Search Results (1,670)

This study addresses the environmental problems stemming from greenhouse gas (GHG) emissions from public transportation in the cities of Chillán and Chillán Viejo. Specifically, it analyzes emissions from fossil-fuel-powered buses, which contribute to climate change and negatively affect people’s quality of life. Given this situation, the need to reduce these emissions and move towards more sustainable mobility systems is recognized. The main objective of this research is to estimate the CO₂-equivalent reduction that could be achieved by replacing fossil-fuel-powered public transportation with electric vehicles in the aforementioned cities. To this end, the ISO 14064 methodology is used, subject to specific scope and limitations. This study reviews key aspects, including current environmental legislation, Chile’s international commitments regarding climate change, and the state of emissions in the transportation sector, to illustrate the current state of electromobility in Chile. Finally, the impact of the transition to electromobility in public passenger transport by bus is quantified, resulting in a reduction of 9429 tons of CO₂ equivalent emissions, equivalent to 63.4% compared to the 2023 bus fleet, considering the average emission factor of the national electricity system for 2023. The proposal consists of implementing a 100% electric bus public transport system, highlighting its advantages in reducing emissions, improving energy efficiency, improving air quality, and reducing noise pollution. However, this requires a significant financial investment of approximately USD 57 million, excluding public charging stations for electric buses. Furthermore, public policies offering means of accelerating the transition of public transport in Chile are analyzed. Full article

The energy transition process encompasses the transformation of traditional energy systems towards more sustainable energy sources. It is recognized that a well-executed energy transition plays a key role in achieving sustainable development. It should, among other things, minimize environmental impact, support economic growth, ensure equal access to energy, and so on. The energy transition process affects most countries in Europe and around the world, but the pace and scope of these changes vary significantly. Therefore, a significant research issue is assessing the progress of energy transition in EU countries and forecasting this progress by analysing the impact of these transition processes on the environment, economy, and society. The scientific contribution of this article includes the use of an advanced methodological approach, which yields reliable results for assessing and forecasting the progress of energy transition. The study utilized a multi-criteria decision analysis methodology based on the PROSA-G method, enabling a native assessment of the progress of energy transition in accordance with a strong sustainability paradigm. The results indicate that Sweden, Denmark, Estonia, and Finland are the leading countries, with Greece and Cyprus trailing behind. In the coming years, Malta may join the ranks, while Spain and Poland will also be among the outsiders if they do not change their current energy policies. Full article

Sustainability research has seen tremendous growth as a field of study in recent years, evolving and changing in scope along the way. In this review, we track the growth and development of sustainability from 1980 to 2024 within the academic literature, utilize a comparison of works conducted with U.S.- and Chinese-based samples to demonstrate how different countries may influence sustainability practices, and outline possible areas for future research on this topic. As the largest economies in the world and the largest emitters of greenhouse gases, the U.S. and China can have a substantial impact on reducing climate change if they commit to sustainability. Articles for this review were acquired using a Scopus search for titles containing “sustainability AND China” and also titles containing “sustainability AND United States”, with years set to 1980–2024. It was also supplemented by a Google Scholar search for studies based in the U.S. and China. This review provides an overall comparison of the two literatures on sustainability from the U.S. and China. Ethical implications of sustainability in the U.S. and China are discussed. It appears that China is clearly positioned to lead the world in clean energy production, both by installing sustainable energy domestically and by selling such technology (e.g., solar) to other countries, because the Chinese government has prioritized this effort. The U.S. has made progress on the clean energy front, but that progress varies depending on the level of commitment from the federal government and may need to be driven by market and consumer demand. We hope that this review will aid in stimulating further investigation to advance the underlying research streams that we identify in this review, along with broadening the focus of sustainability to the global scale. Full article

