Sustainability doi: 10.3390/su182010521

Authors: Rongfei Li Hongzhen Lei

The ethical risks associated with generative large language models (GLLMs) raise concerns about their implications for corporate social responsibility (CSR). Drawing on firm-year observations for Chinese A-share companies over 2015–2024, we investigate how GLLM-related ethical risk relates to CSR performance. A firm-level disclosure-based measure of GLLM-related ethical risk signals is constructed from annual-report text and analyzed using two-way fixed-effect models. The results show a negative and statistically significant association, with higher ethical risk corresponding to lower subsequent CSR performance. This association persists across robustness checks and instrumental variable analyses. Firm-clustered bootstrap analyses reveal significant negative indirect associations through reputational pressure and financing constraints, supporting the proposed mediating pathways. Managerial compliance attention strengthens the negative association between ethical risk and CSR performance. These findings extend research on the antecedents of CSR by identifying the ethical risks of emerging technologies as a relevant organizational concern. They also highlight the importance of integrating ethical AI governance with CSR planning to support responsible technology adoption and sustained corporate sustainability commitments.

Sustainability doi: 10.3390/su182010520

Authors: Hankang Lu Yu Tian Cheng Qian Ruifang Yuan Maoyuan Liu

Reliable short-term water-supply forecasting supports sustainable urban water management by informing pump scheduling, water allocation, and operational planning. This study proposes a wavelet-guided STL–VMD–Informer framework for direct 1-, 3-, and 7-day forecasting while reducing look-ahead bias. Continuous wavelet transform analysis of the training subset identifies the dominant periodicity for STL, and VMD further decomposes the residual into band-limited modes. The training subset is initially decomposed, whereas validation and test features are updated sequentially using only observations available up to each forecast origin. The resulting components and calendar features are jointly modeled using a multivariate Informer. Using 581 daily SCADA observations from Degan Booster Pumping Station, the proposed model achieved an MAE of 4557m3d−1, an RMSE of 5891m3d−1, and an NSE of 0.803 for the 1-day horizon; NSE remained 0.631 and 0.524 for the 3- and 7-day horizons. External validation on public data from Liulin Water Treatment Plant yielded an MAE of 3540m3d−1 and an NSE of 0.857. The results demonstrate the potential of causality-aware multiscale forecasting for reliable and energy-conscious water-supply operation.

Sustainability doi: 10.3390/su182010519

Authors: Siwen Qian Liwei Liu

Coastal wetland protected areas face challenges from landscape change, bird conservation needs, and the tensions between conservation measures and local livelihoods. However, the spatial relationships between rare bird diversity and residents’ conservation-related perceptions remain poorly understood. This study adopted an integrated social-ecological framework combining landscape data from 2000 to 2023, rare bird distribution records, and resident survey data in the Yancheng Rare Birds National Nature Reserve, Jiangsu Province, China. Landscape pattern analysis quantified landscape change, spatial autocorrelation analysis assessed the associations between residents’ perceptions and rare bird diversity, and ordinal logistic regression examined factors associated with residents’ willingness to seek assistance from the reserve administration. The results showed a shift in landscape composition from 2000 to 2023: high-coverage grassland declined by 52.0%, while reservoirs and ponds expanded approximately fourfold. Mudflat area rebounded from its 2020 low to exceed its 2000 extent by 3.6% in 2023, and the CONNECT index increased overall from 4.10% to 5.88%. Rare birds (e.g., Grus japonensis and Ciconia boyciana) were recorded in the reserve’s core zone and adjacent areas. Residents expressed positive attitudes toward conservation, although their perceptions and willingness to seek administrative assistance varied with conservation-related livelihood impacts and direct ecological experience. Town-level mean scores for questionnaire items on residents’ perceptions of conservation-related conflicts and livelihood impacts showed a weak positive spatial association with bird diversity, with marked local heterogeneity. These patterns may reflect the spatial spillover of conservation benefits, mismatches between conservation costs and ecological benefits, and differences in residents’ direct perceptions of bird-related ecological value. The findings may inform conservation planning and community engagement in the Yancheng reserve by identifying local differences in residents’ perceptions and their spatial associations with rare bird diversity, with implications for sustainable wetland management that integrates biodiversity conservation and local livelihood needs.

Sustainability doi: 10.3390/su182010518

Authors: Wenxing Zhu Huan Wang Fangliang Wang

With the background of green development, the relationship between SCN and green innovation in manufacturing enterprises has received increasing attention. However, how the network position is related to GIP still needs further exploration. This study takes Chinese A-share listed manufacturing enterprises from 2015 to 2024 as samples, constructs the SCN based on supplier and customer relationships, examines the association between the enterprise’s network position and GIP, and tests the mediating role of market power and the moderating role of government subsidies. The study finds that both degree centrality and structural hole richness are significantly positively correlated with GIP, while the correlation with betweenness centrality does not reach the statistical significance level. Further analysis supports the partial mediating role of market power in the above relationship, and the positive correlation is more obvious under a higher level of government subsidies. Heterogeneity tests show that enterprises with stronger executive environmental awareness exhibit a more prominent positive association between network position and GIP, and the differences in group coefficients are statistically significant. This study supplements empirical evidence for understanding the connection between the network position of the supply chain and the green innovation of manufacturing enterprises and also provides references for enterprise supply chain relationship management and green innovation practices.

Sustainability doi: 10.3390/su182010516

Authors: Qihua Yin Qi Wang Songlin Zhang

This study examines whether digital finance (DF) and traditional finance (TF) are substitutes or complements in shaping urban population size, and whether service-sector employment serves as a significant mediating channel for DF and a potential channel for DF–TF complementarity. Although prior research has documented the macroeconomic effects of digital finance, three gaps remain: the role of digital finance in urban population size is largely unexplored; whether DF and TF are complements or substitutes in shaping urban population size remains untested; and the mediating role of service-sector employment requires further evidence. Using panel data from 281 Chinese prefecture-level cities for 2011–2022, we estimate a two-way fixed-effects model with city and year fixed effects, incorporating DF, TF, and their interaction term, with robust standard errors. To address endogeneity, we employ instrumental-variable estimation using historical communication infrastructure and geographic proximity. The dependent variable is the logarithm of urban population size. DF and TF are complements rather than substitutes in shaping urban population size. Service-sector employment is a significant mediating channel for DF and a potential channel for DF–TF complementarity. Heterogeneity analysis reveals that the complementary effect is concentrated in large cities and central/western regions. This study expands the finance–urban population nexus from a financial-system complementarity perspective and offers policy implications for coordinating digital and traditional finance to promote sustainable urban development.

Sustainability doi: 10.3390/su182010517

Authors: Yuanwei Sheng Suhaiza Zailani Al Nasrie Weli

Counterfeit goods create economic, security, and sustainability risks for supply chains, yet blockchain, radio-frequency identification (RFID), and artificial intelligence (AI) have mostly been studied as separate technologies. This study conceptualises their joint adoption as Logistics Anti-Counterfeiting Digital Technology (LACD) adoption, a converged capability combining identification, traceability, and analytical detection. Drawing on Rational Choice Theory and Deterrence Theory within a perspective informed by the Technology-Organisation-Environment framework, it examines the antecedents and outcomes of LACD adoption and the moderating role of government regulation. Survey data from 232 medium and large third-party logistics (3PL) firms in China were analysed with partial least squares structural equation modelling. Perceived benefit, deterrent severity, and deterrent certainty were positively associated with LACD adoption, whereas perceived complexity and cost were negatively associated with it; sanction celerity was not significantly associated with adoption. LACD adoption was positively associated with logistics security effectiveness and supply chain resilience. Government regulation strengthened the effects of perceived benefit, deterrent severity, and deterrent certainty and weakened the negative effect of perceived cost, but did not moderate the effects of perceived complexity or sanction celerity. The study also proposes, as an untested proposition, that LACD may provide traceability infrastructure for circular supply chain practices.

Sustainability doi: 10.3390/su182010515

Authors: Yifan Wang Siyang Xu Zheng Xu Lianmei Zhu

We examine whether lagged corporate sustainable growth (Pre-CSG) helps explain cross-firm differences in firm-specific risk responses as commodity futures market stress rises. Using Chinese commodity futures data, we construct a multidimensional Commodity Futures Market Stress Index (CFMSI) and relate it to Pre-CSG and firm-specific risk for Chinese A-share manufacturing firms. We find that firms with higher Pre-CSG exhibit weaker relative firm-specific risk responses as CFMSI rises, with the strongest evidence for downside idiosyncratic volatility. The economic magnitude is small: a one-standard-deviation increase in CFMSI combined with a one-standard-deviation difference in Pre-CSG corresponds to approximately a 0.056-percentage-point reduction in the annualized Downside IVOL differential, or about 0.25% of its sample mean. By contrast, Pre-CSG is not significantly associated with lower risk when CFMSI is around zero, the CFMSI reference-window mean, indicating a state-dependent rather than unconditional relation. The negative interaction is broadly preserved under alternative CFMSI constructions and additional predetermined firm controls, although statistical precision varies, and is further supported by alternative inference procedures and recursive future-stress timing tests. Complementary analyst evidence shows that the CFMSI × Pre-CSG Interaction Exposure is negatively associated with forecast disagreement in more restrictive specifications. In the baseline analyst-risk specification, greater disagreement is positively associated with firm-specific risk measured in the following calendar year; however, this association attenuates and loses statistical significance when disagreement is reconstructed using only forecasts issued before that risk window begins. Overall, our findings suggest that the relation between corporate sustainable growth and firm-specific risk varies with commodity futures market stress.

Sustainability doi: 10.3390/su182010514

Authors: Hui Zhang Huizi Zhang Jianmin Jia

The bus system is considered a green transportation mode to alleviate traffic congestion in big cities. Understanding travel mobility and network robustness contributes to the design, management and sustainability of the bus system. This paper proposes a framework to evaluate the spatiotemporal characteristics of bus ridership and network robustness based on real-world trip data. First, we analyze the spatiotemporal characteristics of passenger flow, including transfer times, equity, spatial autocorrelation and complex network features. Second, the k-means algorithm is adopted to cluster the passengers according to travel attributes in a week. Finally, a node failure process is introduced to evaluate the robustness of the bus network. The bus network of Beijing is taken as an example to test the model. The results show that the passenger flow is concentrated in the central area and approximately 85% of passengers have no intra-bus transfer during a day. Moreover, we find that the bus passengers can be divided into four groups. In addition, the bus network is mostly vulnerable when subjected to degree-based and betweenness-based attacks from the perspective of structures, while it is mostly vulnerable to strength-based attacks from the perspective of transfers.

Sustainability doi: 10.3390/su182010513

Authors: Shukang Zheng Changjiang Zheng Genhua Ma Hanpei Yang Ye Lu Lin Ge Yingjia Chen

Growing urban last-mile delivery demand and low-carbon transition pressures motivate the coordinated use of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). This study develops a two-echelon collaborative delivery model with intermediate transshipment, jointly considering customer allocation, UAV transshipment missions, and UGV routing. A weighted single-objective formulation integrates operational cost, monetized aggregate delivery time, and carbon-emission cost under capacity, UAV-range, and time-window constraints. A learning-enhanced adaptive large neighborhood search method, termed DQN–ALNS, is proposed. A standard deep Q-network with prioritized experience replay selects destroy–repair operator combinations according to the current search state, while ALNS executes these combinations to improve candidate solutions. Experiments cover nine Solomon-based instances with 25, 50, and 100 customers, with ten independent runs per method and instance. DQN–ALNS achieves lower mean objective values than standalone ALNS on six instances, including five of the six medium- and large-scale instances, indicating competitive but instance-dependent performance. Ablation results suggest potential benefits from prioritized experience replay in solution quality and run-to-run stability. A real-data-based scenario study around Nanjing South Railway Station examines different traffic periods. The off-peak scenario yields the lowest integrated objective value of RMB 3042.543 and the shortest delivery completion time of 1.6 h. The proposed framework supports offline route planning and scenario comparison, with DQN–ALNS positioned as a competitive learning-enhanced variant of ALNS.

Sustainability doi: 10.3390/su182010512

Authors: Juan Yang Yang Lv Yaoyu Lei Danyang Yu Pengfei Liu Yingdan Mei

Climate change is driving the accelerated green and low-carbon transition of the transport sector, which is crucial to the realization of China’s carbon peaking and carbon neutrality goals. Based on 41,601 micro-level freight vehicle observations covering 30 provinces across China over the first three quarters of 2025, matched to county-level climate and nighttime-light data, this study uses IPCC emission factor methodology to calculate CO2 emissions and analyzes the emission patterns and drivers through descriptive spatial analysis and county-fuel-type fixed-effects regressions, respectively. In the observed sample, diesel vehicles account for the largest share of total CO2 emissions, with high-emission areas concentrated in eastern coastal regions, while battery electric vehicles (BEVs) exhibit the lowest CO2 emission intensity (CEI), at 39 g CO2/t·km compared with diesel at 50 g CO2/t·km. However, this advantage is compromised in high-carbon grid regions. Temperature negatively impacts CEI, an effect primarily mediated through transport efficiency rather than energy consumption per 100 km. Low temperatures considerably increase CEI, with colder zones experiencing emission intensity increases of up to 7.1%. Newer models and larger marked tonnage also significantly lower CEI. These findings provide empirical support for formulating sustainability-oriented, differentiated climate-resilient road freight decarbonization policies.

Sustainability doi: 10.3390/su182010511

Authors: Ruixi Dong Shuxin Shen Wenqi Wang Chenyao Liu Yuhao Yang

As one of China’s most important industrial clusters, the Beijing–Tianjin–Hebei (BTH) urban agglomeration faces persistent air pollution while remaining a key driver of regional economic growth. In recent years, technological innovation has increasingly supported industrial upgrading and environmental improvement. The key research problem is therefore whether and under what conditions industrial clustering contributes to air pollution, and whether technological innovation can alter this relationship. To address this problem, this study uses panel data from 13 cities in the Beijing–Tianjin–Hebei region from 2015 to 2022 and employs Spatial Durbin Models, Spatial Threshold Models and sector-specific Spatial Durbin Models to examine how industrial clustering affects air pollution and how technological innovation moderates this relationship. The results indicate that (1) industrial clustering and air pollution exhibit an inverted U-shaped relationship, while the role of technological innovation varies across different stages of clustering; (2) technological innovation is associated with lower PM2.5 concentrations, and the positive association between industrial clustering and air pollution becomes weaker at higher levels of technological innovation, with the estimated threshold providing an exploratory division between innovation regimes; (3) the environmental associations between industrial clustering and pollution differ substantially across industrial sectors, reflecting clear sector-specific heterogeneity. Based on these findings, environmental policies in the BTH urban agglomeration should reflect differences in industrial structure and development stages. Technological innovation, industrial upgrading and differentiated emission-reduction measures across industries and cities may help mitigate the environmental costs of clustering while supporting sustainable development.

Sustainability doi: 10.3390/su182010510

Authors: Yu Liu

As the Yellow River Basin (YRB) cultivates new quality productive forces (NQPFs), it faces the urgent task of coordinating pollution reduction and carbon reduction. Using balanced panel data for 68 prefecture-level cities in the YRB from 2012 to 2024, this study combines social network analysis with two-way fixed-effects and mechanism models to examine how the spatial correlation network of NQPFs affects pollution and carbon reduction, that is, pollution emission intensity (P), carbon emission intensity (C) and the synergistic level of pollution and carbon reduction (PCS). The results show that: (1) the network exhibits a gradient pattern of “high in the east and low in the west” and a “core–periphery” structure, in which regional central cities such as Xi’an, Zhengzhou, Jiaozuo, and Luoyang serve as pivotal hubs; (2) network centrality significantly reduces pollution and carbon emission intensity and raises the synergistic level, and this finding remains robust to alternative and lagged explanatory variables, winsorization, sample exclusion, and two-stage least squares estimation; (3) industrial structure upgrading and lower energy consumption intensity are the two main channels; and (4) the effect is significantly stronger in non-resource-based cities and in the upper reaches. These findings provide empirical support for building a differentiated, network-based policy framework for the coordinated reduction of pollution and carbon emissions in the basin.

Sustainability doi: 10.3390/su182010508

Authors: Gabriela Surowiec Marek Furmankiewicz Zbigniew Norbert Piepiora

The village fund (fundusz sołecki) in Poland is a participatory governance mechanism for local community engagement and addressing community needs. It is organised voluntarily by municipalities within auxiliary administrative units, which most commonly cover individual villages. Residents prepare proposals for small-scale projects that involve activities or investments in public spaces within their administrative units. After formal verification, these projects must be implemented by the municipal office in the following financial year. This study aims to examine the geographical dynamics of village fund introduction across Poland, assess their significance for local communities, and identify their opportunities and constraints. Our analysis utilised national data from Statistics Poland, data obtained from a case study municipal office, and telephone interviews with village administrators. Local projects, despite their small scale, can positively contribute to the implementation of SDGs in rural regions, especially SDG 3, 11, and 16. They can enhance residents’ well-being through the development of safe and inclusive public spaces, social inclusion in local planning, and activities that engage and integrate local communities. However, successful implementation requires a baseline level of social activity to foster cooperation among residents during the project preparation phase. Village funds alone are an insufficient incentive for participatory governance in exceptionally passive communities. In such cases, traditional community development approaches involving professional facilitators may yield better results.

