Sustainability

21 pages, 1273 KB

Open AccessArticle

An Extended EWMA Control Chart with Multiple Dependent State Sampling for COM–Poisson Processes and Its Application to Air Quality Index Monitoring Data

by Shin-Li Lu, Su-Fen Yang, Jen-Hsiang Chen and Sheng-Jing Wu

Sustainability 2026, 18(15), 7733; https://doi.org/10.3390/su18157733 - 30 Jul 2026

Abstract

Traditional attribute control charts for defect counts are commonly developed under the assumption that count data follow a homogeneous Poisson distribution. However, this assumption is often violated in practical applications. To overcome this limitation, a two-parameter Poisson distribution, the Conway–Maxwell–Poisson (CMP or COM–Poisson) [...] Read more.

Traditional attribute control charts for defect counts are commonly developed under the assumption that count data follow a homogeneous Poisson distribution. However, this assumption is often violated in practical applications. To overcome this limitation, a two-parameter Poisson distribution, the Conway–Maxwell–Poisson (CMP or COM–Poisson) distribution, has been widely used to construct control charts capable of effectively monitoring count data exhibiting over- or under-dispersion. Furthermore, the multiple dependent state (MDS) sampling scheme evaluates the current process status not only based on the present sample but also by incorporating information from previous samples, thereby achieving higher detection efficiency than single sampling schemes. This study integrates the COM–Poisson distribution with the MDS sampling strategy to develop an attribute control chart based on the extended exponentially weighted moving average statistic. The average run length is obtained under various shift magnitudes using probability-based computations. The simulation results demonstrate that the proposed chart substantially outperforms existing approaches in the prompt detection of out-of-control conditions. A real-world air quality index (AQI) monitoring study showed that the proposed chart effectively detected increases in weekly AQI counts and provided earlier warnings of potential air quality deterioration. Full article

(This article belongs to the Special Issue Sustainable Industrial Engineering and Quality Management)

28 pages, 672 KB

Open AccessArticle

From Sustainability to Symbiosis: Lifestyles as Laboratories of the Symbiocene

by Rita Lankauskienė and Giedrė Rulevienė

Sustainability 2026, 18(15), 7732; https://doi.org/10.3390/su18157732 - 30 Jul 2026

Abstract

Off-grid and low-impact lifestyles have emerged as important sites of socio-ecological experimentation that challenge conventional understandings of sustainability. This study examines the initiative ‘Portugal It Is’, a Lithuanian diaspora homestead in rural Portugal, as a qualitative case through which to explore the relevance [...] Read more.

Off-grid and low-impact lifestyles have emerged as important sites of socio-ecological experimentation that challenge conventional understandings of sustainability. This study examines the initiative ‘Portugal It Is’, a Lithuanian diaspora homestead in rural Portugal, as a qualitative case through which to explore the relevance of such lifestyles to the emerging concept of the Symbiocene. Using an abductive case study approach informed by the Biomimetic–Organizational Ecology framework, the research draws on a longitudinal analysis of publicly available video narratives, supplemented by field observations and informal research conversations. The findings indicate that the transition to off-grid living involved processes of adaptive learning, ecological stewardship, livelihood diversification, and the development of new relationships with local communities, digital networks, and ecological systems. Rather than achieving complete self-sufficiency, the initiative evolved through forms of socio-ecological interdependence and relational value creation. The study develops and empirically illustrates the concept of symbiotic livelihoods to describe livelihood arrangements that integrate environmental care, adaptive learning, and community engagement. The findings suggest that off-grid initiatives can function as experimental niches in which alternative human-nature-economy relationships are developed and refined. The paper contributes to sustainability transitions literature by advancing a regenerative and co-evolutionary perspective on emerging socio-ecological futures. Full article

(This article belongs to the Special Issue Innovation for Sustainability, Circular Economy, System Transitions and Societal Transformations)

18 pages, 6652 KB

Open AccessArticle

Trusted Information Sources and Preferred Delivery Methods for Soil Indicator Information Among Farmers, Advisors, and Researchers

by Alison Ollerenshaw, Nathan Robinson and Aakansha Chadha

Sustainability 2026, 18(15), 7731; https://doi.org/10.3390/su18157731 - 30 Jul 2026

Abstract

Extensive industry efforts have led to the delivery of information supporting farmer production practices, including soil management. Education and extension activities are vital, with wide-ranging information sources being delivered to inform decisions around sustainable food production practices. Despite this, there remain knowledge gaps [...] Read more.

