Climate change poses severe challenges to small-scale fisheries, which require critical adaptation strategies. This study developed a model of climate change adaptation among small-scale fishermen in Bengkulu Province, Indonesia, using a framework that links poverty, livelihood vulnerability, and adaptive capacity. This study contributes novel empirical evidence on how these factors interact to shape adaptive behavior in small-scale fisheries within a developing country context. Data was collected from a survey of 700 fishing households selected by quota sampling. The direct and indirect relationships among socioeconomic variables and adaptation strategies were examined using path analysis in Statistical Package for the Social Sciences (SPSS) and Analysis of Moment Structures (AMOS). The findings revealed that poverty had a significantly adverse effect on the adaptive capacity of fishermen, limiting their capability to respond effectively to climate stressors. Consequently, a majority of fishermen relied on low-cost and easily implemented strategies, such as adjusting fishing times and shifting fishing grounds. Fishing experience, vessel capacity, fishing distance, and the type of fishing gear, in contrast, showed significantly positive effects on adaptation. These results underscore that economic constraints weaken adaptive capacity, while technical assets and practical knowledge enhance resilience. The policy implications highlighted the imperative to strengthen fishermen’s institutions, update fleets, establish cooperatives, diversify fishing gear, and provide accessible digital climate information services. Such governmental interventions are crucial for enhancing adaptive capacity, supporting the sustainable management of fisheries, and improving the economic resilience of coastal communities.
There was incomplete literature on the threshold effect of interest rates on investment, particularly investment by source of capital. This study investigated key macroeconomic factors, such as lending interest rates, inflation, exchange rates, growth in gross domestic product (GDP) and money supply, together with their impact on the proliferation in public capital, private capital, foreign direct investment, and total investment in Vietnam. Threshold regression (TR) was applied to analyze secondary data spanning from year 1996 to 2022; it was discovered that the threshold of interest rate was significant only for the public investment model across four funding sources. Although the threshold test of interest rates was not statistically significant for three of the funding sources, the threshold values of interest rate influenced investment in ownership ranked from low to high, i.e., foreign direct investment, public investment, total investment, and lastly private investment. The gap in the literature and the findings in this study highlighted the response of investment with different ownership to macroeconomic changes, especially in emerging economies like Vietnam. The results illustrated that lending interest rates and inflation negatively impacted private investment, which was subject to the effect of monetary tightening. However, these factors had minimal effects on total investment and foreign direct investment. Public investment and foreign direct investment are primarily influenced by fiscal policies. As regards private investment, it reacts more strongly to changes in exchange rate than foreign direct investment; policy adjustments are therefore recommended to weather the periods of economic instability and high interest rates.
Limited access to energy in rural areas undermines the quality of life and hinders the short-term economic growth in a community. It is therefore essential to identify the evolution of technological tools, the social factors, and the current development in the forms of energy commercialization. Using a bibliometric approach and systematic review, this study aimed to conduct case studies in rural communities that implemented decentralized and sustainable energy systems. The methodology involved: i) A bibliometric analysis under the mapping of co-occurrence by keywords and trend topics using scientific databases like Scopus and Web of Science (WoS); ii) The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method; and iii) A systematic review using the Mixed Methods Appraisal Tool (MMAT). A total of 259 articles from rural communities were analyzed from year 1979 to 2024 to prove that biomass, prevailing throughout history, is the most feasible source of energy generated during implementation; the analysis also provided a better understanding of its utilization mechanisms. Bioenergy accounted for 36% of the scientific contribution, primarily out of its widespread availability and the diversity of methods for harnessing energy from this resource. The energy transition of the last two decades was reflected in renewable energy sources (29%), energy mix (18%), and solar energy (9%), relegating conventional energy to only 2%. This study discovered that the research areas of hydropower and wind energy were influenced by the feasibility and social acceptability of their respective projects. Meanwhile, the use of blockchain, exerting an impact on the traceability of decentralized energy trading, advocated a proposal for change in current markets to strengthen the sustainability of projects, streamline processes, and back up information. To sum up, this study examined the utilization and implementation of renewable energy in decentralized energy projects, thereby contributing to energy autonomy and optimized resource utilization.