Sustainability doi: 10.3390/su182010506

Authors: Xiaowei Li Ya Li Chen Zhou

Regional inequality remains a persistent challenge for development governance. When external support is disconnected from local conditions or excessively displaces local actors, resource inputs may fail to generate sustainable development and even weaken local agency. To examine how external support can be transformed into sustainable local capacity, this study integrates neo-endogenous development theory with synergetics to develop an “exogenous–endogenous synergy” framework. Drawing on multiple rounds of fieldwork and interviews, the study finds that Guangdong–Guangxi collaboration has shifted from compensatory resource transfer towards capacity building and institutional embedding. This transformation operates through three interrelated mechanisms: coordinated guidance, multidimensional incentives, and digital empowerment. Variations in local resource endowments and ideational capacity give rise to three context-contingent pathways: integrated advancement, ideational activation, and resource mobilization, each representing a pathway towards an ideal-type model. The findings suggest that cross-regional collaboration may reduce regional inequality when transferred resources are converted into sustainable local capacity, thereby strengthening rather than substituting for local agency.

Sustainability doi: 10.3390/su182010509

Authors: Jun Zhao Zichen Wang Sasa Song Kaijun Zhong

In this study, we evaluate the effect of China’s Belt and Road Initiative (B&RI) on energy poverty, an essential energy issue that needs to be solved urgently in modern society, by deeply discussing whether energy poverty can be eradicated by expanding electricity supply during the gradual promotion of the B&RI. In this regard, this study applies the data of 126 countries from 2000 to 2019 to test the energy poverty eradication (EPE) effect of the B&RI, and the heterogeneous impacts and ecological consequence are further examined. We discover the following: (1) While the B&RI alleviates energy poverty from the perspective of electricity access, it does not alleviate multidimensional energy poverty, possibly due to limited improvements in energy affordability and cleanliness. (2) The EPE effect of the B&RI is particularly significant in low-income nations; moreover, across all countries, the effect is most prominent in those with stable official governments, low socioeconomic conditions, reliable investment profiles, and low levels of corruption. (3) The promotion and popularization of electricity in the B&RI countries is positively related to greenhouse effect, which may be closely related to the different types of national power generation. Accordingly, we further propose some policy implications to solve the issue of energy poverty.

Sustainability doi: 10.3390/su182010507

Authors: Demetra Demetriou

This study examines whether the transition from the Non-Financial Reporting Directive (NFRD) to the more comprehensive Corporate Sustainability Reporting Directive/European Sustainability Reporting Standards (CSRD/ESRS) is associated with changes in externally assessed sustainability performance and substantive environmental outcomes. Using an unbalanced firm-level panel over 2018–2025 and a Difference-in-Differences design, the analysis compares 1137 first-wave EU firms transitioning from the NFRD to CSRD/ESRS with 11,955 international and 2430 non-treated European firms. The policy shock is therefore interpreted as the incremental effect of more comprehensive sustainability reporting requirements rather than first-time mandatory reporting. ESG Score and Environmental Pillar Score capture assessed, disclosure-sensitive sustainability performance, while Energy, Water, and Waste Intensity capture operational environmental outcomes aligned with SDG 12. The findings do not support the hypothesized improvement in substantive environmental performance (H1). Water Intensity declines under the international benchmark, but this finding is not reproduced under the European counterfactual; Energy Intensity provides no evidence of improvement and shows some evidence of relative deterioration; and Waste Intensity moves in the adverse direction, with significant increases under both counterfactuals in the 2023–2025 sensitivity analysis. The findings also do not support the hypothesized improvement in assessed ESG performance (H2): the primary ESG Score shows no significant positive effect under either counterfactual, while the positive Environmental Pillar effect observed under the international benchmark is not reproduced under the European counterfactual and is accompanied by differential pre-treatment dynamics. Overall, the findings show different response patterns across assessed and substantive sustainability outcomes. From a policy perspective, more comprehensive mandatory disclosure alone may be insufficient to produce broad, immediate improvements in environmental performance during the early NFRD-to-CSRD/ESRS transition.

Sustainability doi: 10.3390/su182010505

Authors: Zhushi Jin Zihao Tian Lixin Tian

Bike-sharing systems are widely promoted as a low-carbon transport option for sustainable urban mobility, but their environmental benefits depend on the travel modes they replace and the emissions generated by system operations. This study develops a net operational carbon-reduction framework for free-floating bike sharing (FFBS) that jointly considers distance-based modal substitution and bicycle rebalancing. Distance tolerance and the fuzzy maximum-membership principle are used to identify plausible modal substitutions, while traveller characteristics and surrounding points of interest (POIs) are incorporated to refine substitution shares. The framework is applied to large-scale bike-sharing trip data from Nanjing, China, for October 2019, February–March 2020, and June 2020. Under the baseline accounting assumptions, the system was estimated to achieve positive net operational greenhouse-gas (GHG) reductions in all three periods, with most riding-stage benefits retained after accounting for rebalancing emissions. Carbon-reduction density was higher in June 2020 than in October 2019 in five of the six analysed districts, while changes in demand density varied across districts. The period differences are interpreted alongside seasonal and pandemic-related changes in travel conditions. These findings highlight the importance of jointly considering modal substitution, operational emissions, and spatial heterogeneity when evaluating the environmental performance of bike-sharing systems. The proposed framework can support district-level assessment of operational carbon performance, inform transport decarbonisation and sustainable urban mobility planning, and identify the data that would be most beneficial to such an assessment.

Sustainability doi: 10.3390/su182010504

Authors: John Ogbeleakhu Aliu Douglas Aghimien Clinton Aigbavboa Bankole Awuzie Londiwe Mthembu

Climate change is impacting ecosystems and infrastructure worldwide, prompting the construction industry to adopt sustainable practices to reduce its carbon footprint. Nature-based Solutions (NbS), such as algae-based materials, are emerging as beneficial alternatives to traditional construction materials. However, research on these innovations in South Africa is limited. This study presents findings from a preliminary assessment of algae-based materials in the country’s construction sector. A post-positivist stance was employed, using a quantitative research design with a questionnaire survey targeting built environment experts. Data analyses were performed using frequency counts, mean item scores, the Kruskal–Wallis H-test, and Fuzzy Synthetic Evaluation (FSE). The findings show low awareness and usage of algae-based materials, with bio-carbon cement as the only widely recognized option. However, the study identifies potential applications of algae in masonry, wall finishes, and concrete for structural elements. FSE indicates that respondents perceived algae-based materials as having significant environmental, social, and economic implications for sustainable construction. Based on responses from 63 built environment professionals from one South African province, this study provides context-specific insights into the potential integration of algae-based materials in the construction sector and identifies avenues for future research on practical applications, regulatory challenges, and the potential for scaling in other developing countries.

Sustainability doi: 10.3390/su182010503

Authors: Francis Bennie Mohamed Khan Andrew Swanson

The increasing penetration of distributed energy resources (DERs) in low-voltage networks is central to the clean energy transition but introduces coupled challenges in voltage regulation, harmonic distortion, and distribution-transformer operation that impact grid sustainability and asset longevity. This paper isolates feeder impedance as a controlled variable and evaluates whether remote-network power-quality severity and transformer consequence follow the same sensitivity trend. A time-domain model used a factory-matched 200 kVA, 11 kV/420 V Dyn11 transformer with 40% DER connected at remote Node S3. The DER current contained prescribed fifth, seventh, eleventh, and thirteenth harmonics, while the LV feeder resistance and inductance were co-scaled from 0.5 to 2.0 pu. Across the DER-connected sweep, Node S3 line-to-line RMS voltage increased from 420.45 V to 428.95 V, and the voltage-rise magnitude increased from 3.03 V to 11.55 V. Selected-order Node S3 VTHD increased monotonically from 1.104% to 1.395%. Baseline-corrected harmonic transfer impedance also increased at every assessed harmonic, supporting a feeder-impedance-driven voltage-response mechanism. In contrast, transformer loading remained within 14.44–14.52%, total transformer loss within 350.26–350.93 W, hot-spot temperature within 38.229–38.246 °C, and common-baseline relative aging within 0.2863–0.2871. The results demonstrate that feeder weakness can materially increase remote-node voltage and harmonic sensitivity without producing a corresponding increase in transformer thermal severity. Network voltage response and transformer consequence should therefore be assessed as related but non-equivalent engineering domains. By separating power quality management from transformer thermal risk, distribution utilities can avoid premature asset replacement, enabling targeted, resource-efficient investments that support sustainable grid planning and long-term renewable integration (SDG 7 and SDG 9).

Sustainability doi: 10.3390/su182010502

Authors: Bing Xiang Xu Cheng Xiaoyun Shang Lili Guo

Government subsidies can alleviate firms’ financing constraints and facilitate production expansion, but they may also increase pollution emissions. Their environmental consequences depend on the relative effects of production expansion and improvements in environmental efficiency. By matching data from the China Environmental Statistics Database and the China Industrial Enterprise Database, this study examines the relationship between government subsidies and firm-level pollution emissions using firm fixed effects and multidimensional interacted fixed effects. The results reveal a significant positive association between government subsidies and firms’ chemical oxygen demand (COD) emissions. This finding remains robust to alternative pollution measures, entropy balancing, double machine learning, and instrumental variable estimation. An examination of firms’ responses shows that government subsidies are associated with higher industrial output, greater resource consumption, and increased wastewater discharge. At the same time, subsidies are associated with lower industrial water use and wastewater discharge per unit of output, as well as higher COD removal rates, suggesting that production expansion and improvements in environmental efficiency may occur simultaneously. Further analysis reveals a significant convex nonlinear relationship between government subsidies and pollution emissions. Firms’ information technology infrastructure weakens the positive relationship, whereas a larger existing capital stock strengthens it. These findings suggest that improvements in resource-use efficiency and pollution abatement may be insufficient to offset the additional emissions associated with production expansion. They highlight a potential trade-off between promoting firm production and controlling pollution through fiscal support, providing firm-level evidence to inform assessments of the environmental consequences of general government subsidies and the design of subsidy policies.

Sustainability doi: 10.3390/su182010501

Authors: Amlan Haque

Artificial intelligence (AI) is increasingly embedded in organisational decision-making, creating opportunities for innovation and sustainability while intensifying concerns about accountability, transparency, stakeholder responsibility and human oversight. This structured theory-building integrative review synthesises a purposively bounded corpus of 35 unique works on responsible AI, AI governance, responsible leadership and organisational sustainability. Responsible AI Governance (RAIG) is conceptualised as a multidimensional organisational capability: the repeatable, coordinated and adaptive capacity through which responsible AI principles are translated into governance structures, decision processes, accountability arrangements, stakeholder relationships, human oversight and assurance across the AI lifecycle. Six interdependent dimensions are specified: ethical-strategic alignment, accountability architecture, human oversight and agency, stakeholder inclusion, transparency and assurance and lifecycle governance and adaptability. Responsible leadership is positioned as an antecedent managerial microfoundation rather than a constitutive dimension of RAIG. The framework separates sustainability from the content of RAIG and theorises sustainable organisational and stakeholder outcomes as consequences of effective governance. Propositions and a staged research programme establish a foundation for construct operationalisation, cross-context validation and subsequent nomological testing.

Sustainability doi: 10.3390/su182010500

Authors: Wilman Z. Llamoca Emilio J. Medrano-Sanchez

The construction sector accounts for a substantial share of global energy consumption and emissions, and bioclimatic design offers a low-cost mitigation pathway when tuned to the local climate. This design-stage screening examines to what extent the passive strategies of a preliminary design for an educational building in Villa María del Triunfo, on the desert coast of Lima, Peru, respond to the bioclimatic potential of its site, and which adjustments could improve their fit before construction. The local climate was characterized from an open-access typical meteorological year (Photovoltaic Geographical Information System, PVGIS-ERA5, 2005–2023), contrasted with a regional weather station, and each project strategy was compared with the climatic priorities derived from the Givoni bioclimatic chart. The results show a mild, very humid climate with no cooling demand, in which 96.2% of the hours have the potential to be addressed through passive strategies and the dominant challenge is to capture heat and manage humidity. The design responds only partially, since it is well-resolved in orientation and thermal mass yet incorporates strategies conceived to dissipate nonexistent heat. From this diagnosis, design recommendations are derived, together with a correspondence matrix whose findings, based on a single case, are indicative for analogous coastal desert climates.

Sustainability doi: 10.3390/su182010499

Authors: Ruiyi Cao Minggao Xue

This paper examines the relationship between firms’ artificial intelligence (AI) capability and corporate green innovation and the potential channels underlying this relationship. Using a firm-year panel of Chinese A-share firms listed on the Shanghai and Shenzhen main boards from 2002 to 2024, we find that stronger AI capability is positively associated with green innovation output, citation-based green innovation impact, and green technological knowledge breadth. Further mechanism analyses provide evidence consistent with knowledge fusion and formal technology cooperation as two potential channels. Specifically, stronger AI capability predicts greater technological overlap between firms’ AI and green patent portfolios and broader formal green technology cooperation in the subsequent year, including inter-firm cooperation and industry–university–research collaboration. Overall, the findings suggest that AI capability may help shape the knowledge generation and collaborative development processes of green innovation, potentially contributing to greater green innovation output, impact, and knowledge breadth.

Sustainability doi: 10.3390/su182010498

Authors: Fahad Mushtaq Shahid Ali Umair Ali Muhammad Asim Rizwan

Groundwater depletion in the Multan-Lodhran aquifer is intensifying as pumping expands faster than replenishment. This study explicitly separates two evidence types: (i) published baseline endpoints, which are recalculated here for transparent growth and water-budget indicators, and (ii) analyses performed in the present manuscript, comprising area-weighted GRACE/GRACE-FO storage residuals (2002–2024), a five-model bias-corrected NEX-GDDP-CMIP6 precipitation ensemble, precipitation-extreme diagnostics, and GIS-based managed aquifer recharge (MAR) screening. From the published baseline, built-up land increased from 346 to 417 km2 between 2000 and 2023; municipal wells rose from 16 to 92 by 2020; the urban-central groundwater decline was about 0.57 m yr−1; and the recalculated recharge-to-abstraction ratio declined from 1.15 in 2006 to 0.72 in 2020 and 0.58 in the 2045 projection. The new GRACE residual analysis indicates persistent regional storage loss, but the GRACE/GRACE-FO mission gap and residual surface-water contributions preclude treating the full-record slope as a homogeneous groundwater-depletion rate; pre-gap Theil–Sen slopes were −0.42 and −0.48 cm yr−1 for pre- and post-monsoon conditions. Under far-future SSP5-8.5, annual precipitation increases by 21.88%, while winter precipitation declines and monsoon/post-monsoon rainfall and upper-tail extremes intensify. These climate results describe precipitation opportunity rather than simulated groundwater recharge. GIS screening identifies low-slope alluvial areas with surface-water access as candidate investigation zones, not validated MAR sites. The framework is therefore intended for planning: site-specific hydrogeology, source-water quality, infiltration performance, and monitoring must be demonstrated, and recharge measures must be implemented alongside abstraction control.

Sustainability doi: 10.3390/su182010496

Authors: Marianna Saill-Dilnot Ryan Bello Scott Rayburg Melissa Neave

The concrete industry is a major source of global carbon emissions, largely due to Portland cement (OPC) production. Supplementary cementitious materials (SCMs), many originating as industrial by-products or waste streams, can reduce these emissions while supporting material circularity. This study compiles published (as at June 2023) data on compressive strength, durability, and global warming potential (GWP) for eight SCMs, integrating these metrics into a combined performance index (CPI) where data coverage permits. Of the eight SCMs, GBFS, fly ash, and silica fume had sufficient data for robust CPI calculation, although a value was also derived for waste marble powder, based on limited data. GBFS above 49% replacement achieved the strongest performance, reducing GWP by up to 62% while maintaining strength and durability comparable to OPC, while fly ash at 30–49% replacement also performed well. Comparison of cement paste and concrete results revealed limited correspondence, indicating paste data are not reliable predictors of concrete performance. These findings highlight the potential of high performing SCMs to lower emissions and improve resource efficiency, but SCM adoption alone will not achieve net zero, underscoring the need for complementary strategies including low-carbon binders and alternative materials.

Sustainability doi: 10.3390/su182010497

Authors: Cherepovitsyn Aleksey Shabalina Anastasia

Decarbonization requires oil and gas companies to combine gas-monetization projects with measures to improve operational efficiency and reduce emissions. This study develops a scenario-based approach to portfolio selection for a gas-condensate asset, accounting for economic value, risk, net gas-resource requirements, and carbon effects. Projects are evaluated relative to baseline pipeline gas sales. Within-scenario uncertainty is represented using triangular distributions and Latin hypercube sampling. Feasible portfolios are generated by exhaustive enumeration, followed by Pareto selection and risk-adjusted ranking. The synthetic model-based application considers six project solutions, generating 63 nonempty combinations. Under the specified assumptions, the number of feasible portfolios decreases from 37 in the inertial scenario to 19 in the moderate scenario and 2 in the stringent scenario. The mere presence of a decarbonization component does not determine project priority. Operational projects gain portfolio significance when they improve resource use and carbon performance. The capital-intensive project combining value-added gas processing with CCUS plays a different role: for the project set considered, it becomes necessary only when the minimum portfolio carbon requirement exceeds 1.90 but does not exceed 2.40 million t CO2e/year. Above this level, no feasible portfolio can be formed. This threshold interval is case-specific. These results reveal how decarbonization can affect both project ranking and portfolio feasibility, highlighting an asset-level energy–environment–economy trade-off.

