Search Results (276)

This study evaluates China’s National Smart Education Platform (NSEP) as a national digital reform aligned with SDG 4 (quality education) and SDG 10 (reduced inequalities), yet evidence remains limited on whether such platforms reduce urban–rural gaps in real-world use and outcomes. A quantitative, stratified, random survey of students, teachers, and administrators used validated scales to measure perceived ease of use (PEOU), perceived usefulness (PU), user satisfaction (US), behavioral intention (BI), engagement level (EL), learning outcomes (LO), and system quality (SQ). The measures demonstrated strong reliability. Hierarchical regression analyses supported an extended technology acceptance model (TAM): SQ, PEOU, and PU significantly predicted US and BI, with PU showing the strongest effect. Interaction effects indicated context-sensitive adoption and the results suggested a persistent rural disadvantage in adoption even after accounting for key predictors. Mediation analyses further showed that US and BI transmitted technology beliefs to LO. Nevertheless, urban–rural gaps remained evident, particularly in PEOU and SQ, and teachers consistently reported a lower PEOU than students and administrators. These findings suggest that NSEP has the potential to support SDG-oriented digital equity, but closing urban–rural gaps requires teacher-centered design, improved usability and system reliability, and targeted infrastructure and capacity-building support in rural contexts. Full article

Sustainability in the agri-food sector has become a cornerstone of global efforts to combat climate change, ensure food security through climate-smart agriculture, and strengthen economic resilience. Sustainability reporting within agri-food systems has gained increasing regulatory significance with the introduction of mandatory frameworks such as the Turkish Sustainability Reporting Standards (TSRSs). This article searches for the sustainability reports of agri-business firms listed in BIST in Turkey. Although TSRS reporting is not yet mandatory for the agribusiness sector, this study examines the first TSRS-aligned sustainability reports published by eight agri-food companies, excluding the retail sector. The analysis assesses how effectively these reports address sector-specific environmental and social challenges defined in the GRI 13 Agriculture, Aquaculture and Fishing Sector Standard and their alignment with the United Nations Sustainable Development Goals (SDGs). Using a structured content analysis approach, disclosure patterns were examined at both thematic and company levels. The findings indicate that TSRS-aligned reports place strong emphasis on environmental and climate-related disclosures, particularly emissions, climate adaptation and resilience, water management, and waste. In contrast, agro-ecological and land-based impacts—such as soil health, pesticide use, and ecosystem conversion—are weakly addressed. Economic disclosures are predominantly framed around climate-related financial risks and supply chain traceability, while social reporting focuses mainly on occupational health and safety, employment practices, and food safety, with limited attention to labor and equity issues across the broader value chain. Company-level results reveal marked heterogeneity, with internationally active firms demonstrating deeper alignment with GRI 13 requirements. From an SDG alignment perspective, high levels of coverage are observed across all companies for SDG 13 (Climate Action), SDG 12 (Responsible Consumption and Production), and SDG 6 (Clean Water and Sanitation). By contrast, SDGs critical to agro-ecological integrity and social equity—namely SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 10 (Reduced Inequalities), and SDG 15 (Life on Land)—are weakly represented or entirely absent. Overall, the results suggest that while TSRS-aligned reporting enhances transparency in climate-related domains, it achieves only selective alignment with the SDG agenda. This underscores the need for a stronger integration of sector-specific sustainability priorities into mandatory sustainability reporting frameworks. Full article

This study investigates regional heterogeneity and spatial interdependence in digital skills mismatch across Indonesia by constructing a Digital Skills Supply–Demand Ratio (DSSDR) from the Indonesia Digital Society Index (IMDI). In line with SDG 10 (Reduced Inequalities) and SDG 4 (Quality Education), the study aims to provide policy-relevant evidence to support a more inclusive and balanced digital transformation. Using district-level data and spatial econometric models (OLS, SAR, and the SDM), the analysis evaluates both local determinants and cross-regional spillover effects. Model comparison identifies the Spatial Durbin Model as the best specification, revealing strong spatial dependence in digital skills imbalance. The results show that most local socioeconomic and digital readiness indicators do not have significant direct effects on DSSDR, while school internet coverage exhibits a consistently negative association, indicating that digital demand expands faster than local supply. In contrast, spatial spillovers are decisive: a higher share of ICT study programs in neighboring regions improves local DSSDR through knowledge and human-capital diffusion, whereas higher GRDP per capita in adjacent regions exacerbates local mismatch, consistent with a talent-attraction mechanism. These findings demonstrate that digital skills mismatch is a spatially interconnected phenomenon driven more by interregional dynamics than by local conditions alone, implying that policy responses should move beyond isolated district-level interventions toward coordinated regional strategies integrating education systems, labor markets, and digital ecosystem development. The study contributes a spatially explicit, supply–demand-based framework for diagnosing regional digital inequality and supporting more equitable and sustainable digital development in Indonesia. Full article

