Search Results (1,576)

As a significant source of global carbon emissions, the construction industry (CI) urgently needs to promote green transformation with the help of digital twin (DT) against the backdrop of human–machine collaboration and sustainable development advocated by CI 5.0. However, there is still a lack of systematic research on its specific driving mechanism and carbon reduction path. This study uses a systematic literature review (SLR) to explore how five key DT-enabled capabilities, namely, resource management (RM), process optimization (PO), real-time monitoring (R-Tm), sustainable design (SD), and predictive maintenance (PM), influence three performance indicators: efficiency improvement (EI), energy optimization (EO), and cost control (CC). Data from 490 companies were analyzed using partial least squares structural equation modeling (PLS-SEM) and a multilayer perceptron (MLP) with Shapley additive explanation (SHAP). The results show that the PLS-SEM and MLP models showed consistent patterns, with EO exhibiting the strongest predictive performance (Q² = 0.372; R² = 0.3666), followed by EI (Q² = 0.307; R² = 0.3109) and CC (Q² = 0.305; R² = 0.2609); the SHAP results further indicated that RM contributed most to EI (0.242), while PO was the most important driver for both EO (0.304) and CC (0.259). Academically, it introduces a quantitative approach combining PLS-SEM and machine learning. Practically, it highlights the priority of key technologies with cross-dimensional effects and offers guidance for governments to optimize digital resource allocation and carbon performance evaluation, as well as for enterprises to apply DT more effectively. Full article

In the context of global energy system transformation and the pursuit of regional sustainability, China’s Air Pollution Control and Prevention Action Plan (APPA) targets both pollution reduction and carbon mitigation, serving as a critical policy instrument for coordinating the energy-economy-environment nexus in the “2+26” cities. This study employs a quasi-natural experiment with a difference-in-difference (DID) method to assess the synergistic impact of this energy-related policy on these cities. Results show that APPA significantly reduces PM2.5 and carbon emissions by 5.56% and 9.89%, respectively, demonstrating a successful alignment of short-term environmental targets with long-term decarbonization goals. Heterogeneity analysis reveals that large cities with higher institutional capacity are more effective in reducing both pollutants, while resource-based cities achieve more PM2.5 reduction, and non-resource-based cities excel in low-carbon energy transition. Mechanism analysis indicates that APPA promotes these outcomes by optimizing the energy-intensive industrial structure and fostering green technological innovation. This study highlights the effectiveness of integrated governance frameworks in enhancing air quality and reducing carbon emissions, providing crucial insights for redesigning sustainable energy policies and managing the socio-economic disruptions of just transitions in rapidly developing regions. Full article

Aviation heavy-fuel piston engines are widely used in UAVs, general aviation, and military platforms due to their fuel efficiency and adaptability. However, emissions of NO_x, PM, and other pollutants pose significant environmental challenges. This paper reviews emission-reduction strategies, including combustion-chamber optimization, fuel-injection control, alternative fuels, and exhaust after-treatment technologies. Research indicates that optimizing combustion-chamber geometry, high-pressure common-rail injection, and turbulence enhancement improve combustion efficiency and reduce emissions. Biofuels, synthetic aviation fuels (SAF), and hydrogen-based fuels demonstrate strong potential for low-carbon emissions, while after-treatment technologies such as SCR, DPF, and EGR effectively mitigate NO_x and PM emissions. Despite technological advancements, challenges remain in balancing combustion efficiency with NO_x control and ensuring compatibility between EGR and combustion stability. Future advancements in intelligent combustion control, novel catalytic materials, low-temperature combustion, and high-efficiency after-treatment systems will drive aviation diesel engines toward lower emissions, higher efficiency, and greater intelligence, contributing to the green and sustainable transformation of aviation propulsion systems. Full article