Sustainability doi: 10.3390/su182010495

Authors: Yuantao Fang Yunhai Dai Zhuoqi Teng Renhong Wu

Against the backdrop of the global shift from scale-driven competition to innovation-driven development, together with the dual trends of climate governance and digital transformation, whether firms can transform ESG performance into sustainable innovation capability has become a central question in assessing the real economic value of ESG practices. Using panel data of Chinese A-share listed companies from 2009 to 2025, this study constructs a two-way fixed-effects model to systematically examine the effects of overall ESG performance and its three dimensions, namely, Environmental (E), Social (S), and Governance (G), on corporate sustainable innovation capability. Furthermore, this study incorporates artificial intelligence (AI) adoption and knowledge diversification (TD) into a unified analytical framework and investigates their roles as parallel mediating mechanisms. The results show that overall ESG performance is positively related to corporate sustainable innovation capability. In the joint regression, all three ESG dimensions have positive effects, with the social dimension exhibiting the largest marginal effect. Artificial intelligence adoption and knowledge diversification constitute two parallel and complementary transmission channels through which ESG enhances sustainable innovation capability. Further analyses find that higher ESG levels are positively associated with corporate sustainable innovation capability, whereas rapid short-term improvements in ESG are negatively related to corporate sustainable innovation capability. It shows that innovation performance experiences short-term pressure before a substantial ESG improvement but gradually surpasses its previous level afterward, indicating the existence of genuine short-term adjustment costs in ESG-driven innovation. This study simultaneously incorporate artificial intelligence adoption and knowledge diversification into the mechanism analysis of the ESG–innovation relationship, providing more fine-grained micro-level evidence on how ESG is transformed into real productive capacity. The findings offer important implications for firms’ differentiated ESG investment strategies and the coordinated design of innovation and sustainability policies.

Sustainability doi: 10.3390/su182010493

Authors: Tawheed Yousuf Rupinder Kaur Irfan Yousf

This study examines whether perceived waste-management quality is associated with tourist satisfaction after accounting for destination and selected visitor characteristics. It also describes how reported awareness and the stated influence of waste management on return and recommendation decisions vary across two Himalayan destinations. An intercept survey of 763 tourists in Gulmarg and Srinagar, Jammu & Kashmir, was conducted from May to July 2026. The study treats TPB and PSR as interpretive traditions rather than as tested causal models. Perceived waste-management quality accounted for the largest relative contribution to explained McFadden pseudo-R2 in the primary satisfaction model (54.4%), followed by destination (42.2%) and origin (3.3%). The association remained similar after adjustment for repeat visitation and length of stay (OR 3.48, 95% CI 2.39–5.13). Longer stays were positively associated with reported awareness of negative waste-management impacts, but this does not establish within-person change over time. The findings support closer examination of visible waste-management provision and maintenance. Communication and behavioural interventions need further evaluation in future research.

Sustainability doi: 10.3390/su182010494

Authors: Tudor Bungau Constantin C. Bungau Gabriela Tonț

Universities increasingly align their activities with the Sustainable Development Goals, but institutional action, measurement, documentary evidence, external assessment, and substantive sustainability impact are not equivalent. This structured evidence-based narrative review with integrative conceptual synthesis examined university sustainability implementation, measurement, reporting, governance, assessment, and outcomes, using the 2026 Times Higher Education Sustainability Impact Ratings as the principal external-assessment exemplar. The review sample comprised heterogeneous peer-reviewed empirical, review, bibliometric, modelling, and case-based studies, while Times Higher Education methodological documentation and University of Oradea (UO) institutional sources were analysed separately. Across the synthesis, recurrent problems in translating institutional action into measurable and documentable performance were grouped into three diagnostic categories: performance gaps, measurement gaps, and evidence gaps, which formed the diagnostic core of the review-derived Institutional Action–Data–Evidence Framework. The framework links gap diagnosis to construct-valid measurement, evidence readiness, management review, and corrective action. It was subsequently illustrated through a documentary institutional case at UO. The case did not contribute to framework derivation and was not used as an empirical validation dataset. Principal limitations include heterogeneous source designs, reliance on publicly accessible and partly institution-generated case documentation, and the absence of prospective external multi-institutional validation. Practically, the framework provides a diagnostic for distinguishing an underlying performance problem from deficiencies in measurement or documentary evidence and for linking each diagnosis to a differentiated institutional response. Future research should evaluate the framework prospectively across multiple universities and longitudinally examine whether external-assessment performance corresponds to independently measured sustainability outcomes.

Sustainability doi: 10.3390/su182010489

Authors: Nicola Pierro Marco Buffi Maria Teresa Petrone Aristide Giuliano Isabella De Bari

This study assesses the long-term potential of European biorefineries toward 2050 by combining georeferenced bioresource data, regulatory eligibility, and technological performance across the EU-27. It links spatially explicit biomass availability with RED-compliant biofuel pathways, distinguishing between options that can be deployed immediately and those with greater long-term scaling potential. The results indicate that maritime biofuel production is strongly shaped by regional resource endowment. Used cooking oil supports only limited production of FAME and HEFA, with modest outputs concentrated in a few highly urbanized or industrialized areas. In contrast, lignocellulosic and wet biomass pathways offer much larger and more geographically distributed potentials. Methanol from gasification and synthesis, liquefied biomethane, liquefied biohydrogen, and microbial-oil-based routes emerge as the most scalable options, supported by regions rich in agricultural residues, forestry resources, municipal organic waste, and manure. Quantitatively, methanol shows the highest standalone potential, reaching about 19.17 Mtoe/y. Liquefied biomethane and liquefied biohydrogen can reach about 23.74 Mtoe/y and 21.37 Mtoe/y, respectively. By comparison, FAME and HEFA reach 18.57 Mtoe/y and 17.92 Mtoe/y, although only about 0.99 Mtoe/y and 0.96 Mtoe/y come directly from used cooking oil. The most promising hotspots are located in Spain, France, Germany, Poland, Romania, northern Italy, northern Finland, and parts of eastern Europe. Overall, the findings show that Europe’s maritime biofuel supply will depend on a strong match between regional feedstock availability, conversion pathway, and regulatory suitability, making a portfolio-based strategy essential.

Sustainability doi: 10.3390/su182010492

Authors: Fortune Ganda

This study examines whether backward-looking corporate environmental disclosure (CED) and forward-looking climate-resilience reporting (CLIM) constitute empirically distinct disclosure architectures in 19 JSE-listed mining firms over 2015–2025 (208 firm-years; 189 consecutive transitions), and whether directors’ ownership helps explain their differences. Original 0–4 scores show that CED is concentrated at score 3 (88.5%). Descriptively, 91.5% of CED transitions retain the same score, compared with 79.4% for CLIM; firm-level trajectories likewise show broader CED stability and greater CLIM movement. These comparisons describe the observed panel and do not provide a formal test of the persistence difference. Because the two constructs use different evidence anchors on the common 0–4 maturity scale, part of the observed contrast may reflect construct-specific rubric calibration. Directors’ ownership is weakly and imprecisely associated with both outcomes, and the adjusted CED–CLIM ownership contrast is statistically indistinguishable from zero. Secondary quadratic and CED institutional-period estimates are sample-sensitive and interpreted descriptively. The contribution is architectural: CED and CLIM differ in content, distribution and temporal behaviour, but those differences do not translate into reliably different ownership sensitivities.

Sustainability doi: 10.3390/su182010490

Authors: Jonatan Villavicencio Moreno Alexandre B. Gonçalves Ana Paula Falcão

This article systematically analyzes and discusses the application of Building Information Modeling (BIM) in generating emergency escape routes within buildings. It is motivated by Sustainable Development Goal 11 (SDG 11), that aims to achieve long-term sustainability of human settlements, enhancing the safety and disaster resilience of the built environment. Following the PRISMA methodology, this study consolidates current research on BIM-based path planning to establish a structured, comprehensive framework for BIM-to-route workflows. Our findings indicate that BIM operates as a central “source of truth” platform, successfully integrating spatial geometry, enriched semantic data, and real-time sensor information to enable dynamic, risk-aware rerouting that extends beyond conventional static shortest-path logic. However, the existing literature remains fragmented, characterized by a lack of standardized system architectures, inconsistent evaluation metrics, and persistent interoperability challenges. Furthermore, validation strategies are predominantly simulation-based (57.6%), with only 7.6% of reviewed studies achieving real-world operational validation. To fully realize the safety benefits of these technologies, future research must prioritize the standardization of data extraction, graph network construction, and evaluation metric sets, while expanding empirical validation using real-incident data across a wider spectrum of hazard scenarios.

Sustainability doi: 10.3390/su182010491

Authors: Fengbao Liu Qiuyue Liang Siqi Yu

Against the background of urban stock renewal, new public cultural facilities are important carriers for improving the public cultural service system, and their spatial configuration is closely related to the equity and efficiency of public cultural resource allocation. The spatio-temporal distribution patterns of public cultural facilities and the factors influencing them have important implications for optimizing the allocation of public cultural facilities and advancing the equalization and sustainable development of public cultural services. Using urban reading rooms (URRs) in Luoyang’s central urban area as a case study, this study employed kernel density estimation, standard deviational ellipse analysis, exploratory space–time data analysis (ESTDA), and the Optimal Parameters-based Geographical Detector (OPGD) to systematically reveal the evolutionary characteristics of their spatio-temporal patterns and driving mechanisms. The results show that (1) the agglomeration pattern evolved from “two primary cores, four secondary cores, and multiple nodes” to “one primary core, one secondary core, and multiple nodes,” and finally to “one primary core and multiple nodes.” The spatial extent first contracted and then expanded, the overall distribution exhibited a northeast–southwest orientation, and the center of gravity shifted from the northeast to the southwest and then to the southeast. (2) The spatial distribution of URRs exhibited significant positive spatial autocorrelation, although the strength of positive spatial autocorrelation gradually weakened. High–high clusters showed a contracting trend, whereas low–high spatial outliers showed an expanding trend and were the most numerous. (3) A total of 79.74% of the grid cells exhibited relatively stable local spatial patterns; the directions of local spatial dependence exhibited pronounced spatial volatility; and 81.39% of the grid cells showed coordinated growth, indicating a high degree of spatial integration. The spatio-temporal mobility and cohesion coefficients indicated that the local spatial association structure of URRs exhibited strong stability and path dependence. (4) Public service facilities, bus stops, shopping facilities, food and beverage facilities, and population are the major factors influencing the spatial distribution of URRs. The vast majority of interactions among the influencing factors exhibit bivariate enhancement or nonlinear enhancement, indicating that the spatial distribution of URRs is characterized by pronounced multi-factor coupled driving effects. (5) The spatio-temporal pattern evolution of URRs results from the combined effects of multiple factors. Road and transport factors enhance connectivity, educational resources exert an attracting effect, socioeconomic factors provide support, public cultural resource factors produce synergistic effects, and everyday service factors play a dominant role. Together, these five categories of factors form a coupled driving mechanism involving multiple factors: connectivity–attraction–support–synergy–dominance. The findings provide a scientific basis for optimizing the spatial configuration of new public cultural facilities and promoting the equalization and sustainable provision of public cultural services in the context of urban renewal.

Sustainability doi: 10.3390/su182010488

Authors: Mayank Sukhija Erdem Coleri Servan Baran Sean P. Gibson

The use phase of the pavement life cycle assessment (LCA) contributes significantly to both economic and environmental burdens. However, its role is often overlooked when making decisions for pavement construction, maintenance, and rehabilitation. Pavement roughness is among the key factors influencing these burdens, and understanding its effect is crucial. This paper presents comprehensive insights into the impact of pavement roughness on road user costs and carbon emissions, while also highlighting associated challenges. The literature review clearly defines pavement roughness and distinguishes it from surface texture, a common source of confusion. Additionally, it outlines the impact of pavement roughness on climate change, energy use, user cost, and carbon emissions. Reported impacts include a 15 to 20% increase in fuel consumption under high-roughness conditions and user cost increases from $84 to $629 per vehicle annually as the International Roughness Index (IRI) rises from 1.58 to 3.95 m/km (100 to 250 inches/mile), with optimized rehabilitation triggers capable of cutting CO2eq emissions by up to 44%. Moreover, this review shows that vehicle electrification directly mitigates roughness-related impacts, with the transition to EVs capable of lowering roughness-induced emissions, with studies reporting reductions of 25% and 54% under different conditions. As a whole, it can be stated that the impact of pavement roughness is inevitably affected by pavement type, vehicle type and speed, vehicle tire condition, traffic load, and environmental factors. Although vehicle electrification offers potential for combating the consequences associated with pavement roughness, it introduces new challenges, including the high initial costs, limited charging ports, battery capacity, heavy load on the grid, and safety concerns. Overall, the current review improves the understanding of pavement roughness as a critical factor in sustainable transportation systems, consequently supporting the decision-making that reduces the effects of climate change and promotes sustainability.

Sustainability doi: 10.3390/su182010487

Authors: Sasha Pesci Allison Alberti Renee Lista

Food waste is a significant contributor to climate change, causing 58% of methane emissions from landfills in the United States. To manage its food waste, New York City (NYC), the largest city in the United States, instituted a citywide Curbside Composting program in 2015. Using a mixed methods approach, this research focuses on its implementation in New York City’s most diverse borough (Queens), examining residents’ awareness, participation, and attitudes toward the program. Data collection methods included an online survey of 83 residents of Queens, eight follow-up semi-structured interviews, and an interview with an informant from the NYC Department of Sanitation (DSNY). Findings from the survey indicate that while the majority of respondents identified benefits of the program, only 49% participated in some capacity. The most common motivators for participation were environmental and sustainability benefits. Additionally, the main deterrent to participation was lack of awareness. Findings from this study provide a community-specific understanding of the behaviors regarding NYC’s Curbside Composting Program. While this study is centered on Queens, these findings could provide insights for NYC and cities internationally looking to implement or improve organic waste collection and composting programs.

Sustainability doi: 10.3390/su182010486

Authors: António Curado Beatriz Lima

This article reports the design, development, and implementation of the WINd project’s Vocational Education and Training (VET) framework for reskilling workers from unsustainable energy sectors into the wind energy industry. This reskilling process is the central focus of the article, set against two converging challenges: the rapid expansion of wind energy in the European Union, projected to require over 700,000 additional workers by 2030, and the parallel displacement of professionals from unsustainable energy sectors, such as Offshore Oil and Gas and conventional electricity generation, driven by decarbonization policies. The WINd project responds by developing a flexible, inclusive VET framework intended to upskill blue-collar workers into wind turbine technician roles. Grounded in skills-matching analyses, stakeholder consultations, and co-designed curricula, the framework comprises a curriculum aligned to European Qualifications Framework (EQF) levels 4–5, Open Educational Resources, a multilingual Massive Open Online Course, a step-by-step technical mobile application, a European blueprint for a micro-credentialing scheme, and an online career support platform. By detailing the rationale, methodology, and outputs underpinning this reskilling process, the article discusses how targeted upskilling initiatives of this kind have the potential to strengthen sectoral skills intelligence, support just transition policies, and contribute to the long-term sustainability of the European wind energy workforce.

Sustainability doi: 10.3390/su182010483

Authors: Song Wu Na Chen Yanbing Chen Zhikang Wei Sen Dou Xuancheng Jin

An increase in grain production relative to household demand can reflect production growth or demand contraction. We examined these accounting pathways and resource indicators across 36 prefectures in Northeast China, using six snapshots from 2000 to 2023 and a comparison based on the inputs for 2020 and 2023. Budyko water yield, the Revised Universal Soil Loss Equation (RUSLE) and Shapley decomposition were combined with sensitivity analysis and ensembles incorporating model residuals. Estimated household grain demand declined in 34 prefectures under baseline inputs, with counts ranging from 9 to 36 under independent ±10% population and consumption perturbations. Production exceeded grain consumption at home in all 36 prefectures in 2023 throughout these perturbations. Baseline resource screening identified three prefectures with water pressure, eight with relatively high erosion and one with both flags. At fixed baseline thresholds, an ensemble incorporating water model residuals changed an average 21.7% of baseline categories per draw. Recent associations between changes in the grain ratio and resource indicators had intervals spanning zero. The framework distinguishes the accounting sources of an improving household grain balance and identifies priorities for local water and soil assessment.

Sustainability doi: 10.3390/su182010484

Authors: Abdulla AL-Rashidi

This study investigates the sustainable optimisation of cement-treated calcareous sandy soils using an integrated finite-element framework that links material-scale mechanical behaviour to foundation-scale response. Experimentally derived shear-strength parameters obtained from drained triaxial tests on sands treated with 1%, 2%, and 4% Portland cement were incorporated into COMSOL Multiphysics simulations to evaluate stress–strain behaviour, plastic deformation, displacement response, and bearing capacity under strip-footing loading conditions. The results demonstrate that artificial cementation substantially enhances soil behaviour by increasing apparent cohesion and limiting plastic deformation. Bearing capacity increased from 816.64 kPa for untreated sand to 5684.64 kPa, 8981.64 kPa, and 13,431.64 kPa for soils treated with 1%, 2%, and 4% cement, respectively. Concurrently, footing displacement and plastic strain development decreased progressively with increasing cement content. Cement stabilisation also improved stress distribution beneath the foundation and confined failure zones to smaller regions surrounding the footing, indicating enhanced foundation stability. To evaluate environmental performance, a quantitative embodied carbon assessment framework incorporating the Carbon Efficiency Index (CEI) and Carbon Intensity Index (CII) was developed. The results indicate that although the 4% cement treatment achieved the highest bearing capacity, the engineering benefit obtained per unit of embodied carbon decreased with increasing cement dosage. The 1% cement treatment exhibited the highest carbon efficiency, whereas the 2% cement treatment provided the most favourable balance between geotechnical improvement and environmental efficiency. The proposed framework integrates finite-element-based foundation analysis with embodied carbon assessment, establishing a direct relationship between soil-strength enhancement, foundation response, and carbon efficiency. The findings demonstrate that substantial improvements in bearing capacity can be achieved without proportionally increasing environmental impacts, supporting performance-based optimisation and sustainable ground-improvement design for sandy soils in arid regions.

