associations rather than longitudinal or experimental causal effects.

Sustainability doi: 10.3390/su18168043

Authors: Admore Samuel Chiumia Betchani H. M. Tchereni Hope Baxter Chamdimba

Clean cooking transitions in Sub-Saharan Africa remain limited despite increasing access to modern energy, highlighting the need to extend traditional demand-side approaches by incorporating risk and uncertainty into household decision-making. This study examines household energy choices under uncertainty in urban and peri-urban Malawi and reconceptualizes fuel diversification, or energy stacking, as a rational risk management strategy. Using cross-sectional data from 3015 households collected in 2026, the study uses binary logistic regression models to estimate the determinants of fuel diversification. The results show that exposure to uncertainty significantly increases the likelihood of energy stacking. Electricity unreliability (p < 0.01), charcoal price variability (p < 0.05), income volatility, and past fuel shortages are all positively associated with diversification behavior. In contrast, stable and higher incomes reduce reliance on multiple fuels. Household size significantly increases the number of fuels used (p < 0.01), reflecting higher energy demand and risk exposure. The findings demonstrate that energy stacking is a deliberate risk mitigation strategy consistent with risk diversification theory and highlight that improving reliability, stabilizing prices, and reducing market uncertainty are critical for accelerating clean cooking transitions.

Sustainability doi: 10.3390/su18168044

Authors: Jing Chen Kedi Wang Siquan Yang Hongyong Yuan Hongquan Sun Guofeng Su Zhonggen Wang Tao Chen Xuecai Xie Xingli Peng

China is one of the countries most severely affected by natural disasters, which are characterized by diverse types, wide distribution, and high frequency. As the cornerstone and first line of defense of the emergency management system, grassroots emergency management plays a decisive role in determining disaster evolution and loss outcomes. However, current grassroots emergency management still faces challenges such as insufficient functional integration, difficulties in institutional operation, and inadequate collaborative governance. Drawing on nationwide statistical data, policy document analysis, and an in-depth county-level case study of District W, we conduct a process-based analysis of grassroots emergency management system reform. The case analysis systematically examines the reform’s background, implementation practices, and post-reform constraints, with particular attention to functional integration, institutional materialization, and coordination mechanisms. On this basis, a problem-oriented reform framework is proposed from the perspective of collaborative governance, based on empirical diagnosis and theoretical synthesis. The proposed framework focuses on integrating grassroots emergency management functions, advancing the substantive operation of grassroots emergency management institutions, and establishing a multi-stakeholder collaborative governance mechanism. The study suggests that collaborative governance provides a practical and effective framework for addressing structural constraints in grassroots emergency management and for enhancing its overall effectiveness and sustainability.

Sustainability doi: 10.3390/su18168042

Authors: Abdullah S. Alnasser Saleh A. Aloraini Mahmoud Mahrous M. Abbas

Sustainable coastal environmental management relies on continuous assessment of sediment quality. In the Saudi Arabian Red Sea, such sediments function as both sinks and potential secondary sources of heavy metals (HMs) originating from natural processes and anthropogenic activities. The present study investigated the concentrations of HMs in surface sediments from Jeddah and Rabigh. Contamination levels, as well as possible natural and anthropogenic inputs and potential risks to human health through ingestion, dermal contact, and inhalation pathways, were evaluated. The results indicated that Fe is the most abundant metal at both sites (1570.40 mg/kg at Jeddah and 1804.11 mg/kg at Rabigh). Cu, Ni, and Zn are present in the sediments at concentrations ranging between 3.12 and 4.49 mg/kg, while Cd and Pb remain below the detection limits in all samples. Generally, the contamination index values indicated low levels in both regions. The evaluation of human health risks identified ingestion as the primary exposure pathway. Non-carcinogenic risk levels were within safe limits for both adults and children. However, the carcinogenic risk assessment of nickel (Ni) indicated that all values fall within the acceptable range (10−6–10−4), although children consistently showed higher risks than adults. Despite the overall low levels of pollution, the moderate enrichment of Cu, Ni, and Zn in Jeddah and Cu in Rabigh, along with the higher non-carcinogenic risks to children at the Rabigh site, highlights the need for continuous environmental monitoring and further investigation to support the sustainable management of coastal ecosystems.

