Small-scale wind energy systems continue to attract attention as distributed renewable energy solutions; however, improving electrical output under varying operating conditions remains a challenge due to nonlinear interactions between environmental and operational parameters. This study investigates the optimization and predictive modelling of the current output of a tubular wind energy conversion system (WECS) through a statistically guided experimental framework. A response surface methodology based on central composite design (RSM–CCD) was employed to evaluate the combined influence of operating time and wind speed on system performance. Experimental observations were analysed using a quadratic polynomial model and analysis of variance (ANOVA) to establish the response relationship and identify operating conditions associated with improved electrical output. The results showed that the developed model achieved strong agreement between predicted and experimental responses with a coefficient of determination ($R^2$) of 0.962. Wind speed was identified as the dominant factor affecting current generation. The optimization analysis showed that the highest current output of 491.897 A was obtained at an operating time of 30 min and a wind speed of 6.88 m/s, corresponding to a desirability value of 0.998. The results indicate that the proposed modelling framework provides an effective approach for describing system response and identifying favourable operating conditions for compact wind energy systems. This study offers a practical methodology for experimental optimization and supports further development of data-driven performance enhancement strategies in renewable energy applications.

The 2030 Agenda for Sustainable Development faces considerable implementation challenges in border regions, where natural and socio‑economic processes transcend administrative boundaries. This study assesses progress towards selected Sustainable Development Goals (SDGs) in two Russian border regions: the Republic of Buryatia and Zabaikalsky Krai, which share borders with China and Mongolia, and identifies directions for bilateral cooperation based on the transboundary challenges. Based on official data from the Federal State Statistics Service of Russia for 2010–2024, the authors analysed 39 indicators covering SDGs 6, 8, 11, 13, 15 and 17. Growth rates were calculated and compared with national averages. The results reveal contrasting development models: Zabaikalsky Krai shows strong economic growth (gross regional product per capita index 114.3% in 2023) but critical deficits in access to quality drinking water (58.1% vs. national 89.2%), safe sanitation (49.2%), buses for persons with reduced mobility (3.2%), and protected forest areas (0.94%). The Republic of Buryatia performs better in social and environmental spheres (urban water access 86.0%, sanitation 80.5%, equipped buses 61.9%, reforestation ratio 247%) but lags economically—gross regional product (GRP) per capita index at 101.1%—and faces unique constraints from strict Baikal environmental norms (only 2.5% of wastewater meets those standards). Both regions suffer extreme wildfires and dispose of almost all municipal solid waste in landfills without recycling. The conclusions indicate that joint bilateral actions should include harmonised environmental standards and monitoring methodologies, creation of cross‑border demonstration zones, and coordinated wildfire and water management. These findings can inform regional strategies, bilateral environmental projects, and statistical harmonisation within BRICS and the Shanghai Cooperation Organisation.

This study assesses the degree to which adaptive governance principles are incorporated into four regional development planning documents of North Sumatra Province, aiming to manage the increasing energy crises and climate threats. Four aspects of adaptive governance are included in the analysis using a document-based evaluation framework: (1) reactivity to uncertainty; (2) scenario-based projection; (3) flexibility of development indicators; and (4) institutional coordinating capacity. The 2025–2045 Regional Long-Term Development Plan (Rencana Pembangunan Jangka Panjang Daerah, RPJPD), the 2025–2029 Technocratic Draft of the Regional Medium-Term Development Plan (Rencana Pembangunan Jangka Menengah Daerah, RPJMD), the 2024–2026 Regional Development Plan (Rencana Pembangunan Daerah, RPD), and the Development Planning Agency’s 2024–2026 Strategic Plan are among the documents examined. Document content was categorized using a qualitative thematic coding process in relation to the assessment matrix. The findings show that planning is still technocratic and linear, lacking institutional tools to facilitate adaptive decision-making, risk-responsive indicators, and alternative scenarios. This disparity indicates that the planning tools required to anticipate crisis-driven disruptions in the energy and environmental sectors are not aligned with the sustainability agenda. In order to improve provincial readiness and hasten the achievement of Sustainable Development Goals (SDGs) 7, 13, and 16, the study suggests integrating risk-based planning, dynamic performance indicators, and cross-sector institutional platforms.