Sustainability doi: 10.3390/su182010485

Authors: Francesco Filippi

This study investigates the potential of Autonomous Electric Wagons (AEWs) as an emerging technology for sustainable urban logistics. Because AEWs are still at the pilot-development stage, the objective is to develop a conceptual framework for assessing how such vehicles could be integrated into a metropolitan freight system and to explore its application to Rome. The proposed framework combines a peripheral Urban Consolidation Center (UCC), autonomous electric rail transport, inner-urban Urban Distribution Centers (UDCs), and low-emission last-mile delivery. The Rome application uses parcel-demand estimation, AEW capacity and fleet dimensioning, railway-cycle analysis, and scenario analysis to examine the potential scale and operating requirements of the proposed system. Under the reference assumptions, approximately 40,000 parcels/day are on average estimated for Amazon’s Rome market. A four-AEW platoon completing four daily cycles provides a theoretical capacity of approximately 54,000 parcels/day, indicating that the reference configuration could accommodate the estimated demand with a substantial margin. A second scenario with a UCC managed by a third-party logistics (3PL) operator and a shorter cycle time, allows a four AEW platoon six daily cycles for a theoretical transport capacity of 81,000 parcels/day. The analysis also identifies railway capacity, coupling and terminal operations, signaling and interoperability, and the availability of reliable freight-demand data as critical conditions requiring further investigation. The study therefore provides a conceptual and quantitative basis for evaluating AEWs in urban logistics and identifies the technical and operational issues that must be addressed before pilot-scale implementation can be assessed.

Sustainability doi: 10.3390/su182010482

Authors: Haidong Li Yiwen Wang Feifei Zhai Yunxing Zhang

Historic commercial districts sustain urban memory and public life, yet variations in their spatial conditions and user experiences present challenges for renewal. However, existing studies often examine accessibility, spatial vitality, and user perceptions separately, with limited quantitative integration of objective and subjective evidence. Taking Dehua Pedestrian Commercial Street in Zhengzhou, China, as a case study, this study investigates spatial variations and the relationships among these three dimensions within an integrated analytical framework. A multi-source approach combines space syntax analysis, POI kernel density analysis, street-view image semantic segmentation, and social media sentiment analysis to characterize spatial structure, functional activity, and user experience. The results reveal distinct spatial variations within the district, including uneven public service provision, limited accessibility in peripheral areas, and low greenery coverage. Pearson correlation analysis indicates positive associations among the three dimensions, with the strongest association between accessibility and spatial vitality (r = 0.65). User evaluations are generally positive, although concerns remain regarding greening, traffic congestion, and spatial openness. Overall, these findings demonstrate the interrelationships among accessibility, spatial vitality, and user perceptions and highlight the value of integrating objective and subjective evidence to identify spatial shortcomings and inform targeted renewal strategies for historic commercial districts.

Sustainability doi: 10.3390/su182010481

Authors: Anna Wieland Carla Romagna Stefanie Schulze Claas Thede Kristine Sperlich

The SCIP database currently lists nearly 18 million articles associated with electrical and electronic equipment (EEE) containing RoHS-restricted substances above the applicable threshold, raising fundamental questions about the overall effectiveness of the RoHS Directive. While the restriction applies to nearly all EEE categories, exemptions permit the continued use of restricted substances where substitution is not yet feasible. However, the continued high prevalence of RoHS-restricted substances in SCIP may indicate that exemption use remains widespread. This study provides a systematic analysis of the RoHS exemption process. The median time between submission and decision is at least 6.1 years, substantially exceeding the intended time frame. Three hotspot exemptions (Nos. 6(c), 7(a), and 7(c)-I) were identified, all material- rather than application-specific, associated with large estimated lead quantities entering the EU market, and characterized by an insufficiently specified scope. Transparency regarding these exemption use remains critically low, making it impossible to estimate total quantities of restricted substances entering the EU market and leaving market surveillance authorities, waste operators, and customers without the information needed to verify legitimate use. Mandatory disclosure of exemption use would improve market surveillance, accelerate exemption specification, and create competitive pressure to phase out exemption use in favor of sustainable alternatives.

Sustainability doi: 10.3390/su182010479

Authors: Weiyi Tian Jing Qiu Zhe Yuan Jiafeng Lin Xin Lu Zongting Xie

Local energy sharing can support more sustainable distribution systems by coordinating rooftop photovoltaic generation, behind-the-meter storage, and flexible demand among prosumers. Its expansion to larger energy communities, however, requires benefit-allocation mechanisms that remain computationally tractable while maintaining physically meaningful and sufficiently stable incentives for heterogeneous participants. This paper develops a fidelity-controlled WRT-inspired player-reduction framework for scalable cooperative energy sharing in distribution networks. Participants are characterized by physical–economic signatures incorporating temporal net demand, operational flexibility, stand-alone economics, marginal contribution, and network sensitivity. Candidate partitions generated through hierarchical entropy weighting and density-based grouping are screened according to feature-space compactness, member-wise game consistency, and aggregation-interaction consistency. Reduced coalitions are restored to their original participants before network-constrained physical evaluation, and the reduced-space nucleolus is subsequently recovered at the participant level. A split-coalition correction with independent out-of-sample validation is further introduced to improve allocation stability. For the primary N = 10 benchmark, the game consistent reduced formulation (Case 3) retains 6.07% of the original coalition space, limits the normalized L1 allocation error to 3.67%, and achieves a 5.40× speedup over the full-space nucleolus. The complete stability-corrected framework (Case 4) further reduces the out-of-sample violation probability from 0.900% to 0.433% while retaining a 1.73× speedup. Across five independently generated N = 10 instances, Case 4 achieves a median normalized L1 allocation error of 8.74% and a median speedup of 1.50×. At N = 30, the reduced representation contains 16,382 proper coalitions, corresponding to an approximately 6.55 × 104-fold reduction in coalition space. By enabling scalable and stability-aware benefit allocation while retaining participant heterogeneity and network operating constraints, the framework provides computational and economic enabling conditions for sustained participation in prosumer communities with distributed renewable energy resources. These outcomes concern the scalability and economic viability of cooperative participation.

Sustainability doi: 10.3390/su182010480

Authors: Ebru Kükey Ayşe Ülkü Kan

Preparing prospective teachers capable of addressing sustainable development challenges requires not only sustainable development awareness but also competencies that support evidence-based reasoning. However, empirical evidence regarding the relationship between perceived mathematical competence and sustainable development awareness remains limited. This study examined the relationship between prospective classroom teachers’ perceived mathematical competence and sustainable development awareness and investigated the moderating roles of gender and year of study. The study employed a cross-sectional research design with 341 prospective classroom teachers from four universities in Türkiye. Data were examined to determine the relationship between perceived mathematical competence and sustainable development awareness and to test the moderating roles of gender and year of study through moderation analysis. The findings revealed that perceived mathematical competence was positively and significantly associated with sustainable development awareness (r = 0.37, p < 0.001). Furthermore, gender significantly moderated this relationship (B = 0.56, p < 0.001, ΔR2 = 0.04), whereas year of study did not demonstrate a significant moderating effect (ΔR2 = 0.0045, p = 0.621). These findings indicate that prospective classroom teachers who perceive themselves as more mathematically competent also tend to report higher levels of sustainable development awareness. The study contributes to the literature by providing empirical evidence of the association between perceived mathematical competence and sustainable development awareness and highlights the potential relevance of perceived mathematical competence to education for sustainable development within teacher education programs.

Sustainability doi: 10.3390/su182010478

Authors: Dayu Wu Chuhan Chen Shanglin Du

Cultural sustainability in intangible cultural heritage (ICH) design requires contemporary visual innovation to retain cultural meaning and involve heritage holders. This study examines how generative AI capability relates to culturally grounded innovation using cross-sectional data from 542 matched designer–inheritor dyads in Guangyuan. Partial least squares structural equation modeling, multi-group analysis, necessary-condition analysis and fuzzy-set qualitative comparative analysis were applied. Generative AI-enabled visual design capability was positively associated with ICH visual design innovation, directly and indirectly through heritage knowledge integration, cultural visual translation and the theoretically ordered knowledge integration–visual translation pathway. Higher designer–inheritor collaboration quality was associated with stronger relationships between AI capability and both knowledge integration and visual translation. Point estimates followed the proposed heritage-context differences, but the group contrasts were not statistically supported. Necessary-condition and configurational analyses identified combinations of technological, cultural and relational capabilities, with limited configurational coverage and sensitivity to calibration. Integrating the dynamic capabilities and knowledge-boundary perspectives, the study distinguishes knowledge interpretation from visual enactment and locates collaboration quality within these capability relationships. The findings inform culturally sustainable use of GenAI by connecting visual exploration with verified heritage knowledge, continued inheritor participation and cultural-boundary governance. Design teams should document cultural sources and permissions, involve inheritors in interpretation and review, and assess cultural recognizability alongside novelty. These project-level associations identify capabilities relevant to cultural sustainability; long-term heritage transmission and safeguarding outcomes require further investigation.

Sustainability doi: 10.3390/su182010477

Authors: Ziwei Wang Xinbo Jiang Jinsheng Xuan Yuntao Liao Yi Zeng Wentao Wang

Rapid urbanization has intensified the urban heat island (UHI) effect, yet the river cooling distance and its associated influencing factors remain poorly understood. We retrieved Land Surface Temperature (LST) from Landsat imagery and mapped Local Climate Zones (LCZs) using the Random Forest algorithm. By integrating multi-ring buffer analysis with the Geodetector model, we quantified the river cooling distance across different LCZ types along the urban reach of the Xiang River in Hengyang City. Our results indicated that: (1) surface thermal conditions exhibited marked cross-LCZ thermal contrasts among the three summer acquisitions, with the most prominent warming anomalies found in LCZ 3, 7, 8, and 10; (2) the river cooling distances of built-up LCZs were 820 m (2011), 970 m (2018), and 780 m (2025), all falling within the 750–1000 m range; (3) the primary spatially influencing factors shifted from built-up intensity (NDBI) to nighttime light (NTL) and population density (POP). The distance factor alone showed weak explanatory power (q < 0.05) but exhibited strong synergistic interactions when combined with other factors. These findings suggest that future waterfront planning should maintain a core cooling protection zone while reducing anthropogenic heat sources in built-up areas, thereby enhancing the overall cooling benefits of river cold sources.

Sustainability doi: 10.3390/su182010474

Authors: Qiang Hu Xiangpeng Liang Wenjing Si Yingyue Hou

Mountain nature-based recreation spaces often combine high ecological quality with practical accessibility, yet they may also be constrained by sudden flash floods. Existing studies generally assess recreation opportunities and flood hazards separately, making it difficult to determine how potential recreation spaces progressively enter the scope of safety attention under different rainfall conditions. Taking Guizhou Province, China, as a case study, we developed history-informed standardised event-rainfall scenarios, assessed relative flash-flood potential using an NRCS-CN–HAND framework, and identified potential nature-based recreation opportunities from habitat quality and road proximity. We then analysed how areas requiring safety attention changed across rainfall conditions. The results show that the spatial extent of high relative flash-flood potential increased with event-total rainfall, but the rate of expansion varied markedly among rainfall stages, with the greatest province-wide expansion occurring between 30 and 40 mm. When potential recreation opportunities were intersected with high-potential areas, the resulting safety-attention areas expanded rapidly between 40 and 60 mm, with the largest increment between 40 and 50 mm. Activation rainfall for potential recreation opportunities was concentrated mainly between 50 and 70 mm and differed among prefecture-level units. By evaluating recreation opportunities and flash-flood constraints independently and linking them under comparable rainfall conditions, this study extends static recreation-opportunity mapping into dynamic safety screening and provides a practical spatial basis for prioritised site review, tiered inspection, and differentiated management of mountain nature-based recreation spaces.

Sustainability doi: 10.3390/su182010475

Authors: Gergana Kirova Margarita Stoytcheva Zdravka Velkova Georgi Avdeev Nikolay Zahariev Velizar Gochev

The presence of antibiotic residues in aquatic environments poses a significant risk to water quality and public health, creating a need for effective and sustainable treatment technologies. In this study, a chitosan-based nanocomposite containing silver, cobalt, and iron (CS-HNC) was synthesized under mild conditions without a calcination step and evaluated for the removal of tetracycline (TC) from aqueous solutions. Attention was given to TC removal at an initial concentration of 10 mg L−1. Although this concentration exceeds those typically reported for natural surface waters, it is lower than the concentrations frequently employed in adsorption studies and therefore provides a useful basis for evaluating the performance of the developed adsorbent under controlled laboratory conditions. The material was characterized by field-emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), and Fourier transform infrared spectroscopy (FTIR). The characterization results confirmed the successful formation of the nanocomposite and the incorporation of metal-containing phases within the chitosan matrix. The effects of key sorption parameters were investigated, showing that TC removal was only weakly influenced by pH and ionic strength. The maximum sorption capacity reached 45.7 mg g−1, while removal efficiencies of 94.3% and 98.4% were achieved after 30 and 120 min, respectively, at an initial TC concentration of 10 mg L−1. Sorption kinetics were best described by the pseudo-second-order model, whereas equilibrium data were better fitted by the Freundlich isotherm model. No detectable leaching of Ag, Co, or Fe was observed after soaking the material in deionized water and in a solution adjusted to pH 2 for 24 h, indicating good stability of the synthesized material under the investigated conditions. These findings suggest that the developed CS-HNC nanocomposite is a promising sorbent for the removal of TC.

Sustainability doi: 10.3390/su182010476

Authors: Zehua Chen Ning Xu

Urban renewal (UR) increasingly depends on the precise identification of the existing spatial stock and on cross-departmental coordination. Treating the staggered launch of local government data openness platforms as a quasi-natural experiment, this paper uses panel data on 282 cities over 2009–2024 and applies staggered difference-in-differences to test whether public data openness (PDO) improves UR. PDO raises the urban renewal index by 0.0019 to 0.0090, about 2% to 9% of the sample mean. The baseline estimate of 0.0090 is the upper end of this range. The local effect is 0.0040 after controlling for simultaneous openness in neighboring cities, and the estimate falls to 0.0019 when the time-varying effects of multiple predetermined characteristics are jointly controlled for. The increase comes mainly from facility improvements within existing built-up areas rather than outward urban expansion. PDO works mainly by promoting green technology innovation and raising land resource allocation efficiency, while the evidence for innovative talent inflow is weaker. The effect of PDO is stronger in cities with higher openness quality, better digital foundations, and higher administrative rank. PDO is also significantly associated with UR improvements in neighboring cities, mainly within about 300 km. Therefore, shifting PDO from platform construction toward data quality improvement and strengthening data coordination within city clusters will help achieve sustainable UR.

Sustainability doi: 10.3390/su182010473

Authors: Fanmeng Kong Ziming Qu Tong Zhao Xin Li Binghua Zhou Chao Lu

Water and mud inrush is a major hazard impeding the construction sustainability of tunnel crossings of water-rich active faults, where seismic-induced fracturing may compromise the integrity of water-resisting rock masses. Natural rock masses commonly contain pre-existing cracks and mineral veins, but their influences on dynamic failure under coupled geostress, hydraulic pressure, and seismic loading remain insufficiently understood. Taking the Kangding No. 2 Tunnel of the Sichuan–Tibet Railway crossing the Yunongxi active fault as the engineering background, a coupled hydro-mechanical discrete element model was established to investigate representative pre-existing crack and quartz-vein configurations corresponding to inclinations of 0°, 30°, 60°, and 90°. The model was subjected to principal stresses of 23.7 and 12.7 MPa, a groundwater pressure of 3.33 MPa, and combined horizontal and vertical seismic loading, with the horizontal component prescribed at 0.8 g and 5 Hz. The results show that pre-existing crack tips acted as preferential sites for fracture initiation, whereas quartz veins generally impeded fracture propagation before vein rupture. Shear fractures dominated the dynamic failure process in all investigated cases. The tensile-fracture ratios ranged from 7.90% to 13.15% for the crack-containing models, with the maximum value occurring in the 30° configuration, compared with only 7.01–7.84% for the vein-containing models. The AE b values of the crack-containing models ranged from 2.14 to 2.94 and exhibited a trapezoid-shaped variation among the investigated configurations, whereas the vein-containing models showed an oblique N-shaped variation, with a maximum b value of 2.23 in the 90° configuration. Abrupt increases and pronounced fluctuations in AE counts and energy accompanied intensified fracture propagation and model failure. These results provide numerical indications of potentially fracture-prone structural configurations, which can guide precise directional grouting, early warning and ecological protection in the migration of water and mud inrush, eventually supporting the construction sustainability of the tunnel.

Sustainability doi: 10.3390/su182010471

Authors: Bingjie Li Xiaoyan Hu Jing Shi Zesen Li Jiao Dai Zikai Fan Hu Li Zhongfu Tan Zehua Xue

Sustainable energy-system planning requires compact scenario sets that retain the renewable variability and operating stresses that determine investment, yet conventional typical-period methods can preserve average trajectories while removing these conditions. This paper develops a decision-faithful multi-temporal scenario clustering framework that evaluates representativeness through temporal structure and operating consequence. Hourly, daily, multi-day, and seasonal features describe source–load behavior, while a common screening fleet produces diagnostic signatures of cost, curtailment, adequacy, reserve pressure, ramping, storage-duration stress, transfer stress, scarcity price, and renewable-ramp interaction. A composite distance connects both representations to greedy facility location with seasonal and threshold-derived coverage, and assignment mass supplies scenario probabilities. The aggregate capacity-expansion benchmark comprises three years of hourly trajectories, a two-year design library, and a separate third-year dispatch evaluation. With 18 representative scenarios and design-calibrated (α,β)=(0.30,0.2), decision-signature error is 2.96%, compared with 4.87% for raw K-means, and capacity-vector error is 1.14%. Storage-boundary, screening-fleet, comparator, and exact-solver audits quantify the dependence on modeling choices. Across ten seeds from an independent unlabeled generator, signature error is 3.84±0.95% and capacity error is 15.38±6.66%. The computational experiments quantify representation and investment fidelity across the primary chronology, independent-generator cases, and sensitivity settings, and connect scenario reduction to renewable curtailment and adequacy under the planning model.