Sustainability doi: 10.3390/su18168040

Authors: Liang Liu Sen Yang Xin Lv Na Wu

This study explored the utilization of coal gangue with high iron content to synthesize poly-ferric-alum-sulfate (PAFS) and coal gangue leaching residue-PAFS (CG@PAFS) coagulants, which were subsequently applied to treat landfill leachate and its concentrate. The results demonstrated that the PAFS coagulant exhibited notable removal efficiency for key pollutants, including chemical oxygen demand (COD) and total phosphorus (TP), with removal rates of 23.8% and 77.5%, respectively. Its performance was comparable to polyferric sulfate (PFS) and superior to aluminum polysulfate (PAS). Mechanistic investigations revealed that Fe3+ in the PAFS coagulant reacted chemically with phosphate ions, forming insoluble precipitates and facilitating phosphate removal through flocculation. Furthermore, PAFS also exhibited moderate removal efficiency for COD and ammonia nitrogen (NH3-N) via flocculation processes. From a sustainability perspective, this study advances a circular economy model by simultaneously addressing two pressing environmental challenges: the valorization of coal gangue (a massive industrial solid waste) and the treatment of landfill leachate (a hazardous wastewater). Importantly, the post-treatment sludge, rich in available phosphorus and silicon, demonstrates promising potential for beneficial reuse as a soil conditioner, thereby closing the material loop and reducing reliance on virgin chemical resources. This integrated waste-to-resource approach aligns with multiple Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), and SDG 12 (Responsible Consumption and Production). Overall, this study provides valuable insights into the resource-efficient utilization of coal gangue and presents an effective, low-carbon, and sustainable approach for landfill leachate management.

Sustainability doi: 10.3390/su18168039

Authors: Juan Carlos Vesga Ferreira Alexander Florez Martinez Brayan Elias Vargas Niño

The inefficient management of agro-industrial residues, particularly cocoa pod husk and mucilage, represents a critical environmental and economic challenge in Santander and Norte de Santander, Colombia, where over 55,000 tons of biomass waste are generated annually from a regional production exceeding 23,500 tons of cocoa beans. Furthermore, these residues, which constitute approximately 70% to 75% of the fruit’s total weight, are currently underutilized, generating severe localized pollution through uncontrolled decomposition and causing substantial economic losses by wasting compounds with high valorization potential. This article proposes the design and systematic experimental calibration and internal cross-validation of an empirical model based on artificial intelligence capable of predicting quantities of valuable compounds, including bioethanol, essential oils, paraffins, antioxidants, and pectins, obtained from cocoa residues. The model integrates critical variables such as cocoa variety, extraction methods, and process conditions, incorporating advanced machine learning techniques trained on a 100% empirical database of eighty-four (84) laboratory trials, combined with a post-inference sensitivity analysis via the Monte Carlo method with 10,000 simulations. Preliminary results demonstrate significant varietal differences; for instance, the CCN-51 variety achieves a mean bioethanol yield of 79.30 ± 4.96 mL/kg with a 95% confidence interval of (69.44–88.93) mL/kg, while the Criollo variety reaches 43.55 ± 2.72 mL/kg (38.14–48.84 mL/kg), exhibiting highly synchronized coefficients of variation of 6.255% and 6.246%, respectively. Furthermore, the integration of a cascading extraction sequence combined with neural networks may potentially contribute to maximizing by-product yields, with theoretical mass balance estimations suggesting a possible reduction of up to 40% in final residue generation compared to conventional isolated extraction pathways, as detailed in the proposed framework. This tool could potentially support the circular economy and alignment with Sustainable Development Goals 7, 9, and 12, while offering a possible pathway to contribute to the competitiveness of the Colombian cocoa industry through data-driven decision-making and sustainable technology adoption.

