Search Results (4,444)

This study examines how mothers raising children with disabilities in American Samoa experience the processes of seeking diagnosis, navigating special education, and advocating for services within an insular rural context. American Samoa, an unincorporated U.S. territory located 2600 miles from Hawaiʻi with a population under 50,000, represents a case of what we term insular rurality—a condition in which the structural disadvantages of rurality are intensified by oceanic isolation, territorial governance, and colonial history. Data were collected through three focus groups with fifteen mothers whose children hold a range of disability diagnoses, with a card sort activity at the outset of each session serving as an idiographic anchor to protect individual voice within the group format. Analysis followed Interpretative Phenomenological Analysis adapted for focus groups (IPA-FG), proceeding from line-by-line exploratory noting through Personal Experiential Themes and Group Experiential Themes within each focus group case to cross-case convergence and divergence analysis, interpreted through the Fonofale model of Pacific wellness. Findings reveal two overarching themes: systemic invalidation, in which mothers encountered deficit-based assumptions, stagnant educational goals, and institutional disengagement; and parent peer support as the primary infrastructure, in which mothers became de facto experts, built community-driven solutions, and envisioned more inclusive futures. Technology emerged as a contradictory force—valuable for parent learning but largely ineffective for children’s remote therapy. These findings suggest how workforce shortages and geographic isolation create conditions in which maternal advocacy becomes a systems-level necessity rather than a personal choice. Implications for rural education policy, IDEA implementation in U.S. territories, and culturally grounded family support are discussed. Full article

Tourism plays an increasingly important role in promoting economic growth and rural revitalization in ecologically fragile regions. However, tourism systems in Tibet–related areas of Sichuan, China, are highly vulnerable to natural disasters, ecological degradation, and regional development imbalances, posing challenges to sustainable tourism development. This study aims to evaluate tourism system resilience and identify its key influencing factors from a sustainability perspective. Based on the regional characteristics of Tibet-related areas in Sichuan, a comprehensive evaluation framework is constructed covering four subsystems: tourism infrastructure and scale, economy, society, and ecology. An integrated entropy weight–analytic hierarchy process (AHP) model, coupling coordination model, and obstacle degree model are employed to assess tourism system resilience and examine subsystem interactions using panel data from 2011 to 2020. The results indicate that: (1) the resilience levels of tourism subsystems show no clear spatial or temporal regularity across the study areas; (2) ecological resilience remains significantly lower than tourism, economic, and social resilience, representing the weakest component of the tourism system; (3) the coupling coordination among subsystems remains at a low level, suggesting insufficient synergy for sustainable regional development; and (4) ecological constraints are the primary limiting factors affecting overall tourism system resilience. This study contributes to sustainable tourism research by revealing the critical role of ecological governance and subsystem coordination in enhancing tourism resilience in ecologically sensitive regions. Policy implications include strengthening ecological protection, improving tourism infrastructure, promoting digital tourism marketing, and advancing rural revitalization to achieve long-term sustainable development. However, this study is limited by data availability and the spatial scope of the selected case-study areas, which may affect the generalizability of the findings. Full article

This study investigates the spatiotemporal dynamics of peri-urban expansion and land use transformation in Izmir, Türkiye, over 36 years (1986–2022) using an integrated GIS-based Multi-Criteria Decision Analysis (MCDA) framework. Multi-source datasets, including Landsat imagery, CORINE land cover (CLC) data, demographic statistics, and spatial variables (slope, transportation proximity, and distance to the city center), were combined to delineate urban, peri-urban, and rural zones. Results reveal a substantial percentage increase in urban areas from 2.8% in 1986 to 10.48% in 2022, corresponding to an expansion of approximately 7.6% (≈908.56 km²). In contrast, agricultural land declined by 5.8%, while forest areas experienced a more severe reduction of 19.1%, indicating significant environmental degradation. Population dynamics further support this transformation, with peri-urban districts exhibiting growth rates exceeding the metropolitan core average of 1.8% (1986–2010), followed by a relative slowdown to 0.5% after 2010, accompanied by outward migration-driven expansion. Spatial analysis demonstrates that peri-urban growth is strongly influenced by accessibility and topography, with development concentrated within 30–50 km of the city center and along major transportation corridors (500–1000 m buffers). Land Surface Temperature (LST) analysis indicates increasing urban heat island intensity, with surface temperatures ranging from 12 °C to 46 °C, particularly in densely built inner peri-urban zones. The MCDA-based classification identifies distinct inner and outer peri-urban belts, characterized by contrasting density, land use patterns, and environmental pressures. Overall, the findings highlight that Izmir’s peri-urbanization is a heterogeneous and rapidly evolving process driven by demographic, spatial, and policy-related factors. The study provides a replicable methodological framework and emphasizes the urgent need for integrated, sustainability-oriented planning strategies to mitigate ecological loss and uncontrolled urban sprawl. Full article