Sustainability doi: 10.3390/su182010472

Authors: Tiangang Chen Yaping Li Hui Wang Hong Pan Quangang Yang Yuping Zhuge Yanhong Lou

This study evaluated how wheat-straw input modifies the effects of 2% (w/w) wheat straw-derived biochar on Cd availability, soil physicochemical properties, enzyme activities, N transformation and microbial communities during a 49-day incubation. Combining 2% biochar with 6% straw reduced soil-available Cd by 7.14–14.28% relative to the biochar-only treatment, whereas increasing straw input from 6% to 9% did not further improve Cd immobilisation. Compared with straw-only treatments, biochar-amended soils maintained higher pH and lower available Cd, indicating that biochar buffered straw-induced acidification and Cd mobilisation. High carbon input increased β-glucosidase activity and AOB-amoA abundance, which was consistent with enhanced nitrification-related processes and may indirectly influence Cd mobility through soil-pH dynamics. These effects were partly buffered by the alkalinity of biochar. Biochar alone supported the highest microbial alpha diversity, whereas increasing carbon input reduced community richness. The BS6 treatment also maintained relatively high microbial biomass during incubation. Soil pH, mineral N and enzyme activities were associated with a variation in microbial community structure. Overall, moderate wheat-straw input combined with biochar improved Cd immobilisation while maintaining microbial activity and soil biochemical stability, suggesting potential for the remediation of Cd-contaminated agricultural soils.

Sustainability doi: 10.3390/su182010469

Authors: Qingyuan Jiang Danhua Liu Feng Xue Xuwei Tang

The adoption of provincial carbon-trading market-construction policies in China expanded rapidly before a five-year hiatus in new qualifying policies. This study examines how industrial-structure and GDP-feasibility learning cues relate to diffusion alongside pilot designation, regional competition, and media attention. Directed provincial-pair models cover the lagged-covariate period of 2013–2022 within a descriptive observation window of 2012–2022. Industrial-structure learning has a positive association in the additive model, and the highest signed-gap quartile differs positively from the lowest quartile, whereas GDP-feasibility learning is not supported. The industrial association becomes imprecise when national-market phases are included, and multiple-testing adjustments further qualify the evidence. Interaction estimates do not consistently support signal interference. The hiatus coincides with national-market construction and a changing population of nonadopters. Exploratory provincial scenarios also remain uncertain. These findings distinguish structural learning cues from economic-capacity cues while emphasizing that nationwide institutional change must be considered when interpreting provincial diffusion.

Sustainability doi: 10.3390/su182010467

Authors: Ahmed M. Elbisy Ayman H. Nassar

Schedule overruns in marine construction are pervasive, and on a given project, they typically exceed the cost deviation recorded on the same work. This study identifies the causes of those overruns and establishes their relative criticality for the schedule dimension on its own. A three-tier literature review and a three-round Delphi process produced 173 candidate delay causes, which were organized under the eight performance domains of the PMBOK Guide (Seventh Edition). Criticality was measured with a paired probability-impact index, and stress was tested with a 50,000-run Monte Carlo simulation. The ratings of 200 industry practitioners were ranked and compared between stakeholder roles and experience bands with the Kruskal-Wallis test under false-discovery-rate control. The perception ranking was then set against the documented outcomes of 59 completed marine projects in Egypt and the Gulf, where delays averaged 41.5% of planned duration and reached 100%. The leading causes were escalation in resource prices, delays in work and labor permits and licenses, long-term beach erosion, and delayed geotechnical and bathymetric surveys. Delay magnitude tracked the breadth of co-occurring causes (Spearman’s ρ = 0.76) far more closely than project size or duration. The sharpest discriminators of severe delay were permit delays, skilled-labor shortages, subcontractor delivery failures, and the financial standing of owner and contractor. Environmental uncertainty supplied over a quarter of all documented delay evidence, which indicates that the marine environment acts mainly as a schedule risk. Perception varied more with professional experience than with organizational role.

Sustainability doi: 10.3390/su182010470

Authors: Agnieszka Jankowska Adam Przybyłowski Oskar Gach Daniel Kaszubowski Alicja Pawłowska Klaudia Kościk

Across Europe, cities are redefining the function of streets in city centers, transforming them from spaces primarily serving car traffic into vibrant, liveable public spaces. These transformations reflect a broader shift toward sustainable urban development, aimed at fostering local communities, enhancing walkability, and reducing the environmental impact of transport. Gdynia’s Starowiejska Street—one of the key service-oriented streets in the port city center—underwent a redesign in 2023 that prioritized pedestrians, local services, and social interaction. This article examines customers’ transport preferences when visiting retail and service establishments along Starowiejska Street, analyzing differences by business type and the perceived role of parking availability. The study draws on a field survey conducted in May 2025 among 588 users of the street, complemented by inferential testing, binary logistic regression, correspondence analysis, and k-means cluster analysis, providing both descriptive and multivariate evidence on customer mobility patterns in a shared street environment. The results confirm that the street functions primarily as a local, pedestrian- and public transport-oriented destination, with walking (46.6%) and public transport (28.2%) dominating access modes. Statistically significant associations between travel mode, visit frequency, and business type were established through chi-square testing. Cluster analysis identified three distinct customer mobility profiles—Local Regulars, Occasional Visitors, and Car-Oriented Visitors—reflecting differentiated accessibility needs across the street’s commercial mix. Because the survey was conducted on a single day in 2025, two years after the redesign and without a pre-redesign baseline or a comparison street, the study describes the current, post-redesign accessibility pattern rather than demonstrating a change caused by the redesign. Within this scope, the case of Starowiejska Street illustrates how the organization of access to local services and public space is associated with everyday mobility choices in a way that appears compatible with environmental and economic sustainability goals. The redesign also illustrates, descriptively, how a more inclusive, pedestrian-oriented built environment can broaden accessibility for diverse user groups—including older residents, caregivers, and people with mobility limitations—whose needs are central to universal design thinking. The study contributes to the growing body of research on sustainable urban mobility by providing empirical evidence on the relationship between accessibility, street design, and local commerce in a single European port-city case. The research was supported by Gdynia Maritime University and conducted within the framework of the EU Horizon project SPINE—Smart Public Transport Initiative for Climate-Neutral Cities in Europe—situating the findings within a broader European context of mobility transition.

Sustainability doi: 10.3390/su182010468

Authors: Thai Huynh Phuong Lan David J. H. Blake

Inclusive participation is widely recognised as a prerequisite for effective and equitable water governance. However, the extent to which women are able to participate meaningfully in water management institutions remains poorly understood in many Southeast Asian countries. This study critically examines women’s participation in irrigation governance institutions in the context of Vietnam’s Mekong Delta using an intersectional gender framework and a qualitative typology of participation. Drawing on ethnographic field data from a district bordering Cambodia, the research explores how gender intersects with ethnicity, and how cultural norms limit genuine inclusive participation. The findings reveal a significant gap between women’s nominal presence in meetings and other management activities and their substantive involvement in decision-making processes. Meaningful participation in formal irrigation institutions was mostly observed as passive or tokenistic. Decision-making authority remains concentrated among male actors within hierarchical governance structures. The study identified a range of barriers, including unequal care responsibilities, language constraints affecting Khmer women, institutional bias, and cultural perceptions of water management as a masculine and technical domain. These factors collectively limit women’s ability to participate fully and influence governance outcomes. The findings show that representation alone does not ensure inclusion and underscores the need for more gender-responsive, culturally inclusive policies that address structural inequalities.

Sustainability doi: 10.3390/su182010466

Authors: Usame Demir Halil Erdi Gülcan Salih Özer Erdal Tunçer

This study experimentally investigates the performance, emission, energy, and exergy characteristics of six fuels in a two-cylinder, air-cooled, two-stroke unmanned aerial vehicle (UAV) engine, using neat gasoline (G100) as the reference fuel. The test matrix comprised G100, neat JP-8, gasoline–1-decanol blends containing 10 and 20 vol.% decanol (G90D10 and G80D20), and gasoline–diisopropyl ether blends containing 10 and 20 vol.% DIPE (G90E10 and G80E20). Experiments were conducted at shaft speeds of 3250, 3750, 4500, 5250, and 6250 rpm under matched speed–load conditions. Fuel consumption, exhaust-gas temperature, excess-air ratio, gaseous emissions, and first- and second-law thermodynamic performance were evaluated. The inclusion of G100 enabled the effects of the oxygenated additives to be quantified directly. At 5250 rpm, G90E10 reduced BSFC by 0.73% relative to G100 while increasing energy and exergy efficiencies by 1.69% and 1.61%, respectively. G80E20 produced larger reductions in brake-specific CO and HC emissions, 6.63% and 14.58%, respectively, and increased energy and exergy efficiencies by 2.43% and 2.27%, respectively, although both DIPE blends increased NOx. In contrast, increasing the decanol fraction increased BSFC and reduced thermodynamic efficiency relative to G100 despite moderate reductions in CO. JP-8 showed the strongest operating-point dependence; at 5250 rpm its BSFC was 9.52% lower than G100 and its energy and exergy efficiencies were 12.33% and 12.84% higher, respectively, whereas its advantage diminished markedly at the highest speed. Overall, the results demonstrate that oxygenate type and concentration produce distinct trade-offs between fuel utilization and gaseous emissions, while the suitability of JP-8 for gasoline-oriented two-stroke UAV propulsion is strongly dependent on operating conditions. From an operational-sustainability perspective, the results show that improvements in fuel utilization and incomplete-combustion emissions are strongly fuel and operating-point dependent. However, fuel production pathways, life-cycle greenhouse-gas emissions, durability, economic impacts, and mission-level environmental effects were outside the scope of this study and should be addressed before broader sustainability conclusions are drawn.

Sustainability doi: 10.3390/su182010465

Authors: Reem Alshagri Basmah Mohammed Attowaim Jawaher Binsuwadan

This study examines the effects of global supply chain shocks on inflation in Saudi Arabia, using monthly data from January 2014 to March 2026. Supply chain resilience has emerged as a critical dimension of economic sustainability, yet its inflationary consequences in commodity-dependent economies remain insufficiently understood. The analysis applies both Structural Vector Autoregression (SVAR) and Local Projection (LP) models to estimate impulse response functions. Inflation is measured using the wholesale price index (WPI) and its primary components. Findings from both methodologies are consistent, demonstrating that global supply chain shocks have positive, statistically significant impacts on most measures of wholesale price inflation in the short to medium term. The magnitude and persistence of these effects differ across components. In proportional terms, the most pronounced responses are found in ores and minerals and agricultural products—sectors closely tied to food security and sustainable resource management. However, their contribution to the aggregate WPI depends on their relative weights, with higher-weight categories, particularly metal products, machinery and equipment and food-related products, contributing more to aggregate wholesale price movements. Although the effects diminish in statistical significance over longer horizons, the cumulative responses indicate that supply chain disruptions can leave a persistent upward effect on wholesale price levels across specific categories, even after the direct inflationary impulse has subsided. These findings underscore the importance of building supply chain resilience as part of broader strategies for sustainable economic stability, with direct implications for monetary policy and inflation management in resource-dependent economies.

Sustainability doi: 10.3390/su182010464

Authors: Taoufyq Elansari Badr Ben Elallid Nabil Benamar Mohammed Ouanan Hamid Bourray

Long short-term memory (LSTM) networks, a specialized class of Recurrent Neural Networks (RNNs), excel at capturing temporal dependencies in time-series data but face significant performance trade-offs due to manual architectural design and parameter redundancy. This study introduces a dual-stage architecture optimization framework designed to enhance computational efficiency and structural compactness in LSTMs. The proposed framework combines metaheuristic search techniques specifically, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA) with Hadamard-based binary mask pruning during candidate search, which is followed by physical sub-network extraction for deployment. Coupled with the Adam optimizer for weight updates, the methodology is validated through an empirical application to solar energy forecasting using real-world photovoltaic plant data. Experimental results demonstrate that the proposed framework physically prunes active network capacity down to 23.6–28.3% (reducing the parameter count from 1051 K to 248 K and FLOPs from 2.10 to 0.49 MFLOPs) while attaining superior predictive precision (R2=0.979, MAE =116.04 kW over 30 independent seeds) and sub-millisecond inference latencies (≤0.92 ms). By outperforming standard baselines and modern time-series architectures, the framework establishes a highly efficient solution for real-time edge sequential prediction in renewable energy systems.

Sustainability doi: 10.3390/su182010463

Authors: Yan Li Ning Li Shanshan Wang

Taking the areas along the Pinglu Canal as the research case, this paper explores the mechanisms of tourists’ destination emotion, tourism subjective well-being and revisit intention. Based on 502 online questionnaires, structural equation modeling is used to examine the relationships among restorative environmental perception, destination emotion, tourism subjective well-being and revisit intention, and the K-means clustering algorithm is used to identify heterogeneous tourist groups. Meanwhile, LDA topic analysis is performed on 210 UGC texts to gain information about tourists’ activity preferences and information demands. The results reveal that restorative environmental perception significantly improves destination emotion, tourism subjective well-being and revisit intention. Destination emotion exerts a positive effect on tourism subjective well-being and revisit intention, while tourism subjective well-being further promotes revisit intention. Both destination emotion and tourism subjective well-being play mediating roles in this framework. Tourists can be classified into four categories with significant differences in psychological perception and behavioral tendencies. UGC analysis demonstrates that coastal leisure vacation and ecological mountain experience are the primary themes of tourist concern. This study provides references for the optimization of health tourism products, segmented marketing and sustainable development along the Pinglu Canal.

Sustainability doi: 10.3390/su182010462

Authors: Qian Zhang Zhou Zhou Zeyang Qi

Urban UAV route planning requires an explicit connection between spatial inputs, route restrictions, and evaluation criteria. This study presents a single-case demonstration of risk-map-based adaptive ant colony optimization (RMA-ACO) within an OD-based spatial routing framework. Building geometry and origin–destination activity supply receiver-related inputs under a common trip-generation-rate assumption. The method combines spatial exclusions, a local distance–noise heuristic, backtracking, early stopping, and geometric postprocessing. One origin–destination pair in a residential area of Changzhou, China, is examined at a fixed altitude of 10 m. History-dependent local scores guide route selection, whereas final routes are evaluated by geometric length and an unscaled noise-related model index on a common field. Across 30 fixed-seed runs at 5 m, RMA-ACO versus ACO means are 2763.6 versus 3190.1 m for route length, 143.2 versus 202.9 s for runtime, and 59.2 versus 60.9 for the noise index (paired difference: −1.7; 95% CI: −2.26 to −1.14). These results compare the complete tested configurations under the prescribed proxy settings. They do not isolate component effects or establish measured exposure reductions, transferability to other delivery connections, or operational flight feasibility.

Sustainability doi: 10.3390/su182010461

Authors: Wei Luo Jinli Du Hengwu Li

Logistics network development and supply chain organizational innovation may create external conditions for corporate green innovation. Using 30,700 firm-year observations for Chinese A-share listed companies from 2012 to 2024, this study examines the relationship between joint coverage by the Commercial Logistics Node City Program and the Supply Chain Innovation and Application Pilot Program and corporate green innovation. Double machine learning is employed to account flexibly for nonlinear relationships between policy coverage, firm characteristics, and green innovation. Dual-policy coverage is positively and significantly associated with green invention patent applications, with a baseline coefficient of 0.1131. The result remains positive under alternative cross-fitting folds, machine learning algorithms, sample restrictions, and measures of green innovation. Channel analyses indicate that dual-policy coverage is associated with greater supply chain digitalization, lower supply chain risk, and higher innovation efficiency. The estimated association is stronger among firms with higher R&D intensity and weaker among firms facing greater environmental uncertainty. These findings provide firm-level evidence that logistics connectivity and supply chain organizational conditions are relevant to corporate green innovation and offer policy implications for sustainable industrial development.

Sustainability doi: 10.3390/su182010454

Authors: Mesut Tabuk Barış Çetin

Preparing pre-service teachers to use artificial intelligence (AI) critically and equitably is part of the quality-education agenda of Sustainable Development Goal 4. Within a framework informed by the theory of planned behaviour, this study examined how AI literacy is associated with pre-service teachers’ belief that AI will play an important role in the teaching profession, and whether a gender difference in this belief runs through attitudes and perceived technological competence. Data from 493 pre-service teachers at one Turkish faculty were analysed with a latent structural equation model for ordinal indicators. Within this model, the association between self-reported AI literacy competence and the belief ran predominantly through positive attitude (indirect β = 0.20) and secondarily through perceived competence (β = 0.07). Ethical understanding was associated with stronger concerns about AI (β = 0.30). Women held a weaker belief than men (standardised difference = −0.28), a difference statistically accounted for mainly by lower positive attitude, with weaker evidence for perceived competence. Coefficients were stable across specifications. Because the design is cross-sectional and single-institution, the associations are not causal and require replication; they suggest that equitable AI preparation may be better targeted at positive experience with AI and perceived competence than at demographic categories.