Sustainability doi: 10.3390/su18168041

Authors: Eduardo Bastida-Escamilla Carlos Peña Humberto Genaro Cisneros-Salinas Dan Trowsdale

This study examined changes in students’ self-perceived Sustainability Action Competence (SAC) and Collaboration Competence (CC) associated with participation in the Tequila Game, a multiplayer serious game in which students assume the role of competing retailers and make operational, sustainability, and voluntary collaboration decisions in a shared market. A quasi-experimental pretest–posttest control-group design was conducted with 188 undergraduate engineering students across eight course sections. Students in the treatment group participated in the Tequila Game, whereas the control group completed alternative active-learning activities. Compared with the control group, participants in the Tequila Game achieved significantly larger gains in overall SAC and CC (both p < 0.001). Among the component dimensions, the largest improvements were observed for Learning (t = 7.31, p < 0.001, dz = 0.79), Willingness to Act (t = 7.01, p < 0.001, dz = 0.76), and Confidence in One’s Own Influence (t = 5.77, p < 0.001, dz = 0.63). Gameplay analyses complemented the survey findings by showing that collaboration was conditional rather than automatic: inventory sharing increased primarily when retailers held substantial surpluses, transportation sharing consistently improved vehicle utilization, and collaboration occasionally failed despite broad support and the absence of clear operational incentives for defection. These findings demonstrate that serious games can strengthen sustainability- and collaboration-related competencies while exposing students to the operational and behavioral complexities of collaborative decision making.

Sustainability doi: 10.3390/su18168036

Authors: Jun Ren Omolomo Odunayo Tobora

The transportation sector faces growing supply chain disruptions driven by workforce shortages, digital skills gaps, and weak cultural readiness for risk. Human Resource Management (HRM) offers a credible path toward stronger supply chain resilience (SCR), yet existing decision support tools lack the formal reasoning and auditability that systematic HR risk assessment requires. This paper proposes a Task-Typed Reasoning Module-Enhanced Retrieval-Augmented Generation (RAG) Expert System framework for HR-driven risk assessment in transportation supply chains. The framework employs a six-layer architecture integrating four core components: a Task-Aware RAG layer for knowledge extraction from heterogeneous HR documents, a Task-Routed Evidence Extractor for risk factor identification and source reliability scoring, a Task-Based Reasoning Core applying weighted Mamdani fuzzy inference, and a Task-Guided Synthesis Module using Dempster–Shafer evidential reasoning for risk profiling. Task-Typed Reasoning Modules (TTRMs) organise reasoning into reusable, adaptable units covering Likelihood, Impact, Vulnerability, Mitigation, and Prioritisation, refined through an expert-gated feedback loop. Applied to an illustrative UK transportation logistics case study, the framework ranked HR-driven workforce risks, quantified uncertainty through belief-plausibility intervals, and generated traceable recommendations linked to four HRM-SCR dimensions. As a proof-of-concept demonstration, the framework provides a conceptual foundation for HR risk management in transportation, extending expert system reasoning through adaptive AI to offer mathematically grounded, traceable outputs for practitioners and researchers; empirical validation in live organisational settings remains a necessary next step. By formalising the human dimension of resilience, the framework contributes toward socially, economically, and environmentally sustainable transportation supply chains, aligning HR risk management with the sustainable development objectives examined in this study.

Sustainability doi: 10.3390/su18168037

Authors: Gulnihal Sakrak Ekin Yakin Ekin Onur Akbulut Tunahan Celik

This study examines carrying capacity in parks and protected recreation areas as a measurement, monitoring, and adaptation component of sustainable visitor use management. For a concept-focused critical narrative review, Scopus and the Web of Science Core Collection were searched, and 2493 records were identified. After removing 819 duplicates, 1674 unique records were screened. Overall, 370 records were evaluated as topically eligible. A 78-source critical-synthesis core, comprising central database records, foundational books, and institutional documents identified through citation chaining, was evaluated against seven common criteria. The findings demonstrate that carrying capacity is not a single, context-independent visitor count. Rather, it is an adaptive process requiring the definition of desired ecological and experiential conditions, the monitoring of indicators and standards, and management intervention when thresholds are exceeded. The study’s contribution lies in comparing ROS, LAC, VAMP, CCAP, VIM, VERP, and IVUMF using common criteria, explaining the interdependence of physical, ecological, social, managerial, and economic dimensions, and jointly evaluating geographic transferability and digital data governance. In conclusion, sustainable management depends more on the organizational implementation of an indicator–standard–monitoring–action chain than on a numerical limit.