Farmers’ investment decisions can shape their capacity to implement practices consistent with sustainable development objectives. The article identifies the declarative structure of investment decisions on Polish dairy farms based on a survey and diverse theoretical frameworks (resource-based view, institutional approach, real options theory, behavioural theory, and the theory of planned behaviour). The purpose is to identify the determinants of the extent and structure of declared agricultural investments. The authors determined the relationships between declared investments and groups of variables and identified investment axes and interdependencies. Investment decision predictions are founded on logistic regression, an SEM model for relationship structuring, and residual correlation analysis for mapping relationships and evaluating the correlation demasking effect, according to which raw correlations between investment axes may hide underlying residual associations between them. We found that declared farmland investments were associated with milk production volume and appeared to be linked to long-term farm development objectives. The respondents became less keen on investing in livestock production as they aged, whereas older farmers showed a greater propensity to undertake energy-related investments. These results suggest that farmers’ declared investment intentions may be consistent with conditions conducive to achieving sustainable development objectives through their potential association with farm viability, resource-use efficiency, and rural economic development. Our findings may have potential policy relevance by informing the design of public measures aimed at strengthening farms’ adaptive capacity in the context of sustainability transitions. Full article

The sustainable transformation of idle built environments represents a critical pathway for advancing low-carbon development and achieving carbon neutrality targets. This study examines how idle rural building stocks may contribute to sustainable built environment systems through rural building repurposing and regeneration strategies. It introduces the concept of Green Rural Centers (GRCs), multifunctional facilities formed through the adaptive reuse of idle buildings that integrate low-carbon design, community services, and local economic functions. Within the proposed framework, GRCs are conceptually characterized as facilities that may: (1) achieve 50–70% reductions in operational energy demand through passive and renewable measures, (2) incorporate two or more community-oriented functions (e.g., education, governance, cultural services), and (3) demonstrate embodied carbon savings of ≥40% compared to demolition-and-rebuild scenarios. Grounded in fieldwork from Fujian Province, China, and aligned with national policies, the study evaluates spatial transformation, carbon mitigation, and institutional integration. Using a mixed-methods approach that combines scenario-based carbon-reduction estimation and appraisal, spatial analysis, comparative case studies, and policy evaluation, the findings indicate that retrofitting 30% of approximately 68,000 idle rural schools could achieve approximately 734,400 metric tons of cumulative CO₂ reduction by 2060 under the baseline scenario. Under conservative and ambitious implementation conditions, the estimated cumulative reductions are approximately 408,000 and 1,224,000 metric tons of CO₂, respectively. Sensitivity analysis shows that moderate improvements in retrofit quality or implementation rates significantly amplify emissions reduction outcomes. Beyond environmental performance, the proposed framework may also support community resilience, decentralized service provision, and socio-economic revitalization. This research reframes idle building stock as a strategic asset within sustainable built environment systems, policy-relevant exploratory framework potentially adaptable to comparable rural contexts. This study contributes to the sustainable built environment discourse by demonstrating how underutilized rural building stocks can function as broader low-carbon rural regeneration systems. Full article