Sustainability doi: 10.3390/su182010460

Authors: Yumin Chen Yang Wang Yunchi Qiao Han Zhang Hongli Liu

Against the growing prominence of global climate change and environmental governance challenges, synergistic pollution and carbon reduction (SPCR) has emerged as a core pathway for regional sustainable-development strategies. Focusing on the refined evaluation and dynamic prediction of intra-urban SPCR, this study selects 20 county-level administrative units in Chengdu, western China, and establishes an SPCR analytical framework based on a spatiotemporal adaptive ensemble model. First, the TOPSIS–gray relational analysis (GRA) approach is adopted to systematically measure the spatiotemporal evolution pattern of county-scale SPCR during 2001–2022. The overall SPCR level exhibits gradual improvement following a U-shaped trend. Complex-network theory is further applied to reveal the synergistic characteristics of its “core-periphery” structure. Second, the XGBoost–SHAP model identifies that the increased proportion of the tertiary industry and the control of total energy consumption constitute the most prominent positive and inhibiting driving factors for SPCR, respectively. On this basis, a Spatiotemporal Heterogeneity Ensemble Learning Model (STE-ML) is constructed. By dynamically integrating geographical proximity and socio-economic functional relevance, this model adaptively synthesizes the strengths of base learners, including the geographically and temporally weighted regression (GTWR) model, geographical optimal similarity (GOS) model, and Random Forest (RF), and achieves high-accuracy simulation of county-level SPCR (R2 = 0.806). Finally, four scenarios, namely the Business-as-Usual Scenario (BAUS), Structural Optimization Scenario (SOS), Technology Leadership Scenario (TLS), and Collaborative Governance Scenario (CGS), were established to simulate the evolutionary pathways of SPCR from 2023 to 2035. The results indicate that the BAUS, which continues the existing development pattern, will trigger further divergence in regional synergistic levels. By contrast, the CGS, which incorporates in-depth adjustment of industrial structure, low-carbon technological innovation, and cross-regional collaborative governance, can most effectively elevate the overall SPCR level and facilitate balanced development among county-level jurisdictions. In terms of robustness, a single-factor sensitivity analysis with ±10% variation in scenario parameters and a 95% prediction-interval test were conducted. The results show that the absolute value of the sensitivity index |S| does not exceed 0.0113, and the gap (1.44%) between the CGS and BAUS substantially exceeds the maximum effect of any single parameter. These findings verify that the forecasting conclusions are robust and that scenario discrepancies are not driven by a single hypothetical parameter. This study provides methodological support and empirical evidence for the implementation of differentiated and refined collaborative governance of pollution and carbon reduction within cities.

Sustainability doi: 10.3390/su182010459

Authors: Mahmut Dingil Levent Atatanır

Rapid and uncontrolled urban growth poses a severe threat to arable agricultural oases by jeopardizing vital ecosystem services and regional food security. This study investigates the spatiotemporal dynamics of urban sprawl over a 16-year period (2007–2023) in Faiyum City (Egypt), an ancient oasis surrounded by prime agricultural soils, and projects future spatial trends under unconstrained development scenarios. Utilizing high-resolution multi-temporal satellite imagery integrated with Remote Sensing (RS) and Geographic Information Systems (GIS) techniques, built-up area expansion was quantitatively measured, sectoral decomposition shows expansion on every flank of the historic core but at markedly uneven rates, converting between 13.8% and 55.7% of the land available in each direction and an area-based growth model was applied to simulate short- and long-term land transformation trends. Empirical findings reveal that between 2007 and 2023 the urban built-up area expanded by 55.7%, from 861.7 ha to 1341.6 ha, at an average annual compound growth rate of 2.8%, raising its share of the enclosed study area from 37.7% to 58.6%. Sampling of the converted area shows that 80.6% of it had been agricultural land at the baseline date, giving 386.9 ha of farmland lost over the period. The projections indicate that, without intervention, built-up cover would occupy 67.3% of the 2287 ha enclosed by the Ring Road by 2028 and 77.3% by 2033, leaving 518.7 ha of the unbuilt land that remained in 2023. This trajectory bears directly on SDG 11 and SDG 15 targets. Containment instruments such as binding Urban Growth Boundaries and compact infill policies are discussed as directions indicated by the spatial evidence, although their feasibility, cost and enforcement requirements lie outside the scope of this analysis.

Sustainability doi: 10.3390/su182010458

Authors: Altan Yılmaz Elvan Karabay

Road networks represent essential municipal infrastructure assets that require timely preservation to maintain serviceability and traffic safety. However, premature pavement degradation driven by operational traffic loading presents a continual challenge for municipal pavement management. This study presents a locally calibrated empirical framework to evaluate the degradation of the pavement condition index (PCI) under different traffic compositions. Standardized visual distress surveys across 406 sample units (ASTM D6433) were combined with directional peak-hour classified traffic monitoring across primary urban corridors in Burdur, Turkey. An empirical multiple linear regression (MLR) model was developed using hourly traffic volume (V) and heavy vehicle ratio (HVR) across 12 representative non-rehabilitated pavement sections. The calibrated model demonstrated high explanatory power (R2 = 0.925, SE = 3.56, p < 0.001) and robust internal validity, as indicated by Leave-One-Out Cross-Validation (Q2 = 0.884) and a 1000-iteration non-parametric pairs bootstrap analysis. Key findings show that the standardized regression coefficients highlight heavy-vehicle exposure (β* = −0.712) as exerting an approximately 1.66-fold stronger relative impact on surface distress than gross traffic volume (β* = −0.428). Sensitivity simulations further reveal that increasing the heavy-vehicle ratio from 4% to 12% results in a 21.0-point absolute reduction in PCI, substantially compressing the operational margin before reaching critical rehabilitation thresholds (PCI ≤ 40). Ultimately, this cross-sectional framework provides municipal agencies with an indicative screening reference for understanding traffic-related deterioration patterns without requiring high-cost data collection platforms.

Sustainability doi: 10.3390/su182010457

Authors: Jovana Vitošević Jovana Radoičić-Dimitrijević Milica Filipović Biljana Vitošević Katarzyna Sterkowicz-Przybycień Miloš Popović Strahinja Milovanović Tijana Purenović-Ivanović

The gamblification of sport has entered a fintech-enabled phase in which betting is no longer merely advertised around sport but designed into the act of watching it—continuous, mobile, frictionless, and seamlessly financed. Because this transformation shortens the pathway between impulse and expenditure, its consequences are increasingly financial; yet the evidence on how it affects the financial wellbeing of fans has not been synthesised. This scoping review, conducted in accordance with the PRISMA-ScR guidelines, mapped research linking the gamblification of sport—in both its marketing and its fintech dimensions—to fan financial wellbeing. Three databases (Scopus, Web of Science, PubMed), supplemented by hand-searching and a Google Scholar sweep, yielded 69 included studies. The evidence is young, expanding, and still largely exploratory in character. It is weighted heavily toward the marketing channel (advertising, sponsorship, inducements, normalisation), which is mature and well-theorised, whereas the fintech affordances of the betting product form a distinct but smaller literature, and financial wellbeing is most often reached only indirectly through marketing-driven overspend. Only five of the 69 studies directly measured a financial outcome, and all five lay within the fintech channel; the intersection at the centre—where the redesigned product meets the financial lives of vulnerable fans—remains largely unoccupied. We reframe this gap as a question of the social sustainability of sport, bearing on equity, wellbeing, and responsible consumption (SDGs 10, 3, and 12), and set out a research and governance agenda to address it.

Sustainability doi: 10.3390/su182010456

Authors: Yang Chen Hong Xu Ming Mu Yinglin Wang

The digital economy is reshaping talent development needs and programme and curriculum provision in higher education, making sustained alignment between programme provision and societal needs an important concern for sustainable higher education. However, how different digital economy conditions jointly influence university programme structure optimisation remains insufficiently understood. Using data from 29 provincial-level regions in China, this study characterises digital economy development across five dimensions: digital service accessibility, digital innovation, industrial digitalisation, digital industrialisation, and the policy and fiscal support environment. It constructs an index of university programme structure optimisation for digital transformation and distinguishes the shares of new engineering and non-engineering programmes. Fuzzy-set qualitative comparative analysis (fsQCA), fixed-effects models, and system generalised method of moments (GMM) estimation are combined to identify configurational pathways and linear effects. The results show that multiple digital economy conditions jointly shape programme structure optimisation, with digital service accessibility and the digital industrial base providing relatively consistent support. Engineering programmes respond more directly to digital economy development and exhibit clearer pathways, whereas non-engineering adjustments are more complex and involve indirect institutional influences and knowledge reconfiguration. From a programme and curriculum change perspective, this study reveals multiple pathways and regional differences in programme structure optimisation. The findings inform regionally tailored programme and curriculum restructuring and the sustained adaptation of higher education to socioeconomic needs.

Sustainability doi: 10.3390/su182010453

Authors: Domingo Rodríguez Benavides José Antonio Climent Hernández Mario Gómez Luis Fernando Hoyos Reyes

This study examines whether the predictive relationship between atmospheric CO2 concentration and global surface temperature anomalies remains stable over time. Monthly deseasonalized observations from March 1958 to August 2025 are analyzed with structural-break unit-root tests and forward-expanding, rolling, and recursive-evolving time-varying Granger-causality (TVGC) algorithms within a lag-augmented vector autoregression (LA-VAR). The unit-root evidence classifies temperature anomalies as I(0) and atmospheric CO2 concentration as I(1). With two lags, predictive evidence from CO2 concentration to temperature is weaker and algorithm-dependent, whereas temperature-to-CO2 predictive content is significant across all three algorithms. With 12 lags, the no-Granger-causality null is rejected at the 1% level in both directions and for all algorithms. These results document time variation and lag sensitivity in conditional predictive precedence; they do not establish a bidirectional physical mechanism. The detected changes can support climate-monitoring diagnostics and evidence-informed assessment relevant to Sustainable Development Goals.

Sustainability doi: 10.3390/su182010455

Authors: Arora Anchal Nir Y. Krakauer Ajay Jha

Conflict and turmoil over the last 50 years have impaired Afghanistan’s agricultural and water infrastructure and threatened rural livelihoods and economic stability. This study assesses value-added, home-based, women-empowered agri-processing in Afghanistan as a sustainable strategy to promote rural economic development, empower women, and enhance food security. By analyzing existing literature, global reports, and regional case studies, this paper highlights the roles of adaptable technologies, microcredit mechanisms, and market linkages in building resilient rural economies and overcoming limitations such as land fragmentation, low technology inputs, and poor agri-infrastructure. The main growth drivers would be harnessing adaptable technology, building rural infrastructure, adopting efficient agricultural practices, and connecting to skilled education. The findings underscore the significance of supportive policies and investments in home-based value-added agri-processing to foster sustainable growth, poverty reduction, and economic inclusivity in Afghanistan.

Sustainability doi: 10.3390/su182010452

Authors: Shakhmar Sarsenbay Yershat Sapazhanov Grzegorz Załęski Bobir Razhametov Robert Szarota

Universities admit students on thin evidence. Where admission rests on an examination score and the judgment of a committee, mismatch between an applicant’s profile and the demands of a degree program surfaces later as disengagement, attrition, and wasted institutional resources. This paper treats that outcome as a problem of decision quality and frames admission as selection risk management, by analogy with personnel selection in human resource management, where psychometric evidence is long established as a way of reducing the cost of a poor match. We set out the managerial chain connecting screening to sustainable human capital formation under SDG 4.4, state which link this study tests and which remain hypotheses, and report the evidentiary step any such system presupposes: whether the instrument in use measures anything dependable. Exploratory and confirmatory factor analysis of two blocks completed by Generation Z applicants at a Central Asian university (abilities, 45 items, N = 839; personality, 60 items, N = 807) retained seven factors in each block. Reliability is weak: only six of the fourteen retained factors reach 0.70 on Cronbach’s α and McDonald’s ω, and eight fall below it. Confirmatory fit was poor for the ability block (CFI = 0.789, SRMR = 0.117) and good for the personality block (CFI = 0.962, SRMR = 0.062), though in the latter the factors intercorrelate up to 0.895, which limits their discriminant interpretation. The instrument therefore requires revision before subscale-level use. The principal contribution is managerial: an institutional integration model specifying how screening evidence enters admission and advising decisions, with an explicit account of the evidential conditions a university must satisfy before acting on such instruments.

Sustainability doi: 10.3390/su182010448

Authors: Miloš Krstić Ivan Đekić Lidija Madžar

Climate change is often seen as the most global and complex problem that has emerged in the development of humanity so far. Rising temperatures, changing precipitation and more frequent extreme climate events affect all countries regardless of their geographical location and level of development, determining national production potential and the quality of life of the population. Starting from these challenges, this paper analyzes the contribution of key socio-economic determinants of climate change, which are quantified through CO2 emissions, in eighteen European Union countries, with a special emphasis on the spatial spillovers of these impacts between countries (the period 2014–2023). The research results indicate that climate change in a country does not depend exclusively on “domestic” factors, but is also exposed to spillovers from neighboring countries, which confirms the existence of spatial dependence. By applying the econometric model SARAR, public expenditure on research, development and demonstration of energy technologies, electricity prices for households, and social protection expenditures were identified as key and statistically significant predictors of CO2 emissions, where the estimated effects are conditioned by the specification of the spatial weight matrix and the choice of fixed or random effects. The research findings highlight the role of public expenditure for R&D in the field of energy that has a significant negative impact on CO2 emissions. In addition to direct emission reductions within the observed country, the model confirms the existence of a strong indirect (regional) spillover effect. This proves that investments in clean energy technologies effectively decrease pollution in neighboring geographical areas.

Sustainability doi: 10.3390/su182010446

Authors: Verónica Isabel Vera Vera Sonnya Patricia Mendoza Lombana Ana Gabriela Balseca Vaca Wilson Alexander Zambrano Vélez

The integration of Artificial Intelligence (AI) in educational settings creates pedagogical opportunities while raising environmental concerns regarding data center energy consumption and physical infrastructure footprint. This systematic review synthesizes scientific evidence on the algorithmic carbon footprint of AI tools implemented in environmental education programs. Adhering to the PRISMA 2020 statement and an adapted PICoS framework (Population: educational stakeholders; Phenomenon of interest: AI carbon/energy auditing; Context: environmental/sustainability education; Study design: empirical and theoretical studies), systematic searches were conducted across Scopus, Web of Science, IEEE Xplore, and ERIC up to 6 August 2026. Seven studies met the eligibility criteria: 5 empirical, 1 scoping review, and 1 theoretical-conceptual synthesis. Quality appraisal utilized MMAT (2018 version) for primary empirical studies and an adapted SANRA (2019 version) for non-empirical documents, followed by qualitative narrative synthesis. Results indicate that, within the reviewed corpus (n = 7), studies predominantly examine conversational agents and large language models (LLMs) applied to sustainability education, while highlighting a critical measurement gap regarding the empirical auditing of energy consumption and physical infrastructure during model training and inference. Conceptual frameworks synthesized across non-empirical literature hypothesize a potential misalignment between educational content promoting planetary conservation and the environmental opacity of underlying technological deployments. Key limitations include inferential fragility due to a small, methodologically heterogeneous evidence base restricted to higher education settings. This review was funded by Universidad Estatal Península de Santa Elena (grant Fcm_012) and hosted on the Open Science Framework project repository (DOI: 10.17605/OSF.IO/AD6TM), with its formal frozen protocol registration archived under DOI: 10.17605/OSF.IO/KBWFS.

Sustainability doi: 10.3390/su182010450

Authors: Jie Shan Zhengshan Luo Zhe Song

Against the backdrop of global climate judicial governance and human rights protection, public interest litigation, as an important judicial system for supervising government carbon reduction duties and regulating enterprise carbon emissions, deserves in-depth investigation. Based on panel data from 30 Chinese provinces over 2013–2021 and 14,073 public interest litigation judgment documents, the research adopts an ESG perspective and treats public interest litigation as a judicial form of environmental governance. Using a fixed-effects model, the research examines the association between public interest litigation and carbon emission intensity. The results show a significant negative association between public interest litigation and carbon emission intensity, which remains robust after instrumental variable regression and the exclusion of municipality samples. Heterogeneity analysis indicates that the negative association is relatively weaker for civil public interest litigation than for administrative and civil public interest litigation attached to criminal proceedings. Moderation analysis reveals that government duty fulfillment and enterprise green innovation positively moderate the negative association, while the moderating effect of public judicial attention is not statistically significant. Based on this, the research suggests maintaining judicial modesty while supervising government duties, strengthening the principal role of enterprises in carbon reduction, and improving institutional channels for public participation in judicial governance. The research provides empirical evidence on the association between public interest litigation and carbon emissions, contributing to the international academic discussion on judicial governance and low-carbon transition.

Sustainability doi: 10.3390/su182010451

Authors: Xin Cai Haitao Fan Zhen Zhang Wanqiao Zhao

This study examines governance path selection and emission reduction in e-commerce supply chains under a hybrid carbon-pricing mechanism. A tripartite evolutionary game is developed in which the government chooses Collaborative or Direct Governance, the platform chooses Green Empowerment or Routine Operation, and manufacturers choose Low-Carbon or Conventional Production. Carbon taxes enter government revenue, while manufacturers sell surplus allowances or purchase shortfalls at effective prices that reflect trading frictions. The analysis derives strategy thresholds and local stability conditions, followed by simulations of initial strategies, platform incentives, accountability fines, and aggregate carbon-pricing intensity. The results show that a stable Collaborative Governance–Green Empowerment–Low-Carbon Production equilibrium requires compatible incentives among the three participants. At the benchmark policy share, the manufacturers’ basic payoff difference becomes positive above the normalized aggregate carbon-pricing threshold κ* ≈ 0.4823; trading frictions have a modest effect on policy composition. Platform performance rewards encourage Green Empowerment, while rewards above S2∗=3.2 shift the government’s locally stable choice toward Direct Governance under the benchmark conditions. Accountability fines mainly accelerate platform adjustment when Conventional Production remains prevalent. These findings inform the coordination of carbon pricing and platform governance during supply chain decarbonization.