Extensive industry efforts have led to the delivery of information supporting farmer production practices, including soil management. Education and extension activities are vital, with wide-ranging information sources being delivered to inform decisions around sustainable food production practices. Despite this, there remain knowledge gaps about actual and preferred delivery of soil indicator information for Australian farmers and supportive stakeholders, including advisors and researchers. This research explored the current and preferred sources for delivering information about soil indicators for farmers and industry stakeholders across different farming enterprises (cattle, grains, and sheep). Data were collected using a 20-item survey. Survey responses (N = 265) were received from farmers (n = 156), advisors (n = 72), and researchers (n = 37) to understand how they currently receive soil indicator information, what sources they prefer for receiving this information, and the relationships between sources of soil indicator information to support farming practices. The findings indicate that farmers receive soil information from many sources but prefer to receive it from industry advisors—including researchers; farmer, grower, and producer groups; agronomists; and consultants—and at industry events such as field days, farm walks, and tours, as well as via education and training. The findings demonstrate that information about soil health for farmers must be delivered by trusted individuals and organisations in ways that farmers will find, understand, access, and use. This includes prioritising information delivery through stakeholder engagement and connections, to foster personalised information exchange. In contrast, no preferred information sources were identified for advisors and researchers. While online sources of information delivery are increasing in the digital age, this study did not identify any strong associations between farmers and these approaches. This study highlights the pivotal role that trusted industry intermediaries have in delivering information about soil indicators. This identifies a priority for future support that is directed towards industry advisors and researchers to optimise their delivery of soil health information to farmers. Full article

(This article belongs to the Section Sustainable Agriculture)

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15 pages, 340 KB

Open AccessArticle

Energy Use Efficiency and Greenhouse Gas Emissions in Industrial Hemp (Cannabis sativa L.) Production Under Semi-Arid Central Anatolian Conditions

by Osman Özbek, Sadiye Ayşe Çelik, Tanzer Eryılmaz, Ergün Çıtıl, Zeki Bayramoğlu, Nicoleta Ungureanu and Nicolae-Valentin Vlăduț

Sustainability 2026, 18(15), 7730; https://doi.org/10.3390/su18157730 - 30 Jul 2026

Abstract

The objective of this study was to determine the energy balance and greenhouse gas (GHG) emissions associated with the production of industrial hemp (Cannabis sativa L.) under semi-arid Central Anatolian conditions. A field experiment was conducted using the registered industrial hemp cultivar [...] Read more.

The objective of this study was to determine the energy balance and greenhouse gas (GHG) emissions associated with the production of industrial hemp (Cannabis sativa L.) under semi-arid Central Anatolian conditions. A field experiment was conducted using the registered industrial hemp cultivar ‘Vezir’ under semi-arid conditions, and energy use indicators and greenhouse gas emissions were quantified through an input–output analysis based on field-level agricultural inputs and biomass yield. The total energy input was calculated as 13,688.50 MJ ha^–1, of which chemical fertilizers (54.339%) and diesel fuel (32.09%) jointly accounted for more than 90%, followed by irrigation water (4.66%), machinery 2.87%), and human labor (0.21%). The corresponding energy output reached 388,073.80 MJ ha^–1, yielding an energy use efficiency of 28.35, a specific energy of 0.62 MJ kg^–1, an energy productivity of 1.61 kg MJ^–1 and a net energy of 374,385.28 MJ ha^–1. Of the total energy input, 36.95% was direct and 63.05% indirect, while 89.35% originated from non-renewable sources and only 10.65% originated from renewable sources. Total GHG emissions amounted to 590.14 kg CO₂ eq ha^–1, with diesel fuel and nitrogen fertilizer identified as the dominant emission sources. These findings indicate that industrial hemp combines high productivity with low environmental burdens under semi-arid conditions. Beyond its favorable energy balance, hemp offers potential contributions to climate-smart agriculture through efficient resource use, reduced greenhouse gas emissions per unit of output, and diversification of cropping systems in water-limited environments. Therefore, industrial hemp can support the transition toward more sustainable and resilient agricultural systems in semi-arid regions of Türkiye and similar agroecological zones. Full article

(This article belongs to the Topic Greenhouse Gas Emission Reductions and Carbon Sequestration in Agriculture)

23 pages, 960 KB

Open AccessArticle

Sustainability-Oriented Management of Invasive Alien Species Risk in Infrastructure Projects with Significant Environmental Impact: A Case Study from Poland

by Paweł Nicia, Paweł Zadrożny, Mariusz Dacko, Tomasz Wojewodzic, Romualda Bejger and Piotr Parzych

Sustainability 2026, 18(15), 7729; https://doi.org/10.3390/su18157729 - 30 Jul 2026

Abstract

Invasive alien species (IAS) are an important but insufficiently integrated risk in sustainable infrastructure development, particularly in projects involving earthworks, soil movement, habitat disturbance and prolonged construction. Their spread may cause biodiversity loss, ecosystem degradation, higher maintenance costs, project delays and long-term deterioration [...] Read more.

