Search Results (2,142)

This paper aims to conduct a gap analysis and explore the potential for greenhouse gas (GHG) emissions reduction in the tourism sector of Chiang Mai province, with the goal of promoting sustainable tourism. Chiang Mai is a major tourism hub in Thailand, located in the Northern Economic Corridor (NEC). The gap analysis of small- and medium-sized tourism enterprises will be examined across four dimensions: (1) management, (2) socio-economy, (3) cultural, and (4) environmental. In 2024, Chiang Mai’s tourism revenue accounted for 46.97% of the northern region’s total tourism revenue and 3.73% of Thailand’s total tourism revenue. Given this economic significance, the development of sustainable tourism should be accelerated to meet the expectations of new tourists who are increasingly concerned about the environment. To address this need, this study analyzes the gaps in small- and medium-sized tourism enterprises and assesses GHG emissions through interviews and surveys of 90 tourism-related establishments across nine sectors: hotels, restaurants and beverages, tour agencies, transportation, souvenirs, attractions and activities, spas and wellness, community-based tourism, and farm tourism. The total GHG emissions from these establishments were found to be 15,303.72 tCO₂eq. Moreover, if renewable energy from solar power were adopted, an installation capacity of 21,866.84 kWp would be required. Such a transition would not only reduce emissions, but also support low-carbon development in small- and medium-sized tourism enterprises and ultimately contribute to achieving net-zero tourism. Finally, this study contributes to the advancement of STGs 1–17, adapted from the SDGs 1–17, with particular emphasis on SDG 7 on clean energy and SDG 13 on climate change. Full article

As global demand for clean and renewable energy continues to rise, wind power has become a critical component of the sustainable energy transition. However, the increasingly complex operating conditions and structural configurations of modern wind turbines pose significant challenges for system reliability and control. Specifically, accurate load torque estimation is crucial for supporting the long-term stable operation of the wind power system. This paper presents a novel load torque estimation approach based on a nonlinear extended state observer (NLESO) for wind turbines with permanent magnet synchronous generators. In this method, the load torque is estimated using current measurements and observer-derived acceleration, thereby eliminating the need for torque sensors. This not only reduces hardware complexity but also improves system robustness, particularly in harsh or fault-prone environments. Furthermore, the stability of the observer is rigorously proven through Lyapunov theory using the variable gradient method. Finally, simulation results under different wind speed conditions validate the method’s accuracy, robustness, and adaptability. Full article

This study proposes methods of computer simulation to study and optimize the cybersecurity of Small Modular Nuclear Reactors (SMRs). SMRs hold the potential to help build a clean and sustainable power grid but will struggle to gain widespread adoption without public confidence in their security. SMRs are emerging technologies and potentially carry higher cyber threats due to remote operations, large numbers of cyber-physical systems, and cyber connections with other industrial concerns. A method of agent-based computer simulations to model the effects, or payoff, of collaboration between cyber defenders, power plants, and cybersecurity vendors is proposed to strengthen SMR cybersecurity as these new power generators enter into the market. The agent-based model presented in this research is intended to illustrate the potential of using simulation to model a payoff function for collaborative efforts between stakeholders. Employing simulation to heighten cybersecurity will help to safely leverage the potential of SMRs in a modern and low-emission energy grid. Full article

Hydrogen is a sustainable, clean source of energy and a viable alternative to carbon-based fossil fuels. To support the transport sector’s transition from fossil fuels to hydrogen, a hydrogen refuelling station network is being developed to refuel hydrogen-powered vehicles. However, hydrogen’s inherent properties present a significant safety challenge, and there have been several hydrogen incidents noted, with severe impacts to people and assets reported from operational hydrogen refuelling stations worldwide. This paper presents the outcome of an analysis of hydrogen incidents that occurred at hydrogen refuelling stations. For this purpose, the HIAD 2.1 and H2tool.org databases were used for the collection of hydrogen incidents. Forty-five incidents were reviewed and analysed to determine the frequent equipment failures in the hydrogen refuelling stations and the underlying causes. This study adopted a mixed research approach for the analysis of the incidents in the hydrogen refuelling stations. The analysis reveals that storage tank failures accounted for 40% of total reported incidents, hydrogen dispenser failures accounted for 33%, compressors accounted for 11%, valves accounted for 9%, and pipeline failures accounted for 7%. To enable the safe operation of hydrogen refuelling stations, hazards must be understood, effective barriers implemented, and learning from past incidents incorporated into safety protocols to prevent future incidents. Full article