Achieving urban climate neutrality and interim mitigation targets requires rapid demand-side emission reductions, yet current user-centred interventions remain fragmented, are often concentrated on low-impact actions, and rarely provide a traceable basis for comparing outcomes, validity conditions, and equity implications across contexts. This paper reframes demand-side mitigation as a design problem of “use infrastructures”: integrated configurations of communication, product-technology, services, interaction, and governance that make low-carbon choices practicable within everyday routines. We introduce the Design Evidence Link (DEL) as a traceability device supporting ex ante configuration (selection and orchestration of levers) and ex post verification (monitoring, attribution of outcomes, and trade-off control). Through a design-led comparative analysis of nine international cases in high-impact sectors (household energy, ground mobility, food systems, and circular economy/materials), we derive and consolidate a shared extraction and coding protocol that links determinants (barriers and enablers) to design requirements and decision-grade metrics (carbon impact, adoption, continuity, and equity), explicitly qualifying uncertainty and evidence levels. Cross-case results show that effective interventions rely less on isolated information and more on coordinated action packages that reduce cognitive and economic frictions, enhance data credibility through standards and accountability, and embed follow-up mechanisms that support behavioural continuity. DEL also surfaces recurring validity conditions and failure modes (digital exclusion, trust erosion, rebound, and lock-in), translating them into operational criteria for policy and design. Compared with behaviour-change or theory-of-change framings, DEL focuses on the observable orchestration of integrated conditions of use and on the explicit grading of evidence. It should therefore be read as a structured analytical–operational framework for ex ante and ex post assessment, whose transferability remains conditional on source quality, contextual prerequisites, and the limits of the selected cases. Full article

The development of modern transport energy systems is driven by increasing demands for energy efficiency, environmental sustainability, and operational reliability of vehicles. One of the most critical challenges in internal combustion engine operation is the cold-start condition, which results in increased fuel consumption, intensified component wear, and elevated emissions. Under these conditions, the development of intelligent thermal conditioning systems capable of accelerating engine warm-up and maintaining optimal thermal regimes becomes essential. This study proposes an intelligent engine and vehicle thermal conditioning system based on the integration of digital twin technology and phase-change thermal (PCM) energy storage. A digital twin architecture of the engine thermal conditioning system is developed to enable the integration of monitoring, simulation and predictive control of engine thermal processes. A mathematical model of the thermal conditioning system describing the dynamic temperature behavior of the engine, coolant, engine oil and PCM-based thermal energy storage units is formulated. A model predictive control strategy is implemented within the digital twin environment to support decision-making and optimization of engine thermal conditioning processes. Simulation and experimental results demonstrate that the proposed system can reduce engine warm-up time by 17.8–68.4%, decrease fuel consumption during the cold start phase by approximately 19.5–56.25%, and reduce harmful emissions. These findings confirm the potential of integrating digital twin technologies, predictive control and phase change thermal energy storage for improving the energy efficiency and environmental performance of modern transport power systems. Full article

With the advancement of agricultural modernization, issues related to resource conservation, intensive utilization, and green, low-carbon development have become increasingly prominent. To enhance water and fertilizer use efficiency in Henan Province and promote green, low-carbon, and sustainable agricultural development, field experiments were conducted during 2023–2024. The experiment employed a randomized complete block design with three replications. Each plot measured 30 m² (5 m × 6 m), totaling 36 plots. An IoT-based real-time coordinated water-fertilizer regulation technology, driven by continuous WSH-TDR310S sensor monitoring of soil moisture and nitrogen status with automated threshold-based control logic, was implemented. By transforming the traditional static scheduling approach into a dynamic feedback mechanism driven by real-time sensor data, the synchronization between resource supply and crop demand was achieved. This study aimed to elucidate the response characteristics of summer maize growth dynamics and farmland N₂O emissions under the proposed regulation strategy. The experiment included three levels of water deficit (mild, moderate, and severe) and three fertilization levels (low, medium, and high), resulting in a total of nine real-time water–fertilizer coordinated regulation treatments, along with three local border irrigation control treatments. The results showed that under real-time water–fertilizer regulation, plant height, stem diameter, and leaf area index of summer maize exhibited unimodal variation patterns, with the medium irrigation–medium fertilization (B2) treatment performing optimally. Compared with the border-irrigation medium-fertilization control (D2), plant height and stem diameter under the B2 treatment increased significantly. Cumulative farmland N₂O emissions increased with higher irrigation and fertilization levels, with the border-irrigation high-fertilization treatment producing the highest emissions. Yield formation was mainly governed by structural growth traits, with plant height showing the strongest predictive ability, followed by stem diameter, whereas leaf area index showed weaker explanatory power. Summer maize yield exhibited a unimodal response to both irrigation and nitrogen input levels. Compared with the D2 treatment, the B2 treatment increased grain yield by 41.33%, while achieving water-saving and fertilizer-saving rates of 38.10% and 35.75%, respectively, thereby achieving an optimal balance between high yield and efficient water–fertilizer utilization. These findings provide theoretical support for summer maize production in the North China Plain and contribute to the promotion of green and sustainable agricultural development. Full article