This study aims to inform evidence-based policy for climate change adaptation in the Philippines by estimating the climate sensitivity of household electricity demand among select cities in Metro Manila during the COVID-19 pandemic. Localized climate data from 2001 to 2021 were matched to households based on their city of residence to construct measures of climate variability. Heat Index (HI), which combines temperature and relative humidity, provides a measure of perceived thermal discomfort. Cooling Degree Days (CDD), defined as the number of days when daily HI exceeds a long-run threshold of 34.82 °C (the 75th percentile of historical HI), serve as another indicator of exposure to extreme heat conditions. Correlated random effects (Mundlak) regressions reveal strong climate sensitivity of electricity use. Household electricity consumption increases when high temperature coincides with high humidity. A 1 °C rise in HI leads to a 19 kWh increase in monthly electricity use, while an additional CDD raises monthly consumption by about 6 kWh. The estimated positive relationship between temperature, humidity, and electricity consumption is consistent with increased demand for cooling services during periods of higher thermal stress. Overall, the results suggest that households adjust their electricity consumption in response to perceived heat conditions through a range of cooling-related behaviors. However, electricity demand among lower-income households is significantly less responsive to climate fluctuations, which may indicate limited adaptive capacity amidst greater thermal discomfort. Conversely, higher-income households exhibit greater responsiveness, highlighting their potential for targeted adoption of energy-efficient appliances and rooftop solar systems. The results underscore the importance of climate-sensitive energy policies that simultaneously advance climate mitigation goals and address equity concerns.

In this research, both Synthetic Aperture Radar (SAR) and optical satellite data are used independently to evaluate the urban expansion, thermal change (Land Surface Temperature (LST)/Urban Heat Island (UHI)), and particulate air quality (PM$_{10}$) ten-year forecasts for Dehradun, Uttarakhand, India for the decade 2014–2024. The Sentinel-1 C-band SAR data (backscatter amplitude $\sigma^{\circ}$ and interferometric coherence $\gamma$) provide a cloud-penetrating and structurally-based evaluation of urban extent. The data used include Landsat-8 OLI/TIRS, which are used for supervised classification of land use and land cover (LULC) by maximum likelihood. The maximum likelihood classification (MLC) and LST retrieval using Mono-Window Algorithm (MWA). The both sensors are processed through independent analytical pipelines and offering corroborating lines of evidence for urban change. The results show important environmental changes: There was an increase in urban area of +28.3 km$^2$ (+3.9%). agricultural land increased by +55.9 km$^2$ (+8.15%), while forest cover declined sharply by -83.1 km$^2$ (-12.05%)—figures with area adjusted uncertainty estimates. The mean LST increased by $\sim$+3.0 °C over the study transect, with mean annual air temperature rising from 21.22 °C to 24.21 °C (+14.1%), which is in line with the rise in temperature at the station, confirming intensification of the Surface Urban Heat Island (SUHI). The concentration of PM$_{10}$ at all the three Central Pollution Control Board (CPCB) monitoring stations it was consistently found that levels of SO$_2$ exceeded the national annual standard for India (60 $\mu$g/m$^3$) by 2.5–2.7 times throughout the study period. These are analyzed in a framework of Environmental Impact Assessment (EIA), which links to Identified land cover change to environmental impact pathways, management implications and policies Himalayan Mountain cities suggestions for urban planning, green space protection and air quality control.