Rural household energy-saving behavior is central to low-carbon development in ecologically fragile plateau regions. This study explores whether climate risk perception promotes household energy-saving behavior, through which livelihood capital mechanisms this effect operates, and which livelihood capital configurations support high levels of such behavior. Drawing on survey data from 315 rural households in Xining, China, a sustainable livelihood framework is integrated with the pressure–state–response model, and PLS-SEM, an ANN, and fsQCA are applied. The integrated framework regards climate risk perception as external pressure, livelihood capital as the household livelihood state, and energy-saving behavior as the behavioral response. The sustainable livelihood framework identifies the multidimensional resource conditions of rural households, whereas the pressure–state–response model specifies the causal sequence through which perceived climate pressure affects livelihood states and induces behavioral responses. The results show that climate risk perception significantly promotes energy-saving behavior. Physical, human, and social capital exert positive effects, whereas natural and financial capital exert negative effects. Moreover, natural, financial, and social capital significantly mediate the link between climate risk perception and energy-saving behavior. Multi-group analysis shows that physical capital matters more for agriculture-dominated households than non-farm households. The ANN results identify social and human capital as the strongest predictors, and the fsQCA results show that high levels of energy-saving behavior arise not from any single condition but from multiple capital configurations, in which social capital is consistently central. Energy conservation under climate risk is therefore best understood as a multidimensional, nonlinear adaptation process embedded in household livelihood structures rather than a response to any single factor. These findings extend rural energy-saving research by linking climate pressure, livelihood conditions, and configurational decision logic in a plateau socio-ecological context. Policy interventions should combine energy-efficient infrastructure, targeted financial incentives, community-based diffusion, and livelihood-sensitive support for rural households. Full article

We propose a quantitative, spatially explicit framework for assessing local self-sufficiency and resilience within the Water–Energy–Food (WEF) Nexus. The methodology introduces normalized, per capita indicators that quantify the degree of dependence on local versus external resources, explicitly incorporating physical availability, renewability, energy requirements, infrastructure, and land-use constraints. In contrast to conventional composite indices, the proposed framework adopts a non-compensatory structure, whereby deficiencies in one sector cannot be offset by surpluses in another, reflecting the physical constraints of the nexus. Indicator values range from 0 (complete dependence on external resources) to 1 (full local self-sufficiency) and are formulated dynamically, enabling comparison across existing conditions and alternative infrastructural or policy scenarios. The framework is applied as a proof of concept to a small rural settlement in North Euboea, Greece. The results indicate substantial potential for food and renewable energy self-sufficiency under optimized infrastructure configurations, while also revealing critical vulnerabilities associated with groundwater-dependent water supply and seasonal energy imbalances. The analysis further demonstrates how spatial proximity, energy–water coupling, and land-use competition jointly constrain achievable self-sufficiency levels, highlighting trade-offs that are often overlooked in sectoral or purely volumetric assessments. By explicitly linking resource flows with spatial proximity and infrastructural choices, the proposed indicators provide a robust and transparent tool for resilience-oriented planning under conditions of climatic, environmental, and systemic uncertainty. Full article

Northeast China is one of China’s major commodity grain bases and plays a strategic role in national food security. Against the background of rural population outflow and agricultural modernization, new agricultural business entities (NABEs), including family farms, farmers’ cooperatives, and agribusinesses, have become important actors in reshaping agricultural production organization. Based on registration data for 2014, 2018, and 2023, this study uses kernel density estimation (KDE), standard deviational ellipse (SDE) analysis, spatial autocorrelation analysis, ordinary least squares (OLS) regression, and multiscale geographically weighted regression (MGWR) to examine the spatiotemporal patterns and driving factors of NABEs in Northeast China. The results show that: (1) NABEs expanded rapidly from 2014 to 2023 and became increasingly concentrated in agriculturally advantageous plain areas. (2) Family farms showed the fastest expansion, farmers’ cooperatives had the widest spatial coverage, and agribusinesses were mainly concentrated around transport corridors and market nodes. (3) In terms of industrial structure, crop-production entities remained dominant, followed by animal husbandry entities, while forestry, fishery, and agricultural support service entities accounted for relatively small shares; however, their numbers continued to increase. (4) The OLS results showed that the reclamation rate and road network density had relatively stable associations with the spatial distribution of multiple entity types, whereas economic development, science and technology investment, and fiscal support showed differentiated relationships across entity types and regions. (5) The MGWR results further reveal spatial heterogeneity in the effects of driving factors. These findings provide empirical evidence for type-specific cultivation and differentiated policy support for NABEs in major grain-producing areas. Full article