Invasive alien species (IAS) are an important but insufficiently integrated risk in sustainable infrastructure development, particularly in projects involving earthworks, soil movement, habitat disturbance and prolonged construction. Their spread may cause biodiversity loss, ecosystem degradation, higher maintenance costs, project delays and long-term deterioration of land-use sustainability. This study identifies critical stages of infrastructure project implementation associated with elevated IAS risk and proposes management measures supporting prevention, early detection, rapid response and post-intervention monitoring. The research used a comparative multiple-case study of three large infrastructure projects in Poland implemented under FIDIC conditions: flood embankment reconstruction, railway line modernisation and express road construction. A Before–After approach combined analysis of pre-construction environmental documentation, baseline ecological inventories, field verification after IAS detection, control measures and monitoring outcomes. Japanese knotweed (Reynoutria japonica Houtt.) was analysed as a model species because of its high regeneration potential and relevance to soil management. The analysed cases indicate that elevated IAS risk may occur during site preparation, earthworks, topsoil stripping and storage, soil reuse, finishing, landscaping and utility relocation. The study proposes a practical IAS risk classification framework to support risk identification, preventive action and monitoring intensity with the potential to support sustainability performance and reduce ecological and economic impacts. Full article

(This article belongs to the Section Sustainability, Biodiversity and Conservation)

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36 pages, 7992 KB

Open AccessArticle

Production-Dependent Effects of Agricultural Mechanization on Rural Income: Evidence from China

by Chenyang Wei, Junwen Zheng and Xiaodong Liu

Sustainability 2026, 18(15), 7728; https://doi.org/10.3390/su18157728 - 30 Jul 2026

Abstract

This study examines whether agricultural mechanization promotes rural income growth in China. Using provincial panel data from 2000–2023, a two-way fixed effects model and a Spatial Durbin Model (SDM) are employed to estimate the direct, conditional, and spatial effects of mechanization. The results [...] Read more.

This study examines whether agricultural mechanization promotes rural income growth in China. Using provincial panel data from 2000–2023, a two-way fixed effects model and a Spatial Durbin Model (SDM) are employed to estimate the direct, conditional, and spatial effects of mechanization. The results show that the positive association between mechanization and rural income becomes statistically insignificant after controlling for agricultural production, while agricultural production remains significantly associated with rural income. Mechanization exhibits diminishing returns as production levels increase and appears to be more effective in grain-oriented agricultural systems. Spatial analysis further reveals that agricultural production generates significant spillover effects, whereas mechanization itself does not. This study contributes to the literature by distinguishing the income effect of mechanization from its production-related and spatial effects. The findings suggest that policies should focus on strengthening production capacity, improving agricultural service systems, and better aligning mechanization investment with regional production structures. Full article

(This article belongs to the Section Sustainable Agriculture)

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37 pages, 1427 KB

Open AccessReview

Embankments for Transportation Infrastructure as a Pathway for Valorisation of Incineration Bottom Ash and Mine Tailings

by Jandira N. Domingos, Beatriz S. Bandarra, Margarida J. Quina and Paulo A. L. F. Coelho

Sustainability 2026, 18(15), 7727; https://doi.org/10.3390/su18157727 - 30 Jul 2026

Abstract

The growing demand for granular materials in transportation infrastructure increases the extraction of natural aggregates and the environmental impacts of the construction sector. At the same time, large volumes of municipal solid waste incineration bottom ash (IBA) and mine tailings (MTs) are generated [...] Read more.

The growing demand for granular materials in transportation infrastructure increases the extraction of natural aggregates and the environmental impacts of the construction sector. At the same time, large volumes of municipal solid waste incineration bottom ash (IBA) and mine tailings (MTs) are generated and stored, posing environmental and geotechnical challenges. This review critically evaluates the potential of these waste streams as alternative materials for transportation infrastructure embankments, including zoned embankment approaches, that may enhance sustainability. The analysis integrates evidence on physical, geotechnical, and environmental performance, including compaction, compressibility, shear strength, permeability, bearing capacity, chemical composition, leaching, and ecotoxicity. IBA generally exhibits favourable engineering properties, although its performance depends on ageing and pre-treatment. MTs show greater variability, with behaviour largely controlled by mineralogy, particle-size distribution, and contaminant mobilisation potential. Environmental assessment should consider total chemical composition alongside leaching behaviour, ecotoxicity, and exposure conditions. Overall, the safe use of IBA and MTs requires an integrated evaluation of geotechnical and environmental performance, enabling their selective placement within functional embankment zones. Such approaches can support circular resource use and more sustainable transportation infrastructure without compromising technical performance. Full article

(This article belongs to the Special Issue Circular Economy in Construction: Innovations, Challenges, and Sustainable Practices)

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26 pages, 4934 KB

Open AccessArticle

Decoupling Economic Growth from CO₂ Emissions in Honduras: A Longitudinal Machine-Learning and Econometric Assessment of Low-Carbon Development, 1990–2023

by Dely Ramirez, Jonathan Muñoz Tabora and Ozy D. Melgar-Dominguez

Sustainability 2026, 18(15), 7726; https://doi.org/10.3390/su18157726 - 30 Jul 2026

Abstract

Decoupling economic growth from CO₂ emissions is a key challenge for developing economies, with limited evidence for small Central American economies. This study evaluates Honduras during 1990–2023 using GDP per capita, CO₂ emissions per capita, energy intensity, and renewable energy share [...] Read more.