Hydrogen energy offers high energy density and carbon-free combustion, making it a promising fuel for next-generation propulsion and power generation systems. Hydrogen offers approximately three times more energy per unit mass than natural gas, and its combustion yields only water as a byproduct, making it an exceptionally clean and efficient energy source. Materials used in hydrogen-fueled combustion engines must exhibit high thermal stability as well as resistance to corrosion caused by high-temperature water vapor. This study introduces a novel ceramic matrix composite (CMC) designed for such harsh environments. The composite is made of yttria-stabilized zirconia (YSZ) fiber-reinforced silicoboron carbonitride [Si(B)CN]. CMCs were fabricated via the polymer infiltration and pyrolysis (PIP) method. Multiple PIP cycles, which help to reduce the porosity of the composite and enhance its properties, were utilized for CMC fabrication. The Si(B)CN precursor formed an amorphous ceramic matrix, where the presence of boron effectively suppressed crystallization and enhanced oxidation resistance, offering superior performance than their counter part. Thermogravimetric analysis (TGA) confirmed negligible mass loss (≤3%) after 30 min at 1350 °C. The real-time ablation performance of the CMC sample was assessed using a hydrogen torch test. The material withstood a constant heat flux of 185 W/cm² for 10 min, resulting in a front-surface temperature of ~1400 °C and a rear-surface temperature near 700 °C. No delamination, burn-through, or erosion was observed. A temperature gradient of more than 700 °C between the front and back surfaces confirmed the material’s effective thermal insulation performance during the hydrogen torch test. Post-hydrogen torch test X-ray diffraction indicated enhanced crystallinity, suggesting a synergistic effect of the oxidation-resistant amorphous Si(B)CN matrix and the thermally stable crystalline YSZ fibers. These results highlight the potential of YSZ/Si(B)CN composites as high-performance materials for hydrogen combustion environments and aerospace thermal protection systems. Full article

This study presents a comparative analysis of electrocardiogram (ECG) and accelerometer (ACC) data in the context of unsupervised human activity recognition and subject identification. Recordings were obtained from 30 participants performing activities of daily living such as walking, sitting, lying, cleaning the floor, and climbing stairs. Distance-based signal comparison methods and clustering techniques were employed to evaluate the feasibility of each modality, both individually and in combination, to discriminate between individuals and activities. Results indicate that ACC signals provide superior performance in activity recognition (NMI = 0.728, accuracy = 0.817), while ECG signals show higher discriminative power for subject identification (NMI = 0.641, accuracy = 0.500). In contrast, combining ACC and ECG signals yielded lower scores in both tasks, suggesting that multimodal fusion introduced additional variability. These findings highlight the importance of selecting the most appropriate modality depending on the recognition objective and emphasize the challenges associated with multimodal approaches in unsupervised scenarios. Full article

This research investigated how detergent type and concentration, solution temperature, and flow rate affect ultrasonic cleaning efficiency in jewelry manufacturing. A silver bracelet without gemstones served as the test sample, and the study combined harmonic response analysis to assess acoustic pressure distribution with computational fluid dynamics to examine fluid flow patterns inside an ultrasonic cleaning machine. Cleaning tests were performed under real factory conditions to verify the simulations. Results showed that cleaning efficiency depends on the combined chemical and ultrasonic effects. Adding detergent lowered surface tension, encouraging cavitation bubble formation; higher temperatures (up to 60 °C) softened dirt, making removal easier; and moderate solution flow improved the cleaning, helping to carry dirt away from jewelry surfaces. Too much flow, however, decreased cavitation activity. The highest cleaning efficiency (93.890%) was achieved with 3% U-type detergent at 60 °C and a flow rate of 5 L/min, while pure water at room temperature (30 °C) without flow had the lowest efficiency (0.815%), confirmed by weighing and scanning electron microscope measurements. Interestingly, maximum ultrasonic power concentration did not always match the highest cleaning efficiency. The study supports sustainable practices by limiting detergent use to 3%, in line with Sustainable Development Goal (SDG) 9 (Industry, Innovation, and Infrastructure). Full article

With the global energy transition and decarbonization goals, tower-type solar thermal power generation is increasingly important for dispatchable clean energy due to its high efficiency, thermal storage capacity, and regulation performance. However, current research focuses on ideal conditions, ignoring real geographical constraints on heliostat layout and environmental impacts on receiver performance. More practical scene modeling and performance evaluation methods are urgently needed. To address these issues, we propose a heliostat field simulation algorithm based on heat loss mechanisms and real site characteristics. The algorithm includes optical performance evaluation (cosine efficiency, shading, truncation, atmospheric transmittance) and heat loss mechanisms (radiation, convection, conduction) for realistic net heat output estimation. Experiments revealed the following: (1) higher central towers improve optical efficiency by increasing solar elevation angle; (2) radiation losses dominate at high power and tower height, while convection losses dominate at low power and tower height. Using the Economic-Integrated Score (EIS) optimization algorithm, we achieved optimal tower and receiver configuration with 40.22% average improvement over other configurations (maximum 3.9× improvement). This provides a scientific design basis for improving tower-type solar thermal systems’ adaptability and economy in different geographical environments. Full article