Conversion of carbon dioxide (CO₂) to methanol in a traditional reactor (TR) with catalytic packed bed faces the challenge of lower reactant conversion due to thermodynamic limitations. On the contrary, membrane reactors selectively remove reaction products, enhancing the conversion, but it is still limited, and existing designs face challenges of structural integrity and scale-up complications. Therefore, for the first time, a ceramic membrane microchannel reactor (CMMR) system was developed with 500 µm deep microchannels, incorporated with catalytic membrane for CO₂ conversion to methanol. Computational fluid dynamic (CFD) simulations confirmed the uniform flow distribution among the microchannels. A catalytic LTA zeolite membrane was synthesized with thin layer (~45 µm) of Cu-ZnO-Al₂O₃ catalyst coating and tested at a temperature of 220 °C and 3.0 MPa pressure. The results showed a significantly higher CO₂ conversion of 82%, which is approximately 10 times higher than TR and 3 times higher than equilibrium conversion while 1.5 times higher than conventional tubular membrane reactor. Additionally, methanol selectivity and yield were achieved as 51.6% and 42.3%, respectively. The research outputs showed potential of replacing the current industrial process of methanol synthesis, addressing the Sustainable Development Goals of SDG-7, 9, and 13 for clean energy, industry innovation, and climate action, respectively. Full article

Existing office buildings in Australia contribute to 24% of the nation’s electricity consumption and 10% of greenhouse gas emissions, with energy use projected to rise by 84%. Meeting the 2050 sustainability target and United Nations (UN) 17 Sustainable Development Goals (SDGs) requires improving sustainability within existing office buildings. This systematic review examines net zero energy and climate resilience strategies in these buildings by analysing 74 studies from scholarly literature, government reports, and industry publications. The literature search was conducted across Scopus, Google Scholar, and Web of Science databases, with the final search in early 2025. Studies were selected based on keywords and research parameters. A narrative synthesis identified key technologies, evaluating the integration of net zero principles with climate resilience to enhance energy efficiency through HVAC modifications. Technologies like heat pumps, energy recovery ventilators, thermal energy storage, and phase change materials (PCMs) have been identified as crucial in reducing HVAC energy usage intensity (EUI). Lighting control and plug load management advancements are examined for reducing electricity demand. This review highlights the gap between academic research and practical applications, emphasising the need for comprehensive field studies to provide long-term performance data. Current regulatory frameworks influencing the net zero transition are discussed, with recommendations for policy actions and future research. This study links net zero performance with climate adaptation objectives for existing office buildings and provides recommendations for future research, retrofit planning, and policy development. Full article

Accurate monitoring of income inequality is critical for sustainable socioeconomic development and realizing the United Nations Sustainable Development Goals (SDGs). However, assessing inequality for counties continues to be challenging because of the high cost of household surveys and the limited accuracy of traditional nighttime light (NTL) proxies. To address this gap, we develop the Distribution Matching-based Individual Income Inequality Estimation Model (DM-I3EM), which integrates NTL data with household surveys. The model employs a three-stage workflow: logarithmic transformation of NTL data, estimation of Gini coefficients through Weibull distribution fitting, and selection of region-specific regression models, enabling high-resolution mapping and spatiotemporal analysis of county-level income inequality across China. Results show that DM-I3EM achieves superior performance, with an R² of 0.76 in China’s Eastern region (outperforming conventional NTL-based methods, R ≈ 0.5). By overcoming the spatiotemporal gaps of survey data, the model enables full-coverage estimation, revealing a regional divergence in income inequality across China from 2013 to 2022: inequality is intensifying in northern and western counties while stabilizing in the developed southern coastal regions. Furthermore, spatial agglomeration of inequality has strengthened, particularly in coastal urban clusters. These findings highlight emerging risks to socioeconomic sustainability. This study provides a robust, replicable framework for estimating inequality in data-scarce regions, offering policymakers actionable evidence to identify high-risk areas and design targeted strategies for advancing SDG 10 (Reduced Inequalities). Full article