India annually produces about 62 million tons of municipal solid waste, comprising 50–60% of organic matter. Accelerating urbanization and population growth in this country have intensified the challenges confronted by managing food, agricultural, and biodegradable waste, as the waste if handled improperly, would lead to groundwater contamination, soil degradation, and methane emission from landfills. This review provided a comprehensive assessment of the organic waste management (OWM) landscape in India, ranging from conventional methods like composting and vermicomposting to advanced approaches such as anaerobic digestion and biogas generation. It also evaluated the influence of policy frameworks and community-led initiatives on promoting sustainable practices. The focus of this study on the emerging role of artificial intelligence (AI) in the OWM highlighted its potential for improving waste segregation, process optimization, and real-time monitoring. While the application of AI in waste management has demonstrated over 90% of segregation accuracy in the pilot and global studies, its adoption remains minimal in India. By systematically comparing national practices with global benchmarks, this review identified critical gaps in technology adoption, scalability, and integration between policy and infrastructure; to fill a noticeable void in the existing literature, AI-driven innovations were adopted to deal with the unique challenge of waste management in India. The findings underscored the need for targeted support, capacity building, and technological deployment to transform organic waste from an environmental liability into a renewable and value-generating resource. Practical recommendations were offered to align technology, governance, and community participation with sustainable and resource-efficient OWM.
This study presents an all-inclusive benchmarking framework as a strategic tool for Saudi Arabian higher education institutions (HEIs) aiming to enhance their performance in the UI GreenMetric World University Ranking (UIGWUR), with extended applications for HEIs in other countries. The proposed framework progresses beyond statistical reporting to offer a transferable data-driven tool that could support HEIs worldwide in diagnosing gaps, prioritizing actions and strategically advancing sustainability outcomes. The number and trends of ranking by Saudi Arabian HEIs participated in the UIGWUR between year 2014 and 2024 are quantitatively analyzed to reveal insights into their sustainability performance and areas for improvement. Results from the analysis indicated steady growth in their participation, beginning from one HEI in year 2014 to 14 out of 67 HEIs in year 2024. Four institutions, in particular, could serve as benchmark models for others aspiring to improve their global standing: King Abdulaziz University (KAU) and Princess Nourah bint Abdulrahman University (PNU) have ranked among the top 100 consistently whereas Qassim University (QU) and Imam Abdulrahman Bin Faisal University (IABFU) have also secured top 100 positions in the recent years. To help other HEIs obtain comparable achievement, this study, with a detailed benchmarking analysis from year 2020 onward, identified the minimum performance scores for attaining a top 100 position in year 2025. The study categorized the required levels of effort into Aligned, Low, Medium, and High across different UIGWUR criteria, hence offering a structured roadmap for improvement. It was recommended that approximately 79% of the participated HEIs in year 2024 should invest Medium to High levels of effort to be qualified for top 100 in year 2025. Though the current analysis focused on Saudi Arabian HEIs, the proposed framework could offer a scalable tool applicable to global HEIs to boost their sustainability performance.
The assessment of urban sustainability and the development of performance-based practical tools for achieving Sustainable Development Goals (SDGs) are key items for discussion on the public agenda. Despite the urgency of the issues, there is a noticeable lack of studies related to a comprehensive model that could holistically assess sustainability performance at the city level. To address this research gap, SIMURG_CITIES conceptual model, the sub-project of “A Performance-based and Sustainability-oriented Integration Model Using Relational database architecture to increase Global competitiveness of the construction industry” (SIMURG), introduces a system-based methodology to evaluate urban sustainability of different cities. SIMURG_CITIES adopts multiple city layers and their associated key performance indicator (KPI) sets within the built environment dimension of 3D Cartesian system architecture to offer new insights. The purpose of this paper is to develop conceptual models at paradigmatic/philosophical, organizational process, interoperability/integrational, and computational/assessment components, paving the way for practical applications with a relational database model. The model and its relationship with interrelated components are explored by an iterative systems approach using “input–process–output–outcome–impact” (IPO) model and the “people-process-technology” (PPT) methodology. This structure steers the integration of humane, procedural, and technological factors into urban sustainability assessment. In addition, the model could help individuals select ideal urban environments to align with their expectations and to enhance accountability, transparency, and legitimacy in the decision-making processes of public authorities. Through this study, a technology-based approach is found to be effective in assessing urban sustainability and a conceptual framework is established in the contexts of Society 5.0 and urban governance.