Controlling carbon dioxide (CO₂) emissions remains a central challenge in Indonesia’s energy transition and its commitment to achieving net-zero emission targets. Carbon Capture and Storage (CCS) and Carbon Capture, Utilization, and Storage (CCUS) are widely recognized as important mitigation pathways, particularly for energy and industrial sectors where rapid decarbonization remains difficult. In parallel, cold plasma technology has emerged in the recent scientific literature as an early-stage, non-thermal approach for CO₂ activation under relatively low bulk temperature conditions, attracting interest as a potential long-term research pathway. This paper examines cold plasma technology within the broader CCS/CCUS landscape in Indonesia from a policy and technology perspective. The study adopts a qualitative and descriptive approach, synthesizing the selected academic literature on plasma-based CO₂ conversion, global CCUS development trends, and Indonesia’s regulatory, infrastructural, and energy system context. Rather than assessing techno-economic feasibility, the analysis focuses on identifying structural constraints, performance trade-offs, and policy-relevant considerations. The findings indicate that across plasma configurations, including dielectric barrier discharge, gliding arc, microwave, and radio frequency plasmas, current research outcomes remain constrained by low energy efficiency, limited scalability, and low technology readiness for large-scale applications. Reported performance metrics are largely derived from laboratory-scale studies under controlled conditions and cannot yet be extrapolated to real-world emission sources without a comprehensive system-level evaluation. Compared with established CCS and CCUS pathways, cold plasma technologies remain exploratory and lack the maturity required for near-term deployment. From a policy and research perspective, cold plasma should therefore be regarded as a long-term research option rather than an implementable mitigation solution for Indonesia, with its potential contribution lying in informing future research agendas, technology monitoring, and innovation planning, particularly in relation to CO₂ utilization concepts and decentralized energy systems, contingent upon significant advances in energy performance, system integration, and standardized evaluation frameworks. Full article

Shooting activities offer educational and recreational value; however, their application in school physical education and recreational settings remains limited due to safety concerns, high costs, and restricted access to specialized facilities and equipment. To address these constraints, this study designed and implemented a low-cost laser shooting system suitable for school physical education and recreational use. The proposed system comprises a laser-gun module, a physical electronic target providing immediate on-site feedback using an illuminance sensor, a Fresnel lens, and RGB LEDs, and a web-based electronic target that enables real-time scoring, logging, and visualization via smartphone or tablet cameras and browser-based processing. By adopting a low-power, projectile-free laser structure with pulse-limited emission, the system enhances operational safety, while the use of general-purpose components and web standards reduces cost and lowers barriers to adoption. Technical verification conducted under controlled indoor conditions demonstrated stable single-shot operation, reliable hit detection, and accurate score calculation for both the physical and web-based targets. Expert validation involving specialists in physical education, educational technology, and sports technology yielded consistently high evaluations across safety, cost efficiency, functional completeness, and field applicability. These findings suggest that the proposed system represents a practical and scalable alternative for school physical education classes and recreational programs. Future research should examine user-level usability, learning outcomes, system robustness under diverse environmental conditions, and structured expert consensus processes. Full article