This research presents Geographic Information System (GIS) mapping and development of biomass for combined heat and power (CHP) generation in Nigeria. It includes crop and forest classification, thermodynamic, and exergo-economic analyses using ArcGIS, Engineering Equation Solver, and Microsoft Excel. Syngas generated from biomass residues powered an integrated CHP system combining a gas turbine (GT), dual steam turbine (DST), and a cascade organic Rankine cycle (CORC) plant. The net power output of the integrated system stood at 2911 MW, with a major contribution from the gas turbine cycle (GTC) unit. The system had a total exergy destruction of 6480 MW, mainly in the combustion chamber (2143 MW) and HP-HRSG (1660 MW), and produced 3370.41 MW of heat, with a flue gas exit temperature of 74 °C. The plant’s energy and exergy efficiencies were 87.16% and 50.30%, respectively. The BCHP system showed good economic and environmental performance, with an annualized life cycle cost of USD 93.4 million, unit cost of energy of 0.0076 USD/kWh, and a 7.5-year break-even. The emissions and impact factors align with those of similar existing plants. It demonstrates that biomass residue can significantly support Nigeria’s energy needs and contribute to clean energy goals under the Paris Agreement and UN-SDGs. This work suggests a pathway to tackle energy insecurity, inform policymakers on biomass-to-energy, and serve as a foundation for future techno-economic–environmental assessment of biomass residues across suitable locations in Nigeria. Full article

Plant microbial fuel cells (PMFCs) represent an eco-friendly solution for generating clean energy by converting biological processes into electricity. This work presents the first integration of tin sulfide (SnS)-coated 304 stainless steel (SS304) electrodes into Aloe vera-based PMFCs for enhanced energy harvesting. SnS thin films were obtained via chemical bath deposition and screen printing, followed by thermal treatment. X-ray diffraction (XRD) revealed a crystal size of 15 nm, while scanning electron microscopy (SEM) confirmed film thicknesses ranging from 3 to 13.75 µm. Over a 17-week period, SnS-coated SS304 electrodes demonstrated stable performance, with open circuit voltages of 0.6–0.7 V and current densities between 30 and 92 mA/m², significantly improving power generation compared to uncoated electrodes. Polarization analysis indicated an internal resistance of 150 Ω and a power output of 5.8 mW/m². Notably, the system successfully charged a 15 F supercapacitor with 8.8 J of stored energy, demonstrating a practical proof-of-concept for powering low-power IoT devices and advancing PMFC applications beyond power generation. Microbial biofilm formation, observed via SEM, contributed to enhanced electron transfer and system stability. These findings highlight the potential of PMFCs as a scalable, cost-effective, and sustainable energy solution suitable for industrial and commercial applications, contributing to the transition toward greener energy systems. These incremental advances demonstrate the potential of combining low-cost electrode materials and energy storage systems for future scalable and sustainable bioenergy solutions. Full article

Recently, there has been a surge in the popularity of renewable energy systems due to their lucrative and sustainable attributes. Among these, photovoltaic (PV) systems stand out as prominent examples. Nevertheless, it is imperative to ascertain the management of waste produced by these systems in order to mitigate environmental pollution and harness their economic potential. This study aims to assess the present status and forecast the accumulation of waste generated by PV power plants in Chile. Utilizing openly available public data, a database is constructed to track the accumulation of waste. Two scenarios, namely, early-loss and regular-loss scenarios are employed to estimate the projected accumulation of PV waste. The findings indicate that by the years 2035 and 2043, the accumulation of waste is estimated to reach 100,000 tons under the early-loss scenario and regular-loss scenario. The total anticipated waste from solar PV modules is projected to be 284,906 tons, with c-Si PV modules contributing 175,595 tons to this total in Chile. Remarkably, it is determined that more than 235,000 tons of materials from this waste is recoverable, amounting to nearly USD 781 million in economic value. Silver is projected to bring the most economic value, with nearly USD 379 million, while lead, tin, cadmium, and zinc are each valued at less than USD 1 million. This study highlights the importance of promoting the sustainable development of PV systems, particularly in alignment with Sustainable Development Goals 7 (Affordable and Clean Energy) and 13 (Climate Action). Future research is expected to place greater emphasis on eco-design approaches in PV module production. Full article