Air pollution is an emerging environmental and public health concern in Uganda; however, the evolution of atmospheric pollution research in the country has not been comprehensively synthesized. This study presents a scoping review of peer-reviewed literature published between 1990 and 2025, examining the temporal trends in research output, key pollutants investigated, the study environments and research methodological approaches. A structured literature search was conducted across three academic databases (Google Scholar, Web of Science, and PubMed) and eligible studies were screened and analysed using a standardized data extraction framework. The results reveal highly uneven growth in research output, with minimal activity prior to 2010, followed by rapid expansion after 2015 and a pronounced surge between 2020 and 2025. Particulate matter (PM_2.5 and PM₁₀) dominated the literature across all periods, while gaseous pollutants such as NO₂, SO₂, CO, and O₃ were comparatively underrepresented. Most studies were conducted in urban environments, particularly in Kampala, whereas rural ambient monitoring remained limited. Methodologically, the literature evolved from proxy-based and gravimetric approaches to the increased use of low-cost sensors, portable monitors and satellite-derived data. Despite recent advances, the predominance of short-term and spatially constrained studies highlights persistent gaps in long-term and nationally representative air quality monitoring. This review synthesizes trends, methodological developments, and evidence gaps in atmospheric pollution research in Uganda over a 35-year period, providing a foundation for strengthening future monitoring and policy frameworks. Full article

The aesthetic value of agricultural landscapes is gaining importance as rural tourism burgeons during urbanization. To ascertain key elements influencing the visual appeal of agricultural landscapes, this research employed a visual choice experiment in Hangzhou Plain during the spring flowering period to assess public preferences for four landscape attributes in ground and aerial perspectives. The mixed logit model was utilized to evaluate the respondents’ average preference, while the latent class logit model helped in identifying distinct preference groups. The research revealed that participants exhibited different preferences between the two perspectives. The diversity within public preferences was highlighted, with respondents favoring oilseed rape-dominated landscapes with a single agricultural land cover proportion in ground perspective while favoring diverse landscapes in aerial perspective. Gender, education level, landscape familiarity, connection to agriculture, and membership in relevant organizations significantly shape individual preferences. These results can help refine multi-objective policy targeting by incorporating aesthetic value perspective in agricultural landscapes. Full article

As the global energy transition accelerates, distribution systems are integrating increasing shares of inverter-interfaced renewables, making reliable voltage support a key operational requirement. In grid-connected microgrids, especially weak radial feeders in rural and remote areas, voltage-reactive power (Volt/Var) control must coordinate multiple inverters under uncertainty from photovoltaic (PV) intermittency, load volatility, and point-of-common-coupling (PCC) disturbances. Existing droop, model-based optimization, and non-graph reinforcement learning (RL) approaches often rely on fixed rules or do not explicitly exploit electrical topology, which limits adaptive coordination. To address this gap, we propose a topology-aware graph reinforcement learning framework for voltage-reactive power control in grid-connected microgrids under uncertainty. The method encodes node states with a graph convolutional network (GCN) and learns coordinated PV/storage reactive-power actions via proximal policy optimization (PPO) with a multi-objective reward balancing voltage quality, control effort, and action smoothness. In a controlled comparison against a multilayer perceptron (MLP)-PPO baseline with identical action space, reward, and PPO objective, our method reduces voltage violation rate (VVR) from 0.0316 ± 0.0086 to 0.0048 ± 0.0019. Additional validation on a modified IEEE 33-bus feeder further reduces VVR from 0.00726 for MLP-PPO and 0.02999 for Droop control to 0.00095, supporting the effectiveness of topology-aware state representation on a larger radial benchmark feeder. Full article

Agrivoltaic systems, which enable simultaneous crop production and solar photovoltaic (PV) electricity generation on the same land, can support climate mitigation, food security, and rural development. Leguminous crops like beans are globally important, yet there is limited performance studies on diverse agrivoltaic trials. This limits appropriate policy guidance. To overcome these limitations, this study assessed organic green bush bean performance under thirteen PV configurations with varying transparency and spectral properties, comparing both agricultural outcomes against national yields and policy standards. The results in vegetative metrics indicated that blue-spectrum thin-film and intermediate-transparency c-Si modules supported growth near German productivity thresholds. Although no agrivoltaic system matched national average yields, combining crop and energy revenues revealed substantial benefits: the 44%—transparent c-Si configuration generated 340% more total revenue than traditional farming, and the blue 70%—transparent thin-film system achieved 94% of national yield but 164% of conventional farm revenue per acre. Electricity generation gains outweighed modest crop reductions, highlighting strong synergies between food and energy. The results of this study highlights the potential of agrivoltaic systems to enhance land-use efficiency, support renewable energy expansion, and improve rural economic resilience, while underscoring the need for multi-year trials and site-specific controls to validate long-term sustainability outcomes. Full article