Individual actions play a pivotal role in climate change, one of the most urgent global challenges, as daily behaviors generate substantial greenhouse gas emissions. Saudi Arabia, in particular, demonstrates its strong commitment to environmental sustainability through the Saudi Green Initiative and Middle East Green Initiative, aiming for net-zero emissions by 2060 and advancing reforestation, land conservation, and renewable energy under Vision 2030. However, many Saudi individuals remain unaware of the environmental consequences of their choices, including transportation, energy consumption, and lifestyle habits. To address this gap, this study developed GreenKSA, the first Arabic-supported gamified mobile application designed to promote pro-environmental behavior within the Saudi culture. The app integrates gamification elements grounded in Self-Determination Theory (SDT) and Trans-Theoretical Model (TTM) in an attempt to bridge the gap between theory and practice. GreenKSA delivers multimedia content—short videos and infographics—demonstrating sustainable routines in households, workplaces, and mobility. The design and user experience of GreenKSA were evaluated in a pilot study of 10 participants. The results indicated high usability (SUS = 91.25) and a positive overall user experience. By combining theory-driven design with culturally relevant gamification elements, this study contributes to digital sustainability interventions and aligns with the global Sustainable Development Goals SDG 12: Responsible Consumption and Production, and SDG 13: Climate Action. Full article

Accurate mapping of rice cultivation is vital for ensuring food security, reducing greenhouse gas emissions, and achieving sustainable development goals. However, large-scale deep learning–based crop mapping remains limited due to the demand for vast, uniformly distributed, high-quality samples. To address this challenge, we propose a Progressive Deep Learning Crop Mapping (PDLCM) framework for national-scale, high-resolution rice mapping. Beginning with a small set of localized rice and non-rice samples, PDLCM progressively refines model performance through iterative enhancement of positive and negative samples, effectively mitigating sample scarcity and spatial heterogeneity. By combining time-series Sentinel-2 optical data with Sentinel-1 synthetic aperture radar imagery, the framework captures distinctive phenological characteristics of rice while resolving spatiotemporal inconsistencies in large datasets. Applying PDLCM, we produced 10 m rice maps from 2022 to 2024 across the middle and lower Yangtze River Basin, covering more than one million square kilometers. The results achieved an overall accuracy of 96.8% and an F1 score of 0.88, demonstrating strong spatial and temporal generalization. All datasets and source codes are publicly accessible, supporting SDG 2 and providing a transferable paradigm for operational large-scale crop mapping. Full article

In this study, the technical, economic, and environmental performances of a Linear Fresnel Reflector (LFR) integrated with an Organic Rankine Cycle (ORC), designed with a non-storage approach, and a monocrystalline photovoltaic (PV) system were comparatively evaluated in meeting a building’s 10 kW electricity demand. Solar-based electricity generation systems play a critical role in reducing carbon emissions and increasing energy self-sufficiency in buildings, yet small-scale, storage-free LFR-ORC applications remain relatively underexplored compared to PV systems. The optimal areas for both systems were determined using the P₁–P₂ methodology. The electricity generation of the LFR-ORC system was calculated based on experimentally measured thermal power output and ORC efficiency, while the production of the PV system was determined using panel area, efficiency, and measured solar irradiation data. System performance was assessed through self-consumption and self-sufficiency ratios, and the economic analysis included life cycle savings (LCS), payback period, and levelized cost of electricity (LCOE). The results indicate that the PV system is more advantageous economically, with an optimal payback of 4.93 years and lower LCOE of 0.053 €/kWh when the economically optimal panel area is considered. On the other hand, the LFR-ORC system exhibits up to 35% lower life-cycle CO₂ emissions compared to grid electricity under grid-connected operation (15.86 tons CO₂-eq for the standalone LFR-ORC system versus 50.57 tons CO₂-eq for PV over 25-year lifetime), thus providing superiority in terms of environmental sustainability. In this context, the study presents an engineering-based approach for the technical, economic, and environmental assessment of small-scale, non-storage solar energy systems in line with the United Nations Sustainable Development Goals (SDG 7: Affordable and Clean Energy and SDG 13: Climate Action) and contributes to the existing literature. Full article