This study presents an integrated engineering methodology aligned with the planning phase of the ISO 50001:2018 (Energy Management Systems—Requirements with Guidance for Use. International Organization for Standardization (ISO): Geneva, Switzerland, 2018) energy management standard for the design, sizing, and assessment of a solar thermal system applied to domestic hot water production in a medium-scale hotel building. The proposed framework focuses on the energy review stage of ISO 50001, incorporating site-specific climatic assessment, spatial layout optimization, structural feasibility analysis, and energy performance evaluation to support informed technology selection and system viability. Thermal performance is assessed using real operational data from the case study, complemented by a data-driven multivariable regression-based energy performance indicator (EnPI) that relates electricity consumption to cooling degree days and room occupancy. This regression model, developed in accordance with ISO 50001 recommendations, enables transparent monitoring of energy performance under real operating conditions without relying on black-box predictive techniques. Material selection criteria for absorber plates, heat-transfer components, transparent covers, and insulation layers are discussed to support both initial efficiency and performance stability under site-specific climatic conditions. In addition, an indicative and qualitative analysis of material-dependent performance evolution is introduced to support comparative decision-making, without implying quantitative lifetime prediction. Structural feasibility of the collector support system is examined through finite-element simulations under combined gravitational and wind loads, providing illustrative verification of stress distribution under representative operating conditions. The installed system delivers an annual thermal energy contribution of 8468 kWh, resulting in an estimated reduction of 7.79 t of CO${}_2$ emissions per year. Economic indicators suggest a short payback period and a favorable internal rate of return, which should be interpreted as order-of-magnitude estimates within the planning scope of the methodology. Overall, the proposed methodology provides a replicable and multidisciplinary planning-phase framework aligned with ISO 50001 for the design and assessment of solar thermal systems in medium-scale buildings under real operating conditions. Full article

Driven by cleaner energy demands, environmental regulations, and technological advances, coal science is rapidly evolving, creating the need to understand its transition and transformation within the global energy research landscape. Building upon earlier national- and topic-specific bibliometric studies, this study presents a comprehensive long-term global bibliometric analysis of coal research (1975–2024), based on 272,370 Web of Science records, applying the Cross-Disciplinary Publication Index (CDPI), the Technology–Economic Linkage Model (TELM), VOSviewer, and Excel to assess research growth, structural shifts, and interdisciplinary integration. Results show that coal research is dominated by articles (74%) with publication output peaking at ~19,500 in 2024, reflecting fluctuations in global coal prices due to energy transition market dynamics. CDPI results highlight Energy & Fuels (0.83), Chemical Engineering (0.80), Environmental Sciences (0.77), Materials Science (0.74), and Geosciences (0.66), showing coal’s central role across technology, environment, and geological research domains and revealing a clear shift toward sustainability-oriented and advanced material applications. China leads output (122,130 publications), with strong contributions from the China University of Mining and Technology and the Chinese Academy of Sciences, while the USA, Australia, and Europe maintain strong international collaboration networks. The evolution of coal research can be divided into three major phases: conventional mining, coal preparation, combustion, and coalbed methane commercialization (1975–2004; ~64,000 publications); integrated gasification combined cycle (IGCC) and carbon capture and storage (CCS) technologies (2005–2014; ~58,707 publications); and a recent phase dominated by by-product valorization, carbon capture utilization and storage (CCUS), and digital technologies (AI, IoT, ML) (2015–2024; ~146,174 publications). Contemporary coal research spans three interconnected domains: energy supply (≈36% of global electricity generation and ~15 Gt CO₂ emissions), resource and geoscience applications (including large-scale fly ash utilization and critical element recovery), and environmental and health impacts related to greenhouse gas and pollutant emissions. The findings demonstrate that coal science is transitioning from a conventional fossil fuel-centered discipline toward an integrated, interdisciplinary energy research field, emphasizing emission reduction, resource efficiency, digitalization, and circular economy applications, thereby extending prior bibliometric studies through unprecedented temporal coverage, global scope, and the combined application of CDPI and TELM frameworks, providing critical insights for future energy strategies and policy development. Full article

Q-method analysis is used to determine participants’ subjective viewpoints on a given subject. A review of the extant literature revealed a paucity of research examining participants’ viewpoints on environmental awareness within Education for Sustainable Development (ESD) using Q-method analysis. The aim of this study is to uncover teachers’ viewpoints on environmental awareness within ESD using Q method analysis. Accordingly, the study employed Q-method analysis as a mixed research methodology. Issues related to ESD are addressed in primary and secondary school curricula in Türkiye, primarily within the scope of science and social studies courses. The participants in the study consist of science, social studies, and primary school teachers working in the Gaziantep province of Türkiye. The data collection instrument, developed through criterion sampling, was a Q-method form created by the researchers based on insights from the relevant literature and field specialists. Quantitative and qualitative data were analyzed using PQ Method 2.35 statistical software. The findings indicate that participants’ viewpoints on environmental awareness within ESD were grouped into two factors and were predominantly positive (93%), showing consistency across gender and teaching field variables. While all 66 participants in Factor 1 demonstrated wholly positive attitude towards ESD, the 5 participants in Factor 2 exhibited partially positive attitudes. Participants expressed the most positive viewpoints regarding the protection of forests, energy resources, and recycling, whereas the least positive viewpoints were related to the ozone layer, climate change, and the economical use of resources. Based on these findings, it is recommended that teachers’ awareness of issues such as the ozone layer, global warming, and the economical use of resources be enhanced. Full article