Decoupling economic growth from CO₂ emissions is a key challenge for developing economies, with limited evidence for small Central American economies. This study evaluates Honduras during 1990–2023 using GDP per capita, CO₂ emissions per capita, energy intensity, and renewable energy share from World Bank Indicators and the Global Carbon Project. The methodology integrates k-means clustering, PELT structural break detection, the Tapio decoupling index, Environmental Kuznets Curve (EKC) modelling, Granger causality, and Random Forest analysis. Since energy-intensity data are available only from 2000, a full GDP-CO₂ series (1990–2023, n = 34) is distinguished from a complete four-variable panel (2000–2021, n = 22). Clustering identifies two structural regimes rather than three (silhouette 0.490 vs. 0.476). EKC results support an inverted-U relationship (β₂ = −3.012, p < 0.001; adjusted R² = 0.766), with an estimated turning point of USD 2388 (95% CI: USD 2156–2644, delta method), near the upper boundary of the estimation sample, which Honduras’ 2023 GDP per capita (USD 2527) marginally exceeds as an out-of-sample extrapolation. However, Granger tests find no significant temporal precedence between GDP, renewable share, and CO₂ emissions (all p > 0.05), and Random Forest shows GDP per capita (%IncMSE = 31.47) vastly outweighs renewable share (%IncMSE = 0.16). Honduras has likely crossed the EKC threshold, but evidence does not support a renewable-driven decoupling. Full article

(This article belongs to the Special Issue Low-Carbon Development and Transition Paths: Emissions, Controls and Drivers)

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19 pages, 3575 KB

Open AccessArticle

Sustainability Assessment of Slurry Application Through Soil Carbon and Nitrogen Dynamics

by Cristina Lull, María R. Yagüe, Blanca Safont, María G. Molina and Àngela D. Bosch-Serra

Sustainability 2026, 18(15), 7725; https://doi.org/10.3390/su18157725 - 30 Jul 2026

Abstract

The sustainability of agricultural systems is linked to soil organic carbon (SOC) and nitrogen (N) dynamics, both of which are influenced by fertilization management. To investigate the long-term effects of pig slurry, a 10-year field experiment was conducted in a Mediterranean semi-arid rainfed [...] Read more.

The sustainability of agricultural systems is linked to soil organic carbon (SOC) and nitrogen (N) dynamics, both of which are influenced by fertilization management. To investigate the long-term effects of pig slurry, a 10-year field experiment was conducted in a Mediterranean semi-arid rainfed cereal system. Four N treatments were compared: mineral fertilizer (MN), slurry from fattening pigs (FS), slurry from gestating sows (SS), and a zero-N control. Grain and straw yields, SOC and its fractions, microbial biomass and activity, and N mineralization were measured after the final cropping season. Slurry increased grain yield by 21% compared with MN. The FS treatment also increased SOC by 24% compared with the MN treatment, mainly through the mineral-associated organic matter fraction (<0.05 mm). Soil basal respiration dynamics (Gompertz model) and the N mineralization rate (0.04382 day^–1; Stanford–Smith model) did not differ among N-fertilized treatments. However, the potentially mineralizable N pool increased under N fertilization, from 19% in MN to 51% in FS relative to the control. These results indicate that repeated applications of pig slurry can replace mineral fertilizer while maintaining or improving crop productivity and soil C storage. Incorporating N mineralization models into fertilization planning could further optimize slurry application rates and timing. Full article

(This article belongs to the Section Sustainable Agriculture)

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30 pages, 797 KB

Open AccessArticle

Low-Carbon City Pilot Policy and Urban Carbon Productivity: Unveiling the Dual Pathways of Green Innovation and Economic Agglomeration

by Lei Wang and Xiaohan Zhao

Sustainability 2026, 18(15), 7724; https://doi.org/10.3390/su18157724 - 30 Jul 2026

Abstract

To advance its green and low-carbon transition, China has implemented the Low-Carbon City Pilot Policy (LCCPP) as a strategic initiative. A critical question remains unanswered on whether this policy effectively improves urban carbon productivity and facilitates the decoupling of economic growth from carbon [...] Read more.