Social media has the potential to serve beneficial purposes. The abundance of uploaded content and responses from the public generates various opinions, allowing them to be identified as positive or negative regarding the portrayal of Bandung Regency. This research aims to analyse the classification and frequency of words for each sentiment expressed by X (Twitter) users regarding Bandung Regency. The research employs the Support Vector Machine (SVM) method. We expect the results to aid in formulating governmental programmes for Bandung Regency. The research revealed that the SVM model, which uses the Sigmoid kernel function with parameters $C$ = 10 and gamma ($\gamma$) = 1, is the most optimal sentiment classification model for handling an imbalanced dataset. This model achieved an 83.01% negative recall value. Furthermore, frequent words appearing in both classes indicate that several positive opinions about Bandung Regency exhibit similar dominance, except for football dominance in negative opinions. This research pertains to the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities) and SDG 16 (Peace, Justice, and Strong Institutions). The suggested technique facilitates evidence-based policy reviews, transparent governance, and enhanced responsive public services by analysing public sentiment regarding local government performance. The results illustrate how social media analytics can aid local governments in assessing popular sentiment and pinpointing areas for policy response. Full article

This research investigates the socioeconomic factors that lead to ineffective plastic waste management in household areas and their consequences for water sustainability in four villages in Guyana: Mon Repos, Lusignan, De Endragt, and Good Hope. The study uses a household survey (N = 384), chi-square tests, and a binary logistic model. It finds that labour status, schooling, and earnings affect unsafe disposal practices like dumping, incineration, or leaving garbage. The risk of inappropriate disposal is 20%, higher than the 6.8% among university graduates. The unemployed are at highest risk, with 32.7% at high risk. Low-income individuals (≤GYD $85,000) have a 21.9% rate, which is 2.5 times higher than the 7.6% rate among higher-income individuals. Strikingly, 63.2% of the high-risk households reported seeing “some” or “vast” amounts of dumped garbage in the close vicinity. It suggests a greater possibility of water contamination. Lacking direct proof of water quality, the strong correlation between socioeconomic disadvantage, litter visibility, and proximity to drainage infrastructure is one of the environmental justice concerns. The findings show plastic littering to be a structural issue associated with inequality, rather than purely individual behaviour, beyond the lack of access to sound waste management services. From a sustainability perspective, there needs to be a priority on straightforward strategies that encompass waste infrastructure development alongside poverty reduction and sustainable management practices. If these intrinsic disparities are not addressed, efforts to protect community water resources and realise SDGs 6, 10, and 12 will likely be futile. Full article

This study identifies key determinants shaping countries’ Sustainable Development Goals performance and develops classification models for predicting country group membership based on the SDG Index. The research addresses the urgent need to optimize development policies amid limited resources and the approaching 2030 Agenda deadline. Using data from 154 countries (2024), the analysis reveals that key SDG determinants are fundamentally method-dependent: discriminant analysis identified Goals 10, 6, 15, and 5 as most influential for differentiating countries by SDGI level, while Random Forest identified Goals 4, 9, and 2 as the most important predictors. This divergence reflects fundamentally different analytical perspectives—linear contributions to group separation versus complex nonlinear interactions and synergies between goals—with critical policy implications for prioritization strategies. Correlation analysis demonstrates that sustainable development dynamics operate differently across development stages: high-development countries show strongest associations with technological advancement and institutional capacity, while low-development countries exhibit compensation effects where basic infrastructure provision occurs alongside lagging human capital development. The discriminant model achieved 94.08% overall accuracy with perfect classification for extreme SDGI categories, while the Random Forest model provides complementary insights into interactive pathways. The scientific contribution lies in demonstrating that perceived variable importance depends on analytical framework rather than representing objective reality, and in providing validated classification tools for rapid assessment in data-limited contexts. These findings offer actionable guidance for evidence-based resource allocation and policy prioritization in the critical final years of SDG implementation. Full article

Urban health, well-being, and equity—core objectives of Sustainable Development Goals (SDGs 3, 10, and 11)—have become key themes in contemporary urban planning research and landscape research. While existing studies focus predominantly on quantitative assessment, environmental exposure, and human mobility, the historical origins of health-oriented urban green space planning remain insufficiently explored. Focusing on Lingnan area as a representative case, this research investigates the emergence of public green space in late Qing cities and its early contributions to urban health and spatial governance. Through a systematic examination of American and British Gardens at the Thirteen Factories in Guangzhou, the planned public green space system of the Shameen concession, and the municipal greening practices of neighboring Hong Kong and Macao, the study further analyzes Zhang Zhidong’s tree-lined boulevard project along Changdi avenue as a key instance of localized institutional adaptation. Drawing on late-Qing and Republican newspapers, nineteenth-century Western travelogs and reports, historical and contemporary studies and photo albums, the study finds the following: (1) the American and British Gardens marked the earliest emergence of health-oriented urban green space in Lingnan area; (2) the systematically planned green space network of the Shameen concession constituted a prototypical form of health-oriented urban green space planning; (3) the botanical gardens, street-tree systems, public parks, and institutionalized management practices in Hong Kong and Macao exerted a strong regional demonstrative influence on Guangzhou; (4) the street-tree planting along Changdi Avenue represented a localized absorption of foreign planning paradigms and marked the institutionalization of municipal greening in Guangzhou. Although these early practices did not yet form a modern healthy city planning framework at that time, they played a crucial role in improving urban sanitation, enhancing public space quality, and shaping urban order. By tracing the historical trajectory from transnational demonstration to local adaptation and institutional consolihdation, this study provides new insights into the historical foundations of health-oriented urban planning in China and contributes a long-term perspective to contemporary debates on healthy cities and nature-based urban interventions. Full article