Plug-in hybrid electric vehicles (PHEVs) operate using both electricity and liquid fuel, offering emissions reduction while eliminating driving-range concerns. Determining the optimal electric range or battery capacity is crucial for the total cost of ownership, decarbonization potential, and battery material demand. However, the effect of battery degradation has not been incorporated into market-oriented range-optimization studies. This paper extends the existing MOR-PHEV range optimization model by integrating both cycle-based and calendar-based battery degradations. The results show meaningful optimization benefits, reducing consumer ownership cost by approximately $3000–5000. The optimal solution—defined by the minimized lifetime cost and the optimal battery capacity—is robust across the key external parameters. Intertwined with certain factors, battery degradation can have a significant impact on the optimal battery capacity. Particularly, at faster cycle-based degradation, high driving intensity and high CS efficiency can lead to optimization tipping points, where the degradation effect is so significant that the consumer is better off by choosing a small-battery PHEV (or HEV if the choice space expands beyond PHEV) in order to fully degrade the battery faster, totally avoid the charging behavior cost earlier, and maximally benefit from the high CS efficiency earlier. This points to the importance of reducing the cycle-based degradation coefficient and improving the vehicle energy efficiency and charging convenience. One basis point (0.01%) reduction in the cycle-based degradation coefficient is estimated to reduce the optimal battery capacity by 4.9–5.2 kWh and increase consumer value by $275–497, depending on the battery unit cost. These are useful insights into decision-making regarding battery technology R&D, battery chemistry roadmaps, critical material supply risks, and EV product strategies. While the findings in the study scope depend on assumptions of consumer behavior, battery degradation, vehicle efficiency and charging infrastructure, the expanded MOR-PHEV provides a systematic framework for considering different assumptions in support of user-defined decision context and discussing future research. Full article

This comprehensive study presents an integrated analysis of NO_x reduction strategies and operational optimization for the HYUNDAI-HiMSEN 7H35DFP dual-fuel marine engine. The optimization scope focuses on selective catalytic reduction control strategies and operational decision-making (fuel mode selection, load management) rather than engine hardware modifications, ensuring practical applicability within certified marine engine operational envelopes. The research employs a multifaceted approach combining experimental investigation, computational fluid dynamics (CFD) modeling, and advanced control algorithms to address the stringent IMO Tier III emission standards. The 3500 kW, 7-cylinder engine achieves IMO Tier III compliance through dual pathways: (1) gas mode operation meeting the 2.4 g/kWh limit inherently with measured emissions of 1.41–2.29 g/kWh across 25–100% load without aftertreatment, and (2) diesel mode achieving compliance via SCR aftertreatment, reducing Tier II baseline emissions (7.68–10.71 g/kWh) by 75–82% to final values of 1.60–1.96 g/kWh. The research quantifies NO_x reduction mechanisms separately for each operating mode and establishes optimal operational strategies for mode selection. A MATLAB v2025a-based SCR optimization model successfully predicts optimal urea injection rates, achieving >75% NO_x reduction efficiency across all operating conditions. Multivariate analysis using principal component analysis identifies the following three primary factors explaining 89.3% of dataset variability: combustion intensity (45.2%), fuel mixing characteristics (28.7%), and thermal management (15.4%). CFD analysis reveals that gas mode combustion produces more uniform temperature distributions (peak ~2000 K) compared to diesel operation (>2200 K), directly explaining NO_x generation differences. The developed digital twin framework with machine learning algorithms achieves 94.2% accuracy in SCR catalyst degradation prediction and 91.8% in fuel injection system performance prediction. Waste heat recovery analysis indicates 25–30% of fuel energy resides in exhaust gases, with theoretical energy recovery potential of 8.5–15.3%. This integrated approach validates dual-fuel technology’s capability to meet current and future maritime environmental regulations while maintaining operational flexibility. Full article