The management of hazardous municipal solid waste incineration (MSWI) residues represents a critical challenge for sustainable development due to their increasing generation and environmental risk. At the same time, the cement industry faces urgent pressure to reduce CO₂ emissions associated with clinker production, creating a demand for alternative supplementary cementitious materials. The aim of this study was to evaluate the feasibility of valorising hazardous municipal solid waste incineration (MSWI) air pollution control fly ash (EWC 19 01 07*) as a constituent of Portland composite cement, in line with circular economy principles and the need to reduce CO₂ emissions associated with clinker production. The investigated fly ash, originating from flue gas cleaning processes, is characterised by high alkalinity and elevated concentrations of heavy metals, which currently necessitate controlled landfilling. To enable its safe reuse, the ash was subjected to high-temperature thermal treatment following granulation and subsequently incorporated into cement formulations under semi-industrial conditions. Two Portland composite cements were produced with different ash contents, corresponding to CEM II/A-07 and CEM II/B-07, while a Portland cement manufactured from the same clinker was used as a reference material. The chemical and phase composition of the ash before and after thermal treatment was analysed using XRF and XRD, supported by SEM/EDS observations. The results demonstrate that thermal treatment at 1150 °C induces partial phase stabilisation of APC fly ash without full vitrification, allowing its integration into cement systems under semi-industrial conditions. The incorporation of ash significantly alters hydration behaviour through increased water demand governed by particle porosity, CaO-rich phase composition, and early ionic interactions in the pore solution, leading to reduced workability and mechanical performance. While immobilisation efficiencies exceeding 99.5% were achieved for most heavy metals due to precipitation and incorporation into hydration products, barium exhibited persistent leaching controlled by its solubility under highly alkaline conditions and limited incorporation into C–S–H phases. These findings define both the technological feasibility and the key environmental constraints of APC fly ash utilisation in Portland composite cement. From a sustainability perspective, the proposed approach contributes to the reduction in hazardous waste landfilling and supports clinker substitution in cement production. The results demonstrate the potential of integrating waste management and low-carbon material design within a circular economy framework while highlighting current environmental limitations related to barium leaching. Full article

Low-count positron emission tomography (PET) is inherently affected by Poisson-dominated noise, which degrades image contrast, structural delineation, and quantitative reliability. This study systematically evaluated residual learning-based deep neural networks to investigate the influence of residual block depth on PET image restoration performance under low-count conditions. We employed a physically controlled striatum phantom, fabricated using 3D printing technology, to ensure reproducible acquisition conditions and controlled physical variability. PET images were acquired using a clinical PET/computed tomography (CT) system with list-mode acquisition. Low-count images reconstructed from short-duration acquisition were paired with high-count reference images reconstructed from extended acquisitions. We compared conventional filtering techniques, including median, Wiener, and modified median Wiener filters, with residual network (ResNet)-based models incorporating 8, 16, and 32 residual blocks. Image quality was quantitatively assessed using contrast-to-noise ratio (CNR), coefficient of variation (COV), line profile analysis, universal quality index (UQI), and perceptual image patch similarity (LPIPS). The results demonstrated that ResNet-based restorations substantially outperformed conventional filtering techniques in contrast recovery, signal stability, and structural preservation. The ResNet-16 model achieved the most balanced performance, yielding the highest CNR (9.02) and lowest COV (0.105), while also demonstrating superior structural and perceptual similarity, as indicated by UQI (0.9224) and LPIPS (0.0174), relative to the high-count reference images. Deeper network configurations exhibited diminishing returns and reduced structural consistencies. These findings indicate that an intermediate residual block depth is optimal for low-count PET image restoration and highlight the importance of architectural optimization in deep learning-based PET image enhancement with phantom-based evaluation frameworks. Full article