The incorporation of utilized plastic waste into concrete mix designs for precast pavement applications presents a highly efficacious strategy, yielding demonstrably superior mechanical properties. High-density polyethylene (HDPE) is the proposed type of plastic in this study. It demonstrates remarkable performance and durability characteristics. The methodology not only significantly curtails landfill waste and incineration but also contributes to a reduction in energy consumption within the concrete sector, thereby establishing itself as a definitive sustainable solution that addresses environmental, economic, and societal imperatives. The optimal incorporation ratio for the recycled plastic within concrete matrices is determined to fall between 10% and 15%, as this range facilitates the attainment of the most desirable material properties. This study specifically focuses on plastic waste and the incorporation of recycled plastic into concrete materials. The emphasis on plastic is due to its material properties, which are particularly well-suited for concrete applications. Experimental tests are conducted on recycled concrete in comparison with the conventional concrete. The results demonstrate high mechanical properties to the recycled concrete. The novelty of this research is the type of plastic used in the concrete mix. Although most of the worldwide applications use Polyethylene Terephthalate (PET), HDPE showed exceeding properties and performance. Two important factors that influence the architectural aspect of construction materials are the heat island effect and the solar reflective index. These factors affect the energy absorption and emissivity rates of construction materials. The embodied carbon in the concrete mix impacts environmental and energy consumption rates, which directly relate to climate change, one of the Sustainable Development Goals (SDGs). Full article

Against the dual backdrop of rapid population aging and legacy neighborhood renewal, morphologically planning-locked legacy neighborhoods in high-density cities face persistent imbalances in outdoor activity spaces that undermine aging-in-place participation and health equity. This study advances a Spatial Pathology framework. Using nine representative communities in Longtan Subdistrict, Dongcheng District, Beijing, we develop a GIS-assisted spatial audit, a systematic behavioral observation protocol with temporal-intensity metrics, and a validated perception instrument. These tools form a closed evidentiary loop with explicit indicator definitions, formulas, and decision thresholds, alongside a reproducible analytic and visualization pipeline. Tri-dimensional baselines revealed substantial inter-community disparities: Spatial Quality Index (SQI) ranged from 43.3 to 77.0; activity intensity varied from 1.5 to 15.7 persons/100 m²·hour; and overall satisfaction scores spanned 3.88–4.49. It quantifies and identifies three core paradoxes in outdoor activity spaces within this context: (1) the Functional Failure Paradox with FFI exceeding +0.5 and ELR surpassing 60% in dormant communities; (2) the Value Misalignment Paradox where Facilities & Equipment showed the strongest satisfaction impact (β = 0.344) yet the largest unmet-need gap (VQGI > +8); (3) the Practice–Perception Decoupling Paradox evidenced by a negative correlation (r = −0.38) between usage intensity and satisfaction. These paradoxes reveal the spatial roots of planning-locked legacy neighborhoods—compound mechanisms of planning inertia, decision–demand information gaps, and elderly adaptability masking environmental deficits. We translate the diagnosis into typology-specific prescriptions—reactivating dormant spaces via “route–node–plane” continuity and proximal micro-spaces; decongesting peak periods through elastic zoning and equipment redistribution; and precision calibration of facilities and walking loops—implemented through co-creation and light-touch stewardship. This provides evidence-based, precision-targeted intervention pathways for micro-renewal of aging neighborhoods, supporting localized implementation of UN Sustainable Development Goals (SDG 11 Sustainable Cities; SDG 10 Reduced Inequalities). This methodological framework is transferable to other high-density aging cities, offering theoretical scaffolding and empirical reference for multi-source geographic data-driven urban spatial analysis and equity-oriented age-friendly retrofitting. Full article