Nuclear power serves as an efficient, clean, and low-carbon energy source that constitutes a significant component of the energy portfolio in numerous countries. Most nuclear power plants are predominantly situated in coastal regions, utilizing seawater as the ultimate heat sink for their cooling systems. Real-time monitoring of marine organism dynamics near water intakes is essential to mitigate the risk of unit shutdowns triggered by outbreaks of disaster-causing organisms (DCOs). This study employed LiveScope scanning sonar videos captured near the Ningde Nuclear Power Plant to develop a dataset for detecting the light spot area of the DCOs. We proposed a directionally optimized model, Bio-YOLO v7, which significantly enhances the detection of small targets in sonar images. The Bio-YOLO v7 model achieved precision, recall, and average precision rates of 85.29%, 83.28%, and 81.49%, respectively, demonstrating superior performance in identifying DCOs near the intakes of nuclear power plant. The light spot size of the DCOs exhibited significant periodic variations, serving as a crucial indicator for forecasting outbreak events. Full article

The built environment is a major contributor to global greenhouse gas emissions and urgently requires decarbonization. Despite the decline in operational carbon emissions, which continue to fall as energy-efficient buildings rise, embodied carbon (EC) emissions from material extraction, production, and construction have become increasingly prominent, accounting for an increasing share of total building emissions. Establishing a benchmark value for buildings is essential for assessing, comparing, and mitigating emissions in new construction because it helps set goals, evaluate performance and resource efficiency, promote sustainable building practices, and lay the groundwork for decarbonizing the urban built environment. Globally, building carbon benchmarks are developed using life cycle assessment and statistical methods, whereas whole-life carbon assessment frameworks are increasingly adopted with regulatory integration. However, broader applicability remains constrained by methodological inconsistencies. This research reviews existing benchmarking studies and identifies discrepancies via semi-systematic and critical analyses. The results reveal that 81% of benchmark studies apply bottom-up approaches, and nearly 88% focus on residential buildings. The range of benchmark values for residential buildings using the bottom-up approach varies from 1.3 to 63.9 kg CO₂e/m²/year, whereas the top-down approach ranges from 1.2 to 27 kg CO₂e/m²/year. The overall range is 1.2 to 92.5 kg CO₂e/m²/year, reflecting substantial variation due to variable scopes, typologies, modeling approaches, and data sources. This research highlights the urgent need for standardized benchmarking methods to ensure comparability across studies, enable effective policy implementation, and support decarbonization. Additionally, this study proposes a framework for establishing EC benchmarks and strategies that promote low-carbon, resource-efficient urban development. Full article

The performance of Gas Metal Arc-Directed Energy Deposition (GMA-DED) strongly depends on efficient path-planning strategies that balance trajectory quality and computational cost. With the purpose of developing a computationally faster and more scalable path-planning approach, this study introduces the Fast Advanced-Pixel strategy by integrating the K-means clustering algorithm into to the Advanced Pixel strategy version to reduce the dimensionality of an optimization problem. Computational validation was conducted on four geometrically distinct parts using different clustering configurations. Statistical analysis (ANOVA) was applied to assess the significance of the results. The findings revealed that by increasing the number of clusters, computational time is substantially reduced, achieving up to a twenty-fold improvement compared with the former strategy, while maintaining consistent trajectory quality. Experimental validation using complex parts, such as a “Jaw Gripper” and a “C-frame” of a resistance spot welding gun, confirmed defect-free deposition and dimensional agreement with the CAD models. Accordingly, within the scope of GMA-DED technology and pixel-based path-planning strategies, the Fast Advanced-Pixel approach demonstrates a significant improvement in computational efficiency while preserving trajectory quality, enabling the accurate and reliable fabrication of geometrically complex metallic parts. Full article

Background: Explainable Artificial Intelligence (XAI) is deployed in Internet of Things (IoT) ecosystems for smart cities and precision agriculture, where opaque models can compromise trust, accountability, and regulatory compliance. Objective: This survey investigates how XAI is currently integrated into distributed and federated IoT architectures and identifies systematic gaps in evaluation under real-world resource constraints. Methods: A structured search across IEEE Xplore, ACM Digital Library, ScienceDirect, SpringerLink, and Google Scholar targeted publications related to XAI, IoT, edge/fog computing, smart cities, smart agriculture, and federated learning. Relevant peer-reviewed works were synthesized along three dimensions: deployment tier (device, edge/fog, cloud), explanation scope (local vs. global), and validation methodology. Results: The analysis reveals a persistent resource–interpretability gap: computationally intensive explainers are frequently applied on constrained edge and federated platforms without explicitly accounting for latency, memory footprint, or energy consumption. Only a minority of studies quantify privacy–utility effects or address causal attribution in sensor-rich environments, limiting the reliability of explanations in safety- and mission-critical IoT applications. Contribution: To address these shortcomings, the survey introduces a hardware-centric evaluation framework with the Computational Complexity Score (CCS), Memory Footprint Ratio (MFR), and Privacy–Utility Trade-off (PUT) metrics and proposes a hierarchical IoT–XAI reference architecture, together with the conceptual Internet of Things Interpretability Evaluation Standard (IOTIES) for cross-domain assessment. Conclusions: The findings indicate that IoT–XAI research must shift from accuracy-only reporting to lightweight, model-agnostic, and privacy-aware explanation pipelines that are explicitly budgeted for edge resources and aligned with the needs of heterogeneous stakeholders in smart city and agricultural deployments. Full article