Biomass combustion, as a key technology for achieving a low-carbon transformation of the energy system, faces multiple challenges in its efficient and clean utilization, including the high heterogeneity of fuels, the complex multi-scale coupling of the combustion process, and the attainment of ultra-low emissions. Traditional research methods have significant disconnections between microscopic mechanism understanding, macroscopic performance prediction of reactors, and end-of-pipe pollution control, which restricts the improvement of system performance. This review presents recent advances in advanced numerical simulation, pollutant control strategies, and bioenergy with carbon capture and storage (BECCS) pathways targeting ultra-low emissions in biomass combustion. This work synthesizes progress across three interconnected domains. First, methodologies are examined for integrating detailed chemical kinetics, particle-scale models, and reactor-scale simulations to develop high-fidelity predictive tools. Second, low-nitrogen combustion and synergistic pollutant control strategies for primary furnace types (e.g., grate, fluidized bed) are evaluated, alongside process optimization from fuel pretreatment to flue gas purification. Third, the potential for integrated design of biomass energy systems with carbon capture is assessed, emphasizing that system efficiency hinges on holistic “fuel-combustion-capture” chain optimization rather than isolated unit improvements. Future research directions are highlighted, including the development of physics-informed AI modeling paradigms, deeper co-design of multiple processes, and the establishment of robust life-cycle assessment frameworks. This review aims to provide a structured reference to inform both fundamental research and the practical development of next-generation clean biomass combustion technologies. Full article

Empty Container Management (ECM) represents a cost-intensive and environmentally impactful component of global container logistics, with its effects most visibly manifested in inland transport systems. Despite extensive academic attention, research on ECM remains fragmented across optimisation, coordination, sustainability, and technology-oriented approaches, often addressing isolated processes or decision problems. As a result, persistent costs, inefficiencies, and emissions continue to characterise inland container logistics. This study applies PRISMA guidelines to systematically review the ECM literature. The analysis focuses on three aspects: the structural causes of container imbalances, the operational activities generating costs and emissions, and the stakeholders influencing ECM decisions. The findings show that empty container imbalances do not arise from a single source. Instead, they result from the interaction of global trade asymmetries, demand uncertainty, fragmented inland operations, and diverse regulatory and institutional environments. The answers to the research questions reveal three fundamental research gaps in the existing literature. First, optimising locally does not always improve the entire system, as it might simply shift costs to other parts of the empty container management (ECM) system. Second, technological solutions cannot operate effectively without appropriate governance mechanisms and data-sharing arrangements. Third, the actors responsible for setting rules and controlling equipment availability often do not bear the full consequences of empty container movements. This review provides a structured foundation for developing integrative decision-support approaches capable of addressing inland ECM under real-world structural constraints. Full article