To advance its green and low-carbon transition, China has implemented the Low-Carbon City Pilot Policy (LCCPP) as a strategic initiative. A critical question remains unanswered on whether this policy effectively improves urban carbon productivity and facilitates the decoupling of economic growth from carbon emissions. Using the phased expansion of the LCCPP across Chinese cities as a quasi-natural experiment, this study constructs a multi-period difference-in-differences (DID) model based on a panel dataset of 276 prefecture-level and above cities from 2007 to 2023. The empirical results show that the LCCPP significantly enhances urban carbon productivity in pilot cities relative to non-pilot counterparts. This finding remains robust across a series of sensitivity checks. Mechanism analysis provides suggestive evidence that the policy may operate through two primary channels: fostering green technological innovation and promoting economic agglomeration. Heterogeneity analysis indicates that the policy’s positive effects are more marked in developed cities, innovation-active cities, high-carbon-emission cities, and environmentally prioritized cities. Furthermore, moderation analysis demonstrates that stricter environmental regulations strengthen the policy’s effectiveness. These findings provide empirical evidence for optimizing the design of low-carbon policies and offer actionable insights for tailoring green urban transformation strategies to local conditions. Full article

(This article belongs to the Topic Advances in Urban Resilience for Sustainable Futures)

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24 pages, 3414 KB

Open AccessArticle

Project-Level Embodied Carbon Prediction Across Building Design Stages Using a Machine Learning Framework

by Zihang Wang, Ling Zhang and Mengmeng Pu

Sustainability 2026, 18(15), 7723; https://doi.org/10.3390/su18157723 - 30 Jul 2026

Abstract

Rapid and reliable prediction of embodied carbon emissions is essential for supporting sustainable design decision-making and reducing the environmental impacts of building engineering projects. However, existing studies have mainly focused on single buildings, with limited attention to project-level prediction and variations in information [...] Read more.

Rapid and reliable prediction of embodied carbon emissions is essential for supporting sustainable design decision-making and reducing the environmental impacts of building engineering projects. However, existing studies have mainly focused on single buildings, with limited attention to project-level prediction and variations in information availability across design stages. To address this gap, this study developed a machine learning framework for project-level embodied carbon prediction based on a dataset of 78 projects involving 426 individual buildings. Using project attributes, scale indicators, structural characteristics, material quantities, and construction-related information, nine machine learning models were developed for the schematic design stage and the construction drawing design stage. Two residual-corrected weighted ensemble models were further introduced to improve predictive performance. The results show that the Extra Trees–KNN residual-corrected weighted ensemble model achieved the best performance at the construction drawing design stage, with a test-set R² of 0.949. SHAP analysis further revealed a stage-dependent shift in dominant drivers: gross floor area and land area dominated at the schematic design stage, whereas concrete and reinforcement quantities became the leading predictors at the construction drawing design stage. The proposed framework provides interpretable and stage-specific quantitative support for low-carbon design decision-making, thereby facilitating embodied carbon reduction and the transition toward a more sustainable built environment. Full article

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20 pages, 272 KB

Open AccessArticle

Does Digital Finance Build a Sustainable Buffer? Exploring Its Impacts on Manufacturing Supply Chain Resilience

by Baoyan Gao, Xiaolong Li, Chi-Wei Su and Zixin Luo

Sustainability 2026, 18(15), 7722; https://doi.org/10.3390/su18157722 - 30 Jul 2026

Abstract

Enhancing supply chain resilience has become crucial for sustainable manufacturing development as firms face repeated disruptions from pandemics, geopolitical shocks, logistics bottlenecks, and climate-related uncertainty. As digital finance alleviates corporate financing constraints and improves information transmission across supply chains, it may strengthen supply [...] Read more.

Enhancing supply chain resilience has become crucial for sustainable manufacturing development as firms face repeated disruptions from pandemics, geopolitical shocks, logistics bottlenecks, and climate-related uncertainty. As digital finance alleviates corporate financing constraints and improves information transmission across supply chains, it may strengthen supply chain resilience, thereby supporting the sustainable development of manufacturing firms. Accordingly, this paper examines this effect using panel data consisting of 21,060 firm-year observations of Chinese A-share listed manufacturing firms spanning the period 2011–2023. It combines the proxy of digital finance, which is the city-level Baidu search index for digital finance, with the entropy-weighted and firm-level supply chain resilience index to assess its sustainability. Based on the fixed-effects model, digital finance positively affects the resilience of manufacturing companies’ supply chains and, by extension, promotes the sustainable development of manufacturing supply chains. We also find that digital finance improves manufacturing supply chain resilience by enhancing information transparency, resolving maturity mismatches between investment and financing, and mitigating financial risks. This impact is larger in poorly developed traditional financial regions, firms with poor governance, and in growing companies. Policy recommendations center on advancing digital supply chain finance, strengthening data governance, and improving risk management systems to reinforce supply chain resilience and promote the long-term sustainable development of manufacturing firms. Full article

(This article belongs to the Special Issue Pathway to an Environmental Economy: The Role of Sustainable Natural Resources)

18 pages, 4305 KB

Open AccessArticle

Predicting the Potential Distribution of Camellia osmantha in Response to Climate Change Using the MaxEnt Model

by Mengli Zhou, Ning Zhang, Haotian Guo, Jing Chen, Fang Guo, Dongfeng Yan, Bingqing Hao and Jianbo Shen

Sustainability 2026, 18(15), 7721; https://doi.org/10.3390/su18157721 - 30 Jul 2026

Abstract

Camellia osmantha is an economically valuable woody oil plant with increasing cultivation in southern China, yet its potential distribution under climate change remains poorly understood. Here, we used an optimized MaxEnt model with 27 occurrence points and 11 environmental variables (retained from 27 [...] Read more.