Fostering the coupled and coordinated progress of agricultural pollution control and carbon emission reduction (AGR) is integral to agricultural modernization and high-quality agricultural development. As China’s green finance policies have been steadily refined, green finance has emerged as a pivotal driver of AGR enhancement. To examine the influence of green finance on AGR, this study analyzes their nexus over the 2008–2023 period. The results demonstrate that green finance markedly improves AGR, and this effect exhibits heterogeneity. In terms of mechanism, green finance strengthens AGR by bolstering agricultural technological innovation (INN) and raising farmers’ income (INC). Agricultural fiscal support (FIN) and the state of rural education (EDU) serve as important external conditions for green finance to effectively promote AGR. The findings further suggest that green finance is progressively evolving into a major force for advancing AGR. Full article

Rural electrification in Sub-Saharan Africa faces a trilemma: cutting carbon emissions, making it economically viable, and achieving fair access to energy for all. This paper develops a multi-objective framework that optimises carbon revenue, net present value (NPV), total energy supply, cooking fuel (firewood and LPG), health costs, and benefit to society. The model uses continuous decision variables: daily energy allocation among four sources (solar, generator, firewood, LPG) to three population groups (men, women, children). The case study is a rural community of 7000 people in Nigeria (Tier 1 energy consumers). Six policy scenarios are considered: baseline, high carbon price, low carbon price, microfinance, government subsidy and community cooperative. This study compared algorithms and identified a hybrid Non-dominated Sorting Genetic Algorithm and Particle Swarm Optimisation II as the most suitable algorithm for solving the formulated optimisation problem. It was found that NPV and unit cost of energy would increase to $175,500 and 26.4 ¢/kWh, respectively, by increasing the price of carbon from $8/ton to $12/ton. Firewood generates health savings and carbon revenue in the range of $4100–$12,270/year. Prices below $8/ton do not induce optimal reconfigurations in the system. The best energy supply (2825 kWh/day) and the lowest unsatisfied demand occur in the government subsidy scenario with the greatest disparity index, displaying an equity-efficiency trade-off. The framework shows that sustainable access to energy can be unlocked using strategic integration of carbon finance, valuation of health benefits and equity constraints. Full article

Background/Objectives: Prostate biopsy is essential for diagnosing prostate cancer. Social determinants of health (SDOH), including socioeconomic status, race, occupation, education, and environment, affect access, outcomes, and quality of life. Recognizing disparities from technology access to complications is crucial for equitable care. A systematic review examined how SDOH impacts biopsy access, technology, and complications. Methods: A systematic search of PubMed, Web of Science, and Scopus was performed to identify eligible studies published through February 2026. We included studies that evaluated the association between one or more SDOHs and prostate biopsy. Relevant outcomes included biopsy utilization, use of specific biopsy technologies (e.g., magnetic resonance imaging (MRI)-guided, transperineal), and post-procedural complications. Results: Nine observational studies met the inclusion criteria. The findings revealed disparities across three key domains. First, access to advanced biopsy technology was uneven. Four studies showed that Black men were significantly less likely than White men to receive MRI-guided biopsies. Additionally, post-biopsy outcomes showed that Black and Hispanic men faced significantly higher rates of post-biopsy infection and hospitalization compared to White men. Lastly, patients in rural areas, those in public hospitals, and individuals with lower socioeconomic status demonstrated reduced access to modern techniques, including MRI-guided or transperineal biopsy. Conclusions: Social and economic factors influence who receives a prostate biopsy and who has access to advanced technologies. Minority and low-income patients face diagnosis barriers and higher complication rates, highlighting systemic inequities. The healthcare system often rewards access over need, and without bold policy changes, gaps in technology and resources will worsen, moving us further from truly equitable prostate cancer care. Full article