Sustainability doi: 10.3390/su18168038

Authors: Tomasz Codogni Filip Nawrot Michał Presz Mateusz Cieślik Grzegorz Zych Krzysztof Zamasz

This article asks a practical question: do current renewable-energy rules encourage end users to become prosumers, or do they mainly serve those already prepared to invest? This analysis maps recent Polish reforms, especially the shift from net metering to value-based net billing and later adjustments to settlements: the return to monthly average pricing for many early adopters, an optional hourly price model, and a strengthened prosumer deposit intended to reduce the sell–buy gap. It also examines the expanding catalogue of prosumer statuses, from the individual prosumer, through collective prosumption in multi-unit buildings, to the virtual prosumer, which may include people without a suitable roof or land. The article then considers civic forms of organisation—energy cooperatives, energy clusters and citizen energy communities—and the role of municipalities as conveners and intermediaries. It argues that regulatory responsiveness, even when market-oriented and technologically aware, is not enough. Uptake depends on whether the rules fit real constraints: finance, administrative effort, grid capacity and fair allocation of risk.

Sustainability doi: 10.3390/su18168034

Authors: Daisuke Nagatomo Ching-Yu Yao Ming-Ni Chan

This study examines how Generative AI (GenAI) was integrated into creative sustainability education through the STEM Education for Sustainability (STEM4S) framework. Conducted in 2024, the study examined a nine-week intervention comprising a breastfeeding-room track in a second-year interior-design course and a sports-gym track in a third-year commercial-space-design course. Twenty students completed the pre-assignment questionnaire, and 18 completed matched pre- and post-assignment questionnaires after two withdrawals. GenAI was introduced as a scaffolded method-bank tool to support prompt-based ideation, visualization, and critique. A qualitative-dominant mixed-methods case-study design combined matched pre- and post-assignment questionnaires, student reflections, classroom observations, project outcomes, and professional critique records. Paired comparisons showed that students’ self-rated SDG 11 knowledge increased from 2.94 ± 1.16 to 3.56 ± 0.92 (p = 0.012, Cohen’s dz = 0.67), while SDG 5 knowledge decreased from 4.39 ± 0.70 to 3.72 ± 1.02 (p = 0.014, Cohen’s dz = −0.65); both findings are interpreted as exploratory due to the small sample. Qualitative findings indicate that GenAI supported visual exploration but also produced prompt difficulty, visual repetition, and spatial inconsistency. The findings suggest that GenAI can extend the STEM4S method bank when embedded within civic learning, critique, and human design judgment, while its transferability requires further testing across contexts.

Sustainability doi: 10.3390/su18168033

Authors: Rawin Thinnakorn Boontaree Chanklap Onanong Cheablam Suleman Dauda

Agrarian cultural landscapes depend not only on the symbolic value of place but also on the viability of the producers who sustain landscape-bearing practices. This study asks which indigenous rice value-chain pathway is most supportable in the near term under current production, post-harvest, market, and coordination conditions, and what this implies for conservation planning. Using the Pak Phanang Basin, Thailand, as an area-based case, the study integrates evidence from 52 indigenous rice-farming households in four subdistricts, farmer meetings and focus group discussions, value-chain actors, relevant agencies, spatial and documentary sources, and a consumer survey used as supplementary demand-side evidence. Seven value-chain pathways were compared qualitatively using six criteria: downstream demand or final use, quality requirements, post-harvest burden, investment needs, coordination burden, and producer readiness. The findings show that farmer participation remains concentrated in low-risk channels, especially household consumption and mill sales. Paddy rice for game fowl and native chicken feed emerged as the most territorially supportable near-term pathway because it showed the strongest practical fit among identifiable downstream buyers and final-use clarity, moderate quality requirements, manageable post-harvest and investment burdens, coordination requirements, and producer readiness. Its feasibility, however, depends on reducing post-harvest bottlenecks, improving aggregation, managing quality, and coordinating with downstream buyers. The study concludes that feasible value-chain upgrading should be planned as conservation-enabling support for custodian viability, rather than as a simple shift toward higher-value markets.