Camellia osmantha is an economically valuable woody oil plant with increasing cultivation in southern China, yet its potential distribution under climate change remains poorly understood. Here, we used an optimized MaxEnt model with 27 occurrence points and 11 environmental variables (retained from 27 candidate predictors via correlation filtering and MaxEnt-based contribution and permutation importance) to predict its potential distribution in Guangxi under current and future climate scenarios (2050s, 2090s; SSP126, SSP370, SSP585). The model demonstrated acceptable predictive performance (training AUC = 0.7784, test AUC = 0.6935) with the test AUC falling within the acceptable/fair range (0.6–0.7) according to standard evaluation criteria. The dominant drivers were available water capacity (24.3%), altitude (24.1%), and temperature annual range (21.9%), with suitability declining when AWC exceeded 3.0, altitude exceeded 543 m, or bio7 fell below 23.06 °C. Current suitable habitats cover 18.53 × 10⁴ km² (89.7% of Guangxi), with high suitability areas concentrated in the northeast and southwest. Under future scenarios, total suitable area remained stable (−1.2% to +3.2%), while high suitability areas expanded under SSP370/SSP585 (+39.0%/+41.1%) and contracted under SSP126 (−30.3%) by 2090s; centroid shifts were limited (2.95–14.93 km), with core habitats remaining in central Guangxi. These findings provide a quantitative basis for conservation and sustainable cultivation strategies for this species under climate change, and highlight the importance of soil water availability alongside topographic and climatic factors in shaping its distribution. Full article

(This article belongs to the Special Issue New Technological Applications in Agriculture for the Development of the Circular Bioeconomy, 2nd Edition)

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22 pages, 6337 KB

Open AccessArticle

Creative Upcycling of Wood Waste into Furniture: Bridging Durability Testing and Economic Viability, a Case Study

by Małgorzata Grotowska, Emilia Grzegorzewska, Piotr Beer and Sylwia Oleńska

Sustainability 2026, 18(15), 7720; https://doi.org/10.3390/su18157720 - 30 Jul 2026

Abstract

In this article, static durability testing is combined with an economic analysis of selected furniture manufactured from solid oak residues. Durability was assessed under the EN 1728 and EN 12520 static-load procedures, and dimensional stability was examined using statistical process-control tools (normality analysis, [...] Read more.

In this article, static durability testing is combined with an economic analysis of selected furniture manufactured from solid oak residues. Durability was assessed under the EN 1728 and EN 12520 static-load procedures, and dimensional stability was examined using statistical process-control tools (normality analysis, kurtosis and Shewhart control charts). Chairs intended for children were tested for the body mass of five-, seven- and nine-year-old children, as well as for an adult (seat force F1 = 250–850 N, backrest force F2 = 90–290 N). The tested chairs met the strength and durability requirements of the applied standards, and none overturned or tended to tip. A manufacturing cost and profitability analysis then quantified the cost structure. Material accounted for only 10–31% of manufacturing costs, with labour as the dominant component, reflecting the labour intensity of upcycling irregular residues into individually designed furniture. Manufacturing costs per item ranged from PLN 108 to PLN 251 against trial sale prices of PLN 250 to PLN 1300, yielding net profit margins of 46–81%. The findings indicate that upcycling post-production residues can improve the economic and potential environmental performance of furniture enterprises and support circular-economy objectives by reducing demand for virgin timber. Full article

(This article belongs to the Special Issue From Waste to Resource: Processing Waste and By-Products into Valuable Products)

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31 pages, 2548 KB

Open AccessArticle

Outbound Path Optimization for Sustainable China–Europe Railway Express Operations Considering Cargo Consolidation and Departure-Time Matching

by Fenling Feng, Wenli Sun and Meng Qi

Sustainability 2026, 18(15), 7719; https://doi.org/10.3390/su18157719 - 30 Jul 2026

Abstract

In outbound China–Europe Railway Express (CR Express) operations, dispersed cargo access, transshipment-node activation, order consolidation path assignment, block train line selection, and departure-time matching are strongly coupled, directly affecting the economic performance, timeliness, and block train operation efficiency of transport plans. Existing studies [...] Read more.