Sustainability doi: 10.3390/su182010449

Authors: Inass Saidni Jihane Gharib

Smart manufacturing increasingly combines digital technologies with operational excellence and Industry 5.0 principles, yet evidence remains fragmented across technological, organizational, human, and sustainability perspectives. This study conducts a PRISMA 2020 systematic literature review of 115 manufacturing studies published between 2020 and 2026. The synthesis identifies intelligent digital capabilities, organizational readiness, human-centered capabilities, and operational excellence practices as recurrent evidence-derived dimensions, with sustainable manufacturing performance as the principal outcome domain. Building on these findings, the authors propose user-centered operational excellence (UCOE) as a conceptual higher-order capability that integrates digital intelligence, organizational alignment, human participation, and structured continuous improvement. The proposed architecture distinguishes evidence-derived dimensions from author-synthesized role assignments and links UCOE to operational and economic, environmental, social and human, and resilience outcomes under contextual and feedback effects. The corpus contains substantial review and conceptual evidence and comparatively limited direct industrial validation; consequently, the propositions are presented as testable theoretical relationships rather than established causal effects. The study provides an evidence-traceable basis for future construct validation and industrial testing of sustainable human-centered smart manufacturing.

Sustainability doi: 10.3390/su182010442

Authors: Ruining Cai Feifei Sun

Maintaining export resilience against trade policy shocks is a critical challenge for industrial exporters amid rising global trade protectionism. Treating the 2018 US–China trade friction as a quasi-natural experiment, this study examines the interactive effects of research and development (R&D) capability and environmental, social, and governance (ESG) performance based on panel data of Chinese A-share listed manufacturing firms from 2015 to 2024. Measuring export resilience via annual export growth deviations relative to the pre-shock benchmark, our continuous Difference-in-Differences (DID) estimates show that trade policy shocks significantly reduce corporate export resilience, whereas robust pre-shock R&D capability serves as a core buffer that mitigates this adverse impact. Furthermore, a quadruple interaction model indicates that ESG performance positively moderates the buffering effect of R&D rather than functioning as an independent buffer on its own. Marginal-effect comparisons confirm that the protective value of ESG is conditional on a firm’s innovation capacity; when R&D capability is weak, high ESG performance alone offers limited protection against tariff pressures. Overall, R&D capability and ESG performance exhibit synergistic complementarity in sustaining export resilience under external trade shocks.

Sustainability doi: 10.3390/su182010445

Authors: Marija Živić Matej Đuranović Antun Barac Katica Šimunović

Building heating energy demand is influenced by indoor temperature, air exchange, and climatic conditions. This study examines the individual and combined effects of these parameters on a district-heated multi-apartment residential building in Osijek, Croatia. A TRNSYS model was evaluated using measured space-heating consumption for the analysed period from October 2024 to April 2025 and representative TMYx weather data. In the model, air exchange was represented by an effective air-change rate accounting for both uncontrolled air infiltration through the building envelope and natural ventilation associated with occupant window opening. The measured seasonal consumption was 666.16 MWh, while the model predicted 670.61 MWh, resulting in a deviation of 0.67%. The model was then used for a full-factorial analysis including nine indoor temperatures from 18 to 26 °C, nine effective air-change rates from 0.30 to 0.70 h−1, and six Croatian locations, giving 486 simulation scenarios. Under reference conditions, heating demand in Zadar and Split was 44.05% and 50.93% lower than in Osijek/Čepin. Increasing the indoor temperature from 18 to 26 °C increased seasonal demand by 432.63–525.32 MWh, while increasing the effective air-change rate from 0.30 to 0.70 h−1 increased it by 182.67–296.55 MWh. The analysis also showed a positive interaction between indoor temperature and effective air-change rate. For the analysed building, the results can support more sustainable energy use by informing energy-efficient building operation and district-heating demand planning, while the reported numerical sensitivities remain specific to the case-study building.

Sustainability doi: 10.3390/su182010447

Authors: Syed Rafid Ali Shah Yajuan Dong Amin Ullah Khan

Transportation-related CO2 emissions remain an important challenge for sustainable mobility and the energy transition in rapidly developing economies. This study examines transportation-related CO2 emissions in China using annual data for 1990–2024 within a STIRPAT-informed forecasting framework. Urban population share, GDP per capita, the fossil-energy share, and physical freight activity are used as theory-guided predictors. The analysis compares naïve persistence, a dynamic OLS benchmark, Support Vector Regression (SVR), XGBoost, and a compact Long Short-Term Memory (LSTM) model using chronological rolling-origin evaluation. One-year-ahead forecasts are assessed for 2010–2024 using RMSE, MAE, MSE, out-of-sample R2, and Harvey–Leybourne–Newbold-adjusted Diebold–Mariano tests, with a direct two-year-ahead experiment used as a robustness check. In the primary experiment, the LSTM records the lowest observed RMSE (45.254) and MAE (35.956), closely followed by the dynamic OLS benchmark in RMSE and XGBoost in MAE. At the two-year horizon, XGBoost records the lowest RMSE (45.537) and MAE (34.426). Most pairwise forecast-accuracy differences are not statistically significant at the 5% level, and the LSTM–XGBoost difference is not significant under either squared or absolute loss. Rolling-origin SHAP analysis identifies GDP as the largest source of incremental predictive information for XGBoost, followed by freight activity, while strong collinearity limits structural interpretation. Conditional sensitivity experiments further show that the fitted forecasting model should not be treated as a causal policy simulator. Overall, the findings demonstrate that temporal validation, conventional benchmarks, and robustness analysis are essential when evaluating complex forecasting models on short annual emissions series.

Sustainability doi: 10.3390/su182010444

Authors: Youcai Su Min Li Gui Yu Yue Zhang Jie Liu Jiazhen Sun Qunyi Huang Binghua Huang Qingyu Huang Yixiang Xiong

In the context of global climate mitigation and China’s “Dual Carbon” targets, accurately identifying emission drivers and forecasting long-term trajectories at the provincial level has become a critical research priority for designing sustainable transition pathways. This study investigates carbon emissions in Sichuan Province over the period 1997–2022 using an integrated analytical workflow that sequentially couples Pareto-based feature selection and robust partial least squares regression (PLSR) for explanatory driver identification, with recurrent neural network (RNN) modeling for independent trend projection. Pareto filtering is employed to isolate 34 high-impact variables that collectively explain 85% of total emissions. To address numerical instability in the explanatory phase, a log-transformed robust PLSR is implemented. Separately, to extrapolate near-term trajectories, a dynamically switched long short-term memory (LSTM) and gated recurrent unit (GRU) architecture is utilized under stability assumptions, operating within a data-driven framework with empirically calibrated physical constraints. This integrated modeling approach demonstrates strong explanatory performance (training R2 = 0.9237, cross-validation Q2 = 0.7241) and yields a mean absolute percentage error (MAPE) of 3.11–3.53% on a chronologically separated five-year validation period (2018–2022). This low error—achieved over a holdout interval encompassing the Double Carbon policy announcement and COVID-19 disruptions—provides preliminary evidence of the model’s capacity to capture the dominant inter-annual emission dynamics for short-horizon projection, despite the inherent constraint of limited annual observations (N = 26). Among the identified drivers, the utilization of by-product gases in heavy industry and gasoline consumption in urban transportation exhibit the strongest positive influence, with variable importance in projection (VIP) scores exceeding 1.5. Conversely, coal use in urban residential sectors exerts a modest negative effect on emission growth (elasticity = −0.023). Under empirically bounded stability assumptions, the constrained baseline projection suggests that total emissions may edge down to 259.84 Mt by 2027. However, this apparent trajectory, is strictly conditioned by the imposed year-to-year change limits. It must be interpreted as a restricted scenario outcome rather than an independent predictive discovery of an approaching carbon-peaking plateau. While the explanatory fit of the PLSR component does not mathematically validate the subsequent neural-network forecasts, this research offers a practical methodological reference for the application-specific integration of established statistical and deep-learning tools in regional emission diagnosis.

Sustainability doi: 10.3390/su182010441

Authors: Ruixiang Liu Bing Hu Peng Peng Bohong Fan

Heritage trees connect ecological functions with cultural meanings, but conservation research often treats these evaluations and people’s emotional relationships with heritage settings separately. This study develops an integrated appraisal model that distinguishes ecological value perception, cultural ecosystem service perception, place attachment, and sustainable conservation support. A cross-sectional survey of 500 adults in China with direct or mediated heritage-site familiarity was analyzed using latent-variable structural equation modeling. Heritage trees were understood broadly as older, large, notable, and traditional courtyard trees with ecological or cultural significance. Ecological recognition was positively associated with cultural-service appraisal, which in turn was associated with tree-related attachment appraisal and stated conservation support. Ecological and cultural appraisals also retained direct associations with support, indicating that attachment was not the sole link between perceived value and conservation endorsement. The positive path pattern persisted after excluding patterned responses and among respondents reporting direct visits. The study refines attachment-centered accounts by distinguishing cultural meaning appraisal from emotional connection and by specifying complementary routes to support. These findings inform the evaluation of heritage interpretation and participatory management that connect ecological protection with cultural continuity.

Sustainability doi: 10.3390/su182010443

Authors: Joanna Lizińska

The study aims to map the intellectual landscape of research on the relationship between sustainability engagement and earnings management (EM). The way a company communicates its reliability translates into stakeholder relations and influences performance. The study integrates corporate social responsibility (CSR) and environmental, social, and governance (ESG) concepts in a bibliometric analysis of 578 publications on the CSR/ESG–EM relationship (2006–2026). Co-citation, keyword co-occurrence, and thematic evolution analyses were conducted using Bibliometrix and VOSviewer. Since 2016, publication output has increased sharply, with over 60% of publications appearing within the last five years. The field is interdisciplinary, with widely dispersed authorship and publication venues. Research activity is concentrated in China, whereas the UK serves as a key hub for international collaboration. The field draws on three research traditions: mainstream accounting and finance, CSR and sustainability, and regulatory and institutional research. Rooted in accounting journals, the field now publishes mainly in sustainability journals. The thematic analysis reveals shifts from CSR to ESG and from accrual to real EM, with ESG becoming the motor theme and concerns moving towards the credibility of ESG information. Geographic and thematic gaps leave the research agenda open. The findings have implications for standard-setters, auditors and investors.

Sustainability doi: 10.3390/su182010440

Authors: Manuela T. Fernandez Verónica A. El Mujtar Fabio D. Trinco Sofía Hara Silvana López Andrea Cardozo Valeria E. Álvarez Pablo Tittonell

Living Labs (LLs) are often described as top-down, formally designed innovation spaces, and literature about LL research highlights scarce reports of LLs in Latin America. However, grassroots territorial-innovation spaces exist in Latin America, and we hypothesized that some of them probably agree with the LL framework. The Comarca Andina del Paralelo 42 (CAP42), located in north Patagonia, Argentina, has already seen the emergence of agroecology and organic farming in the 1960s. We considered the CAP42 as a case study for our research. We applied a multidisciplinary approach combining socio-cultural and environmental assessment at the landscape level. We revealed that interacting institutional and cultural factors have shaped the region into a site of agroecological co-innovation, and that agroecological innovation and knowledge co-creation have emerged as bottom-up, non-formalized, long-term process. The assessment of environmental indicators (forest cover loss, land use-related changes of soil properties, etc.) provided evidence for the sustainability of the CAP42 landscape. Forest cover loss observed in the last two decades (2000–2023) was mainly linked to fires rather than agricultural expansion or intensive livestock production. The CAP42 covers the three-layer network approach and place defined in the LL framework, as it is a real-world learning and innovation space enabling multi-actor co-development of context-specific solutions, through multiple forms of knowledge co-creation that align with current LL definitions. It also illustrates that sustainable, long-lasting LLs may result from historically constructed conditions, providing key insights for the development of future LLs.

Sustainability doi: 10.3390/su182010433

Authors: Jinfeng Zhang António Benjamim Mapossa Maryam Rasouli Yuxin Liu Uttandaraman Sundararaj

Urban water systems face acute disruptions, including drinking-water advisories and wildfire-related contamination, alongside chronic pressures from climate variability, ageing infrastructure, and limited institutional capacity. Decentralized treatment components may complement centralized infrastructure at point-of-use, point-of-entry, building, and district scales. Within these systems, compact adsorbent and catalytic modules could provide targeted polishing or emergency-treatment functions; however, many candidate materials are still evaluated as powders in batch tests. Three-dimensional (3D) printing can instead shape them into recoverable monoliths with tunable, interconnected flow channels. This review evaluates 3D-printed metal–organic framework (MOF), porous carbon, and MOF-derived carbon monoliths for resilient urban water treatment. We assess material selection, fabrication, and performance across four linked scales: active material, engineered monolith, treatment device, and urban water system. The evidence shows that additive manufacturing can improve material recovery, control macroscopic flow, expose active phases, and enable regenerable modules. Nevertheless, most studies remain laboratory-scale demonstrations based on model contaminants, batch operation, simplified matrices, or short cycling. Long-term continuous-flow performance, pressure drop, active-material release, transformation products, potable-water safety, device-specific life-cycle impacts, and field economics remain poorly characterized. Progress requires geometry-controlled comparisons, realistic-water breakthrough tests, service-relevant regeneration, leachables assessment, and accountable maintenance and end-of-life strategies. Resilience therefore depends on integrating material chemistry, hydraulic design, treatment-train compatibility, environmental performance, and equitable service delivery.

Sustainability doi: 10.3390/su182010439

Authors: Haowen Duan Xiangdong Liang Wenxue Zhang

Under the ‘new normal’ of economic growth, the platform economy has expanded rapidly, creating entrepreneurial and employment opportunities while exerting novel influences on the urban–rural income gap. Using balanced panel data from 288 Chinese prefecture-level cities (2010–2024), this paper treats the “National E-commerce Demonstration City” policy as an exogenous shock and applies a multi-period staggered difference-in-differences model. The results show that policy-induced platform economy development significantly widens the urban–rural income gap due to the digital divide, a conclusion robust to various checks. Mechanism analysis supports three channels: entrepreneurial activity, labor agglomeration, and digital infrastructure construction, all with net transmission effects. The widening effect is larger in cities with greater scale and lower digital inclusive finance levels, while the rural land transfer result is only preliminary. Further analysis indicates that a well-established institutional environment and high market potential can mitigate the widening effect. This paper provides empirical evidence and policy implications for regulating the platform economy to optimize income distribution and promote sustainable urban–rural integration.

Sustainability doi: 10.3390/su182010438

Authors: Junjie Zhang Chaowang Zou

Water infrastructure underpins progress toward Sustainable Development Goal 6 and SDG 9, yet financing shortfalls constrain investment in many developing economies. This paper examines whether market-oriented water allocation reform—specifically water rights trading (WRT)—can mobilize sustainable infrastructure financing. Exploiting China’s 2014 provincial WRT pilot as a quasi-natural experiment, we estimate difference-in-differences models using province-level panel data from 2010 to 2023 (an effective sample of 434 province–year observations across 31 provinces), supplemented by event-study analysis, mediation modeling, and heterogeneity tests. WRT raises per capita water infrastructure investment by approximately 18.3% (p < 0.01), with effects materializing gradually over three to four years and persisting thereafter. Three channels mediate the relationship: water resource value realization (average causal mediation effect, ACME = 0.062), financing cost reduction (ACME = 0.048), and marketization-driven investment incentives (ACME = 0.071). Treatment effects are more pronounced in water-scarce provinces and regions with stronger market institutions. These findings indicate that water market reform can unlock sustainable infrastructure financing, particularly when complemented by pricing reform, financial market development, and regionally tailored implementation.

Sustainability doi: 10.3390/su182010436

Authors: Marta Aleksandrowicz-Trzcińska Szymon Bijak Jolanta Behnke-Borowczyk Michał Zasada Wojciech Kwasowski Karol Bronisz

Natural regeneration of forests on abandoned agricultural land represents a cost-effective and sustainable pathway for restoring ecosystem functions and enhancing biodiversity. Root-associated fungi can influence the success of forest regeneration, especially under harsh habitat conditions, and serve as indicators of ecosystem maturation. Therefore, this study analyzed root-associated fungal communities in four silver birch stands regenerated by self-sowing on post-agricultural land. Stand ages were 13–14, 14–19, 18–23, and 23–28 years. Community analysis was based on sequencing of the ITS1 region using the AVITI (Element Biosciences), and soil C, N, and C:N ratios were determined. Taxa richness differed among stands, both for exclusive taxa (4–28) and total taxa per stand (49–84), with higher richness ecorded in the older stands. Trophic structure and α-diversity remained stable across stands. Ordination revealed a distinct clustering of root-associated fungal communities among the four studied stands. Late-stage ectomycorrhizal taxa dominated the older sites, whereas soil chemistry showed no clear association with community structure. Differences in fungal community assembly were likely driven by inoculum availability, local microsite conditions, and stochastic processes. These findings indicate that fungal succession during passive forest restoration on post-agricultural land is characterized primarily by progressive turnover in community composition rather than increasing diversity, with stand development and local factors jointly shaping fungal community assembly.

Sustainability doi: 10.3390/su182010437

Authors: Raphael I. Areola Abayomi A. Adebiyi

In grid-connected PV-ESS plants, battery degradation is often treated as an external correction rather than a quantity coupled directly to sizing and dispatch decisions. This study develops a constraint-aware NSGA-II framework in which cycle- and calendar-induced capacity fade are evaluated from the simulated state-of-charge trajectory at every fitness evaluation and optimized jointly with net present cost (NPC), expected energy not served (EENS), and curtailment. The key innovation is in the explicit coupling of four-objective degradation and optimization, along with identifying an intermediate lifecycle-cost operating region, rather than assuming that minimum degradation is always the most economical choice. The framework runs in MATLAB/Simulink R2023b. Degradation performance is assessed against laboratory data and compared with 18 months of battery management system data from Nigeria’s Olorunsogo site; cases in South Africa and India are simulated and serve as transferability tests rather than field validations. In the pooled NMC simulation results, a descriptive cost fit has an interior minimum near 2% per year; the selected regional solutions range from 2.2% to 2.8% per year. Relative to an aggressive 4% per year cycling baseline, the model estimates approximately 11% lower 20-year lifecycle cost in this intermediate operating region and with later battery replacement. While the exact optimal point varies with chemistry and assumptions, sensitivity analysis indicates that an intermediate, moderate degradation rate stays economically advantageous within the tested uncertainty ranges. In practice, this framework helps designers balance initial battery size and cycling frequency against replacement risk, rather than choosing systems based only on immediate cost.