Sustainability doi: 10.3390/su18168031

Authors: Derk Jan Stobbelaar Else Vermeulen Dana Kamphorst

When it comes to encouraging nature-inclusive behaviour, a ‘one-size-fits-all’ approach is still often used in practice. The literature suggests that approaches which take account of the differences between people are much more effective. However, research into how this should be tackled is still insufficient. This study aims to identify promising governance approaches that can effectively support behavioural change towards nature-inclusive behaviour. We conducted eight case studies across the Netherlands, applying an action-research approach to explore how citizens’ behaviour can be influenced in practice. Behavioural change was analysed using an adapted I-change model, while governance approaches were examined through the Policy Arrangement Approach. The findings from the case studies informed the design and implementation of targeted interventions. The results demonstrated that citizens differ substantially in their intentions to adopt nature-inclusive behaviour and therefore require approaches tailored to their specific needs and behavioural states. Importantly, the study also showed that all groups—including those who had initially not considered changing their behaviour—can potentially be encouraged to do so. Key triggers for behavioural change include ability factors, supporting factors, social-cultural influences, and information factors. We recommend that governmental organisations initially collaborate with receptive groups that are already active in nature-inclusive practices. Through this cooperation, governments can subsequently engage citizens in the preparation state by removing barriers to participation. Finally, people in the contemplation and pre-contemplation states can be reached by linking greening initiatives to liveability and by offering accessible social activities.

Sustainability doi: 10.3390/su18168032

Authors: Anna Cedro Ryszard K. Borówka Wojciech Drzewicki Bernard Cedro Katarzyna Piotrowicz Łukasz Pogoński Weronika Ceglarek Paweł Osóch Krzysztof Stefaniak Bronisław Wojtuń Anna Hrynowiecka Monika Niska Mateusz Meserszmit Renata Stachowicz-Rybka Mariusz Jędrysek Jarosław Sikorski Adam Michczyński Danuta Michczyńska

Norway spruce (Picea abies L.) growing in mountain forests is a sensitive indicator of environmental change, but its growth response may be strongly modified by local site conditions, which is important for sustainable forest management under climate change. This study examined two spruce populations in the upper montane zone of the Śnieżnik Massif, Eastern Sudetes, southwestern Poland: one growing on a raised bog (Sadzonki—TS) and the other on mineral soil (Owczarnia—OW). Tree-ring width (TRW) chronologies were developed from 59 sampled trees represented by increment cores and stem discs, covering 1781–2023 for TS and 1800–2023 for OW. Annual δ13C analysis was performed for a selected TS tree, and decadal wood geochemistry was analyzed for a selected disc. Spruces growing on the raised bog showed tree-ring widths that were less than half those of trees growing on mineral soil. TRW was mainly controlled by summer or spring–summer temperature, while precipitation had a stronger positive effect at the mineral-soil site. δ13C showed weak relationships with TRW but negative correlations with mean annual and summer temperature. Elevated concentrations of Na, K, Ca, Mg, Fe, Mn, Cu, Zn, and Pb occurred mainly in 1941–1950 and 1971–1980, indicating the influence of historical air pollution. The contrasting growth trends and health status of the two populations demonstrate that local habitat conditions strongly shape spruce responses to environmental change and should be considered in sustainable mountain forest conservation and adaptation strategies.

Sustainability doi: 10.3390/su18168030

Authors: Hubert Kryszk Krystyna Kurowska

Land-use conflicts in non-urbanized areas are fundamentally governance problems rather than purely environmental ones: sustainability outcomes increasingly depend on integrated, cross-sectoral decision-making reconciling forestry, agriculture, tourism, infrastructure, and urbanization within a finite land resource. This study examines whether statutory land acquisitions by a public forest administration can be understood as such a governance instrument rather than simply forest-area expansion, using an original transaction-level database of 911 land purchases by the Polish State Forests (Lasy Panstwowe) through statutory pre-emption rights between 2022 and mid-2026. The database covers 2806.1 hectares and, for the 903 transactions with a determinable price, approximately 114.2 million PLN. Using descriptive statistics, concentration indices (Gini, Herfindahl–Hirschman), an exploratory hedonic-style log–log regression of unit price on parcel area with location and year fixed effects, and a spatial-autocorrelation analysis (Moran’s I), the study examines spatial concentration, price differentiation, and parcel-size effects. Results show pronounced sub-regional concentration (county-level Gini = 0.615, more than double the voivodeship-level value of 0.284), a systematic price premium for parcels below 0.5 ha, and a dominant role of location over parcel size in explaining price variation (R-squared rising from 0.042 to 0.198 with location fixed effects); these are descriptive associations rather than causal estimates, given the absence of parcel-level quality covariates and a fully specified spatial–econometric model. The findings support interpreting statutory pre-emption purchases as a market-based institutional mechanism contributing to boundary rationalization, ownership consolidation, and mediation of competing land-use pressures, with implications for county-level monitoring and cross-sectoral coordination with spatial planning.