In outbound China–Europe Railway Express (CR Express) operations, dispersed cargo access, transshipment-node activation, order consolidation path assignment, block train line selection, and departure-time matching are strongly coupled, directly affecting the economic performance, timeliness, and block train operation efficiency of transport plans. Existing studies have mainly focused on the local optimization of consolidation paths, train routes, or departure times. At the same time, insufficient attention has been paid to the bilevel combinatorial structure between node activation and order path assignment. To address this issue, this study proposes an outbound path optimization model for the CR Express considering cargo consolidation, and develops a graph-guided adaptive large neighborhood search (Gra-ALNS) algorithm. The algorithm is organized around a bilevel search structure of node activation and order path assignment. At the upper level, a transport organization graph is constructed, and graph convolutional network (GCN) embeddings are integrated with cargo-access reachability to generate H-node scores, which guide the search for promising transshipment-node activation combinations. At the lower level, outbound generalized paths are used as the basic search units, and upper confidence bound (UCB)-based operator selection, local exact refinement, and cross-

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-grid elite-solution warm starts are combined to optimize order consolidation paths, block train line selection, and departure-time matching. Numerical results show that the proposed Gra-ALNS outperforms conventional adaptive large neighborhood search (ALNS) in computational efficiency and multi-objective solution-set quality. Activating transshipment nodes can reduce the transport cost and in-transit time cost of some orders, but may increase fixed train operating cost and reduce average load factors. The findings provide methodological support for outbound cargo organization optimization, transshipment-node configuration, and block train operation planning of the CR Express. By improving cargo consolidation efficiency, coordinating departure-time matching, and revealing the trade-off between temporal accessibility and train-loading efficiency, this study provides a decision-support reference for a more efficient and sustainable CR Express freight organization. Full article

(This article belongs to the Section Sustainable Transportation)

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23 pages, 563 KB

Open AccessArticle

Bridging Sustainability and Logistics Service: Antecedents of Green Employee Service Behavior in Logistics Enterprises

by Thanh Nhat Lai Nguyen

Sustainability 2026, 18(15), 7718; https://doi.org/10.3390/su18157718 - 30 Jul 2026

Abstract

This study examines the determinants of green employee service behavior (GESB) in maritime logistics by integrating the Theory of Planned Behavior and Social Identity Theory. Using survey data from maritime logistics employees and structural equation modeling, the findings show that environmental knowledge, green [...] Read more.

This study examines the determinants of green employee service behavior (GESB) in maritime logistics by integrating the Theory of Planned Behavior and Social Identity Theory. Using survey data from maritime logistics employees and structural equation modeling, the findings show that environmental knowledge, green organizational climate, green organizational identity, green organizational support, perceived customer green expectations, and perceived behavioral control all significantly influence GESB. Perceived behavioral control emerges as the strongest predictor, followed by green organizational climate and green organizational support, underscoring the importance of employees’ perceived capability and enabling organizational conditions. Furthermore, green organizational identity and perceived customer green expectations partially mediate the effects of organizational factors on GESB. By conceptualizing GESB as a customer-facing form of employee green behavior embedded in logistics service delivery, this study extends existing green behavior research beyond internal workplace environmental actions and offers theoretical and managerial insights for advancing sustainability in maritime logistics. Full article

(This article belongs to the Section Economic and Business Aspects of Sustainability)

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26 pages, 572 KB

Open AccessArticle

Fortune or Not? How Context Drives Passive Resistance to Pro-Social Innovations in Base-of-the-Pyramid Markets: An Empirical Study and a Research Agenda

by Michelle Greene, Allard C. R. van Riel, Josée Bloemer and Sandra Streukens

Sustainability 2026, 18(15), 7717; https://doi.org/10.3390/su18157717 - 30 Jul 2026

Abstract

Many innovations, including potentially highly beneficial pro-social innovations, fail to diffuse successfully at the base of the pyramid (BoP). Explanations traditionally emphasize shortcomings in the value proposition or, more recently, interpret non-adoption as a consequence of innovation resistance. This study investigates whether passive [...] Read more.

Many innovations, including potentially highly beneficial pro-social innovations, fail to diffuse successfully at the base of the pyramid (BoP). Explanations traditionally emphasize shortcomings in the value proposition or, more recently, interpret non-adoption as a consequence of innovation resistance. This study investigates whether passive innovation resistance (PIR) among BoP consumers should be understood not merely as an individual predisposition, but also as a response shaped by characteristics of the social context. Drawing upon a service ecosystem perspective, we develop and empirically test a model linking three contextual antecedents to PIR among BoP consumers: distrust of retail, use of informal consumption practices, and limitations in resources. Survey data from 282 consumers in Zambia were used to test the model for the case of a mobile-money-related innovation. The findings demonstrate that characteristics of the social context strongly influence PIR. Beyond limitations in resources, distrust of retail and use of informal practices emerge as important antecedents, indicating that in this case, resistance to innovation in BoP settings is not solely a psychological disposition but also a context-dependent response to environmental conditions. These findings extend innovation resistance theory beyond affluent market settings by identifying important contextual antecedents of PIR. From a managerial and societal perspective, the results support the development and diffusion of pro-social innovations that are better aligned with the realities of structurally vulnerable populations, thereby contributing to poverty alleviation and sustainable development. Full article