Sustainability doi: 10.3390/su182010435

Authors: Grzegorz S. Jodłowski Marta Wójcik

Climate change shifts governments’ focus to introducing policies that decrease the impacts of GHGs (among other emissions) generated by the energy production industry. Biomass is regarded as a net-zero emission source of renewable chemical energy, but analyses show that this is not true at the national scale. The purpose of this study is to determine the scale at which fossil fuels can be replaced with biomass in Poland. Different scenarios of biomass usage were analyzed—theoretical resources, technical possibilities, and sustainable bioresource management. Scenarios regarding the increase in energy demand alongside biomass CO2 coverage up to 2050 were also forecasted. An inventory of biomass resources in five categories suitable for energy use in the Polish commercial power industry revealed a fuel shortage of approximately 20% with respect to meeting the total current demand (2025), with critical shortages of up to 60% by 2050. Further analysis revealed the impossibility of balancing the carbon dioxide produced during biomass combustion for energy production. At current energy production levels, the theoretical potential is sufficient, but when technical feasibility is considered, the imbalance reaches 20% and, with sustainable resource management, even 30%. By 2050, 50% and 60% of the shortages at the technical and sustainability levels, respectively, will occur in the CO2 exchange system.

Sustainability doi: 10.3390/su182010434

Authors: Yamil Liscano Jhony Diaz Vallejo Jamil Cedillo-Balcázar Mario J. Valladares-Garrido

Traditional flood risk assessment of health infrastructure focuses primarily on direct structural building damage, frequently overlooking the logistical functional isolation caused by road network disruption. This study aimed to quantify the spatial distribution of physical–social vulnerability and functional isolation across licensed healthcare facilities in Santiago de Cali, Colombia, evaluating whether flood risk exposure associates with institutional care complexity. A geospatial multicriteria decision analysis based on the Analytic Hierarchy Process integrated water hazard, area-level social vulnerability, and road isolation into a synthetic risk index for 863 licensed provider institutions. The association between complexity level (I, II, III) and risk category (1 to 5) was evaluated using the Monte Carlo χ2 test of independence, Cramér’s V, and the adjusted Pearson residuals. Systemic accessibility resilience was modeled via a network-based travel time degradation analysis. No statistically significant association was observed between institutional complexity level and flood risk category (χ2 = 12.69, df = 8, p = 0.122; Cramér’s V = 0.086). Public facilities exhibited a higher descriptive exposure share in high-risk categories (45.5%) compared to private facilities (4.3%). Functional isolation affected facilities across all complexity tiers, with severe travel time increases to advanced care concentrated in specific peripheral hotspots (comuna 22: +210.6%, comuna 1: +189.1%, comuna 20: +155.5%), whereas 82% of the urban population experienced negligible transit delays. Flood exposure across the municipal healthcare grid appears to be driven by pre-existing urban socioeconomic and topographic gradients rather than deliberate risk-sensitive institutional siting. These empirical insights highlight the value of incorporating network accessibility into resilient, equity-oriented urban health planning aligned with Sustainable Development Goals 3, 10, 11, and 13.

Sustainability doi: 10.3390/su182010429

Authors: Jiaotao Xu Xiangling Li Shizhong Zhang Tieliang An Gangwei Fan Zihan Kong Shaodong Li Ziquan Wu

With the gradual depletion of high-quality and readily mineable coal resources, recovering coal beneath buildings while controlling surface subsidence is important for sustainable resource development and protection of surface structures. Using the 11205 working face of Taitou Coal Mine as a case study, a three-roadway continuous mining and backfilling scheme combined with compact backfilling by grout injection into bags was proposed, and Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D) simulations were performed to evaluate the effects of branch-roadway width and backfilling ratio. At a 97% backfilling ratio, increasing branch-roadway width from 4 to 6 m increased maximum roof subsidence from 40.41 to 65.21 mm, maximum horizontal displacement from 1.220 to 2.174 mm, and the stress concentration factor from 2.62 to 2.96. At a 5 m width, increasing the backfilling ratio from 83% to 89% reduced maximum roof subsidence by 14.4%, whereas increasing it from 90% to 97% reduced subsidence by only 0.35 mm, indicating a pronounced diminishing-return response with markedly reduced sensitivity around 89–90%. Considering both subsidence control and construction efficiency, a branch-roadway width of 5 m and a backfilling ratio of 95% were selected. Field monitoring showed maximum strike and dip subsidence of 16.60 and 17.93 mm within 30 days. These results provide a reference for subsidence-controlled coal recovery beneath buildings under similar conditions.

Sustainability doi: 10.3390/su182010430

Authors: Burak Belli Turgay Kerem Koramaz

Urban digital transformation is commonly framed as a function of information and communication technology (ICT) provision, treating the socio-spatial conditions that shape technology uptake as background. Empirical work is correspondingly spatially blind and aggregates distinct dimensions of digital availability into composite indices that assume shared determinants. This study addresses both gaps in Istanbul, a developing-country megacity whose districts differ sixfold in household income. Thirty-one indicators for all 39 districts are reduced by principal component analysis to four ICT dimensions and three socio-spatial conditions, keeping conditions proportionate to cases. No condition proves necessary, so fuzzy-set Qualitative Comparative Analysis identifies the configurations sufficient for each dimension and for its absence. The dimensions share no common configuration: digital entrepreneurship follows socio-economic status alone (coverage 0.855, consistency 0.849); public Wi-Fi provision relative to fixed broadband follows economic activity in ageing districts (0.548, 0.844); mobile access with digital-learning provision follows economic activity in young or low-status districts (0.629, 0.821); and digital skills (0.777, 0.714) arise both from socio-economic status and, independently of it, from economic activity. Because the same condition accompanies different outcomes depending on the socio-spatial structure it meets, policy must be matched to the configuration of the district it addresses rather than applied city-wide.

Sustainability doi: 10.3390/su182010432

Authors: Jianfa Qiu Ruiyu Wang Ying Bao Yunye Cao

The sustainable renewal of existing university student dormitories requires effective identification of occupant-perceived improvement needs to support targeted interventions and efficient resource allocation. This study develops a renewal need prioritization framework by integrating explainable machine learning and impact-asymmetry analysis (IAA). Based on 1507 valid questionnaires from 10 campuses of seven universities in Guangdong Province, an XGBoost-SHAP model was used to identify key environmental attributes influencing overall satisfaction, followed by IAA to examine their asymmetric effects. The results show that: (1) 17 key attributes were identified from 42 indicators, of which 15 met the criteria for IAA classification and exhibited distinct asymmetric effects; (2) a five-level renewal need prioritization framework was established, with per capita usable area, bathroom type, storage space, study and discussion space, damp and mold prevention, and sound insulation identified as core renewal needs; and (3) improving residential unit comfort through spatial optimization, furniture configuration, and environmental enhancement is an important pathway for enhancing occupant well-being and the long-term adaptability of existing dormitory buildings. This study provides empirical evidence for prioritizing existing dormitory renewal and allocating limited resources more efficiently, contributing to the sustainability of existing university residential environments.

Sustainability doi: 10.3390/su182010425

Authors: Songlin Zhang Libo Zhao Yuxi Liu

Although green finance policies are widely recognized as important instruments for promoting city green growth, how they reshape the behavioral responses of economic actors remains insufficiently understood. This study examines green innovation and entrepreneurship within a common analytical framework, with the former representing a technological response and the latter a market-entry response. Drawing on a panel of 282 Chinese prefecture-level cities over 2011–2022, this study exploits the implementation of the Pilot Zone for Green Finance Reform and Innovation (PZGFRI) policy as a quasi-natural experiment and estimates its effect on green total factor productivity using a difference-in-differences design. The baseline estimate is 0.168, implying an effect equivalent to about 15.7% of the sample mean of GTFP, and this result is broadly comparable across robustness checks. The mechanism analyses further show positive policy effects on green innovation and entrepreneurial entry, with both lagged measures positively associated with subsequent city GTFP. Heterogeneity analyses suggest that policy effects are more pronounced in peripheral cities, cities with lower government efficiency, and those with lower pollution pressure. The results imply that green finance should be more precisely targeted, stimulate both technological and market-entry responses, and be adapted to local development conditions. These insights may also be relevant to developing economies seeking to turn policy-based financial support into sustained green growth.

Sustainability doi: 10.3390/su182010431

Authors: Tamara Hladik Louis Moustakas

This study researched how alpinists perceive the changes climate change is bringing to the Austrian Alps and how they are adapting their behaviour. Data were collected through an online questionnaire, resulting in 199 responses included in the analysis. Based on substitution behaviour theories, results showed that informational coping strategies are favoured most, followed by temporal and spatial substitution, while activity substitution ranked last. Through three multiple regression analyses, correlations between perceived impacts and resulting behaviour shifts were analysed. The results indicate that respondents adapt their behaviour when they perceive actual constraints, such as routes deteriorating or becoming too difficult because of the impacts of climate change. Similarly, perceived increases in risk relate to behaviour shifts. Acceptance of climate change showed no significant association with behaviour change in this sample, though this result should be interpreted cautiously given that 98.5% of respondents already accepted climate change as real, leaving minimal variance for the predictor to explain. Interestingly, perceived changes in rockfalls were not significantly related to behaviour shifts and, in relation to activity substitution, even had a negative effect. The results partially confirm findings from previous studies, yet the unexpected negative effect of perceived changes in rockfall events contradicts current research. More investigation is needed to understand how alpinists perceive rockfall events and associated risks in the Austrian Alps. Resulting practical implications suggest that alpinists need to be made aware of the current state of routes and any prevailing risks. Awareness of these actual constraints appears to relate to alpinists reconsidering whether they are planning their trips safely and to adjust their plans if necessary.

Sustainability doi: 10.3390/su182010428

Authors: Marouane Lamzirai Hicham Boudounit Ilias Serifi Houssine Khalili Achraf Nour-Eddine Hicham Mastouri

Heterogeneous simulation archives can contain traceable numerical outputs that do not support the physical or comparative claims attached to them. This study presents a retrospective, author-applied case study of claim admissibility in one prototype-scale photovoltaic (PV), concentrated solar power (CSP), geothermal and waste heat recovery archive. A procedural checklist separates four evidence classes from five gates addressing traceability, numerical credibility, physical closure, commensurability and downstream assessment inputs. Intended claims are registered before the present scoring, and any narrower permitted statement is recorded separately. The audit identifies byte-identical mesh inspection files under different model filenames and unresolved discrepancies between saved solver states and scenario exports. PV DC exports of 33.31–65.44 W and CSP heat transfer exports of 2.333–6.421 kW remain reportable as archived values. The CSP launcher inputs imply a Reynolds number of approximately 141; unresolved receiver geometry, boundary mapping and inlet-state evidence prevent a demonstrated energy balance. Pressure–flow quantities remain as diagnostics because the thermal-to-electric chain is unclosed. Within-scenario PV voltage–temperature relations reproduce an archived correction rather than independently validate electrical performance. The numerical models themselves have not been validated, and this study does not establish predictive accuracy. The contributions are a documented procedure and its application to this archive, not a new uncertainty theory. Independent scoring reliability, cross-dataset generalizability and an empirical all-gates-pass case remain untested.

Sustainability doi: 10.3390/su182010426

Authors: María Angélica Sastoque Forero María del Pilar Espitia Botia Nidia Stella Robles Mejia

Community Action Boards constitute fundamental grassroots organizations for democratic participation and infrastructure development across Colombian territories. Nevertheless, these organizations face substantial structural constraints in the formulation, management, and long-term sustainability of projects arising from collective community initiatives. This study analyzes project-management capacities, knowledge-transfer practices, and capacity-building needs in the Central Province of Boyacá, Colombia, and uses this diagnosis to inform context-specific knowledge-transfer strategies for sustainable community project management. The study involved semi-structured interviews with 15 Community Action Board presidents and structured surveys administered to 50 community leaders and active members. The findings reveal significant gaps in formal training, methodological knowledge, and institutional coordination, while existing knowledge is acquired predominantly through informal exchanges of experience. Based on these findings, the study developed a context-specific knowledge-transfer framework comprising three interconnected components—practice-based capacity development, systematization of community knowledge, and interinstitutional coordination—together with a six-module training program and a methodological handbook for sustainable project formulation and management. Conceptually, the framework integrates knowledge conversion, organizational learning, capacity building, social capital, and sustainability within the community project-management context. Practically, the proposed training and methodological resources translate identified capacity gaps into structured guidance for project formulation, resource management, sustainability, and institutional coordination. These outputs constitute context-specific proposals for subsequent stakeholder validation, implementation, and evaluation rather than evidence of demonstrated effectiveness. Participants also highlighted the importance of retaining organizational knowledge during leadership transitions.

Sustainability doi: 10.3390/su182010427

Authors: Patrick Ofori-Oppong

The study assesses the role that financial inclusion plays in the relationship between green finance and inclusive growth. Drawing on institutional and financial intermediation theories, the study investigates panel data from 35 African countries over the period 2000–2023 employing a fixed effect and two-step System Generalised Method of Moments estimator. Green finance was measured using renewable energy investment flows reported by IRENA, expressed in US dollars, as a proxy for the financial resources mobilised toward environmentally sustainable projects. Financial availability, financial accessibility and financial usage are the three indicators used to measure financial inclusion. Inclusive growth was measured using a multidimensional composite index capturing economic performance, equity, and social development dimensions. The results reveal that green finance increases financial inclusion. Green finance and inclusive growth are inversely related. There is no significant evidence to prove that financial inclusion moderates the relationship between green finance and inclusive growth. The contribution from the study shows that green finance promotes financial inclusion but does not automatically guarantee inclusive growth. The study departs from the predominantly linear treatment of green finance in the African literature by showing that financial deepening and inclusive development are not necessarily complementary outcomes of green investment. It is, therefore, imperative for policymakers to deliberately design green finance with redistribution and institutional safeguards in mind to ensure that inclusion leads to broad-based development.

Sustainability doi: 10.3390/su182010424

Authors: Teresa Abramowicz-Gerigk Miroslaw K. Gerigk

This study presents solutions utilizing varying degrees of autonomy in seaport operational systems, including port infrastructure, environmental monitoring systems and autonomous equipment for transshipment terminals. The applications currently used in the most developed seaports are analyzed in terms of their preparation for servicing MASSs (Maritime Autonomous Surface Ships). In the context of safety in a mixed-navigation environment, the importance of the currently fastest-developing drone technologies is assessed. Drone technologies based on unmanned vehicles, in various configurations, supervised by remote operations centers, are mainly used for surveillance and monitoring port areas. The technology still under development is the UWV (Unmanned WIG Vehicle), using the WIG (wing in the ground) effect to enable fast and efficient movement over the sea surface. The analysis of the strengths and limitations of this technology allowed the most important directions for its further evolution to be determined. Based on the analysis of the existing UWV solutions, the key design and operational drivers are highlighted, and a new UWV application, which cooperates with the Autonomous Underwater Vehicle platform designed for effective observation, supervision and monitoring of subsurface infrastructure, is proposed.

Sustainability doi: 10.3390/su182010422

Authors: Bedaso Taye Zewdu Abro Aseffa Seyoum Admasu Tsegaye Workneh Ayalew Menale Kassie

Pollination services are vital to agricultural productivity. Despite the growing importance of pollinators, there is limited evidence on farmers’ awareness and willingness to pay (WTP) for such services. This study assesses farmers’ awareness and WTP for managed pollination services and their determinants using data from 2811 households in Ethiopia. Using a structured household survey and the contingent valuation method, we elicited binary and continuous WTP responses for managed pollination services. We employed binary models to analyze factors influencing WTP and the amount farmers are willing to pay. The results show that 62% are willing to pay for managed pollination services, with an average of ETB 476 per hectare per year. Knowledge and awareness of honeybees’ role in crop productivity significantly increases both the likelihood and amount of their WTP. WTP tends to be higher for younger farmers, beekeepers, and those who received training in beekeeping. Farmers with bee colonies nearby, who know other pollinators or are in high vegetation cover areas, tend to offer lower amounts. Regional variation is also significant, with higher WTP in coffee-producing districts. The study highlights a substantial demand for managed pollination services. These findings underline the importance of tailored extension services, targeted training, and region-specific pricing strategies to scale up managed pollination services as part of sustainable agricultural development in Ethiopia.

Sustainability doi: 10.3390/su182010423

Authors: Subhodeep Dasgupta Igor A. Mayburov

This study examines the relative implementation efficiency under a specified input–output framework and documented sustainability outcomes of New Development Bank (NDB)-financed infrastructure projects in India, China, and South Africa. Data Envelopment Analysis (DEA) is applied to 24 projects using loan amount and planned project duration as inputs and completion status and disbursement rate as outputs. An input-oriented Variable Returns to Scale (VRS) model is employed as the primary specification, complemented by Constant Returns to Scale (CRS) and scale-efficiency estimates. The results indicate substantial variation in relative implementation efficiency, with mean VRS efficiency of 0.631 and only three projects reaching the efficiency frontier. Mean scale efficiency is 0.882, with 17 of 24 projects exhibiting full scale efficiency. Sustainability evidence was available for 20 projects and was organized using a Sustainable Infrastructure Outcome Matrix (SIOM), which records project-specific environmental, social, and economic/development outcomes without aggregating heterogeneous indicators into a single sustainability index. Comparison of the efficiency and sustainability profiles indicates that implementation efficiency and documented sustainability outcomes do not necessarily coincide. Supplementary analysis further shows that financial disbursement represents a distinct dimension of project performance. The findings support a multidimensional approach to evaluating NDB infrastructure projects in which implementation efficiency, financial execution, and project-specific sustainability outcomes are assessed separately but considered together.