Many companies in the mining industry include decarbonization of production among their key strategic goals as part of their internal sustainability strategy. This need is driven by a number of factors: stricter regulation in the area of carbon footprint (introduction of carbon taxes, emissions quotas, reporting requirements); sustained growth in demand for electricity and rising market prices; economic feasibility—the need to optimize operating costs and improve energy efficiency. This study provides a comprehensive technical and economic justification for implementing a hybrid power supply system—combining a solar power plant (SPP) and a gas engine power plant (GPP)—at Solidcore Resources’ Varvarinsky hub in Kazakhstan. The methodology includes modeling the energy balance of the real asset (156.9 GWh of annual energy consumption), calculating the output of a 22.6 MW SPP based on local GHI/PR/η parameters, forming and determining the adaptability coefficient Kₐ (proportion of PV in total monthly electricity generation), conducting an economic assessment (NPV, payback period, sensitivity), and inventorying CO₂ emissions under Scope 1–2. The SPP provides approximately 41.3 GWh of electricity generation per year, with an average annual K_a = 0.263; the 40 MW installed capacity of the gas piston power plant covers the residual demand, forming a stable daily and seasonal balance. The project demonstrates a positive NPV (After Tax) = USD 23.65 million with an estimated payback period of 10 years, while the cost of energy in extraction and processing is reduced by almost three times, and the total reduction in CO₂ emissions will be 51%. Thus, hybridization of energy supply systems is a practical compromise between reliability and decarbonization. Determining the adaptability coefficient K_a allows the flexibility of the system to be taken into account, shows how effectively the new energy system uses renewable energy sources, and can be used to optimize the operation of the energy system to achieve the company’s internal sustainable development goals. Full article

Municipalities aiming for climate neutrality and resilience must take a systemic approach to planning, implementing, and monitoring climate actions, to be able to mobilise the resources needed to achieve this ambitious goal. This involves complementing conventional top-down and technological measures with bottom-up and inclusive strategies that include not only citizen engagement but also the innovation of social practices. This study presents a comparative analysis of social innovation actions for climate neutrality planned by 53 cities from 21 countries participating in the Pilot Programme of the EU-funded project NetZeroCities. By identifying 445 actions across all cities’ pilot programmes and classifying them into 10 categories and 38 sub-categories, it is found that 53.71% of actions are linked with social innovation, offering timely insights into how social innovations are being designed in cities’ urban plans. The results reveal emerging patterns and geographical variations across Europe. With more than half of all social innovation interventions focused on stationary-energy and Scope-3-related emissions reduction, the analysis reveals that cities are increasingly relying on social innovation to foster the behavioural and socio-technical changes needed to shape sustainable energy use, consumption, and mobility patterns. These actions are based on co-creation, co-design, cross-sectoral partnerships, and public-sector capacity building, with regional differences. The comparative approach and analysis contribute to the transdisciplinary discourse on social innovation assessment in systemic innovation for transitions. Full article

Considering the challenges of decarbonization, the energy transition, and the necessity to increase resource efficiency in the context of the circular economy, there is a need to develop sustainable solutions for the material and energy use of biogenic waste. Biogenic waste, which remains underutilized and can be regarded as an untapped resource, offers significant potential for sustainable energy production. In this context, biogas plants are a key technology, as they convert biogenic waste into renewable energy, reduce greenhouse gas emissions, and contribute to closing material cycles. The standardized life cycle assessment (LCA) methodology is a tool for the systematic analysis and evaluation of environmental impacts of products, systems, or services. The objective of this study is to develop a methodological and conceptual framework for the LCA of the innovative biogas plant based on a rotating drum fermenter. The environmental aspects of biowaste utilization and the role of the biogas plant in waste reduction and energy production are discussed in the broader context of the circular economy. Due to its complexity, this paper considers LCA with focus on the definition of the goal and scope of the study in accordance with international standards. Full article