Flexible inflatable structures play an important role in emergency sealing and protection systems where rapid deployment and adaptive contact with complex boundaries are required. However, the operational performance of inflatable sealing systems is strongly influenced by the coupled interaction among internal pressure evolution, nonlinear membrane deformation, and interface contact behaviour under confined conditions. This study investigates the pressure-deformation-contact coupling behaviour of a Z-fold inflatable barrier during the sealing process of an underground tunnel. A nonlinear finite element model was developed using ABAQUS, in which the Yeoh hyperelastic constitutive model was adopted to describe the large deformation behaviour of the membrane material. The inflation process was simulated using the fluid cavity method, and the interaction between the inflatable membrane and tunnel boundary was defined through contact analysis. The evolution of structural morphology, stress distribution, volume variation, and contact development was systematically analysed to reveal the coupled mechanical response of the sealing system. The results showed that the deployment process consisted of three successive stages, including gravitational descent, inflation-driven expansion, and stable sealing. The complete deployment process was achieved within approximately 30 s. The maximum von Mises stress during inflation was 12.15 MPa, while the stabilized stress decreased to approximately 10.13 MPa, remaining considerably below the material tensile strength of 200 MPa. The airbag volume increased from 0.16 m³ to 5.79 m³, and the final contact area with the tunnel wall reached 4.55 m², corresponding to a sealing coverage rate of 81.3%. The results indicate that the sealing performance of inflatable tunnel barriers is governed by the coupled evolution of pressure loading, nonlinear structural deformation, and boundary contact interaction. This study provides new insights into the multiphysics response mechanism of flexible inflatable systems and offers a numerical basis for the design and optimization of rapid-response sealing devices in underground engineering applications.

Photovoltaic technology has become one of the most promising approaches for sustainable electricity generation; however, its performance is strongly influenced by environmental conditions, including dust accumulation and operating temperature. In this study, the combined effects of dust deposition and panel tilt angle on the thermal behavior and electrical performance of photovoltaic modules were experimentally investigated under controlled artificial illumination generated by light bulbs. Five irradiance levels (100, 200, 300, 400, and 500 W/m²) were employed to simulate different operating conditions, while various dust loading levels and panel tilt angles were systematically evaluated. The results demonstrated that the tilt angle significantly affected photovoltaic performance. As the dust loading increased, the panel's temperature rose. Although electrical power generation was successfully achieved through the bulbs, the output remained substantially low. Dust deposition reduced the amount of incident solar radiation reaching the photovoltaic modules, thereby decreasing electrical power generation and energy conversion efficiency. These findings provide valuable experimental evidence for optimizing photovoltaic system installation and maintenance in dusty environments and contribute to the development of more efficient and sustainable photovoltaic energy systems.

Signalized intersections often cause congestion. Factors contributing to congestion include the high proportion of intersections operating beyond their capacity and malfunctioning traffic signals. This study aims to develop a sustainable model for signalized intersections in border areas. Primary data were collected by calculating the number of motorized vehicles at each intersection and obtaining expert opinions through focus group discussions (FGDs) to determine the relevant attributes and dimensions. The results from the five signalized intersections show that the Salabenda intersection achieved the highest technological dimension score (72.33%), indicating that technological sustainability is well developed and measurable. The Semplak intersection also demonstrated a strong technological dimension (62.36%), reflecting the implementation of measurable traffic management technology. The Bubulak intersection obtained a social dimension score of 57.71%, indicating that social sustainability, including accessibility and public service aspects, is relatively well implemented. The POMAD intersection achieved an ecological dimension score of 59.44%, showing that environmental considerations are becoming more prominent in traffic management. In the institutional dimension, the Bubulak intersection scored 50.00%, indicating that institutional coordination and management are moderately measurable. Meanwhile, the Ciawi intersection obtained the lowest score in the economic dimension (42.97%), suggesting that economic sustainability still requires improvement. The new simulation model produced four scenarios: sustaining intersection functions through technology, collaborative management of transportation infrastructure for both road and rail systems, and sustainable accessibility control based on the characteristics of border areas. Strengthening the institutional dimension, including interregional cooperation, requires more effective policy and decision-making processes. The novelty of this research lies in the system model node (SYSMODE) concept. This single-point system concept provides benefits across all five sustainability dimensions. The implementation of this five-dimensional model at each intersection must be carried out properly and in a controlled manner. The proposed model is expected to improve the performance of signalized intersections for both road and rail transportation, supported by complete and measurable infrastructure facilities in border areas.