Rapid urban expansion in sub-Saharan Africa has increasingly posed challenges to ecological sustainability and climatic stability. In this study, the spatiotemporal impacts of urban growth on biodiversity and surface temperature dynamics in Abomey-Calavi, Republic of Benin, were quantitatively assessed. A multi-decadal analysis was conducted using satellite imagery from the Landsat series (1992, 2002, 2012, and 2022), temperature records, and relevant literature, in alignment with Sustainable Development Goal (SDG) Indicator 11.3.1 and Indicator 1 of the Singapore City Biodiversity Index (CBI). Findings revealed a significant imbalance between land consumption and population growth, with a land use to population ratio of 4.25, substantially exceeding the sustainable threshold of 1. This trend denotes unsustainable urban development. Concurrently, biologically active land—serving as a proxy for biodiversity—declined from 472.42 km² (94.75% of the study area) in 1992 to 220.31 km² (44.19%) in 2022, amounting to a biodiversity area loss exceeding 50%. Thermal analysis detected statistically significant shifts in both minimum and maximum temperatures, with minimum temperatures increasing from 24.41℃ to 25.14℃ (p = 3.14 × 10⁻⁵) and maximum temperatures rising from 30.30℃ to 31.02℃ (p = 7.62 × 10⁻⁵). These findings indicate that urban sprawl has not only driven ecological degradation through habitat fragmentation and biodiversity depletion but has also exacerbated the urban heat island effect. The methodological integration of geospatial analysis, climate data, and urban biodiversity indicators demonstrates the utility of multidisciplinary approaches in diagnosing the environmental consequences of unregulated urbanization. The results underscore an urgent need for evidence-based urban planning and biodiversity-sensitive development policies tailored to rapidly expanding West African cities.
In light of the European Union’s 2050 decarbonization objectives, a fundamental transformation of urban energy systems is required—characterized by decentralization, decarbonization, and digitalization. Within this context, the Renewable Energy Community (REC) model has been identified as a pivotal mechanism for enabling the integration and equitable sharing of locally generated renewable energy, while simultaneously delivering environmental, social, and economic co-benefits. A systemic and place-based approach has therefore been proposed, in which the interactions among buildings, neighborhoods, and communities are holistically considered in the design and governance of urban energy systems. The operationalization of RECs has been shown to rely heavily on the deployment of digital technologies, including Information and Communication Technology (ICT) platforms, smart metering infrastructure, automated control of energy flows, and demand response mechanisms. These technologies serve not only to optimize energy efficiency and flexibility but also to enhance user engagement and energy awareness. A national standard recently published in Italy has formalized this integrated methodology, supporting the coordinated development of smart and low-carbon cities. Concurrently, innovative tools are being developed to facilitate decision-making and strategic planning for RECs at multiple spatial scales. Among them, the Italian geo-portal for RECs and the Public Energy Living Lab (PELL) have been introduced to support the acquisition, organization, and interpretation of territorial and urban energy data. These tools have also enabled the definition and monitoring of context-specific Key Performance Indicators (KPIs), critical for assessing the performance and scalability of REC initiatives. The framework presented herein contributes to the broader objectives of Smart Cities by enabling data-driven, participatory, and resilient energy transitions in urban contexts. Particular emphasis has been placed on harmonizing spatial data infrastructures with energy governance processes, thereby laying the groundwork for replicable and adaptable REC models across diverse territorial configurations.
The accelerating demand for sustainable energy solutions in urban environments has prompted the application of building-integrated photovoltaic (BIPV) systems in electric vehicles (EVs). This study assessed the impact of BIPV-EV systems in Surabaya, Indonesia, forecasting its energy production, environmental advantages, and economic viability between 2026 and 2036. Simulations conducted using HOMER Pro and photovoltaic system (PVsyst) suggested that the rooftop photovoltaic (RPV) capacity will increase from 4.6 GW in 2026 to 6.0 GW by 2036, while facade photovoltaic (FaPV) capacity is projected to grow from 1.6 GW to 2.0 GW. The combined generation of RPV and FaPV is anticipated to reach 9.71 GWh annually by 2036, ultimately reducing grid dependency to 36.6%. Additionally, carbon emissions from the BIPV-EV systems are expected to decrease from 616 tons per year in a grid-based scenario to 520 tons annually, hence reducing carbon intensity to 0.05 kg CO₂/kWh. Although the initial investment is projected at USD 3.2 billion and USD 4.8 billion in 2026 and 2036, respectively, the implementation of BIPV-EV systems is advantageous owing to significant savings on energy costs in the long run and decreasing reliance on fossil fuels. These findings underscored the potential of BIPV in advancing urban sustainability and accomplishing the objectives of energy transition in Indonesia.
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