Oxy-fuel combustion is a near-zero emission technology that utilizes high-concentration O₂ in place of air, combined with recycled flue gas, to achieve efficient combustion and enable effective CO₂ capture. In this study, air (21% O₂/79% N₂) was used as the control atmosphere, and rice straw combustion experiments were conducted using thermogravimetric analysis and differential scanning calorimetry and differential scanning calorimetry coupled with mass spectrometry (TG-MS) at heating rates of 10, 20, and 30 °C/min under oxy-fuel conditions of 30% O₂/70% CO₂, 50% O₂/50% CO₂, and 70% O₂/30%CO₂. The combustion behavior, pollutant emissions, reaction kinetics, and underlying mechanisms were systematically evaluated. The results show that CO₂ in oxy-fuel atmospheres exhibits a higher thermal inertia, due to its greater density and specific heat capacity, thereby enhancing flame stability. Oxy-fuel atmospheres reduce the ignition temperature (Tᵢ) and burnout temperature (T_f), shorten the combustion duration, shift DTG and DSC peaks to lower temperatures, and result in sharper peaks along with an increased ignition index (Cᵢ), burnout index (C_b), and comprehensive combustion index (S). Mass spectrometry (MS) analysis reveals that oxy-fuel atmospheres combined with heating rates of 20–30 °C/min suppress O₂ diffusion and thermal NO formation, reducing NO_x emissions by over 75% and simultaneously inhibiting the release of SO₂ and COS. Kinetic analysis using the FWO and Friedman methods shows that the activation energy decreases from 210.5 kJ/mol and 219.1 kJ/mol under air conditions to 110.5 kJ/mol and 114.6 kJ/mol in oxy-fuel atmospheres, representing a reduction in reaction barriers of 47.5% and 47.7%, respectively. The reaction mechanisms were identified as three-dimensional diffusion-controlled processes at heating rates of 20–30 °C/min, and random nucleation followed by growth under high O₂ concentration conditions at a heating rate of 30 °C/min. Optimizing the combustion atmosphere and heating rate enhances the rice straw combustion efficiency and reduces pollutant emissions, thereby providing theoretical support for its clean and efficient utilization. Full article

Industrial-scale Anaerobic Digestion (AD) is a key technology for the energy recovery of agro-industrial and municipal waste and for the mitigation of greenhouse gas emissions; however, the actual operational performance of industrial biodigesters continues to show significant discrepancies with respect to the theoretical values reported in the scientific literature. In this context, there is still a lack of systematic analysis to identify which operating parameters are consistently monitored in industrial settings and which remain insufficiently explored, particularly those that describe the overall state of the digestion environment. To address this gap, a systematic literature review was conducted in the Scopus database for the period 2000–2026, complemented by a bibliometric analysis using VOSviewer software v1.6.18. 3. After applying inclusion criteria focused exclusively on industrial-scale and pilot systems, 1327 documents corresponding to the category of operating parameters were selected and analyzed using keyword co-occurrence networks and evaluation of occurrence frequencies and total link intensities. The analysis shows a marked concentration of the literature on a small set of classic parameters, highlighting pH (154 occurrences, 3667 link intensities), temperature (147 occurrences, 3255 link intensities), and ammonia (131 occurrences, 2824 link intensities) as the most recurrent variables in the industrial operation of anaerobic digesters. Complementarily, parameters such as chemical oxygen demand, total and volatile solids, and hydrogen sulfide have progressively increased their presence since 2015, mainly associated with effluent quality assessment, nutrient recovery, and overall process sustainability. In contrast, variables that integrate the state of the environment, such as electrical conductivity, oxidation-reduction potential, and the rheological properties of digestate, appear in less than $5\%$ of the studies analyzed, despite their ability to integrate information on stability, buffer capacity, and overall operating conditions. Taken together, these findings highlight an imbalance between the intensive use of traditional parameters and the limited incorporation of integrative indicators in industrial monitoring, suggesting that their systematic inclusion, together with the development of soft sensors and predictive models, could contribute to improving operational control and reducing the gap between the theoretical performance and actual behavior of industrial biodigesters. Full article

Light-based diagnostic and therapeutic approaches are increasingly important in modern biomedicine, with organic dyes emerging as versatile optical agents due to their tunable photophysical properties. Precise control over absorption and emission characteristics has enabled their application in fluorescence, photoacoustic, and Raman imaging, as well as in photodynamic and photothermal therapies. However, challenges related to biocompatibility, aqueous stability, and in vivo performance remain critical for clinical translation. Organic dyes that absorb in the near-infrared region are particularly attractive because of their deeper tissue penetration and reduced background interference. This review highlights key structure property relationships of organic dyes and summarizes current design strategies, including chromophore modification, peripheral functionalization for water solubility, and self-assembled nanotheranostic systems. Recent biomedical applications in cancer diagnosis and therapy, bacterial detection, and imaging-guided treatment are discussed, along with future directions for advancing dye-based technologies in healthcare. Full article