Against the backdrop of the global transition towards clean energy, deep-sea wind-power hydrogen production integrates offshore wind with green hydrogen technology. Addressing the technical coupling complexity and the impact of uncertain hydrogen prices, this paper develops a capacity optimization model. The model incorporates floating wind turbine output, the technical distinctions between alkaline (ALK) electrolyzers and proton exchange membrane (PEM) electrolyzers, and the synergy with energy storage. Under three hydrogen price scenarios, the results demonstrate that as the price increases from 26 CNY/kg to 30 CNY/kg, the optimal ALK capacity decreases from 2.92 MW to 0.29 MW, while the PEM capacity increases from 3.51 MW to 5.51 MW. Correspondingly, the system’s Net Present Value (NPV) exhibits an upward trend. To address the limitations of traditional methods in handling multi-dimensional benefit correlations and information ambiguity, a comprehensive benefit evaluation framework encompassing economic, technical, environmental, and social synergies was constructed. Sensitivity analysis indicates that the comprehensive benefit level falls within a relatively high-efficiency interval. The numerical characteristics, an entropy value of 3.29 and a hyper-entropy of 0.85, demonstrate compact result distribution and robust stability, validating the applicability and stability of the proposed offshore wind–hydrogen benefit assessment model. Full article

Today, on the island of Gran Canaria, conventional photovoltaic installations are being implemented on the ground, with the excuse that electricity production must be decarbonized. This is located on a highly populated island, with a shortage of flat land, and a high dependence on food, in a biodiversity hot spot on the planet. We would like to point out that agrivoltaics could provide a double solution and allow the carbon footprint of this human settlement to be further reduced. In addition, it provides greater resilience to climate change, and by reducing dependence on the outside, it would minimize the effects suffered by pandemics such as SARS-CoV-2. It would also help mitigate water stress in one area facing serious water shortage problems. The reduction of local CO₂ emissions would be achieved in four ways: production of clean electricity, reduction of the transport of fuel for electricity generation, reduction of the transport of food goods from abroad, and the absorption of CO₂ together with the emission of O₂ by the planted crops. It would also lead to greater job creation, a remedy against great soil desertification, stopping agricultural abandonment, and life in rural inland areas. This study analyzes two possible agrivoltaic installation configurations of equal power in a potato field: one with a vertical bifacial (VB) configuration and another with an optimum angle (OA). The monthly production is examined and, specifically, the economic income in the event of pouring all the production into the grid. All this takes into account the reality of the chosen place, the island of Gran Canaria (Spain). Full article

Syngas, a renewable fuel primarily composed of hydrogen and carbon monoxide, is emerging as a viable alternative to conventional fossil fuels in internal combustion engines (ICEs). Obtained mainly through the gasification of biomass and organic waste, syngas offers significant environmental benefits but also presents challenges due to its lower heating value and variable composition. This review establishes recent advances in understanding syngas combustion, chemical kinetics, and practical applications in spark-ignition (SI) and compression-ignition (CI) engines. Variability in syngas composition, dependent on feedstock and gasification conditions, strongly influences ignition behavior, flame stability, and emissions, demanding detailed kinetic models and adaptive engine control strategies. In SI engines, syngas can replace up to 100% of conventional fuel, typically at 20–30% reduced power output. CI engines generally require a pilot fuel representing 10–20% of total energy to start combustion, favoring dual-fuel (DF) operation for efficiency and emissions control. This work underlines the need to integrate advanced modelling approaches with experimental insights to optimize performance and meet emission targets. By addressing challenges of fuel variability and engine adaptation, syngas reveals promising potential as a clean fuel for future sustainable power generation and transport applications. Full article

Electrochemical energy storage technology, primarily lithium-ion batteries, has been widely applied in large-scale energy storage systems. However, differences in assembly structures, manufacturing processes, and operating environments introduce parameter inconsistencies among cells within a pack, producing complex, high-volume datasets with redundant and fragmented charge–discharge records that hinder efficient and accurate system monitoring. To address this challenge, we propose a hybrid ASW-UKF-TRF framework for the classification and compression of battery data collected from energy storage power stations. First, an adaptive sliding-window Unscented Kalman Filter (ASW-UKF) performs online data cleaning, imputation, and smoothing to ensure temporal consistency and recover missing/corrupted samples. Second, a temporally aware TRF segments the time series and applies an importance-weighted, multi-level compression that formally prioritizes diagnostically relevant features while compressing low-information segments. The novelty of this work lies in combining deployment-oriented engineering robustness with methodological innovation: the ASW-UKF provides context-aware, online consistency restoration, while the TRF compression formalizes diagnostic value in its retention objective. This hybrid design preserves transient fault signatures that are frequently removed by conventional smoothing or generic compressors, while also bounding computational overhead to enable online deployment. Experiments on real operational station data demonstrate classification accuracy above 95% and an overall data volume reduction in more than 60%, indicating that the proposed pipeline achieves substantial gains in monitoring reliability and storage efficiency compared to standard denoising-plus-generic-compression baselines. The result is a practical, scalable workflow that bridges algorithmic advances and engineering requirements for large-scale battery energy storage monitoring. Full article