(This article belongs to the Section Economic and Business Aspects of Sustainability)

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29 pages, 2328 KB

Open AccessArticle

Benchmarking Türkiye’s Sustainable Development Performance: SDG Interactions, Macroeconomic Predictors, and Explainable Machine Learning Evidence from Selected Major Muslim Economies

by Cemal Zehir, Tuğçe Ekiz Yılmaz, Umut Elbir and Zahid Farrukh Mamedov

Sustainability 2026, 18(15), 7716; https://doi.org/10.3390/su18157716 - 30 Jul 2026

Abstract

Sustainable development has become a strategic priority for countries seeking long-term economic prosperity while balancing social, environmental, and institutional objectives. According to the April 2026 International Monetary Fund World Economic Outlook projections, Türkiye is expected to become the largest economy among the selected [...] Read more.

Sustainable development has become a strategic priority for countries seeking long-term economic prosperity while balancing social, environmental, and institutional objectives. According to the April 2026 International Monetary Fund World Economic Outlook projections, Türkiye is expected to become the largest economy among the selected major Muslim economies in terms of nominal gross domestic product. Motivated by this development, this study benchmarks Türkiye’s sustainable development performance against nine comparable economies and examines the relationships between selected Sustainable Development Goal (SDG) indicators and economic performance. The analytical framework integrates benchmarking, correlation, SDG network analysis, regression modeling, and explainable machine learning using SDG and macroeconomic data. The findings reveal both synergies and trade-offs among the selected SDGs. Strong positive relationships emerge between SDG12 and SDG13 and between SDG4 and SDG16, confirming the interconnected structure of sustainable development. Türkiye ranks second in overall SDG performance and performs particularly strongly in clean energy, innovation and infrastructure, and international partnerships. Regression results identify education, clean energy, innovation, and climate action as statistically associated with economic performance. Under a strict year-based chronological holdout and rolling-origin validation framework, the tuned Random Forest model achieved the strongest out-of-sample predictive performance. SHapley Additive exPlanations analysis indicates that one-year lagged economic performance is the dominant predictor, while current macroeconomic conditions and selected SDG indicators provide additional predictive information. The findings demonstrate substantial temporal persistence in economic performance and show that sustainability indicators complement prior economic information in forecasting. The study contributes to sustainability research by integrating comparative assessment, systems-oriented analysis, econometric modeling, and explainable machine learning while clearly distinguishing statistical association from predictive contribution. Full article

(This article belongs to the Section Development Goals towards Sustainability)

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13 pages, 281 KB

Open AccessArticle

Performance on Standardized Pedagogical Assessments: A Sustainability-Oriented Analysis in Physical Education Teacher Education

by Francisco Gallardo-Fuentes, Bastian Carter-Thuillier, Johan Rivas-Valenzuela, Carolina Martínez-Angulo, Sebastián Peña-Troncoso, Jorge Gallardo-Fuentes and Luis Añazco-Martínez

Sustainability 2026, 18(15), 7715; https://doi.org/10.3390/su18157715 - 30 Jul 2026

Abstract

Initial teacher education requires assessment mechanisms capable of identifying strengths and weaknesses in professional preparation. This study analyzes the performance of students in Initial Teacher Education in Physical Education against the pedagogical standards assessed by the 2024 National Diagnostic Assessment (NDA) in Chile, [...] Read more.

Initial teacher education requires assessment mechanisms capable of identifying strengths and weaknesses in professional preparation. This study analyzes the performance of students in Initial Teacher Education in Physical Education against the pedagogical standards assessed by the 2024 National Diagnostic Assessment (NDA) in Chile, examining achievement patterns and differences by sex and administrative dependency. A quantitative, cross-sectional, and correlational design was employed, based on official census data corresponding to 1035 students enrolled in Chilean universities offering this degree program. Descriptive analyses and non-parametric inferential tests were con-ducted, using the Mann–Whitney U test for comparisons by sex, and the Kruskal–Wallis test followed by Dunn’s post hoc comparisons with Bonferroni correction for comparisons across administrative dependency categories. The highest levels were observed in pro-fessional ethics (M = 0.69) and student learning and development (M = 0.57), and the lowest in respectful and well organized learning environments (M = 0.39) and curricular pedagogical content knowledge (M = 0.40). Significant differences by sex appeared only in personal and social development and professional ethics (p = 0.01; r = 0.08), favoring women. Differences by administrative dependency were significant in few standards and consistently small (r ≤ 0.14). These effects indicate that achievement is largely comparable across institutions and that the main weaknesses are systemic. Strengthening these di-mensions constitutes a challenge for the sustainability of teacher education, rather than a problem restricted to specific institutions. Full article

(This article belongs to the Special Issue A New Paradigm in Teacher Education: Sustainability in Teacher Training)

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